Physical Sciences and Mathematics Commons^™

Interannual Variability And Seasonal Dynamics Of Evapotranspiration Of Arundo Donax L. And Populations Of Its Biological Control Agent (Tetramesa Romana), Alexis Racelis, Pradeep Wagle, Jose R. Escamilla Jr., John A. Goolsby, Prasanna Gowda

School of Earth, Environmental, & Marine Sciences Faculty Publications

Giant reed (Arundo donax L.), a woody grass native to the Mediterranean, has become a cause of concern for national water security in its invaded range of the arid southwestern United States, Australia, New Zealand, and South Africa. The main objective of this study was to provide the first, landscape-level estimates of water use by giant reed. The study utilized the eddy covariance method to quantify evapotranspiration (ET) throughout the 2014 and 2015 growing seasons along the Rio Grande River in Eagle Pass, Texas. We monitored ET concurrently with the implementation of a biological control program targeting giant reed. …

A Subsurface Eddy Associated With A Submarine Canyon Increases Availability And Delivery Of Simulated Antarctic Krill To Penguin Foraging Regions, K. Hudson, M. J. Oliver, J. Kohut, Michael S. Dinniman, John M. Klinck, M. A. Cimino, K. S. Bernard, H. Statscewich, W. Fraser

OES Faculty Publications

The distribution of marine zooplankton depends on both ocean currents and swimming behavior. Many zooplankton perform diel vertical migration (DVM) between the surface and subsurface, which can have different current regimes. If concentration mechanisms, such as fronts or eddies, are present in the subsurface, they may impact zooplankton near-surface distributions when they migrate to near-surface waters. A subsurface, retentive eddy within Palmer Deep Canyon (PDC), a submarine canyon along the West Antarctic Peninsula (WAP), retains diurnal vertically migrating zooplankton in previous model simulations. Here, we tested the hypothesis that the presence of the PDC and its associated subsurface eddy increases …

Frequent Mental Distress Among Adults In The United States And Its Association With Socio-Demographic Characteristics, Unhealthy Lifestyle, And Chronic Physical Health Status, Mamunur Rashid, M. Mazharul Islam, Aiping Li, Naima Shifa

Mathematics Faculty Publications

Frequent mental distress (FMD) is a measure of poor mental health days for at least 14 days out of 30 days. It is one of the important dimensions of the health-related quality of life. The underlying causes of FMD are diverse. However, the issue has not been explored extensively due to the lack of reliable data on mental health. The aim of this study was to examine the level and trends of FMD among the adults of the United States (US) and identify the socio-demographic, lifestyles, and chronic health outcomes related correlates of FMD. The data for the study was …

Monitoring And Modelling The Dynamics Of The Cellular Glycolysis Pathway: A Review And Future Perspectives, Nitin Patil, Hugh Byrne, Orla L. Howe, Paul A. Cahill

Articles

Background

The dynamics of the cellular glycolysis pathway underpin cellular function and dysfunction, and therefore ultimately health, disease, diagnostic and therapeutic strategies. Evolving our understanding of this fundamental process and its dynamics remains critical.

Scope of review

This paper reviews the medical relevance of glycolytic pathway in depth and explores the current state of the art for monitoring and modelling the dynamics of the process. The future perspectives of label free, vibrational microspectroscopic techniques to overcome the limitations of the current approaches are considered.

Major conclusions

Vibrational microspectroscopic techniques can potentially operate in the niche area of limitations of other …

Analysis Of Sex-Specific Prostanoid Production Using A Mouse Model Of Selective Cyclooxygenase-2 Inhibition, Rita K. Upmacis, Wendy L. Becker, Donna M. Rattendi, Raven S. Bell, Kelsey D. Jordan, Shayan Saniei, Elena Mejia

Faculty Papers and Publications

Background: Prostanoids are a family of lipid mediators formed from arachidonic acid by cyclooxygenase enzymes and serve as biomarkers of vascular function. Prostanoid production may be different in males and females indicating that different therapeutic approaches may be required during disease.

Objecti ves: We examined sex-dependent differences in COX-related metabolites in genetically modified mice that produce a cyclooxygenase- 2 (COX2) enzyme containing a tyrosine 385 to phenylalanine (Y385F) mutation. This mutation renders the COX2 enzyme unable to form a key intermediate radical required for complete arachidonic acid metabolism and provides a model of selective COX2 inhibition.

Design and …

Privacy Concerns With Using Public Data For Suicide Risk Prediction Algorithms: A Public Opinion Survey Of Contextual Appropriateness, Michael Zimmer, Sarah Logan

Computer Science Faculty Research and Publications

Purpose

Existing algorithms for predicting suicide risk rely solely on data from electronic health records, but such models could be improved through the incorporation of publicly available socioeconomic data – such as financial, legal, life event and sociodemographic data. The purpose of this study is to understand the complex ethical and privacy implications of incorporating sociodemographic data within the health context. This paper presents results from a survey exploring what the general public’s knowledge and concerns are about such publicly available data and the appropriateness of using it in suicide risk prediction algorithms.

Design/methodology/approach

A survey was developed to measure …

Testing The Efficiency Of The Nfl Betting Market, Ryan Earl Oswald

Honors Program Theses

This paper seeks to investigate the NFL betting market, using statistical and economic tests to challenge the Efficient Market Hypothesis’ claim that it is efficient and no strategy can be expected to make a profit. Specifically, this paper studies the spread, over-under, and money line markets to see if each is efficient on their own and as a collective. In looking to see how these lines can influence the outcomes of each other, this paper finds a number of strategies that were profitable over the timeframe of the data. This shows that the NFL betting market was not completely efficient …

Chromatography-Mass Spectroscopy Analysis Of Native American Pottery For Maple Syrup Residues, Alexis Wirtz

Honors Program Theses

The research conducted regards whether or not Native Americans understood how to create maple syrup before the influence of Europeans. The analytical technique that was used is gas chromatography-mass spectrometry (GC-MS). This technique assisted in understanding what organic residues resided within the pottery and what those organic residues tell us about Native American history. An analysis of organic residues was performed on the following types of pottery: proof of concept pottery, weathered pottery (an analog of the proof of concept), and Native American pottery. The residues used in analysis were obtained through the usage of different solvent systems - Acetone: …

Contextualized Vector Embeddings For Malware Detection, Vinay Pandya

Master's Projects

Malware classification is a technique to classify different types of malware which form an integral part of system security. The aim of this project is to use context dependant word embeddings to classify malware. Tansformers is a novel architecture which utilizes self attention to handle long range dependencies. They are particularly effective in many complex natural language processing tasks such as Masked Lan- guage Modelling(MLM) and Next Sentence Prediction(NSP). Different transfomer architectures such as BERT, DistilBert, Albert, and Roberta are used to generate context dependant word embeddings. These embeddings would help in classifying different malware samples based on their similarity …

Investigating Lattice-Based Cryptography, Michaela Molina

Master's Projects

Cryptography is important for data confidentiality, integrity, and authentication. Public key cryptosystems allow for the encryption and decryption of data using two different keys, one that is public and one that is private. This is beneficial because there is no need to securely distribute a secret key. However, the development of quantum computers implies that many public-key cryptosystems for which security depends on the hardness of solving math problems will no longer be secure. It is important to develop systems that have harder math problems which cannot be solved by a quantum computer.

In this project, two public-key cryptosystems which …

Multi-Step Prediction Using Tree Generation For Reinforcement Learning, Kevin Prakash

Master's Projects

The goal of reinforcement learning is to learn a policy that maximizes a reward function. In some environments with complete information, search algorithms are highly useful in simulating action sequences in a game tree. However, in many practical environments, such effective search strategies are not applicable since their state transition information may not be available. This paper proposes a novel method to approximate a game tree that enables reinforcement learning to use search strategies even in incomplete information environments. With an approximated game tree, the agent predicts all possible states multiple steps into the future and evaluates the states to …

Jparsec - A Parser Combinator For Javascript, Sida Zhong

Master's Projects

Parser combinators have been a popular parsing approach in recent years. Compared with traditional parsers, a parser combinator has both readability and maintenance advantages.

This project aims to construct a lightweight parser construct library for Javascript called Jparsec. Based on the modular nature of a parser combinator, the implementation uses higher-order functions. JavaScript provides a friendly and simple way to use higher-order functions, so the main construction method of this project will use JavaScript's lambda functions. In practical applications, a parser combinator is mainly used as a tool, such as parsing JSON files.

In order to verify the utility of …

Using Machine Learning To Maximize First-Generation Student Success A Contribution To The Mission Of Aiding The Underserved, Mustafa Emre Yesilyurt

Master's Projects

The Leadership and Career Accelerator (UNVS 101) is a course offered at San José State University (SJSU) designed to hone industry skills in and provide support to students of underserved backgrounds. The main goal of this study is to determine which features are most significant to identifying the students at risk of failing the course. This will allow faculty to better focus data collection efforts and facilitate an increase in classifier accuracy. The data came as three distinct sets (sources). One contained features describing student demographics and academic history, another described the students’ experience in the course, and a third …

A Study On Human Face Expressions Using Convolutional Neural Networks And Generative Adversarial Networks, Sriramm Muthyala Sudhakar

Master's Projects

Human beings express themselves via words, signs, gestures, and facial emotions. Previous research using pre-trained convolutional models had been done by freezing the entire network and running the models without the use of any image processing techniques. In this research, we attempt to enhance the accuracy of many deep CNN architectures like ResNet and Senet, using a variety of different image processing techniques like Image Data Generator, Histogram Equalization, and UnSharpMask. We used FER 2013, which is a dataset containing multiple classes of images. While working on these models, we decided to take things to the next level, and we …

Editorial: Coastal Flooding: Modeling, Monitoring, And Protection Systems, Valentina Prigiobbe, Clint Dawson, Yao Hu, Hatim O. Sharif, Navid Tahvildari

Civil & Environmental Engineering Faculty Publications

Coastal flooding has received significant attention in recent years due to future sea-level rise (SLR) projections and intensification of precipitation, which will exacerbate frequent flooding, coastal erosion, and eventually create permanently inundated low-elevation land. Coastal governments will be forced to implement measures to manage risk on the population and infrastructure and build protection systems to mitigate or adapt to the negative impacts of flooding. Research in this area is required to establish holistic frameworks for timely and accurate flooding forecast and design of protection systems.

Dynamic Modeling Of Inland Flooding And Storm Surge On Coastal Cities Under Climate Change Scenarios: Transportation Infrastructure Impacts In Norfolk, Virginia Usa As A Case Study, Yawen Shen, Navid Tahvildari, Mohamed M. Morsy, Chris Huxley, T. Donna Chen, Jonathan Lee Goodall

Civil & Environmental Engineering Faculty Publications

Low-lying coastal cities across the world are vulnerable to the combined impact of rainfall and storm tide. However, existing approaches lack the ability to model the combined effect of these flood mechanisms, especially under climate change and sea level rise (SLR). Thus, to increase flood resilience of coastal cities, modeling techniques to improve the understanding and prediction of the combined effect of these flood hazards are critical. To address this need, this study presents a modeling system for assessing the combined flood impact on coastal cities under selected future climate scenarios that leverages ocean modeling with land surface modeling capable …

Rhodium-Catalyzed Decarbonylation Of Aroyl Chlorides, Wiktoria M. Koza

Dissertations

The development of efficient strategies for the synthesis of aryl–halogen bonds is highly desirable due to the prevalence of these moieties in pharmaceuticals, agrochemicals, and organic synthesis. Although there are numerous applications of aryl chlorides in chemistry, an efficient strategy for the preparation of these molecules is underdeveloped. Transition metal-catalyzed decarbonylation provides an efficient and selective approach for aryl–halogen bond formation. There has been significant progress in the development of new decarbonylation strategies, particularly involving aldehydes for the synthesis of new carbon–hydrogen (C–H) bonds or for cross-coupling reactions. However, transition metal-catalyzed decarbonylation methods for carbon–halogen (C–X) bond formation have been …

Peripherally Restricted Opioid Conjugates And Its Use As Pharmacological Probes And Potential Therapeutics, Md Tariqul Haque Tuhin

University of the Pacific Theses and Dissertations

Opioid-induced constipation (OIC) is one of the major adverse effects of opioid analgesics used by millions of patients each year. While progress has been made, there remains a significant unmet medical need in the treatment of OIC. Major gaps remain in our understanding of the role of the gastrointestinal tract and central nervous system (CNS) in precipitating OIC. For the last four decades, numerous investigations to study the sites of action of opioid analgesics have utilized peripherally acting mu-opioid receptor antagonists (PAMORAs), which have been incorrectly believed to have limited penetration across the blood-brain barrier (BBB). Several preclinical and clinical …

Harnessing The Power Of Interdisciplinary Research With Psychology-Informed Cyberbullying Detection Models, Deborah Hall, Yasin N. Silva, Brittany Wheeler, Lu Cheng, Katie Baumel

Computer Science: Faculty Publications and Other Works

Cyberbullying has become increasingly prevalent, particularly on social media. There has also been a steady rise in cyberbullying research across a range of disciplines. Much of the empirical work from computer science has focused on developing machine learning models for cyberbullying detection. Whereas machine learning cyberbullying detection models can be improved by drawing on psychological theories and perspectives, there is also tremendous potential for machine learning models to contribute to a better understanding of psychological aspects of cyberbullying. In this paper, we discuss how machine learning models can yield novel insights about the nature and defining characteristics of cyberbullying and …

The Lick Agn Monitoring Project 2016: Velocity-Resolved Hβ Lags In Luminous Seyfert Galaxies, Vivian U, Aaron J. Barth, H. Alexander Vogler, Hengxiao Guo, Tommaso Treu, Vardha N. Bennert, Gabriela Canalizo, Alexei V. Filippenko, Elinor Gates, Frederick Hamann, Michael D. Joner, Matthew A. Malkan, Anna Pancoast, Peter R. Williams, Jong-Hak Woo, Bela Abolfathi, L. E. Abramson, Stephen F. Armen, Hyun-Jin Bae, Thomas Bohn, Benjamin D. Boizelle, Azalee Bostroem, Andrew Brandel, Thomas G. Brink, Sanyum Channa, M. C. Cooper, Maren Cosens, Edward Donohue, Sean P. Fillingham, Diego González-Buitrago, Goni Halevi, Andrew Halle, Carol E. Hood, Keith Horne, J. Chuck Horst, Maxime De Kouchkovsky, Benjamin Kuhn, Sahana Kumar, Douglas C. Leonard, Donald Loveland, Christina Manzano-King, Ian Mchardy, Raúl Michel, Melanie Kae B. Olaes, Daeseong Park, Songyoun Park, Liuyi Pei, Timothy W. Ross, Jordan N. Runco, Jenna Samuel, Javier Sánchez, Bryan Scott, Remington O. Sexton, Jaejin Shin, Isaac Shivvers, Chance L. Spencer, Benjamin E. Stahl, Samantha Stegman, Isak Stomberg, Stefano Valenti, L. Villafaña, Jonelle L. Walsh, Heechan Yuk, Weikang Zheng

Physics

We carried out spectroscopic monitoring of 21 low-redshift Seyfert 1 galaxies using the Kast double spectrograph on the 3 m Shane telescope at Lick Observatory from 2016 April to 2017 May. Targeting active galactic nuclei (AGNs) with luminosities of λLλ(5100 Å) ≈ 1044 erg s−1 and predicted Hβ lags of ∼20–30 days or black hole masses of 107–108.5 M⊙, our campaign probes luminosity-dependent trends in broad-line region (BLR) structure and dynamics as well as to improve calibrations for single-epoch estimates of quasar black hole masses. Here we present the first results from the campaign, including …

Bias Mitigation For Toxicity Detection Via Sequential Decisions, Lu Cheng, Ahmadreza Mosallanezhad, Yasin N. Silva, Deborah Hall, Huan Liu

Computer Science: Faculty Publications and Other Works

Increased social media use has contributed to the greater prevalence of abusive, rude, and offensive textual comments. Machine learning models have been developed to detect toxic comments online, yet these models tend to show biases against users with marginalized or minority identities (e.g., females and African Americans). Established research in debiasing toxicity classifiers often (1) takes a static or batch approach, assuming that all information is available and then making a one-time decision; and (2) uses a generic strategy to mitigate different biases (e.g., gender and racial biases) that assumes the biases are independent of one another. However, in real …

Dbsnap 2: New Features To Construct Database Queries By Snapping Blocks, Yasin N. Silva, Alexis Loza, Humberto Razente

Computer Science: Faculty Publications and Other Works

Block-based environments for creating computer programs have become very useful learning tools in computer science as they enable focusing on the logic of a program rather than on its syntactical details. While most block-based environments support conventional (imperative) instructions, a few tools have been proposed to create database queries. One of these tools is DBSnap, a highly dynamic and open-source tool to create database query trees by dragging and connecting visual blocks representing datasets and database operators. In this paper, we introduce DBSnap 2, an extension of DBSnap that provides a set of improvements to facilitate the creation of simple …

Biocatalytic Intramolecular C−H Aminations Via Engineered Heme Proteins: Full Reaction Pathways And Axial Ligand Effects, Yang Wei, Melissa Conklin, Yong Zhang

Chemistry: Faculty Publications and Other Works

Engineered heme protein biocatalysts provide an efficient and sustainable approach to develop amine-containing compounds through C−H amination. A quantum chemical study to reveal the complete heme catalyzed intramolecular C−H amination pathway and protein axial ligand effect was reported, using reactions of an experimentally used arylsulfonylazide with hemes containing L=none, SH−, MeO−, and MeOH to simulate no axial ligand, negatively charged Cys and Ser ligands, and a neutral ligand for comparison. Nitrene formation was found as the overall rate-determining step (RDS) and the catalyst with Ser ligand has the best reactivity, consistent with experimental reports. Both RDS and non-RDS (nitrene transfer) …

Healing Earth In A Time Of Crisis: Curriculum For Integral Ecology, Caleb Steindam

Dissertations

This intrinsic multiple case study examined secondary- and university-level educators’ experiences teaching with Healing Earth, a curriculum developed by the International Jesuit Ecology Project at Loyola University Chicago, which merges scientific, social, spiritual, and ethical analyses of pressing ecological issues. Based on the conceptual framework of integral ecology, Healing Earth is a response to Pope Francis’s (2015a) call for “a new way of thinking about human beings, life, society and our relationship with nature” (§215).

This study primarily consisted of in-depth interviews with educators who have used Healing Earth in a variety of secondary and post-secondary Catholic educational contexts. A …

Chicago Community Area Data, 1930-2010, Nate Falling, Jacob Nelson, Miguel Torres, Richard T. Melstrom

School of Environmental Sustainability: Faculty Publications and Other Works

We are releasing a set of community area
statistics collected from fact book and census
profile data series. These statistics are in the file
Chicago_Community_Area_Data_1930-2010,
which is available from the attached dataset. The statistics do not reflect all of the
data contained in the historical sources.
Additional digitized data can be found at
https://robparal.com/chicago-data/.

Improvement Of The Fine Tuning Algorithm, Joseph Mietkiewicz, Anders Madsen

Articles

Khalil El Hindi has developed a fine-tuning algorithm to
improve the classification accuracy of the Naive Bayes. His algorithm optimizes the conditional probability tables of the Naive Bayes after the
training phase. The values of the probabilities of a variable are modified if it causes misclassification of a training instance. The algorithm out-performs in many cases the Naive Bayes. We analyze the performance
of the algorithm, discussed its issues, and compare it to a modified algorithm. The new algorithm simplifies the formula used in the fine-tuning algorithm and uses a more efficient scoring metric, the Brier score, to
fine-tune the …

Smart Application For Every Car (Saec). (Ar Mobile Application), Murad Al-Rajab, Samia Loucif, Ossama Kousi, Mohamad Bassem Irani

All Works

Technology is continuously evolving at an exponential rate. Fast technological advances are being made, especially in the field of smart phones, that facilitate the conduct of our daily activities in many areas such as driving. The ever-increasing number of vehicles on roads increases the likelihood of traffic accidents, resulting in higher number of deaths and serious injuries to drivers, passengers, and pedestrians. Among the main causes of road accidents are over speeding, unsafe lane jumping, and failure to keep a safe distance between vehicles, to name a few. In an attempt to contribute to the improvement of road traffic safety, …

Secure Storage Model For Digital Forensic Readiness, Avinash Singh, Richard Adeyemi Ikuesan, Hein Venter

All Works

Securing digital evidence is a key factor that contributes to evidence admissibility during digital forensic investigations, particularly in establishing the chain of custody of digital evidence. However, not enough is done to ensure that the environment and access to the evidence are secure. Attackers can go to extreme lengths to cover up their tracks, which is a serious concern to digital forensics – particularly digital forensic readiness. If an attacker gains access to the location where evidence is stored, they could easily alter the evidence (if not remove it altogether). Even though integrity checks can be performed to ensure that …

Crowdsensing Application On Coalition Game Using Gps And Iot Parking In Smart Cities, Hasan Abu Hilal, Narmeen Abu Hilal, Ala’ Abu Hilal, Tariq Abu Hilal

All Works

This paper provides an overview of crowdsensing and some of its applications. Crowdsensing is a part of the collecting data situations also; it’s built on a data system on multiple customer interactions. Moreover, writing the general information of the smart cities can be used to boost to received number frequency to send messages. This work mentioned the Crowdsensing layers that describe Mobile crowdsensing. The article focuses on crowdsensing layers, developed an application in Coalition Game using crowdsensing in terms of GPS. In addition, this paper discussed the Mobile crowdsensing system and how important the cloud is in serving the wireless …

On The Use Of Allen’S Interval Algebra In The Coordination Of Resource Consumption By Transactional Business Processes, Zakaria Maamar, Fadwa Yahya, Lassaad Ben Ammar

All Works

This paper presents an approach to coordinate the consumption of resources by transactional business processes. Resources are associated with consumption properties known as unlimited, limited, limited-but-extensible, shareable, and non-shareable restricting their availabilities at consumption-time. And, processes are associated with transactional properties known as pivot, retriable, and compensatable restricting their execution outcomes in term of either success or failure. To consider the intrinsic characteristics of both consumption properties and transactional properties when coordinating resource consumption by processes, the approach adopts Allen’s interval algebra through different time-interval relations like before, overlaps, and during to set up the coordination, which should lead to …