Digital Commons Network^™

Mitigation Of Potential Risks In Chemical Laboratories: A Focused Review, Hossein Abedsoltan, Mark B. Shiflett

Chemical and Biochemical Engineering Faculty Research & Creative Works

This review paper presents an analysis of safety practices in chemical laboratories. It encompasses a systematic exploration of various facets including risk assessment, hazard mitigation, and the implementation of safety protocols. Emphasis is placed on the critical role of continuous education and training, advocating a proactive safety culture, and adapting to technological advancements. Additionally, the paper underscores the importance of adhering to regulatory standards, promoting exceeding baseline compliance toward establishing best practices in laboratory safety. This comprehensive approach highlights the dynamic, multifaceted nature of laboratory safety, positioning it as a fundamental aspect of scientific research.

Revolutionizing Feature Selection: A Breakthrough Approach For Enhanced Accuracy And Reduced Dimensions, With Implications For Early Medical Diagnostics, Shabia Shabir Khan, Majid Shafi Kawoosa, Bonny Bannerjee, Subhash C. Chauhan, Sheema Khan

Research Symposium

Background: The system's performance may be impacted by the high-dimensional feature dataset, attributed to redundant, non-informative, or irrelevant features, commonly referred to as noise. To mitigate inefficiency and suboptimal performance, our goal is to identify the optimal and minimal set of features capable of representing the entire dataset. Consequently, the Feature Selector (Fs) serves as an operator, transforming an m-dimensional feature set into an n-dimensional feature set. This process aims to generate a filtered dataset with reduced dimensions, enhancing the algorithm's efficiency.

Methods: This paper introduces an innovative feature selection approach utilizing a genetic algorithm with an ensemble crossover operation …

Oral Administration Of Ph-Responsive Polymeric Nanoparticles Based On Zein And Their Therapeutic Potential On Cancer., Bruno Alejandro Valades-Aguilar, José Raúl Rangel-López, Jennifer Citlally Leos-Rivera, Moisés Armides Franco-Molina, María Cristina Rodríguez-Padilla, Diana Ginette Zárate-Triviño

Research Symposium

Background: Zein is a water-insoluble protein extracted from the endosperm of corn seeds, this polymer is an attractive matrix to encapsulate hydrophilic compounds because of its high proportion of hydrophobic amino acids, making it a potential smart delivery material for several treatments in the biopharmaceutical industry. nanoparticles have been used as drug delivery systems for the improvement of oral bioavailability; however, the strategies of nanoparticle obtention need the addition of stabilizers. in this study, a modified method to obtain zein nanoparticles was developed.

Methods: Zein nanoparticles (ZNps) were made by a thermal treatment and precipitated into ovalbumin at a ratio …

La1-Xsrxcoo3 Perovskite Nanomaterial: Synthesis, Characterization, And Its Biomedical Application, Adhira Tippur, Anyet Shohag, Luke Franco, Ahmed Touhami, Swati Mohan, Mohammed Uddin

Research Symposium

Early cancer detection is paramount for effective treatment and potential cures. This research explores the application of perovskite materials, specifically Sr2+-doped Lanthanum Cobaltite (La1-xSrxCoO3) nanomaterials, in cancer detection, with a focus on rats as an experimental model. The ferroelectric nature of these materials, synthesized through a combination of sol-gel and molten-salt processes, was examined at varying Sr2+ doping levels (1-20 wt%). Rigorous characterization, employing X-ray diffraction and scanning electron microscopy, confirmed the uniform morphology of nano cubes, laying the foundation for subsequent investigations. The magnetic properties of the perovskite nanoparticles were probed, suggesting their potential as a diagnostic tool for …

Exploring The Use Of Enhanced Swad Towards Building Learned Models That Generalize Better To Unseen Sources, Brandon M. Weinhofer

USF Tampa Graduate Theses and Dissertations

Deep learning models, typically, take significant time to train. Classifier ensembles are areliable way to increase classifier accuracy and perhaps generalizability to unseen sources of data. These classifiers can be combined with a simple voting scheme. The problem is that having multiple models can very heavily increase training time. Snapshot ensembles have been shown to provide a boost in performance by creating an ensemble of classifiers with different weights during the training of a single deep learned model. This can somewhat solve the problem of the increased training time as you do not have to train separate models. As Machine …

Digital Performance Management: An Evaluation Of Manufacturing Performance Management Andmeasurement Strategies In An Industry 4.0 Context, Nathaniel David Smith

Theses and Dissertations

Manufacturing management and operations place heavy emphasis on monitoring and improving production performance. This supervision is accomplished through strategies of manufacturing performance management, a set of measurements and methods used to monitor production conditions. Over the last thirty years the most prevalent measurement of traditional performance management has been overall equipment effectiveness, a percentile summary metric of a machine's utilization. The technologies encapsulated by Industry 4.0 have expanded the ability to gather, process, and store vast quantities of data, creating opportunity to innovate on how performance is measured. A new method of managing manufacturing performance utilizing Industry 4.0 technologies has …

Potential For Climate-Based Financing Of Watershed Management To Restore Streams And Improve Water Quality Following A Wildfire: A Case Study Of The Provo River Watershed, Braxton Wayne Porter

Theses and Dissertations

Following wildfires, water quality in forested watersheds is prone to degradation, impacting drinking water treatment and causing increased emissions due to additional energy consumption. We explore the potential for climate-based financing to support wildfire mitigation and watershed restoration and thereby reduce potential water treatment energy demand within the Provo River watershed of Utah, USA. Pre- and post-wildfire erosion and water quality in the Provo River is modeled using GeoWEPP. Energy data from the Don A. Christiansen drinking water treatment plant in the watershed and related literature data are used to estimate the increase in energy use for treating degraded water. …

Leveraging Systems Thinking For Global Environmental Health, Martha M. Mcalister

USF Tampa Graduate Theses and Dissertations

Environmental health inequities such as household air pollution, inadequate water, sanitation, and hygiene, and chemical pollution persist globally and have myriad consequences on individual and societal well-being. Unfortunately, while billions of dollars and countless hours of research have been applied towards addressing these issues in development, humanitarian, and environmental justice contexts, attempts to reduce the environmental burden of disease can seem successful at first, but then backslide to pre-intervention conditions (or worse). This is indicative of policy resistance, a tendency of complex systems that makes it very difficult to enact change if the “rules” of the system are misunderstood. There …

Exploring Extended Reality In An Aqueous Processing Test Bed For Nuclear Material, Sam Wald

Undergraduate Honors Theses

This research aided in the ongoing creation of an extended reality training experience for Beartooth, an aqueous processing test bed for nuclear material, by exploring what will be comfortable and effective for users of the experience. Participants consisted of staff members from Idaho National Laboratory (INL) and authorized members of the Augmented Learning Lab at BYU. We conducted usability testing with participants who were given extended reality (XR) equipment to explore the Beartooth virtual training system. We also performed a heuristic evaluation on the system using an augmented reality evaluation checklist. Findings were discussed with the INL team and recommendations …

Comparative Assessment Of Gold Nanoparticle-Antibody Conjugates With Two Differently Shaped Particles For Multimodal Colorimetric Lateral Flow Assay, Vinayak Sharma, Bilal Javed, Furong Tian

Articles

Novel detection strategies that exploit the unique properties of gold nanoparticles (AuNPs) hold great potential for the advancement of point-of-care (POC) diagnostics, such as lateral flow and dipstick immunoassay [1–3]. Owing to its biocompatibility and convenient surface modifications, gold nanoparticles with enhanced sensitivity reduce the sample-to-answer times to less than 5 min (Figure 1). Methods like covalent conjugation and electrostatic adsorption are explored for antibody immobilization to develop a gold nanoparticle-based biosensor for fast and sensitive localized surface plasmon resonance (LSPR) for both basic research and clinical diagnostics. The mounting of antibodies on the gold nanoparticle surface requires selective binding …

How Individuals’ Opinions Influence Society’S Resistance To Epidemics: An Agent-Based Model Approach, Geonsik Yu, Michael Garee, Mario Ventresca, Yuehwern Yih

Purdue University Libraries Open Access Publishing Fund

Background

Protecting public health from infectious diseases often relies on the cooperation of citizens, especially when self-care interventions are the only viable tools for disease mitigation. Accordingly, social aspects related to public opinion have been studied in the context of the recent COVID-19 pandemic. However, a comprehensive understanding of the effects of opinion-related factors on disease spread still requires further exploration.

Methods

We propose an agent-based simulation framework incorporating opinion dynamics within an epidemic model based on the assumption that mass media channels play a leading role in opinion dynamics. The model simulates how opinions about preventive interventions change over …

Study On R&D Strategies In Nanoscale Science And Technology Of Powerhouses And Insights, Wenyue Bian, Xingjie Liang, Chunlei Ge, Zhongyang Hui, Xiaoqi Jia, Si Liu, Jing Ye, Xiaoyi Chen, Wenjun Wang, Huajun Ju

Bulletin of Chinese Academy of Sciences (Chinese Version)

Nanoscale science and technology (nano S&T) are at the frontier of global strategic high-tech competition. After examining nearly 160 strategy and planning documents released by scientific and technological powerhouses from 2000 to 2023, the study finds ten common approaches adopted by the powerhouses to advance nano S&T as follows. (1) Recognizing nano S&T as a key area for the economy and global competition. (2) Establishing cross-department organizations to meet the cross-disciplinary nature of nano S&T. (3) Developing strategic plans to guide the development of nano S&T and implementing major programs with significant investment. (4) Establishing multidisciplinary nano S&T research centers …

Sanitation In Urban Areas May Limit The Spread Of Antimicrobial Resistance Via Flies, Drew Capone, Oliver Cumming, Abeoseh Flemister, Victor Ilevbare, Seth R. Irish, Ishi Keenum, Jackie Knee, Rassul Nala, Joe Brown

Michigan Tech Publications

Synanthropic filth flies are common where sanitation is poor and fecal wastes are accessible to them. These flies have been proposed as mechanical vectors for the localized transport of fecal microbes including antimicrobial resistant (AMR) organisms and associated antimicrobial resistance genes (ARGs), increasing exposure risks. We evaluated whether an onsite sanitation intervention in Maputo, Mozambique reduced the concentration of enteric bacteria and the frequency of detection of ARGs carried by flies collected in household compounds of low-income neighborhoods. Additionally, we assessed the phenotypic resistance profile of Enterobacteriaceae isolates recovered from flies during the pre-intervention phase. After fly enumeration at study …

Emotion Recognition As A Novel Indicator For Assessing Brain Health: A Machine Learning Approach, Nayarah Shabir, Parveen Lehana

Research Symposium

Background: Emotion is being referred to as a person’s mental state, since it relates to their ideas, feelings, and actions. There is a lot of evidence that health affects the emotion. Therefore, the nature of emotions ought to reveal the health of a person. The emotions are represented by facial expressions controlled by muscular motor actions. Brain health may affect the working of the muscles leading to the emotional changes extracted from the facial images.

Methods: A dataset of facial images annotated with matching emotion labels is the first step in using convolutional neural networks (CNNs) for facial …

An Analysis Of Driven Pile Relaxation In Florida Soils, Dalton E. Knowles

USF Tampa Graduate Theses and Dissertations

Prestressed concrete piles (PCP) are a common geotechnical foundational element employed in marine and land bridges. PCP are commonly driven by an impact diesel hammer until the desired nominal bearing resistance is reached at the end of the initial drive (EOID). At a later time, the pile resistance may be verified, but not always, via a restrike, usually with the same impact hammer. At the beginning of a restrike, the resistance of the pile is rarely equal to the resistance at the EOID either increasing, known as set-up, or decreasing, known as relaxation. Set-up is clearly beneficial, however, this thesis …

03.18.2024 Orsp Connect, Liz Williamson

ORED Newsletter

SPAN and ARC form training, Nature Masterclasses, Glisto Rice, Useful Links

Dissolved Nitrogen Removal In Biochar Amended, High Permeability Media For Urban Stormwater Treatment, Mark Vicciardo

USF Tampa Graduate Theses and Dissertations

Nutrient pollution in stormwater drives the eutrophication of inland and costal waterbodies which leads to sea grass retreat and the proliferation of harmful algal blooms (HAB). These anthropogenic effects destabilize ecosystems, and some HABs can pose direct human health risk. Bioretention, or the storage and controlled discharge of stormwater run-off in an ecologically engineered setting, is a potential solution to this problem. However, it relies heavily on the settling of particles as a nutrient removal mechanism, and thus struggles with pollutants, such as dissolved nitrogen, which is a particular problem in Florida where the geological prominence of phosphorus leaves nitrogen …

Understanding Lightning Damage Formation In A Carbon-Epoxy Pultruded Rod Stitched Efficient Unitized Structure (Prseus) Composite, Dounia Boushab, Aniket Mote, Khari Harrison, Juhyeong Lee, Charles U. Pittman Jr., Thomas E. Lacy Jr.

Mechanical and Aerospace Engineering Faculty Publications

Lightning damage to composite aircraft structures results from a concurrent and sequential interaction between arc discharge multi-physics and the anisotropic electrical and thermal composite properties. In this study, the impact of nominal 50 and 125 kA lightning strikes on damage formation in a carbon-epoxy Pultruded Rod Stitched Efficient Unitized Structure (PRSEUS) was investigated. A combination of visual inspection, ultrasonic phased array testing, destructive sectioning, and various microscopy techniques was employed to characterize the damage. Localized damage, including severe matrix decomposition, melting of polyester warp-knitting yarns, fiber splitting, and large-scale delamination, was confined to the immediate vicinity of the lightning attachment …

Programmable And Scalable Bit-Sliced Vlsi Architecture For Decision Tree Based Machine Learning Edge Inference, Raaga Sai Somesula

USF Tampa Graduate Theses and Dissertations

As the volume and diversity of Internet-of-Things (IoT) data continues to grow, traditional cloud-based processing methods face significant challenges, including latency, bandwidth constraints, and privacy concerns. Our research focuses on employing decision trees (DTs) as an intelligent filtering mechanism on the edge. Preliminary comparisons across four datasets revealed DTs are significantly more efficient than multilayer perceptrons (MLP), saving 97-98\% in area and power, leading to the selection of DT for our proposed architecture for lightweight IoT devices. We propose a novel programmable and scalable custom application specific integrated circuit (ASIC) architecture designed for Decision Tree based ML inference. Each bit-slice …

Chronic Obstructive Pulmonary Disease Remote Patient Monitoring Using Spirometry: A Systematic Review, Joseph Nielson

Undergraduate Honors Theses

Chronic obstructive pulmonary disease (COPD) affects an estimated 30 million Americans and is the third leading cause of death worldwide. A recent effort to curb deaths and hospitalizations involves remote patient monitoring (RPM). Of all possible monitoring parameters, spirometry presents itself as potentially helpful. Existing RPM studies using spirometry present software systems in early stages of development that have yet to be tested thoroughly in large trials. Further, the array of data elements and software features that should be combined with spirometry for effective COPD RPM and care have yet to be determined. A meta-analysis was performed to determine a …

Using Lean Six Sigma Methodologies To Improve The Patient Experience At A Local Health Center, Marshall S. Butler

Undergraduate Honors Theses

Lean Six Sigma is a methodology originally designed for a manufacturing context but has process improvement applications that can be used in many fields including medical and business. These tools were applied to addressing issues at a local health center with the aim to help patients receive better medical treatment and have a more positive overall experience. Initial baseline data was collected to identify the core problems patients were experiencing with the health center. Adjustments were made in the survey process to capture more accurate results about the patient experience, which led to the creation of a patient-focused action plan …

On The Use Of Machine Learning And Data-Transformation Methods To Predict Hydration Kinetics And Strength Of Alkali-Activated Mine Tailings-Based Binders, Sahil Surehali, Taihao Han, Jie Huang, Aditya Kumar, Narayanan Neithalath

Electrical and Computer Engineering Faculty Research & Creative Works

The escalating production of mine tailings (MT), a byproduct of the mining industry, constitutes significant environmental and health hazards, thereby requiring a cost-effective and sustainable solution for its disposal or reuse. This study proposes the use of MT as the primary ingredient (≥70%mass) in binders for construction applications, thereby ensuring their efficient upcycling as well as drastic reduction of environmental impacts associated with the use of ordinary Portland cement (OPC). The early-age hydration kinetics and compressive strength of MT-based binders are evaluated with an emphasis on elucidating the influence of alkali activation parameters and the amount of slag or cement …

Advanced Hyperthermia Treatment: Optimizing Microwave Energy Focus For Breast Cancer Therapy, Burak Acar, Tuba Yilmaz Abdolsaheb, Ali Yapar

Turkish Journal of Electrical Engineering and Computer Sciences

This paper presents a fast antenna phase optimization scheme to enable microwave power focusing for breast cancer hyperthermia. The power focusing is achieved through the maximization of the deposited electric field on the target malignant tumor tissue. To do so, a malignant breast tumor, the surrounding breast medium, and the skin of the breast are modeled as a cylindrical structure composed of eccentric cylinders, and electric field distribution is computed analytically in terms of cylindrical harmonics. This approach minimized the computational cost and simplified the breast medium model. To ensure applicability across various breast types, the dielectric properties (DPs) of …

Uncovering And Mitigating Spurious Features In Domain Generalization, Saeed Karimi, Hamdi̇ Di̇bekli̇oğlu

Turkish Journal of Electrical Engineering and Computer Sciences

Domain generalization (DG) techniques strive to attain the ability to generalize to an unfamiliar target domain solely based on training data originating from the source domains. Despite the increasing attention given to learning from multiple training domains through the application of various forms of invariance across those domains, the enhancements observed in comparison to ERM are nearly insignificant under specified evaluation rules. In this paper, we demonstrate that the disentanglement of spurious and invariant features is a challenging task in conventional training since ERM simply minimizes the loss and does not exploit invariance among domains. To address this issue, we …

Evaluation Of Infrared Thermography Dataset For Delamination Detection In Reinforced Concrete Bridge Decks, Eberechi Ichi, Sattar Dorafshan

Civil Engineering Faculty Publications

Structural health monitoring and condition assessment of existing bridge decks is a growing challenge. Conventional manned inspections are costly, labor-intensive, and often risky to execute. Sub-surface delamination, a leading cause of deck replacement, can be autonomously and objectively detected using infrared thermography (IRT) data with developed deep learning AI models to address some of the limitations associated with manned inspection. As one of the most promising classifiers, deep convolutional neural networks (DCNNs) have not been utilized to their fullest potential for delamination detection, arguably due to the scarcity of realistic ground truth datasets. In this study, a common encoder–decoder semantic …

Under Pressure: The Soft Robotic Clap-And-Fling Of Cuvierina Atlantica, Daniel Mead

USF Tampa Graduate Theses and Dissertations

Evolution over billions of years has led to unique animals of all types. The tiny sea butterfly is one that remains mostly anonymous because of its size and low place on the food chain, but it is a swimming creature that when examined closely reveals a surprise. Shockingly, it has a swimming motion nearly identical to small insects flying at intermediate Reynolds numbers, referred to as the clap-and-fling. The centimeter long pteropod flapping briskly at 5Hz escapes attention with its size and speed. Modeling the clap-and-fling motion of the sea butterfly at a larger scale allows the benefits and uniqueness …

Unmanned Aircraft Systems In Road Assessment: A Novel Approach To The Pavement Condition Index And Vizir Methodologies, Diana Marcela Ortega Rengifo, Jose Capa Salinas, Javier Alexander Perez Caicedo, Manuel Alejandro Rojas Manzano

Purdue University Libraries Open Access Publishing Fund

This paper presents an innovative approach to road assessment, focusing on enhancing the Pavement Condition Index (PCI) and Visión Inspection de Zones et Itinéraires Á Risque (VIZIR) methodologies by integrating Unmanned Aircraft System (UAS) technology. The research was conducted in an urban setting, utilizing a UAS to capture high-resolution imagery, which was subsequently processed to generate detailed orthomosaics of road surfaces. This study critically analyzed the discrepancies between traditional field measurements and UAS-derived data in pavement condition assessment. The study findings demonstrate that photogrammetry-derived data from UAS offer at least similar or, in some cases, improved information on the collection …

Civil Rights Nondiscrimination Information For Local Public Agencies, Taffanee Keys

Purdue Road School

This session will discuss new ADA/Title VI.

Local Agency Workforce Challenges & Opportunities, Jennifer L. Sharkey

Purdue Road School

This session will explore the workforce issues faced by Indiana’s local road agencies and provide strategies to inform local leaders and policy makers.

Indot Dynamic Wireless Power Transfer (Dwpt) In-Pavement Ev Charging Pilot Project, Greg Reilly, Aaron Brovont, Tommy E. Nantung

Purdue Road School

INDOT, in collaboration with Purdue University/Aspire and AECOM, is conducting a pilot project for dynamic wireless power transfer (DWPT) on US-52/231 in West Lafayette, IN. High-power DWPT has the potential to reduce range anxiety and allow for smaller and lighter batteries in vehicles. This presentation will give an overview of our project, why this is important for Indiana, how this relates to the future of wirelessly charged vehicles, and other AECOM DWPT projects.