Digital Commons Network^™

Aphid-Ant Relationships: The Role Of Cuticular Hydrocarbons And Different Chemical Stimuli In Triggeringmutualistic Behavior, Amged El-Harairy, Ahmed El-Harairy, Alaa Mahfouz

Department of Chemical and Biomolecular Engineering: Faculty Publications

In ant-aphid interactions, various aphid species offer honeydew to the ant partner and increase their density by ant attendance, whilst others never attend ant species, in which case ants tend to treat them as prey. In this regard, ants should have the ability to distinguish myrmecophile aphid species from non-mutualistic species, so that mutualistic aphids will be accepted as partners rather than prey. Although ant-aphid interactions are now the focus of chemical ecology studies, the role of the different chemical stimuli in determining mutualistic interactions has not been completely clarified. Therefore, we have investigated the cuticular hydrocarbon profile of four …

The Quest For A Sensitive And Accurate Flash Radiation Model: Whole Abdominal Irradiation And Real Time Dosimetry, Noah J G Daniel

Dartmouth College Master’s Theses

Cancer remains the second leading cause of death in the US, and more than 50% of all cancer patients receive radiation therapy (RT), often in combination with surgery, chemotherapy and/or immunotherapy. However, the fundamental limit on radiotherapy treatment efficacy is normal tissue tolerance. One potential way to overcome this limitation is through ultra-high dose rate radiation (FLASH RT). Compared to conventional radiotherapy (CONV RT), FLASH RT has been shown to be just as damaging to cancerous tissue but far more sparing of healthy tissue.

However, clinical translation of FLASH research has been obstructed by the failure of many labs to …

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 …

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 …

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 …

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 …

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 …

Atomic Comagnetometer Gyroscopes For Inertial Navigation Systems: A Review, Murat Salim Karabinaoglu, Bekir Çakir, Mustafa Engin Başoğlu

Turkish Journal of Electrical Engineering and Computer Sciences

In recent years, developments in quantum sensing, laser, and atomic sensor technologies have also enabled advancement in the field of quantum navigation. Atomic-based gyroscopes have emerged as one of the most critical atomic sensors in this respect. In this review, a brief technology statement of spin exchange relaxation free (SERF) and nuclear magnetic resonance (NMR) type atomic comagnetometer gyroscope (CG) is presented. Related studies in the literature have been gathered, and the fundamental compositions of CGs with technical basics are presented. A comparison of SERF and NMR CGs is provided. A basic simulation of SERF CG was carried out because …

Consensus-Based Virtual Leader Tracking Algorithm For Flight Formation Control Of Swarm Uavs, Berat Yıldız, Akif Durdu, Ahmet Kayabaşi

Turkish Journal of Electrical Engineering and Computer Sciences

Technological developments in industrial areas also impact unmanned aerial vehicles (UAVs). Recent improvements in both software and hardware have significantly increased the use of many UAVs in social and military fields. In particular, the widespread use of these vehicles in social areas such as entertainment, shipping, transportation, and delivery and military areas such as surveillance, tracking, and offensive measures has accelerated the research on swarm systems. This study examined the previous investigations on swarm UAVs and aimed to create a more efficient algorithm. The effectiveness of the proposed algorithm was compared with other leader-based applications. A swarm consisting of 5 …

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 …

Nutrient Removal Of Biochar Amended Modified Bioretention Systems Treating Nursery Runoff, Nicholas Richardson

USF Tampa Graduate Theses and Dissertations

Excess inputs of nutrients, such as nitrogen and phosphorus, to surface water bodies can lead to the presence of harmful algal blooms (HABs). HABs can damage their surrounding environments and the economies dependent on them. Nutrient pollution can be properly controlled and monitored at point-sources, such as wastewater treatment plants, but is more difficult to control for non-point sources, such as fertilizer runoff. One form of fertilizer runoff that remains overlooked is runoff from plant nurseries. Controlled release fertilizers (CRFs) embedded in plant containers at nurseries can leach excess nutrients into the runoff. For nurseries in Florida, best management practices …

Anti-Phishing Approach For Iot System In Fog Networks Based On Machine Learning Algorithms, Mahmoud Gad Awwad, Mohamed M. Ashour, El Said A. Marzouk, Eman Abdelhalim

Mansoura Engineering Journal

As the Internet of Things (IoT) continues to expand, ensuring the security and privacyِ of IoT systems becomes increasingly critical. Phishing attacks pose a significant threat to IoT devices and can lead to unauthorized access, data breaches, and compromised functionality. In this paper, we propose an anti-phishing approach for IoT systems in fog networks that leverages machine learning algorithms, including a .fusion with deep learning techniques We explore the effectiveness of eleven traditional machine learning algorithms combined with deep learning in detecting and preventing phishing attacks in IoT systems. By utilizing a diverse range of algorithms, we aim to enhance …

Resolving The Nanoscale Structure Of Β-Sheet Peptide Self-Assemblies Using Single-Molecule Orientation–Localization Microscopy, Weiyan Zhou, Conor L. O'Neill, Tianben Ding, Oumeng Zhang, Jai S. Rudra, Matthew D. Lew

Electrical & Systems Engineering Publications and Presentations

Synthetic peptides that self-assemble into cross-β fibrils are versatile building blocks for engineered biomaterials due to their modularity and biocompatibility, but their structural and morphological similarities to amyloid species have been a long-standing concern for their translation. Further, their polymorphs are difficult to characterize using spectroscopic and imaging techniques that rely on ensemble averaging to achieve high resolution. Here, we utilize Nile red (NR), an amyloidophilic fluorogenic probe, and single-molecule orientation-localization microscopy (SMOLM) to characterize fibrils formed by the designed amphipathic enantiomers KFE8^L and KFE8^D and the pathological amyloid-beta peptide Aβ42. Importantly, NR SMOLM reveals the helical (bilayer) …

Spatiotemporal Reaction Dynamics Control In Two-Photon Polymerization For Enhancing Writing Characteristics, Aofei Mao, Sarah Fess, Nada Kraiem, P. Li, Zhipeng P. Wu, Qiuchi Zhu, Xi Huang, Peixun Fan, Bai Cui, Jean-Francois Silvain, Suxing Hu, Mitchell Anthamatten, Sean P. Regan, David Harding, Yongfeng Lu

Department of Electrical and Computer Engineering: Faculty Publications

Since 2001, 3D microfabrication based on two-photon polymerization (TPP) has drawn extensive attention and interest in biology, optics, photonics, material science, and high-energy physics. The in-volume fabrication capability due to the threshold behavior of two-photon absorption enables TPP higher flexibility compared with other nanofabrication techniques. However, as determined by the in-volume fabrication feature as well as various reaction dynamics, the writing characteristics of TPP, such as throughput, accuracy, surface quality, and fabrication capability, are still limited. Herein, a comprehensive study is performed on the spatiotemporal behavior of reaction dynamics during TPP fabrication, mainly focusing on spatiotemporal characteristics of radical diffusion, …

6d Single-Fluorogen Orientation-Localization Microscopy For Elucidating The Architecture Of Beta-Sheet Assemblies And Biomolecular Condensates, Tingting Wu, Weiyan Zhou, Jai S. Rudra, Rohit V. Pappu, Matthew D. Lew

Electrical & Systems Engineering Publications and Presentations

We develop six-dimensional single-molecule orientation-localization microscopy (SMOLM) to measure the 3D positions and 3D orientations simultaneously of single fluorophores. We show how careful optimization of phase and polarization modulation components can encode phase, polarization, and angular spectrum information from each fluorescence photon into a microscope’s dipole-spread function. We used the transient binding and blinking of Nile red (NR) to characterize the helical structure of fibrils formed by designed amphipathic peptides, KFE8^L and KFE8^D, and the pathological amyloid-beta peptide Aβ42. We also deployed merocyanine 540 to uncover the interfacial architectures of biomolecular condensates.

Single And Dual Cell Encapsulation Via Liquid Core Hydrogels Using Pico Injection, Jade Houston

USF Tampa Graduate Theses and Dissertations

In this project, a comprehensive microfluidic device, along with several interdependent subsystems, was designed and developed in SolidWorks, leveraging a combination of 3D resin printing with biocompatible resin and micromachining with polymethylmethacrylate (PMMA). The microfluidics chip integrated both passive and active components to facilitate its primary function: dual cell encapsulation via liquid core sodium alginate hydrogel droplets.

Integral to the microfluidics chip design were key features including a 5-convolution Archimedes spiral for particle sorting, a flow focusing junction for droplet generation, and a pico injector for injecting additional cells into passing droplets via the manipulation of an electric field.

An …

Comparison Of Conventional And Adaptive Acoustic Beamforming Algorithms Using A Tetrahedral Microphone Array In Noisy Environments, Megan Brittany Ewers

Dissertations and Theses

In situ acoustic measurements are often plagued by interfering sound sources that occur within the measurement environment. Both adaptive and conventional beamforming algorithms, when applied to the outputs of a microphone array arranged in a tetrahedral geometry, are able to capture sound sources in desired directions and reject sound from unwanted directions. Adaptive algorithms may be able to measure a desired sound source with greater spatial precision, but require more calculations and, therefore, computational power. A conventional frequency-domain phase-shift algorithm and a modified adaptive frequency-domain Minimum Variance Distortionless Response (MVDR) algorithm were applied to simulated and recorded signals from a …

Comparing Task Graph Scheduling Algorithms: An Adversarial Approach, Jared Coleman, Bhaskar Krishnamachari

Computer Science Faculty Works

Scheduling a task graph representing an application over a heterogeneous network of computers is a fundamental problem in distributed computing. It is known to be not only NP-hard but also not polynomial-time approximable within a constant factor. As a result, many heuristic algorithms have been proposed over the past few decades. Yet it remains largely unclear how these algorithms compare to each other in terms of the quality of schedules they produce. We identify gaps in the traditional benchmarking approach to comparing task scheduling algorithms and propose a simulated annealing-based adversarial analysis approach called PISA to help address them. We …

Highly Efficient Dopamine Sensing With A Carbon Nanotube-Encapsulated Metal Chalcogenide Nanostructure, Harish Singh, Jiandong Wu, Kurt A.L. Lagemann, Manashi Nath

Chemical and Biochemical Engineering Faculty Research & Creative Works

Carbon nanotube-encapsulated nickel selenide composite nanostructures were used as nonenzymatic electrochemical sensors for dopamine detection. These composite nanostructures were synthesized through a simple, one-step, and environmentally friendly chemical vapor deposition method, wherein the CNTs were formed in situ from pyrolysis of a carbon-rich metallo-organic precursor. The composition and morphology of these hybrid NiSe2-filled carbon nanostructures were confirmed by powder X-ray diffraction, Raman, X-ray photoelectron spectroscopy, and high-resolution transmission electron microscopy images. Electrochemical tests demonstrated that the as-synthesized hybrid nanostructures exhibited outstanding electrocatalytic performance toward dopamine oxidation, with a high sensitivity of 19.62 μA μM-1 cm-2, low detection limit, broad linear …

Feature Engineering And Supervised Machine Learning To Forecast Biogas Production During Municipal Anaerobic Co-Digestion, Hunter W. Schroer, Craig L. Just

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Municipalities with excess anaerobic digestion capacity accept offsite wastes for co-digestion to meet sustainability goals and create more biogas. Despite the benefits inherent to co-digestion, the temporal and compositional heterogeneity of external waste streams creates operational challenges that lead to upsets or conservative co-digestion. Given the complex microbial bioprocesses occurring during anaerobic digestion, prediction and modeling of the outcomes can be challenging, and machine learning has the potential to improve understanding and control of co-digestion processes. Biogas flows are a surrogate for process health, and here, we predicted biogas production from historical data collected by a water resource recovery facility …

Development Of Quantitative Structure Activity Relationships (Qsars) For Predicting The Aggregation Of Tio2 Nanoparticles Under Favorable Conditions, Jaewoong Lee

Department of Civil and Environmental Engineering: Faculty Publications

This study developed multi-linear regression (MLR) quantitative structure-activity relationships (QSARs) to predict n-TiO₂ aggregation in the presence of high concentrations of representative emerging organic contaminants (EOCs), which presented favorable conditions to interaction with n-TiO₂. The largest diameter change (Δ 517 nm at 0 h and Δ 1164 nm at 12 h) of n-TiO₂ was observed by estrone, while the smallest diameter change (Δ -114 nm at 0 h and – 4 nm at 12 h) was observed by lincomycin during experimental periods. In addition, the zeta potential changes of n-TiO₂ were …

Accuracy Of Nitrate Hysteresis And Flushing For Agricultural Watersheds In The Midwest, Noah Rudko, Sara K. W. Mcmillian, Jane Frankenberger, François Birgand

Graduate Industrial Research Symposium

Storm event-based metrics, such as hysteresis (HI) and flushing (FI), are used to differentiate nitrate pathways and sources, which is essential for watershed management. Estimations of these event-based metrics typically use high frequency (15-minute – hourly) measurements, but daily data are also used due to their greater availability. To date, there has been no study assessing how using lower frequency samples affect the accuracy of HI and FI, which could skew interpretation of potential nutrient pathways and sources. We used continuous measurements of nitrate collected at 9 watersheds throughout the Midwest spanning 448 storms. HI and FI were estimated from …

Sustainable Water Treatment Systems In The La Vega Region Of The Dominican Republic, Hannah Fulton, Justina Thomae, Jorge Del Angel, Ramin Ansari, Karina Peate, Rylan Elliott, Adam Spieth, Thalia May, Morgan Jung, Ernest R. Blatchley Iii, Rebecca C. Johnson

Graduate Industrial Research Symposium

Purdue University's service-learning course, Water Supply in Developing Countries (WSDC) is dedicated to ensuring access to safe drinking water in the La Vega region of the Dominican Republic. The focus in the current academic year is to enhance the functionality, sustainability, and independence of community-based water treatment systems installed by previous WSDC students. Despite the construction of four water systems since 2012, operational challenges ensued, rendering them currently inoperable. Our objective is to learn from past mistakes, restore the systems and ensure their continuous functionality. During the fall semester, class members assessed repair needs in two communities with existing systems, …

Autonomous Roadside Mower Testing And Evaluation In Digital Twin Environments, Michael Mardikes, Ethan Brown, Timothy Wiegman, Nathan Sprague, Shreyas Supe, J. T. Evans

Graduate Industrial Research Symposium

Modern day roadside mowing operations in Indiana are performed by contractors operating tractors that pull flex-wing mowers. These mowing operations span over 11,000 miles of road across the state and create serious risk for human operators. Autonomous mowers can provide a safer alternative, but a replacement system must demonstrate an acceptable level of trust before large-scale deployment. A high-fidelity digital-twin environment can facilitate the capability to rapidly test and evaluate platforms in their desired application, while enabling zero real-world risk, a wide range of test variables, and repeatability of a test setup. The simulation environment must be at a level …

A Machine Learning Model Of Perturb-Seq Data For Use In Space Flight Gene Expression Profile Analysis, Liam F. Johnson, James Casaletto, Lauren Sanders, Sylvain Costes

Graduate Industrial Research Symposium

The genetic perturbations caused by spaceflight on biological systems tend to have a system-wide effect which is often difficult to deconvolute it into individual signals with specific points of origin. Single cell multi-omic data can provide a profile of the perturbational effects, but does not necessarily indicate the initial point of interference within the network. The objective of this project is to take advantage of large scale and genome-wide perturbational datasets by using them to train a tuned machine learning model that is capable of predicting the effects of unseen perturbations in new data. Perturb-Seq datasets are large libraries of …

Characterizing Chemistry And Microbiomes During Continuous Anaerobic Codigestion Of Organics And Cattle Manure Digestate, Emily V. Schmitz, Hunter W. Schroer, Timothy E. Mattes, Craig L. Just

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

We characterized chemical and microbial responses to changes in the carbon-to-nitrogen ratio (C:N) and organic loading rate (OLR) during anaerobic codigestion (ACoD) of cattle manure digestate mixed with industrial organics. C:Ns of 25 and 35, both operating at OLRs ≤ 4 gVS L-1 d-1, sustained methane production averages of 0.36 ± 0.03 L gVS-1 d-1 and 0.32 ± 0.05 L gVS-1 d-1, respectively, throughout a 15-day period. Using 16S rRNA high-throughput sequencing coupled with PICRUSt2, taxonomy and predicted gene abundances were mapped to the major ACoD stages. C:N (25, 35) and the OLR (2, 4 gVS L-1 d-1) had minimal …

Composting Reduces The Risks Of Resistome In Beef Cattle Manure At The Transcriptional Level, Yuepeng Sun, Zachery R. Staley, Bryan Woodbury, Jean-Jack Riethoven, Xu Li

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Transcriptomic evidence is needed to determine whether composting is more effective than conventional stockpiling in mitigating the risk of resistome in livestock manure. The objective of this study is to compare composting and stockpiling for their effectiveness in reducing the risk of antibiotic resistance in beef cattle manure. Samples collected from the center and the surface of full-size manure stockpiling and composting piles were subject to metagenomic and metatranscriptomic analyses. While the distinctions in resistome between stockpiled and composted manure were not evident at the DNA level, the advantages of composting over stockpiling were evident at the transcriptomic level in …

Temporospatial Deep Learning Strategies For Prediction Of Disease Progression In Radiology, John D. Mayfield

USF Tampa Graduate Theses and Dissertations

While the fields of machine learning and medicine are deeply rooted in axiomatic scientific principles, there is an element of art that makes the practice imperfect, yet innately human. As the two fields have seen the greatest overlap in their collective history, there remains a chasm between them in terms of practical translation for the patients who desire and deserve personalized medicine. As presented in this dissertation, I and my collaborators have contributed to the groundwork for future exploration of predicting disease progression by identifying signals within sequential medical imaging to provide a temporospatial relationship upon which we can make …

Blow-Spun Hybrid Pcl-Peo/Hnts Scaffolds With Enhanced Biological And Mechanical Properties, Meichen Liu

Doctoral Dissertations

With the development of technology and engineering, nanotechnology has been a multidisciplinary scientific field applied in nearly all science areas, including medicine, genetics, food industry, robotics. In this respect, nanomedicine has gained increasing attention and been a useful, effective therapy for cancer diagnosis, gene transfer, and drug delivery. To design an ideal nano drug delivery system with controlled drug releasing and improved encapsulated drug’s pharmacokinetic and pharmacodynamic profiles, hydrogels and polymer composites have witnessed increased research interest during the last decades. Recently, numerous polymers have been studied to fabricate the ideal wound dressing with biocompatibility, biodegradability, porous structural, and suitable …

Development Of An Integrated Workflow For Nucleosome Modeling And Simulations, Ran Sun

Doctoral Dissertations

Nucleosomes are the building blocks of eukaryotic genomes and thus fundamental to to all genetic processes. Any protein or drug that binds DNA must either cooperate or compete with nucleosomes. Given that a nucleosome contains 147 base pairs of DNA, there are approximately 4^147 or 10^88 possible sequences for a single nucleosome. Exhaustive studies are not possible. However, genome wide association studies can identify individual nucleosomes of interest to a specific mechanism, and today's supercomputers enable comparative simulation studies of 10s to 100s of nucleosomes. The goal of this thesis is to develop and present and end-to-end workflow that serves …