Physical Sciences and Mathematics Commons^™

One-Loop Corrections To Dihadron Production In Dis At Small X, Filip Bergabo

Dissertations, Theses, and Capstone Projects

We calculate the one-loop corrections to dihadron production in Deep Inelastic Scattering (DIS) at small x using the Color Glass Condensate formalism. We show that all UV and soft singularities cancel while the collinear divergences are absorbed into quark and anti quark-hadron fragmentation functions. Rapidity divergences lead to JIMWLK evolution of dipoles and quadrupoles describing multiple-scatterings of the quark anti-quark dipole on the target proton/nucleus. The resulting cross section is finite and can be used for phenomenological studies of dihadron angular correlations at small x in a future Electron-Ion Collider (EIC).

Engineered Plga Nanofibers For Drug Delivery, Andrew Mancuso

Dissertations, Theses, and Capstone Projects

Poly-lactic-co-glycolic acid (PLGA) polymers are rapidly gaining momentum as a platform for next-generation drug delivery systems due to their ease and low cost of synthesis, favorable biocompatibility and biodegradability, and lack of toxicity. In particular, the application of drug-loaded PLGA nanofibers directly to a target tissue may represent a promising alternative to traditional routes of drug administration (e.g., oral, injectable) as they offer the potential to greatly improve bioavailability, increase efficacy, and reduce off-target toxicity. Furthermore, the use of such a system may potentially allow for greater flexibility in clinical drug development, by enabling the use of compounds which have …

Coreflooding Evaluation Of Fiber-Assisted Recrosslinkable Preformed Particle Gel Using An Open Fracture Model, Shuda Zhao, Ali Al Brahim, Junchen Liu, Baojun Bai, Thomas P. Schuman

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Recrosslinkable Preformed Particle Gels (RPPGs) Have Been Used to Treat the Problem of Void Space Conduits (VSC) and repair the "Short-Circuited" Waterflood in Alaska's West Sak Field. Field Results Showed a 23% Increase in Success Rates over Typical Preformed Particle Gel (PPG) Treatments. in This Paper, We Evaluated Whether Adding Fiber into RPPGs Can Increase the RPPG Plugging Efficiency and Thus Further Improve the Success Rate. We Designed Open Fracture Models to Represent vs.C and Investigated the Effect of Swelling Ratio (SR), Fracture Size, and Fiber Concentration on Gel Injection Pressure, Water Breakthrough Pressure, and Permeability Reduction. Results Show that …

Future Aware Pricing And Matching For Sustainable On-Demand Ride Pooling, Xianjie Zhang, Pradeep Varakantham, Hao Jiang

Research Collection School Of Computing and Information Systems

The popularity of on-demand ride pooling is owing to the benefits offered to customers (lower prices), taxi drivers (higher revenue), environment (lower carbon footprint due to fewer vehicles) and aggregation companies like Uber (higher revenue). To achieve these benefits, two key interlinked challenges have to be solved effectively: (a) pricing – setting prices to customer requests for taxis; and (b) matching – assignment of customers (that accepted the prices) to taxis/cars. Traditionally, both these challenges have been studied individually and using myopic approaches (considering only current requests), without considering the impact of current matching on addressing future requests. In this …

Soil Organic Matter Diagenetic State Informs Boreal Forest Ecosystem Feedbacks To Climate Change, Allison N. Myers-Pigg, Karl Kaiser, Ronald Benner, Susan E. Ziegler

Faculty Publications

The fate of soil organic carbon (SOC) in boreal forests is dependent on the integrative ecosystem response to climate change. For example, boreal forest productivity is often nitrogen (N) limited, and climate warming can enhance N cycling and primary productivity. However, the net effect of this feedback on the SOC reservoir and its longevity with climate change remain unclear due to difficulty in detecting small differences between large and variable carbon (C) fluxes needed to determine net changes in soil reservoirs. The diagenetic state of SOC – resulting from the physicochemical and biological transformations that alter the original biomolecular composition …

Wallaby Pilot Survey: H I Gas Kinematics Of Galaxy Pairs In Cluster Environment, Shin-Jeong Kim, Se-Heon Oh, Jing Wang, Lister Staveley-Smith, Bärbel S. Koribalski, Minsu Kim, Hye-Jin Park, Shinna Kim, Kristine Spekkens, Juan P. Madrid

Physics and Astronomy Faculty Publications and Presentations

We examine the H I gas kinematics of galaxy pairs in two clusters and a group using Australian Square Kilometre Array Pathfinder (ASKAP) WALLABY pilot survey observations. We compare the H I properties of galaxy pair candidates in the Hydra I and Norma clusters, and the NGC 4636 group, with those of non-paired control galaxies selected in the same fields. We perform H I profile decomposition of the sample galaxies using a tool, BAYGAUD, which allows us to deblend a line-of-sight velocity profile with an optimal number of Gaussian components. We construct H I superprofiles of the sample galaxies via …

Cross-Domain Graph Anomaly Detection Via Anomaly-Aware Contrastive Alignment, Qizhou Wang, Guansong Pang, Mahsa Salehi, Wray Buntine, Christopher Leckie

Research Collection School Of Computing and Information Systems

Cross-domain graph anomaly detection (CD-GAD) describes the problem of detecting anomalous nodes in an unlabelled target graph using auxiliary, related source graphs with labelled anomalous and normal nodes. Although it presents a promising approach to address the notoriously high false positive issue in anomaly detection, little work has been done in this line of research. There are numerous domain adaptation methods in the literature, but it is difficult to adapt them for GAD due to the unknown distributions of the anomalies and the complex node relations embedded in graph data. To this end, we introduce a novel domain adaptation approach, …

Optimized Peptide Nanomaterials As Delivery Vehicles For Hydrophobic Metal-Based Anticancer Agents, Yaron Marciano

Dissertations, Theses, and Capstone Projects

Enzyme-responsive materials have been well explored, particularly as therapeutic and diagnostic agents. In this thesis we demonstrate that anionic self-assembling peptides can be utilized as delivery vehicles for metal-based hydrophobic payloads. The tunability of the system is highlighted as well as the increase in cytotoxicity and selectivity in vitro. The rapid degradation of peptides in cell media may lead to the formation of new peptide-drug bioconjugates with increased activity and selectivity. The physiological stability of these peptide delivery vehicles has been optimized by capping the N-terminus with an acetyl group. This simple backbone modification was shown to not prevent self-assembly, …

Revealing The Three-Dimensional Magnetic Texture With Machine Learning Models, Shihua Zhao

Dissertations, Theses, and Capstone Projects

Revealing three-dimensional (3D) magnetic textures with vector field electron tomography (VFET) is essential in studying novel magnetic materials with topologically protected spin textures potentially being used in the next-generation semiconductor industry. In this dissertation, we use machine learning (ML) models to reconstruct 3D magnetic textures from electron holography (EH) data.

We can feed the EH data, a series of two-dimensional (2D) phasemaps, into a neural network (NN) architecture directly or feed the EH data into a conventional VFET and then feed the reconstructed results into a NN. Thus, perceptive NN, either a simple convolutional neural network (CNN) or Unet architecture, …

Coloring Complexes And Combinatorial Hopf Monoids, Jacob A. White

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

We generalize the notion of a coloring complex of a graph to linearized combinatorial Hopf monoids. We determine when a linearized combinatorial Hopf monoid has such a construction, and discover some inequalities that are satisfied by the quasisymmetric function invariants associated to the combinatorial Hopf monoid. We show that the collection of all such coloring complexes forms a linearized combinatorial Hopf monoid, which is the terminal object in the category of combinatorial Hopf monoids with convex characters. We also study several examples of combinatorial Hopf monoids.

Combinatorial Identities Associated With A Bivariate Generating Function For Overpartition Pairs, Atul Dixit, Ankush Goswami

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

We obtain a three-parameter q-series identity that generalizes two results of Chan and Mao. By specializing our identity, we derive new results of combinatorial significance in connection with N(r,s,m,n), a function counting certain overpartition pairs recently introduced by Bringmann, Lovejoy and Osburn. For example, one of our identities gives a closed-form evaluation of a double series in terms of Chebyshev polynomials of the second kind, thereby resulting in an analogue of Euler's pentagonal number theorem. Another of our results expresses a multi-sum involving N(r,s,m,n) in terms of just the partition function p(n). Using a result of Shimura we also relate …

On Viscoelastic Fiber Jet Formation By Forcespinning At High Rotation Rate, Daniel N. Riahi, Saulo Orizaga

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

We consider a nonlinear three-dimensional viscoelastic fiber jet that is generated during a forcespinning process. We provide a particular case for such a rotating jet at a high rotation rate. We use a viscoelastic constitutive model for the jet equations and then applying a new slender body approach, we continue with proper scaling and perturbation technique to develop a new model for such a jet system. We find that the profiles for jet quantities versus arc length are notably different from all those in related studies reported before for either high or low rotation rates. In particular, jet radius first …

Effective Graph Kernels For Evolving Functional Brain Networks, Xinlei Wang, Jinyi Chen, Bing Tian Dai, Junchang Xin, Yu Gu, Ge Yu

Research Collection School Of Computing and Information Systems

The graph kernel of the functional brain network is an effective method in the field of neuropsychiatric disease diagnosis like Alzheimer's Disease (AD). The traditional static brain networks cannot reflect dynamic changes of brain activities, but evolving brain networks, which are a series of brain networks over time, are able to seize such dynamic changes. As far as we know, the graph kernel method is effective for calculating the differences among networks. Therefore, it has a great potential to understand the dynamic changes of evolving brain networks, which are a series of chronological differences. However, if the conventional graph kernel …

Planning And Learning For Non-Markovian Negative Side Effects Using Finite State Controllers, Aishwarya Srivastava, Sandhya Saisubramanian, Praveen Paruchuri, Akshat Kumar, Shlomo Zilberstein

Research Collection School Of Computing and Information Systems

Autonomous systems are often deployed in the open world where it is hard to obtain complete specifications of objectives and constraints. Operating based on an incomplete model can produce negative side effects (NSEs), which affect the safety and reliability of the system. We focus on mitigating NSEs in environments modeled as Markov decision processes (MDPs). First, we learn a model of NSEs using observed data that contains state-action trajectories and severity of associated NSEs. Unlike previous works that associate NSEs with state-action pairs, our framework associates NSEs with entire trajectories, which is more general and captures non-Markovian dependence on states …

On Generalized Degree Fairness In Graph Neural Networks, Zemin Liu, Trung Kien Nguyen, Yuan Fang

Research Collection School Of Computing and Information Systems

Conventional graph neural networks (GNNs) are often confronted with fairness issues that may stem from their input, including node attributes and neighbors surrounding a node. While several recent approaches have been proposed to eliminate the bias rooted in sensitive attributes, they ignore the other key input of GNNs, namely the neighbors of a node, which can introduce bias since GNNs hinge on neighborhood structures to generate node representations. In particular, the varying neighborhood structures across nodes, manifesting themselves in drastically different node degrees, give rise to the diverse behaviors of nodes and biased outcomes. In this paper, we first define …

Pose- And Attribute-Consistent Person Image Synthesis, Cheng Xu, Zejun Chen, Jiajie Mai, Xuemiao Xu, Shengfeng He

Research Collection School Of Computing and Information Systems

PersonImageSynthesisaimsattransferringtheappearanceofthesourcepersonimageintoatargetpose. Existingmethods cannot handle largeposevariations and therefore suffer fromtwocritical problems: (1)synthesisdistortionduetotheentanglementofposeandappearanceinformationamongdifferentbody componentsand(2)failureinpreservingoriginalsemantics(e.g.,thesameoutfit).Inthisarticle,weexplicitly addressthesetwoproblemsbyproposingaPose-andAttribute-consistentPersonImageSynthesisNetwork (PAC-GAN).Toreduceposeandappearancematchingambiguity,weproposeacomponent-wisetransferring modelconsistingoftwostages.Theformerstagefocusesonlyonsynthesizingtargetposes,whilethelatter renderstargetappearancesbyexplicitlytransferringtheappearanceinformationfromthesourceimageto thetargetimageinacomponent-wisemanner. Inthisway,source-targetmatchingambiguityiseliminated duetothecomponent-wisedisentanglementofposeandappearancesynthesis.Second,tomaintainattribute consistency,werepresenttheinputimageasanattributevectorandimposeahigh-levelsemanticconstraint usingthisvectortoregularizethetargetsynthesis.ExtensiveexperimentalresultsontheDeepFashiondataset demonstratethesuperiorityofourmethodoverthestateoftheart,especiallyformaintainingposeandattributeconsistenciesunderlargeposevariations.

Lightweight And Non-Invasive User Authentication On Earables, Changshuo Hu, Xiao Ma, Dong Ma, Ting Dang

Research Collection School Of Computing and Information Systems

The widespread adoption of wireless earbuds has advanced the developments in earable-based sensing in various domains like entertainment, human-computer interaction, and health monitoring. Recently, researchers have shown an increased interest in user authentication using earables. Despite the successes witnessed in acoustic probing and speech based authentication systems, this paper proposed a lightweight and non-invasive ambient sound based user authentication scheme. It employs the difference between the in-ear and out-ear sounds to estimate the individual-specific occluded ear canal transfer function (OECTF). Specifically, the {out-ear, in-ear} scaling factors at different frequency bands are captured via linear regression and treated as the OECTF …

The Gender Wage Gap In An Online Labor Market: The Cost Of Interruptions, Abi Adams-Prassl, Kotaro Hara, Kristy Milland, Chris Callison-Burch

Research Collection School Of Computing and Information Systems

This paper analyses gender differences in working patterns and wages on Amazon Mechanical Turk, a popular online labour platform. Using information on 2 million tasks, we find no gender differences in task selection nor experience. Nonetheless, women earn 20% less per hour on average. Gender differences in working patterns are a significant driver of this wage gap. Women are more likely to interrupt their working time on the platform with consequences for their task completion speed. A follow-up survey shows that the gender differences in working patterns and hourly wages are concentrated amongst workers with children.

A Fair Incentive Scheme For Community Health Workers, Avinandan Bose, Tracey Li, Arunesh Sinha, Tien Mai

Research Collection School Of Computing and Information Systems

Community health workers (CHWs) play a crucial role in the last mile delivery of essential health services to under-served populations in low-income countries. Many non-governmental organizations (NGOs) provide training and support to enable CHWs to deliver health services to their communities, with no charge to the recipients of the services. This includes monetary compensation for the work that CHWs perform, which is broken down into a series of well-defined tasks. In this work, we partner with a NGO D-Tree International to design a fair monetary compensation scheme for tasks performed by CHWs in the semi-autonomous region of Zanzibar in Tanzania, …

An Empirical Study Of Package Management Issues Via Stack Overflow, Syful Islam, Raula Kula, Christoph Treude, Bodin Chinthanet, Takashi Ishio, Kenichi Matsumoto

Research Collection School Of Computing and Information Systems

The package manager (PM) is crucial to most technology stacks, acting as a broker to ensure that a verified dependency package is correctly installed, configured, or removed from an application. Diversity in technology stacks has led to dozens of PMs with various features. While our recent study indicates that package management features of PM are related to end-user experiences, it is unclear what those issues are and what information is required to resolve them. In this paper, we have investigated PM issues faced by end-users through an empirical study of content on Stack Overflow (SO). We carried out a qualitative …

Safe Delivery Of Critical Services In Areas With Volatile Security Situation Via A Stackelberg Game Approach, Tien Mai, Arunesh Sinha

Research Collection School Of Computing and Information Systems

Vaccine delivery in under-resourced locations with security risks is not just challenging but also life threatening. The COVID pandemic and the need to vaccinate added even more urgency to this issue. Motivated by this problem, we propose a general framework to set-up limited temporary (vaccination) centers that balance physical security and desired (vaccine) service coverage with limited resources. We set-up the problem as a Stackelberg game between the centers operator (defender) and an adversary, where the set of centers is not fixed a priori but is part of the decision output. This results in a mixed combinatorial and continuous optimization …

Constrained Reinforcement Learning In Hard Exploration Problems, Pankayaraj Pathmanathan, Pradeep Varakantham

Research Collection School Of Computing and Information Systems

One approach to guaranteeing safety in Reinforcement Learning is through cost constraints that are imposed on trajectories. Recent works in constrained RL have developed methods that ensure constraints can be enforced even at learning time while maximizing the overall value of the policy. Unfortunately, as demonstrated in our experimental results, such approaches do not perform well on complex multi-level tasks, with longer episode lengths or sparse rewards. To that end, wepropose a scalable hierarchical approach for constrained RL problems that employs backward cost value functions in the context of task hierarchy and a novel intrinsic reward function in lower levels …

Solving Large-Scale Pursuit-Evasion Games Using Pre-Trained Strategies, Shuxin Li, Xinrun Wang, Youzhi Zhang, Wanqi Xue, Jakub Cerny, Bo An

Research Collection School Of Computing and Information Systems

Pursuit-evasion games on graphs model the coordination of police forces chasing a fleeing felon in real-world urban settings, using the standard framework of imperfect-information extensive-form games (EFGs). In recent years, solving EFGs has been largely dominated by the Policy-Space Response Oracle (PSRO) methods due to their modularity, scalability, and favorable convergence properties. However, even these methods quickly reach their limits when facing large combinatorial strategy spaces of the pursuit-evasion games. To improve their efficiency, we integrate the pre-training and fine-tuning paradigm into the core module of PSRO -- the repeated computation of the best response. First, we pre-train the pursuer's …

Organic–Inorganic Manganese (Ii) Halide Hybrid Combining The Two Isomers Cis/Trans Of [Mncl4(H2o)2]: Crystal Structure, Physical Properties, Pharmacokinetics And Biological Evaluation, Mansoura Bourwina, Sandra Walha, Najeh Krayem, Riadh Badraoui, Faten Brahmi, Mark M. Turnbull, Wejdan M. Alshammari, Mejdi Snoussi, Thierry Roisnel, Houcine Naïli

Chemistry

A manganese (II) complex templated by hexahydro-1,4-diazepinediium as a counter ion was grown by slow evaporation from an aqueous solution at room temperature. The X-ray diffraction analysis revealed that the compound (C₅H₁₄N₂)[MnCl₄(H₂O)₂] crystallizes in the centrosymmetric space group P2/c of the monoclinic system. The crystal structure of the Mn(II) complex is characterized by an alternation of 0-dimensional organic and inorganic stacks linked together by N/O-H…Cl and N-H…O hydrogen bonds, which lead to a three-dimensional supramolecular architecture. In this structure, the inorganic layer is built up by independent anionic …

Working With (Not Against) The Technology: Gpt3 And Artificial Intelligence (Ai) In College Composition, James Hutson, Daniel Plate

Faculty Scholarship

The use of artificial intelligence (AI) for improvement of writing is commonplace with word-processing software and cloudbased writing assistants such as Grammarly and Microsoft Word. However, more and more options are cropping up that move beyond assistance with grammar, spelling, and punctuation to complete essay generation. The free availability of AI essay generators has led to lamenting the coming death of college writing. But AI has been used in the previously noted examples for decades without such a reaction. In fact, the idea that the use of essay generating software is synonymous with academic dishonesty is as passé as worries …

The Use And Challenges Of Spatial Data In Archaeology, Carla Klehm

Anthropology Faculty Publications and Presentations

Spatial data, under the broader umbrella of digital data, is becoming increasingly integral to all stages of archaeological research design and dissemination. As archaeologists lean toward reuse and interoperability, with ethics on their minds, how to treat spatial data is of particular importance. This is because of the complexities involved at every life-cycle stage, from collection to publication, including black box issues that may be taken for granted, and because the size of spatial data can lead to archiving difficulties. Here, the “DIY” momentum of increasingly accessible spatial methods such as photogrammetry and handheld lidar is examined alongside forthcoming changes …

Alignment-Enriched Tuning For Patch-Level Pre-Trained Document Image Models, Lei Wang, Jiabang He, Xing Xu, Ning Liu, Hui Liu

Research Collection School Of Computing and Information Systems

Alignment between image and text has shown promising im provements on patch-level pre-trained document image mod els. However, investigating more effective or finer-grained alignment techniques during pre-training requires a large amount of computation cost and time. Thus, a question natu rally arises: Could we fine-tune the pre-trained models adap tive to downstream tasks with alignment objectives and achieve comparable or better performance? In this paper, we pro pose a new model architecture with alignment-enriched tuning (dubbed AETNet) upon pre-trained document image models, to adapt downstream tasks with the joint task-specific super vised and alignment-aware contrastive objective. Specifically, weintroduce an extra …

The Effects Of Robot Voices And Appearances On Users' Emotion Recognition And Subjective Perception, Sangjin Ko, Jaclyn A. Barnes, Jiayuan Dong, Chung Hyuk Park, Ayanna Howard, Myounghoon Jeon

Michigan Tech Publications

As the influence of social robots in people's daily lives grows, research on understanding people's perception of robots including sociability, trust, acceptance, and preference becomes more pervasive. Research has considered visual, vocal, or tactile cues to express robots' emotions, whereas little research has provided a holistic view in examining the interactions among different factors influencing emotion perception. We investigated multiple facets of user perception on robots during a conversational task by varying the robots' voice types, appearances, and emotions. In our experiment, 20 participants interacted with two robots having four different voice types. While participants were reading fairy tales to …

Effects Of Supply Chain Transparency, Alignment, Adaptability, And Agility On Blockchain Adoption In Supply Chain Among Smes, Mohammad Iranmanesh, Parisa Maroufkhani, Shahla Asadi, Morteza Ghobakhloo, Yogesh K. Dwivedi, Ming-Lang Tseng

Research outputs 2022 to 2026

This study aims to investigate the extent to which the contributions of blockchain technology to supply chain parameters influence blockchain adoption among SMEs. Drawing on contingency theory, the study investigates the moderating effect of market turbulence. The data were collected from 204 SMEs in Malaysia's manufacturing sector and analysed using the partial least squares technique. The results showed that the intention of SMEs’ managers to adopt blockchain is influenced by the contributions of blockchain to supply chain transparency and agility. Supply chain transparency, alignment, adaptability, and agility are interrelated. Market turbulence moderates positively the association between agility and intention to …

Deep Feature Meta-Learners Ensemble Models For Covid-19 Ct Scan Classification, Jibin B. Thomas, K. V. Shihabudheen, Sheik Mohammed Sulthan, Adel Al-Jumaily

Research outputs 2022 to 2026

The infectious nature of the COVID-19 virus demands rapid detection to quarantine the infected to isolate the spread or provide the necessary treatment if required. Analysis of COVID-19-infected chest Computed Tomography Scans (CT scans) have been shown to be successful in detecting the disease, making them essential in radiology assessment and screening of infected patients. Single-model Deep CNN models have been used to extract complex information pertaining to the CT scan images, allowing for in-depth analysis and thereby aiding in the diagnosis of the infection by automatically classifying the chest CT scan images as infected or non-infected. The feature maps …