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A New Interpretation Of The √7×√7 R19.1° Structure For P Adsorbed On A Ni(111) Surface, Elizabeth Barrow, Grant S. Seuser, Hiroko Ariga-Miwa, Donna A. Chen, Jochen A. Lauterbach, Kiyotaka Asakura
A New Interpretation Of The √7×√7 R19.1° Structure For P Adsorbed On A Ni(111) Surface, Elizabeth Barrow, Grant S. Seuser, Hiroko Ariga-Miwa, Donna A. Chen, Jochen A. Lauterbach, Kiyotaka Asakura
Faculty Publications
We have studied P adsorption on Ni(111), a system which shows complex adsorbate structures. We determined the phase diagram of the surface P adsorbed on Ni(111). At low coverage, amorphous P was observed. At temperatures between 373 and 673 K and coverages above 0.1 monolayer, we found a √7×√7 R19.1° structure, but above 673 K, other complex structures were created. These structures seemed to correlate with each other and we reinterpret a √7×√7 R19.1° structure of P adsorbed on Ni(111) based on the similarities of these surface structures. The new rectangular structure for the √7×√7 19.1° is discussed in relation …
A New Interpretation Of The √7×√7 R19.1° Structure For P Adsorbed On A Ni(111) Surface, Elizabeth Barrow, Grant S. Seuser, Hiroko Ariga-Miwa, Donna A. Chen, Jochen A. Lauterbach, Kiyotaka Asakura
A New Interpretation Of The √7×√7 R19.1° Structure For P Adsorbed On A Ni(111) Surface, Elizabeth Barrow, Grant S. Seuser, Hiroko Ariga-Miwa, Donna A. Chen, Jochen A. Lauterbach, Kiyotaka Asakura
Faculty Publications
We have studied P adsorption on Ni(111), a system which shows complex adsorbate structures. We determined the phase diagram of the surface P adsorbed on Ni(111). At low coverage, amorphous P was observed. At temperatures between 373 and 673 K and coverages above 0.1 monolayer, we found a √7×√7 R19.1° structure, but above 673 K, other complex structures were created. These structures seemed to correlate with each other and we reinterpret a √7×√7 R19.1° structure of P adsorbed on Ni(111) based on the similarities of these surface structures. The new rectangular structure for the √7×√7 19.1° is discussed in relation …
Towards Overcoming The Curse Of Dimensionality: The Third-Order Adjoint Method For Sensitivity Analysis Of Response-Coupled Linear Forward/Adjoint Systems, Uncertainty Quantification And Predictive Modeling With Applications To Nuclear Energy Systems, Dan Gabriel Cacuci
Faculty Publications
This work presents the Third-Order Adjoint Sensitivity Analysis Methodology (3rd-ASAM) for response-coupled forward and adjoint linear systems. The 3rd-ASAM enables the efficient computation of the exact expressions of the 3rd-order functional derivatives (“sensitivities”) of a general system response, which depends on both the forward and adjoint state functions, with respect to all of the parameters underlying the respective forward and adjoint systems. Such responses are often encountered when representing mathematically detector responses and reaction rates in reactor physics problems. The 3rd-ASAM extends the 2nd-ASAM in the quest to overcome the “curse of dimensionality” in sensitivity analysis, uncertainty quantification and predictive …
Towards Overcoming The Curse Of Dimensionality: The Third-Order Adjoint Method For Sensitivity Analysis Of Response-Coupled Linear Forward/Adjoint Systems, With Applications To Uncertainty Quantification And Predictive Modeling, Dan Gabriel Cacuci
Faculty Publications
This work presents the Third-Order Adjoint Sensitivity Analysis Methodology (3rd-ASAM) for response-coupled forward and adjoint linear systems. The 3rd-ASAM enables the efficient computation of the exact expressions of the 3rd-order functional derivatives ("sensitivities") of a general system response, which depends on both the forward and adjoint state functions, with respect to all of the parameters underlying the respective forward and adjoint systems. Such responses are often encountered when representing mathematically detector responses and reaction rates in reactor physics problems. The 3rd-ASAM extends the 2nd-ASAM in the quest to overcome the "curse of dimensionality" in sensitivity analysis, uncertainty quantification and predictive …
Comprehensive Second-Order Adjoint Sensitivity Analysis Methodology (2nd-Asam) Applied To A Subcritical Experimental Reactor Physics Benchmark: I. Effects Of Imprecisely Known Microscopic Total And Capture Cross Sections, Daniel Gabriel Cacuci, Ruixian Fang, Jeffrey A. Favorite
Comprehensive Second-Order Adjoint Sensitivity Analysis Methodology (2nd-Asam) Applied To A Subcritical Experimental Reactor Physics Benchmark: I. Effects Of Imprecisely Known Microscopic Total And Capture Cross Sections, Daniel Gabriel Cacuci, Ruixian Fang, Jeffrey A. Favorite
Faculty Publications
The subcritical polyethylene-reflected plutonium (PERP) metal fundamental physics benchmark, which is included in the Nuclear Energy Agency (NEA) International Criticality Safety Benchmark Evaluation Project (ICSBEP) Handbook, has been selected to serve as a paradigm illustrative reactor physics system for the application of the Second-Order Adjoint Sensitivity Analysis Methodology (2nd-ASAM) that was developed by Cacuci. The 2nd-ASAM enables the exhaustive deterministic computation of the exact values of the 1st-order and 2nd-order sensitivities of a system response to the parameters underlying the respective system. The PERP benchmark is numerically modeled in this work by using the deterministic multigroup neutron transport equation discretized …
Gasification Of Pelletized Corn Residues With Oxygen Enriched Air And Steam, Poramate Sittisun, Nakorn Tippayawong, Sirivatch Shimpalee
Gasification Of Pelletized Corn Residues With Oxygen Enriched Air And Steam, Poramate Sittisun, Nakorn Tippayawong, Sirivatch Shimpalee
Faculty Publications
This work studied generation of producer gas using oxygen-enriched air and steam mixture as gasifying medium. Corn residues consisting of cobs and stover were used as biomass feedstock. Both corn residues were pelletized and gasified separately with normal air, oxygen enriched air and steam mixture in a fixed bed reactor. Effects of oxygen concentration in enriched air (21-50%), equivalence ratio (0.15-0.35), and steam to biomass ratio (0-0.8) on the yield of product gas, the combustible gas composition such as H2, CO, and CH4, the lower heating value (LHV), and the gasification efficiency were investigated. It was found that the decrease …
Comprehensive Second-Order Adjoint Sensitivity Analysis Methodology (2nd-Asam) Applied To A Subcritical Experimental Reactor Physics Benchmark: Ii. Effects Of Imprecisely Known Microscopic Scattering Cross Sections, Daniel Gabriel Cacuci, Ruixian Fang
Comprehensive Second-Order Adjoint Sensitivity Analysis Methodology (2nd-Asam) Applied To A Subcritical Experimental Reactor Physics Benchmark: Ii. Effects Of Imprecisely Known Microscopic Scattering Cross Sections, Daniel Gabriel Cacuci, Ruixian Fang
Faculty Publications
This work continues the presentation commenced in Part I of the second-order sensitivity analysis of nuclear data of a polyethylene-reflected plutonium (PERP) benchmark using the Second-Order Adjoint Sensitivity Analysis Methodology (2nd-ASAM). This work reports the results of the computations of the first- and second-order sensitivities of this benchmark's computed leakage response with respect to the benchmark's 21,600 parameters underlying the computed group-averaged isotopic scattering cross sections. The numerical results obtained for the 21,600 first-order relative sensitivities indicate that the majority of these were small, the largest having relative values of O (10(-2)). Furthermore, the vast majority of the (21600)(2) second-order …
Comprehensive Second-Order Adjoint Sensitivity Analysis Methodology (2nd-Asam) Applied To A Subcritical Experimental Reactor Physics Benchmark: Iii. Effects Of Imprecisely Known Microscopic Fission Cross Sections And Average Number Of Neutrons Per Fission, Dan Gaberiel Cacuci, Ruixian Fang, J. A. Favorite, M. C. Badea, F. Di Rocco
Comprehensive Second-Order Adjoint Sensitivity Analysis Methodology (2nd-Asam) Applied To A Subcritical Experimental Reactor Physics Benchmark: Iii. Effects Of Imprecisely Known Microscopic Fission Cross Sections And Average Number Of Neutrons Per Fission, Dan Gaberiel Cacuci, Ruixian Fang, J. A. Favorite, M. C. Badea, F. Di Rocco
Faculty Publications
The Second-Order Adjoint Sensitivity Analysis Methodology (2nd-ASAM) is applied to compute the first-order and second-order sensitivities of the leakage response of a polyethylene-reflected plutonium (PERP) experimental system with respect to the following nuclear data: Group-averaged isotopic microscopic fission cross sections, mixed fission/total, fission/scattering cross sections, average number of neutrons per fission (), mixed /total cross sections, /scattering cross sections, and /fission cross sections. The numerical results obtained indicate that the 1st-order relative sensitivities for these nuclear data are smaller than the 1st-order sensitivities of the PERP leakage response with respect to the total cross sections but are larger than those …
First Principles Investigation Of Anomalous Pressure-Dependent Thermal Conductivity Of Chalcopyrites, Loay Flalfy, Denis Music, Ming Hu
First Principles Investigation Of Anomalous Pressure-Dependent Thermal Conductivity Of Chalcopyrites, Loay Flalfy, Denis Music, Ming Hu
Faculty Publications
The effect of compression on the thermal conductivity of CuGaS2, CuInS2, CuInTe2, and AgInTe2 chalcopyrites (space group I-42d) was studied at 300 K using phonon Boltzmann transport equation (BTE) calculations. The thermal conductivity was evaluated by solving the BTE with harmonic and third-order interatomic force constants. The thermal conductivity of CuGaS2 increases with pressure, which is a common behavior. Striking differences occur for the other three compounds. CuInTe2 and AgInTe2 exhibit a drop in the thermal conductivity upon increasing pressure, which is anomalous. AgInTe2 reaches a very low thermal conductivity of 0.2 W·m−1 ·K −1 at 2.6 GPa, being beneficial …
Upcycling Single-Use Polyethylene Into High-Quality Liquid Products, Gokhan Celik, Robert M. Kennedy, Ryan A. Hackler, Magali Ferrandon, Akalanka Tennakoon, Smita Patnaik, Anne M. Lapointe, Salai Ammal, Andreas Heyden, Frédéric A. Perras, Marek Pruski, Susannah L. Scott, Kenneth R. Poeppelmeier, Aaron D. Sadow, Massimiliano Delferro
Upcycling Single-Use Polyethylene Into High-Quality Liquid Products, Gokhan Celik, Robert M. Kennedy, Ryan A. Hackler, Magali Ferrandon, Akalanka Tennakoon, Smita Patnaik, Anne M. Lapointe, Salai Ammal, Andreas Heyden, Frédéric A. Perras, Marek Pruski, Susannah L. Scott, Kenneth R. Poeppelmeier, Aaron D. Sadow, Massimiliano Delferro
Faculty Publications
Our civilization relies on synthetic polymers for all aspects of modern life; yet, inefficient recycling and extremely slow environmental degradation of plastics are causing increasing concern about their widespread use. After a single use, many of these materials are currently treated as waste, underutilizing their inherent chemical and energy value. In this study, energy-rich polyethylene (PE) macromolecules are catalytically transformed into value-added products by hydrogenolysis using well-dispersed Pt nanoparticles (NPs) supported on SrTiO3 perovskite nanocuboids by atomic layer deposition. Pt/SrTiO3 completely converts PE (Mn = 8000− 158,000 Da) or a single-use plastic bag (Mn = 31,000 Da) into high-quality liquid …
Ligaos Is A Fast Li-Ion Conductor: A First-Principles Prediction, Xueling Lei, Wenjun Wu, Bo Xu, Chuying Ouyang, Kevin Huang
Ligaos Is A Fast Li-Ion Conductor: A First-Principles Prediction, Xueling Lei, Wenjun Wu, Bo Xu, Chuying Ouyang, Kevin Huang
Faculty Publications
Solid Li-ion conducting electrolytes are highly sought for all solid-state Li-batteries, which are considered the next-generation safe batteries. Here a systematic computational study on the intrinsic transport properties of lithium gallium oxysulfide, LiGaOS (S. G. Pmc21), as a potential solid-state Li-ion electrolyte have been reported. The phonon dispersion spectrum analysis indicates that LiGaOS crystal structure is dynamically stable. The energy band structure and density of states calculations suggest that LiGaOS is an insulator with a wide indirect band gap of ∼5.44 eV. The CI-NEB calculations reveal that the “kick-off” collective migration via Li-interstitials is the dominant conduction mechanism …
Preparation Of Activated Biochar-Supported Magnetite Composite For Adsorption Of Polychlorinated Phenols From Aqueous Solutions, Byung-Moon Jun, Yejin Kim, Jonghun Han, Yeomin Yoon, Chang Min Park
Preparation Of Activated Biochar-Supported Magnetite Composite For Adsorption Of Polychlorinated Phenols From Aqueous Solutions, Byung-Moon Jun, Yejin Kim, Jonghun Han, Yeomin Yoon, Chang Min Park
Faculty Publications
For this study, we applied activated biochar (AB) and its composition with magnetite (AB-Fe3O4) as adsorbents for the removal of polychlorophenols in model wastewater. We comprehensively characterized these adsorbents and performed adsorption tests under several experimental parameters. Using FTIR, we confirmed successful synthesis of AB-Fe3O4 composite through cetrimonium bromide surfactant. We conducted adsorption tests using AB and AB-Fe3O4 to treat model wastewater containing polychlorophenols, such as 2,3,4,6-Tetrachlorophenol (TeCP), 2,4,6-Trichlorophenol (TCP), and 2,4-Dichlorophenol (DCP). Results of the isotherm and the kinetic experiments were well adapted to Freundlich’s isotherm model and the …
Fkrr-Mvsf: A Fuzzy Kernel Ridge Regression Model For Identifying Dna-Binding Proteins By Multi-View Sequence Features Via Chou's Five-Step Rule, Yi Zou, Yijie Ding, Jijun Tang, Fei Guo, Li Peng
Fkrr-Mvsf: A Fuzzy Kernel Ridge Regression Model For Identifying Dna-Binding Proteins By Multi-View Sequence Features Via Chou's Five-Step Rule, Yi Zou, Yijie Ding, Jijun Tang, Fei Guo, Li Peng
Faculty Publications
DNA-binding proteins play an important role in cell metabolism. In biological laboratories, the detection methods of DNA-binding proteins includes yeast one-hybrid methods, bacterial singles and X-ray crystallography methods and others, but these methods involve a lot of labor, material and time. In recent years, many computation-based approachs have been proposed to detect DNA-binding proteins. In this paper, a machine learning-based method, which is called the Fuzzy Kernel Ridge Regression model based on Multi-View Sequence Features (FKRR-MVSF), is proposed to identifying DNA-binding proteins. First of all, multi-view sequence features are extracted from protein sequences. Next, a Multiple Kernel Learning (MKL) algorithm …
Fkrr-Mvsf: A Fuzzy Kernel Ridge Regression Model For Identifying Dna-Binding Proteins By Multi-View Sequence Features Via Chou's Five-Step Rule, Yi Zou, Yije Ding, Jijun Tang, Fei Guo, Li Peng
Fkrr-Mvsf: A Fuzzy Kernel Ridge Regression Model For Identifying Dna-Binding Proteins By Multi-View Sequence Features Via Chou's Five-Step Rule, Yi Zou, Yije Ding, Jijun Tang, Fei Guo, Li Peng
Faculty Publications
DNA-binding proteins play an important role in cell metabolism. In biological laboratories, the detection methods of DNA-binding proteins includes yeast one-hybrid methods, bacterial singles and X-ray crystallography methods and others, but these methods involve a lot of labor, material and time. In recent years, many computation-based approachs have been proposed to detect DNA-binding proteins. In this paper, a machine learning-based method, which is called the Fuzzy Kernel Ridge Regression model based on Multi-View Sequence Features (FKRR-MVSF), is proposed to identifying DNA-binding proteins. First of all, multi-view sequence features are extracted from protein sequences. Next, a Multiple Kernel Learning (MKL) algorithm …
Limited Data Rolling Bearing Fault Diagnosis With Few-Shot Learning, Ansi Zhang, Shaobo Li, Yuxin Cui, Wanli Yang, Rongzhi Dong, Jianjun Hu
Limited Data Rolling Bearing Fault Diagnosis With Few-Shot Learning, Ansi Zhang, Shaobo Li, Yuxin Cui, Wanli Yang, Rongzhi Dong, Jianjun Hu
Faculty Publications
This paper focuses on bearing fault diagnosis with limited training data. A major challenge in fault diagnosis is the infeasibility of obtaining sufficient training samples for every fault type under all working conditions. Recently deep learning based fault diagnosis methods have achieved promising results. However, most of these methods require large amount of training data. In this study, we propose a deep neural network based few-shot learning approach for rolling bearing fault diagnosis with limited data. Our model is based on the siamese neural network, which learns by exploiting sample pairs of the same or different categories. Experimental results over …
A Review Of Text Corpus-Based Tourism Big Data Mining, Qin Lin, Shaobo Li, Sen Zhang, Jie Hu, Jianjun Hu
A Review Of Text Corpus-Based Tourism Big Data Mining, Qin Lin, Shaobo Li, Sen Zhang, Jie Hu, Jianjun Hu
Faculty Publications
With the massive growth of the Internet, text data has become one of the main formats of tourism big data. As an effective expression means of tourists’ opinions, text mining of such data has big potential to inspire innovations for tourism practitioners. In the past decade, a variety of text mining techniques have been proposed and applied to tourism analysis to develop tourism value analysis models, build tourism recommendation systems, create tourist profiles, and make policies for supervising tourism markets. The successes of these techniques have been further boosted by the progress of natural language processing (NLP), machine learning, and …
A Review Of Text Corpus-Based Tourism Big Data Mining, Qin Li, Shaobo Li, Sen Zhang, Jie Hu, Jianhun Hu
A Review Of Text Corpus-Based Tourism Big Data Mining, Qin Li, Shaobo Li, Sen Zhang, Jie Hu, Jianhun Hu
Faculty Publications
With the massive growth of the Internet, text data has become one of the main formats of tourism big data. As an effective expression means of tourists’ opinions, text mining of such data has big potential to inspire innovations for tourism practitioners. In the past decade, a variety of text mining techniques have been proposed and applied to tourism analysis to develop tourism value analysis models, build tourism recommendation systems, create tourist profiles, and make policies for supervising tourism markets. The successes of these techniques have been further boosted by the progress of natural language processing (NLP), machine learning, and …
Post-Treatment Of Nanofiltration Polyamide Membrane Through Alkali-Catalyzed Hydrolysis To Treat Dyes In Model Wastewater, Byung-Moon Jun, Yeomin Yoon, Chang Min Park
Post-Treatment Of Nanofiltration Polyamide Membrane Through Alkali-Catalyzed Hydrolysis To Treat Dyes In Model Wastewater, Byung-Moon Jun, Yeomin Yoon, Chang Min Park
Faculty Publications
This research focused on the influence of post-treatment using alkali-catalyzed hydrolysis with a full-aromatic nanofiltration (NF) polyamide membrane and its application to the efficient removal of selected dyes. The post-treated membranes were characterized through Fourier transform infrared spectroscopy, goniometry, and zeta-potential analysis to analyze the treatment-induced changes in the intrinsic properties of the membrane. Furthermore, the changes in permeability induced by the post-treatment were evaluated via the measurement of water flux, NaCl rejection, and molecular weight cutoff (MWCO) under different pH conditions and post-treatment times. Major changes induced by the post-treatment in terms of physicochemical properties were the enhancement of …
Communication: First-Principles Evaluation Of Alkali Ion Adsorption And Ion Exchange In Pure Silica Lta Zeolite (Vol 149, 131102, 2018), Vancho Kocevski, Benjamin D. Zeidman, Charles H. Henager Jr., Theodore M. Besmann
Communication: First-Principles Evaluation Of Alkali Ion Adsorption And Ion Exchange In Pure Silica Lta Zeolite (Vol 149, 131102, 2018), Vancho Kocevski, Benjamin D. Zeidman, Charles H. Henager Jr., Theodore M. Besmann
Faculty Publications
Using first-principles calculations, we studied the adsorption of alkali ions in pure silica Linde Type A (LTA) zeolite. The probability of adsorbing alkali ions from solution and the driving force for ion exchange between Na+ and other alkali ions at the different adsorption sites were analyzed. From the calculated ion exchange isotherms, we show that it is possible to exchange Na+ with K+ and Rb+ in water, but that is not the case for systems in a vacuum. We also demonstrate that a solvation model should be used for the accurate representation of ion exchange in an LTA and that …
Transverse Vibration Of Clamped-Pinned-Free Beam With Mass At Free End, Jonathan Hong, Jacob Dodson, Simon Laflamme, Austin Downey
Transverse Vibration Of Clamped-Pinned-Free Beam With Mass At Free End, Jonathan Hong, Jacob Dodson, Simon Laflamme, Austin Downey
Faculty Publications
Engineering systems undergoing extreme and harsh environments can often times experience rapid damaging effects. In order to minimize loss of economic investment and human lives, structural health monitoring (SHM) of these high-rate systems is being researched. An experimental testbed has been developed to validate SHM methods in a controllable and repeatable laboratory environment. This study applies the Euler-Bernoulli beam theory to this testbed to develop analytical solutions of the system. The transverse vibration of a clamped-pinned-free beam with a point mass at the free end is discussed in detail. Results are derived for varying pin locations and mass values. Eigenvalue …
Personalized Product Evaluation Based On Gra-Topsis And Kansei Engineering, Huafeng Quan, Shaobo Li, Hongjing Wei, Jianjun Hu
Personalized Product Evaluation Based On Gra-Topsis And Kansei Engineering, Huafeng Quan, Shaobo Li, Hongjing Wei, Jianjun Hu
Faculty Publications
With the improvement of human living standards, users’ requirements have changed from function to emotion. Helping users pick out the most suitable product based on their subjective requirements is of great importance for enterprises. This paper proposes a Kansei engineering-based grey relational analysis and techniques for order preference by similarity to ideal solution (KE-GAR-TOPSIS) method to make a subjective user personalized ranking of alternative products. The KE-GRA-TOPSIS method integrates five methods, including Kansei Engineering (KE), analytic hierarchy process (AHP), entropy, game theory, and grey relational analysis-TOPSIS (GRA-TOPSIS). First, an evaluation system is established by KE and AHP. Second, we define …
Using Big Data Analytics To Improve Hiv Medical Care Utilisation In South Carolina: A Study Protocol, Bankole Olatosi, Jiajia Zhang, Sharon Weissman, Jianjun Hu, Mohammad Rifat Haider, Xiaoming Li
Using Big Data Analytics To Improve Hiv Medical Care Utilisation In South Carolina: A Study Protocol, Bankole Olatosi, Jiajia Zhang, Sharon Weissman, Jianjun Hu, Mohammad Rifat Haider, Xiaoming Li
Faculty Publications
Introduction Linkage and retention in HIV medical care remains problematic in the USA. Extensive health utilisation data collection through electronic health records (EHR) and claims data represent new opportunities for scientific discovery. Big data science (BDS) is a powerful tool for investigating HIV care utilisation patterns. The South Carolina (SC) office of Revenue and Fiscal Affairs (RFA) data warehouse captures individual-level longitudinal health utilisation data for persons living with HIV (PLWH). The data warehouse includes EHR, claims and data from private institutions, housing, prisons, mental health, Medicare, Medicaid, State Health Plan and the department of health and human services. The …
Hydrodynamic Modeling Coupled With Long-Term Field Data Provide Evidence For Suppression Of Phytoplankton By Invasive Clams And Freshwater Exports In The San Francisco Estuary, Bruce G. Hammock
Faculty Publications
The San Francisco Estuary (California, USA) had abundant pelagic fish in the late 1960s, but has few pelagic fish today. A primary cause for this decline in fish is thought to be a trophic cascade, triggered by declining phytoplankton. Here, we describe the changes in pelagic community structure of the San Francisco Estuary. Then, we examine whether changes in hydrodynamics due to freshwater exports, which increased exponentially beginning in 1967, in addition to the 1986 invasion by the clam Potamocorbula amurensis, explain the phytoplankton loss. Hydrodynamic variables were reconstructed back to 1956 using statistical models fit to, and cross-validated against, …
Challenges For Natural Hydrogels In Tissue Engineering, Esmaiel Jabbari
Challenges For Natural Hydrogels In Tissue Engineering, Esmaiel Jabbari
Faculty Publications
Protein-based biopolymers derived from natural tissues possess a hierarchical structure in their native state. Strongly solvating, reducing and stabilizing agents, as well as heat, pressure, and enzymes are used to isolate protein-based biopolymers from their natural tissue, solubilize them in aqueous solution and convert them into injectable or preformed hydrogels for applications in tissue engineering and regenerative medicine. This review aims to highlight the need to investigate the nano-/micro-structure of hydrogels derived from the extracellular matrix proteins of natural tissues. Future work should focus on identifying the nature of secondary, tertiary, and higher order structure formation in protein-based hydrogels derived …
Challenges For Natural Hydrogels In Tissue Engineering, Esmaiel Jabbari
Challenges For Natural Hydrogels In Tissue Engineering, Esmaiel Jabbari
Faculty Publications
Protein-based biopolymers derived from natural tissues possess a hierarchical structure in their native state. Strongly solvating, reducing and stabilizing agents, as well as heat, pressure, and enzymes are used to isolate protein-based biopolymers from their natural tissue, solubilize them in aqueous solution and convert them into injectable or preformed hydrogels for applications in tissue engineering and regenerative medicine. This review aims to highlight the need to investigate the nano-/micro-structure of hydrogels derived from the extracellular matrix proteins of natural tissues. Future work should focus on identifying the nature of secondary, tertiary, and higher order structure formation in protein-based hydrogels derived …
Challenges For Natural Hydrogels In Tissue Engineering, Esmaiel Jabbari
Challenges For Natural Hydrogels In Tissue Engineering, Esmaiel Jabbari
Faculty Publications
Protein-based biopolymers derived from natural tissues possess a hierarchical structure in their native state. Strongly solvating, reducing and stabilizing agents, as well as heat, pressure, and enzymes are used to isolate protein-based biopolymers from their natural tissue, solubilize them in aqueous solution and convert them into injectable or preformed hydrogels for applications in tissue engineering and regenerative medicine. This review aims to highlight the need to investigate the nano-/micro-structure of hydrogels derived from the extracellular matrix proteins of natural tissues. Future work should focus on identifying the nature of secondary, tertiary, and higher order structure formation in protein-based hydrogels derived …
Hypermongone C Accelerates Wound Healing Through The Modulation Of Inflammatory Factors And Promotion Of Fibroblast Migration, Sara E. Moghadam, Moridi Mahdi Farimani, Sara Soroury, Samad N. Ebrahimi, Ehsan Jabbarzadeh
Hypermongone C Accelerates Wound Healing Through The Modulation Of Inflammatory Factors And Promotion Of Fibroblast Migration, Sara E. Moghadam, Moridi Mahdi Farimani, Sara Soroury, Samad N. Ebrahimi, Ehsan Jabbarzadeh
Faculty Publications
The physiology of wound healing is dependent on the crosstalk between inflammatory mediators and cellular components of skin regeneration including fibroblasts and endothelial cells. Therefore, strategies to promote healing must regulate this crosstalk to achieve maximum efficacy. In light of the remarkable potential of natural compounds to target multiple signaling mechanisms, this study aims to demonstrate the potential of hypermongone C, a polycyclic polyprenylated acylphloroglucinol (PPAP), to accelerate wound closure by concurrently enhancing fibroblast proliferation and migration, promoting angiogenesis, and suppressing pro-inflammatory cytokines. This compound belongs to a family of plants (Hypericum) that traditionally have been used to treat injuries. …
Deep Autoencoder Neural Networks For Short-Term Traffic Congestion Prediction Of Transportation Networks, Sen Zhang, Yong Yao, Jie Hu, Yong Zhao, Shaobo Li, Jianjun Hu
Deep Autoencoder Neural Networks For Short-Term Traffic Congestion Prediction Of Transportation Networks, Sen Zhang, Yong Yao, Jie Hu, Yong Zhao, Shaobo Li, Jianjun Hu
Faculty Publications
Traffic congestion prediction is critical for implementing intelligent transportation systems for improving the efficiency and capacity of transportation networks. However, despite its importance, traffic congestion prediction is severely less investigated compared to traffic flow prediction, which is partially due to the severe lack of large-scale high-quality traffic congestion data and advanced algorithms. This paper proposes an accessible and general workflow to acquire large-scale traffic congestion data and to create traffic congestion datasets based on image analysis. With this workflow we create a dataset named Seattle Area Traffic Congestion Status (SATCS) based on traffic congestion map snapshots from a publicly available …
Deep Autoencoder Neural Networks For Short-Term Traffic Congestion Prediction Of Transportation Networks, Sen Zhang, Yong Yao, Jie Hu, Yong Zhao, Shaobo Li, Jianjun Hu
Deep Autoencoder Neural Networks For Short-Term Traffic Congestion Prediction Of Transportation Networks, Sen Zhang, Yong Yao, Jie Hu, Yong Zhao, Shaobo Li, Jianjun Hu
Faculty Publications
Traffic congestion prediction is critical for implementing intelligent transportation systems for improving the efficiency and capacity of transportation networks. However, despite its importance, traffic congestion prediction is severely less investigated compared to traffic flow prediction, which is partially due to the severe lack of large-scale high-quality traffic congestion data and advanced algorithms. This paper proposes an accessible and general workflow to acquire large-scale traffic congestion data and to create traffic congestion datasets based on image analysis. With this workflow we create a dataset named Seattle Area Traffic Congestion Status (SATCS) based on traffic congestion map snapshots from a publicly available …
Deep Autoencoder Neural Networks For Short-Term Traffic Congestion Prediction Of Transportation Networks, Sen Zhang, Yong Yao, Jie Hu, Yong Zhao, Shaobo Li, Jianjun Hu
Deep Autoencoder Neural Networks For Short-Term Traffic Congestion Prediction Of Transportation Networks, Sen Zhang, Yong Yao, Jie Hu, Yong Zhao, Shaobo Li, Jianjun Hu
Faculty Publications
Traffic congestion prediction is critical for implementing intelligent transportation systems for improving the efficiency and capacity of transportation networks. However, despite its importance, traffic congestion prediction is severely less investigated compared to traffic flow prediction, which is partially due to the severe lack of large-scale high-quality traffic congestion data and advanced algorithms. This paper proposes an accessible and general workflow to acquire large-scale traffic congestion data and to create traffic congestion datasets based on image analysis. With this workflow we create a dataset named Seattle Area Traffic Congestion Status (SATCS) based on traffic congestion map snapshots from a publicly available …