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Ranked List Fusion And Re-Ranking With Pre-Trained Transformers For Arqmath Lab, Shaurya Rohatgi, Jian Wu, C. Lee Giles Jan 2021

Ranked List Fusion And Re-Ranking With Pre-Trained Transformers For Arqmath Lab, Shaurya Rohatgi, Jian Wu, C. Lee Giles

Computer Science Faculty Publications

This paper elaborates on our submission to the ARQMath track at CLEF 2021. For our submission this year we use a collection of methods to retrieve and re-rank the answers in Math Stack Exchange in addition to our two-stage model which was comparable to the best model last year in terms of NDCG’. We also provide a detailed analysis of what the transformers are learning and why is it hard to train a math language model using transformers. This year’s submission to Task-1 includes summarizing long question-answer pairs to augment and index documents, using byte-pair encoding to tokenize formula and …

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Adaptive Physics-Based Non-Rigid Registration For Immersive Image-Guided Neuronavigation Systems, Fotis Drakopoulos, Christos Tsolakis, Angelos Angelopoulos, Yixun Liu, Chengjun Yao, Kyriaki Rafailia Kavazidi, Nikolaos Foroglou, Andrey Fedorov, Sarah Frisken, Ron Kikinis, Alexandra Golby, Nikos Chrisochoides Jan 2021

Adaptive Physics-Based Non-Rigid Registration For Immersive Image-Guided Neuronavigation Systems, Fotis Drakopoulos, Christos Tsolakis, Angelos Angelopoulos, Yixun Liu, Chengjun Yao, Kyriaki Rafailia Kavazidi, Nikolaos Foroglou, Andrey Fedorov, Sarah Frisken, Ron Kikinis, Alexandra Golby, Nikos Chrisochoides

Computer Science Faculty Publications

Objective: In image-guided neurosurgery, co-registered preoperative anatomical, functional, and diffusion tensor imaging can be used to facilitate a safe resection of brain tumors in eloquent areas of the brain. However, the brain deforms during surgery, particularly in the presence of tumor resection. Non-Rigid Registration (NRR) of the preoperative image data can be used to create a registered image that captures the deformation in the intraoperative image while maintaining the quality of the preoperative image. Using clinical data, this paper reports the results of a comparison of the accuracy and performance among several non-rigid registration methods for handling brain deformation. A …

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Combining Cryo-Em Density Map And Residue Contact For Protein Secondary Structure Topologies, Maytha Alshammari, Jing He Jan 2021

Combining Cryo-Em Density Map And Residue Contact For Protein Secondary Structure Topologies, Maytha Alshammari, Jing He

Computer Science Faculty Publications

Although atomic structures have been determined directly from cryo-EM density maps with high resolutions, current structure determination methods for medium resolution (5 to 10 Å) cryo-EM maps are limited by the availability of structure templates. Secondary structure traces are lines detected from a cryo-EM density map for α-helices and β-strands of a protein. A topology of secondary structures defines the mapping between a set of sequence segments and a set of traces of secondary structures in three-dimensional space. In order to enhance accuracy in ranking secondary structure topologies, we explored a method that combines three sources of information: a set …

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See-Trend: Secure Traffic-Related Event Detection In Smart Communities, Stephan Olariu, Dimitrie C. Popescu Jan 2021

See-Trend: Secure Traffic-Related Event Detection In Smart Communities, Stephan Olariu, Dimitrie C. Popescu

Computer Science Faculty Publications

It has been widely recognized that one of the critical services provided by Smart Cities and Smart Communities is Smart Mobility. This paper lays the theoretical foundations of SEE-TREND, a system for Secure Early Traffic-Related EveNt Detection in Smart Cities and Smart Communities. SEE-TREND promotes Smart Mobility by implementing an anonymous, probabilistic collection of traffic-related data from passing vehicles. The collected data are then aggregated and used by its inference engine to build beliefs about the state of the traffic, to detect traffic trends, and to disseminate relevant traffic-related information along the roadway to help the driving public make informed …

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Parallel Anisotropic Unstructured Grid Adaptation, Christos Tsolakis, Nikos Chrisochoides, Michael A. Park, Adrien Loseille, Todd Michal Jan 2021

Parallel Anisotropic Unstructured Grid Adaptation, Christos Tsolakis, Nikos Chrisochoides, Michael A. Park, Adrien Loseille, Todd Michal

Computer Science Faculty Publications

Computational fluid dynamics (CFD) has become critical to the design and analysis of aerospace vehicles. Parallel grid adaptation that resolves multiple scales with anisotropy is identified as one of the challenges in the CFD Vision 2030 Study to increase the capacity and capability of CFD simulation. The study also cautions that computer architectures are undergoing a radical change, and dramatic increases in algorithm concurrency will be required to exploit full performance. This paper reviews four different methods to parallel anisotropic grid adaptation. They cover both ends of the spectrum: 1) using existing state-of-the-art software optimized for a single core and …

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A Tool For Segmentation Of Secondary Structures In 3d Cryo-Em Density Map Components Using Deep Convolutional Neural Networks, Yongcheng Mu, Salim Sazzed, Maytha Alshammari, Jiangwen Sun, Jing He Jan 2021

A Tool For Segmentation Of Secondary Structures In 3d Cryo-Em Density Map Components Using Deep Convolutional Neural Networks, Yongcheng Mu, Salim Sazzed, Maytha Alshammari, Jiangwen Sun, Jing He

Computer Science Faculty Publications

Although cryo-electron microscopy (cryo-EM) has been successfully used to derive atomic structures for many proteins, it is still challenging to derive atomic structures when the resolution of cryo-EM density maps is in the medium resolution range, such as 5–10 Å. Detection of protein secondary structures, such as helices and β-sheets, from cryo-EM density maps provides constraints for deriving atomic structures from such maps. As more deep learning methodologies are being developed for solving various molecular problems, effective tools are needed for users to access them. We have developed an effective software bundle, DeepSSETracer, for the detection of protein secondary structure …

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Detecting Incentivized Review Groups With Co-Review Graph, Yubao Zhang, Shuai Hao, Haining Wang Jan 2021

Detecting Incentivized Review Groups With Co-Review Graph, Yubao Zhang, Shuai Hao, Haining Wang

Computer Science Faculty Publications

Online reviews play a crucial role in the ecosystem of nowadays business (especially e-commerce platforms), and have become the primary source of consumer opinions. To manipulate consumers’ opinions, some sellers of e-commerce platforms outsource opinion spamming with incentives (e.g., free products) in exchange for incentivized reviews. As incentives, by nature, are likely to drive more biased reviews or even fake reviews. Despite e-commerce platforms such as Amazon have taken initiatives to squash the incentivized review practice, sellers turn to various social networking platforms (e.g., Facebook) to outsource the incentivized reviews. The aggregation of sellers who …

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Ssentiaa: A Self-Supervised Sentiment Analyzer For Classification From Unlabeled Data, Salim Sazzed, Sampath Jayarathna Jan 2021

Ssentiaa: A Self-Supervised Sentiment Analyzer For Classification From Unlabeled Data, Salim Sazzed, Sampath Jayarathna

Computer Science Faculty Publications

In recent years, supervised machine learning (ML) methods have realized remarkable performance gains for sentiment classification utilizing labeled data. However, labeled data are usually expensive to obtain, thus, not always achievable. When annotated data are unavailable, the unsupervised tools are exercised, which still lag behind the performance of supervised ML methods by a large margin. Therefore, in this work, we focus on improving the performance of sentiment classification from unlabeled data. We present a self-supervised hybrid methodology SSentiA (Self-supervised Sentiment Analyzer) that couples an ML classifier with a lexicon-based method for sentiment classification from unlabeled data. We first introduce LRSentiA …

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Analysis Of Subtelomeric Rextal Assemblies Using Quast, Tunazzina Islam, Desh Ranjan, Mohammad Zubair, Eleanor Young, Ming Xiao, Harold Riethman Jan 2021

Analysis Of Subtelomeric Rextal Assemblies Using Quast, Tunazzina Islam, Desh Ranjan, Mohammad Zubair, Eleanor Young, Ming Xiao, Harold Riethman

Computer Science Faculty Publications

Genomic regions of high segmental duplication content and/or structural variation have led to gaps and misassemblies in the human reference sequence, and are refractory to assembly from whole-genome short-read datasets. Human subtelomere regions are highly enriched in both segmental duplication content and structural variations, and as a consequence are both impossible to assemble accurately and highly variable from individual to individual. Recently, we developed a pipeline for improved region-specific assembly called Regional Extension of Assemblies Using Linked-Reads (REXTAL). In this study, we evaluate REXTAL and genome-wide assembly (Supernova) approaches on 10X Genomics linked-reads data sets partitioned and barcoded using the …

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Understanding And Predicting Retractions Of Published Work, Sai Ajay Modukuri, Sarah Rajtmajer, Anna Cinzia Squicciarini, Jian Wu, C. Lee Giles Jan 2021

Understanding And Predicting Retractions Of Published Work, Sai Ajay Modukuri, Sarah Rajtmajer, Anna Cinzia Squicciarini, Jian Wu, C. Lee Giles

Computer Science Faculty Publications

Recent increases in the number of retractions of published papers reflect heightened attention and increased scrutiny in the scientific process motivated, in part, by the replication crisis. These trends motivate computational tools for understanding and assessment of the scholarly record. Here, we sketch the landscape of retracted papers in the Retraction Watch database, a collection of 19k records of published scholarly articles that have been retracted for various reasons (e.g., plagiarism, data error). Using metadata as well as features derived from full-text for a subset of retracted papers in the social and behavioral sciences, we develop a random forest classifier …

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Automatic Metadata Extraction Incorporating Visual Features From Scanned Electronic Theses And Dissertations, Muntabir Hasan Choudhury, Himarsha R. Jayanetti, Jian Wu, William A. Ingram, Edward A. Fox Jan 2021

Automatic Metadata Extraction Incorporating Visual Features From Scanned Electronic Theses And Dissertations, Muntabir Hasan Choudhury, Himarsha R. Jayanetti, Jian Wu, William A. Ingram, Edward A. Fox

Computer Science Faculty Publications

Electronic Theses and Dissertations (ETDs) contain domain knowledge that can be used for many digital library tasks, such as analyzing citation networks and predicting research trends. Automatic metadata extraction is important to build scalable digital library search engines. Most existing methods are designed for born-digital documents, so they often fail to extract metadata from scanned documents such as ETDs. Traditional sequence tagging methods mainly rely on text-based features. In this paper, we propose a conditional random field (CRF) model that combines text-based and visual features. To verify the robustness of our model, we extended an existing corpus and created a …

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Recognizing Figure Labels In Patents, Ming Gong, Xin Wei, Diane Oyen, Jian Wu, Martin Gryder Jan 2021

Recognizing Figure Labels In Patents, Ming Gong, Xin Wei, Diane Oyen, Jian Wu, Martin Gryder

Computer Science Faculty Publications

Scientific documents often contain significant information in figures. The United States Patent and Trademark Office (USPTO) awards thousands of patents each week, with each patent containing on the order of a dozen figures. The information conveyed by these figures typically include a drawing or diagram, a label, caption and reference text within the document. Yet associating the short bits of text to the figure is challenging when labels are embedded within the figure, as they typically are in patents. Using patents as a testbench, this paper highlights an open challenge in analyzing all of the information presented in scientific/technical documents …

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Extractive Research Slide Generation Using Windowed Labeling Ranking, Athar Sefid, Prasenjit Mitra, Jian Wu, C. Lee Giles Jan 2021

Extractive Research Slide Generation Using Windowed Labeling Ranking, Athar Sefid, Prasenjit Mitra, Jian Wu, C. Lee Giles

Computer Science Faculty Publications

Presentation slides generated from original research papers provide an efficient form to present research innovations. Manually generating presentation slides is labor-intensive. We propose a method to automatically generates slides for scientific articles based on a corpus of 5000 paper-slide pairs compiled from conference proceedings websites. The sentence labeling module of our method is based on SummaRuNNer, a neural sequence model for extractive summarization. Instead of ranking sentences based on semantic similarities in the whole document, our algorithm measures the importance and novelty of sentences by combining semantic and lexical features within a sentence window. Our method outperforms several baseline methods …

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Systematizing Confidence In Open Research And Evidence (Score), Nazanin Alipourfard, Beatrix Arendt, Daniel M. Benjamin, Noam Benkler, Michael Bishop, Mark Burstein, Martin Bush, James Caverlee, Yiling Chen, Chae Clark, Anna Dreber Almenberg, Timothy M. Errington, Fiona Fidler, Nicholas Fox, Aaron Frank, Hannah Fraser, Scott Friedman, Ben Gelman, James Gentile, Jian Wu, Et Al., Score Collaboration Jan 2021

Systematizing Confidence In Open Research And Evidence (Score), Nazanin Alipourfard, Beatrix Arendt, Daniel M. Benjamin, Noam Benkler, Michael Bishop, Mark Burstein, Martin Bush, James Caverlee, Yiling Chen, Chae Clark, Anna Dreber Almenberg, Timothy M. Errington, Fiona Fidler, Nicholas Fox, Aaron Frank, Hannah Fraser, Scott Friedman, Ben Gelman, James Gentile, Jian Wu, Et Al., Score Collaboration

Computer Science Faculty Publications

Assessing the credibility of research claims is a central, continuous, and laborious part of the scientific process. Credibility assessment strategies range from expert judgment to aggregating existing evidence to systematic replication efforts. Such assessments can require substantial time and effort. Research progress could be accelerated if there were rapid, scalable, accurate credibility indicators to guide attention and resource allocation for further assessment. The SCORE program is creating and validating algorithms to provide confidence scores for research claims at scale. To investigate the viability of scalable tools, teams are creating: a database of claims from papers in the social and behavioral …

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Labilization And Diversification Of Pyrogenic Dissolved Organic Matter By Microbes, Aleksandar I. Goranov, Andrew S. Wozniak, Kyle W. Bostick, Andrew R. Zimmerman, Siddhartha Mitra, Patrick G. Hatcher Jan 2021

Labilization And Diversification Of Pyrogenic Dissolved Organic Matter By Microbes, Aleksandar I. Goranov, Andrew S. Wozniak, Kyle W. Bostick, Andrew R. Zimmerman, Siddhartha Mitra, Patrick G. Hatcher

Chemistry & Biochemistry Faculty Publications

With the increased occurrence of forest fires around the world, interest in the chemistry of pyrogenic organic matter (pyOM) and its fate in the environment has increased. Upon leaching from soils by rain events, significant amounts of dissolved pyOM (pyDOM) enter the aquatic environment and interact with microbial communities that are essential for cycling organic matter within the different biogeochemical cycles. To evaluate the bio-reactivity of pyDOM, aqueous extracts of laboratory-produced chars were incubated with soil microbes and the molecular changes to the composition of pyDOM were probed using ultrahigh resolution mass spectrometry (Fourier transform – ion cyclotron resonance – …

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Design Matters: Development And Validation Of The Online Course Design Elements (Ocde) Instrument, Florence Martin, Doris U. Bolliger, Claudia Flowers Jan 2021

Design Matters: Development And Validation Of The Online Course Design Elements (Ocde) Instrument, Florence Martin, Doris U. Bolliger, Claudia Flowers

STEMPS Faculty Publications

Course design is critical to online student engagement and retention. This study focused on the development and validation of an online course design elements (OCDE) instrument with 38 Likert-type scale items in five subscales: (a) overview, (b) content presentation, (c) interaction and communication, (d) assessment and evaluation, and (e) learner support. The validation process included implementation with 222 online instructors and instructional designers in higher education. Three models were evaluated which included a one-factor model, five-factor model, and higher-order model. The five-factor and higher-order models aligned with the development of the OCDE. The frequency of use of OCDE items was …

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Electroosmotic Flow Of Viscoelastic Fluid Through A Constriction Microchannel, Jianyu Ji, Shizhi Qian, Zhaohui Liu Jan 2021

Electroosmotic Flow Of Viscoelastic Fluid Through A Constriction Microchannel, Jianyu Ji, Shizhi Qian, Zhaohui Liu

Mechanical & Aerospace Engineering Faculty Publications

Electroosmotic flow (EOF) has been widely used in various biochemical microfluidic applications, many of which use viscoelastic non-Newtonian fluid. This study numerically investigates the EOF of viscoelastic fluid through a 10:1 constriction microfluidic channel connecting two reservoirs on either side. The flow is modelled by the Oldroyd-B (OB) model coupled with the Poisson–Boltzmann model. EOF of polyacrylamide (PAA) solution is studied as a function of the PAA concentration and the applied electric field. In contrast to steady EOF of Newtonian fluid, the EOF of PAA solution becomes unstable when the applied electric field (PAA concentration) exceeds a critical value for …

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Assessment Of Tidal Range Changes In The North Sea From 1958 To 2014, Leon Jänicke, Andra Ebener, Sönke Dangendorf, Arne Arns, Michael Schindelegger, Sebastian Niehüser, Ivan D. Haigh, Philip Woodworth, Jürgen Jensen Jan 2021

Assessment Of Tidal Range Changes In The North Sea From 1958 To 2014, Leon Jänicke, Andra Ebener, Sönke Dangendorf, Arne Arns, Michael Schindelegger, Sebastian Niehüser, Ivan D. Haigh, Philip Woodworth, Jürgen Jensen

CCPO Publications

We document an exceptional large-spatial scale case of changes in tidal range in the North Sea, featuring pronounced trends between -2.3 mm/yr at tide gauges in the United Kingdom and up to 7 mm/yr in the German Bight between 1958 and 2014. These changes are spatially heterogeneous and driven by a superposition of local and large-scale processes within the basin. We use principal component analysis to separate large-scale signals appearing coherently over multiple stations from rather localized changes. We identify two leading principal components (PCs) that explain about 69% of tidal range changes in the entire North Sea including the …

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Contrasting Heat Stress Response Patterns Of Coral Holobionts Across The Red Sea Suggest Distinct Mechanisms Of Thermal Tolerance, Christian R. Voolstra, Jacob J. Valenzuela, Serdar Turkarslan, Anny Cárdenas, Benjamin C.C. Hume, Gabriela Perna, Carol Buitrago-López, Katherine Rowe, Monica V. Orellana, Nitin S. Baliga, Suman Paranjape, Guilhem Banc-Prandi, Jessica Bellworthy, Moaz Fine, Sarah Frias-Torres, Daniel J. Barshis Jan 2021

Contrasting Heat Stress Response Patterns Of Coral Holobionts Across The Red Sea Suggest Distinct Mechanisms Of Thermal Tolerance, Christian R. Voolstra, Jacob J. Valenzuela, Serdar Turkarslan, Anny Cárdenas, Benjamin C.C. Hume, Gabriela Perna, Carol Buitrago-López, Katherine Rowe, Monica V. Orellana, Nitin S. Baliga, Suman Paranjape, Guilhem Banc-Prandi, Jessica Bellworthy, Moaz Fine, Sarah Frias-Torres, Daniel J. Barshis

Biological Sciences Faculty Publications

Corals from the northern Red Sea, in particular the Gulf of Aqaba (GoA), have exceptionally high bleaching thresholds approaching >5℃ above their maximum monthly mean (MMM) temperatures. These elevated thresholds are thought to be due to historical selection, as corals passed through the warmer Southern Red Sea during recolonization from the Arabian Sea. To test this hypothesis, we determined thermal tolerance thresholds of GoA versus central Red Sea (CRS) Stylophora pistillata corals using multi-temperature acute thermal stress assays to determine thermal thresholds. Relative thermal thresholds of GoA and CRS corals were indeed similar and exceptionally high (~7℃ above MMM). However, …

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Evaluation Of Murrell’S Ekf-Based Attitude Estimation Algorithm For Exploiting Multiple Attitude Sensor Configurations, Sharanabasaweshwara Asundi, Norman Fitz-Coy, Haniph Latchman Jan 2021

Evaluation Of Murrell’S Ekf-Based Attitude Estimation Algorithm For Exploiting Multiple Attitude Sensor Configurations, Sharanabasaweshwara Asundi, Norman Fitz-Coy, Haniph Latchman

Mechanical & Aerospace Engineering Faculty Publications

Pico- and nano-satellites, due to their form factor and size, are limited in accommodating multiple or redundant attitude sensors. For such satellites, Murrell's implementation of the extended Kalman filter (EKF) can be exploited to accommodate multiple sensor configurations from a set of non redundant attitude sensors. The paper describes such an implementation involving a sun sensor suite and a magnetometer as attitude sensors. The implementation exploits Murrell's EKF to enable three sensor configurations, which can be operationally commanded, for satellite attitude estimation. Among the three attitude estimation schemes, (i) sun sensor suite and magnetometer, (ii) magnetic field vector and its …

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Digital Twins For Manufacturing And Logistics Systems: Is Simulation Practice Ready?, Francesco Longo, Antonio Padovano, Letizia Nicoletti, Mohaiad Elbasheer, Rafael Diaz Jan 2021

Digital Twins For Manufacturing And Logistics Systems: Is Simulation Practice Ready?, Francesco Longo, Antonio Padovano, Letizia Nicoletti, Mohaiad Elbasheer, Rafael Diaz

VMASC Publications

This article provides a theoretical contribution to the state-of-the-art of digital twins for manufacturing and logistics systems. The primary goal of this paper is to draw attention to the gap between the theoretical framework of digital twins in manufacturing and supply chain and their practical implementation from a simulation modeling point of view. Therefore, highlighting the recent innovations in the simulation practice that could provide the basis for digital twins with high levels of data integration, automation, and smart capabilities. This study follows a comparative approach to analyzing theoretical and technical readiness for developing digital twins with high fidelity and …

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Stable And Convergent Difference Schemes For Weakly Singular Convolution Integrals, Wesley Davis, Richard D. Noren Jan 2021

Stable And Convergent Difference Schemes For Weakly Singular Convolution Integrals, Wesley Davis, Richard D. Noren

Mathematics & Statistics Faculty Publications

We obtain new numerical schemes for weakly singular integrals of convolution type called Caputo fractional order integrals using Taylor and fractional Taylor series expansions and grouping terms in a novel manner. A fractional Taylor series expansion argument is utilized to provide fractional-order approximations for functions with minimal regularity. The resulting schemes allow for the approximation of functions in Cγ [0, T], where 0 < γ <= 5. A mild invertibility criterion is provided for the implicit schemes. Consistency and stability are proven separately for the whole-number-order approximations and the fractional-order approximations. The rate of convergence in the time variable is shown …

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Stock Trend Prediction Using Candlestick Charting And Ensemble Machine Learning Techniques With A Novelty Feature Engineering Scheme, Yaohu Lin, Shancun Liu, Haijun Yang, Harris Wu Jan 2021

Stock Trend Prediction Using Candlestick Charting And Ensemble Machine Learning Techniques With A Novelty Feature Engineering Scheme, Yaohu Lin, Shancun Liu, Haijun Yang, Harris Wu

Information Technology & Decision Sciences Faculty Publications

Stock market forecasting is a knotty challenging task due to the highly noisy, nonparametric, complex and chaotic nature of the stock price time series. With a simple eight-trigram feature engineering scheme of the inter-day candlestick patterns, we construct a novel ensemble machine learning framework for daily stock pattern prediction, combining traditional candlestick charting with the latest artificial intelligence methods. Several machine learning techniques, including deep learning methods, are applied to stock data to predict the direction of the closing price. This framework can give a suitable machine learning prediction method for each pattern based on the trained results. The investment …

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Trends And Opportunities In Tick-Borne Disease Geography, Catherine A. Lippi, Sadie J. Ryan, Alexis L. White, Holly D. Gaff, Colin J. Carlson Jan 2021

Trends And Opportunities In Tick-Borne Disease Geography, Catherine A. Lippi, Sadie J. Ryan, Alexis L. White, Holly D. Gaff, Colin J. Carlson

Biological Sciences Faculty Publications

Tick-borne diseases are a growing problem in many parts of the world, and their surveillance and control touch on challenging issues in medical entomology, agricultural health, veterinary medicine, and biosecurity. Spatial approaches can be used to synthesize the data generated by integrative One Health surveillance systems, and help stakeholders, managers, and medical geographers understand the current and future distribution of risk. Here, we performed a systematic review of over 8,000 studies and identified a total of 303 scientific publications that map tick-borne diseases using data on vectors, pathogens, and hosts (including wildlife, livestock, and human cases). We find that the …

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Near-Infrared And Visible Opacities Of S-Type Stars: The B¹Π—X¹Σ⁺ Band System Of Zro, Jason J. Sorensen, Peter F. Bernath Jan 2021

Near-Infrared And Visible Opacities Of S-Type Stars: The B¹Π—X¹Σ⁺ Band System Of Zro, Jason J. Sorensen, Peter F. Bernath

Chemistry & Biochemistry Faculty Publications

The ZrO B1Π—X1Σ+ transition is an important opacity source in the near-infrared and optical spectrum of S-type stars. The 0–0, 0–1, 0–2, 1–0, 1–2, 1–3, 2–0, 2–1, 2–3, 2–4, 3–1, 3–4, and 4–2 bands of the 90Zr16O B1Π—X1Σ+ transition are reanalyzed using a high-temperature (2390 K) high-resolution (0.04 cm−1) emission spectrum collected at the National Solar Observatory (Kitt Peak). A modern spectroscopic analysis was performed using the PGOPHER program to provide updated spectroscopic constants and to produce a high-precision line list with line strengths based on an …

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Influence Of The Inherent Safety Principles On Quantitative Risk In Process Industry: Application Of Genetic Algorithm Process Optimization (Gapo), Mehdi Jahangiri, Abolfazl Moghadasi, Mojtaba Kamalinia, Farid Sadeghianjahromi, Sean Banaee Jan 2021

Influence Of The Inherent Safety Principles On Quantitative Risk In Process Industry: Application Of Genetic Algorithm Process Optimization (Gapo), Mehdi Jahangiri, Abolfazl Moghadasi, Mojtaba Kamalinia, Farid Sadeghianjahromi, Sean Banaee

Community & Environmental Health Faculty Publications

Inherent safety (IS) refers to a set of measures that enhance the safety level of processes and equipment, rendering additional equipment and/or add-ons. The early design phase of processes is suited best for implementation of IS strategies as some of such strategies either are impossible to be implemented at the operation phase or substantially increase costs. The purpose of this study is to present a new approach called genetic algorithm process optimization (GAPO), by which processes can be made inherently safer even at the operation phase. This study simulates the IS principle, assessing its impact on quantitative risk and the …

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Structual Analysis Of The Cl-Par-4 Tumor Suppressor As A Function Of Ionic Environment, Krishna K. Raut, Komala Ponniah, Steven M. Pascal Jan 2021

Structual Analysis Of The Cl-Par-4 Tumor Suppressor As A Function Of Ionic Environment, Krishna K. Raut, Komala Ponniah, Steven M. Pascal

Chemistry & Biochemistry Faculty Publications

Prostate apoptosis response-4 (Par-4) is a proapoptotic tumor suppressor protein that has been linked to a large number of cancers. This 38 kilodalton (kDa) protein has been shown to be predominantly intrinsically disordered in vitro. In vivo, Par-4 is cleaved by caspase-3 at Asp-131 to generate the 25 kDa functionally active cleaved Par-4 protein (cl-Par-4) that inhibits NF-κB-mediated cell survival pathways and causes selective apoptosis in tumor cells. Here, we have employed circular dichroism (CD) spectroscopy and dynamic light scattering (DLS) to assess the effects of various monovalent and divalent salts upon the conformation of cl-Par-4 in vitro. We have …

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Biolability Of Fresh And Photodegraded Pyrogenic Dissolved Organic Matter From Laboratory-Prepared Chars, K. W. Bostick, A. R. Zimmerman, A. I. Goranov, S. Mitra, P. G. Hatcher, A. S. Wozniak Jan 2021

Biolability Of Fresh And Photodegraded Pyrogenic Dissolved Organic Matter From Laboratory-Prepared Chars, K. W. Bostick, A. R. Zimmerman, A. I. Goranov, S. Mitra, P. G. Hatcher, A. S. Wozniak

Chemistry & Biochemistry Faculty Publications

Pyrogenic dissolved organic matter (pyDOM) is known to be an important biogeochemical constituent of aquatic ecosystems and the carbon cycle. While recent studies have examined how pyDOM production, composition, and photolability varies with parent pyrogenic solid material type, we lack an understanding of potential microbial mineralization and transformation of pyDOM in the biogeosphere. Thus, leachates of oak, charred at 400 °C and 650 °C, as well as their photodegraded counterparts were incubated with a soil‐extracted microbial consortium over 96 days. During the incubation, significantly more carbon was biomineralized from the lower versus higher temperature char leachate (45% vs. 37% lost, …

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A Dual Nanostructured Approach To Sers Substrates Amenable To Large-Scale Production, Kory Brian Castro, Cicely Rathmell, John Cooper Jan 2021

A Dual Nanostructured Approach To Sers Substrates Amenable To Large-Scale Production, Kory Brian Castro, Cicely Rathmell, John Cooper

Chemistry & Biochemistry Faculty Publications

Surface enhanced Raman spectroscopy (SERS), although popular in research, has not yet been adopted in industrial applications. This is largely due to the challenge of manufacturing cost-effective, reproducible SERS substrates in volume that can be read by a compact reader for practical deployment in the field. Here we demonstrate and characterize a new dual-nanostructured SERS substrate approach that could be amenable to large-scale production. This dual-nanostructured surface combines long-range ordering of silver nanowires (AgNWs) with dense non-ordered decoration via silver nanoparticles (AgNPs) to improve on the SERS response characteristics of the individual structures, using fabrication methods that could be scaled …

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Aggregation And Degradation Of Dispersants And Oil By Microbial Exopolymers (Addomex): Toward A Synthesis Of Processes And Pathways Of Marine Oil Snow Formation In Determining The Fate Of Hydrocarbons, Antonietta Quigg, Peter H. Santschi, Chen Xu, Kai Ziervogel, Manoj Kamalanathan, Wei-Chun Chin, Adrian B. Burd, Andrew Wozniak, Patrick G. Hatcher Jan 2021

Aggregation And Degradation Of Dispersants And Oil By Microbial Exopolymers (Addomex): Toward A Synthesis Of Processes And Pathways Of Marine Oil Snow Formation In Determining The Fate Of Hydrocarbons, Antonietta Quigg, Peter H. Santschi, Chen Xu, Kai Ziervogel, Manoj Kamalanathan, Wei-Chun Chin, Adrian B. Burd, Andrew Wozniak, Patrick G. Hatcher

Chemistry & Biochemistry Faculty Publications

Microbes (bacteria, phytoplankton) in the ocean are responsible for the copious production of exopolymeric substances (EPS) that include transparent exopolymeric particles. These materials act as a matrix to form marine snow. After the Deepwater Horizon oil spill, marine oil snow (MOS) formed in massive quantities and influenced the fate and transport of oil in the ocean. The processes and pathways of MOS formation require further elucidation to be better understood, in particular we need to better understand how dispersants affect aggregation and degradation of oil. Toward that end, recent work has characterized EPS as a function of microbial community and …

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