Physical Sciences and Mathematics Commons^™

Drinking Water Contaminants: Lead, Bruce I. Dvorak, Becky M. Schuerman

Department of Civil and Environmental Engineering: Faculty Publications

Any lead exposure, even low levels, can be a serious health concern, especially for infants, children, and developing fetuses. This NebGuide discusses how to safely manage lead in a domestic water supply (or often referred to as a private well). This NebGuide includes discussion related to topics such as lead services lines and changes in public water supply regulations related to lead in drinking water.

Thermal, Magnetic, And Electrical Properties Of Thin Films And Nanostructures: From Magnetic Insulators To Organic Thermoelectrics, Michael J. M. Roos

Electronic Theses and Dissertations

Modern fabrication and growth techniques allow for the development of increasingly smaller and more complex solid state structures, the characterization of which require highly specialized measurement platforms. In this dissertation I present the development of techniques and instrumentation used in magnetic, thermal, and electrical property measurements of thin films and nanostructures. The understanding of trapped-flux induced artifacts in SQUID magnetometry of large paramagnetic substrates allows for the resolution of increasingly small moments. Using these methods, the antiferromagnetic coupling of the interface between a Y₃Fe₅O₁₂ film and Gd₃Ga₅O₁₂substrate is quantitatively …

Copper-Indazolate Nanojars: Synthesis And Characterization, Nicholas Alexander Rudell

Masters Theses

The field of synthetic supramolecular chemistry has exploded since the first syntheses of crown ethers by Charles Pedersen in the 1960s, leading to further development in the area of macrocycles and incorporation into a vast array of metal-organic structures. Supramolecular chemistry came to the forefront of science with the 1987 Nobel Prize in Chemistry, awarded jointly to Donald J. Cram, Jean-Marie Lehn, and Charles Pedersen “for their development and use of molecules with structure-specific interactions of high selectivity.”

Nanojars are supramolecular metal-organic complexes with a high affinity for hydrophilic anions and can efficiently transfer such anions from water into organic …

What Is The Mathematics In Mathematics Education?, Eva Thanheiser

Mathematics and Statistics Faculty Publications and Presentations

In this paper I tackle the question What is the mathematics in mathematics education? By providing three different frames for the word mathematics.

1.

Frame 1: Mathematics as an abstract body of knowledge/ideas, the organization of that into systems and structures, and a set of methods for reaching conclusions.

2.

Frame 2: Mathematics as contextual, ever present, as a lens or language to make sense of the world.

3.

Frame 3: Mathematics as a verb (not a noun), a human activity, part of one’s identity.

After introducing the frames and examining their distinction and their overlap, I discuss their implication …

End-To-End Gpu Acceleration Of Low-Order-Refined Preconditioning For High-Order Finite Element Discretizations, Will Pazner, Tzanio Kolev, Jean-Sylvain Camier

Mathematics and Statistics Faculty Publications and Presentations

In this article, we present algorithms and implementations for the end-to-end GPU acceleration of matrix-free low-order-refined preconditioning of high-order finite element problems. The methods described here allow for the construction of effective preconditioners for high-order problems with optimal memory usage and computational complexity. The preconditioners are based on the construction of a spectrally equivalent low-order discretization on a refined mesh, which is then amenable to, for example, algebraic multigrid preconditioning. The constants of equivalence are independent of mesh size and polynomial degree. For vector finite element problems in H(curl) and H(div) (e.g., for electromagnetic or radiation diffusion problems), …

Search For Low-Mass Dark Matter Via Bremsstrahlung Radiation And The Migdal Effect In Supercdms, M. F. Albakry, I. Alkhatib, D. Alonso-González, D. W.P. Amaral, T. Aralis, T. Aramaki, I. J. Arnquist, I. Ataee Langroudy, E. Azadbakht, S. Banik, C. Bathurst, R. Bhattacharyya, P. L. Brink, R. Bunker, B. Cabrera, R. Calkins, R. A. Cameron, C. Cartaro, D. G. Cerdeño, Y. Y. Chang, M. Chaudhuri, R. Chen, N. Chott, J. Cooley, H. Coombes, J. Corbett, P. Cushman, S. Das

All Works

We present a new analysis of previously published SuperCDMS data using a profile likelihood framework to search for sub-GeV dark matter (DM) particles through two inelastic scattering channels: bremsstrahlung radiation and the Migdal effect. By considering these possible inelastic scattering channels, experimental sensitivity can be extended to DM masses that are undetectable through the DM-nucleon elastic scattering channel, given the energy threshold of current experiments. We exclude DM masses down to 220 MeV/c2 at 2.7×10-30 cm2 via the bremsstrahlung channel. The Migdal channel search provides overall considerably more stringent limits and excludes DM masses down to 30 MeV/c2 at 5.0×10-30 …

Weird Winter Weather In The Anthropocene: How Volatile Temperatures Shape Violent Crime, Christopher Thomas, Kevin T. Wolff

Publications and Research

Purpose: Current evidence suggests volatile temperatures are becoming more common because of climate change and can be expected to become even more frequent in the future. By focusing on recent temperature variability, we attempt to estimate one important dimension of the impact of climate change on violent crime. We also explore whether sudden upward temperature anomalies have stronger positive impacts on violent crime in the coldest months of the year, as routine activities are likely to change more drastically during this period.

Methods: This study explores the association between sudden temperature anomalies (both upward and downward) and the daily incidence …

The Effect Of The Carbon Nanotubes’ Surface Area On The Morphology And Performance Of Cellulose Acetate Nanocomposite Membranes In Nanofiltration Applications, Nouran Elbadawi

Theses and Dissertations

Population increase and climate change have significantly affected the availability of fresh water for consumption. Studies by UNESCO showed that more than 28% of the world population didn’t have access to clean safe drinking water in 2020. This situation is expected to get more serious over the coming 30 years with the limited availability of natural fresh water sources. The need to find solutions from alternative non-freshwater resources for drinking or irrigation is becoming a necessity. Within the context of desalination technologies, thousands of investigations are conducted to find the cheapest most efficient way of water treatment aiming at expanding …

Strategic Planning For Flexible Agent Availability In Large Taxi Fleets, Rajiv Ranjan Kumar, Pradeep Varakantham, Shih-Fen Cheng

Research Collection School Of Computing and Information Systems

In large scale multi-agent systems like taxi fleets, individual agents (taxi drivers) are self interested (maximizing their own profits) and this can introduce inefficiencies in the system. One such inefficiency is with regards to the "required" availability of taxis at different time periods during the day. Since a taxi driver can work for limited number of hours in a day (e.g., 8-10 hours in a city like Singapore), there is a need to optimize the specific hours, so as to maximize individual as well as social welfare. Technically, this corresponds to solving a large scale multi-stage selfish routing game with …

Towards Explaining Sequences Of Actions In Multi-Agent Deep Reinforcement Learning Models, Phyo Wai Khaing, Minghong Geng, Budhitama Subagdja, Shubham Pateria, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Although Multi-agent Deep Reinforcement Learning (MADRL) has shown promising results in solving complex real-world problems, the applicability and reliability of MADRL models are often limited by a lack of understanding of their inner workings for explaining the decisions made. To address this issue, this paper proposes a novel method for explaining MADRL by generalizing the sequences of action events performed by agents into high-level abstract strategies using a spatio-temporal neural network model. Specifically, an interval-based memory retrieval procedure is developed to generalize the encoded sequences of action events over time into short sequential patterns. In addition, two abstraction algorithms are …

Unbiased Multiple Instance Learning For Weakly Supervised Video Anomaly Detection, Hui Lyu, Zhongqi Yue, Qianru Sun, Bin Luo, Zhen Cui, Hanwang Zhang

Research Collection School Of Computing and Information Systems

Weakly Supervised Video Anomaly Detection (WSVAD) is challenging because the binary anomaly label is only given on the video level, but the output requires snippet-level predictions. So, Multiple Instance Learning (MIL) is prevailing in WSVAD. However, MIL is notoriously known to suffer from many false alarms because the snippet-level detector is easily biased towards the abnormal snippets with simple context, confused by the normality with the same bias, and missing the anomaly with a different pattern. To this end, we propose a new MIL framework: Unbiased MIL (UMIL), to learn unbiased anomaly features that improve WSVAD. At each MIL training …

Evading Deepfake Detectors Via Adversarial Statistical Consistency, Yang Hou, Qing Guo, Yihao Huang, Xiaofei Xie, Lei Ma, Jianjun Zhao

Research Collection School Of Computing and Information Systems

In recent years, as various realistic face forgery techniques known as DeepFake improves by leaps and bounds, more and more DeepFake detection techniques have been proposed. These methods typically rely on detecting statistical differences between natural (i.e., real) and DeepFake-generated images in both spatial and frequency domains. In this work, we propose to explicitly minimize the statistical differences to evade state-of-the-art DeepFake detectors. To this end, we propose a statistical consistency attack (StatAttack) against DeepFake detectors, which contains two main parts. First, we select several statistical-sensitive natural degradations (i.e., exposure, blur, and noise) and add them to the fake images …

Groundnlq @ Ego4d Natural Language Queries Challenge 2023, Zhijian Hou, Lei Ji, Difei Gao, Wanjun Zhong, Kun Yan, Chong-Wah Ngo, Wing-Kwong Chan, Chong-Wah Ngo, Nan Duan, Mike Zheng Shou

Research Collection School Of Computing and Information Systems

In this report, we present our champion solution for Ego4D Natural Language Queries (NLQ) Challenge in CVPR 2023. Essentially, to accurately ground in a video, an effective egocentric feature extractor and a powerful grounding model are required. Motivated by this, we leverage a two-stage pre-training strategy to train egocentric feature extractors and the grounding model on video narrations, and further fine-tune the model on annotated data. In addition, we introduce a novel grounding model GroundNLQ, which employs a multi-modal multiscale grounding module for effective video and text fusion and various temporal intervals, especially for long videos. On the blind test …

Ifundit: Visual Profiling Of Fund Investment Styles, Rong Zhang, Bon Kyung Ku, Yong Wang, Xuanwu Yue, Siyuan Liu, Ke Li, Huamin Qu

Research Collection School Of Computing and Information Systems

Mutual funds are becoming increasingly popular with the emergence of Internet finance. Clear profiling of a fund's investment style is crucial for fund managers to evaluate their investment strategies, and for investors to understand their investment. However, it is challenging to profile a fund's investment style as it requires a comprehensive analysis of complex multi-dimensional temporal data. In addition, different fund managers and investors have different focuses when analysing a fund's investment style. To address the issue, we propose iFUNDit, an interactive visual analytic system for fund investment style analysis. The system decomposes a fund's critical features into performance attributes …

Distpreserv: Maintaining User Distribution For Privacy-Preserving Location-Based Services, Yanbing Ren, Xinghua Li, Yinbin Miao, Robert H. Deng, Jian Weng, Siqi Ma, Jianfeng Ma

Research Collection School Of Computing and Information Systems

Location-Based Services (LBSs) are one of the most frequently used mobile applications in the modern society. Geo-Indistinguishability (Geo-Ind) is a promising privacy protection model for LBSs since it can provide formal security guarantees for location privacy. However, Geo-Ind undermines the statistical location distribution of users on the LBS server because of perturbed locations, thereby disabling the server to provide distribution-based services (e.g., traffic congestion maps). To overcome this issue, we give a privacy definition, called DistPreserv, to enable the LBS server to acquire valid location distributions while providing users with strict location protection. Then we propose a privacy-preserving LBS scheme …

Gnnlens: A Visual Analytics Approach For Prediction Error Diagnosis Of Graph Neural Networks., Zhihua Jin, Yong Wang, Qianwen Wang, Yao Ming, Tengfei Ma, Huamin Qu

Research Collection School Of Computing and Information Systems

Graph Neural Networks (GNNs) aim to extend deep learning techniques to graph data and have achieved significant progress in graph analysis tasks (e.g., node classification) in recent years. However, similar to other deep neural networks like Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs), GNNs behave like a black box with their details hidden from model developers and users. It is therefore difficult to diagnose possible errors of GNNs. Despite many visual analytics studies being done on CNNs and RNNs, little research has addressed the challenges for GNNs. This paper fills the research gap with an interactive visual analysis …

A System Dynamics Approach To Evaluate Advanced Persistent Threat Vectors, Mathew Nicho, Christopher D. Mcdermott, Hussein Fakhry, Shini Girija

All Works

Cyber-attacks targeting high-profile entities are focused, persistent, and employ common vectors with varying levels of sophistication to exploit social-technical vulnerabilities. Advanced persistent threats (APTs) deploy zero-day malware against such targets to gain entry through multiple security layers, exploiting the dynamic interplay of vulnerabilities in the target network. System dynamics (SD) offers an alternative approach to analyze non-linear, complex, and dynamic social-technical systems. This research applied SD to three high-profile APT attacks - Equifax, Carphone, and Zomato - to identify and simulate socio-technical variables leading to breaches. By modeling APTs using SD, managers can evaluate threats, predict attacks, and reduce damage …

Generative Ai Tools In Art Education: Exploring Prompt Engineering And Iterative Processes For Enhanced Creativity, James Hutson, Peter Cotroneo

Faculty Scholarship

The rapid development and adoption of generative artificial intelligence (AI) tools in the art and design education landscape have introduced both opportunities and challenges. This timely study addresses the need to effectively integrate these tools into the classroom while considering ethical implications and the importance of prompt engineering. By examining the iterative process of refining original ideas through multiple iterations, verbal expansion, and the use of OpenAI’s DALL E2 for generating diverse visual outcomes, researchers gain insights into the potential benefits and pitfalls of these tools in an educational context. Students in the digital at case study were taught prompt …

Beyond Covid-19: Designing Inclusive Public Health Surveillance By Including Wastewater Monitoring., Rochelle H. Holm, Na'taki Osborne Jelks, Rebecca Schneider, Ted Smith

Faculty and Staff Scholarship

Wastewater-based epidemiology is a promising and expanding public health surveillance method. The current wastewater testing trajectory to monitor primarily at community wastewater treatment plants was necessitated by immediate needs of the pandemic. Going forward, specific consideration should be given to monitoring vulnerable and underserved communities to ensure inclusion and rapid response to public health threats. This is particularly important when clinical testing data are insufficient to characterize community virus levels and spread in specific locations. Now is a timely call to action for equitably protecting health in the United States, which can be guided with intentional and inclusive wastewater monitoring.

Flow Patterns For Newtonian And Non-Newtonian Fluids In A Cylindrical Pipe, Erick Sanchez, Dambaru Bhatta

School of Mathematical & Statistical Sciences Faculty Publications

A fully developed laminar steady flow of an incompressible, viscous fluid in a horizontal cylindrical pipe is considered here. Flow patterns for an incompressible, viscous fluid for both Newtonian and non-Newtonian fluids such as shear-thinning, shear-thickening and Bingham plastic fluids are analyzed in this study. Assuming that the flow is only due to the wall shear stress and the pressure drop, the velocity component in the axial direction for these cases is derived. Computational results of the velocity profiles for various cases are obtained using MATLAB and presented in graphical forms. It is observed that the velocity profile is parabolic …

Calculating Carbon: Calculate The Carbon Emissions From Your Farm Business, Department Of Primary Industries And Regional Development, Western Australia

Climate science factsheets

Farming systems produce greenhouse gas (GHG) emissions, primarily in the form of methane (mostly caused by animal digestion and respiration) and nitrous oxide (mostly from fertilisers).

The Department of Primary Industries and Regional Development (DPIRD) recommend undertaking a basic carbon account to understand and explore options to reduce your emissions and consider which approaches will fit into your business plan. A baseline carbon account for your farm will give the total GHG emissions for the farm and the carbon intensity of your products such as wool, meat and grain.

What’S Scope 3 Good For?, Madison Condon

Faculty Scholarship

Opposition to the Securities and Exchange Commission’s (“SEC”) new rule on updated climate risk reporting has focused on one category of disclosures as particularly objectionable: Scope 3 emissions.⁷ Otherwise known as “supply chain emissions,” Scope 3 emissions have been voluntarily reported by a growing number of companies since the term was invented as part of the Greenhouse Gas Protocol in 2001.⁸ They include all the emissions both up and downstream of a corporations’ own activities: the emissions of the privately-owned factory that produced the shoes Target sells, as well as the emissions you burn while driving to the …

Perturbative Aspects Of Cpt-Even Lorentz-Violating Scalar Chromodynamics, Brett Altschul, L. C.T. Brito, J. C.C. Felipe, S. Karki, A. C. Lehum, A. Yu Petrov

Faculty Publications

In this work, we formulate the theory of Lorentz-violating scalar quantum chromodynamics with an arbitrary non-Abelian gauge group. This theory belongs to the class of models encompassed by the standard model extension framework. At the lowest order in the theory's Lorentz violation parameters, we calculate the divergent quantum corrections, including the renormalization group β-functions of the theory. The Lorentz-violating sector is shown to be scale invariant if there is a particular relation between the couplings.

Estimation Of Quantitative Genetic Parameters Of The Eastern Oyster (Crassostrea Virginica) In The Gulf Of Mexico, Heather King

Master's Theses

The decline of natural oyster reefs in Gulf of Mexico (Gulf) states has stimulated the development of aquaculture to support the industry and restoration programs. Gulf habitats feature diverse salinity environments that may require oysters bred for habitat-specific optimal genetic characteristics. In this work, genetic parameters for performance in habitats with different salinity were estimated. In September 2020, 102 males and 102 females sourced from 17 natural reefs across the northern Gulf were bred according to 2 males x 2 females non-overlapping factorial crossing designs, resulting in 204 full and half sibs. All families were pooled after fertilization according to …

Gradient-Based Trade-Off Design For Engineering Applications, Lena A. Royster, Gene Hou

Mechanical & Aerospace Engineering Faculty Publications

The goal of the trade-off design method presented in this study is to achieve newly targeted performance requirements by modifying the current values of the design variables. The trade-off design problem is formulated in the framework of Sequential Quadratic Programming. The method is computationally efficient as it is gradient-based, which, however, requires the performance functions to be differentiable. A new equation to calculate the scale factor to control the size of the design variables is introduced in this study, which can ensure the new design achieves the targeted performance objective. Three formal approaches are developed in this study for trade-off …

Hydrodynamic And Physicochemical Interactions Between An Active Janus Particle And An Inactive Particle, Jessica S. Rosenberg

Dissertations, Theses, and Capstone Projects

Active matter is an area of soft matter science in which units consume energy and turn it into autonomous motion. Groups of these units – whether flocks of birds, bacterial colonies, or even collections of synthetically-made active particles – may exhibit complex behavior on large scales. While the large-scale picture is of great importance, so is the microscopic scale. Studying the individual particles that make up active matter will allow us to understand how they move, and whether and under what circumstances their activity can be controlled.

Here we delve into the world of active matter by studying colloidal-sized (100 …

Phantom Shootings, Allan Ambris

Dissertations, Theses, and Capstone Projects

This capstone is a website designed to critique NYC Open Data reporting with respect to shootings through a series of visualizations and discoveries. The NYPD Shooting Incidents datasets (Historic and Year to Date) introduce themselves to the user by claiming to be a “list of every shooting incident that occurred in NYC.” The supplied documentation reveals that this is not the case.

After understanding the supporting materials, there are still undisclosed truths. My exploration of the data revealed that a single victim may be represented across multiple entries. Additionally, multiple victims may be represented by a single entry. It is …

The Development Of Novel Radioimmunoconjugates For The Pet Imaging And Radioimmunotherapy Of Cancer, Samantha M. Sarrett

Dissertations, Theses, and Capstone Projects

Antibodies have long played a vital role in nuclear medicine for both the diagnosis and therapy of various malignancies. The role and development of antibodies in nuclear medicine can be broadly separated into three different categories: 1) bioconjugation strategies, 2) immunoPET imaging, and 3) radioimmunotherapy. This dissertation will attempt to comprehensively cover each of these categories through a series of studies, protocols, and reviews. For the bioconjugation strategies, we will describe the development of a novel site-selective bioconjugation strategy using an innovative lysine-targeting reagent, PFP-bisN₃, to prepare [⁸⁹Zr]Zr-^SSKDFO-pertuzumab for visualizing HER2+ breast cancer. Further, …

Statistical And Biological Analyses Of Acoustic Signals In Estrildid Finches, Moises Rivera

Dissertations, Theses, and Capstone Projects

Acoustic communication is a process that involves auditory perception and signal processing. Discrimination and recognition further require cognitive processes and supporting mechanisms in order to successfully identify and appropriately respond to signal senders. Although acoustic communication is common across birds, classical research has largely disregarded the perceptual abilities of perinatal altricial taxa. Chapter 1 reviews the literature of perinatal acoustic stimulation in birds, highlighting the disproportionate focus on precocial birds (e.g., chickens, ducks, quails). The long-held belief that altricial birds were incapable of acoustic perception in ovo was only recently overturned, as researchers began to find behavioral and physiological evidence …

Performance Modeling For Network Anomaly Detection And Sensor Networks, Jie Chu

Dissertations, Theses, and Capstone Projects

Computer networks have become one of the fundamental communication infrastructures of the modern world. Data collection and data analysis over computer networks is a broad area of research and is getting more and more complicated as the ever-increasing complexity of the computer networks. In this dissertation, I will conduct performance modeling work for a few network scenarios and applications. In the first part of this dissertation, I will focus on two vital perspectives of the Internet, one from network administrators and the other from network users. Network administrators are key to manage and protect a computer network. I will study …