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Alejandro Correa, Marc Barcelo, Antoni Morell, Jose Lopez Vicario
In the last decade, the interest in Indoor Location Based Services (ILBS) has increased stimulating the development of Indoor Positioning Systems (IPS). In particular, ILBS look for positioning systems that can be applied anywhere in the world for millions of users, that is, there is a need for developing IPS for mass market applications. Those systems must provide accurate position estimations with minimum infrastructure cost and easy scalability to different environments. This survey overviews the current state of the art of IPSs and classifies them in terms of the infrastructure and methodology employed...
August 22, 2017: Sensors
Farhana R Pinu, Silas G Villas-Boas
Microorganisms produce and secrete many primary and secondary metabolites to the surrounding environment during their growth. Therefore, extracellular metabolites provide important information about the changes in microbial metabolism due to different environmental cues. The determination of these metabolites is also comparatively easier than the extraction and analysis of intracellular metabolites as there is no need for cell rupture. Many analytical methods are already available and have been used for the analysis of extracellular metabolites from microorganisms over the last two decades...
August 22, 2017: Metabolites
Md Asafuddoula, Hemant Kumar Singh, Tapabrata Ray
Multiobjective optimization problems with more than three objectives are commonly referred to as many-objective optimization problems (MaOPs). Development of algorithms to solve MaOPs has garnered significant research attention in recent years. ``Decomposition'' is a commonly adopted approach toward this aim, wherein the problem is divided into a set of simpler subproblems guided by a set of reference vectors. The reference vectors are often predefined and distributed uniformly in the objective space. Use of such uniform distribution of reference vectors has shown commendable performance on problems with ''regular'' Pareto optimal front (POF), i...
August 18, 2017: IEEE Transactions on Cybernetics
Chien-Chih Liao, Chuan-Kang Ting
The Set k-Cover problem aims to partition a set of nodes for the maximal number of covers. This problem is crucial for extending the lifetime of wireless sensor networks (WSNs) under the constraint of covering all targets. More specifically, the Set k-Cover problem enables partitioning the set of sensors into several covers over all targets and activating the covers by turns to effectively extend the WSN lifetime. To resolve this problem, we propose a novel memetic algorithm (MA) based on integer-coded genetic algorithm and local search...
August 21, 2017: IEEE Transactions on Cybernetics
Mrinal Kanti Bhowmik, Usha Rani Gogoi, Gautam Majumdar, Debotosh Bhattacharjee, Dhritiman Datta, Anjan Kumar Ghosh
The advancement of research in a specific area of clinical diagnosis crucially depends on the availability and quality of the radiology and other test related databases accompanied by ground truth and additional necessary medical findings. The paper describes the creation of the Department of Biotechnology-Tripura University-Jadavpur University (DBT-TU-JU) breast thermogram database. The objective of creating the DBT-TU-JU database is to provide a breast thermogram database that is annotated with the ground truth images of the suspicious regions...
August 17, 2017: IEEE Journal of Biomedical and Health Informatics
Sunil Kumar Yadav, Ulrich Reitebuch, Konrad Polthier
This paper presents a two-stage mesh denoising algorithm. Unlike other traditional averaging approaches, our approach uses an element-based normal voting tensor to compute smooth surfaces. By introducing a binary optimization on the proposed tensor together with a local binary neighborhood concept, our algorithm better retains sharp features and produces smoother umbilical regions than previous approaches. On top of that, we provide a stochastic analysis on the different kinds of noise based on the average edge length...
August 17, 2017: IEEE Transactions on Visualization and Computer Graphics
Sungsoo Ha, Klaus Mueller
Iterative algorithms have become increasingly popular in Computed Tomography (CT) image reconstruction since they better deal with the adverse image artifacts arising from low radiation dose image acquisition. But iterative methods remain computationally expensive. The main cost emerges in the projection and backprojection operations where accurate CT system modeling can greatly improve the quality of the reconstructed image. We present a framework that improves upon one particular aspect - the accurate projection of the image basis functions...
August 18, 2017: IEEE Transactions on Medical Imaging
Marcelino Bermúdez-López, David Arroyo, Àngels Betriu, Luis Masana, Elvira Fernández, Jose M Valdivielso
chronic kidney disease (CKD) is a world-wide health concern associated with a significantly higher cardiovascular morbidity and mortality. One of the principal cardiovascular risk factors is the lipid profile. CKD patients have a more frequent and progressive atheromatous disease that cannot be explained by the classical lipid parameters used in the daily clinical practice. Areas covered: the current review summarizes prevailing knowledge on the role of lipids in atheromathosis in CKD patients, including an overview of lipoprotein metabolism highlighting the CKD-induced alterations...
August 22, 2017: Expert Opinion on Therapeutic Targets
Florent Olivon, Pierre-Marie Allard, Alexey Koval, Davide Righi, Gregory Genta-Jouve, Johan Neyts, Cécile Apel, Christophe Pannecouque, Louis-Félix Nothias, Xavier Cachet, Laurence Marcourt, Fanny Roussi, Vladimir L Katanaev, David Touboul, Jean-Luc Wolfender, Marc Litaudon
Natural products represent an inexhaustible source of novel therapeutic agents. Their complex and constrained three-dimensional structures endow these molecules with exceptional biological properties, thereby giving them a major role in drug discovery programs. However, the search for new bioactive metabolites is hampered by the chemical complexity of the biological matrices in which they are found. The purification of single constituents from such matrices requires such a significant amount of work that should ideally be performed only on molecules of high potential value (i...
August 22, 2017: ACS Chemical Biology
Natalia Z Bielczyk, Alberto Llera, Jan K Buitelaar, Jeffrey C Glennon, Christian F Beckmann
PURPOSE: Multiple computational studies have demonstrated that essentially all current analytical approaches to determine effective connectivity perform poorly when applied to synthetic functional Magnetic Resonance Imaging (fMRI) datasets. In this study, we take a theoretical approach to investigate the potential factors facilitating and hindering effective connectivity research in fMRI. MATERIALS AND METHODS: In this work, we perform a simulation study with use of Dynamic Causal Modeling generative model in order to gain new insights on the influence of factors such as the slow hemodynamic response, mixed signals in the network and short time series, on the effective connectivity estimation in fMRI studies...
August 2017: Brain and Behavior
Bruno Korbar, Andrea M Olofson, Allen P Miraflor, Catherine M Nicka, Matthew A Suriawinata, Lorenzo Torresani, Arief A Suriawinata, Saeed Hassanpour
CONTEXT: Histopathological characterization of colorectal polyps is critical for determining the risk of colorectal cancer and future rates of surveillance for patients. However, this characterization is a challenging task and suffers from significant inter- and intra-observer variability. AIMS: We built an automatic image analysis method that can accurately classify different types of colorectal polyps on whole-slide images to help pathologists with this characterization and diagnosis...
2017: Journal of Pathology Informatics
Tabea Treppmann, Katja Ickstadt, Manuela Zucknick
Bayesian variable selection becomes more and more important in statistical analyses, in particular when performing variable selection in high dimensions. For survival time models and in the presence of genomic data, the state of the art is still quite unexploited. One of the more recent approaches suggests a Bayesian semiparametric proportional hazards model for right censored time-to-event data. We extend this model to directly include variable selection, based on a stochastic search procedure within a Markov chain Monte Carlo sampler for inference...
2017: Computational and Mathematical Methods in Medicine
Remo Monti, Iros Barozzi, Marco Osterwalder, Elizabeth Lee, Momoe Kato, Tyler H Garvin, Ingrid Plajzer-Frick, Catherine S Pickle, Jennifer A Akiyama, Veena Afzal, Niko Beerenwinkel, Diane E Dickel, Axel Visel, Len A Pennacchio
Epigenomic mapping of enhancer-associated chromatin modifications facilitates the genome-wide discovery of tissue-specific enhancers in vivo. However, reliance on single chromatin marks leads to high rates of false-positive predictions. More sophisticated, integrative methods have been described, but commonly suffer from limited accessibility to the resulting predictions and reduced biological interpretability. Here we present the Limb Enhancer Genie (LEG), a collection of highly accurate, genome-wide predictions of enhancers in the developing limb, available through a user-friendly online interface...
August 21, 2017: PLoS Computational Biology
Jagadeesh Suriyaprakash, Y B Xu, Y L Zhu, L X Yang, Y L Tang, Y J Wang, S Li, X L Ma
Engineering of novel functional nanocomposite as like as the metallic nanocrystals supported non-stoichiometric perovskite nanomaterial in controlled parameters (size, shape and ratio of chemical characteristics) is a challengeable task. In this context, we present a facile route to fabricate and study its physicochemical property at real time mode in this report. Nanoscale pure Pb crystals surfaced on non-stoichiometric A-site deficient Pb1-xTiO3-y nanoparticle were fabricated when a precursor lead titanate (PbTiO3) nanoparticle was exposed to an electron beam irradiation (EBI) in a transmission electron microscope (TEM) at ambient temperature...
August 21, 2017: Scientific Reports
Thavasyappan Thambi, Yi Li, Doo Sung Lee
Hydrogels are natural or synthetic polymer networks that exhibit high water absorbent capacities and have been used as scaffolds for tissue engineering or as delivery carriers for therapeutic agents and cells. Owing to their tunable physicochemical properties, hydrogels can provide spatial and temporal control over the release of loaded therapeutic agents, including chemotherapeutic drugs, proteins or cells. In particular, in situ-forming injectable hydrogels, the state-of-the-art clear free flowing polymer solutions that transform to viscoelastic gels upon exposure to stimuli including pH, temperature, light, enzymes and magnetic field, have been widely studied as delivery carriers for therapeutic agents...
August 4, 2017: Journal of Controlled Release: Official Journal of the Controlled Release Society
Waqaar Khawar, Nathan Smith, Saqib Masroor
BACKGROUND: Patients with atrial fibrillation are at increased risk for thromboembolic stroke originating predominantly in the left atrial appendage. To reduce the risk, the standard of care is anticoagulation. In addition, several devices for exclusion of the left atrial appendage have been developed. METHODS: PubMed was searched for articles relevant to left atrial appendage management. The resulting articles were reviewed as were relevant articles in their bibliographies...
August 19, 2017: Annals of Thoracic Surgery
Isaac M Jackson, Peter J H Scott, Stephen Thompson
Radiolabeled peptides are a valuable class of radiotracer that occupies the space between small molecules and large biologics, and are able to exploit the advantages of both classes of compound. To date, radiolabeled peptides have mainly been utilized in oncology, where the same peptide can often be exploited for diagnostic imaging and targeted radiotherapy by simply varying the radionuclide. In this review, we introduce the main strategies used for synthesis of radiolabeled peptides, and highlight the state of the art for clinical imaging (and therapy) in oncology using the main classes of radiolabeled peptides that have been translated to date...
September 2017: Seminars in Nuclear Medicine
Adam D DeVore, Priyesh A Patel, Chetan B Patel
More than 2,400 continuous-flow left ventricular assist devices (LVADs) are implanted each year in the United States alone. Both the number of patients living with LVADs and the life expectancy of these patients are increasing. As a result, patients with LVADs are increasingly encountered by non-LVAD specialists who do not have training in managing advanced heart failure for general medical care, cardiovascular procedures, and other subspecialty care. An understanding of the initial evaluation and management of patients with LVADs is now an essential skill for many health care providers...
August 3, 2017: JACC. Heart Failure
Marcus Nyström, Richard Andersson, Diederick C Niehorster, Ignace Hooge
Despite early reports and the contemporary consensus on microsaccades as purely binocular phenomena, recent work has proposed not only the existence of monocular microsaccades, but also that they serve functional purposes. We take a critical look at the detection of monocular microsaccades from a signal perspective, using raw data and a state-of-the-art, video-based eye tracker. In agreement with previous work, monocular detections were present in all participants using a standard microsaccade detection algorithm...
August 16, 2017: Vision Research
Zhao Zhang, Lei Jia, Min Zhang, Bing Li, Li Zhang, Fanzhang Li
In this paper, we mainly propose a novel adaptive transductive label propagation approach by joint discriminative clustering on manifolds for representing and classifying high-dimensional data. Our framework seamlessly combines the unsupervised manifold learning, discriminative clustering and adaptive classification into a unified model. Also, our method incorporates the adaptive graph weight construction with label propagation. Specifically, our method is capable of propagating label information using adaptive weights over low-dimensional manifold features, which is different from most existing studies that usually predict the labels and construct the weights in the original Euclidean space...
August 1, 2017: Neural Networks: the Official Journal of the International Neural Network Society
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