Physical Sciences and Mathematics Commons^™

Investigation Of The Use Of Nanotechnology In Food Packaging, Ollie-May Woodland

The Plymouth Student Scientist

This review discusses topics related to the use and development of nanotechnology and nanomaterials in food packaging applications. The accelerated use of these technologies brings about relevant safety, environmental, ethical and legislative/ regulatory concerns and as such the aim of this work is to assess the viability of the use of current commercialised nano-enabled packaging and to evaluate the potential future trends in the progression of these technologies against public opinion and potential risk(s). The data for this report was collected through comprehensive research of nanotechnology and its applications, specifically the packaging industry in the food sector. An online survey …

Application Of Two-Directional Carbonyl Ene Reaction To The Synthesis Of Complex Tetrahydropyrans, And Studies Toward The Synthesis Of C26-C39 Subunit Of Spirastrellolide B., Md Abid Abid Hasan

Dissertations - ALL

The use of exocyclic enol ethers as nucleophiles in carbon-carbon bond forming reactions has been underutilized in organic synthesis. This work describes the use of 6-iodomethyl-2-methylenetetrahydropyran as a bis-exocyclic enol ether equivalent for the synthesis of pyran derivatives. Use of this linchpin allows for bidirectional elaboration of the pyran core by two directional carbonyl ene. The development of a convergent, modular synthesis of 2,6-disubstituted-4H-pyrans in a three-step sequence starting from 6-iodomethyl-2-methylenetetrahydropyran is described. Initial carbonyl ene reaction of 6-iodomethyl-2-methylenetetrahydropyran with aldehydes or activated ketones was followed by elimination of iodide to give cross oriented bis-enol ethers that contain both endocyclic …

Advancing Continuous Manufacturing: The Role Of Process Analytical Technology In Process Development, Samuel R. Henson

Electronic Theses and Dissertations

The pharmaceutical industry is actively pursuing technologies which improve manufacturing processes with the goal of producing high-quality pharmaceutical products for patients, manifesting in an industry-wide investment in continuous manufacturing (CM). Process analytical technology (PAT) has been recognized for its successful monitoring of critical quality attributes during routine production and is often cited alongside CM due to its ability to make timely, in-line measurements of intermediate materials. Various PAT tools are valuable in process development, particularly as continuous wet granulation processes are developed for use within pharmaceutical manufacturing. This work applied PAT and chemometric modeling during CM process development to enhance …

Development Of A Real-Time Convolution System To Simulate Speech In Different Rooms For The Study Of Vocal Strain, Bethany E. Wu

Theses and Dissertations

Due to prevalent vocal health issues in teachers, the acoustics of K-12 classrooms has become a topic of study in acoustics. One way to understand the effects of a classroom's physical space on speech is with vocal effort studies. This thesis aims to enable these studies, without the need to move a talker from room to room, by creating auralizations through real-time convolution of speech with oral binaural room impulse responses (OBRIRs). These auralizations can be used to test talkers inside an anechoic chamber as they experience speaking in different acoustical environments. A system that can successfully execute convolution in …

Re: Approval Letter For The Butte Priority Soils Operable Unit (Bpsou) Final Bpsou Insufficiently Reclaimed Sites Belle Of Butte (Bres No. 8 & Ur-39) Remedial Action Work Plan (Rawp) Request For Change Ir-2024-Ra-02 (Dated December 19, 2024), Molly Roby

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Optimal Operation Scheduling Of Integrated Energy System Considering Energy Priority, Dongli Jia, Keyan Liu, Zhaoying Ren, Zezhou Wang, Dongsheng Tang

Journal of System Simulation

Abstract: Integrated with the actual situation of power grid and the growth of new energy, a multiobjective model for optimal scheduling of the integrated energy system(IES) is established based on the analysis of the energy-flow relationship of the IES and taking into account the priority of energy utilization and the load demand response in terms of the mismatch between the distributed energy sources and the loads, the net benefit of the unit cost of the IES, and the load response degree. Combined with the equipment and the environmental benefits system, a priority constraint for energy utilization has been established for …

Research On Scheduling Strategies Simulation For Building Air-Conditioning Systems Based On Transfer Imitation Learning, Qiaochu Wang, Yan Ding, Chuanzhi Liang, Haozheng Zhang, Chen Huang

Journal of System Simulation

Abstract: To solve the problem of unstable performance and inefficient training process of low-quality data conditions at the initial stage of online deployment of air conditioner scheduling, we propose a migration-imitation learning-based air conditioning scheduling strategy simulation method. Reinforcement learning methods are used to generate building operation strategies. A standard building simulation model serves as the source domain, upon which migration learning is applied. An imitation learning loss function is incorporated into the intelligent loss function to enhance algorithm performance. The results indicate that, compared with the non-use of migration learning, the proposed method can improve the operational efficiency by …

Behavioral Modeling Of Manned-Unmanned Cooperative Air Combat Based On Improved Abc Algorithm, Peng Wang, Haoyu Liu, Ni Li, Zexi Yu, Shangjie Jia

Journal of System Simulation

Abstract: To solve the problem of difficulty in establishing collaborative behavior models and weak adversarial capabilities in typical MAV/UAV air combat scenarios, a mixed decision based MAV/UAV behavior modeling framework is proposed. Using collaborative rule sets, rule subsets, tactical action sets, and other tools, a hierarchical decision collaborative behavior model supporting five types of collaborative tactics, including grinding tactics and unilateral flanking tactics, is constructed in this framework. a behavior model parameter optimization method based on an improved artificial bee colony (ABC) algorithm is proposed. By using the Mason rotation method to initialize the population, a better initial honey source …

Privacy Protection In Machine Learning Via Exploitation Of Constrained Adversarial Evasion, Brian Testa

Dissertations - ALL

Deep neural networks are extensively applied to real-world tasks. In many cases, the data feeding these tasks are human generated content, which emphasizes the criticality of privacy and data protection. The diverse modalities of this user data provide fertile ground for 3rd parties to monetize a user’s data. This work considers two such modalities: user speech when interacting with smart speaker voice assistants (VAs) and images shared with online service providers. In these cases, the user would like to support some form of machine learning (ML) inference without allowing others. A user interacting with a smart speaker would like the …

Development Of Methods For Predicting Second Harmonic Generation (Shg) Responses Of New Infrared Nonlinear Optical (Ir-Nlo) Materials, Katherine Colbaugh

Electronic Theses and Dissertations

Dissertation supervised by Dr. Jennifer A. Aitken.

In this work, calculations-based methods were evaluated for use in prediction of second harmonic generation (SHG), specifically χ⁽²⁾ values, of infrared nonlinear optical (IR-NLO) materials. Net dipole moment and dipole moment per volume were calculated by the bond valence sum method. Average F-index, proposed in this research, and group F-index, both representing induced dipole moment were also calculated. Each calculation was evaluated by comparing the results to single crystal and powder χ⁽²⁾ measurements of IR-NLO materials. The selected dataset consisted of ninety-six compounds including polar and nonpolar structures, newly discovered and …

Rna Structural-Dynamical Hierarchy: Sars-Cov, Sars-Cov-2, And Delta/Omicron Variant S2m Monomers, Kissing Complexes, And Extended Duplexes, Adam Kensinger

Electronic Theses and Dissertations

The power and promise of ribonucleic acid (RNA) molecules are only beginning to be realized in living organisms and pharmaceutical intervention. Specifically, defining the chemical physics of RNA’s heterogenous structural ensemble and dynamics, which has experienced expansive growth over the last few years, is central to a complete understanding, yet continues to be a significant challenge. A 41-nucleotide hairpin called the stem-loop II motif (s2m), present in the viral genomes of severe acute respiratory syndrome (SARS), SARS-coronavirus-2 (SARS-CoV-2), and the Delta and Omicron variants responsible for the COVID-19 pandemic, is a potential antiviral target due to its high sequence conservation …

Harmonic Impedance Modeling And Oscillation Analysis Of Modular Multilevel Converter, Yuhong Wang, Wensheng Chen, Shilin Gao, Jianquan Liao, Yangfan Cheng

Journal of System Simulation

Abstract: To facilitate rapid analysis of the oscillation stability mechanism in modular multilevel converter-based high voltage direct current (MMC-HVDC) systems and streamline the simulation process for determining MMC impedance characteristics, a simplified mathematical simulation model for MMC closed-loop impedance is developed using the harmonic state space method. This model considers various control strategies and includes both AC-side and DC-side impedance models. By applying a Nyquist criterion-based impedance analysis method, the stability mechanisms on the AC and DC sides of the MMC are examined. In addition, a data-driven oscillation stability analysis method is also proposed, leveraging a global sensitivity algorithm based …

Path Planning Of Desert Robot Based On Deep Reinforcement Learning, Ming Li, Wangzhong Ye, Jiehua Yan

Journal of System Simulation

Abstract: Due to the complexity and variability of the desert environment, the key to the high-efficient of mobile robot is how to avoid obstacles and plan its path. To solve the problems of poor search efficiency and slow convergence of deep reinforcement learning algorithm in complex environment, an improved deep reinforcement learning path planning algorithm is proposed. The exploration factor is improved and dynamically adjusted according to the convergence degree of the algorithm, so that the exploration factor dynamically decreases with the increase of the understanding degree of the agent to the environment, thus speeding up the convergence speed of …

Multimodal Representation Learning Frameworks For Modeling Progression And Heterogeneity In Alzheimer’S Disease, Sayantan Kumar

McKelvey School of Engineering Graduate Student Theses & Dissertations

Alzheimer’s Disease (AD) is the leading cause of dementia, characterised by cognitive and functional impairments that disrupt daily activities. Different clinical modalities such as neuroimaging biomarkers, cognitive assessments, fluid biomarkers and genetic data provide unique and complementary information, contributing to a more comprehensive understanding of disease progression and heterogeneity in disease characteristics. With recent advancements in computational capabilities, particularly in deep learning, multimodal representation learning frameworks aim to integrate diverse clinical modalities into a cohesive framework, capturing the most significant patterns within each modality. Existing data-driven multimodal representation learning frameworks in AD research have two major limitations. First, AD progresses …

Reimagining The Machine Vision Pipeline In Cyber Physical Systems For Trustworthiness And Efficiency, Adith Boloor

McKelvey School of Engineering Graduate Student Theses & Dissertations

Cyber-physical systems (CPS), including autonomous vehicles, drones, and mobile robots, rely on intricate sensors, actuators, and machine learning algorithms to perceive the physical world and execute actions within their surroundings. In the context of vision-driven CPS, achieving this demands processing a substantial volume of visual data captured by on-board cameras. The data is subsequently channeled through digital processors and harnessed by deep neural networks for tasks such as image classification, object detection, and depth perception. This data-centric, machine-vision-infused CPS fosters intelligent decision-making, thereby enhancing overall system performance. Trustworthiness, encompassing the robustness of the entire machine-vision pipeline, and system-level efficiency are …

Multimodal Representation Learning Frameworks For Modeling Progression And Heterogeneity In Alzheimer’S Disease, Sayantan Kumar

McKelvey School of Engineering Graduate Student Theses & Dissertations

Alzheimer’s Disease (AD) is the leading cause of dementia, characterised by cognitive and functional impairments that disrupt daily activities. Different clinical modalities such as neuroimaging biomarkers, cognitive assessments, fluid biomarkers and genetic data provide unique and complementary information, contributing to a more comprehensive understanding of disease progression and heterogeneity in disease characteristics. With recent advancements in computational capabilities, particularly in deep learning, multimodal representation learning frameworks aim to integrate diverse clinical modalities into a cohesive framework, capturing the most significant patterns within each modality. Existing data-driven multimodal representation learning frameworks in AD research have two major limitations. First, AD progresses …

Reimagining The Machine Vision Pipeline In Cyber Physical Systems For Trustworthiness And Efficiency, Adith Boloor

McKelvey School of Engineering Graduate Student Theses & Dissertations

Cyber-physical systems (CPS), including autonomous vehicles, drones, and mobile robots, rely on intricate sensors, actuators, and machine learning algorithms to perceive the physical world and execute actions within their surroundings. In the context of vision-driven CPS, achieving this demands processing a substantial volume of visual data captured by on-board cameras. The data is subsequently channeled through digital processors and harnessed by deep neural networks for tasks such as image classification, object detection, and depth perception. This data-centric, machine-vision-infused CPS fosters intelligent decision-making, thereby enhancing overall system performance. Trustworthiness, encompassing the robustness of the entire machine-vision pipeline, and system-level efficiency are …

Re: Butte Mine Flooding Operable Unit Berkeley Pit And Discharge Pilot Project – November 2024 Monthly Discharge Monitoring Report, Mark Thompson, Dave Griffis

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Re: Approval Letter For The Butte Priority Soils Operable Unit (Bpsou) Unreclaimed Sites And Insufficiently Reclaimed Areas – Racetrack Borrow Material Usage (Dated December 19, 2024), Molly Roby

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

November 2024 Berkeley Pit Migratory Waterfowl Protection Monthly Report, Mark Thompson, Loren Burmeister

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Action Logic And Agenda Game Of Global Methane Emission Control And China’S Countermeasures, Bo Zhang, Jinling Guo, Bing Zhong, Junlian Gao, Guosheng Zhang, He Liu

Bulletin of Chinese Academy of Sciences (Chinese Version)

Originated from the global response to climate change, methane emission control has evolved into a focus of international climate negotiations in recent years. At present, the agenda for controlling methane emission in global climate governance is basically taking shape, but in the process of shifting from scientific consensus to political consensus, the content of the topic and the focus of the game continue to evolve. To carry out global action, it is necessary to address issues such as the allocation of responsibilities, international rules, climate investment and financing, and risk prevention, as well as the basic capacity guarantees behind them. …

Architecture And Key Technologies Of New Research Informatization Infrastructure Platform Under The Fifth Research Paradigm, Fangyu Liao, Yang Wang, Rongqiang Cao, Bo Zhang, Zhenyu Li, Huajin Wang, Xin Chen, Dong Li, Yangang Wang, Xin Wei

Bulletin of Chinese Academy of Sciences (Chinese Version)

The basic platform of research informatization is an indispensable pedestal for modern scientific research and an important manifestation of national scientific and technological innovation capability. As the research paradigm continues to evolve, the architecture and technologies of research informatization infrastructure platform are bound to evolve as well. The new research paradigm brings unique demands and challenges to the algorithmic computility, network transmission capacity, and data storage and management. Consequently, it is an urgent requirement for research informatization infrastructure platform to make technological breakthroughs in the areas of intelligent computility, large-scale data storage and high throughput read/write, cross-network software and hardware …

Overall Promotion Of Integrated Management And Utilization Of Saline-Alkali Land In Northwest China: Conditions, Challenges, And Recommendations, Qi Feng, Xinwei Yin, Meng Zhu, Jutao Zhang, Wei Liu, Haiyang Xi, Tengfei Yu, Linshan Yang, Wen Liu, Zhixiang Lu

Bulletin of Chinese Academy of Sciences (Chinese Version)

Cultivated land is the lifeblood of grain production and the foundation for food security. Saline-alkali land in Northwest China is an important cultivated land reserve resource and a potential granary for guaranteeing national food security, so the high-quality promotion of comprehensive management and utilization of saline-alkali land in Northwest China is a strategic measure to achieve the goal of “storing grain in land and technology”. Based on a profound understanding of the great significance for promoting the integrated management and utilization of saline-alkali land in Northwest China, this study systematically summarizes the quantity, distribution pattern, and utilization potential of saline-alkali …

China’S Rare Earths Trade Flow Analysis: Trade Patterns And Strategic Insights, Linbin Tang, Peng Wang, Wei Chen, Yawen Han, Yuning Jin, Zilong Peng, Weiqiang Chen

Bulletin of Chinese Academy of Sciences (Chinese Version)

Rare earth elements are strategic critical metals that support low-carbon energy, aerospace, and defense technologies. Currently, China’s rare earth industry lacks competitiveness and faces the risk of “multidimensional pressures” in global competition. Therefore, it is crucial to systematically analyze the supply-demand and trade patterns of rare earths, accurately identify the bottlenecks and pain points in China’s entire rare earth industry chain, and provide strategies to transform China’s rare earth resource advantage into a strategic competitive edge. Based on customs trade data, this study traces the trade flows of various forms of rare earth products across the full industry chain in …

How Should China Respond To “Pan-Data Sovereignty” Competition Among China, U.S., And Eu—An Analysis Based On The Digital Stack Model?, Yan Liu, Congjing Ran

Bulletin of Chinese Academy of Sciences (Chinese Version)

Data sovereignty has become deeply intertwined with various economic and social development factors such as technology, trade, economy, culture, society, and politics, leading to a “Pan-Data Sovereignty” competition pattern in the digital space. Through the digital stack model, which examines digital technologies in a layered framework, we can more clearly assess the competitive capacities in“Pan-Data Sovereignty” of China, United States, and European Union. The analysis identifies a three-tiered global “Pan-Data Sovereignty” competition structure among China, U.S., and EU, with each entity holding distinct advantages across various layers of the digital stack. Intense future competition is anticipated in fields such as …

Research And Reflection On Transformation Of Resource-Based Cities In China—A Case Study Of Datong City, Shanxi Province, Zhijian Xiong, Hong Zhao, Xiuli Liu

Bulletin of Chinese Academy of Sciences (Chinese Version)

Currently, there are 262 resource-based cities in China, of which mature and declining cities account for 79.39%. These cities have made significant contributions to the country’s economic and social development, but now they are facing severe challenges and difficulties, and their transformation problems urgently need to be solved. This work studies the mechanism of resource-based transformation and proposes strategies for the transformation of resource-based cities: (1) Transformation should be comprehensive, balanced, and sustainable; (2) Transformation should fully leverage the leading role of the market while also taking into account the fundamental role of the government; (3) Transformation should fully leverage …

A Comprehensive Usability And Economic Analysis Of Heat-Related Wearable Technologies: Applications To Occupational Health, Ryan T. Cannady

Theses & Dissertations

The purpose of this research was to analyze the usability and economic considerations of real-time wearable technologies that are implemented in occupational settings to assess risk of heat stress and heat strain. The study population included current agriculture workers and Department of Energy (DOE), Environmental Management (EM) contractors. We employed a mixed-methods approach to comprehensively analyze the usability and economic considerations of heat-related technologies. Specifically, our approach assessed three distinct aspects the applications of these technologies in occupational settings to comprehensively address our research objective: (1) worker perceptions of heat-related wearable technologies, (2) field-based assessment of these heat-related wearable technologies, …

A Confidence-Based Knowledge Integration Framework For Cross-Domain Table Question Answering, Yuankai Fan, Tonghui Ren, Can Huang, Beini Zheng, Yinan Jing, Zhenying He, Jinbao Li, Jianxin Li

Research outputs 2022 to 2026

Recent advancements in TableQA leverage sequence-to-sequence (Seq2seq) deep learning models to accurately respond to natural language queries. These models achieve this by converting the queries into SQL queries, using information drawn from one or more tables. However, Seq2seq models often produce uncertain (low-confidence) predictions when distributing probability mass across multiple outputs during a decoding step, frequently yielding translation errors. To tackle this problem, we present CKIF, a confidence-based knowledge integration framework that uses a two-stage deep-learning-based ranking technique to mitigate the low-confidence problem commonly associated with Seq2seq models for TableQA. The core idea of CKIF is to introduce a flexible …

Intrinsic Gas-Phase Behavior Of Uranium Species: A Comprehensive Reactivity Study Of [O=U≡Ch]+ And [Uh]+, Justin Terhorst

Electronic Theses and Dissertations

The intrinsic chemistry of actinide elements, particularly uranium, remains a key challenge in understanding f-block reactivity due to the complexity introduced by solvent interactions, counter-ions, and complex equilibria in the condensed phase. In this dissertation, a systematic gas-phase study utilizing preparative tandem ion-trap mass spectrometry (PTMSⁿ) is presented, focusing on the reactivity of uranium-centered species, specifically [OUCH]⁺, an oxy uranium methylidyne species, and [UH]⁺ ions. By stripping away solvent effects and isolating the ions, PTMSⁿ provides a powerful platform to probe the fundamental chemical behavior of uranium species in their intrinsic state.

The …

Gmr-4234 Evaluating Instance Segmentation Models On Histopathology Datasets, Sai Chandana Koganti

C-Day Computing Showcase

Instance segmentation is transforming digital pathology by enhancing the speed and accuracy of tissue sample analysis through advanced image processing techniques. Whole Slide Imaging (WSI) converts traditional microscope slides into high-resolution digital formats, enabling detailed examinations. This paper presents a brief experimental survey of instance segmentation models on two prominent histopathology datasets: PanNuke and NuCLS. Unlike previous surveys that merely describe deep learning models for general pathology images, we conduct experiments using state-of-the-art models including Mask R-CNN, Detectron2, YOLOv8, YOLOv9, and HoverNet on both datasets. Our study evaluates these models for both binary and multiclass instance segmentation tasks. The NuCLS …