JECS Staff and Student Research

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The mission of the Erik Jonsson School of Engineering and Computer Science is to:

  • Deliver state-of-the-art high-technology engineering degree programs for Dallas and Collin Counties, the DFW Metroplex and the State of Texas.
  • Produce versatile students infused not only with technical skills, but also with innovative and entrepreneurial skills.
  • Address problems of critical societal need through research aimed at the creation of new engineering knowledge and technology transfer to industry.
  • Develop partnerships with government and the private sector to apply new knowledge for economic growth and high-tech job creation in order to strengthen existing regional firms, promote the growth of new regional firms and create new high-paying private sector jobs.
  • Provide leadership and outreach to nurture tomorrow's leaders in science, mathematics and high-technology education and business.


Recent Submissions

Now showing 1 - 20 of 172
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    PET-MRI Image Fusion Using Adaptive Filter Based on Spectral and Spatial Discrepancy
    (Springer London Ltd, 2018-07-21) Saboori, Arash; Birjandtalab, Javad; Birjandtalab, Javad
    Recently, medical imaging equipment has undergone major developments. They play an important role in healthcare industry since they provide visual interpretation of human organs. Magnetic resonance imaging (MRI) and positron emission tomography (PET) are two well-known technologies which capture the structural and functional characteristics of the body organs, respectively. Fusing such functional and structural information can help physicians to better understand the normal and abnormal behaviors of tissues and organs. The contribution of this paper is twofold. First, an adaptive filter-based image fusion method is proposed to integrate information of MRI and PET images. Second, the notion of spatial discrepancy is added to the conventional spectral discrepancy and both discrepancy criteria are used for optimizing the filter parameters. The proposed image fusion technique is tested on seven publicly available brain image datasets including two cases of Alzheimer's disease, normal coronal, normal sagittal, normal axial, grade II astrocytoma, and grade IV astrocytoma provided by Harvard University. The proposed method is compared with other biomedical image fusion approaches in both quantitative and visual manners. The results show that the proposed image fusion technique provides better performance in improving spectral and structural characteristics of the original images.
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    Robot Motion Planning in an Unknown Environment with Danger Space
    (MDPI, 2019-02-10) Jahanshahi, Hadi; Jafarzadeh, Mohsen; Sari, Naeimeh Najafizadeh; Viet-Thanh Pham; Van Van Huynh; Xuan Quynh Nguyen; 0000-0001-7719-7081 (Jafarzadeh, M); Jafarzadeh, Mohsen
    This paper discusses the real-time optimal path planning of autonomous humanoid robots in unknown environments regarding the absence and presence of the danger space. The danger is defined as an environment which is not an obstacle nor free space and robot are permitted to cross when no free space options are available. In other words, the danger can be defined as the potentially risky areas of the map. For example, mud pits in a wooded area and greasy floor in a factory can be considered as a danger. The synthetic potential field, linguistic method, and Markov decision processes are methods which have been reviewed for path planning in a free-danger unknown environment. The modified Markov decision processes based on the Takagi-Sugeno fuzzy inference system is implemented to reach the target in the presence and absence of the danger space. In the proposed method, the reward function has been calculated without the exact estimation of the distance and shape of the obstacles. Unlike other existing path planning algorithms, the proposed methods can work with noisy data. Additionally, the entire motion planning procedure is fully autonomous. This feature makes the robot able to work in a real situation. The discussed methods ensure the collision avoidance and convergence to the target in an optimal and safe path. An Aldebaran humanoid robot, NAO H25, has been selected to verify the presented methods. The proposed methods require only vision data which can be obtained by only one camera. The experimental results demonstrate the efficiency of the proposed methods.
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    Luminescent Silica-Based Nanostructures from in Vivo Iridium-Doped Diatoms Microalgae
    (Amer Chemical Soc, 2018-12-12) Della Rosa, Giulia; Vona, Danilo; Aloisi, Alessandra; Ragni, Roberta; Di Corato, Riccardo; Lo Presti, Marco; Cicco, Stefania R.; Altamura, Emiliano; Taurino, Antonietta; Catalano, Massimo; Farinola, Gianluca M.; Rinaldi, Rosaria; Catalano, Massimo
    A novel biotechnological approach to the preparation of Ir-doped luminescent silica-based nanostructures is proposed availing use of diatoms microalgae which generate highly nanostructured biosilica shells (frustules) by in vivo biomineralization of orthosilicic acid. After the in vivo incorporation of a phosphorescent organometallic complex (Ir-1) in Thalassiosira weissflogii diatom frustules (DFs), bulk functionalized phosphorescent silica-based nanostructures are obtained by isolation and proper ultrafine processing of Ir-1-doped DFs. High-resolution characterization reveals the presence of phosphorescent hybrid organic/inorganic clusters composed of biogenic silica NPs intimately trapped within the diatom organic residual matter. The biofactory strategy investigated herein can be a sustainable, cost-effective, and scalable route to transition metal-doped silica nanomaterials and can pave the way to a great variety of heavy-metal and rare-earth metal doped silica nanostructures, whose applications range from photonics to imaging, sensing, and biomedicine.
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    Fabrication of Micro-Patterned Surface for Pool-Boiling Enhancement by Using Powder Injection Molding Process
    (MDPI, 2019-02-07) Cho, Hanlyun; Godinez, Juan; Han, Jun Sae; Fadda, Dani; You, Seung Mun; Lee, Jungho; Park, Seong Jin; 0000-0002-1078-5310 (Godinez, J); Godinez, Juan; Fadda, Dani; You, Seung Mun
    In this study, two kinds of copper micro-patterned surfaces with different heights were fabricated by using a powder injection molding (PIM) process. The micro-pattern's size was 100 μm, and the gap size was 50 μm. The short micro-pattern's height was 100 μm, and the height of the tall one was 380 m. A copper powder and wax-polymer-based binder system was used to fabricate the micro-patterned surfaces. The critical heat flux (CHF) and heat transfer coefficient (HTC) during pool-boiling tests were measured with the micro-patterned surfaces and a reference plain copper surface. The CHF of short and tall micro-patterned surfaces were 1434 and 1444 kW/m², respectively, and the plain copper surface's CHF was 1191 kW/m². The HTC of the plain copper surface and the PIM surface with short and tall micro-patterned surfaces were similar in value up to a heat flux 1000 kW/m². Beyond that value, the plain surface quickly reached its CHF, while the HTC of the short micro-patterned surface achieved higher values than that of the tall micro-patterned surface. At CHF, the maximum values of HTC for the short micro-pattern, tall micro-pattern, and the plain copper surface were 68, 58, and 57 kW/m² K.
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    Timing Jitter Distribution and Power Spectral Density of a Second-Order Bang-Bang Digital PLL with Transport Delay Using Fokker-Planck Equations
    (IEEE-Inst Electrical Electronics Engineers Inc, 2018-12-18) Bondalapati, Pratheep; Namgoong, Won; 0000-0002-8864-8324 (Bondalapati, P); 0000-0003-3047-2888 (Namgoong, W); Bondalapati, Pratheep; Namgoong, Won
    In this paper, a second-order bang-bang digital phase-locked loop (BBPLL) with dominant random walk phase noise and transport delay is analyzed using Fokker-Plank equations. Explicit closed-form expressions are derived for the timing error probability distribution function, jitter variance, and power spectral density (psd). For the type-II BBPLL considered in this paper, the timing error distribution is shown to be Laplacian and not Gaussian distributed as previously assumed, while the derived psd is Lorentzian, which is consistent with earlier works. The analytical solutions are valid as long as the continuous-time approximation of the BBPLL dynamics is accurate as is the case for typical operating loop bandwidths. The accuracy of the derived expressions is validated via simulation.
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    Geofog4health: A Fog-Based SDI Framework for Geospatial Health Big Data Analysis
    (Springer Heidelberg, 2018-02-21) Barik, Rabindra Kumar; Dubey, Harishchandra; Mankodiya, Kunal; Sasane, Sapana Ashok; Misra, Chinmaya; Dubey, Harishchandra
    Spatial Data Infrastructure (SDI) is an important framework for sharing geospatial big data using the web. Integration of SDI with cloud computing led to emergence of Cloud-SDI as a tool for transmission, processing and analysis of geospatial data. Fog computing is a paradigm where embedded computers are employed to increase the throughput and reduce latency at the edge of the network. In this study, we developed and evaluated a Fog-based SDI framework named GeoFog4Health for mining analytics from geo-health big data. We built prototypes using Intel Edison and Raspberry Pi for studying the comparative performance. We conducted a case study on Malaria vector-borne disease positive maps of Maharastra state in India. The proposed framework had provision of lossless data compression for reduced data transfer. Also, overlay analysis of geospatial data was implemented. In addition, we discussed energy savings, cost analysis and scalability of the proposed framework with respect to efficient data processing. We compared the performance of the proposed framework with the state-of-the-art Cloud-SDI in terms of analysis time. Results and discussions showed the efficacy of the proposed system for enhanced analysis of geo-health big data generated from a variety of sensing frameworks.
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    Analyzing of Joint Strength, Impact Energy, and Angular Distortion of the ABS Friction Stir Welded Joints Reinforced by Nanosilica Addition
    (Springer London Ltd, 2018-10-16) Azhiri, Reza Bagherian; Sola, Jalal Fathi; Tekiyeh, Ramin Mehdizad; Javidpour, Farid; Bideskan, Abolfaz Salmani; Azhiri, Reza Bagherian
    In the present work, experimental investigation has been carried out to enhance the properties of acrylonitrile butadiene styrene joints. Here, nanosilica particle was used as reinforcement to form composite-like structure in the friction stir processed region and improve the joint strength. Experiments were designed based on response surface methodology to correlate relationship between parameters viz. nanosilica volume fraction, pass number, tool rotation speed, and travel speed to responses viz. tensile strength, hardness, and angular distortion. Analysis of variances has also been performed to find which factor has the greatest impact on joint properties. It is found from the results that silica addition and pass number have significant influence on tensile strength and hardness. Also, the angular distortion is mainly influenced by silica volume fraction and tool rotational speed. In order to find optimal combination of process parameter regarding maximum strength and hardness as well as minimum angular distortion, desirability approach function was utilized. The obtained results showed that in order, 20% silica volume fraction, two pass numbers, 1600rpm tool rotation, and 40mm/min travel speed cause desirability of 83%. The optimum results were further verified through confirmatory experiment.
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    Dynamic Prescribed-Wake Vortex Method for Aerodynamic Analysis of Offshore Floating Wind Turbines
    (Sage Publications Ltd, 2018-12-31) Aird, Jeanie; Gaertner, Evan; Lackner, Matthew; Aird, Jeanie
    A prescribed-wake vortex model for evaluating the aerodynamic loads on offshore floating turbines has been developed. As an extension to the existing UMass analysis tool, WInDS, the developed model uses prescribed empirical wake node velocity functions to model aerodynamic loading. This model is applicable to both dynamic flow conditions and dynamic rotational and translational platform motions of floating offshore turbines. With this model, motion-induced wake perturbations can be considered, and their effect on induction can be modeled, which is useful for floating offshore wind turbine design. The prescribed-wake WInDS model is shown to increase computational efficiency drastically in all presented cases and maintain comparable accuracy to the free wake model. Results of prescribed-wake model simulations are presented and compared to results obtained from the free wake model to confirm model validity.
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    Phonon-Assisted Tunneling in Direct-Bandgap Semiconductors
    (Amer Inst Physics, 2019-01-02) Mohammed, Mazharuddin; Verhulst, Anne S.; Verreck, Devin; Van de Put, Maarten L.; Magnus, Wim; Soree, Bart; Groeseneken, Guido; 0000-0001-9179-6443 (Van de Put, ML); Van de Put, Maarten L.
    In tunnel field-effect transistors, trap-assisted tunneling (TAT) is one of the probable causes for degraded subthreshold swing. The accurate quantum-mechanical (QM) assessment of TAT currents also requires a QM treatment of phonon-assisted tunneling (PAT) currents. Therefore, we present a multi-band PAT current formalism within the framework of the quantum transmitting boundary method. An envelope function approximation is used to construct the electron-phonon coupling terms corresponding to local Frohlich-based phonon-assisted inter-band tunneling in direct-bandgap III-V semiconductors. The PAT current density is studied in up to 100 nm long and 20 nm wide p-n diodes with the 2- and 15-band material description of our formalism. We observe an inefficient electron-phonon coupling across the tunneling junction. We further demonstrate the dependence of PAT currents on the device length, for our non-self-consistent formalism which neglects changes in the electron distribution function caused by the electron-phonon coupling. Finally, we discuss the differences in doping dependence between direct band-to-band tunneling and PAT current. Published under license by AIP Publishing.
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    Digital Image Steganalysis Based on Visual Attention and Deep Reinforcement Learning
    (IEEE-Inst Electrical Electronics Engineers Inc, 2019-02-18) Hu, Donghui; Zhou, Shengnan; Shen, Qiang; Zheng, Shuli; Zhou, Zhongqiu; Fan, Yuqi; Fan, Yuqi
    Recently, the adaptive steganography methods have been developed to embed secret information with the minimal distortion of images. As the opposite art, steganalysis methods, especially some convolutional neural network-based steganalysis methods, have been proposed to detect whether an image is embedded with secret information or not. The state-of-the-art steganography methods hide secret information in different regions of an image with different probabilities. However, most of the current steganalysis methods extract the steganalysis features from different regions without discrimination, which reduces the performance of the current deep-learning-based steganalysis methods when attacking the adaptive steganography methods. In this paper, we propose a new self-seeking steganalysis method based on visual attention and deep reinforcement learning to detect the JPEG-based adaptive steganography. First, a region is selected from the image by a visual attention method, and a continuous decision is then made to generate a summary region by reinforcement learning. Thereby, the deep learning model is guided to focus on these regions that are favorable to steganalysis and ignore those regions that are unfavorable. Finally, the quality of training set and the detection ability of steganalysis are improved by replacing the mis-classified training images with their corresponding summary regions. The experiments show that our method obtains the competitive detection accuracy, compared with the other state-of-the-art advanced detection methods.
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    SAF-BAGE: Salient Approach for Facial Soft-Biometric Classification - Age, Gender, and Facial Expression
    (IEEE, 2019) Gurnani, Ayesha; Shah, Kenil; Gajjar, Vandit; Mavani, Viraj; Khandhediya, Yash; Gurnani, Ayesha; Mavani, Viraj
    How can we improve the facial soft-biometric classification with help of the human visual system? This paper explores the use of saliency which is equivalent to the human visual system to classify Age, Gender and Facial Expression soft-biometric for facial images. Using the Deep Multi-level Network (ML-Net) [1] and off-the-shelf face detector [2], we propose our approach - SAF-BAGE, which first detects the face in the test image, increases the Bounding Box (B-Box) margin by 30%, finds the saliency map using ML-Net, with 30% reweighted ratio of saliency map, it multiplies with the input cropped face and extracts the Convolutional Neural Networks (CNN) predictions on the multiplied reweighted salient face. Our CNN uses the model AlexNet [3], which is pre-trained on ImageNet. The proposed approach surpasses the performance of other approaches, increasing the state-of-the-art by approximately 0.8% on the widely-used Adience [28] dataset for Age and Gender classification and by nearly 3% on the recent AffectNet [36] dataset for Facial Expression classification. We hope our simple, reproducible and effective approach will help ease future research in facial soft-biometric classification using saliency.
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    Effects of Upstream Buildings on the Performance of a Synergistic Roof-and-Diffuser Augmentation System for Cross Flow Wind Turbines
    (Elsevier Science BV, 2018-12-10) Zanforlin, Stefania; Letizia, Stefano; Letizia, Stefano
    In a previous work we investigated the effectiveness of combining the concentration effects generated by a dual-pitched roof and a convergent-divergent semi-diffuser placed over a cross flow turbine (CFT), which is rooftop mounted with horizontal shaft running close to the roof ridge. By means of 2D CFD we now assess the effects of the upstream buildings on the performance of this concentration system. Three different urban layouts are simulated via a challenging fully-resolved URANS approach that gives unprecedented insight into the complex interactions of the flow around buildings, diffuser and turbine's blades. A promising power augmentation of 40% with respect to the case without diffuser are obtained and the mechanism behind this performance enhancement are analysed. The beneficial effect of the diffuser on the torque fluctuations damping (similar to 60%) is also discussed. Important remarks on the load control strategy for diffuser-augmented CFT are finally presented.
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    A VLA–GMRT Look At 11 Powerful Fr II Quasars
    (Oxford University Press, 2018-12-27) Vaddi, S.; Kharb, P.; Daly, R. A.; O’Dea, C. P.; Baum, S. A.; Deo, D. K.; Barbusca, T. C.; Murali, Chintak; Murali, Chintak
    We present results from 1.4 and 5 GHz observations at matched resolution with the Karl G. Jansky Very Large Array (VLA) of 11 powerful 3C FR II quasars. We examine the 11 quasars along with a sample of 13 narrow-line FR II radio galaxies and find that radio-loud unification largely holds but environmental effects cannot be ignored. The radio core prominence, largest linear size, and axial ratio parameter values indicate that quasars are at relatively smaller angles compared to the radio galaxies and thus probe orientation. Lack of correlation between statistical orientation indicators such as misalignment angle and radio core prominence, and larger lobe distortions in quasars compared to radio galaxies suggest that intrinsic/environment effects are also at play. Some of 150 MHz observations with the TGSS–GMRT reveal peculiar lobe morphologies in these FR II sources, suggesting complex past lives and possibly restarted AGN activity. Using the total 150 MHz flux density we estimate the time-averaged jet kinetic power in these sources and this ranges from (1–38) × 10⁻⁴⁵ erg s⁻¹, with 3C 470 having the highest jet kinetic power. © 2018 The Author(s).
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    Hide and Seek: An Architecture for Improving Attack-Visibility in Industrial Control Systems
    (Springer Verlag, 2019-06) Giraldo, Jairo; Urbina, David; Cardenas, A. A.; Tippenhauer, N. O.; Giraldo, Jairo; Urbina, David
    In the past years we have seen an emerging field of research focusing on using the “physics” of a Cyber-Physical System to detect attacks. In its basic form, a security monitor is deployed somewhere in the industrial control network, observes a time-series of the operation of the system, and identifies anomalies in those measurements in order to detect potentially manipulated control commands or manipulated sensor readings. While there is a growing literature on detection mechanisms in that research direction, the problem of where to monitor the physical behavior of the system has received less attention. In this paper, we analyze the problem of where should we monitor these systems, and what attacks can and cannot be detected depending on the location of this network monitor. The location of the monitor is particularly important, because an attacker can bypass attack-detection by lying in some network interfaces while reporting that everything is normal in the others. Our paper is the first detailed study of what can and cannot be detected based on the devices an attacker has compromised and where we monitor our network. We show that there are locations that maximize our visibility against such attacks. Based on our analysis, we design a low-level security monitor that is able to directly observe the field communication between sensors, actuators, and Programmable Logic Controllers (PLCs). We implement that security monitor in a realistic testbed, and demonstrate that it can detect attacks that would otherwise be undetected at the supervisory network. © Springer Nature Switzerland AG 2019.
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    Development and Characterization of Photodiode N-ZnO/p-Si By Radio Frecuency Sputtering, A Sensor with Low Voltage Operation and its Response to Visible and UV Light
    (Elsevier Science SA, 2018-10-11) Chávez-Urbiola, Iker Rodrigo; Willars-Rodriguez, F. J.; Ramirez Bon, R.; Vorobiev, P.; Vorobiev, Yu V.; Chávez-Urbiola, Iker Rodrigo
    The heterostructure n-ZnO/p-Si was fabricated by Radio Frequency Sputtering. The photodiode characteristics were obtained from current-voltage curves. The photovoltaic effect and photodiode sensitivity were measured by transient photo-current, both under UV-Light and VIS-Light. The results show a well define rectification character, the relation between current at forward bias and reverse bias was about two orders of magnitude. The photovoltaic effect was observed for UV and Vis light; the photodiode presents a higher sensitivity for Vis light than for UV light. The transient-photocurrent was recorded at a different voltage (-2, -1 and 0 V) under Vis and UV light. The photo-response for UV and Vis light at -1 V were 1.71 mA/W and 9.35 mA/W and for 0 V were 0.62 mA/W and 0.70 mA/W respectively.
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    Dual Sensitization Effect and Conductive Structure of Fe₃O₄@mTiO₂/C Photocatalyst Towards Superior Photodegradation Activity for Bisphenol A Under Visible Light
    (Elsevier B.V., 2019-05-31) Zhao, X.; Wang, R.; Lu, Z.; Wang, Weichao; Yan, Y.; Wang, Weichao
    In this paper, we prepared Fe₃O₄@mTiO₂/C (the mesoporous TiO₂ denoted as mTiO₂) photocatalyst via a simple synthetic method, and it exhibits strong light response under visible light region because of the dual sensitization effect of Fe₃O₄ and carbon. In addition, the composite photocatalyst also has double conductivity, which is beneficial to the transfer and separation of charge carriers due to the synergetic effect of Fe₃O₄, carbon and mTiO₂. As a consequence, the double conductive structure Fe₃O₄@mTiO₂/C photocatalyst displays prominent photocatalytic activity in degradation of BPA under visible light. Furthermore, the photocatalyst not only was recycled easily to reduce the secondary pollution of the environment but also had a superior stability. This work may provide a new inspiration toward constructing dual sensitization and double conductive structure with other semiconductor photocatalyst to effectively improve the photocatalytic activity under visible light for practical application.
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    Symmetry-Protected Localized States at Defects in Non-Hermitian Systems
    (American Physical Society, 2019-06-12) Wu, Ya-Jie; Hou, Junpeng; Wu, Ya-Jie; Hou, Junpeng
    Understanding how local potentials affect system eigenmodes is crucial for experimental studies of nontrivial bulk topology. Recent studies have discovered many exotic and highly nontrivial topological states in non-Hermitian systems. As such, it would be interesting to see how non-Hermitian systems respond to local perturbations. In this work we consider chiral and particle-hole-symmetric non-Hermitian systems on a bipartite lattice, including the Su-Schrieer-Heeger model and photonic graphene, and find that a disordered local potential could induce bound states evolving from the bulk. When the local potential on a single site becomes infinite, which renders a lattice vacancy, chiral-symmetry-protected zero-energy mode and particle-hole-symmetry-protected bound states with purely imaginary eigenvalues emerge near the vacancy. These modes are robust against any symmetry-preserved perturbations. Our work generalizes the symmetry-protected localized states to non-Hermitian systems. © 2019 American Physical Society.
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    Discriminant Analysis and Machine Learning Approach for Evaluating and Improving the Performance of Immunohistochemical Algorithms for COO Classification of DLBCL
    (Biomed Central Ltd., 2019-06-11) Perfecto-Avalos, Y.; Garcia-Gonzalez, A.; Hernandez-Reynoso, Ana; Sánchez-Ante, G.; Ortiz-Hidalgo, C.; Scott, S. -P; Fuentes-Aguilar, R. Q.; DIaz-Dominguez, R.; León-Martínez, G.; Velasco-Vales, V.; Cárdenas-Escudero, M. A.; Hernández-Hernández, J. A.; Santos, A.; Borbolla-Escoboza, J. R.; Villela, L.; Hernandez-Reynoso, Ana
    Background: Diffuse large B-cell lymphoma (DLBCL) is classified into germinal center-like (GCB) and non-germinal center-like (non-GCB) cell-of-origin groups, entities driven by different oncogenic pathways with different clinical outcomes. DLBCL classification by immunohistochemistry (IHC)-based decision tree algorithms is a simpler reported technique than gene expression profiling (GEP). There is a significant discrepancy between IHC-decision tree algorithms when they are compared to GEP. Methods: To address these inconsistencies, we applied the machine learning approach considering the same combinations of antibodies as in IHC-decision tree algorithms. Immunohistochemistry data from a public DLBCL database was used to perform comparisons among IHC-decision tree algorithms, and the machine learning structures based on Bayesian, Bayesian simple, Naïve Bayesian, artificial neural networks, and support vector machine to show the best diagnostic model. We implemented the linear discriminant analysis over the complete database, detecting a higher influence of BCL6 antibody for GCB classification and MUM1 for non-GCB classification. Results: The classifier with the highest metrics was the four antibody-based Perfecto-Villela (PV) algorithm with 0.94 accuracy, 0.93 specificity, and 0.95 sensitivity, with a perfect agreement with GEP (κ = 0.88, P < 0.001). After training, a sample of 49 Mexican-mestizo DLBCL patient data was classified by COO for the first time in a testing trial. Conclusions: Harnessing all the available immunohistochemical data without reliance on the order of examination or cut-off value, we conclude that our PV machine learning algorithm outperforms Hans and other IHC-decision tree algorithms currently in use and represents an affordable and time-saving alternative for DLBCL cell-of-origin identification. © 2019 The Author(s).
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    Mixtures of Lithium Salts and Ionic Liquids at Defected Graphene Walls
    (Elsevier B.V., 2019-06-02) Montes-Campos, H.; Manuel Otero-Mato, J.; Longo, Roberto Carlos; Cabeza, O.; Javier Gallego, L.; Miguel Varela, L.; Longo, Roberto Carlos
    In order to investigate the effect of defects on the structure of an electrode on the electric double layer of ionic-liquid-based electrolytes, we perform classical molecular dynamic simulations on mixtures of 1-butyl-3-methylimidazolium tetrafluoroborate ([BMIM][BF4]) and lithium tetrafluoroborate (LiBF4) near charged graphene electrodes with different percentages of single defect vacancies, assuming planarity of the defected graphene, as follows from our density-functional theory calculations. Defects on the electrode's surface modify the surface charge density at the innermost layer of the electrochemical interface, which allows studying the structure of the electric double layer at a constant density of ions without changing either the voltage or the electrolyte composition. Indeed, we report that the presence of defects on the graphene electrodes can induce structural transitions in the innermost layer of the electric double layer. This result is supported by a thorough analysis of the structural properties of the layer and its energy landscape, particularly showing that there is a direct correlation between this defect-induced layer structure and the adsorption of the salt cations at the electrode, which is of utmost importance for the usage of these novel electrolytic mixtures in actual electrochemical devices. © 2019 Elsevier B.V.
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    Design and Analysis of Three-Stage Amplifier for Driving pF-to-nF Capacitive Load Based on Local Q-Factor Control and Cascode Miller Compensation Techniques
    (MDPI AG, 2019-05-29) Cheng, Qi; Li, W.; Tang, X.; Guo, J.; Cheng, Qi
    This paper presents a new frequency compensation approach for three-stage amplifiers driving a pF-to-nF capacitive load. Thanks to the cascode Miller compensation, the non-dominant complex pole frequency is extended effectively, and the physical size of the compensation capacitors is also reduced. A local Q-factor control (LQC) loop is introduced to alter the Q-factor adaptively when loading capacitance CL varies significantly. This LQC loop decides how much damping current should be injected into the corresponding parasitic node to control the Q-factor of the complex-pole pair, which affects the frequency peak at the gain plot and the settling time of the proposed amplifier in the closed-loop step response. Additionally, a left-half-plane (LHP) zero is created to increase the phase margin and a feed-forward transconductance stage is paralleled to improve the slew rate (SR). Simulated in 0.13-µm CMOS technology, the amplifier is verified to handle a 4-pF-to-1.5-nF (375× drivability) capacitive load with at least 0.88-MHz gain-bandwidth (GBW) product and 42.3° phase margin (PM), while consuming 24.0-µW quiescent power at 1.0-V nominal supply voltage. ©2019 by the authors. Licensee MDPI, Basel, Switzerland.