Physical Sciences and Mathematics Commons^™

Development Of A Modified Screen Printed Electrode For The Determination Of Heavy Metals In Water Before And After Remediation With Food Grade Pectin And Citrofortunella Microcarpa Rinds, Shirley Palisoc, Natividad Michelle, Marissa Noel

Angelo King Institute for Economic and Business Studies (AKI)

The rapid increase in population, urbanization, and industrialization, along with inadequate water quality monitoring and wastewater management, contribute heavily to the pollution of water resources. Among the water contaminants of major concern, heavy metals are particularly considered as the most worrisome. Heavy metals tend to accumulate in the tissues of aquatic organisms (Ahmed et al., 2019; Rajeshkumar & Li, 2018; Tabrez et al., 2021) and thus increase in concentration upon moving higher up the food chain. This indicates that once humans ingest these organisms, they have a high risk of experiencing health problems as heavy metals are absorbed into their …

Front Matter

The Synapse: Intercollegiate science magazine

No abstract provided.

Back Matter

The Synapse: Intercollegiate science magazine

No abstract provided.

The Synapse: Issue 2022

The Synapse: Intercollegiate science magazine

No abstract provided.

Acing Coping Fromw Ace: How Individuals And Communities Can Alleviate The Effects Of Childhood Trauma, Kathy Nguyen

The Synapse: Intercollegiate science magazine

No abstract provided.

Two Birds With One Stone: Recycling Carbon Dioxide To Produce Plastic, Sydney Rosensaft

The Synapse: Intercollegiate science magazine

No abstract provided.

The Long Haul Virus, Sadia Haidari

The Synapse: Intercollegiate science magazine

No abstract provided.

Halluiclluistnrataed Tbyi Eovelnyn L Aozenr Medical Revolution: Using Psychedelics As A New Treatment For Disorders, Asha Shukla

The Synapse: Intercollegiate science magazine

No abstract provided.

Featured Artist, Claire Wong

The Synapse: Intercollegiate science magazine

No abstract provided.

Harnessing Cosmic Power To Fuel Earth: Nuclear Fusion’S Rise As The Promising Renewable Energy, Tara Sefchick

The Synapse: Intercollegiate science magazine

No abstract provided.

The Hidden Powers Of Plants: The Fascinating Ways Plants Express Themselves, Saurav Chakraborty

The Synapse: Intercollegiate science magazine

No abstract provided.

Diseases Hidden In Ice: Ancient Bacteria In Permafrost Could Spread Ancient Diseases, Jessica John

The Synapse: Intercollegiate science magazine

No abstract provided.

How Social Media Controls Your Gut: The Internet, Health Misinformation, And The Human Gut Microbe, Maggie Willis

The Synapse: Intercollegiate science magazine

No abstract provided.

The Mystery Of Superagers: Are Superagers Simply An Example Of Winning The Genetic Lottery, Or Something, Barbara Asantewaa-Boadi

The Synapse: Intercollegiate science magazine

No abstract provided.

Getting Started Analyzing Data In Spss, Kristi Thompson

Western Libraries Presentations

SPSS is a popular package for analyzing data. This session will discuss how to get started on a simple quantitative analysis project using SPSS. Topics covered will include getting summary statistics, creating and modifying variables, creating graphs, running simple analyses, and interpreting SPSS output.

Synthesis And Characterization Of Unique Pyridazines, William Hobbs

Senior Honors Theses

The field of semiconductive organic chemistry is vast and expanding as numerous applications are being discovered for semiconductors. The research reported in this thesis focuses on the synthesis and characterization of three pyridazines. Pyridazines are organic heterocyclic aromatic semiconductors containing nitrogen and are planar in structure. The three pyridazine compounds were successfully isolated as evidenced by a high percent yield and then characterized by melting point and infrared spectroscopy. The research goal was achieved as a small library of pyridazines was compiled to be further analyzed concerning their potential within various applications in the electronic and industrial world.

Which Neural Network Makes More Explainable Decisions? An Approach Towards Measuring Explainability, Mengdi Zhang, Jun Sun, Jingyi Wang

Research Collection School Of Computing and Information Systems

Neural networks are getting increasingly popular thanks to their exceptional performance in solving many real-world problems. At the same time, they are shown to be vulnerable to attacks, difficult to debug and subject to fairness issues. To improve people’s trust in the technology, it is often necessary to provide some human-understandable explanation of neural networks’ decisions, e.g., why is that my loan application is rejected whereas hers is approved? That is, the stakeholder would be interested to minimize the chances of not being able to explain the decision consistently and would like to know how often and how easy it …

Kinetic Monte Carlo Simulations Of Quantum Dot Self-Assembly, Matthew Abramson, Hunter J. Coleman, Paul J. Simmonds, Tim P. Schulze, Christian Ratsch

Physics Faculty Publications and Presentations

In the Stranski–Krastanov growth mode for heteroepitaxial systems, layer-by-layer growth is followed by the formation and growth of three-dimensional (3D) islands. In this paper, we use a kinetic Monte Carlo method to simulate this growth mode behavior. We present a detailed and systematic investigation into the effects of key model parameters including strain, growth temperature, and deposition rate on this phenomenon. We show that increasing the strain lowers the apparent critical thickness that is defined by the onset of 3D island formation. Similarly, increasing the growth temperature lowers the apparent critical thickness, until intermixing, and the resulting relevance of entropic …

Zeroth-Order Negative Curvature Finding: Escaping Saddle Points Without Gradients, Hualin Zhang, Huan Xiong, Bin Gu

Machine Learning Faculty Publications

We consider escaping saddle points of nonconvex problems where only the function evaluations can be accessed. Although a variety of works have been proposed, the majority of them require either second or first-order information, and only a few of them have exploited zeroth-order methods, particularly the technique of negative curvature finding with zeroth-order methods which has been proven to be the most efficient method for escaping saddle points. To fill this gap, in this paper, we propose two zeroth-order negative curvature finding frameworks that can replace Hessian-vector product computations without increasing the iteration complexity. We apply the proposed frameworks to …

Validation Of A Method For Pantoprazole And Its Sulfone Metabolite In Goat Plasma Using High Performance Liquid Chromatography, Sherry Cox, Lainey Harvill, Sarah Bullock, Joseph Smith, Joan Bergman

Faculty Publications and Other Works -- Large Animal Clinical Sciences

No abstract provided.

Filling Critical Gaps In The Space-Time Record Of High Lava Plains And Co-Columbia River Basalt Group Rhyolite Volcanism, Vanessa Marie Swenton, Martin J. Streck, Daniel P. Miggins, William C. Mcintosh

Geology Faculty Publications and Presentations

Miocene rhyolitic volcanism of eastern Oregon, USA, can be divided into two main episodes. Mantle plume upwelling is thought to have generated Columbia River Basalt Group (CRBG) lavas and coeval >16.5−15 Ma silicic volcanism trending north−south from northeast Oregon to northern Nevada. Rhyolite volcanism of the 12−0 Ma High Lava Plains province has been ascribed to either buoyancy-driven westward plume spreading or to slab rollback and mantle convection spanning from southeast Oregon to Newberry Volcano to the west. The apparent ca. 15−12 Ma eruptive hiatus suggests that rhyolites of these provinces were a product of separate processes, yet this gap …

Zeroth-Order Hard-Thresholding: Gradient Error Vs. Expansivity, William De Vazelhes, Hualin Zhang, Huimin Wu, Xiao Tong Yuan, Bin Gu

Machine Learning Faculty Publications

ℓ0 constrained optimization is prevalent in machine learning, particularly for high-dimensional problems, because it is a fundamental approach to achieve sparse learning. Hard-thresholding gradient descent is a dominant technique to solve this problem. However, first-order gradients of the objective function may be either unavailable or expensive to calculate in a lot of real-world problems, where zeroth-order (ZO) gradients could be a good surrogate. Unfortunately, whether ZO gradients can work with the hard-thresholding operator is still an unsolved problem. To solve this puzzle, in this paper, we focus on the ℓ0 constrained black-box stochastic optimization problems, and propose a new stochastic …

Iowa Waste Reduction Center Newsletter, November 2022, University Of Northern Iowa. Iowa Waste Reduction Center.

Iowa Waste Reduction Center Newsletter

In this Issue:

--- Thank You
--- Iowa Strategic Goals Workshop
--- Your guide to Small Business Assistance: Air Permit Applications & Emissions Reporting
--- Welcome Paige and Nikayla!
--- Free Energy Assessments
--- Industry News

Lstm-Sdm: An Integrated Framework Of Lstm Implementation For Sequential Data Modeling[Formula Presented], Hum Nath Bhandari, Binod Rimal, Nawa Raj Pokhrel, Ramchandra Rimal, Keshab R. Dahal

Arts & Sciences Faculty Publications

LSTM-SDM is a python-based integrated computational framework built on the top of Tensorflow/Keras and written in the Jupyter notebook. It provides several object-oriented functionalities for implementing single layer and multilayer LSTM models for sequential data modeling and time series forecasting. Multiple subroutines are blended to create a conducive user-friendly environment that facilitates data exploration and visualization, normalization and input preparation, hyperparameter tuning, performance evaluations, visualization of results, and statistical analysis. We utilized the LSTM-SDM framework in predicting the stock market index and observed impressive results. The framework can be generalized to solve several other real-world time series problems.

Discovery Of Two Inhibitors Of The Type Iv Pilus Assembly Atpase Pilb As Potential Antivirulence Compounds, Keane J. Dye, Nancy J. Vogelaar, Megan O'Hara, Pablo Sobrado, Webster Santos, Paul R. Carlier, Zhaomin Yang

Chemistry Faculty Research & Creative Works

With the pressing antibiotic resistance pandemic, Anti virulence has been increasingly explored as an alternative strategy against bacterial infections. The bacterial type IV pilus (T4P) is a well-documented virulence factor and an attractive target for small molecules for Anti virulence purposes. The PilB ATPase is essential for T4P biogenesis because it catalyzes the assembly of monomeric pilins into the polymeric pilus filament. Here, we describe the identification of two PilB inhibitors by a high-throughput screen (HTS) in vitro and their validation as effective inhibitors of T4P assembly in vivo. We used Chloracidobacterium thermophilum PilB as a model enzyme to optimize …

Snapshots Of Coastal Ecology During Glacial And Deglacial Intervals: A Multiproxy Assessment Of Northern Gulf Of Mexico Sediment Cores, Kendall Emilie Brome

LSU Master's Theses

Terrestrial ecosystems along exposed continental shelves during times of relatively low sea level and glaciation are rarely preserved due to the mechanically erosive nature of marine transgression and regression. In this study, I investigate the geochemical and palynological characteristics of two well-preserved sites in the northern Gulf of Mexico (NGOM) to determine the ecologic settings and subsequent mechanisms of preservation in this region. Both sites contain preserved terrigenous sediments of previously exposed coastal margins; the first is located at the Alabama Underwater Forest (~13 km south of Gulf Shores, AL, at ~15 mbsl), and optically stimulated luminescence dates to 72–56 …

Transcriptional Regulatory Network Topology With Applications To Bio-Inspired Networking: A Survey, Satyaki Roy, Preetam Ghosh, Nirnay Ghosh, Sajal K. Das

Computer Science Faculty Research & Creative Works

The advent of the edge computing network paradigm places the computational and storage resources away from the data centers and closer to the edge of the network largely comprising the heterogeneous IoT devices collecting huge volumes of data. This paradigm has led to considerable improvement in network latency and bandwidth usage over the traditional cloud-centric paradigm. However, the next generation networks continue to be stymied by their inability to achieve adaptive, energy-efficient, timely data transfer in a dynamic and failure-prone environment - the very optimization challenges that are dealt with by biological networks as a consequence of millions of years …

Dtc: A Dynamic Transaction Chopping Technique For Geo-Replicated Storage Services, Ning Huang, Lihui Wu, Weigang Wu, Sajal K. Das

Computer Science Faculty Research & Creative Works

Replicating data across geo-distributed datacenters is usually necessary for large scale cloud services to achieve high locality, durability and availability. One of the major challenges in such geo-replicated data services lies in consistency maintenance, which usually suffers from long latency due to costly coordination across datacenters. Among others, transaction chopping is an effective and efficient approach to address this challenge. However, existing chopping is conducted statically during programming, which is stubborn and complex for developers. In this article, we propose Dynamic Transaction Chopping (DTC), a novel technique that does transaction chopping and determines piecewise execution in a dynamic and automatic …

Stable Matching Based Resource Allocation For Service Provider's Revenue Maximization In 5g Networks, Ajay Pratap, Sajal K. Das

Computer Science Faculty Research & Creative Works

5G technology is foreseen to have a heterogeneous architecture with the various computational capability, and radio-enabled service providers (SPs) and service requesters (SRs), working altogether in a cellular model. However, the coexistence of heterogeneous network model spawns several research challenges such as diverse SRs with uneven service deadlines, interference management, and revenue maximization of non-uniform computational capacities enabled SPs. Thus, we propose a coexistence of heterogeneous SPs and SRs enabled cellular 5G network and formulate the SPs' revenue maximization via resource allocation, considering different kinds of interference, data rate, and latency altogether as an optimization problem and further propose a …

Deep Near-Infrared Survey Towards The W40 And Serpens South Region In The Aquila Rift: A Comprehensive Catalogue Of Young Stellar Objects, Min Long

Computer Science Faculty Publications and Presentations

Active star-forming regions are excellent laboratories for studying the origins and evolution of young stellar object (YSO) clustering. The W40–Serpens South region is such a region, and we compile a large near- and mid-infrared catalogue of point sources in it, based on deep near-infrared observations of Canada-France-Hawaii Telescope (CFHT) in combination with Two Micron All Sky Survey (2MASS), UKIRT Infrared Deep Sky Survey (UKIDSS), and Spitzer catalogues. From this catalogue, we identify 832 YSOs, and classify 15, 135, 647, and 35 of them to be deeply embedded sources, Class I YSOs, Class II YSOs, and transition disc sources, respectively. In …