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Articles 31 - 53 of 53
Full-Text Articles in Physical Sciences and Mathematics
A Mild Dyssynchronous Contraction Pattern Detected By Spect Myocardial Perfusion Imaging Predicts Super-Response To Cardiac Resynchronization Therapy, Xiao Hu, Zhiyong Qian, Fengwei Zou, Siyuan Xue, Xinwei Zhang, Yao Wang, Xiaofeng Hou, Weihua Zhou, Jiangang Zou
A Mild Dyssynchronous Contraction Pattern Detected By Spect Myocardial Perfusion Imaging Predicts Super-Response To Cardiac Resynchronization Therapy, Xiao Hu, Zhiyong Qian, Fengwei Zou, Siyuan Xue, Xinwei Zhang, Yao Wang, Xiaofeng Hou, Weihua Zhou, Jiangang Zou
Michigan Tech Publications
Background: Using single photon emission computed tomography myocardial perfusion imaging (SPECT MPI) with phase analysis (PA), we aimed to identify the predictive value of a new contraction pattern in cardiac resynchronization therapy (CRT) response. Methods: Left ventricular mechanical dyssynchrony (LVMD) was evaluated using SPECT MPI with PA in non-ischemic dilated cardiomyopathy (DCM) patients with left bundle branch block (LBBB) indicated for CRT. CRT super-response was defined as LV ejection fraction (EF) ≥50% or an absolute increase of LVEF >15%. The LV contraction was categorized as the mild dyssynchronous pattern when the phase standard deviation (PSD) ≤ 40.3° and phase histogram …
Integrating Deep Learning And Hydrodynamic Modeling To Improve The Great Lakes Forecast, Pengfei Xue, Aditya Wagh, Gangfeng Ma, Yilin Wang, Yongchao Yang, Tao Liu, Chenfu Huang
Integrating Deep Learning And Hydrodynamic Modeling To Improve The Great Lakes Forecast, Pengfei Xue, Aditya Wagh, Gangfeng Ma, Yilin Wang, Yongchao Yang, Tao Liu, Chenfu Huang
Michigan Tech Publications
The Laurentian Great Lakes, one of the world’s largest surface freshwater systems, pose a modeling challenge in seasonal forecast and climate projection. While physics-based hydrodynamic modeling is a fundamental approach, improving the forecast accuracy remains critical. In recent years, machine learning (ML) has quickly emerged in geoscience applications, but its application to the Great Lakes hydrodynamic prediction is still in its early stages. This work is the first one to explore a deep learning approach to predicting spatiotemporal distributions of the lake surface temperature (LST) in the Great Lakes. Our study shows that the Long Short-Term Memory (LSTM) neural network, …
Deep-Learning-Incorporated Augmented Reality Application For Engineering Lab Training, John Estrada, Sidike Paheding, Xiaoli Yang, Quamar Niyaz
Deep-Learning-Incorporated Augmented Reality Application For Engineering Lab Training, John Estrada, Sidike Paheding, Xiaoli Yang, Quamar Niyaz
Michigan Tech Publications
Deep learning (DL) algorithms have achieved significantly high performance in object detection tasks. At the same time, augmented reality (AR) techniques are transforming the ways that we work and connect with people. With the increasing popularity of online and hybrid learning, we propose a new framework for improving students’ learning experiences with electrical engineering lab equipment by incorporating the abovementioned technologies. The DL powered automatic object detection component integrated into the AR application is designed to recognize equipment such as multimeter, oscilloscope, wave generator, and power supply. A deep neural network model, namely MobileNet-SSD v2, is implemented for equipment detection …
Black Carbon Aerosol Number And Mass Concentration Measurements By Picosecond Short-Range Elastic Backscatter Lidar, Romain Ceolato, Andrés E. Bedoya-Velásquez, Frédéric Fossard, Vincent Mouysset, Lucas Paulien, Sidonie Lefebvre, Claudio Mazzoleni, Christopher Sorensen, Matthew J. Berg, Jérôme Yon
Black Carbon Aerosol Number And Mass Concentration Measurements By Picosecond Short-Range Elastic Backscatter Lidar, Romain Ceolato, Andrés E. Bedoya-Velásquez, Frédéric Fossard, Vincent Mouysset, Lucas Paulien, Sidonie Lefebvre, Claudio Mazzoleni, Christopher Sorensen, Matthew J. Berg, Jérôme Yon
Michigan Tech Publications
Black carbon aerosol emissions are recognized as contributors to global warming and air pollution. There remains, however, a lack of techniques to remotely measure black carbon aerosol particles with high range and time resolution. This article presents a direct and contact-free remote technique to estimate the black carbon aerosol number and mass concentration at a few meters from the emission source. This is done using the Colibri instrument based on a novel technique, referred to here as Picosecond Short-Range Elastic Backscatter Lidar (PSR-EBL). To address the complexity of retrieving lidar products at short measurement ranges, we apply a forward inversion …
A Priori And A Posteriori Error Estimates For The Quad-Curl Eigenvalue Problem, Lixiu Wang, Qian Zhang, Jiguang Sun, Zhimin Zhang
A Priori And A Posteriori Error Estimates For The Quad-Curl Eigenvalue Problem, Lixiu Wang, Qian Zhang, Jiguang Sun, Zhimin Zhang
Michigan Tech Publications
In this paper, we consider a priori and a posteriori error estimates of the H(curl2)-conforming finite element when solving the quad-curl eigenvalue problem. An a priori estimate of eigenvalues with convergence order 2(s − 1) is obtained if the corresponding eigenvector u ∈ Hs − 1(Ω) and ∇ × u ∈ Hs(Ω). For the a posteriori estimate, by analyzing the associated source problem, we obtain lower and upper bounds for the errors of eigenvectors in the energy norm and upper bounds for the errors of eigenvalues. Numerical examples are presented for validation.
A Few-Shot Learning Model Based On A Triplet Network For The Prediction Of Energy Coincident Peak Days, Jinxiang Liu, Laura Brown
A Few-Shot Learning Model Based On A Triplet Network For The Prediction Of Energy Coincident Peak Days, Jinxiang Liu, Laura Brown
Michigan Tech Publications
In an electricity system, a coincident peak (CP) is defined as the highest daily power demand in a year, which plays an important role in keeping the balance between power supply and its demand. Advanced information about the time of coincident peaks would be helpful for both utility companies and their customers. This work addresses the prediction of the five coincident peak days (5CP) in a year. We present a few-shot learning model to classify a day as a 5CP day or a non-5CP day 24-hours ahead. A triplet network is implemented for the 2-way-5-shot classifications on six different historical …
A Priori And A Posteriori Error Estimates For The Quad-Curl Eigenvalue Problem, Lixiu Wang, Qian Zhang, Jiguang Sun, Zhimin Zhang
A Priori And A Posteriori Error Estimates For The Quad-Curl Eigenvalue Problem, Lixiu Wang, Qian Zhang, Jiguang Sun, Zhimin Zhang
Michigan Tech Publications
In this paper, we consider a priori and a posteriori error estimates of the H(curl2)-conforming finite element when solving the quad-curl eigenvalue problem. An a priori estimate of eigenvalues with convergence order 2(s 1) is obtained if the corresponding eigenvector u a Hs 1(Ω) and-u a Hs(Ω). For the a posteriori estimate, by analyzing the associated source problem, we obtain lower and upper bounds for the errors of eigenvectors in the energy norm and upper bounds for the errors of eigenvalues. Numerical examples are presented for validation.
Large-Eddy Simulations Of A Convection Cloud Chamber: Sensitivity To Bin Microphysics And Advection, Fan Yang, Mikhail Ovchinnikov, Subin Thomas, Alexander Khain, Robert Mcgraw, Raymond Shaw, Andrew M. Vogelmann
Large-Eddy Simulations Of A Convection Cloud Chamber: Sensitivity To Bin Microphysics And Advection, Fan Yang, Mikhail Ovchinnikov, Subin Thomas, Alexander Khain, Robert Mcgraw, Raymond Shaw, Andrew M. Vogelmann
Michigan Tech Publications
Bin microphysics schemes are useful tools for cloud simulations and are often considered to provide a benchmark for model intercomparison. However, they may experience issues with numerical diffusion, which are not well quantified, and the transport of hydrometeors depends on the choice of advection scheme, which can also change cloud simulation results. Here, an atmospheric large-eddy simulation model is adapted to simulate a statistically steady-state cloud in a convection cloud chamber under well-constrained conditions. Two bin microphysics schemes, a spectral bin method and the method of moments, as well as several advection methods for the transport of the microphysical variables …
A Computationally Efficient Clustering Linear Combination Approach To Jointly Analyze Multiple Phenotypes For Gwas, Meida Wang, Shuanglin Zhang, Qiuying Sha
A Computationally Efficient Clustering Linear Combination Approach To Jointly Analyze Multiple Phenotypes For Gwas, Meida Wang, Shuanglin Zhang, Qiuying Sha
Michigan Tech Publications
There has been an increasing interest in joint analysis of multiple phenotypes in genome-wide association studies (GWAS) because jointly analyzing multiple phenotypes may increase statistical power to detect genetic variants associated with complex diseases or traits. Recently, many statistical methods have been developed for joint analysis of multiple phenotypes in genetic association studies, including the Clustering Linear Combination (CLC) method. The CLC method works particularly well with phenotypes that have natural groupings, but due to the unknown number of clusters for a given data, the final test statistic of CLC method is the minimum p-value among all p-values of the …
Synthesis And Characterization Of Alkyne-Functionalized Photo-Cross-Linkable Polyesters, Warrick Ma, Xiaochu Ding, Ying Chen, Yadong Wang
Synthesis And Characterization Of Alkyne-Functionalized Photo-Cross-Linkable Polyesters, Warrick Ma, Xiaochu Ding, Ying Chen, Yadong Wang
Michigan Tech Publications
An alkyne-functionalized elastomer derived from sebacic acid, 1,3-propanediol, and alkyne-functionalized serinol is synthesized via melt condensation. A low-power UV lamp triggers the cross-linking rapidly via thiol-yne click chemistry. The cross-linking behavior is studied by photorheology and NMR spectroscopy. The resultant elastomer possesses mechanical properties similar to those of human soft tissues and exhibits in vitro degradability and good cytocompatibility.
Einstein-Roscoe Regression For The Slag Viscosity Prediction Problem In Steelmaking, Hiroto Saigo, Dukka Kc, Noritaka Saito
Einstein-Roscoe Regression For The Slag Viscosity Prediction Problem In Steelmaking, Hiroto Saigo, Dukka Kc, Noritaka Saito
Michigan Tech Publications
In classical machine learning, regressors are trained without attempting to gain insight into the mechanism connecting inputs and outputs. Natural sciences, however, are interested in finding a robust interpretable function for the target phenomenon, that can return predictions even outside of the training domains. This paper focuses on viscosity prediction problem in steelmaking, and proposes Einstein-Roscoe regression (ERR), which learns the coefficients of the Einstein-Roscoe equation, and is able to extrapolate to unseen domains. Besides, it is often the case in the natural sciences that some measurements are unavailable or expensive than the others due to physical constraints. To this …
Long-Term Spectra Of The Blazars Mrk 421 And Mrk 501 At Tev Energies Seen By Hawc, A. Albert, R. Alfaro, C. Alvarez, J. R.Angeles Camacho, J. C. Arteaga-Velázquez, K. P. Arunbabu, D. Huang, P. Huntemeyer, X. Wang, Et. Al.
Long-Term Spectra Of The Blazars Mrk 421 And Mrk 501 At Tev Energies Seen By Hawc, A. Albert, R. Alfaro, C. Alvarez, J. R.Angeles Camacho, J. C. Arteaga-Velázquez, K. P. Arunbabu, D. Huang, P. Huntemeyer, X. Wang, Et. Al.
Michigan Tech Publications
The High Altitude Water Cherenkov (HAWC) Gamma-Ray Observatory surveys the very high-energy sky in the 300 GeV to >100 TeV energy range. HAWC has detected two blazars above 11σ, Markarian 421 (Mrk 421) and Markarian 501 (Mrk 501). The observations are comprised of data taken in the period between 2015 June and 2018 July, resulting in ∼1038 days of exposure. In this work, we report the time-averaged spectral analyses for both sources, above 0.5 TeV. Taking into account the flux attenuation due to the extragalactic background light, the intrinsic spectrum of Mrk 421 is described by a power law with …
Hawc Study Of The Ultra-High-Energy Spectrum Of Mgro J1908+06, A. Albert, R. Alfaro, C. Alvarez, J. D. Álvarez, J. R.Angeles Camacho, J. C. Arteaga-Velázquez, R. Babu, D. Huang, P. Hüntemeyer, R. Turner, X. Wang, Et. Al.
Hawc Study Of The Ultra-High-Energy Spectrum Of Mgro J1908+06, A. Albert, R. Alfaro, C. Alvarez, J. D. Álvarez, J. R.Angeles Camacho, J. C. Arteaga-Velázquez, R. Babu, D. Huang, P. Hüntemeyer, R. Turner, X. Wang, Et. Al.
Michigan Tech Publications
We report TeV gamma-ray observations of the ultra-high-energy source MGRO J1908+06 using data from the High Altitude Water Cherenkov Observatory. This source is one of the highest-energy known gamma-ray sources, with emission extending past 200 TeV. Modeling suggests that the bulk of the TeV gamma-ray emission is leptonic in nature, driven by the energetic radio-faint pulsar PSR J1907+0602. Depending on what assumptions are included in the model, a hadronic component may also be allowed. Using the results of the modeling, we discuss implications for detection prospects by multi-messenger campaigns.
Determination Of Optical Density (Od) Of Oligodeoxynucleotide From Hplc Peak Area, Komal Chillar, Yipeng Yin, Dhananjani Eriyagama, Shiyue Fang
Determination Of Optical Density (Od) Of Oligodeoxynucleotide From Hplc Peak Area, Komal Chillar, Yipeng Yin, Dhananjani Eriyagama, Shiyue Fang
Michigan Tech Publications
Oligodeoxynucleotides (ODNs) are typically purified and analysed with HPLC equipped with a UV-Vis detector. Quantities of ODNs are usually determined using a UV-Vis spectrometer separately after HPLC, and are reported as optical density at 260 nm (OD260). Here, we describe a method for direct determination of OD260 of ODNs using the area of the peaks in HPLC profiles.
Gene-Based Association Tests Using Gwas Summary Statistics And Incorporating Eqtl, Xuewei Cao, Xuexia Wang, Shuanglin Zhang, Qiuying Sha
Gene-Based Association Tests Using Gwas Summary Statistics And Incorporating Eqtl, Xuewei Cao, Xuexia Wang, Shuanglin Zhang, Qiuying Sha
Michigan Tech Publications
Although genome-wide association studies (GWAS) have been successfully applied to a variety of complex diseases and identified many genetic variants underlying complex diseases via single marker tests, there is still a considerable heritability of complex diseases that could not be explained by GWAS. One alternative approach to overcome the missing heritability caused by genetic heterogeneity is gene-based analysis, which considers the aggregate effects of multiple genetic variants in a single test. Another alternative approach is transcriptome-wide association study (TWAS). TWAS aggregates genomic information into functionally relevant units that map to genes and their expression. TWAS is not only powerful, but …
Light Curve Test Of Grb 200716c As A Gravitationally Lensed Echo, Oindabi Mukherjee, Robert J. Nemiroff
Light Curve Test Of Grb 200716c As A Gravitationally Lensed Echo, Oindabi Mukherjee, Robert J. Nemiroff
Michigan Tech Publications
A gravitational lens can imprint distinct features on the light curve of a gamma-ray burst (GRB). Most prominently, when creating multiple images, the light curves for all images should be identical, within a scale factor in amplitude. For GRB images that are bright enough to have significant counts in multiple time bins, the similarity of the light curves can be assessed with a straightforward χ2 test. In response to a recent claim that the two pulses in GRB 200716C are lensed images of the same pulse, such a χ2 test was computed. The test indicated that the likelihood …
Light Curve Test Of Grb 200716c As A Gravitationally Lensed Echo, Oindabi Mukherjee, Robert J. Nemiroff
Light Curve Test Of Grb 200716c As A Gravitationally Lensed Echo, Oindabi Mukherjee, Robert J. Nemiroff
Michigan Tech Publications
A gravitational lens can imprint distinct features on the light curve of a gamma-ray burst (GRB). Most prominently, when creating multiple images, the light curves for all images should be identical, within a scale factor in amplitude. For GRB images that are bright enough to have significant counts in multiple time bins, the similarity of the light curves can be assessed with a straightforward χ2 test. In response to a recent claim that the two pulses in GRB 200716C are lensed images of the same pulse, such a χ2 test was computed. The test indicated that the likelihood …
Simian Immunodeficiency Virus Infection Mediated Changes In Jejunum And Peripheral Sars-Cov-2 Receptor Ace2 And Associated Proteins Or Genes In Rhesus Macaques, Nongthombam Boby, Xuewei Cao, Kelsey Williams, Shiva Kumar Goud Gadila, Monica N. Shroyer, Peter J. Didier, Sudesh K. Srivastav, Arpita Das, Kate Baker, Qiuying Sha, Bapi Pahar
Simian Immunodeficiency Virus Infection Mediated Changes In Jejunum And Peripheral Sars-Cov-2 Receptor Ace2 And Associated Proteins Or Genes In Rhesus Macaques, Nongthombam Boby, Xuewei Cao, Kelsey Williams, Shiva Kumar Goud Gadila, Monica N. Shroyer, Peter J. Didier, Sudesh K. Srivastav, Arpita Das, Kate Baker, Qiuying Sha, Bapi Pahar
Michigan Tech Publications
Angiotensin converting enzyme-2 (ACE2) and associated proteins play a pivotal role in various physiological and pathological events, such as immune activation, inflammation, gut barrier maintenance, intestinal stem cell proliferation, and apoptosis. Although many of these clinical events are quite significant in SIV/HIV infection, expression profiling of these proteins has not been well reported. Considering the different pathological consequences in the gut after HIV infection, we hypothesized that the expression of ACE2 and associated proteins of the Renin-angiotensin system (RAS) could be compromised after SIV/HIV infection. We quantified the gene expression of ACE2 as well as AGTR1/2, ADAM17, and TMPRSS2, and …
Jamming Detection And Classification In Ofdm-Based Uavs Via Feature- And Spectrogram-Tailored Machine Learning, Y. Li, J. Pawlak, J. Price, K. Al Shamaileh, Q. Niyaz, S. Paheding, V. Devabhaktuni
Jamming Detection And Classification In Ofdm-Based Uavs Via Feature- And Spectrogram-Tailored Machine Learning, Y. Li, J. Pawlak, J. Price, K. Al Shamaileh, Q. Niyaz, S. Paheding, V. Devabhaktuni
Michigan Tech Publications
In this paper, a machine learning (ML) approach is proposed to detect and classify jamming attacks against orthogonal frequency division multiplexing (OFDM) receivers with applications to unmanned aerial vehicles (UAVs). Using software-defined radio (SDR), four types of jamming attacks; namely, barrage, protocol-aware, single-tone, and successive-pulse are launched and investigated. Each type is qualitatively evaluated considering jamming range, launch complexity, and attack severity. Then, a systematic testing procedure is established by placing an SDR in the vicinity of a UAV (i.e., drone) to extract radiometric features before and after a jamming attack is launched. Numeric features that include signal-to-noise ratio (SNR), …
Organic And Elemental Carbon In The Urban Background In An Eastern Mediterranean City, Tareq Hussein, Xinyang Li, Zaid Bakri, Andres Alastuey, Sharif Arar, Afnan Al-Hunaiti, Mar Viana, Tuukka Petäjä
Organic And Elemental Carbon In The Urban Background In An Eastern Mediterranean City, Tareq Hussein, Xinyang Li, Zaid Bakri, Andres Alastuey, Sharif Arar, Afnan Al-Hunaiti, Mar Viana, Tuukka Petäjä
Michigan Tech Publications
The Mediterranean region is an important area for air pollution as it is the crossroads between three continents; therefore, the concentrations of atmospheric aerosol particles are influenced by emissions from Africa, Asia, and Europe. Here we concentrate on an eleven-month time series of the ambient concentration of organic carbon (OC) and elemental carbon (EC) between May 2018– March 2019 in Amman, Jordan. Such a dataset is unique in Jordan. The results show that the OC and EC annual mean concentrations in PM2.5 samples were 5.9 ± 2.8 µg m–3 and 1.7 ± 1.1 µg m–3, respectively. It was found that …
Testing Effects Of Lorentz Invariance Violation In The Propagation Of Astroparticles With The Pierre Auger Observatory, P. Abreu, M. Aglietta, J. M. Albury, I. Allekotte, K. Almeida Cheminant, A. Almela, B. Fick, D. Nitz, A. Puyleart, Et. Al.
Testing Effects Of Lorentz Invariance Violation In The Propagation Of Astroparticles With The Pierre Auger Observatory, P. Abreu, M. Aglietta, J. M. Albury, I. Allekotte, K. Almeida Cheminant, A. Almela, B. Fick, D. Nitz, A. Puyleart, Et. Al.
Michigan Tech Publications
Lorentz invariance violation (LIV) is often described by dispersion relations of the form E i2 = m i2+p i2+δi,n E 2+n with delta different based on particle type i, with energy E, momentum p and rest mass m. Kinematics and energy thresholds of interactions are modified once the LIV terms become comparable to the squared masses of the particles involved. Thus, the strongest constraints on the LIV coefficients δi,n tend to come from the highest energies. At sufficiently high energies, photons produced by cosmic ray interactions as they propagate through the Universe could be subluminal and unattenuated over cosmological distances. …
Differentially Private Fractional Frequency Moments Estimation With Polylogarithmic Space, Lun Wang, Iosif Pinelis, Dawn Song
Differentially Private Fractional Frequency Moments Estimation With Polylogarithmic Space, Lun Wang, Iosif Pinelis, Dawn Song
Michigan Tech Publications
We prove that Fp sketch, a well-celebrated streaming algorithm for frequency moments estimation, is differentially private as is when p ∈ (0, 1]. Fp sketch uses only polylogarithmic space, exponentially better than existing DP baselines and only worse than the optimal non-private baseline by a logarithmic factor. The evaluation shows that Fp sketch can achieve reasonable accuracy with differential privacy guarantee. The evaluation code is included in the supplementary material.
Emissions, Shawn Urbanski, Susan O'Neill, Amara L. Holder, Sarah Green, Rick L. Graw
Emissions, Shawn Urbanski, Susan O'Neill, Amara L. Holder, Sarah Green, Rick L. Graw
Michigan Tech Publications
This chapter assesses the current state of the science regarding the composition, intensity, and drivers of wildland fire emissions in the USA and Canada. Globally and in the USA wildland fires are a major source of gases and aerosols which have significant air quality impacts and climate interactions. Wildland fire smoke can trigger severe pollution episodes with substantial effects on public health. Fire emissions can degrade air quality at considerable distances downwind, hampering efforts by air regulators to meet air standards. Fires are a major global source of aerosols which affect the climate system by absorbing and scattering radiation and …