Digital Commons Network^™

How The Value Of The Environment Controls Persistence In Visual Search, Michael R. Traner, Ethan S. Bromberg-Martin, Ilya E. Monosov

Open Access Publications

Classic foraging theory predicts that humans and animals aim to gain maximum reward per unit time. However, in standard instrumental conditioning tasks individuals adopt an apparently suboptimal strategy: they respond slowly when the expected value is low. This reward-related bias is often explained as reduced motivation in response to low rewards. Here we present evidence this behavior is associated with a complementary increased motivation to search the environment for alternatives. We trained monkeys to search for reward-related visual targets in environments with different values. We found that the reward-related bias scaled with environment value, was consistent with persistent searching after …

Neutrophil Extracellular Trap Inhibition Increases Inflammation, Bacteraemia And Mortality In Murine Necrotizing Enterocolitis, Hala Chaaban, Kathryn Burge, Jeffrey Eckert, Ravi S Keshari, Robert Silasi, Cristina Lupu, Barbara Warner, Marilyn Escobedo, Michael Caplan, Florea Lupu

Open Access Publications

Necrotizing enterocolitis (NEC) is a devastating gastrointestinal disease affecting primarily premature infants. The disease is characterized by intestinal inflammation and leucocyte infiltration, often progressing to necrosis, perforation, systemic inflammatory response and death. Neutrophil extracellular traps (NETs), denoting nuclear DNA, histone and antimicrobial protein release, have been suggested to play a role in NEC. This study aimed to determine the role of NETs in NEC and explore the effect of chloramidine, a NET inhibitor, on a murine NEC-like intestinal injury model. Blood and intestinal tissues were collected from infants diagnosed with ≥ Stage II NEC, and levels of nucleosomes and NETs, …

From Canines To Humans: Clinical Importance Of Staphylococcus Pseudintermedius, Karen C. Carroll, Carey-Ann D. Burnham, Lars F. Westblade

Open Access Publications

No abstract provided.

Screening Of Severe Acute Respiratory Syndrome Coronavirus 2 Rna-Dependent Rna Polymerase Inhibitors Using Computational Approach, Poonam Dhankhar, Vikram Dalal, Viney Kumar

Open Access Publications

The detrimental effect of coronavirus disease 2019 (COVID-19) pandemic has manifested itself as a global crisis. Currently, no specific treatment options are available for COVID-19, so therapeutic interventions to tackle the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection must be urgently established. Therefore, cohesive and multidimensional efforts are required to identify new therapies or investigate the efficacy of small molecules and existing drugs against SARS-CoV-2. Since the RNA-dependent RNA Polymerase (RdRP) of SARS-CoV-2 is a promising therapeutic target, this study addresses the identification of antiviral molecules that can specifically target SARS-CoV-2 RdRP. The computational approach of drug development was …

Adolescent Brain Cognitive Development (Abcd) Study Linked External Data (Led): Protocol And Practices For Geocoding And Assignment Of Environmental Data, Chun Chieh Fan, Andrew Marshall, Harry Smolker, Marybel R Gonzalez, Susan F Tapert, Deanna M Barch, Elizabeth Sowell, Gayathri J Dowling, Carlos Cardenas-Iniguez, Jessica Ross, Wesley K Thompson, Megan M Herting

Open Access Publications

Our brain is constantly shaped by our immediate environments, and while some effects are transient, some have long-term consequences. Therefore, it is critical to identify which environmental risks have evident and long-term impact on brain development. To expand our understanding of the environmental context of each child, the Adolescent Brain Cognitive Development (ABCD) Study® incorporates the use of geospatial location data to capture a range of individual, neighborhood, and state level data based on the child's residential location in order to elucidate the physical environmental contexts in which today's youth are growing up. We review the major considerations and types …

Comparison Of Machine Learning Clustering Algorithms For Detecting Heterogeneity Of Treatment Effect In Acute Respiratory Distress Syndrome: A Secondary Analysis Of Three Randomised Controlled Trials, Pratik Sinha, Alexandra Spicer, Kevin L Delucchi, Daniel F Mcauley, Carolyn S Calfee, Matthew M Churpek

Open Access Publications

BACKGROUND: Heterogeneity in Acute Respiratory Distress Syndrome (ARDS), as a consequence of its non-specific definition, has led to a multitude of negative randomised controlled trials (RCTs). Investigators have sought to identify heterogeneity of treatment effect (HTE) in RCTs using clustering algorithms. We evaluated the proficiency of several commonly-used machine-learning algorithms to identify clusters where HTE may be detected.

METHODS: Five unsupervised: Latent class analysis (LCA), K-means, partition around medoids, hierarchical, and spectral clustering; and four supervised algorithms: model-based recursive partitioning, Causal Forest (CF), and X-learner with Random Forest (XL-RF) and Bayesian Additive Regression Trees were individually applied to three prior …

Identification Of Histone Deacetylase Inhibitors With (Arylidene)Aminoxy Scaffold Active In Uveal Melanoma Cell Lines, Susanna Nencetti, Doretta Cuffaro, Elisa Nuti, Lidia Ciccone, Armando Rossello, Marina Fabbi, Flavio Ballante, Gabriella Ortore, Grazia Carbotti, Francesco Campelli, Irene Banti, Rosaria Gangemi, Garland R Marshall, Elisabetta Orlandini

Open Access Publications

Uveal melanoma (UM) represents an aggressive type of cancer and currently, there is no effective treatment for this metastatic disease. In the last years, histone deacetylase inhibitors (HDACIs) have been studied as a possible therapeutic treatment for UM, alone or in association with other chemotherapeutic agents. Here we synthesised a series of new HDACIs based on the SAHA scaffold bearing an (arylidene)aminoxy moiety. Their HDAC inhibitory activity was evaluated on isolated human HDAC1, 3, 6, and 8 by fluorometric assay and their binding mode in the catalytic site of HDACs was studied by molecular docking. The most promising hit was …

Insulin And Glucose Metabolism With Olanzapine And A Combination Of Olanzapine And Samidorphan: Exploratory Phase 1 Results In Healthy Volunteers, Frederico G S Toledo, William F Martin, Linda Morrow, Carine Beysen, Daiva Bajorunas, Ying Jiang, Bernard L Silverman, David Mcdonnell, Mark N Namchuk, John W Newcomer, Christine Graham

Open Access Publications

A combination of olanzapine and samidorphan (OLZ/SAM) received US Food and Drug Administration approval in May 2021 for the treatment of adults with schizophrenia or bipolar I disorder. OLZ/SAM provides the efficacy of olanzapine, while mitigating olanzapine-associated weight gain. This exploratory study characterized the metabolic profile of OLZ/SAM in healthy volunteers to gain mechanistic insights. Volunteers received once-daily oral 10 mg/10 mg OLZ/SAM, 10 mg olanzapine, or placebo for 21 days. Assessments included insulin sensitivity during an oral glucose tolerance test (OGTT), hyperinsulinemic-euglycemic clamp, other measures of glucose/lipid metabolism, and adverse event (AE) monitoring. Treatment effects were estimated with analysis …

Butte Priority Soils Operable Unit (Bpsou) Insufficiently Reclaimed Sites - Field Sampling Plan (Fsp) Bres No. 154 – Clark Mill Tailings Ne., Mike Mcanulty

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Classifying Electrocardiogram With Machine Learning Techniques, Hillal Jarrar

Master's Theses

Classifying the electrocardiogram is of clinical importance because classification can be used to diagnose patients with cardiac arrhythmias. Many industries utilize machine learning techniques that consist of feature extraction methods followed by Naive- Bayesian classification in order to detect faults within machinery. Machine learning techniques that analyze vibrational machine data in a mechanical application may be used to analyze electrical data in a physiological application. Three of the most common feature extraction methods used to prepare machine vibration data for Naive-Bayesian classification are the Fourier transform, the Hilbert transform, and the Wavelet Packet transform. Each machine learning technique consists of …

Millipyde: A Cross-Platform Python Framework For Transparent Gpu Acceleration, James B. Asbury

Master's Theses

The prevalence of general-purpose GPU computing continues to grow and tackle a wider variety of problems that benefit from GPU-acceleration. This acceleration often suffers from a high barrier to entry, however, due to the complexity of software tools that closely map to the underlying GPU hardware, the fast-changing landscape of GPU environments, and the fragmentation of tools and languages that only support specific platforms. Because of this, new solutions will continue to be needed to make GPGPU acceleration more accessible to the developers that can benefit from it. AMD’s new cross-platform development ecosystem ROCm provides promise for developing applications and …

Optimizing A Virtual Human Platform For Depression/Suicide Ideation Identification For The American Soldier, Christina M. Monahan

Master's Theses

Suicide surpassed homicide to be the second leading cause of death among people 10-24 years old in the United States \cite{1}. This statistic is alarming especially when combined with the more than eight distinctly different types of clinical depression among society today \cite{2}. To further complicate this health crisis, let’s consider the current worldwide isolating pandemic often referred to as COVID-19 that has spanned 12 months. It is more important than ever to consider how we can get ahead of the crisis by identifying the symptoms as they set in and more importantly ahead of the decision to commit suicide. …

Jited: A Framework For Jit Education In The Classroom, Caleb Watts

Master's Theses

The study of programming languages is a rich field within computer science, incorporating both the abstract theoretical portions of computer science and the platform specific details. Topics studied in programming languages, chiefly compilers or interpreters, are permanent fixtures in programming that students will interact with throughout their career. These systems are, however, considerably complicated, as they must cover a wide range of functionality in order to enable languages to be created and run. The process of educating students thus requires that the demanding workload of creating one of the systems be balanced against the time and resources present in a …

Benchmark Testing Of Gold Ribbon Bonds On Thin-Film Microchips With New Gold Ribbon Auto-Bonder, Austin Conrad

Master's Theses

The focus of this document is on the gold ribbon bond testing and creation of a bonding map for the new gold ribbon Auto-Bonder at Keysight Technologies in Santa Rosa, California. The new Auto-Bonder replaces a nearly 50-year-old machine that no longer had any documentation for the original process of thin-film microchip ribbon bonding. The original process was developed in the early 1970s to provide an electrical connection from the top to the bottom of the microchip. The electrical connection takes the place of what would be a via in a modern silicon microchip. Gold wire bonding is a common …

Wi-Fi Sensing: Device-Free In-Zone Object Movement Detection, Nicholas P. Schnorr

Master's Theses

Wi-Fi Sensing is becoming a prominent field with a wide range of potential applications. Using existing hardware on a wireless network such as access points, cell phones, and smart home devices, important information can be inferred about the current physical environment. Through the analysis of Channel State Information collected in the Neighborhood Discovery Protocol process, the wireless network can detect disturbances in Wi-Fi signals when the physical environment changes. This results in a system that can sense motion within the Wi-Fi network, allowing for movement detection without any wearable devices.

The goal of this thesis is to answer whether Wi-Fi …

On The Mobility Of Small Aperture Telescopes For Initial Orbit Determination And Apparent Magnitude Derivation Of Low Earth Satellites, Jonathan Ian Hernandez

Master's Theses

Maintaining Space Domain Awareness (SDA) of satellites in low Earth orbit (LEO) requires effective methods of tracking and characterization. Optical measurements of these objects are generally sparse due to limited access intervals and high angular rates. Light pollution and geographic obstructions may also preclude consistent observations. However, a mobile small aperture telescope grants the ability to minimize such environmental effects, thereby increasing capture likelihoods for objects within this regime. By enhancing LEO satellite visibility in this way, extensive orbital and visual data are obtainable.

An 8-inch Meade LX200GPS telescope equipped with a Lumenera SKYnyx2-0M CCD camera comprises the system that …

Characterizing Direction Specific Ganglion Cell Receptor Activation Using A Perturbation Based Decomposition Method, Camila Paola Monchini Moline

Master's Theses

Characterizing postsynaptic current signals in the retina by neuroreceptor activation frequency is important for studying the mechanism of action behind phototransduction of varied visual stimuli. A better understanding could in turn lead to the creation of methods for early detection and prevention of debilitating optical neuropathies, such as glaucoma, age-related macular degeneration, and retinitis pigmentosa. More recent in-vitro and in-vivo studies have aimed to differentiate the effects of various neurotransmitters, such as acetylcholine, GABA, and glutamate, on receiving and processing different types of visual stimuli from the retina into the visual cortex.

The focus of this work will be to …

Assessing The Effects Of Oxaliplatin On An In Vitro Three-Dimensional Human Colorectal Cancer Model, Sabrina Nelson

Master's Theses

Colorectal cancer is the third most common cancer in the United States with a 5-year late-stage survival rate of only 14%. Due to the lack of translation between animal models and clinical trials as well as the inefficacy of many chemotherapeutics in initial clinical trials, researchers are turning to in vitro drug screening models in an effort to mimic the conditions in vivo. This research project aimed to validate an in vitro tumor culture model within a microfluidic device using a clinically relevant chemotherapy drug. The first experiment consisted of a cell density and drug concentration study to determine …

Indoor Positioning Using Synchronized Ultrasonic Ofdma Signals, Julian Bartolone

Master's Theses

This paper proposes a method of short-range indoor localization using differential phase measurements of synchronized two-tone ultrasonic signals in an Orthogonal Frequency Multiple Access (OFDMA) scheme. This indoor positioning system (IPS) operates at an ultrasonic frequency of approximately 40kHz and synchronizes using an infrared signal. The OFDMA scheme allows for a receiver to process the signals from multiple transmitters continuously without the signals interfering with each other. The phases of the signals are measured using Goertzel Filters, allowing for low-complexity frequency content analysis. A MATLAB simulation using the proposed localization method is performed using four transmitter nodes in the corners …

Performance Loss Rate And Temperature Modeling In Predictive Energy Yield Programs For Utility-Scale Solar Power Plants, Katelynn M. Dinius

Master's Theses

The Gold Tree Solar Farm, designed by REC Solar, has a rated output power of 4.5 MW and began operation in 2018 to provide electricity to Cal Poly’s campus. Gold Tree Solar Farm site terrain consists of rolling hills and uneven slopes. The uneven typography results in interrow shading, requiring a modified tracking control algorithm to maximize power production. Predicting a utility solar field’s lifetime energy yield is a critical step in assessing project feasibility and calculating project revenue. The MATLAB-based predictive power model developed for this field overpredicted power in the middle of the day. The purpose of this …

Foreword: Law + Computation: An Algorithm For The Rule Of Law And Justice?, Daniel W. Linna Jr.

Northwestern Journal of Technology and Intellectual Property

No abstract provided.

The Legislative Recipe: Syntax For Machine-Readable Legislation, Megan Ma, Bryan Wilson

Northwestern Journal of Technology and Intellectual Property

Legal interpretation is a linguistic venture. In judicial opinions, for example, courts are often asked to interpret the text of statutes and legislation. As time has shown, this is not always as easy as it sounds. Matters can hinge on vague or inconsistent language and, under the surface, human biases can impact the decision-making of judges. This raises an important question: what if there was a method of extracting the meaning of statutes consistently? That is, what if it were possible to use machines to encode legislation in a mathematically precise form that would permit clearer responses to legal questions? …

Machine-Learning-Based Approach To Decoding Physiological And Neural Signals, Elnaz Lashgari

Computational and Data Sciences (PhD) Dissertations

In recent years, machine learning algorithms have been developing rapidly, becoming increasingly powerful tools in decoding physiological and neural signals. The aim of this dissertation is to develop computational tools, and especially machine learning techniques, to identify the most effective methods for feature extraction and classification of these signals. This is particularly challenging due to the highly non-linear, non-stationery, and artifact- and noise-prone nature of these signals.

Among basic human-control tasks, reaching and grasping are ubiquitous in everyday life. I investigated different linear and non-linear dimensionality reduction techniques for feature extraction and classification of electromyography (EMG) during a reach-grasp-lift task. …

Improving Maternal And Child Health In Pakistan: A Programme Evaluation Using A Difference In Difference Analysis, Muhammad Ashar Malik, Lara Riedige Rohm, Pieter Van Baal, Eddy Van Doorslaer Van Doorslaer

Community Health Sciences

Introduction: Pakistan is a country with high maternal and infant mortality. Several large foreign funded projects were targeted at improving maternal, neonatal and child health. The Norway-Pakistan Partnership Initiative (NPPI) was one of these projects. This study aims to evaluate whether NPPI was successful in improving access and use of skilled maternal healthcare.
Methods: We used data from three rounds (2009-2010, 2011-2012 and 2013-2014) of the Pakistan Social and Living Standards Measurement Survey (PSLM). A difference-in-difference regression framework was used to estimate the effectiveness of NPPI and its different programme components with respect to maternal healthcare seeking behaviour of pregnant …

Cloud Internet Of Things For The Smart Environment Of A Smart City, Junho Kim

Electronic Theses, Projects, and Dissertations

The environmental service area for smart city construction provides sustainability, economic, stage, and safe energy savings in building a smart city. The smart environment monitoring system can manage the agricultural environment, water quality, and air quality of smart cities through the Internet of Things and cloud computing technology. Smart environmental monitoring (SEM) systems to reduce environmental problems in smart cities are important service domains that can improve citizens' quality of life. The purpose of this project is to identify services through the introduction of technologies to solve environmental problems in smart cities, the use and management of the technologies introduced. …

Integration Of Blockchain Technology Into Automobiles To Prevent And Study The Causes Of Accidents, John Kim

Electronic Theses, Projects, and Dissertations

Automobile collisions occur daily. We now live in an information-driven world, one where technology is quickly evolving. Blockchain technology can change the automotive industry, the safety of the motoring public and its surrounding environment by incorporating this vast array of information. It can place safety and efficiency at the forefront to pedestrians, public establishments, and provide public agencies with pertinent information securely and efficiently. Other industries where Blockchain technology has been effective in are as follows: supply chain management, logistics, and banking. This paper reviews some statistical information regarding automobile collisions, Blockchain technology, Smart Contracts, Smart Cities; assesses the feasibility …

Supply Chain Management Integration With Blockchain, Venkat Veramallu

Electronic Theses, Projects, and Dissertations

Maintaining the integrity of data within the supply chain is a challenge. Many current implementations lack a capability to provide a trustworthy system for the stakeholders in a supply chain, making communication amongst stakeholders easy but unreliable. Organizations are considering blockchain technology as it provides access control, immutability, transparency and trust amongst the stakeholders in a supply chain. This project is an investigative study on the benefits and challenges of implementing blockchain technology in supply chain management, a framework for integration of blockchain technology, and a project prototype which shows a blockchain use case implementation in supply chain management. The …

Phishing For All Ages, Rachana Vann

Electronic Theses, Projects, and Dissertations

Since the start of the pandemic in 2020 and the increase in teleworking, we have witnessed a subsequent increase in cyber-attacks. This project focused on the tools and techniques a teleworker should use to stay safe from online predators. An online predator or hacker is defined as someone who uses the internet to get access to proprietary information or seek a ransom. This project sought to introduce tools and techniques that would help people of all ages to stay safe online. The questions asked were: What techniques do online predators use to lure their unsuspecting victims? On the American Generation …

Measure And Integration, Jeonghwan Lee

Electronic Theses, Projects, and Dissertations

Measure and Integral are important when dealing with abstract spaces such as function spaces and probability spaces. This thesis will cover Lebesgue Measure and Lebesgue integral. The Lebesgue integral is a generalized theory of Riemann integral learned in mathematics. The Riemann integral is centered on the domain of the function, but the Lebesgue integral is different in that it is centered on the range of the function, and uses the basic concept of analysis. Measure and integral have widely applied not only to mathematics but also to other fields.

Shopping For A Cause: Social Influencers, Performative Allyship, And The Commodification Of Activism, Emily Mckellar

Electronic Theses, Projects, and Dissertations

Since the early 2010s, social media has been a powerful tool for protestors and activists throughout the world. In times of crisis and political uprisings, users have pulled out their phones and taken to platforms like Twitter, Facebook, and, more recently, Instagram, to capture “the revolution” in real time. Although originally intended for networking purposes, social media has provided people with a digital space to share their stories, disseminate resources, and broadcast live, allowing them to share their efforts with millions.

While social media has helped assemble protests, amplify marginalized voices, and educate the public, it has also become a …