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Showing papers by "The Chinese University of Hong Kong published in 2013"


Journal ArticleDOI
TL;DR: The guided filter is a novel explicit image filter derived from a local linear model that can be used as an edge-preserving smoothing operator like the popular bilateral filter, but it has better behaviors near edges.
Abstract: In this paper, we propose a novel explicit image filter called guided filter. Derived from a local linear model, the guided filter computes the filtering output by considering the content of a guidance image, which can be the input image itself or another different image. The guided filter can be used as an edge-preserving smoothing operator like the popular bilateral filter [1], but it has better behaviors near edges. The guided filter is also a more generic concept beyond smoothing: It can transfer the structures of the guidance image to the filtering output, enabling new filtering applications like dehazing and guided feathering. Moreover, the guided filter naturally has a fast and nonapproximate linear time algorithm, regardless of the kernel size and the intensity range. Currently, it is one of the fastest edge-preserving filters. Experiments show that the guided filter is both effective and efficient in a great variety of computer vision and computer graphics applications, including edge-aware smoothing, detail enhancement, HDR compression, image matting/feathering, dehazing, joint upsampling, etc.

4,730 citations


Journal ArticleDOI
TL;DR: This Position Paper summarises the main outcomes of this international effort to provide the STandards for ReportIng Vascular changes on nEuroimaging (STRIVE).
Abstract: Cerebral small vessel disease (SVD) is a common accompaniment of ageing. Features seen on neuroimaging include recent small subcortical infarcts, lacunes, white matter hyperintensities, perivascular spaces, microbleeds, and brain atrophy. SVD can present as a stroke or cognitive decline, or can have few or no symptoms. SVD frequently coexists with neurodegenerative disease, and can exacerbate cognitive deficits, physical disabilities, and other symptoms of neurodegeneration. Terminology and definitions for imaging the features of SVD vary widely, which is also true for protocols for image acquisition and image analysis. This lack of consistency hampers progress in identifying the contribution of SVD to the pathophysiology and clinical features of common neurodegenerative diseases. We are an international working group from the Centres of Excellence in Neurodegeneration. We completed a structured process to develop definitions and imaging standards for markers and consequences of SVD. We aimed to achieve the following: first, to provide a common advisory about terms and definitions for features visible on MRI; second, to suggest minimum standards for image acquisition and analysis; third, to agree on standards for scientific reporting of changes related to SVD on neuroimaging; and fourth, to review emerging imaging methods for detection and quantification of preclinical manifestations of SVD. Our findings and recommendations apply to research studies, and can be used in the clinical setting to standardise image interpretation, acquisition, and reporting. This Position Paper summarises the main outcomes of this international effort to provide the STandards for ReportIng Vascular changes on nEuroimaging (STRIVE).

3,691 citations


Journal ArticleDOI
TL;DR: Crizotinib is superior to standard chemotherapy in patients with previously treated, advanced non-small-cell lung cancer with ALK rearrangement and greater improvement in global quality of life with crizotinIB than with chemotherapy.
Abstract: BACKGROUND: In single-group studies, chromosomal rearrangements of the anaplastic lymphoma kinase gene (ALK ) have been associated with marked clinical responses to crizotinib, an oral tyrosine kinase inhibitor targeting ALK. Whether crizotinib is superior to standard chemotherapy with respect to efficacy is unknown. METHODS: We conducted a phase 3, open-label trial comparing crizotinib with chemotherapy in 347 patients with locally advanced or metastatic ALK-positive lung cancer who had received one prior platinum-based regimen. Patients were randomly assigned to receive oral treatment with crizotinib (250 mg) twice daily or intravenous chemotherapy with either pemetrexed (500 mg per square meter of body-surface area) or docetaxel (75 mg per square meter) every 3 weeks. Patients in the chemotherapy group who had disease progression were permitted to cross over to crizotinib as part of a separate study. The primary end point was progression-free survival. RESULTS: The median progression-free survival was 7.7 months in the crizotinib group and 3.0 months in the chemotherapy group (hazard ratio for progression or death with crizotinib, 0.49; 95% confidence interval [CI], 0.37 to 0.64; P<0.001). The response rates were 65% (95% CI, 58 to 72) with crizotinib, as compared with 20% (95% CI, 14 to 26) with chemotherapy (P<0.001). An interim analysis of overall survival showed no significant improvement with crizotinib as compared with chemotherapy (hazard ratio for death in the crizotinib group, 1.02; 95% CI, 0.68 to 1.54; P=0.54). Common adverse events associated with crizotinib were visual disorder, gastrointestinal side effects, and elevated liver aminotransferase levels, whereas common adverse events with chemotherapy were fatigue, alopecia, and dyspnea. Patients reported greater reductions in symptoms of lung cancer and greater improvement in global quality of life with crizotinib than with chemotherapy. CONCLUSIONS: Crizotinib is superior to standard chemotherapy in patients with previously treated, advanced non-small-cell lung cancer with ALK rearrangement. (Funded by Pfizer; ClinicalTrials.gov number, NCT00932893.) Copyright © 2013 Massachusetts Medical Society.

3,074 citations


Journal ArticleDOI
TL;DR: The LUX-Lung 3 study as mentioned in this paper investigated the efficacy of chemotherapy compared with afatinib, a selective, orally bioavailable ErbB family blocker that irreversibly blocks signaling from epidermal growth factor receptor (EGFR/ErbB1), human epIDERmal growth factors receptor 2 (HER2/ERbB2), and ErbbB4 and has wide-spectrum preclinical activity against EGFR mutations.
Abstract: Purpose The LUX-Lung 3 study investigated the efficacy of chemotherapy compared with afatinib, a selective, orally bioavailable ErbB family blocker that irreversibly blocks signaling from epidermal growth factor receptor (EGFR/ErbB1), human epidermal growth factor receptor 2 (HER2/ErbB2), and ErbB4 and has wide-spectrum preclinical activity against EGFR mutations. A phase II study of afatinib in EGFR mutation–positive lung adenocarcinoma demonstrated high response rates and progression-free survival (PFS). Patients and Methods In this phase III study, eligible patients with stage IIIB/IV lung adenocarcinoma were screened for EGFR mutations. Mutation-positive patients were stratified by mutation type (exon 19 deletion, L858R, or other) and race (Asian or non-Asian) before two-to-one random assignment to 40 mg afatinib per day or up to six cycles of cisplatin plus pemetrexed chemotherapy at standard doses every 21 days. The primary end point was PFS by independent review. Secondary end points included tumor...

2,550 citations


20 Sep 2013
TL;DR: Afatinib is associated with prolongation of PFS when compared with standard doublet chemotherapy in patients with advanced lung adenocarcinoma and EGFR mutations.
Abstract: Purpose The LUX-Lung 3 study investigated the efficacy of chemotherapy compared with afatinib, a selective, orally bioavailable ErbB family blocker that irreversibly blocks signaling from epidermal growth factor receptor (EGFR/ErbB1), human epidermal growth factor receptor 2 (HER2/ErbB2), and ErbB4 and has wide-spectrum preclinical activity against EGFR mutations. A phase II study of afatinib in EGFR mutation-positive lung adenocarcinoma demonstrated high response rates and progression-free survival (PFS). Patients and Methods In this phase III study, eligible patients with stage IIIB/IV lung adenocarcinoma were screened for EGFR mutations. Mutation-positive patients were stratified by mutation type (exon 19 deletion, L858R, or other) and race (Asian or non-Asian) before two-to-one random assignment to 40 mg afatinib per day or up to six cycles of cisplatin plus pemetrexed chemotherapy at standard doses every 21 days. The primary end point was PFS by independent review. Secondary end points included tumor response, overall survival, adverse events, and patient-reported outcomes (PROs). Results A total of 1,269 patients were screened, and 345 were randomly assigned to treatment. Median PFS was 11.1 months for afatinib and 6.9 months for chemotherapy (hazard ratio [HR], 0.58; 95% CI, 0.43 to 0.78; P = .001). Median PFS among those with exon 19 deletions and L858R EGFR mutations (n = 308) was 13.6 months for afatinib and 6.9 months for chemotherapy (HR, 0.47; 95% CI, 0.34 to 0.65; P = .001). The most common treatmentrelated adverse events were diarrhea, rash/acne, and stomatitis for afatinib and nausea, fatigue, and decreased appetite for chemotherapy. PROs favored afatinib, with better control of cough, dyspnea, and pain. Conclusion Afatinib is associated with prolongation of PFS when compared with standard doublet chemotherapy in patients with advanced lung adenocarcinoma and EGFR mutations.

2,380 citations


Proceedings ArticleDOI
23 Jun 2013
TL;DR: This work tackles saliency detection from a scale point of view and proposes a multi-layer approach to analyze saliency cues, by finding saliency values optimally in a tree model.
Abstract: When dealing with objects with complex structures, saliency detection confronts a critical problem - namely that detection accuracy could be adversely affected if salient foreground or background in an image contains small-scale high-contrast patterns. This issue is common in natural images and forms a fundamental challenge for prior methods. We tackle it from a scale point of view and propose a multi-layer approach to analyze saliency cues. The final saliency map is produced in a hierarchical model. Different from varying patch sizes or downsizing images, our scale-based region handling is by finding saliency values optimally in a tree model. Our approach improves saliency detection on many images that cannot be handled well traditionally. A new dataset is also constructed.

1,624 citations


Journal ArticleDOI
TL;DR: This review presents a comprehensive overview of the flourishing field of Au nanorods in the past five years, focusing mainly on the approaches for the growth, shape and size tuning, functionalization, and assembly of Au Nanorods, as well as the methods for the preparation of their hybrid structures.
Abstract: Gold nanorods have been receiving extensive attention owing to their extremely attractive applications in biomedical technologies, plasmon-enhanced spectroscopies, and optical and optoelectronic devices. The growth methods and plasmonic properties of Au nanorods have therefore been intensively studied. In this review, we present a comprehensive overview of the flourishing field of Au nanorods in the past five years. We will focus mainly on the approaches for the growth, shape and size tuning, functionalization, and assembly of Au nanorods, as well as the methods for the preparation of their hybrid structures. The plasmonic properties and the associated applications of Au nanorods will also be discussed in detail.

1,494 citations


Proceedings ArticleDOI
23 Jun 2013
TL;DR: The proposed approach outperforms state-of-the-art methods in both detection accuracy and reliability and can avoid local minimum caused by ambiguity and data corruption in difficult image samples due to occlusions, large pose variations, and extreme lightings.
Abstract: We propose a new approach for estimation of the positions of facial key points with three-level carefully designed convolutional networks. At each level, the outputs of multiple networks are fused for robust and accurate estimation. Thanks to the deep structures of convolutional networks, global high-level features are extracted over the whole face region at the initialization stage, which help to locate high accuracy key points. There are two folds of advantage for this. First, the texture context information over the entire face is utilized to locate each key point. Second, since the networks are trained to predict all the key points simultaneously, the geometric constraints among key points are implicitly encoded. The method therefore can avoid local minimum caused by ambiguity and data corruption in difficult image samples due to occlusions, large pose variations, and extreme lightings. The networks at the following two levels are trained to locally refine initial predictions and their inputs are limited to small regions around the initial predictions. Several network structures critical for accurate and robust facial point detection are investigated. Extensive experiments show that our approach outperforms state-of-the-art methods in both detection accuracy and reliability.

1,462 citations


Proceedings ArticleDOI
23 Jun 2013
TL;DR: A novel perspective for person re-identification based on unsupervised salience learning, which applies adjacency constrained patch matching to build dense correspondence between image pairs, which shows effectiveness in handling misalignment caused by large viewpoint and pose variations.
Abstract: Human eyes can recognize person identities based on some small salient regions. However, such valuable salient information is often hidden when computing similarities of images with existing approaches. Moreover, many existing approaches learn discriminative features and handle drastic viewpoint change in a supervised way and require labeling new training data for a different pair of camera views. In this paper, we propose a novel perspective for person re-identification based on unsupervised salience learning. Distinctive features are extracted without requiring identity labels in the training procedure. First, we apply adjacency constrained patch matching to build dense correspondence between image pairs, which shows effectiveness in handling misalignment caused by large viewpoint and pose variations. Second, we learn human salience in an unsupervised manner. To improve the performance of person re-identification, human salience is incorporated in patch matching to find reliable and discriminative matched patches. The effectiveness of our approach is validated on the widely used VIPeR dataset and ETHZ dataset.

1,125 citations


Proceedings ArticleDOI
23 Jun 2013
TL;DR: This paper proposes a generalized and mathematically sound L0 sparse expression, together with a new effective method, for motion deblurring that does not require extra filtering during optimization and demonstrates fast energy decreasing, making a small number of iterations enough for convergence.
Abstract: We show in this paper that the success of previous maximum a posterior (MAP) based blur removal methods partly stems from their respective intermediate steps, which implicitly or explicitly create an unnatural representation containing salient image structures. We propose a generalized and mathematically sound L0 sparse expression, together with a new effective method, for motion deblurring. Our system does not require extra filtering during optimization and demonstrates fast energy decreasing, making a small number of iterations enough for convergence. It also provides a unified framework for both uniform and non-uniform motion deblurring. We extensively validate our method and show comparison with other approaches with respect to convergence speed, running time, and result quality.

1,010 citations


Proceedings ArticleDOI
01 Dec 2013
TL;DR: An efficient sparse combination learning framework based on inherent redundancy of video structures achieves decent performance in the detection phase without compromising result quality and reaches high detection rates on benchmark datasets at a speed of 140-150 frames per second on average.
Abstract: Speedy abnormal event detection meets the growing demand to process an enormous number of surveillance videos. Based on inherent redundancy of video structures, we propose an efficient sparse combination learning framework. It achieves decent performance in the detection phase without compromising result quality. The short running time is guaranteed because the new method effectively turns the original complicated problem to one in which only a few costless small-scale least square optimization steps are involved. Our method reaches high detection rates on benchmark datasets at a speed of 140-150 frames per second on average when computing on an ordinary desktop PC using MATLAB.

Journal ArticleDOI
TL;DR: This paper proposes a mechanism that combines data deduplication with dynamic data operations in the privacy preserving public auditing for secure cloud storage and shows that the proposed mechanism is highly efficient and provably secure.
Abstract: Using cloud storage, users can remotely store their data and enjoy the on-demand high-quality applications and services from a shared pool of configurable computing resources, without the burden of local data storage and maintenance. However, the fact that users no longer have physical possession of the outsourced data makes the data integrity protection in cloud computing a formidable task, especially for users with constrained computing resources. Moreover, users should be able to just use the cloud storage as if it is local, without worrying about the need to verify its integrity. Thus, enabling public auditability for cloud storage is of critical importance so that users can resort to a third-party auditor (TPA) to check the integrity of outsourced data and be worry free. To securely introduce an effective TPA, the auditing process should bring in no new vulnerabilities toward user data privacy, and introduce no additional online burden to user. In this paper, we propose a secure cloud storage system supporting privacy-preserving public auditing. We further extend our result to enable the TPA to perform audits for multiple users simultaneously and efficiently. Extensive security and performance analysis show the proposed schemes are provably secure and highly efficient. Our preliminary experiment conducted on Amazon EC2 instance further demonstrates the fast performance of the design.

Journal ArticleDOI
TL;DR: In this paper, a CMOS compatible graphene/silicon-heterostructure photodetector formed by integrating graphene onto a silicon optical waveguide on silicon-on-insulator and operating in the near and mid-infrared regions is demonstrated.
Abstract: A CMOS-compatible graphene/silicon-heterostructure photodetector formed by integrating graphene onto a silicon optical waveguide on silicon-on-insulator and operating in the near- and mid-infrared regions is demonstrated. A responsivity as high as 0.13 A W−1 is obtained at a bias of 1.5 V for 2.75-μm light at room temperature.

Journal ArticleDOI
TL;DR: This paper reviews the recent development of relevant technologies from the perspectives of computer vision and pattern recognition, and discusses how to face emerging challenges of intelligent multi-camera video surveillance.

Proceedings ArticleDOI
01 Dec 2013
TL;DR: This paper forms these four important components in pedestrian detection into a joint deep learning framework and proposes a new deep network architecture that achieves a 9% reduction in the average miss rate compared with the current best-performing pedestrian detection approaches on the largest Caltech benchmark dataset.
Abstract: Feature extraction, deformation handling, occlusion handling, and classification are four important components in pedestrian detection. Existing methods learn or design these components either individually or sequentially. The interaction among these components is not yet well explored. This paper proposes that they should be jointly learned in order to maximize their strengths through cooperation. We formulate these four components into a joint deep learning framework and propose a new deep network architecture. By establishing automatic, mutual interaction among components, the deep model achieves a 9% reduction in the average miss rate compared with the current best-performing pedestrian detection approaches on the largest Caltech benchmark dataset.

Journal ArticleDOI
04 Apr 2013-Nature
TL;DR: This draft genome sequence provides insight into the environmental adaptation of bread wheat and can aid in defining the large and complicated genomes of wheat species.
Abstract: About 8,000 years ago in the Fertile Crescent, a spontaneous hybridization of the wild diploid grass Aegilops tauschii (2n = 14; DD) with the cultivated tetraploid wheat Triticum turgidum (2n = 4x = 28; AABB) resulted in hexaploid wheat (T. aestivum; 2n = 6x = 42; AABBDD). Wheat has since become a primary staple crop worldwide as a result of its enhanced adaptability to a wide range of climates and improved grain quality for the production of baker's flour. Here we describe sequencing the Ae. tauschii genome and obtaining a roughly 90-fold depth of short reads from libraries with various insert sizes, to gain a better understanding of this genetically complex plant. The assembled scaffolds represented 83.4% of the genome, of which 65.9% comprised transposable elements. We generated comprehensive RNA-Seq data and used it to identify 43,150 protein-coding genes, of which 30,697 (71.1%) were uniquely anchored to chromosomes with an integrated high-density genetic map. Whole-genome analysis revealed gene family expansion in Ae. tauschii of agronomically relevant gene families that were associated with disease resistance, abiotic stress tolerance and grain quality. This draft genome sequence provides insight into the environmental adaptation of bread wheat and can aid in defining the large and complicated genomes of wheat species.

Journal ArticleDOI
04 Apr 2013-Nature
TL;DR: The T. urartu genome assembly provides a diploid reference for analysis of polyploid wheat genomes and is a valuable resource for the genetic improvement of wheat.
Abstract: The genome sequence and its analysis of the diploid wild wheat Triticum urartu (progenitor of the wheat A genome) represent a tool for studying the complex, polyploid wheat genomes and should be a valuable resource for the genetic improvement of wheat. The hexaploid genome of bread wheat Triticum aestivum, designated AABBDD, evolved as a result of hybridization between three ancestral grasses. Two papers published in the issue of Nature present genome sequences and analysis of two of these wheat progenitors. First, the genome sequence of the diploid wild wheat T. urartu (ancestor of the A genome), which resembles cultivated wheat more strongly than either Aegilops speltoides (the B ancestor) or Ae. tauschii (the D donor). And second, the Ae. tauschii genome, together with an analysis of its transcriptome. These genomes and their analyses will be powerful tools for the study of complex, polyploid wheat genomes and a valuable resource for genetic improvement of wheat. Bread wheat (Triticum aestivum, AABBDD) is one of the most widely cultivated and consumed food crops in the world. However, the complex polyploid nature of its genome makes genetic and functional analyses extremely challenging. The A genome, as a basic genome of bread wheat and other polyploid wheats, for example, T. turgidum (AABB), T. timopheevii (AAGG) and T. zhukovskyi (AAGGAmAm), is central to wheat evolution, domestication and genetic improvement1. The progenitor species of the A genome is the diploid wild einkorn wheat T. urartu2, which resembles cultivated wheat more extensively than do Aegilops speltoides (the ancestor of the B genome3) and Ae. tauschii (the donor of the D genome4), especially in the morphology and development of spike and seed. Here we present the generation, assembly and analysis of a whole-genome shotgun draft sequence of the T. urartu genome. We identified protein-coding gene models, performed genome structure analyses and assessed its utility for analysing agronomically important genes and for developing molecular markers. Our T. urartu genome assembly provides a diploid reference for analysis of polyploid wheat genomes and is a valuable resource for the genetic improvement of wheat.

Journal ArticleDOI
TL;DR: The evolution of lung cancer staging towards more non-invasive, endoscopy-based, and image-based methods, and the development of stage-adapted treatment is discussed, with an emphasis on targeted therapies based on the assumption that a treatable driver mutation or gene rearrangement is present within the tumour.

Journal ArticleDOI
TL;DR: This article reviews the various swimming methods with particular focus on helical propulsion inspired by E. coli bacteria, and the frequency-dependent behavior of helical microrobots is discussed and preliminary experimental results are presented showing the decoupling of an individual agent within a group of three microrOBots.
Abstract: Microrobots have been proposed for future biomedical applications in which they are able to navigate in viscous fluidic environments. Nature has inspired numerous microrobotic locomotion designs, which are suitable for propulsion generation at low Reynolds numbers. This article reviews the various swimming methods with particular focus on helical propulsion inspired by E. coli bacteria. There are various magnetic actuation methods for biomimetic and non-biomimetic microrobots, such as rotating fields, oscillating fields, or field gradients. They can be categorized into force-driven or torque-driven actuation methods. Both approaches are reviewed and a previous publication has shown that torque-driven actuation scales better to the micro- and nano-scale than force-driven actuation. Finally, the implementation of swarm or multi-agent control is discussed. The use of multiple microrobots may be beneficial for in vivo as well as in vitro applications. Thus, the frequency-dependent behavior of helical microrobots is discussed and preliminary experimental results are presented showing the decoupling of an individual agent within a group of three microrobots.

Journal ArticleDOI
TL;DR: This work describes an array of submicrometer gold mushrooms with a FOM reaching ~108, which is comparable to the theoretically predicted upper limit for standard PSPR sensors, and demonstrates the array as a biosensor for detecting cytochrome c and alpha-fetoprotein, suggesting that the array is a promising candidate for label-free biomedical sensing.
Abstract: Localized surface plasmon resonance (LSPR)-based sensing has found wide applications in medical diagnosis, food safety regulation and environmental monitoring. Compared with commercial propagating surface plasmon resonance (PSPR)-based sensors, LSPR ones are simple, cost-effective and suitable for measuring local refractive index changes. However, the figure of merit (FOM) values of LSPR sensors are generally 1-2 orders of magnitude smaller than those of PSPR ones, preventing the widespread use of LSPR sensors. Here we describe an array of submicrometer gold mushrooms with a FOM reaching ~108, which is comparable to the theoretically predicted upper limit for standard PSPR sensors. Such a high FOM arises from the interference between Wood's anomaly and the LSPRs. We further demonstrate the array as a biosensor for detecting cytochrome c and alpha-fetoprotein, with their detection limits down to 200 pM and 15 ng ml(-1), respectively, suggesting that the array is a promising candidate for label-free biomedical sensing.

Journal ArticleDOI
TL;DR: The Asia-Pacific Crohn's and Colitis Epidemiology Study as discussed by the authors was a large-scale population-based study and found that although the incidence of IBD varies throughout Asia, it is still lower than in the West.

Proceedings ArticleDOI
23 Jun 2013
TL;DR: A new approach for matching images observed in different camera views with complex cross-view transforms and apply it to person re-identification that jointly partitions the image spaces of two camera views into different configurations according to the similarity of cross- view transforms.
Abstract: In this paper, we propose a new approach for matching images observed in different camera views with complex cross-view transforms and apply it to person re-identification. It jointly partitions the image spaces of two camera views into different configurations according to the similarity of cross-view transforms. The visual features of an image pair from different views are first locally aligned by being projected to a common feature space and then matched with softly assigned metrics which are locally optimized. The features optimal for recognizing identities are different from those for clustering cross-view transforms. They are jointly learned by utilizing sparsity-inducing norm and information theoretical regularization. This approach can be generalized to the settings where test images are from new camera views, not the same as those in the training set. Extensive experiments are conducted on public datasets and our own dataset. Comparisons with the state-of-the-art metric learning and person re-identification methods show the superior performance of our approach.

Journal ArticleDOI
TL;DR: East Asian patients with type 2 diabetes have a higher risk of developing renal complications than Europeans and, with regard to cardiovascular complications, a predisposition for developing strokes and cancer is emerging as the other main cause of mortality.
Abstract: There is an epidemic of diabetes in Asia. Type 2 diabetes develops in East Asian patients at a lower mean body mass index (BMI) compared with those of European descent. At any given BMI, East Asians have a greater amount of body fat and a tendency to visceral adiposity. In Asian patients, diabetes develops at a younger age and is characterized by early β cell dysfunction in the setting of insulin resistance, with many requiring early insulin treatment. The increasing proportion of young-onset and childhood type 2 diabetes is posing a particular threat, with these patients being at increased risk of developing diabetic complications. East Asian patients with type 2 diabetes have a higher risk of developing renal complications than Europeans and, with regard to cardiovascular complications, a predisposition for developing strokes. In addition to cardiovascular–renal disease, cancer is emerging as the other main cause of mortality. While more research is needed to explain these interethnic differences, urgent and concerted actions are needed to raise awareness, facilitate early diagnosis, and encourage preventive strategies to combat these growing disease burdens.

Journal ArticleDOI
TL;DR: There is a need to provide standards for patient/participant selection criteria in research focused on CAI, with justifications using the best available evidence.
Abstract: While research on chronic ankle instability (CAI) and awareness of its impact on society and health care systems has grown substantially in the last 2 decades, the inconsistency in participant/patient selection criteria across studies presents a potential obstacle to addressing the problem properly. This major gap within the literature limits the ability to generalise this evidence to the target patient population. Therefore, there is a need to provide standards for patient/participant selection criteria in research focused on CAI with justifications using the best available evidence. The International Ankle Consortium provides this position paper to present and discuss an endorsed set of selection criteria for patients with CAI based on the best available evidence to be used in future research and study designs. These recommendations will enhance the validity of research conducted in this clinical population with the end goal of bringing the research evidence to the clinician and patient.

Journal ArticleDOI
TL;DR: This work reports here on the direct harvesting of visible-to-near-infrared light for chemical reactions by use of plasmonic Au-Pd nanostructures, and compares the effect of joint plasMonic photocatalysis and photothermal conversion with that of sole Photothermal conversion.
Abstract: The efficient use of solar energy has received wide interest due to increasing energy and environmental concerns. A potential means in chemistry is sunlight-driven catalytic reactions. We report here on the direct harvesting of visible-to-near-infrared light for chemical reactions by use of plasmonic Au–Pd nanostructures. The intimate integration of plasmonic Au nanorods with catalytic Pd nanoparticles through seeded growth enabled efficient light harvesting for catalytic reactions on the nanostructures. Upon plasmon excitation, catalytic reactions were induced and accelerated through both plasmonic photocatalysis and photothermal conversion. Under the illumination of an 809 nm laser at 1.68 W, the yield of the Suzuki coupling reaction was ∼2 times that obtained when the reaction was thermally heated to the same temperature. Moreover, the yield was also ∼2 times that obtained from Au–TiOx–Pd nanostructures under the same laser illumination, where a 25-nm-thick TiOx shell was introduced to prevent the phot...

Journal ArticleDOI
TL;DR: BIS-guided anesthesia reduced anesthetic exposure and decreased the risk of POCD at 3 months after surgery, and for every 1000 elderly patients undergoing major surgery, anesthetic delivery titrated to a range of BIS between 40 and 60 would prevent 23 patients from PocD and 83 patients from delirium.
Abstract: Background:Previous clinical trials and animal experiments have suggested that long-lasting neurotoxicity of general anesthetics may lead to postoperative cognitive dysfunction (POCD). Brain function monitoring such as the bispectral index (BIS) facilitates anesthetic titration and has been shown to

Proceedings Article
03 Aug 2013
TL;DR: This paper proposes a novel matrix factorization method, namely FPMC-LR, to embed the personalized Markov chains and the localized regions in the check-in sequence, and utilizes the information of localized regions to boost recommendation.
Abstract: Personalized point-of-interest (POI) recommendation is a significant task in location-based social networks (LBSNs) as it can help provide better user experience as well as enable third-party services, e.g., launching advertisements. To provide a good recommendation, various research has been conducted in the literature. However, pervious efforts mainly consider the "check-ins" in a whole and omit their temporal relation. They can only recommend POI globally and cannot know where a user would like to go tomorrow or in the next few days. In this paper, we consider the task of successive personalized POI recommendation in LBSNs, which is a much harder task than standard personalized POI recommendation or prediction. To solve this task, we observe two prominent properties in the check-in sequence: personalized Markov chain and region localization. Hence, we propose a novel matrix factorization method, namely FPMC-LR, to embed the personalized Markov chains and the localized regions. Our proposed FPMC-LR not only exploits the personalized Markov chain in the check-in sequence, but also takes into account users' movement constraint, i.e., moving around a localized region. More importantly, utilizing the information of localized regions, we not only reduce the computation cost largely, but also discard the noisy information to boost recommendation. Results on two real-world LBSNs datasets demonstrate the merits of our proposed FPMC-LR.

Proceedings ArticleDOI
01 Dec 2013
TL;DR: This paper exploits the pair wise salience distribution relationship between pedestrian images, and solves the person re-identification problem by proposing a salience matching strategy that outperforms the state-of-the-art methods on both datasets.
Abstract: Human salience is distinctive and reliable information in matching pedestrians across disjoint camera views. In this paper, we exploit the pair wise salience distribution relationship between pedestrian images, and solve the person re-identification problem by proposing a salience matching strategy. To handle the misalignment problem in pedestrian images, patch matching is adopted and patch salience is estimated. Matching patches with inconsistent salience brings penalty. Images of the same person are recognized by minimizing the salience matching cost. Furthermore, our salience matching is tightly integrated with patch matching in a unified structural Rank SVM learning framework. The effectiveness of our approach is validated on the VIPeR dataset and the CUHK Campus dataset. It outperforms the state-of-the-art methods on both datasets.

Journal ArticleDOI
TL;DR: This study explored the use of shotgun massively parallel sequencing of plasma DNA from cancer patients to scan a cancer genome noninvasively and showed that plasma DNA sequencing is a valuable approach for studying tumoral heterogeneity.
Abstract: BACKGROUND: Tumor-derived DNA can be found in the plasma of cancer patients. In this study, we explored the use of shotgun massively parallel sequencing (MPS) of plasma DNA from cancer patients to scan a cancer genome noninvasively. METHODS: Four hepatocellular carcinoma patients and a patient with synchronous breast and ovarian cancers were recruited. DNA was extracted from the tumor tissues, and the preoperative and postoperative plasma samples of these patients were analyzed with shotgun MPS. RESULTS: We achieved the genomewide profiling of copy number aberrations and point mutations in the plasma of the cancer patients. By detecting and quantifying the genomewide aggregated allelic loss and point mutations, we determined the fractional concentrations of tumor-derived DNA in plasma and correlated these values with tumor size and surgical treatment. We also demonstrated the potential utility of this approach for the analysis of complex oncologic scenarios by studying the patient with 2 synchronous cancers. Through the use of multiregional sequencing of tumoral tissues and shotgun sequencing of plasma DNA, we have shown that plasma DNA sequencing is a valuable approach for studying tumoral heterogeneity. CONCLUSIONS: Shotgun DNA sequencing of plasma is a potentially powerful tool for cancer detection, monitoring, and research.

Journal ArticleDOI
01 Apr 2013-Gut
TL;DR: The present review aims to provide an update of the literature exploring geographical variability in IBD and to explore the environmental risk factors that may account for this variability.
Abstract: The changing epidemiology of inflammatory bowel disease (IBD) across time and geography suggests that environmental factors play a major role in modifying disease expression. Disease emergence in developing nations suggests that epidemiological evolution is related to westernisation of lifestyle and industrialisation. The strongest environmental associations identified are cigarette smoking and appendectomy, although neither alone explains the variation in incidence of IBD worldwide. Urbanisation of societies, associated with changes in diet, antibiotic use, hygiene status, microbial exposures and pollution have been implicated as potential environmental risk factors for IBD. Changes in socioeconomic status might occur differently in different geographical areas and populations and, consequently, it is important to consider the heterogeneity of risk factors applicable to the individual patient. Environmental risk factors of individual, familial, community-based, country-based and regionally based origin may all contribute to the pathogenesis of IBD. The geographical variation of IBD provides clues for researchers to investigate possible environmental aetiological factors. The present review aims to provide an update of the literature exploring geographical variability in IBD and to explore the environmental risk factors that may account for this variability.