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Articles 1531 - 1560 of 10894
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Values Of Artificial Intelligence In Marketing, Yingrui Xi
Values Of Artificial Intelligence In Marketing, Yingrui Xi
Masters Theses
“Artificial Intelligence (AI) is causing radical changes in marketing and emerging as a competent assistant supporting all areas of the marketing field. The influences and impacts AI has created in various marketing segments have aroused much interest among marketing professionals and academic scholars. Comprehensive and systematic studies on the values of AI in marketing, however, are still lacking and the existing literature fragmented. This research provides a comprehensive review of the existing literature in the relevant fields as well as a series of systematic interviews using the Value-Focused Thinking approach to understand the values of AI in marketing. This research …
Effect Of Subsurface Microseismicity On The Motion Of Surrounding Dispersed Droplets: Supporting Information, Chao Zeng, Wen Deng
Effect Of Subsurface Microseismicity On The Motion Of Surrounding Dispersed Droplets: Supporting Information, Chao Zeng, Wen Deng
Research Data
The human-induced seismicity has called substantial attention in recent years. The effect of seismicity on the subsurface structure has been extensively studied. However, the effect of seismicity, especially those microseismicity, on surrounding immiscible fluids is rarely investigated. In porous media with two or more immiscible fluids, different amplitudes of vibration induced by seismicity have distinct effects on the dynamic behavior of fluids. Three types of pore-scale models are prevalent in the analysis of the motion of immiscible droplets. The underlying assumptions and accuracy of these models are compared in this study in both frequency domain and time domain. The frequency …
A Hybrid And Scalable Error Correction Algorithm For Indel And Substitution Errors Of Long Reads, Arghya Kusum Das, Sayan Goswami, Kisung Lee, Seung Jong Park
A Hybrid And Scalable Error Correction Algorithm For Indel And Substitution Errors Of Long Reads, Arghya Kusum Das, Sayan Goswami, Kisung Lee, Seung Jong Park
Computer Science Faculty Research & Creative Works
Background: Long-read sequencing has shown the promises to overcome the short length limitations of second-generation sequencing by providing more complete assembly. However, the computation of the long sequencing reads is challenged by their higher error rates (e.g., 13% vs. 1%) and higher cost ($0.3 vs. $0.03 per Mbp) compared to the short reads. Methods: In this paper, we present a new hybrid error correction tool, called ParLECH (Parallel Long-read Error Correction using Hybrid methodology). The error correction algorithm of ParLECH is distributed in nature and efficiently utilizes the k-mer coverage information of high throughput Illumina short-read sequences to rectify the …
Learning Nearest Neighbor Graphs From Noisy Distance Samples, Blake Mason, Ardhendu S. Tripathy, Robert Nowak
Learning Nearest Neighbor Graphs From Noisy Distance Samples, Blake Mason, Ardhendu S. Tripathy, Robert Nowak
Computer Science Faculty Research & Creative Works
We consider the problem of learning the nearest neighbor graph of a dataset of n items. The metric is unknown, but we can query an oracle to obtain a noisy estimate of the distance between any pair of items. This framework applies to problem domains where one wants to learn people's preferences from responses commonly modeled as noisy distance judgments. In this paper, we propose an active algorithm to find the graph with high probability and analyze its query complexity. In contrast to existing work that forces Euclidean structure, our method is valid for general metrics, assuming only symmetry and …
Maxgap Bandit: Adaptive Algorithms For Approximate Ranking, Sumeet Katariya, Ardhendu S. Tripathy, Robert Nowak
Maxgap Bandit: Adaptive Algorithms For Approximate Ranking, Sumeet Katariya, Ardhendu S. Tripathy, Robert Nowak
Computer Science Faculty Research & Creative Works
This paper studies the problem of adaptively sampling from K distributions (arms) in order to identify the largest gap between any two adjacent means. We call this the MaxGap-bandit problem. This problem arises naturally in approximate ranking, noisy sorting, outlier detection, and top-arm identification in bandits. The key novelty of the MaxGap bandit problem is that it aims to adaptively determine the natural partitioning of the distributions into a subset with larger means and a subset with smaller means, where the split is determined by the largest gap rather than a pre-specified rank or threshold. Estimating an arm's gap requires …
Missouri S&T Magazine Fall/Winter 2019, Missouri S&T Marketing And Communications Department, Miner Alumni Association
Missouri S&T Magazine Fall/Winter 2019, Missouri S&T Marketing And Communications Department, Miner Alumni Association
Missouri S&T Magazine
No abstract provided.
Detection And Mitigation Of Attacks In Nonlinear Stochastic System Using Modified Detector, Chandreyee Bhowmick, S. Jagannathan
Detection And Mitigation Of Attacks In Nonlinear Stochastic System Using Modified Detector, Chandreyee Bhowmick, S. Jagannathan
Electrical and Computer Engineering Faculty Research & Creative Works
A novel attack detection method is presented for a nonlinear system with known dynamics using the measured output in the presence of additive process and measurement noise. False data injection (FDI) and replay attacks are considered using a modified fault detector. The difference between the measured and the estimated output from an adaptive observer, often known as the innovation signal, is generated and shown to have a Gaussian distribution with non-zero mean. This innovation signal in conjunction with the modified detector is utilized to detect attacks under a stable controller using the estimated state vector. Unlike FDI attack, where the …
Novel Cyber Fault Prognosis And Resilience Control For Cyber-Physical Systems, Shanshan Bi, Tianchen Wang, Lei Wang, Maciej Zawodniok
Novel Cyber Fault Prognosis And Resilience Control For Cyber-Physical Systems, Shanshan Bi, Tianchen Wang, Lei Wang, Maciej Zawodniok
Electrical and Computer Engineering Faculty Research & Creative Works
Cyber-physical systems (CPSs) consist of a network, computation, and physical process. Embedded networks, which deliver control and sensing signal, can potentially affect CPSs performance. However, the degradation of physical system performance caused by the embedded networks is frequently oversimplified with strong assumptions. The proposed scheme effectively relaxes those assumptions in the existing works that network delays are bounded in a specific range, or its distribution is time invariant. Most of the existing works on fault diagnosis and prognosis addressed the physical system fault detection and isolation and ignore cyber network faults. A novel cyber network fault prognosis scheme is proposed …
Nonlinear Loss Model In Absorptive-Type Ferrite Frequency-Selective Limiters, Anatoliy O. Boryssenko, Scott M. Gillette, Marina Y. Koledintseva
Nonlinear Loss Model In Absorptive-Type Ferrite Frequency-Selective Limiters, Anatoliy O. Boryssenko, Scott M. Gillette, Marina Y. Koledintseva
Electrical and Computer Engineering Faculty Research & Creative Works
Absorptive-type ferrite-based frequency-selective limiters (FSLs) utilize nonlinear (NL) phenomena in magnetized ferrites to provide real-time analog signal processing of RF/microwave electromagnetic (EM) signals. There are no commercially available modeling tools that simulate these interactions, and the development and optimization of FSLs are largely done experimentally. FSL modeling and design is complicated by NL, multiscale, and Multiphysics nature of operation. In this article, an NL loss model in a ferrite is proposed and implemented in an efficient numerical algorithm. The equivalent linear magnetic loss tangent is represented in a closed form. A full-wave numerical EM model with high-fidelity meshing is set …
Design And Sensitivity Analysis Of Ebg Stripline Common-Mode Filters, Marina Y. Koledintseva, Sergiu Radu, Joseph Nuebel
Design And Sensitivity Analysis Of Ebg Stripline Common-Mode Filters, Marina Y. Koledintseva, Sergiu Radu, Joseph Nuebel
Electrical and Computer Engineering Faculty Research & Creative Works
Workflow of electromagnetic bandgap (EBG) common-mode (CM) filter design of edge-coupled differential pairs on a printed circuit board (PCB) and sensitivity of its characteristics to variations of geometrical and material parameters are discussed. A number of simple 20-GHz EBG CM notch filters for differential strip line pairs are designed using full-wave numerical electromagnetic modeling, fabricating, and testing. The cases of one and two strip line differential pairs crossing the EBG patches are considered. The modeled and measured mixed-mode S-parameters are analyzed as functions of geometrical parameters, including size and number of EBG patches, gaps between them, geometry and position of …
Correction To: Better Beware: Comparing Metacognition For Phishing And Legitimate Emails (Metacognition And Learning, (2019), 14, 3, (343-362), 10.1007/S11409-019-09197-5), Casey I. Canfield, Baruch Fischhoff, Alex Davis
Correction To: Better Beware: Comparing Metacognition For Phishing And Legitimate Emails (Metacognition And Learning, (2019), 14, 3, (343-362), 10.1007/S11409-019-09197-5), Casey I. Canfield, Baruch Fischhoff, Alex Davis
Engineering Management and Systems Engineering Faculty Research & Creative Works
The article "Better beware: comparing metacognition for phishing and legitimate emails", written by Casey Inez Canfield, Baruch Fischhoff and Alex Davis, was originally published electronically on the publisher's internet portal (currently SpringerLink) on 20 July 2019 without open access.
Predicting The Daily Return Direction Of The Stock Market Using Hybrid Machine Learning Algorithms, X. Zhong, David Lee Enke
Predicting The Daily Return Direction Of The Stock Market Using Hybrid Machine Learning Algorithms, X. Zhong, David Lee Enke
Engineering Management and Systems Engineering Faculty Research & Creative Works
Big data analytic techniques associated with machine learning algorithms are playing an increasingly important role in various application fields, including stock market investment. However, few studies have focused on forecasting daily stock market returns, especially when using powerful machine learning techniques, such as deep neural networks (DNNs), to perform the analyses. DNNs employ various deep learning algorithms based on the combination of network structure, activation function, and model parameters, with their performance depending on the format of the data representation. This paper presents a comprehensive big data analytics process to predict the daily return direction of the SPDR S&P 500 …
Better Beware: Comparing Metacognition For Phishing And Legitimate Emails, Casey I. Canfield, Baruch Fischhoff, Alex Davis
Better Beware: Comparing Metacognition For Phishing And Legitimate Emails, Casey I. Canfield, Baruch Fischhoff, Alex Davis
Engineering Management and Systems Engineering Faculty Research & Creative Works
Every electronic message poses some threat of being a phishing attack. If recipients underestimate that threat, they expose themselves, and those connected to them, to identity theft, ransom, malware, or worse. If recipients overestimate that threat, then they incur needless costs, perhaps reducing their willingness and ability to respond over time. In two experiments, we examined the appropriateness of individuals' confidence in their judgments of whether email messages were legitimate or phishing, using calibration and resolution as metacognition metrics. Both experiments found that participants had reasonable calibration but poor resolution, reflecting a weak correlation between their confidence and knowledge. These …
Pore Elimination Mechanisms During 3d Printing Of Metals, S. Mohammad H. Hojjatzadeh, Niranjan D. Parab, Wentao Yan, Lianyi Chen, For Full List Of Authors, See Publisher's Website.
Pore Elimination Mechanisms During 3d Printing Of Metals, S. Mohammad H. Hojjatzadeh, Niranjan D. Parab, Wentao Yan, Lianyi Chen, For Full List Of Authors, See Publisher's Website.
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Laser powder bed fusion (LPBF) is a 3D printing technology that can print metal parts with complex geometries without the design constraints of traditional manufacturing routes. However, the parts printed by LPBF normally contain many more pores than those made by conventional methods, which severely deteriorates their properties. Here, by combining in-situ high-speed high-resolution synchrotron x-ray imaging experiments and multi-physics modeling, we unveil the dynamics and mechanisms of pore motion and elimination in the LPBF process. We find that the high thermocapillary force, induced by the high temperature gradient in the laser interaction region, can rapidly eliminate pores from the …
Publisher Correction: Pore Elimination Mechanisms During 3d Printing Of Metals (Nature Communications, (2019), 10, 1, (3088), 10.1038/S41467-019-10973-9), S. Mohammad H. Hojjatzadeh, Niranjan D. Parab, Wentao Yan, Qilin Guo, Lianghua Xiong, Cang Zhao, Mimglei Qu, Luis I. Escano, Xianghui Xiao, Kamel Fezzaa, Wes Everhart, Tao Sun, Lianyi Chen
Publisher Correction: Pore Elimination Mechanisms During 3d Printing Of Metals (Nature Communications, (2019), 10, 1, (3088), 10.1038/S41467-019-10973-9), S. Mohammad H. Hojjatzadeh, Niranjan D. Parab, Wentao Yan, Qilin Guo, Lianghua Xiong, Cang Zhao, Mimglei Qu, Luis I. Escano, Xianghui Xiao, Kamel Fezzaa, Wes Everhart, Tao Sun, Lianyi Chen
Mechanical and Aerospace Engineering Faculty Research & Creative Works
The original version of this Article contained an error in Fig. 4. The x-axis labels in Fig. 4a, b were incorrectly labelled 'Diameter (mm)', rather than the correct 'Diameter (µm)'. This has been corrected in both the PDF and HTML versions of the Article.
The Conundrum Of Relaxation Volumes In First-Principles Calculations Of Charged Defects In Uo₂, Anuj Goyal, Kiran Mathew, Richard G. Hennig, Aleksandr V. Chernatynskiy
The Conundrum Of Relaxation Volumes In First-Principles Calculations Of Charged Defects In Uo₂, Anuj Goyal, Kiran Mathew, Richard G. Hennig, Aleksandr V. Chernatynskiy
Physics Faculty Research & Creative Works
The defect relaxation volumes obtained from density-functional theory (DFT) calculations of charged vacancies and interstitials are much larger than their neutral counterparts, seemingly unphysically large. We focus on UO2 as our primary material of interest, but also consider Si and GaAs to reveal the generality of our results. In this work, we investigate the possible reasons for this and revisit the methods that address the calculation of charged defects in periodic DFT. We probe the dependence of the proposed energy corrections to charged defect formation energies on relaxation volumes and find that corrections such as potential alignment remain ambiguous with …
Introduction Of A Hybrid Monitor For Cyber-Physical Systems, J. Ceasar Aguma, Bruce M. Mcmillin, Amelia Regan
Introduction Of A Hybrid Monitor For Cyber-Physical Systems, J. Ceasar Aguma, Bruce M. Mcmillin, Amelia Regan
Computer Science Faculty Research & Creative Works
Computing systems and mobile technologies have changed dramatically since the introduction of firewall technology in 1988. The internet has grown from a simple network of networks to a cyber and physical entity that encompasses the entire planet. Cyber-physical systems(CPS) now control most of the day to day operations of human civilization from autonomous cars to nuclear energy plants. While phenomenal, this growth has created new security threats. These are threats that cannot be blocked by a firewall for they are not only cyber but cyber-physical. In light of these cyber-physical threats, this paper proposes a security measure that promises to …
The Missouri Miner, November 6, 2019
The Missouri Miner, November 6, 2019
The Missouri Miner Newspaper
No abstract provided.
Blended Root Finding Algorithm Outperforms Bisection And Regula Falsi Algorithms, Chaman Sabharwal
Blended Root Finding Algorithm Outperforms Bisection And Regula Falsi Algorithms, Chaman Sabharwal
Computer Science Faculty Research & Creative Works
Finding the roots of an equation is a fundamental problem in various fields, including numerical computing, social and physical sciences. Numerical techniques are used when an analytic solution is not available. There is not a single algorithm that works best for every function. We designed and implemented a new algorithm that is a dynamic blend of the bisection and regula falsi algorithms. The implementation results validate that the new algorithm outperforms both bisection and regula falsi algorithms. It is also observed that the new algorithm outperforms the secant algorithm and the Newton-Raphson algorithm because the new algorithm requires fewer computational …
Biomarker Discovery In Inflammatory Bowel Diseases Using Network-Based Feature Selection, Mostafa Abbas, John Matta, Thanh Le, Halima Bensmail, Tayo Obafemi-Ajayi, Vasant Honavar, Yasser El-Manzalawy
Biomarker Discovery In Inflammatory Bowel Diseases Using Network-Based Feature Selection, Mostafa Abbas, John Matta, Thanh Le, Halima Bensmail, Tayo Obafemi-Ajayi, Vasant Honavar, Yasser El-Manzalawy
Electrical and Computer Engineering Faculty Research & Creative Works
Reliable identification of Inflammatory biomarkers from metagenomics data is a promising direction for developing non-invasive, cost-effective, and rapid clinical tests for early diagnosis of IBD. We present an integrative approach to Network-Based Biomarker Discovery (NBBD) which integrates network analyses methods for prioritizing potential biomarkers and machine learning techniques for assessing the discriminative power of the prioritized biomarkers. Using a large dataset of new-onset pediatric IBD metagenomics biopsy samples, we compare the performance of Random Forest (RF) classifiers trained on features selected using a representative set of traditional feature selection methods against NBBD framework, configured using five different tools for inferring …
A Multi-Step Approach To Modeling The 24-Hour Daily Profiles Of Electricity Load Using Daily Splines, Abdelmonaem Jornaz, V. A. Samaranayake
A Multi-Step Approach To Modeling The 24-Hour Daily Profiles Of Electricity Load Using Daily Splines, Abdelmonaem Jornaz, V. A. Samaranayake
Mathematics and Statistics Faculty Research & Creative Works
Forecasting of real-time electricity load has been an important research topic over many years. Electricity load is driven by many factors, including economic conditions and weather. Furthermore, the demand for electricity varies with time, with different hours of the day and different days of the week having an effect on the load. This paper proposes a hybrid load-forecasting method that combines classical time series formulations with cubic splines to model electricity load. It is shown that this approach produces a model capable of making short-term forecasts with reasonable accuracy. In contrast to forecasting models that utilize a multitude of regressor …
Angular Memory Effect Of Transmission Eigenchannels, Hasan Yllmaz, Chia Wei Hsu, Arthur Goetschy, Stefan Bittner, Stefan Rotter, Alexey Yamilov, Hui Cao
Angular Memory Effect Of Transmission Eigenchannels, Hasan Yllmaz, Chia Wei Hsu, Arthur Goetschy, Stefan Bittner, Stefan Rotter, Alexey Yamilov, Hui Cao
Physics Faculty Research & Creative Works
The optical memory effect has emerged as a powerful tool for imaging through multiple-scattering media; however, the finite angular range of the memory effect limits the field of view. Here, we demonstrate experimentally that selective coupling of incident light into a high-transmission channel increases the angular memory-effect range. This enhancement is attributed to the robustness of the high-transmission channels against perturbations such as sample tilt or wave front tilt. Our work shows that the high-transmission channels provide an enhanced field of view for memory-effect-based imaging through diffusive media.
Opportunities And Challenges For Rural Broadband Infrastructure Investment, Casey I. Canfield, Ona Egbue, Jacob Hale, Suzanna Long
Opportunities And Challenges For Rural Broadband Infrastructure Investment, Casey I. Canfield, Ona Egbue, Jacob Hale, Suzanna Long
Engineering Management and Systems Engineering Faculty Research & Creative Works
Insufficient internet access is holding back local economies, reducing educational outcomes, and creating health disparities in rural areas of the U.S. At present, federal and state funding is available for rural broadband infrastructure deployment, but existing efforts have not invested in analytical work to maximize efficiency and minimize cost. In this study, we use a state-of-the-art matrix (SAM) to identify key challenges and opportunities facing rural broadband infrastructure from previous research and government reports. We focus on six themes: (1) technology, (2) hardware costs, (3) financing, (4) adoption, (5) regulatory/legal, and (6) management. We highlight key issues to be addressed …
A Study Of Brain Neuronal And Functional Complexities Estimated Using Multiscale Entropy In Healthy Young Adults, Sreevalsan S. Menon, K. Krishnamurthy
A Study Of Brain Neuronal And Functional Complexities Estimated Using Multiscale Entropy In Healthy Young Adults, Sreevalsan S. Menon, K. Krishnamurthy
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Brain complexity estimated using sample entropy and multiscale entropy (MSE) has recently gained much attention to compare brain function between diseased or neurologically impaired groups and healthy control groups. Using resting-state functional magnetic resonance imaging (rfMRI) blood oxygen-level dependent (BOLD) signals in a large cohort (n = 967) of healthy young adults, the present study maps neuronal and functional complexities estimated by using MSE of BOLD signals and BOLD phase coherence connectivity, respectively, at various levels of the brain’s organization. The functional complexity explores patterns in a higher dimension than neuronal complexity and may better discern changes in brain functioning. …
Electrochemistry Of Illusive Barbosalite, Fe²⁺Fe³⁺ 2(Po₄)₂(Oh)₂: An Iron Phosphate Related To Lipscombite Structure, Prashanth Sandineni, Kartik Ghosh, Amitava Choudhury
Electrochemistry Of Illusive Barbosalite, Fe²⁺Fe³⁺ 2(Po₄)₂(Oh)₂: An Iron Phosphate Related To Lipscombite Structure, Prashanth Sandineni, Kartik Ghosh, Amitava Choudhury
Chemistry Faculty Research & Creative Works
Barbosalite, an iron hydroxy-phosphate belonging to the family of Lazulite has been synthesized using hydrothermal route and its electrochemical property is investigated for the first time with respect to Li-ion batteries. The structure, as determined from single-crystal X-ray diffraction data, built up of undulating layers of FeO6 octahedra, consisting of trimers and PO4 tetrahedral units. Magnetic susceptibility measurements show predominant overall anti-ferromagnetic interactions and room temperature 57Fe Mössbauer spectroscopic studies confirm the mixed 3+ and 2+ oxidation states of Fe in the compound. The compound is stable up to 400°C and undergo facile electrochemical lithium insertion. Galvanostatic charge-discharge …
The Effect Of Tantalum Incorporation On The Physical And Chemical Properties Of Ternary Silicon–Calcium–Phosphorous Mesoporous Bioactive Glasses, Andrew Mendonca, Md Saidur Rahman, Adel Alhalawani, Omar Rodriguez, Reid C. Gallant, Heyu Ni, Owen M. Clarkin, Mark R. Towler
The Effect Of Tantalum Incorporation On The Physical And Chemical Properties Of Ternary Silicon–Calcium–Phosphorous Mesoporous Bioactive Glasses, Andrew Mendonca, Md Saidur Rahman, Adel Alhalawani, Omar Rodriguez, Reid C. Gallant, Heyu Ni, Owen M. Clarkin, Mark R. Towler
Chemical and Biochemical Engineering Faculty Research & Creative Works
Synthesis and characterization of the first mesoporous bioactive glasses (MBGs) containing tantalum are reported here, along with their potential application as hemostats. Silica MBGs were synthesized using with the molar composition of (80-x)% Si, 15% Ca, 5% P, and x% Ta. It was found that incorporation of >1 mol % Ta into the MBGs changes their physical and chemical properties. Increasing Ta content from 0 to 10 mol % causes a decrease in the surface area and pore volume of ~20 and ~35%, respectively. This is due to the increase in nonbridging oxygens and mismatch of thermal expansion coefficient which …
Analysis Of Electromagnetic Vortex Beams Using Modified Dynamic Mode Decomposition In Spatial Angular Domain, Yanming Zhang, Menglin L.N. Chen, Li (Lijun) Jun Jiang
Analysis Of Electromagnetic Vortex Beams Using Modified Dynamic Mode Decomposition In Spatial Angular Domain, Yanming Zhang, Menglin L.N. Chen, Li (Lijun) Jun Jiang
Electrical and Computer Engineering Faculty Research & Creative Works
The orbital angular momentum (OAM) modes of electromagnetic (EM) beams are utilized for multiplexing in communication systems, where each OAM mode is encoded with data. The OAM index, or the so-called topological charge, identifies each OAM mode. Recently, the amplitude of OAM mode has also been used as another modulation format. Therefore, accurate extraction of not only the OAM index but also the corresponding amplitude is required. In this paper, a modified dynamic mode decomposition (DMD) algorithm is proposed to analyze the OAM modes. We show that accurate topological charges and high-resolution amplitude patterns of both single OAM mode and …
Why Does This Entity Matter? Support Passage Retrieval For Entity Retrieval, Shubham Chatterjee, Laura Dietz
Why Does This Entity Matter? Support Passage Retrieval For Entity Retrieval, Shubham Chatterjee, Laura Dietz
Computer Science Faculty Research & Creative Works
Our goal is to complement an entity ranking with human-readable explanations of how those retrieved entities are connected to the information need. While related to the problem of support passage retrieval, in this paper, we explore two underutilized indicators of relevance: contextual entities and entity salience. The effectiveness of the indicators is studied within a supervised learning-to-rank framework on a dataset from TREC Complex Answer Retrieval. We find that salience is a useful indicator, but it is often not applicable. In contrast, although performance improvements are obtained by using contextual entities, using contextual words still outperforms contextual entities.
Sequencing Heparan Sulfate Using Hilic Lc-Netd-Ms/Ms, Jiandong Wu, Juan Wei, Pradeep Chopra, Geert Jan Boons, Cheng Lin, Joseph Zaia
Sequencing Heparan Sulfate Using Hilic Lc-Netd-Ms/Ms, Jiandong Wu, Juan Wei, Pradeep Chopra, Geert Jan Boons, Cheng Lin, Joseph Zaia
Chemical and Biochemical Engineering Faculty Research & Creative Works
Heparan Sulfate (HS) Mediates a Wide Range of Protein Binding Interactions Key to Normal and Pathological Physiology. Though Liquid Chromatography Coupled with Mass Spectrometry (LC-MS) based Disaccharide Composition Analysis is Able to Profile Changes in HS Composition, the Heterogeneity of Modifications and the Labile Sulfate Group Present Major Challenges for Liquid Chromatography Tandem Mass Spectrometry (LC-MS/MS) Sequencing of the HS Oligosaccharides that Represent Protein Binding Determinants. Here, We Report Online LC-MS/MS Sequencing of HS Oligosaccharides using Hydrophilic Interaction Liquid Chromatography (HILIC) and Negative Electron Transfer Dissociation (NETD). a Series of Synthetic HS Oligosaccharides Varying in Chain Length (Tetramers and Hexamers), …
Inter-Comparison Of Reflectivity Measurements Between Gpm Dpr And Nexrad Radars, Munsung Keem, Bong Chul Seo, Witold F. Krajewski, K. Robert Morris
Inter-Comparison Of Reflectivity Measurements Between Gpm Dpr And Nexrad Radars, Munsung Keem, Bong Chul Seo, Witold F. Krajewski, K. Robert Morris
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
This study demonstrates the potential use of the NASA's Global Precipitation Measurement (GPM) Dual-frequency Precipitation Radar (DPR) to examine ground radar (GR) miscalibration and other uncertainty sources (e.g., partial beam blockage). We acquired the GPM Ground Validation System Validation Network reflectivity matchups between the DPR and three GRs (two in Iowa and one in South Dakota) for 2014–2017. We then refined the matching parameters (e.g., time separation) to reduce uncertainty in the matchup samples by analyzing the sensitivity of the matchup statistical properties to changes in these parameters. To reconcile the same observables (i.e., reflectivity) with different observational properties among …