School of Engineering

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https://ir.vanderbilt.edu/handle/1803/5549

The mission of the School of Engineering is threefold: to prepare undergraduate and graduate students for roles that contribute to society; to conduct research to advance the state of knowledge and technology and to disseminate these advances through archival publications, conference publications, and technology transfer; and to provide professional services to the community.

Address:	2301 Vanderbilt Place PMB 351826 Nashville, TN 37235-1826
Phone:	615-322-2762
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Now showing 1 - 20 of 23

Adsorption of methylene blue on papaya bark fiber: Equilibrium, isotherm and kinetic perspectives
(Results In Engineering, 2022-12-21) Nipa, Sumaya Tarannum; Shefa, Nawrin Rahman; Parvin, Shahanaz; Khatun, Most Afroza; Alam, Md Jahangir; Chowdhury, Sujan; Khan, M. Azizur R.; Shawon, Sk Md Ali Zaker; Biswas, Biplob K.; Rahman, Md Wasikur
Rapid population growth and industrial expansion lead us to be habitat of a polluted planet. One of the major pollutants that badly affect the ecosystem being organic dyes released from various chemical industries where cleaner production concept is straightway adopted. Papaya (Carica papaya) bark fiber (PBF) is a natural product used for Methylene Blue (MB) dye removal as a cost-effective adsorbent from aqueous solution by batch method. Several parameters as the effect of pH, initial dye concentration, contact time, and adsorbent dosage were studied and optimized for maximum dye recovery. Reaction kinetics of the process and Langmuir and Freundlich adsorption isotherms were investigated. Fourier Transform Infrared (FTIR) spectroscopy and Scanning Electron Microscopy (SEM) were used to confirm the surface properties of the PBF adsorbent. The maximum MB uptake capacity of PBF adsorbent was found to be 66.67 mg/g. Based on the results, the papaya bark fiber might be employed as a cost-effective bio-sorbent for the exclusion of dyestuffs from industrial effluent for cleaner production.
Approximate Loop Unrolling
(CF '19 - PROCEEDINGS OF THE 16TH ACM INTERNATIONAL CONFERENCE ON COMPUTING FRONTIERS, 2019-04-30) Rodriguez-Cancio, Marcelino; Combemale, Benoit; Baudry, Benoit
We introduce Approximate Unrolling, a compiler loop optimization that reduces execution time and energy consumption, exploiting code regions that can endure some approximation and still produce acceptable results. Specifically, this work focuses on counted loops that map a function over the elements of an array. Approximate Unrolling transforms loops similarly to Loop Unrolling. However, unlike its exact counterpart, our optimization does not unroll loops by adding exact copies of the loop's body. Instead, it adds code that interpolates the results of previous iterations.
The Arizona Ring Experiments Dataset (ARED)
(2018) Wu, Fangyu; Stern, Raphael E.; Cui, Shumo; Delle Monache, Maria Laura; Bhadani, Rahul; Bunting, Matt; Churchill, Miles; Hamilton, Nathaniel; Haulcy, R'mani; Piccoli, Benedetto; Seibold, Benjamin; Sprinkle, Jonathan; Work, Daniel
Naturalistic driving data from a series of experiments to understand the development of phantom traffic jams.
Capsule robot pose and mechanism state detection in ultrasound using attention-based hierarchical deep learning
(Scientific Reports, 2022-12-07) Liu, Xiaoyun; Esser, Daniel; Wagstaff, Brandon; Zavodni, Anna; Matsuura, Naomi; Kelly, Jonathan; Diller, Eric
Ingestible robotic capsules with locomotion capabilities and on-board sampling mechanism have great potential for non-invasive diagnostic and interventional use in the gastrointestinal tract. Real-time tracking of capsule location and operational state is necessary for clinical application, yet remains a significant challenge. To this end, we propose an approach that can simultaneously determine the mechanism state and in-plane 2D pose of millimeter capsule robots in an anatomically representative environment using ultrasound imaging. Our work proposes an attention-based hierarchical deep learning approach and adapts the success of transfer learning towards solving the multi-task tracking problem with limited dataset. To train the neural networks, we generate a representative dataset of a robotic capsule within ex-vivo porcine stomachs. Experimental results show that the accuracy of capsule state classification is 97%, and the mean estimation errors for orientation and centroid position are 2.0 degrees and 0.24 mm (1.7% of the capsule's body length) on the hold-out test set. Accurate detection of the capsule while manipulated by an external magnet in a porcine stomach and colon is also demonstrated. The results suggest our proposed method has the potential for advancing the wireless capsule-based technologies by providing accurate detection of capsule robots in clinical scenarios.
Cold exposure induces dynamic, heterogeneous alterations in human brown adipose tissue lipid content
(Scientific Reports, 2019-09-19) Coolbaugh, Crystal L.; Damon, Bruce M.; Bush, Emily C.; Welch, E. Brian; Towse, Theodore F.
Brown adipose tissue undergoes a dynamic, heterogeneous response to cold exposure that can include the simultaneous synthesis, uptake, and oxidation of fatty acids. The purpose of this work was to quantify these changes in brown adipose tissue lipid content (fat-signal fraction (FSF)) using fat-water magnetic resonance imaging during individualized cooling to 3 degrees C above a participant's shiver threshold. Eight healthy men completed familiarization, perception-based cooling, and MRI-cooling visits. FSF maps of the supraclavicular region were acquired in thermoneutrality and during cooling (59.5 +/- 6.5 min). Brown adipose tissue regions of interest were defined, and voxels were grouped into FSF decades (0-10%, 10-20%. 90-100%) according to their initial value. Brown adipose tissue contained a heterogeneous morphology of lipid content. Voxels with initial FSF values of 60-100% (P < 0.05) exhibited a significant decrease in FSF while a simultaneous increase in FSF occurred in voxels with initial FSF values of 0-30% (P < 0.05). These data suggest that in healthy young men, cold exposure elicits a dynamic and heterogeneous response in brown adipose tissue, with areas initially rich with lipid undergoing net lipid loss and areas of low initial lipid undergoing a net lipid accumulation.
Composite Electrode Ink Formulation for All Solid-State Batteries
(Journal of the Electrochemical Society, 2019-09-18) Shen, Fengyu; Dixit, Marm B.; Zaman, Wahid; Hortance, Nicholas; Rogers, Bridget; Hatzell, Kelsey B.
Solid-state batteries employ composite electrodes which contain a solid ion conductor, a solid active material, a conductive additive, and a binder. The electrode microstructure fundamentally differs from electrodes in conventional batteries because the pore region is ion blocking. While there is extensive research on how to integrate a lithium metal with inorganic electrolytes, there is less knowledge on how an electrode can be integrated with an inorganic electrolyte. Solution processing techniques are ideal for scalable manufacturing and rely on creating an ink which combines the solid material, a binder, and solvent. Ink engineering relies on tailoring the fluidics (rheology), aggregation behavior, and stability for a desired coating process. In this work, we systematically probe the role of two ink constituents: the (1) binder, and (2) solvent on electrode microstructure formation. Lithium titanate anodes achieve nearly a 3-4X increase in capacity from 1.5 mAh/g and 3 mAh/g to 9 mAh/g and >= 12 mAh/g when a high viscosity solvent is employed. The binder plays a larger role in dictating performance of the electrode than surface adhesion properties. Inks with well dispersed constituents led to more effective electrodes for charge storage. (C) The Author(s) 2019. Published by ECS.
Dataset of "Evaluation of Traffic Signal Control at Varying Demand Levels: A Comparative Study"
(2023)
Repository for the simulation output dataset associated with the paper "Evaluation of Traffic Signal Control at Varying Demand Levels: A Comparative Study" in IEEE ITSC 2023.
Delivery of Nanoparticles to Brain Metastases of Breast Cancer Using a Cellular Trojan Horse
(Springer, 2012-12) Choi, Mi-Ran; Bardhan, Rizia; Stanton-Maxey, Katie; Badve, Sunil; Nakshatri, Harikrishna; Stantz, Keith M.; Cao, Ning; Halas, Naomi J.; Clare, Susan E.
As systemic cancer therapies improve and are able to control metastatic disease outside the central nervous system, the brain is increasingly the first site of relapse. The blood–brain barrier (BBB) represents a major challenge to the delivery of therapeutics to the brain. Macrophages originating from circulating monocytes are able to infiltrate brain metastases while the BBB is intact. Here, we show that this ability can be exploited to deliver both diagnostic and therapeutic nanoparticles specifically to experimental brain metastases of breast cancer.
Detecting web attacks with end-to-end deep learning
(Journal of Internet Services and Applications, 2019-08-27) Pan, Yao; Sun, Fangzhou; Teng, Zhongwei; White, Jules; Schmidt, Douglas C.; Staples, Jacob; Krause, Lee
Web applications are popular targets for cyber-attacks because they are network-accessible and often contain vulnerabilities. An intrusion detection system monitors web applications and issues alerts when an attack attempt is detected. Existing implementations of intrusion detection systems usually extract features from network packets or string characteristics of input that are manually selected as relevant to attack analysis. Manually selecting features, however, is time-consuming and requires in-depth security domain knowledge. Moreover, large amounts of labeled legitimate and attack request data are needed by supervised learning algorithms to classify normal and abnormal behaviors, which is often expensive and impractical to obtain for production web applications. This paper provides three contributions to the study of autonomic intrusion detection systems. First, we evaluate the feasibility of an unsupervised/semi-supervised approach for web attack detection based on the Robust Software Modeling Tool (RSMT), which autonomically monitors and characterizes the runtime behavior of web applications. Second, we describe how RSMT trains a stacked denoising autoencoder to encode and reconstruct the call graph for end-to-end deep learning, where a low-dimensional representation of the raw features with unlabeled request data is used to recognize anomalies by computing the reconstruction error of the request data. Third, we analyze the results of empirically testing RSMT on both synthetic datasets and production applications with intentional vulnerabilities. Our results show that the proposed approach can efficiently and accurately detect attacks, including SQL injection, cross-site scripting, and deserialization, with minimal domain knowledge and little labeled training data.
Discrimination of Liver Malignancies with 1064 nm Dispersive Raman Spectroscopy
(2015) Pence, Isaac J.; Patil, Chetan A.; Lieber, Chad A.; Mahadevan-Jansen, Anita
Raman spectroscopy has been widely demonstrated for tissue characterization and disease discrimination, however current implementations with either 785 or 830 nm near-infrared (NIR) excitation have been ineffectual in tissues with intense autofluorescence such as the liver. Here we report the use of a dispersive 1064 nm Raman system using a low-noise Indium-Gallium-Arsenide (InGaAs) array to discriminate highly autofluorescent bulk tissue ex vivo specimens from healthy liver, adenocarcinoma, and hepatocellular carcinoma (N = 5 per group). The resulting spectra have been combined with a multivariate discrimination algorithm, sparse multinomial logistic regression (SMLR), to predict class membership of healthy and diseased tissues, and spectral bands selected for robust classification have been extracted. A quantitative metric called feature importance is defined based on classification outputs and is used to guide the association of spectral features with biological indicators of healthy and diseased liver tissue. Spectral bands with high feature importance for healthy and liver tumor specimens include retinol, heme, biliverdin, or quinones (1595 cm−1); lactic acid (838 cm−1); collagen (873 cm−1); and nucleic acids (1485 cm−1). Classification performance in both binary (normal versus tumor, 100% sensitivity and 89% specificity) and three-group cases (classification accuracy: normal 89%, adenocarcinoma 74%, hepatocellular carcinoma 64%) indicates the potential for accurately separating healthy and cancerous tissues and suggests implications for utilizing Raman techniques during surgical guidance in liver resection.
Dissipation of Stop-and-Go Waves via Control of Autonomous Vehicles: Experimental Results: Data
(2017) Stern, Raphael E.; Cui, Shumo; Delle Monache, Maria Laura; Bhadani, Rahul; Bunting, Matt; Churchill, Miles; Hamilton, Nathaniel; Haulcy, R'mani; Pohlmann, Hannah; Wu, Fangyu; Piccoli, Benedetto; Seibold, Benjamin; Sprinkle, Jonathan; Work, Daniel B.
This is the data that accompanies the paper titled, "Dissipation of stop-and-go waves via control of autonomous vehicles: experimental results" and includes all the data and code to generate all the figures that appeared in the paper.
Effects of Prolonged Head-Down Bed Rest on Cardiac and Vascular Baroreceptor Modulation and Orthostatic Tolerance in Healthy Individuals
(Frontiers in Pyhsiology, 2019-08-23) Barbic, Franca; Heusser, Karsten; Minonzio, Maura; Shiffer, Dana; Cairo, Beatrice; Tank, Jens; Jordan, Jens; Diedrich, Andre; Gauger, Peter; Zamuner, Roberto Antonio; Porta, Alberto; Furlan, Raffaello
Orthostatic intolerance commonly occurs after prolonged bed rest, thus increasing the risk of syncope and falls. Baroreflex-mediated adjustments of heart rate and sympathetic vasomotor activity (muscle sympathetic nerve activity - MSNA) are crucial for orthostatic tolerance. We hypothesized that prolonged bed rest deconditioning alters overall baroreceptor functioning, thereby reducing orthostatic tolerance in healthy volunteers. As part of the European Space Agency Medium-term Bed Rest protocol, 10 volunteers were studied before and after 21 days of -6 degrees head down bed rest (HDBR). In both conditions, subjects underwent ECG, beat-by-beat blood pressure, respiratory activity, and MSNA recordings while supine (REST) and during a 15-min 80 degrees head-up tilt (TILT) followed by a 3-min -10 mmHg stepwise increase of lower body negative pressure to pre-syncope. Cardiac baroreflex sensitivity (cBRS) was obtained in the time (sequence method) and frequency domain (spectrum and cross-spectrum analyses of RR interval and systolic arterial pressure - SAP, variability). Baroreceptor modulation of sympathetic discharge activity to the vessels (sBRS) was estimated by the slope of the regression line between the percentage of MSNA burst occurrence and diastolic arterial pressure. Orthostatic tolerance significantly decreased after HDBR (12 +/- 0.6 min) compared to before (21 +/- 0.6 min). While supine, heart rate, SAP, and cBRS were unchanged before and after HDBR, sBRS gain was slightly depressed after than before HDBR (sBRS: -6.0 +/- 1.1 versus -2.9 +/- 1.5 burst% x mmHg(-1), respectively). During TILT, HR was higher after than before HDBR (116 +/- 4 b/min versus 100 +/- 4 b/min, respectively), SAP was unmodified in both conditions, and cBRS indexes were lower after HDBR (alpha index: 3.4 +/- 0.7 ms/mmHg; BRSSEQ 4.0 +/- 1.0) than before (alpha index: 6.4 +/- 1.0 ms/mmHg; BRSSEQ 6.8 +/- 1.2). sBRS gain was significantly more depressed after HDBR than before (sBRS: -2.3 +/- 0.7 versus -4.4 +/- 0.4 burst% x mmHg(-1), respectively). Our findings suggest that baroreflex-mediated adjustments in heart rate and MSNA are impaired after prolonged bed rest. The mechanism likely contributes to the decrease in orthostatic tolerance.
Electrically defined topological interface states of graphene surface plasmons based on a gate-tunable quantum Bragg grating
(Nanophotonics, 2019-08) Fan, Zhiyuan; Dutta-Gupta, Shourya; Gladstone, Ran; Trendafilov, Simeon; Bosch, Melissa; Jung, Minwoo; Iyer, Ganjigunte R. Swathi; Giles, Alexander J.; Shcherbakov, Maxim; Feigelson, Boris; Caldwell, Joshua D.; Allen, Monica; Allen, Jeffery; Shvets, Gennady
A periodic metagate is designed on top of a boron nitride-graphene heterostructure to modulate the local carrier density distribution on the monolayer graphene. This causes the bandgaps of graphene surface plasmon polaritons to emerge because of either the interaction between the plasmon modes, which are mediated by the varying local carrier densities, or their interaction with the metal gates. Using the example of a double-gate graphene device, we discuss the tunable band properties of graphene plasmons due to the competition between these two mechanisms. Because of this, a bandgap inversion, which results in a Zak phase switching, can be realized through electrostatic gating. Here we also show that an anisotropic plasmonic topological edge state exists at the interface between two graphene gratings of different Zak phases. While the orientation of the dipole moments can differentiate the band topologies of each graphene grating, the angle of radiation remains a tunable property. This may serve as a stepping stone toward active control of the band structures of surface plasmons for potential applications in optical communication, wave steering, or sensing.
Engineered fluidic systems to understand lymphatic cancer metastasis
(Biomicrofluidics, 2020-01) Greenlee, Joshua D.; King, Michael R.
The majority of all cancers metastasize initially through the lymphatic system. Despite this, the mechanisms of lymphogenous metastasis remain poorly understood and understudied compared to hematogenous metastasis. Over the past few decades, microfluidic devices have been used to model pathophysiological processes and drug interactions in numerous contexts. These devices carry many advantages over traditional 2D in vitro systems, allowing for better replication of in vivo microenvironments. This review highlights prominent fluidic devices used to model the stages of cancer metastasis via the lymphatic system, specifically within lymphangiogenesis, vessel permeability, tumor cell chemotaxis, transendothelial migration, lymphatic circulation, and micrometastases within the lymph nodes. In addition, we present perspectives for the future roles that microfluidics might play within these settings and beyond.
Engineered models to parse apart the metastatic cascade
(NPJ Precision Oncology, 2019-08-21) Hapach, Lauren A.; Mosier, Jenna A.; Wang, Wenjun; Reinhart-King, Cynthia A.
While considerable progress has been made in studying genetic and cellular aspects of metastasis with in vitro cell culture and in vivo animal models, the driving mechanisms of each step of metastasis are still relatively unclear due to their complexity. Moreover, little progress has been made in understanding how cellular fitness in one step of the metastatic cascade correlates with ability to survive other subsequent steps. Engineered models incorporate tools such as tailored biomaterials and microfabrication to mimic human disease progression, which when coupled with advanced quantification methods permit comparisons to human patient samples and in vivo studies. Here, we review novel tools and techniques that have been recently developed to dissect key features of the metastatic cascade using primary patient samples and highly representative microenvironments for the purposes of advancing personalized medicine and precision oncology. Although improvements are needed to increase tractability and accessibility while faithfully simulating the in vivo microenvironment, these models are powerful experimental platforms for understanding cancer biology, furthering drug screening, and facilitating development of therapeutics.
Loss and Damage Estimation for Extreme Weather Events: State of the Practice
(Sustainability, 2019-08) Doktycz, Charles; Abkowitz, Mark
Extreme weather, climate-induced events that are episodic (e.g., hurricane, heatwave) or chronic (e.g., sea-level rise, temperature change) in nature, is occurring with increasing frequency and severity. This places a growing and time-sensitive need on the development and implementation of adaptation policies and practices. To motivate adaptive behavior, however, requires the ability to deliver improved risk-informed decision-making capability. At the crux of this challenge is the provision of full and accurate loss and damage accounting of the overall impact of an extreme weather event, enabling the business case to be made for adaptation investment. We define loss and damage as the manifestation of impacts associated with extreme weather that negatively affect human and natural systems. Progress in the development of adequate loss and damage accounting has been hampered by issues, such as discrepancies in conceptual frameworks, problems associated with data quantity and quality, and lack of standardized analysis methodologies. In this paper, we have discussed the conceptual basis for measuring loss and damage, reviewed the state of loss and damage data collection and modeling, and offered a narrative on the future direction of the practice.
Multifunctional metaoptics based on bilayer metasurfaces
(Light-Science & Appplications, 2019-09-04) Zhou, You; Kravchenko, Ivan I.; Wang, Hao; Zheng, Hanyu; Gu, Gong; Valentine, Jason
Optical metasurfaces have become versatile platforms for manipulating the phase, amplitude, and polarization of light. A platform for achieving independent control over each of these properties, however, remains elusive due to the limited engineering space available when using a single-layer metasurface. For instance, multiwavelength metasurfaces suffer from performance limitations due to space filling constraints, while control over phase and amplitude can be achieved, but only for a single polarization. Here, we explore bilayer dielectric metasurfaces to expand the design space for metaoptics. The ability to independently control the geometry and function of each layer enables the development of multifunctional metaoptics in which two or more optical properties are independently designed. As a proof of concept, we demonstrate multiwavelength holograms, multiwavelength waveplates, and polarization-insensitive 3D holograms based on phase and amplitude masks. The proposed architecture opens a new avenue for designing complex flat optics with a wide variety of functionalities.
On-chip integrated quantum emitter with 'trap-enhance-guide': a simulation approach
(Optics Express, 2022-12-19) Saha, Samprity; Fomra, Dhruv; Ozgur, Umit; Avrutin, Vitaly; Ndukaife, Justus C.; Kinsey, Nathaniel
To address the challenges of developing a scalable system of an on-chip integrated quantum emitter, we propose to leverage the loss in our hybrid plasmonic-photonic structure to simultaneously achieve Purcell enhancement as well as on-chip maneuvering of nanoscale emitter via optical trapping with guided excitation-emission routes. In this report, we have analyzed the feasibility of the functional goals of our proposed system in the metric of trapping strength (-8KBT), Purcell factor (>1000-), and collection efficiency (-10%). Once realized, the scopes of the proposed device can be advanced to develop a scalable platform for integrated quantum technology.
The Pseudo-Pascal Triangle of Maximum Deng Entropy
(International Journal of Computers Communications & Control, 2020-02) Gao, X.; Deng, Y.
Pascal triangle (known as Yang Hui Triangle in Chinese) is an important model in mathematics while the entropy has been heavily studied in physics or as uncertainty measure in information science. How to construct the the connection between Pascal triangle and uncertainty measure is an interesting topic. One of the most used entropy, Tasllis entropy, has been modelled with Pascal triangle. But the relationship of the other entropy functions with Pascal triangle is still an open issue. Dempster-Shafer evidence theory takes the advantage to deal with uncertainty than probability theory since the probability distribution is generalized as basic probability assignment, which is more efficient to model and handle uncertain information. Given a basic probability assignment, its corresponding uncertainty measure can be determined by Deng entropy, which is the generalization of Shannon entropy. In this paper, a Pseudo-Pascal triangle based the maximum Deng entropy is constructed. Similar to the Pascal triangle modelling of Tasllis entropy, this work provides the a possible way of Deng entropy in physics and information theory.
Quantitative oxygen atom measurements in lean, premixed, H2 tubular flames
(Elsevier, 2021) Marshall, Garrett J; Walsh, Patrick S; Pitz, Robert W
Quantitative O-atom profiles are measured for the first time in tubular flames and used to assess the performance of chemical kinetic mechanisms in tubular flame simulations. Atomic oxygen is measured via femtosecond, Two-Photon Laser Induced Fluorescence (fs-TPLIF) to avoid photolytic interference. The fs- TPLIF signal is corrected for collisional quenching from major species concentrations measured by Raman scattering. Temperature-dependent quenching rate in the form of T ^−0.5 for H2O is applied to better represent the actual physics, and all simulations are found to agree with this method. Atomic oxygen is reported in H2/O2 flames diluted with N2 or CO2 at 200 and 400 s ^−1 stretch rates. The oxygen radical data is compared to predictions using three different, detailed chemical kinetic mechanisms. Predictions of profile shape vary slightly, but the peak O-atom number density is calculated within experimental uncertainty by each mechanism.

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