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Articles 811 - 840 of 115639
Full-Text Articles in Entire DC Network
Third Butte Rmap Biomonitoring (Phase 3) Report, Ramboll, Atlantic Richfield Company
Third Butte Rmap Biomonitoring (Phase 3) Report, Ramboll, Atlantic Richfield Company
Silver Bow Creek/Butte Area Superfund Site
No abstract provided.
Generative Endurance Logic: An Axiomatic Framework For Reasoning About Outcome-Generating Objects Under Constraints, Hafiz Burhan Ul Haq, Muhammad Nauman Irshad
Generative Endurance Logic: An Axiomatic Framework For Reasoning About Outcome-Generating Objects Under Constraints, Hafiz Burhan Ul Haq, Muhammad Nauman Irshad
Neutrosophic Systems with Applications
This paper introduces Generative Endurance Logic (GEL), a formal framework for studying objects through the outcomes they can produce. In many cases, an object cannot be judged only by a fixed truth value, score, or utility value. A rule, model, action, or strategy may behave well in one situation but fail when the context changes or when small perturbations occur. GEL addresses this issue by treating each object as a generator of outcomes. Each object a is linked to a generation map Ga:X×Ω→Y, where X is the context space, Ω is the …
Interval-Valued Neutrosophic Dombi Bonferroni Mean Aggregation Operators In Medical Diagnosis And Sustainable Energy, Maryam Faisal, Muhammad Nadeem, Muhammad Kamran
Interval-Valued Neutrosophic Dombi Bonferroni Mean Aggregation Operators In Medical Diagnosis And Sustainable Energy, Maryam Faisal, Muhammad Nadeem, Muhammad Kamran
Neutrosophic Systems with Applications
Medical diagnosis is one of the most difficult fields in which decisions must be made due to the fact that medical information often has characteristics of uncertainty, incompleteness, imprecision and even contradiction. Traditional aggregation and decision-making methods are often not well suited to such complexities, and may result in less reliable diagnostic outcomes. In order to overcome these drawbacks, the authors propose a new approach using a novel representation of Interval-Valued Neutrosophic Sets (IVNSs), the Dombi operational laws, and Bonferroni Mean (BM) aggregation operators. The proposed framework is specifically aimed at coping with uncertainty, indeterminacy and falsity all at once …
Monte Carlo Analysis Of Dose Distribution In Tumour And Adjacent Healthy Tissues During 192Ir Hdr Brachytherapy In The Presence Of Gold Nanoparticles, Damian P. Tippe, Innocent J. Lugendo
Monte Carlo Analysis Of Dose Distribution In Tumour And Adjacent Healthy Tissues During 192Ir Hdr Brachytherapy In The Presence Of Gold Nanoparticles, Damian P. Tippe, Innocent J. Lugendo
Tanzania Journal of Science
High dose rate (HDR) brachytherapy using 192Ir is an effective modality for cancer treatment; however, its therapeutic efficiency is often constrained by unintended radiation exposure to healthy tissues surrounding the tumour. Fortunately, the incorporation of high atomic number (Z) nanoparticles as radiosensitizers has emerged as a promising strategy to enhance tumour dose while sparing adjacent normal tissues. In this study, the dose distribution in tumour and nearby healthy tissues during 192Ir HDR brachytherapy was investigated in the presence of gold (Au) nanoparticles using Monte Carlo simulations based on the Geant4 toolkit. Radial dose distributions and anisotropy characteristics were analysed …
Natural Radioactivity And Radiological Hazards In Sediments From The Lindi Coast, Indian Ocean, Tanzania, Viator Mujuni, Innocent J. Lugendo
Natural Radioactivity And Radiological Hazards In Sediments From The Lindi Coast, Indian Ocean, Tanzania, Viator Mujuni, Innocent J. Lugendo
Tanzania Journal of Science
The Lindi coast of the Indian Ocean, located in southeastern Tanzania, supports rich biodiversity and has recently experienced rapid growth in socio-economic activities such as fishing, mining, and oil and gas exploration. These activities may enhance levels of natural radioactivity in coastal sediments, potentially increasing radiation exposure to local populations. Therefore, monitoring radioactivity levels and estimating associated radiation doses in this region is important. In this study, thirty-six sediment samples were collected from twelve locations along the Lindi coast and analysed for naturally occurring radionuclides using high-purity germanium (HPGe) gamma-ray spectrometry. The activity concentrations of 226Ra, 232Th, and …
Linear Programming Model For Optimal Crop Allocation Under Varying Land Sizes In Pawaga, Tanzania, Mustapha Abbas Kiswanya, Seleman Ismail, Saul Mpeshe
Linear Programming Model For Optimal Crop Allocation Under Varying Land Sizes In Pawaga, Tanzania, Mustapha Abbas Kiswanya, Seleman Ismail, Saul Mpeshe
Tanzania Journal of Science
Farmers often rely on intuition when selecting crops, which can lead to suboptimal profits. In this study, we examine the optimal annual crop allocation under varying land sizes for farmers in Pawaga, Iringa District, Tanzania. A parametric linear programming (LP) model is developed to determine crop allocation combinations that maximise profit subject to land, labour, and capital constraints. Unlike conventional approaches that require separate models for different farm sizes, the proposed model accommodates land holdings ranging from 1 to 9 acres and integrates nine crop types within a single framework. Data were collected over three (3) agricultural seasons from extension …
Hydrogeochemical Characterization Of Groundwater In Fractured Crystalline Basement Aquifers In Dodoma, Central Tanzania: Implications On Water Quality For Domestic And Irrigation Applications, George J. Ishabairu, Simon R. Melchioly, Charles H. Kasanzu, Gabriel D. Mulibo
Hydrogeochemical Characterization Of Groundwater In Fractured Crystalline Basement Aquifers In Dodoma, Central Tanzania: Implications On Water Quality For Domestic And Irrigation Applications, George J. Ishabairu, Simon R. Melchioly, Charles H. Kasanzu, Gabriel D. Mulibo
Tanzania Journal of Science
Assessment of groundwater hydrogeochemistry characteristics of aquifers plays a vital role in establishing water quality status and its suitability for human and industrial use. The main objective of this research was to carry out hydrogeochemical characterization of groundwater and assess its impacts on water quality and spatial variability of groundwater geochemistry in Dodoma, Tanzania. The methods used include groundwater sampling, laboratory analysis to determine physico- chemical parameters and data processing to classify the groundwater hydrochemical facies. The results show that the average value for pH is 7.2, for electrical conductivity (EC) is 1108 µS/cm and for total dissolved solids (TDS) …
Modern Architecture Of Muqarnas In Damascus: An Original Computational Methodology, Nahed Jawad Chakouf
Modern Architecture Of Muqarnas In Damascus: An Original Computational Methodology, Nahed Jawad Chakouf
All Works
The research aimed to revive muqarnas using digital computational tools, drawing on the techniques of Damascene craftsmen and ancient manuscripts. It involved designing contemporary muqarnas with double-curvature vaults and large spans, incorporating new unit designs and compositional techniques. In Section I, the researcher conducted pre-design studies on four muqarnas types, each associated with one of the four Damascene architectural styles. These studies examined the geometry and behavior of muqarnas types when used on traditional domed surfaces. Section II included a design study of the Dome of the Eagle of the Umayyad Mosque in Damascus, using modern software tools such as …
Forecasting Covid-19 New Cases Using Nbeats Deep Learning And Mobility Data, Amril Nazir, Mohammad Shorfuzzaman, Muhammad Lujaini Lotfi, Firuz Kamalov, Sufian Badawi, Maen Takruri, Abdul Halim Jallad
Forecasting Covid-19 New Cases Using Nbeats Deep Learning And Mobility Data, Amril Nazir, Mohammad Shorfuzzaman, Muhammad Lujaini Lotfi, Firuz Kamalov, Sufian Badawi, Maen Takruri, Abdul Halim Jallad
All Works
COVID-19 is a highly contagious disease transmitted primarily through human contact. Therefore, understanding population mobility is essential for predicting COVID-19 case trends. In this paper, we propose a novel deep learning approach for forecasting new COVID-19 cases using a neural architecture called Neural Basis Expansion Analysis for Interpretable Time Series (N-BEATS). The N-BEATS model effectively handles long input sequences and large output horizons without information loss or increased computational complexity. We compare the performance of N-BEATS with a state-of-the-art benchmark model, LSTM-Markov, across four major countries: the United States, the United Kingdom, Russia, and Brazil. Three distinct COVID-19 datasets from …
The Nist Artificial Intelligence Risk Management Framework: Adoption Challenges And Opportunities, Gillian Kennedy, Devin Patel, Humza Sheikh, Paul Wagner, Robert J. Honomichl
The Nist Artificial Intelligence Risk Management Framework: Adoption Challenges And Opportunities, Gillian Kennedy, Devin Patel, Humza Sheikh, Paul Wagner, Robert J. Honomichl
Journal of Cybersecurity Education, Research and Practice
Artificial intelligence (AI) is being adopted at an exponential rate to improve efficiency, decision-making, and cybersecurity, but its rapid integration introduces new and often poorly understood risks, including system errors, algorithmic bias, data privacy concerns, security vulnerabilities, and ethical dilemmas. This paper examines how organizations are implementing AI and evaluates the National Institute of Standards and Technology's AI Risk Management Framework (NIST AI RMF) as a tool for managing these risks. It reviews the benefits of AI adoption alongside the risks emerging from its use in business and broader society and examines the legal and ethical challenges organizations face when …
Autoencoders As Classifiers Trained On Single Sources Of Radiographic Images For Generalizability Across Unseen Sources, Ryan M. Putney
Autoencoders As Classifiers Trained On Single Sources Of Radiographic Images For Generalizability Across Unseen Sources, Ryan M. Putney
USF Tampa Graduate Theses and Dissertations
Artificial neural networks trained to classify X-ray images according to disease state will learn to distinguish between technical or procedural variations in the images rather than features relevant to the disease. For example, the model might learn to recognize the machine that captured the image or to distinguish an image taken while the patient is lying supine or standing upright. The present work is aimed at using autoencoders as a generalizable classifier to detect COVID vs pneumonia (PNA) X-ray images. The first experiment was to find an architecture for a fully convolutional autoencoder (CAE) and for a convolutional autoencoder with …
Operationalizing Supply-Chain Hygiene In Graduate Is Education: A Hands-On Module For Secure Software And Ai/Ml Pipelines, Dominic A. Wilson
Operationalizing Supply-Chain Hygiene In Graduate Is Education: A Hands-On Module For Secure Software And Ai/Ml Pipelines, Dominic A. Wilson
Journal of Cybersecurity Education, Research and Practice
Supply-chain attacks (including typosquatting, dependency confusion, compromised builds, dataset poisoning, and backdoored models) pose growing threats to analytics platforms central to Information Systems (IS). While frameworks like the Secure Software Development Framework (SSDF) and Supply-chain Levels for Software Artifacts (SLSA) offer guidance, IS curricula often lack accessible, infrastructure-light modules that build practical skills for mitigating these risks. This experience report presents a two-week module embedded in a graduate Secure Coding course required for a Master’s in Applied Security and Analytics degree. The module operationalizes secure development habits across both traditional software and machine learning (ML) pipelines. The module addresses a …
Li+/Na+ Hybrid Ion Conduction Mechanism In The Superionic Conductor Li3–XNaXZr2Si2Po12, Yi-Hong Wu, Xia Xie, Lei Zhu, Mu-Ran Yu, Guo-Tai Zhang, Jun-Chao Chen, Shu-Ying Sun, You-Wei Wang, Wei-Ping Tang
Li+/Na+ Hybrid Ion Conduction Mechanism In The Superionic Conductor Li3–XNaXZr2Si2Po12, Yi-Hong Wu, Xia Xie, Lei Zhu, Mu-Ran Yu, Guo-Tai Zhang, Jun-Chao Chen, Shu-Ying Sun, You-Wei Wang, Wei-Ping Tang
Journal of Electrochemistry
Hybrid ion conductors that transport multiple ionic conductive species provide a useful platform for understanding how mixed-ion transport governs ionic conductivity within a single phase. However, the controlled introduction of multiple mobile ions into solid-state electrolytes and a mechanistic understanding of their migration within the framework remain challenging. Herein, a skeleton-retained Li+↔Na+ cationic exchange was used to simultaneously induce Li+ and Na+ cations into the NASICON-type framework of Li3–xNaxZr2Si2PO12 (0 < x < 3). We show that the interpenetration of NaO6 and NaO8 coordination polyhedra significantly influences the ionic conductivity of hybrid ion conductors. Computational …
Teachers’ Awareness Of Family Engagement In Multilingual Education, Sedighe Zamani Roodsari
Teachers’ Awareness Of Family Engagement In Multilingual Education, Sedighe Zamani Roodsari
Journal of Multicultural Affairs
This study investigated public school teachers’ awareness of family engagement as a linguistic and cultural resource for multilingual students. Multilinguals are typically described as individuals who can communicate in more than one language, with English not being their native language, and their linguistic choices are influenced by societal norms and systems (Šifrar Kalan et al., 2024; Wei, 2008). Preparing pre-service teachers to enhance opportunities for multilingual students remains a critical need in teacher education programs, as they strive to move beyond monolingual ideologies in their teaching practices (Cárdenas Curiel et al., 2024; Kim & Choi, 2020; Williams & Ewing, 2019). …
Binding Energy Of Muonic Beryllium: Perturbative Versus All-Order Calculations, Shikha Rathi, Ulrich D. Jentschura, Paul Indelicato, Ben Ohayon
Binding Energy Of Muonic Beryllium: Perturbative Versus All-Order Calculations, Shikha Rathi, Ulrich D. Jentschura, Paul Indelicato, Ben Ohayon
Physics Faculty Research & Creative Works
We compute the ground-state binding energy of muonic (Formula presented) (Formula presented) Be in two ways: first, the fully perturbative treatment of the nuclear-size effect often employed in light systems, and second, an approach that accounts for the finite-nuclear-size to all orders (and is inspired by calculations otherwise employed for heavy muonic ions). The results are compared term by term and show that both approaches agree to better than one part-per-million of the total energy. The objective of this work is twofold. The first is practical: to provide a parameterization that allows the extraction of the (Formula presented) (Formula presented) …
Trustworthy Reinforcement Learning And Communication-Efficient Multi-Agent Systems, Rui Zuo
Trustworthy Reinforcement Learning And Communication-Efficient Multi-Agent Systems, Rui Zuo
Dissertations - ALL
The rapid proliferation of autonomous systems, such as Unmanned Aircraft Systems (UAS) transitioning to large-scale Beyond Visual Line of Sight (BVLOS) operations, demands a paradigm shift toward reliable, transparent, and resilient autonomy. While Deep Reinforcement Learning (DRL) and Multi-Agent Reinforcement Learning (MARL) have demonstrated exceptional capabilities in complex decision-making and coordination, their real-world deployment in safety-critical domains is hindered by two fundamental challenges. First, the opaque, "black-box" nature of DRL models prevents human operators from understanding and trusting the agents' underlying logic. Second, as multi-agent operations scale, they become severely constrained by the stochastic link qualities and strict bandwidth limitations …
Atropisomer Mechanochemistry Of Diarylethene Mechanophores: A Study Of Structure-Mechanical Activity Relationships, Cijun Zhang
Atropisomer Mechanochemistry Of Diarylethene Mechanophores: A Study Of Structure-Mechanical Activity Relationships, Cijun Zhang
Dissertations - ALL
Stimuli-responsive organic structures are advanced, intelligent platforms that dynamically adjust their physical or chemical properties—such solubility, or color—in response to external stimuli including light, heat, pH, redox conditions, mechanical force, or magnetic fields. Among these structures, mechanophores represent an important class that is specifically responsive to mechanical force. Synthetic mechanophores can be rationally engineered to exhibit tunable mechanosensitivity as well as tailored chemical and physical properties. In this work, we designed and synthesized a type of atropisomeric mechanophores based on sterically congested diarylethene photoswitches, and systematically investigated their mechanical and photochemical properties. Chapter 1 Chapter 1 provides a general introduction …
Scaling Logical Reasoning On Modern Hpc Hardware, Yihao Sun
Scaling Logical Reasoning On Modern Hpc Hardware, Yihao Sun
Dissertations - ALL
Deductive logic reasoning has evolved from a theoretical symbolic artificial intelligence tool into a massive computational workload. Modern domains, ranging from static program analysis and binary reverse engineering to knowledge-graph reasoning, rely on Datalog, a logical query language, to express deeply recursive, declarative specifications. However, scaling logic reasoning to these industrial workload exposes two interlocking ceilings in traditional engines. Architecturally, the memory bandwidth and parallel throughput of single-node CPUs fall drastically short of the read- and write-heavy demands of semi-naive evaluation. Asymptotically, traditional query processing algorithms, such as binary join algorithms generate massive intermediate relations that exhaust device memory on …
(R2153) Advanced Numerical Method For One Dimensional Burgers Equation With A Source Term, Yahaya Alassane Mahaman Nouri, Djibo Moustapha, Maman Yarodji Abdoul, Saley Bisso
(R2153) Advanced Numerical Method For One Dimensional Burgers Equation With A Source Term, Yahaya Alassane Mahaman Nouri, Djibo Moustapha, Maman Yarodji Abdoul, Saley Bisso
Applications and Applied Mathematics: An International Journal (AAM)
This paper investigates a numerical strategy for the one-dimensional Burgers equation with a nonzero source term. Such equations arise in simplified models of transport and diffusion processes and are often used to assess the performance of numerical schemes for nonlinear evolution problems. The proposed approach combines a second-order Crank–Nicolson time discretization with a projection-based procedure that separates the nonlinear convective contribution from diffusive effects. Spatial approximation is carried out using a Chebyshev spectral collocation method, which provides high accuracy for smooth solutions with a limited number of degrees of freedom. The resulting fully discretized system is solved through an iterative …
(R2167) Global Stability Of Seirs Model With Single Dose Vaccination In Varying Population, Govind Jha, Prabhat Mandal, Sarita Jha
(R2167) Global Stability Of Seirs Model With Single Dose Vaccination In Varying Population, Govind Jha, Prabhat Mandal, Sarita Jha
Applications and Applied Mathematics: An International Journal (AAM)
Understanding the evolution of infectious diseases within a dynamic population is essential for formulating effective public health strategies. This work introduces an enhanced SEIRS epidemic model that incorporates demographic variation and a single-dose vaccination strategy, supporting that immunity can be reduced over time. The model reflects diseases in which individuals may return to the susceptible state after recovery. Extending prior reduced three-dimensional models, this study develops a complete four-dimensional SEIRS framework, thereby increasing the model’s applicability to real-world scenarios. The inclusion of the full system presents greater analytical challenges. To overcome this, we extend the second additive compound matrix and …
(R2175) Application Of Similarity Measures On Bipolar Complex Neutrosophic Matrices In United Nations’ Sdg-17 Using Python, T. Muthuraji, N. Krishnapraveen
(R2175) Application Of Similarity Measures On Bipolar Complex Neutrosophic Matrices In United Nations’ Sdg-17 Using Python, T. Muthuraji, N. Krishnapraveen
Applications and Applied Mathematics: An International Journal (AAM)
The increasing complexity of decision-making environments demands mathematical frameworks capable of modeling bipolar, indeterminate, and phase-dependent uncertainty simultaneously. Bipolar Complex Neutrosophic theory provides such a structure, but the extension of similarity measures to matrix-based environments remains largely unexplored. In this study, we formally develop cosine, Dice, Jaccard, and hybrid vector similarity measures for Bipolar Complex Neutrosophic Matrices (BCNMs). Each matrix element is represented by a Bipolar Complex Neutrosophic Number (BCNN), enabling structured representation of multidimensional uncertainty within a matrix framework. We also design and implement efficient Python-based computational tools to automate similarity evaluation for BCNMs. The proposed algorithms reduce computational …
(R2185) Operations On Bipolar Complex Neutrosophic Matrices And Its Application In Un’S Sdg-14 & Sdg-3 Using Python, N. Krishnapraveen, T. Muthuraji
(R2185) Operations On Bipolar Complex Neutrosophic Matrices And Its Application In Un’S Sdg-14 & Sdg-3 Using Python, N. Krishnapraveen, T. Muthuraji
Applications and Applied Mathematics: An International Journal (AAM)
Decision-making in sustainability oriented environments frequently involves bipolar evaluations, indeterminate information and phase dependent uncertainty that cannot be adequately represented by existing neutrosophic matrix models. To address this limitation, this study introduces a Bipolar Complex Neutrosophic Matrix (BCNM) framework that integrates bipolar semantics with complex valued uncertainty in a coherent algebraic structure. Fundamental operations and structural properties are rigorously established to ensure mathematical consistency. To facilitate practical multi criteria decision analysis (MCDA), novel score, accuracy, and hybrid aggregation operators are developed. The computational feasibility of the proposed approach is analyzed, demonstrating linear complexity with respect to the number of alternatives …
R Code And Supporting Data For "Fast And Slow Water Handling Strategies Explain Pinyon Pine Decline And Juniper Expansion", Andrew Kulmatiski, Muhammad Faraz Rehman
R Code And Supporting Data For "Fast And Slow Water Handling Strategies Explain Pinyon Pine Decline And Juniper Expansion", Andrew Kulmatiski, Muhammad Faraz Rehman
Browse all Datasets
This repository contains the datasets, R scripts, HYDRUS-1D model files, weather data, and supporting materials used for the M.S. thesis, "Fast and Slow Water Handling Strategies Explain Pinyon Pine Decline and Juniper Expansion." The study investigated root water uptake and water-use strategies of pinyon pine (Pinus edulis) and Utah juniper (Juniperus osteosperma) using stable isotope tracer experiments, soil water flow modeling, leaf water potential measurements, stomatal conductance measurements, and environmental data collected across an aridity gradient in southern Utah, USA.
An Overlooked Terrestrial Archive: Freshwater Cements And Hydroclimate Signals In Quaternary Glaciogenic Deposits, Owen F. Mccaffrey, Ian Z. Winkelstern, Tara A. Kneeshaw, Melinda C. Higley
An Overlooked Terrestrial Archive: Freshwater Cements And Hydroclimate Signals In Quaternary Glaciogenic Deposits, Owen F. Mccaffrey, Ian Z. Winkelstern, Tara A. Kneeshaw, Melinda C. Higley
University Faculty Publications and Creative Works
Quaternary glaciogenic deposits, which serve as vital groundwater aquifers, are often partially cemented with carbonate minerals, but the timing of emplacement of these cements and their geochemical conditions of formation remain understudied. Here, we integrated petrography, δ18O, Mg/Ca, and clumped isotope (Δ47) data from two calcitecemented outcrops in western Michigan (USA) to investigate the origin of glacial sediment cements. The two sites have contrasting topographic and textural settings reflecting distinct formation conditions. The elevated Wabasis Lake deposit records sequential phreatic-to-vadose cementation, while the Cherry Valley Sands site, very close to the modern water table, shows a …
(R2161) Robust Optimization Of Industrial Hazardous Waste Location-Routing Problem Considering Response Actions To Environmental Risk, Sharareh Teimoori, Farhad Hosseinzadeh Lotfi, Seyyed Esmaeil Najafi, Navid Rafiei
(R2161) Robust Optimization Of Industrial Hazardous Waste Location-Routing Problem Considering Response Actions To Environmental Risk, Sharareh Teimoori, Farhad Hosseinzadeh Lotfi, Seyyed Esmaeil Najafi, Navid Rafiei
Applications and Applied Mathematics: An International Journal (AAM)
The management of hazardous industrial waste has emerged as a significant global challenge due to rapid technological advancements. Industrial hazardous waste management systems must be designed not only to be cost-effective but also to minimize environmental risks. This study proposes a mixed-integer programming model for the location-routing of industrial hazardous waste that incorporates both primary and secondary environmental risks, along with suitable response actions. Furthermore, a scenario-based robust optimization model is developed to address uncertainties in the quantities of industrial hazardous waste. A case study is conducted to demonstrate the applicability and comparative performance of the nominal and robust models. …
From Detection To Segmentation: A Foundation Model Approach To Organoid Brightfield Image Analysis Using Sam 3, Hiren Manani
From Detection To Segmentation: A Foundation Model Approach To Organoid Brightfield Image Analysis Using Sam 3, Hiren Manani
Theses - ALL
This thesis presents the first systematic application of SAM 3, a unified foundation model for promptable segmentation, to mouse small intestinal organoid brightfield microscopy image analysis. The work spans the complete pipeline from zero-shot baseline evaluation through domain-specific fine-tuning on a GPU cluster, and documents the full engineering process required to adapt a state-of-the-art foundation model to a novel biomedical imaging domain. A comprehensive literature review of over 20 papers spanning detection-based, classical segmentation, foundation model, and morphological analysis approaches identified a clear research gap that this thesis addresses. Five critical compatibility patches were developed to deploy SAM 3 on …
Constrained Neural Intelligence: Investigations Into Deep Multi-Objective Optimization, Naveed Tahir
Constrained Neural Intelligence: Investigations Into Deep Multi-Objective Optimization, Naveed Tahir
Dissertations - ALL
Neural intelligence is identified with complex learning problems optimized over the high-dimensional, non-convex parameter spaces of deep neural networks. Solving such problems generally requires handling competing objectives and conflicting constraints. This is traditionally dealt with using heuristic methods that collapse such complexity into unconstrained, singular objectives. While computationally convenient, this invites a tradeoff against the precision and stability afforded by non-heuristic, geometry-aware approaches. This dissertation explores constrained multi-objective learning in various applied and theoretical contexts and highlights the feasibility of approximate methods as well as the necessity of exact methods. We propose a framework for equality-constrained deep learning via approximate …
Thermal Aberrations And Optical Design For Current And Future Gravitational Wave Detectors, Matthew Richard Todd
Thermal Aberrations And Optical Design For Current And Future Gravitational Wave Detectors, Matthew Richard Todd
Dissertations - ALL
Since the first detection of gravitational waves in 2015, the LIGO-Virgo-KAGRA collabo- ration has detected over 300 gravitational-wave events. Planned upgrades to each detector will further improve gravitational wave sensitivity limits, pushing the frontier of multi- messenger astronomy and paving the way for next-generation detectors, like Cosmic Ex- plorer and Einstein Telescope. Though many challenges to reach sensitivity goals are being addressed, there are still cru- cial aspects of the detectors that are poorly understood and will inhibit gravitational wave detection commissioners from bringing future detectors to their design sensitivity. In par- ticular, increased circulating arm power targets will exacerbate …
Peptide And Peptide Bioconjugate Based Drug Development For The Treatment Of Metabolic Diseases, Nancy Cham
Peptide And Peptide Bioconjugate Based Drug Development For The Treatment Of Metabolic Diseases, Nancy Cham
Dissertations - ALL
The Doyle group has coined the term ‘corrination’ to describe the conjugate modification of a peptide, protein, small molecule, or radionuclide with a corrin ring-containing molecule such as cobalamin, also known as vitamin B12 (B12), or cobinamides. By exploiting the innate chemico-physical properties of corrin ring-containing compounds, both in general and specifically via the innate dietary B12 uptake pathway in mammals, corrination has been explored for drug development and targeted/localized delivery of probes and therapeutics. Most recently, it is in the field of peptide-based therapeutics that corrination is generating significant interest, no doubt driven in part by the recent successes …
An Overlooked Terrestrial Archive: Freshwater Cements And Hydroclimate Signals In Quaternary Glaciogenic Deposits, Owen F. Mccaffrey, Ian Z. Winkelstern, Tara A. Kneeshaw, Melinda C. Higley
An Overlooked Terrestrial Archive: Freshwater Cements And Hydroclimate Signals In Quaternary Glaciogenic Deposits, Owen F. Mccaffrey, Ian Z. Winkelstern, Tara A. Kneeshaw, Melinda C. Higley
University Faculty Publications and Creative Works
Quaternary glaciogenic deposits, which serve as vital groundwater aquifers, are often partially cemented with carbonate minerals, but the timing of emplacement of these cements and their geochemical conditions of formation remain understudied. Here, we integrated petrography, δ18O, Mg/Ca, and clumped isotope (Δ47) data from two calcitecemented outcrops in western Michigan (USA) to investigate the origin of glacial sediment cements. The two sites have contrasting topographic and textural settings reflecting distinct formation conditions. The elevated Wabasis Lake deposit records sequential phreatic-to-vadose cementation, while the Cherry Valley Sands site, very close to the modern water table, shows a …