Digital Commons Network^™

Pepblock Builder Vr – An Open-Source Tool For Gaming-Based Bio-Edutainment In Interactive Protein Design, Venkata V. B. Yallapragada, Tianshu Xu, Sidney P. Walker, Sabin Tabirca, Mark Tangney

Cappa Publications

Proteins mediate and perform various fundamental functions of life. This versatility of protein function is an attribute of its 3D structure. In recent years, our understanding of protein 3D structure has been complemented with advances in computational and mathematical tools for protein modelling and protein design. 3D molecular visualisation is an essential part in every protein design and protein modelling workflow. Over the years, stand-alone and web-based molecular visualisation tools have been used to emulate three-dimensional view on computers. The advent of virtual reality provided the scope for immersive control of molecular visualisation. While these technologies have significantly improved our …

Impact Of Angiogenic And Osteogenic Factors In The Presence Of Biodegradable Piezoelectric Films, Jayla Millender

University Scholar Projects

One of the most common causes of bone graft rejection is lack of a vascular network connecting the graft to the existing native tissue – allowing for nutrient flow. Under current grafting techniques, the existing blood vessel network in the patient slowly invades the implant in order to supply the injured site with its necessary nutrients. The purpose of this research is to determine if a synthetic bone graft with a stable microvascular network can be developed in vitro. I hypothesize that the use of indirect angiogenic factors such as sonic hedgehog homolog and hypoxia-inducible factor-1 in combination with the …

Silver Bow Creek/Butte Area Npl Site Butte Priority Soils Operable Unit, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Desalination For Sustainable Water Production With An Emphasis On Low Pressure Distillation, Jessica Vivian Savage

Doctoral Dissertations and Master's Theses

Freshwater resources depletion is a growing concern. This freshwater scarcity motivates research into seawater desalination as a means for alleviating the stresses on water demands. The primary methods of desalination include filtration and distillation. This paper explores the potential energy savings of vacuum distillation for seawater desalination to reduce the amount of energy needed to achieve phase change.

Depending on the vacuum boiler design, the vaporization mechanism may be boiling, evaporation, or cavitation. There is very little literature on cavitation that involves mass transfer, so cavitation is not developed here. This thesis focuses on standard models for boiling and evaporation …

Impact Of Angiogenic And Osteogenic Factors In The Presence Of Biodegradable Piezoelectric Films, Jayla Millender

Honors Scholar Theses

One of the most common causes of bone graft rejection is lack of a vascular network connecting the graft to the existing native tissue – allowing for nutrient flow. Under current grafting techniques, the existing blood vessel network in the patient slowly invades the implant in order to supply the injured site with its necessary nutrients. The purpose of this research is to determine if a synthetic bone graft with a stable microvascular network can be developed in vitro. I hypothesize that the use of indirect angiogenic factors such as sonic hedgehog homolog and hypoxia-inducible factor-1 in combination with the …

Quantum Chemistry Calculations For Metabolomics, Susanta K. Das, Ricardo M. Borges, Sean M. Colby, Arthur S. Edison, Oliver Fiehn, Tobias Kind, Jesi Lee, Amy T. Merrill, Kenneth M. Merz Jr., Thomas O. Metz, Jamie R. Nunez, Dean J. Tantillo, Lee-Ping Wang, Shunyang Wang, Ryan S. Renslow

Mechanical Engineering Publications

A primary goal of metabolomics studies is to fully characterize the small-molecule composition of complex biological and environmental samples. However, despite advances in analytical technologies over the past two decades, the majority of small molecules in complex samples are not readily identifiable due to the immense structural and chemical diversity present within the metabolome. Current gold-standard identification methods rely on reference libraries built using authentic chemical materials (“standards”), which are not available for most molecules. Computational quantum chemistry methods, which can be used to calculate chemical properties that are then measured by analytical platforms, offer an alternative route for building …

A Deep Learning Model For Predicting Covid-19 Transmission In Connecticut, Nathan Choi

Honors Scholar Theses

COVID-19 has immensely impacted life as we know it, as the virus quickly spread throughout the entire world in a matter of weeks since its emergence. It has toppled economies, tested healthcare systems worldwide, and has un- fortunately taken the lives of many in the process. While extensive research has analyzed the issue on a large scale, focusing on entire countries and states, there has not been as much focus on the meso-scale, mainly compris- ing towns and cities, due to the lack of available COVID-19 data at this scale. However, in the case of countries like the United States …

Error Prevention In Sensors And Sensor Systems, Pedro J. Chacon Dominguez

LSU Doctoral Dissertations

Achievements in all fields of engineering and fabrication methods have led towards optimization and integration of multiple sensing devices into a concise system. These advances have caused significant innovation in various commercial, industrial, and research efforts. Integrations of subsystems have important applications for sensor systems in particular. The need for reporting and real time awareness of a device’s condition and surroundings have led to sensor systems being implemented in a wide variety of fields. From environmental sensors for agriculture, to object characterization and biomedical sensing, the application for sensor systems has impacted all modern facets of innovation. With these innovations, …

Tuning Radiation And Microgravity Exposure For Human Brain Organoids, Bailey Mcfarland

Utah Space Grant Consortium

The environment of space, specifically radiation and microgravity, poses a substantial threat to astronauts' brain health. Understanding the damage mechanism and therefore paving the way to finding potential remedies is critical to protect astronauts during space flight. Current models are insufficient at representing the human brain, and insufficient research has been conducted on the effect of radiation and microgravity on the higher structures of the human brain. This ongoing research aims to use brain organoids, a tissue-engineered model that recapitulates the human brain's anatomy and structure and investigate the effects of radiation and microgravity on the brain. At the current …

Identifying Carbon Structure Via Raman Spectroscopy, Nathaniel Bunker

Utah Space Grant Consortium

• Raman Spectroscopy: a method to determine molecular composition.
• Graphene: a conductive, strong, and lightweight material.
• Our Setup: meant for examining biological samples, not optimized for graphene analysis.

Long-Term Spatiotemporal Monitoring And Analysis Of Chlorophyll-A Concentrations In Utah Lake, Kaylee Tanner

Utah Space Grant Consortium

Utah Lake is a unique and valuable natural resource in the semi-arid Utah Valley. Shallow, turbid, eutrophic, and slightly saline, the lake degrades and stabilizes pollution well [1]. The lake is a highly productive ecosystem and provides ecological habitats, water storage, and recreation. Detection of harmful algal blooms (HABs), however, has closed Utah Lake beaches every summer since 2016 [2] and raised concerns over the health of the lake ecosystem [3, 4]. HABs, which involve excessive algal growth that can cause hypoxic and/or toxic water conditions [5], have numerous detrimental effects [6] on lakes and reservoirs in the United States …

Feedback Control Of Particle Positions Using Electric Fields And Chemical Gradients, Mark Mcdonald

Utah Space Grant Consortium

Programmable self-assembly is a promising route to new biomaterial and metamaterial synthesis methods. An important step towards programmable self-assembly is moving component parts to desired locations. We do this by designing and simulating a controller that modifies an external field to move particles on desired paths. We first design a controller using electric fields by modifying established methods, then we apply the insights gained from the electric field controller to a chemical controller that uses model predictive control.

Systematic Design, Optimization, And Sustainability Assessment For Generation Of Efficient Wastewater Treatment Networks, Kirti Maheshkumar Yenkie, Emmanuel A Aboagye, Sean M. Burnham, James Dailey, Rohan Zia, Carley Tran, Maya Desai

Henry M. Rowan College of Engineering Departmental Research

Due to population growth and economic development, there has been an increase in global wastewater (WW) generation footprint. There are different technologies associated with the wastewater treatment (WWT) process. The challenge is to select technologies that minimize the cost of treatment, as well as meet purity requirements. Further, there is a need to integrate sustainability analysis to facilitate a holistic decision. With the application of systems engineering, sustainable and cost-effective solutions can be achieved. In this work, we apply systems engineering to generate a sustainable and cost-effective solution. A superstructure was generated by categorizing technologies into four treatment stages. After …

Breast Cancer Detection From Histopathology Images Using Machine Learning Techniques: A Bibliometric Analysis, Shubhangi A. Joshi, Anupkumar M. Bongale Dr., Arunkumar M. Bongale Dr.

Library Philosophy and Practice (e-journal)

Computer aided diagnosis has become upcoming area of research over past few years. With the advent of machine learning and especially deep learning techniques, the scenario of work flow management in healthcare sector is changing drastically. Artificial intelligence has shown potential in the field of breast cancer care. With datasets for machine learning frameworks getting eventually richer with time, we can definitely get newer insights in the field of breast cancer care. This will help in narrowing down the treatment range for patients and increasing patient survivability. The purpose of this study was to perform bibliometric analysis of the literature …

Exploration Of The Sludge Biodiesel Pathway, Zachary Christman

Department of Agronomy and Horticulture: Dissertations, Theses, and Student Research

Wastewater sludge is an overlooked source of fat, oil, and grease (FOG) that could be converted into biodiesel. The United States produces about 8 million tons of sludge per year. The disposal cost for this amount of sludge is about 2 billion US dollars. The widespread availability and low cost of sludge compared to other biodiesel raw materials make it an economical choice for a renewable fuel. Using sludge as a raw material can produce 25 to 30 mg per gram of fatty acid methyl ester (FAME); the main component of biodiesel. Sludge biodiesel has the potential of transforming a …

Machine Learning Applied To Colloidal Properties Of Perfluorocarbon Nanoemulsions For Imaging In Ards/Ali, Marco Hosfeld

Electronic Theses and Dissertations

Acute Respiratory distress Syndrome (ARDS) and Acute Lung Injury (ALI) are inflammatory lung pathologies consisting of non-hydrostatic pulmonary edema leading to hypoxia and impaired gas exchange in the lungs. ARDS/ALI is both difficult to study and treat as it is not in itself a specific pathology but rather a syndrome consisting of many pathologies that vary case by case. It is, however, consistently characterized by an explosive acute inflammatory response in the lung parenchyma leading to hypoxia. Although time has seen to an increase in the understanding of ARDS/ALI, the mortality rate remains in the range of 30-50%. For these …

Class-Incremental Learning For Wireless Device Identification In Iot, Yongxin Liu, Jian Wang, Jianqiang Li, Shuteng Niu, Houbing Song

Publications

Deep Learning (DL) has been utilized pervasively in the Internet of Things (IoT). One typical application of DL in IoT is device identification from wireless signals, namely Noncryptographic Device Identification (NDI). However, learning components in NDI systems have to evolve to adapt to operational variations, such a paradigm is termed as Incremental Learning (IL). Various IL algorithms have been proposed and many of them require dedicated space to store the increasing amount of historical data, and therefore, they are not suitable for IoT or mobile applications. However, conventional IL schemes can not provide satisfying performance when historical data are not …

Design Optimization Of A Pneumatic Soft Robotic Actuator Using Model-Based Optimization And Deep Reinforcement Learning, Mahsa Raeisinezhad, Nicholas Pagliocca, Behrad Koohbor, Mitja Trkov

Henry M. Rowan College of Engineering Departmental Research

We present two frameworks for design optimization of a multi-chamber pneumatic-driven soft actuator to optimize its mechanical performance. The design goal is to achieve maximal horizontal motion of the top surface of the actuator with a minimum effect on its vertical motion. The parametric shape and layout of air chambers are optimized individually with the firefly algorithm and a deep reinforcement learning approach using both a model-based formulation and finite element analysis. The presented modeling approach extends the analytical formulations for tapered and thickened cantilever beams connected in a structure with virtual spring elements. The deep reinforcement learning-based approach is …

Design Optimization Of A Pneumatic Soft Robotic Actuator Using Model-Based Optimization And Deep Reinforcement Learning, Mahsa Raeisinezhad, Nicholas Pagliocca, Behrad Koohbor, Mitja Trkov

Henry M. Rowan College of Engineering Departmental Research

We present two frameworks for design optimization of a multi-chamber pneumatic-driven soft actuator to optimize its mechanical performance. The design goal is to achieve maximal horizontal motion of the top surface of the actuator with a minimum effect on its vertical motion. The parametric shape and layout of air chambers are optimized individually with the firefly algorithm and a deep reinforcement learning approach using both a model-based formulation and finite element analysis. The presented modeling approach extends the analytical formulations for tapered and thickened cantilever beams connected in a structure with virtual spring elements. The deep reinforcement learning-based approach is …

Device Development For Long-Term Systemic Oral Biologic Drug Delivery, Benjamin Wankum

Department of Mechanical and Materials Engineering: Dissertations, Theses, and Student Research

A biologic drug is a drug that is produced by a living organism. Biologic drugs are used to treat various medical conditions such as arthritis, diabetes, or certain forms of cancers due to their high potency and high selectivity of action. Drawbacks of biologics include their poor stability in the gastrointestinal tract and their poor absorption. In effect, this gives the drugs very low bioavailability and short therapeutic half-lives. To combat these obstacles, current delivery methods include subcutaneous injections at home or intravenous or intramuscular injections in a medical facility.

The overall scientific goal of the research was to utilize …

Detecting A Heterogenous Sample Of Pigmented Melanoma Cell Lines Using Photoacoustic Flow Cytometry, Margaret Cappellano

Electronic Theses and Dissertations

Metastatic melanoma is the deadliest form of skin cancer, which is in part, attributed to its rapid aggression and lack of response to typical treatment methods. There are far too often cases where a lymph node biopsy does not detect the severity of the cancer, which in turn causes a lack of diagnosis until a mass can be visually detected on a scan, such as a PET, CT, or MRI. Once visible on a scan, the cancer is too progressive for successful treatment. To avoid this, we investigated how a blood sample can be used to negate a missed diagnosis, …

Diagnosis Of Melanoma Disease State From Patient Blood Samples Using Photoacoustic Flow Cytometry, Jacob Salvatore

Electronic Theses and Dissertations

Approximately 1 in 50 Americans develop melanoma in their lifetime. Early detection of melanoma is pivotal to the survival of the patient, with a 99% survival rate for 5 or more years after an early diagnosis. Metastasis, or the spread of cancer, increases the chances of cancerous growth in other parts of the body. In this study, we propose the use of photoacoustic flow cytometry as a diagnostic of patient disease state, by closely monitoring the amount of circulating melanoma cells (CMCs) in a patient’s blood before and after chemotherapy treatments. Using this patient data, we were able to make …

Characterizing The Dormancy And Repair Of A Circumneutral Passive Remediation System Receiving Iron And Sulfate-Rich Amd, Garrett Struble

Electronic Theses and Dissertations

The Wingfield Pines remediation system is a ~20-acre circumneutral, gravity-fed system constructed in 2009 to passively remediate Fe from an ~2000 gallon/minute effluent. In 2017, a fracture to the system’s underground cavern caused the AMD effluent to bypass the system, flowing directly into Chartiers Creek and leaving the system decommissioned between 2017-2019. Soil slurry and water samples were collected in the weeks prior to the system’s reinstalment in September 2019 through January 2020 in order to determine the effect of the repair on remediation efficiency and microbial community composition. This study acted as the first to describe the temporary decommissioning …

U-251mg Spheroid Generation Using A Scaffold Based Method Protocol, Lara Carroll, Brijesh K. Tiwari, James F. Curtin, Janith Wanigasekara

Articles

3D cell culture is a technique that is used to grow cells in vitro that will mimic an in vivo environment. 3D cell models are a helpful learning tool for researchers to better understand disease mechanisms and to explore different therapeutic properties of drugs. 3D cell cultures can be developed using patient derived cancer cells. Once they have been grown, these 3D cells can be used to screen for small molecule drugs or for genetic modification in for analysis of disease pathways or to predict drug treatments toxicity or efficacy. 3D cell cultures are a big step towards the more …

Assessment Of Cardiorespiratory Interactions During Life Threatening Events In Preterm Infants Using Point Process And Bivariate Algorithms, Mohammed T. Alenazi

Electrical Engineering Theses

Cardiorespiratory interactions considered as an important indicator of neurodevelopment of preterm infants. The strength of cardiorespiratory interactions are presumed to be weak and rapidly fluctuating. The current signal processing algorithms are insufficient to capture such time varying weak interactions. In addition, detection of these interactions becomes difficult during life threatening events due to lack of information available due to apnea (absence of output from respiratory system) and the transient temporal destabilization of cardiac system due to bradycardia. To detect the cardiorespiratory interactions, a point process algorithm of cardiac system with respiration as covariates is proposed. The bivariate model is embedded …

Translating Convolutional Neural Networks Approach To The Ventral Pathway, Victoria Zhang

McKelvey School of Engineering Graduate Student Theses & Dissertations

Do artificial neurons in CNNs learn to represent the same visual information as the biological neurons in primate brains? Previous studies have shown that the visual recognition pathway (ventral stream) in humans and monkeys increasingly represents animate objects [16]. We used a heatmap attribution technique borrowed from convolutional neural networks to generate biological feature maps identifying regions in scenes that elicit responses from neurons along the ventral stream (V1/V2, V4, and IT). Biological feature maps were then compared to activation maps produced by units in convolutional neural networks. We found that image regions containing animals elicited increasingly larger responses along …

Artificial Intelligence And The Ethics Behind It, Isaac Johnston

Senior Honors Theses

Artificial intelligence (AI) has been a widely used buzzword for the past couple of years. If there is a technology that works without human interaction, it is labeled as AI. But what is AI, and should individuals be concerned? The following research aims to define what artificial intelligence is, specifically machine learning (ML) and neural networks. It is important to understand how AI is used today in cars, image recognition, ad marketing, and other areas. Although AI has many benefits, there are areas of ethical concerns such as autonomous cars, military applications, social media marketing, and others. This paper helps …

Assessment And Improvement Of Performance Of Septic Systems In Cold Climates (Year 1), Stu Geza, Todd Menkhaus, Lianping Li, Galen Hoogestraat

SDWRI Publications and Reports

Onsite septic systems are used for wastewater treatment for households not connected to sewers. There is a concern about surface and groundwater pollution when effectiveness becomes limited due to soil texture, soil temperature, neighborhood density, and distance to water resources. The goal of this study was to assess treatment performance of local soils and selected treatment media. Lab-scale column experiments were conducted using wastewater from Wastewater Reclamation Facility in Rapid City. The experiments were conducted inside and outside the lab to evaluate the effect of temperature. The columns outside the lab were subject to seasonal variation in temperature. Moisture content, …

Post Covid-19 Water And Waste Water Management To Protect Public Health And Geoenvironment, Ken Cornell, Arvin Farid

Chemistry and Biochemistry Faculty Publications and Presentations

The coronavirus disease 2019 pandemic has posed severe threats to humans and the geoenvironment. The findings of severe acute respiratory syndrome coronavirus 2 (Sars-CoV-2) traces in waste water and the practice of disinfecting outdoor spaces in several cities in the world, which can result into the entry of disinfectants and their by-products into storm drainage systems and their subsequent discharge into rivers and coastal waters, raise the issue of environmental, ecological and public health effects. The aims of the current paper are to investigate the potential of water and waste water to operate as transmission routes for Sars-CoV-2 and the …

Expanding Image Datasets For Deep Learning By Evaluating Independence Through Coefficient Correlation And Mean-Squared Error, Ayman Yousef

Biomedical Engineering Undergraduate Honors Theses

With deep learning being leveraged more regularly in the field of image classification, particularly in medical imaging, network optimizations have become a field in and of itself. With open source, comprehensive medical image datasets few and far, computational dataset expansion has become a useful tool for researchers without the ability to further manually collect data. However, with the rich amount of data that imaging modalities like multi-photon microscopy collect at a time, there is potential to expand datasets through proper utilization of this data that often time goes unused. Previous deep learning studies have shown that improper expansion can conflate …