Computational and Mathematical Methods in Medicine The latest articles from Hindawi Publishing Corporation © 2016 , Hindawi Publishing Corporation . All rights reserved. A Dynamic Model of Human and Livestock Tuberculosis Spread and Control in Urumqi, Xinjiang, China Mon, 25 Jul 2016 07:56:55 +0000 We establish a dynamical model for tuberculosis of humans and cows. For the model, we firstly give the basic reproduction number . Furthermore, we discuss the dynamical behaviors of the model. By epidemiological investigation of tuberculosis among humans and livestock from 2007 to 2014 in Urumqi, Xinjiang, China, we estimate the parameters of the model and study the transmission trend of the disease in Urumqi, Xinjiang, China. The reproduction number in Urumqi for the model is estimated to be 0.1811 (95% confidence interval: 0.123–0.281). Finally, we perform some sensitivity analysis of several model parameters and give some useful comments on controlling the transmission of tuberculosis. Shan Liu, Aiqiao Li, Xiaomei Feng, Xueliang Zhang, and Kai Wang Copyright © 2016 Shan Liu et al. All rights reserved. Generalized Information Equilibrium Approaches to EEG Sleep Stage Discrimination Tue, 19 Jul 2016 08:44:45 +0000 Recent advances in neuroscience have raised the hypothesis that the underlying pattern of neuronal activation which results in electroencephalography (EEG) signals is via power-law distributed neuronal avalanches, while EEG signals are nonstationary. Therefore, spectral analysis of EEG may miss many properties inherent in such signals. A complete understanding of such dynamical systems requires knowledge of the underlying nonequilibrium thermodynamics. In recent work by Fielitz and Borchardt (2011, 2014), the concept of information equilibrium (IE) in information transfer processes has successfully characterized many different systems far from thermodynamic equilibrium. We utilized a publicly available database of polysomnogram EEG data from fourteen subjects with eight different one-minute tracings of sleep stage 2 and waking and an overlapping set of eleven subjects with eight different one-minute tracings of sleep stage 3. We applied principles of IE to model EEG as a system that transfers (equilibrates) information from the time domain to scalp-recorded voltages. We find that waking consciousness is readily distinguished from sleep stages 2 and 3 by several differences in mean information transfer constants. Principles of IE applied to EEG may therefore prove to be useful in the study of changes in brain function more generally. Todd Zorick and Jason Smith Copyright © 2016 Todd Zorick and Jason Smith. All rights reserved. Round Randomized Learning Vector Quantization for Brain Tumor Imaging Mon, 18 Jul 2016 08:45:36 +0000 Brain magnetic resonance imaging (MRI) classification into normal and abnormal is a critical and challenging task. Owing to that, several medical imaging classification techniques have been devised in which Learning Vector Quantization (LVQ) is amongst the potential. The main goal of this paper is to enhance the performance of LVQ technique in order to gain higher accuracy detection for brain tumor in MRIs. The classical way of selecting the winner code vector in LVQ is to measure the distance between the input vector and the codebook vectors using Euclidean distance function. In order to improve the winner selection technique, round off function is employed along with the Euclidean distance function. Moreover, in competitive learning classifiers, the fitting model is highly dependent on the class distribution. Therefore this paper proposed a multiresampling technique for which better class distribution can be achieved. This multiresampling is executed by using random selection via preclassification. The test data sample used are the brain tumor magnetic resonance images collected from Universiti Kebangsaan Malaysia Medical Center and UCI benchmark data sets. Comparative studies showed that the proposed methods with promising results are LVQ1, Multipass LVQ, Hierarchical LVQ, Multilayer Perceptron, and Radial Basis Function. Siti Norul Huda Sheikh Abdullah, Farah Aqilah Bohani, Baher H. Nayef, Shahnorbanun Sahran, Omar Al Akash, Rizuana Iqbal Hussain, and Fuad Ismail Copyright © 2016 Siti Norul Huda Sheikh Abdullah et al. All rights reserved. Machine Learning Approach to Automated Quality Identification of Human Induced Pluripotent Stem Cell Colony Images Thu, 14 Jul 2016 10:34:52 +0000 The focus of this research is on automated identification of the quality of human induced pluripotent stem cell (iPSC) colony images. iPS cell technology is a contemporary method by which the patient’s cells are reprogrammed back to stem cells and are differentiated to any cell type wanted. iPS cell technology will be used in future to patient specific drug screening, disease modeling, and tissue repairing, for instance. However, there are technical challenges before iPS cell technology can be used in practice and one of them is quality control of growing iPSC colonies which is currently done manually but is unfeasible solution in large-scale cultures. The monitoring problem returns to image analysis and classification problem. In this paper, we tackle this problem using machine learning methods such as multiclass Support Vector Machines and several baseline methods together with Scaled Invariant Feature Transformation based features. We perform over 80 test arrangements and do a thorough parameter value search. The best accuracy (62.4%) for classification was obtained by using a -NN classifier showing improved accuracy compared to earlier studies. Henry Joutsijoki, Markus Haponen, Jyrki Rasku, Katriina Aalto-Setälä, and Martti Juhola Copyright © 2016 Henry Joutsijoki et al. All rights reserved. Soft Computing in Medical Image Processing Tue, 12 Jul 2016 08:07:52 +0000 Syoji Kobashi, László G. Nyúl, and Jayaram K. Udupa Copyright © 2016 Syoji Kobashi et al. All rights reserved. Alternative Confidence Interval Methods Used in the Diagnostic Accuracy Studies Mon, 11 Jul 2016 06:05:47 +0000 Background/Aim. It is necessary to decide whether the newly improved methods are better than the standard or reference test or not. To decide whether the new diagnostics test is better than the gold standard test/imperfect standard test, the differences of estimated sensitivity/specificity are calculated with the help of information obtained from samples. However, to generalize this value to the population, it should be given with the confidence intervals. The aim of this study is to evaluate the confidence interval methods developed for the differences between the two dependent sensitivity/specificity values on a clinical application. Materials and Methods. In this study, confidence interval methods like Asymptotic Intervals, Conditional Intervals, Unconditional Interval, Score Intervals, and Nonparametric Methods Based on Relative Effects Intervals are used. Besides, as clinical application, data used in diagnostics study by Dickel et al. (2010) has been taken as a sample. Results. The results belonging to the alternative confidence interval methods for Nickel Sulfate, Potassium Dichromate, and Lanolin Alcohol are given as a table. Conclusion. While preferring the confidence interval methods, the researchers have to consider whether the case to be compared is single ratio or dependent binary ratio differences, the correlation coefficient between the rates in two dependent ratios and the sample sizes. Semra Erdoğan and Orekıcı Temel Gülhan Copyright © 2016 Semra Erdoğan and Orekıcı Temel Gülhan. All rights reserved. Biological Computation Indexes of Brain Oscillations in Unattended Facial Expression Processing Based on Event-Related Synchronization/Desynchronization Mon, 04 Jul 2016 11:15:51 +0000 Estimation of human emotions from Electroencephalogram (EEG) signals plays a vital role in affective Brain Computer Interface (BCI). The present study investigated the different event-related synchronization (ERS) and event-related desynchronization (ERD) of typical brain oscillations in processing Facial Expressions under nonattentional condition. The results show that the lower-frequency bands are mainly used to update Facial Expressions and distinguish the deviant stimuli from the standard ones, whereas the higher-frequency bands are relevant to automatically processing different Facial Expressions. Accordingly, we set up the relations between each brain oscillation and processing unattended Facial Expressions by the measures of ERD and ERS. This research first reveals the contributions of each frequency band for comprehension of Facial Expressions in preattentive stage. It also evidences that participants have emotional experience under nonattentional condition. Therefore, the user’s emotional state under nonattentional condition can be recognized in real time by the ERD/ERS computation indexes of different frequency bands of brain oscillations, which can be used in affective BCI to provide the user with more natural and friendly ways. Bo Yu, Lin Ma, Haifeng Li, Lun Zhao, Hongjian Bo, and Xunda Wang Copyright © 2016 Bo Yu et al. All rights reserved. A Canonical Correlation Analysis of AIDS Restriction Genes and Metabolic Pathways Identifies Purine Metabolism as a Key Cooperator Mon, 04 Jul 2016 07:40:40 +0000 Human immunodeficiency virus causes a severe disease in humans, referred to as immune deficiency syndrome. Studies on the interaction between host genetic factors and the virus have revealed dozens of genes that impact diverse processes in the AIDS disease. To resolve more genetic factors related to AIDS, a canonical correlation analysis was used to determine the correlation between AIDS restriction and metabolic pathway gene expression. The results show that HIV-1 postentry cellular viral cofactors from AIDS restriction genes are coexpressed in human transcriptome microarray datasets. Further, the purine metabolism pathway comprises novel host factors that are coexpressed with AIDS restriction genes. Using a canonical correlation analysis for expression is a reliable approach to exploring the mechanism underlying AIDS. Hanhui Ye, Jinjin Yuan, Zhengwu Wang, Aiqiong Huang, Xiaolong Liu, Xiao Han, and Yahong Chen Copyright © 2016 Hanhui Ye et al. All rights reserved. Perfusion Angiography in Acute Ischemic Stroke Sun, 03 Jul 2016 10:52:02 +0000 Visualization and quantification of blood flow are essential for the diagnosis and treatment evaluation of cerebrovascular diseases. For rapid imaging of the cerebrovasculature, digital subtraction angiography (DSA) remains the gold standard as it offers high spatial resolution. This paper lays out a methodological framework, named perfusion angiography, for the quantitative analysis and visualization of blood flow parameters from DSA images. The parameters, including cerebral blood flow (CBF) and cerebral blood volume (CBV), mean transit time (MTT), time-to-peak (TTP), and , are computed using a bolus tracking method based on the deconvolution of the time-density curve on a pixel-by-pixel basis. The method is tested on 66 acute ischemic stroke patients treated with thrombectomy and/or tissue plasminogen activator (tPA) and also evaluated on an estimation task with known ground truth. This novel imaging tool provides unique insights into flow mechanisms that cannot be observed directly in DSA sequences and might be used to evaluate the impact of endovascular interventions more precisely. Fabien Scalzo and David S. Liebeskind Copyright © 2016 Fabien Scalzo and David S. Liebeskind. All rights reserved. A Run-Length Encoding Approach for Path Analysis of C. elegans Search Behavior Thu, 30 Jun 2016 12:02:40 +0000 The nematode Caenorhabditis elegans explores the environment using a combination of different movement patterns, which include straight movement, reversal, and turns. We propose to quantify C. elegans movement behavior using a computer vision approach based on run-length encoding of step-length data. In this approach, the path of C. elegans is encoded as a string of characters, where each character represents a path segment of a specific type of movement. With these encoded string data, we perform -means cluster analysis to distinguish movement behaviors resulting from different genotypes and food availability. We found that shallow and sharp turns are the most critical factors in distinguishing the differences among the movement behaviors. To validate our approach, we examined the movement behavior of tph-1 mutants that lack an enzyme responsible for serotonin biosynthesis. A -means cluster analysis with the path string-encoded data showed that tph-1 movement behavior on food is similar to that of wild-type animals off food. We suggest that this run-length encoding approach is applicable to trajectory data in animal or human mobility data. Li Huang, Hongkyun Kim, Jacob Furst, and Daniela Raicu Copyright © 2016 Li Huang et al. All rights reserved. MD Study of Solution Concentrations on Ion Distribution in a Nanopore-Based Device Inspired from Red Blood Cells Thu, 30 Jun 2016 11:46:50 +0000 A molecular dynamics model of a nanopore-based device, which is similar to the nanopores in a cell membrane, was used to determine the influence of solution concentration on radial ion distribution, screening effects, and the radial potential profile in the nanopore. Results from these simulations indicate that as the solution concentration increases, the density peaks for both the counterion and coion near the charged wall increase at different speeds as screening effects appeared. Consequently, the potential near the charged wall of the nanopore changed from negative to positive during the simulation. The detailed understanding of ion distribution in nanopores is important for controlling the ion permeability and improving the cell transfection and also the design and application of nanofluidic devices. Yanyan Ge, Jieyu Xian, Min Kang, Xiaolin Li, and Meifu Jin Copyright © 2016 Yanyan Ge et al. All rights reserved. Anesthetic Propofol-Induced Gene Expression Changes in Patients Undergoing Coronary Artery Bypass Graft Surgery Based on Dynamical Differential Coexpression Network Analysis Wed, 29 Jun 2016 15:03:59 +0000 We aimed to determine the influence of anesthetic propofol on gene expression in patients treated by coronary artery bypass graft (CABG) surgery based on differential coexpression network (DCN) and to further reveal the novel mechanisms of the cardioprotective effects of propofol. Firstly, we constructed the DCN for disease condition based on Pearson correlation coefficient (PCC) and weight value. Secondly, the inference of modules was applied to search modules from DCN with same members but varied connectivity. Furthermore, we measured the statistical significance of the modules for selecting differential modules (DMs). Finally, attract method was used for DMs analysis to select key modules. Based on the δ value, 11928 edges and 2956 nodes were chosen to construct DCNs. A total of 29 seed genes were selected. Moreover, by quantifying connectivity changes in shared gene modules across different conditions, 8 DMs with higher connectivity dynamics were identified. Then, we extracted key modules using attract method, there were 8 key modules, and the top 3 modules were module 1, 2, and 3. Furthermore, GCG, PPY, and PON1 were initial seed genes of these 3 key modules, respectively. Accordingly, GCG and PON1 might exert important roles in the cardioprotective effects of propofol during CABG. Da Yu, Li-Jun Huang, and Na-Mi Chen Copyright © 2016 Da Yu et al. All rights reserved. Three-Dimensional Visualization of Myocardial Ischemia Based on the Standard Twelve-Lead Electrocardiogram Tue, 28 Jun 2016 15:37:13 +0000 A novel method was proposed for transforming the ischemic information in the 12-lead electrocardiogram (ECG) into the pseudo-color pattern displayed on a 3D heart model based on the projection of a ST injury vector in this study. The projection of the ST injury vector at a point on the heart surface was used for identifying the presence of myocardial ischemia by the difference between the projection value and the detection threshold. Supposing that myocardial ischemia was uniform and continuous, the location and range of myocardial ischemia could be accurately calculated and visually displayed in a color-encoding way. The diagnoses of the same patient were highly consistent (kappa coefficient ) between the proposed method used by ordinary people lacking medical knowledge and the standard 12-lead ECG used by experienced cardiologists. In addition, the diagnostic accuracy of the proposed method was further confirmed by the coronary angiography. The results of this study provide a new way to promote the development of the 3D visualization of the standard 12-lead ECG, which has a great help for inexperienced doctors or ordinary family members in their diagnosis of patients with myocardial ischemia. Ying Ma, Yang Sheng, Tian Ruixia, and Chen Xun Copyright © 2016 Ying Ma et al. All rights reserved. The Dynamical Behaviors in a Stochastic SIS Epidemic Model with Nonlinear Incidence Thu, 23 Jun 2016 12:24:50 +0000 A stochastic SIS-type epidemic model with general nonlinear incidence and disease-induced mortality is investigated. It is proved that the dynamical behaviors of the model are determined by a certain threshold value . That is, when and together with an additional condition, the disease is extinct with probability one, and when , the disease is permanent in the mean in probability, and when there is not disease-related death, the disease oscillates stochastically about a positive number. Furthermore, when , the model admits positive recurrence and a unique stationary distribution. Particularly, the effects of the intensities of stochastic perturbation for the dynamical behaviors of the model are discussed in detail, and the dynamical behaviors for the stochastic SIS epidemic model with standard incidence are established. Finally, the numerical simulations are presented to illustrate the proposed open problems. Ramziya Rifhat, Qing Ge, and Zhidong Teng Copyright © 2016 Ramziya Rifhat et al. All rights reserved. Human Activity Recognition in AAL Environments Using Random Projections Mon, 20 Jun 2016 08:39:04 +0000 Automatic human activity recognition systems aim to capture the state of the user and its environment by exploiting heterogeneous sensors attached to the subject’s body and permit continuous monitoring of numerous physiological signals reflecting the state of human actions. Successful identification of human activities can be immensely useful in healthcare applications for Ambient Assisted Living (AAL), for automatic and intelligent activity monitoring systems developed for elderly and disabled people. In this paper, we propose the method for activity recognition and subject identification based on random projections from high-dimensional feature space to low-dimensional projection space, where the classes are separated using the Jaccard distance between probability density functions of projected data. Two HAR domain tasks are considered: activity identification and subject identification. The experimental results using the proposed method with Human Activity Dataset (HAD) data are presented. Robertas Damaševičius, Mindaugas Vasiljevas, Justas Šalkevičius, and Marcin Woźniak Copyright © 2016 Robertas Damaševičius et al. All rights reserved. A Multiphase Flow in the Antroduodenal Portion of the Gastrointestinal Tract: A Mathematical Model Sun, 19 Jun 2016 09:30:50 +0000 A group of authors has developed a multilevel mathematical model that focuses on functional disorders in a human body associated with various chemical, physical, social, and other factors. At this point, the researchers have come up with structure, basic definitions and concepts of a mathematical model at the “macrolevel” that allow describing processes in a human body as a whole. Currently we are working at the “mesolevel” of organs and systems. Due to complexity of the tasks, this paper deals with only one meso-fragment of a digestive system model. It describes some aspects related to modeling multiphase flow in the antroduodenal portion of the gastrointestinal tract. Biochemical reactions, dissolution of food particles, and motor, secretory, and absorbing functions of the tract are taken into consideration. The paper outlines some results concerning influence of secretory function disorders on food dissolution rate and tract contents acidity. The effect which food density has on inflow of food masses from a stomach to a bowel is analyzed. We assume that the future development of the model will include digestive enzymes and related reactions of lipolysis, proteolysis, and carbohydrates breakdown. P. V. Trusov, N. V. Zaitseva, and M. R. Kamaltdinov Copyright © 2016 P. V. Trusov et al. All rights reserved. Modeling the Mechanical Consequences of Age-Related Trabecular Bone Loss by XFEM Simulation Wed, 15 Jun 2016 15:35:56 +0000 The elderly are more likely to suffer from fracture because of age-related trabecular bone loss. Different bone loss locations and patterns have different effects on bone mechanical properties. Extended finite element method (XFEM) can simulate fracture process and was suited to investigate the effects of bone loss on trabecular bone. Age-related bone loss is indicated by trabecular thinning and loss and may occur at low-strain locations or other random sites. Accordingly, several ideal normal and aged trabecular bone models were created based on different bone loss locations and patterns; then, fracture processes from crack initiation to complete failure of these models were observed by XFEM; finally, the effects of different locations and patterns on trabecular bone were compared. Results indicated that bone loss occurring at low-strain locations was more detrimental to trabecular bone than that occurring at other random sites; meanwhile, the decrease in bone strength caused by trabecular loss was higher than that caused by trabecular thinning, and the effects of vertical trabecular loss on mechanical properties were more severe than horizontal trabecular loss. This study provided a numerical method to simulate trabecular bone fracture and distinguished different effects of the possible occurrence of bone loss locations and patterns on trabecular bone. Ruoxun Fan, He Gong, Xianbin Zhang, Jun Liu, Zhengbin Jia, and Dong Zhu Copyright © 2016 Ruoxun Fan et al. All rights reserved. Patient-Specific Computational Models of Coronary Arteries Using Monoplane X-Ray Angiograms Wed, 15 Jun 2016 13:19:00 +0000 Coronary artery disease (CAD) is the most common type of heart disease in western countries. Early detection and diagnosis of CAD is quintessential to preventing mortality and subsequent complications. We believe hemodynamic data derived from patient-specific computational models could facilitate more accurate prediction of the risk of atherosclerosis. We introduce a semiautomated method to build 3D patient-specific coronary vessel models from 2D monoplane angiogram images. The main contribution of the method is a robust segmentation approach using dynamic programming combined with iterative 3D reconstruction to build 3D mesh models of the coronary vessels. Results indicate the accuracy and robustness of the proposed pipeline. In conclusion, patient-specific modelling of coronary vessels is of vital importance for developing accurate computational flow models and studying the hemodynamic effects of the presence of plaques on the arterial walls, resulting in lumen stenoses, as well as variations in the angulations of the coronary arteries. Ali Zifan and Panos Liatsis Copyright © 2016 Ali Zifan and Panos Liatsis. All rights reserved. A Simulation Study to Assess the Effect of the Number of Response Categories on the Power of Ordinal Logistic Regression for Differential Item Functioning Analysis in Rating Scales Wed, 15 Jun 2016 12:12:57 +0000 Objective. The present study uses simulated data to find what the optimal number of response categories is to achieve adequate power in ordinal logistic regression (OLR) model for differential item functioning (DIF) analysis in psychometric research. Methods. A hypothetical ten-item quality of life scale with three, four, and five response categories was simulated. The power and type I error rates of OLR model for detecting uniform DIF were investigated under different combinations of ability distribution (), sample size, sample size ratio, and the magnitude of uniform DIF across reference and focal groups. Results. When was distributed identically in the reference and focal groups, increasing the number of response categories from 3 to 5 resulted in an increase of approximately 8% in power of OLR model for detecting uniform DIF. The power of OLR was less than 0.36 when ability distribution in the reference and focal groups was highly skewed to the left and right, respectively. Conclusions. The clearest conclusion from this research is that the minimum number of response categories for DIF analysis using OLR is five. However, the impact of the number of response categories in detecting DIF was lower than might be expected. Elahe Allahyari, Peyman Jafari, and Zahra Bagheri Copyright © 2016 Elahe Allahyari et al. All rights reserved. Toward Psychoinformatics: Computer Science Meets Psychology Tue, 14 Jun 2016 09:38:47 +0000 The present paper provides insight into an emerging research discipline called Psychoinformatics. In the context of Psychoinformatics, we emphasize the cooperation between the disciplines of psychology and computer science in handling large data sets derived from heavily used devices, such as smartphones or online social network sites, in order to shed light on a large number of psychological traits, including personality and mood. New challenges await psychologists in light of the resulting “Big Data” sets, because classic psychological methods will only in part be able to analyze this data derived from ubiquitous mobile devices, as well as other everyday technologies. As a consequence, psychologists must enrich their scientific methods through the inclusion of methods from informatics. The paper provides a brief review of one area of this research field, dealing mainly with social networks and smartphones. Moreover, we highlight how data derived from Psychoinformatics can be combined in a meaningful way with data from human neuroscience. We close the paper with some observations of areas for future research and problems that require consideration within this new discipline. Christian Montag, Éilish Duke, and Alexander Markowetz Copyright © 2016 Christian Montag et al. All rights reserved. Abnormal EEG Complexity and Functional Connectivity of Brain in Patients with Acute Thalamic Ischemic Stroke Tue, 14 Jun 2016 09:24:59 +0000 Ischemic thalamus stroke has become a serious cardiovascular and cerebral disease in recent years. To date the existing researches mostly concentrated on the power spectral density (PSD) in several frequency bands. In this paper, we investigated the nonlinear features of EEG and brain functional connectivity in patients with acute thalamic ischemic stroke and healthy subjects. Electroencephalography (EEG) in resting condition with eyes closed was recorded for 12 stroke patients and 11 healthy subjects as control group. Lempel-Ziv complexity (LZC), Sample Entropy (SampEn), and brain network using partial directed coherence (PDC) were calculated for feature extraction. Results showed that patients had increased mean LZC and SampEn than the controls, which implied the stroke group has higher EEG complexity. For the brain network, the stroke group displayed a trend of weaker cortical connectivity, which suggests a functional impairment of information transmission in cortical connections in stroke patients. These findings suggest that nonlinear analysis and brain network could provide essential information for better understanding the brain dysfunction in the stroke and assisting monitoring or prognostication of stroke evolution. Shuang Liu, Jie Guo, Jiayuan Meng, Zhijun Wang, Yang Yao, Jiajia Yang, Hongzhi Qi, and Dong Ming Copyright © 2016 Shuang Liu et al. All rights reserved. Circular Helix-Like Curve: An Effective Tool of Biological Sequence Analysis and Comparison Tue, 14 Jun 2016 09:10:54 +0000 This paper constructed a novel injection from a DNA sequence to a 3D graph, named circular helix-like curve (CHC). The presented graphical representation is available for visualizing characterizations of a single DNA sequence and identifying similarities and differences among several DNAs. A 12-dimensional vector extracted from CHC, as a numerical characterization of CHC, was applied to analyze phylogenetic relationships of 11 species, 74 ribosomal RNAs, 48 Hepatitis E viruses, and 18 eutherian mammals, respectively. Successful experiments illustrated that CHC is an effective tool of biological sequence analysis and comparison. Yushuang Li and Wenli Xiao Copyright © 2016 Yushuang Li and Wenli Xiao. All rights reserved. Automatic Identification of Interictal Epileptiform Discharges in Secondary Generalized Epilepsy Thu, 09 Jun 2016 06:39:46 +0000 Ictal epileptiform discharges (EDs) are characteristic signal patterns of scalp electroencephalogram (EEG) or intracranial EEG (iEEG) recorded from patients with epilepsy, which assist with the diagnosis and characterization of various types of epilepsy. The EEG signal, however, is often recorded from patients with epilepsy for a long period of time, and thus detection and identification of EDs have been a burden on medical doctors. This paper proposes a new method for automatic identification of two types of EDs, repeated sharp-waves (sharps), and runs of sharp-and-slow-waves (SSWs), which helps to pinpoint epileptogenic foci in secondary generalized epilepsy such as Lennox-Gastaut syndrome (LGS). In the experiments with iEEG data acquired from a patient with LGS, our proposed method detected EDs with an accuracy of 93.76% and classified three different signal patterns with a mean classification accuracy of 87.69%, which was significantly higher than that of a conventional wavelet-based method. Our study shows that it is possible to successfully detect and discriminate sharps and SSWs from background EEG activity using our proposed method. Won-Du Chang, Ho-Seung Cha, Chany Lee, Hoon-Chul Kang, and Chang-Hwan Im Copyright © 2016 Won-Du Chang et al. All rights reserved. Image Reconstruction Using Analysis Model Prior Thu, 09 Jun 2016 06:34:34 +0000 The analysis model has been previously exploited as an alternative to the classical sparse synthesis model for designing image reconstruction methods. Applying a suitable analysis operator on the image of interest yields a cosparse outcome which enables us to reconstruct the image from undersampled data. In this work, we introduce additional prior in the analysis context and theoretically study the uniqueness issues in terms of analysis operators in general position and the specific 2D finite difference operator. We establish bounds on the minimum measurement numbers which are lower than those in cases without using analysis model prior. Based on the idea of iterative cosupport detection (ICD), we develop a novel image reconstruction model and an effective algorithm, achieving significantly better reconstruction performance. Simulation results on synthetic and practical magnetic resonance (MR) images are also shown to illustrate our theoretical claims. Yu Han, Huiqian Du, Fan Lam, Wenbo Mei, and Liping Fang Copyright © 2016 Yu Han et al. All rights reserved. Towards Identify Selective Antibacterial Peptides Based on Abstracts Meaning Sun, 05 Jun 2016 06:52:12 +0000 We present an Identify Selective Antibacterial Peptides (ISAP) approach based on abstracts meaning. Laboratories and researchers have significantly increased the report of their discoveries related to antibacterial peptides in primary publications. It is important to find antibacterial peptides that have been reported in primary publications because they can produce antibiotics of different generations that attack and destroy the bacteria. Unfortunately, researchers used heterogeneous forms of natural language to describe their discoveries (sometimes without the sequence of the peptides). Thus, we propose that learning the words meaning instead of the antibacterial peptides sequence is possible to identify and predict antibacterial peptides reported in the PubMed engine. The ISAP approach consists of two stages: training and discovering. ISAP founds that the 35% of the abstracts sample had antibacterial peptides and we tested in the updated Antimicrobial Peptide Database 2 (APD2). ISAP predicted that 45% of the abstracts had antibacterial peptides. That is, ISAP found that 810 antibacterial peptides were not classified like that, so they are not reported in APD2. As a result, this new search tool would complement the APD2 with a set of peptides that are candidates to be antibacterial. Finally, 20% of the abstracts were not semantic related to APD2. Liliana I. Barbosa-Santillán, Juan J. Sánchez-Escobar, M. Angeles Calixto-Romo, and Luis F. Barbosa-Santillán Copyright © 2016 Liliana I. Barbosa-Santillán et al. All rights reserved. Classification of Motor Imagery EEG Signals with Support Vector Machines and Particle Swarm Optimization Mon, 30 May 2016 14:54:28 +0000 Support vector machines are powerful tools used to solve the small sample and nonlinear classification problems, but their ultimate classification performance depends heavily upon the selection of appropriate kernel and penalty parameters. In this study, we propose using a particle swarm optimization algorithm to optimize the selection of both the kernel and penalty parameters in order to improve the classification performance of support vector machines. The performance of the optimized classifier was evaluated with motor imagery EEG signals in terms of both classification and prediction. Results show that the optimized classifier can significantly improve the classification accuracy of motor imagery EEG signals. Yuliang Ma, Xiaohui Ding, Qingshan She, Zhizeng Luo, Thomas Potter, and Yingchun Zhang Copyright © 2016 Yuliang Ma et al. All rights reserved. The Mechanical Analysis of the Biofilm Streamer Nucleation and Geometry Characterization in Microfluidic Channels Mon, 30 May 2016 13:46:54 +0000 Bacteria can form biofilm streamers in microfluidic channels with various geometries. Experiments show that the streamer geometry, such as its shape or thickness, depends on the fluid velocity and the geometry and curvature of the microfluidic channel. In the paper, a mechanical analysis of the flow field is made in different channels, which shows that the secondary flow in the channel is the reason for streamer nucleation and that the shear stress distribution decides the streamer geometry including shape and thickness. Through a finite elements simulation, we obtain the secondary flow forming positions in both static and rotating channels: positions that are the location of nucleation of the streamer. Thick or wide biofilm streamers occur at the points of minimum shear stress in static channels. Furthermore, in rotating channels, spiral-like streamers form, due to the helical shape of the minimum shear stress distribution. The findings may allow the prevention of biofilm formation and also the removal of bacteria adhered onto certain surfaces in channels with small cross sections. The analysis also indicates how one can obtain desirable biofilm streamers by control of the channel geometry and the loading conditions. Xiaoling Wang, Mudong Hao, Xin Du, Guoqing Wang, and Jun-ichi Matsushita Copyright © 2016 Xiaoling Wang et al. All rights reserved. Eradication of Ebola Based on Dynamic Programming Wed, 25 May 2016 11:58:30 +0000 This paper mainly studies the eradication of the Ebola virus, proposing a scientific system, including three modules for the eradication of Ebola virus. Firstly, we build a basic model combined with nonlinear incidence rate and maximum treatment capacity. Secondly, we use the dynamic programming method and the Dijkstra Algorithm to set up M-S (storage) and several delivery locations in West Africa. Finally, we apply the previous results to calculate the total cost, production cost, storage cost, and shortage cost. Jia-Ming Zhu, Lu Wang, and Jia-Bao Liu Copyright © 2016 Jia-Ming Zhu et al. All rights reserved. Segmentation of White Blood Cell from Acute Lymphoblastic Leukemia Images Using Dual-Threshold Method Sun, 22 May 2016 10:07:49 +0000 We propose a dual-threshold method based on a strategic combination of RGB and HSV color space for white blood cell (WBC) segmentation. The proposed method consists of three main parts: preprocessing, threshold segmentation, and postprocessing. In the preprocessing part, we get two images for further processing: one contrast-stretched gray image and one H component image from transformed HSV color space. In the threshold segmentation part, a dual-threshold method is proposed for improving the conventional single-threshold approaches and a golden section search method is used for determining the optimal thresholds. For the postprocessing part, mathematical morphology and median filtering are utilized to denoise and remove incomplete WBCs. The proposed method was tested in segmenting the lymphoblasts on a public Acute Lymphoblastic Leukemia (ALL) image dataset. The results show that the performance of the proposed method is better than single-threshold approach independently performed in RGB and HSV color space and the overall single WBC segmentation accuracy reaches 97.85%, showing a good prospect in subsequent lymphoblast classification and ALL diagnosis. Yan Li, Rui Zhu, Lei Mi, Yihui Cao, and Di Yao Copyright © 2016 Yan Li et al. All rights reserved. Inverse Problem for Color Doppler Ultrasound-Assisted Intracardiac Blood Flow Imaging Sun, 22 May 2016 06:16:57 +0000 For the assessment of the left ventricle (LV), echocardiography has been widely used to visualize and quantify geometrical variations of LV. However, echocardiographic image itself is not sufficient to describe a swirling pattern which is a characteristic blood flow pattern inside LV without any treatment on the image. We propose a mathematical framework based on an inverse problem for three-dimensional (3D) LV blood flow reconstruction. The reconstruction model combines the incompressible Navier-Stokes equations with one-direction velocity component of the synthetic flow data (or color Doppler data) from the forward simulation (or measurement). Moreover, time-varying LV boundaries are extracted from the intensity data to determine boundary conditions of the reconstruction model. Forward simulations of intracardiac blood flow are performed using a fluid-structure interaction model in order to obtain synthetic flow data. The proposed model significantly reduces the local and global errors of the reconstructed flow fields. We demonstrate the feasibility and potential usefulness of the proposed reconstruction model in predicting dynamic swirling patterns inside the LV over a cardiac cycle. Jaeseong Jang, Chi Young Ahn, Jung-Il Choi, and Jin Keun Seo Copyright © 2016 Jaeseong Jang et al. All rights reserved.