Computer Sciences Commons^™

Genetic Association In Entylia Carinata Using Random Forest Classification, Caden J. Harper

Research & Creative Achievement Day

The goal of this research was to identify locations in the genome of the Entylia carinata, known as the treehopper, that are associated with anomalous behavior exhibited by the species. Treehoppers are phytophagous insects and are shown to feed, reproduce, and rear their young on specific aster species. Observation has shown that the insects will disregard potential mates in close proximity in favor of those that originate from the same plant species as themselves. This behavior suggests genetic separation in the species based on plant nativity and warrants genetic analysis. Machine learning offers an effective genetic association technique due to …

Rescape: Transforming Coral-Reefscape Images For Quantitative Analysis, Zachary Ferris, Eraldo Ribeiro, Tomofumi Nagata, Robert Van Woesik

Ocean Engineering and Marine Sciences Faculty Publications

Ever since the first image of a coral reef was captured in 1885, people worldwide have been accumulating images of coral reefscapes that document the historic conditions of reefs. However, these innumerable reefscape images suffer from perspective distortion, which reduces the apparent size of distant taxa, rendering the images unusable for quantitative analysis of reef conditions. Here we solve this century-long distortion problem by developing a novel computer-vision algorithm, ReScape, which removes the perspective distortion from reefscape images by transforming them into top-down views, making them usable for quantitative analysis of reef conditions. In doing so, we demonstrate the …

Hgs-3 The Influence Of A Tandem Cycling Program In The Community On Physical And Functional Health, Therapeutic Bonds, And Quality Of Life For Individuals And Care Partners Coping With Parkinson’S Disease, Leila Djerdjour, Jennifer L. Trilk

SC Upstate Research Symposium

Purpose Statement: Several studies have shown that aerobic exercise can have a positive impact on alleviating symptoms experienced by individuals with Parkinson's disease (PD). Despite this evidence, the potential benefits of exercise for both PD patients and their care partners (PD dyad) remain unexplored. This research project investigates the effectiveness, therapeutic collaborations, and physical outcomes of a virtual reality (VR) tandem cycling program specifically designed for PD dyads.

Methods: Following approval from the Prisma Health Institutional Review Board, individuals with PD were identified and screened by clinical neurologists. The pre-testing measures for PD dyads (N=9) included emotional and cognitive status …

Deep Learning Can Be Used To Classify And Segment Plant Cell Types In Xylem Tissue, Reem Al Dabagh, Benjamin Shin, Sean Wu, Fabien Scalzo, Helen Holmlund, Jessica Lee, Chris Ghim, Samuel Fitzgerald, Marinna Grijalva

Seaver College Research And Scholarly Achievement Symposium

Studies of plant anatomical traits are essential for understanding plant physiological adaptations to stressful environments. For example, shrubs in the chaparral ecosystem of southern California have adapted various xylem anatomical traits that help them survive drought and freezing. Previous studies have shown that xylem conduits with a narrow diameter allows certain chaparral shrub species to survive temperatures as low as -12 C. Other studies have shown that increased cell wall thickness of fibers surrounding xylem vessels improves resistance to water stress-induced embolism formation. Historically, these studies on xylem anatomical traits have relied on hand measurements of cells in light micrographs, …

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 …

Online Class-Incremental Learning For Real-World Food Image Classification, Siddeshwar Raghavan, Jiangpeng He, Fengqing Zhu

Graduate Industrial Research Symposium

Food image classification is essential for monitoring health and tracking dietary in image-based dietary assessment methods. However, conventional systems often rely on static datasets with fixed classes and uniform distribution. In contrast, real-world food consumption patterns, shaped by cultural, economic, and personal influences, involve dynamic and evolving data. Thus, it requires the classification system to cope with continuously evolving data. Online Class Incremental Learning (OCIL) addresses the challenge of learning continuously from a single-pass data stream while adapting to the new knowledge and reducing catastrophic forgetting. Experience Replay (ER) based OCIL methods store a small portion of previous data and …

Investigations Of The Eutectic Formation And Skin Rejuvenation By Hyaluronan - Kojic Acid Dipalmitate System, Syed Waqar Hussain Shah, Sumbal Imran, Iram Bibi, Kashif Ali, Nadia Bashir

Karbala International Journal of Modern Science

Eutectic phenomenon has been investigated in binary system based on biopolymer hyaluronan (HN) and kojic acid dipalmitate (KAD). Solid-liquid phase diagram showed a significant dependence of melting points on weight fraction of KAD up to KAD < 0.5. A negligible regain to melting temperature of pure KAD occurred later. Simulations of molecular mechanics using a four-unit segment of HN and KAD revealed the interaction between carbonyl of KAD with 4-OH on N-acetylglucosamine unit of oligomer. Infrared vibrational spectroscopy also endorsed the existence of a weakly interacting system. Such behavior was expected due to steric hinderance and rigidity of biopolymer. The thermal decomposition temperature of HN (i.e., 215 °C) was increased to 322 °C in HK50 having HN and KAD in 1:50 w/w. Bioelectric impedance analysis revealed that these green materials could promote skin health in humans.

Synthesis And Characterization Of Renewable Heterogeneous Catalyst Zno Supported Biogenic Silica From Pineapple Leaves Ash For Sustainable Biodiesel Conversion, Nadila Pratiwi, Suriati Eka Putri, Yulia Shinta, Arya Ibnu Batara, Diana Eka Pratiwi, Abd Rahman, Nur Ahmad, Heryanto Heryanto

Karbala International Journal of Modern Science

This study reports on the first case of the low-cost and environmentally friendly ZnO/SiO2 heterogeneous catalyst from pineapple leaves ash (PLA). Catalyst shows excellent performance in catalyzing the transesterification of waste cooking oil (WCO) with methanol for biodiesel conversion. This study focuses on assessing the influence of Zn content on physicochemical characteristics, using XRD, FTIR, SEM, and N2 adsorption-desorption methods. In addition, three different Zn content levels (20, 25, and 30 %wt) were applied. The results showed that all ZnO/SiO2 samples exhibited characteristics suitable for use as catalyst with an average crystallite size of 31.83-34.15 nm, and a surface area …

Butterworth Filter To Reduce Reactivity Fluctuations, Daniel Suescún-Díaz, Geraldyne Ule-Duque, Luis E. Cardoso-Páez

Karbala International Journal of Modern Science

In this study, we introduce the calculation of reactivity in nuclear reactors. The proposed method uses the Euler-Maclaurin series to approximate the integral in the inverse equation of point kinetics. The approximation is done with the first three terms, the first term represents the approximation of a zero-order sum, the second term the trapezoidal rule and the third term the first Bernoulli number. These three terms improve the approximation, along with an estimate of the neutron density using the prompt jump approximation. To reduce neutron density fluctuations, a second-order Butterworth filter for the reactivity calculation was implemented, which offers the …

Machine Learning Model And Molecular Docking For Screening Medicinal Plants As Hiv-1 Reverse Transcriptase Inhibitors, Muthia Rahayu Iresha, Firdayani Firdayani, Agam Wira Sani, Nihayatul Karimah, Shelvi Listiana, Irfansyah Yudhi Tanasa, Arief Sartono, Ayu Masyita

Karbala International Journal of Modern Science

The human immunodeficiency virus type 1 reverse transcriptase (HIV-1 RT) plays a significant role in viral replication and is one of the targets for anti-HIV. However, a mutation in viral strains rapidly developed the resistance of the com-pounds to the protein, reducing the effectiveness of the inhibitors. This work seeks to utilize machine learning-based quantitative structure-activity relationship (QSAR) analysis in combination with molecular docking simulations to forecast the presence of active compounds derived from medicinal plants. Specifically, the objective is to identify com-pounds that have the potential to operate as inhibitors of HIV-1 reverse transcriptase (RT), encompassing both wild-type and …

A Reliable Diabetic Retinopathy Grading Via Transfer Learning And Ensemble Learning With Quadratic Weighted Kappa Metric, Sai Venkatesh Chilukoti, Liqun Shan, Vijay Srinivas Tida, Anthony S. Maida, Xiali Hei

Computer Science Faculty Publications

The most common eye infection in people with diabetes is diabetic retinopathy (DR). It might cause blurred vision or even total blindness. Therefore, it is essential to promote early detection to prevent or alleviate the impact of DR. However, due to the possibility that symptoms may not be noticeable in the early stages of DR, it is difficult for doctors to identify them. Therefore, numerous predictive models based on machine learning (ML) and deep learning (DL) have been developed to determine all stages of DR. However, existing DR classification models cannot classify every DR stage or use a computationally heavy …

Multi-Agent System For Portfolio Profit Optimization For Future Stock Trading, Usha Devi, Mohan R

Karbala International Journal of Modern Science

Stock trading highly contributes to the economic growth of the country. The stock trading objective is to earn profits with buy/sell/hold decisions on the set of stocks in the portfolio. The portfolio optimization problem is finding the decision sequence that leads to higher profit and lower risk. Portfolio optimization is challenging due to complex price history patterns and an uncertain environment. Incorrect decisions in stock trading lead to massive losses. The proposed Multi-Agent System for Portfolio Profit Optimization (MASPPO) aims to optimize trading profit and reduce risk with accurate predictions. The proposed model integrates the Fuzzy c-means with the Deep …

Foodmask: Real-Time Food Instance Counting, Segmentation And Recognition, Huu-Thanh Nguyen, Yu Cao, Chong-Wah Ngo, Wing-Kwong Chan

Research Collection School Of Computing and Information Systems

Food computing has long been studied and deployed to several applications. Understanding a food image at the instance level, including recognition, counting and segmentation, is essential to quantifying nutrition and calorie consumption. Nevertheless, existing techniques are limited to either category-specific instance detection, which does not reflect precisely the instance size at the pixel level, or category-agnostic instance segmentation, which is insufficient for dish recognition. This paper presents a compact and fast multi-task network, namely FoodMask, for clustering-based food instance counting, segmentation and recognition. The network learns a semantic space simultaneously encoding food category distribution and instance height at pixel basis. …

A Computational Profile Of Invasive Lionfish In Belize: A New Insight On A Destructive Species, Joshua E. Balan

The Journal of Purdue Undergraduate Research

Since their discovery in the region in 2009, invasive Indonesian-native lionfish have been taking over the Belize Barrier Reef. As a result, populations of local species have dwindled as they are either eaten or outcompeted by the invaders. This has led to devastating losses ecologically and economically; massive industries in the local nations, such as fisheries and tourism, have suffered greatly. Attempting to combat this, local organizations, from nonprofits to ecotourism companies, have been manually spear-hunting them on scuba dives to cull the population. One such company, Reef Conservation Institute (ReefCI), operating out of Tom Owens Caye outside of Placencia, …

A New Paradigm Of Life Science Research Driven By Artificial Intelligence, Xin Li, Hanchao Yu

Bulletin of Chinese Academy of Sciences (Chinese Version)

The rapid development of biotechnology and information technology has brought life sciences into a new era of data explosion. The traditional life science research paradigm struggles to reveal the fundamental rules of complex biological systems from rapidly growing biological big data. As artificial intelligence continues to achieve disruptive breakthroughs in life science, a new paradigm driven by AI is emerging. This study delves into typical examples of life science research driven by AI, proposes the concept and key elements of the new life science research paradigm, elaborates on the cutting-edge of life science research under this new paradigm, and discusses …

Genome-Wide Profiling Of Novel Conserved Zea Mays Micrornas Along With Their Key Biological, Molecular And Cellular Targets And Validation Using An Rt-Pcr Platform, Abdul Baqi, Sami Ullah, Muhammad Ayub, Muhammad Zafar Saleem, Ghulam Mustafa Khan, Asad Ullah

Karbala International Journal of Modern Science

MicroRNAs (miRNAs), which are typically non-coding RNAs that start off as endogenous molecules and regulate post-transcriptional levels of gene expression by mRNA degradation or translational repression. They are 18–26 nucleotides long, evolutionarily conserved and essential for predicting novel miRNAs in a variety of plants. Maize (Zea mays) is a significant food and forage crop in the globe today. In the present study, many maize miRNAs have been found to be associated with both plant development and responses to stress. In this study, 66 unique conserved maize miRNAs from 65 different miRNA families were predicted using several genomics-based methods …

The Role Of Cu (0-0.03) And Zn (0.02) Substitution On The Structural, Optical And Magnetic Properties Of Mgo Nanoparticles, S. Naseem Shah, Atif Dawar, Yasmeen Bibi, Abid Ali, M. Asif Siddiqui

Karbala International Journal of Modern Science

The co-precipitation method was employed to prepared Cu (0-0.03) and Zn (0.02) dual doped MgO nanoparticles. The secondary phases of CuO and Cu₂O were observed along with the cubical phase of MgO. The doping induced effect was noticed for the crystallite size variations (14.39-19.89 nm). The morphological transformation from spherical to rice-like shape were observed. The estimated values of optical bandgap (4.66-4.45 eV) were well correlated with the crystallite size and dopant concentrations. The ferromagnetic ordering was observed at room temperature and the enchantment in the coercivity (142.27 Oe) with Zn (0.02) doping was noticed. Such type of …

Machine Learning As A Tool For Early Detection: A Focus On Late-Stage Colorectal Cancer Across Socioeconomic Spectrums, Hadiza Galadima, Rexford Anson-Dwamena, Ashley Johnson, Ghalib Bello, Georges Adunlin, James Blando

Community & Environmental Health Faculty Publications

Purpose: To assess the efficacy of various machine learning (ML) algorithms in predicting late-stage colorectal cancer (CRC) diagnoses against the backdrop of socio-economic and regional healthcare disparities. Methods: An innovative theoretical framework was developed to integrate individual- and census tract-level social determinants of health (SDOH) with sociodemographic factors. A comparative analysis of the ML models was conducted using key performance metrics such as AUC-ROC to evaluate their predictive accuracy. Spatio-temporal analysis was used to identify disparities in late-stage CRC diagnosis probabilities. Results: Gradient boosting emerged as the superior model, with the top predictors for late-stage CRC diagnosis being anatomic site, …

Model-Based Deep Autoencoders For Clustering Single-Cell Rna Sequencing Data With Side Information, Xiang Lin

Dissertations

Clustering analysis has been conducted extensively in single-cell RNA sequencing (scRNA-seq) studies. scRNA-seq can profile tens of thousands of genes' activities within a single cell. Thousands or tens of thousands of cells can be captured simultaneously in a typical scRNA-seq experiment. Biologists would like to cluster these cells for exploring and elucidating cell types or subtypes. Numerous methods have been designed for clustering scRNA-seq data. Yet, single-cell technologies develop so fast in the past few years that those existing methods do not catch up with these rapid changes and fail to fully fulfil their potential. For instance, besides profiling transcription …

Reducing Food Scarcity: The Benefits Of Urban Farming, S.A. Claudell, Emilio Mejia

Journal of Nonprofit Innovation

Urban farming can enhance the lives of communities and help reduce food scarcity. This paper presents a conceptual prototype of an efficient urban farming community that can be scaled for a single apartment building or an entire community across all global geoeconomics regions, including densely populated cities and rural, developing towns and communities. When deployed in coordination with smart crop choices, local farm support, and efficient transportation then the result isn’t just sustainability, but also increasing fresh produce accessibility, optimizing nutritional value, eliminating the use of ‘forever chemicals’, reducing transportation costs, and fostering global environmental benefits.

Imagine Doris, who is …

Ungrading: Reflections Through A Feminist Pedagogical Lens, Erin M. Eggleston, Shelby Kimmel

Feminist Pedagogy

Ungrading is a pedagogical approach in which no grades are given on any assignments. Instead, students are provided with many opportunities to submit work and gain feedback. The goal is to shift student focus from achieving a grade to growth as a learner and a person. As instructors, our ungrading approach utilized personalized learning plans, checkpoint reflections, and student-professor learning conferences to put agency in the hands of our students. We employed this method in upper-level biology and computer science courses and provide critical reflections here regarding our experiences and the connections between this approach and feminist STEM pedagogy tenets. …

Deep Learning Image Analysis To Isolate And Characterize Different Stages Of S-Phase In Human Cells, Kevin A. Boyd, Rudranil Mitra, John Santerre, Christopher L. Sansam

SMU Data Science Review

Abstract. This research used deep learning for image analysis by isolating and characterizing distinct DNA replication patterns in human cells. By leveraging high-resolution microscopy images of multiple cells stained with 5-Ethynyl-2′-deoxyuridine (EdU), a replication marker, this analysis utilized Convolutional Neural Networks (CNNs) to perform image segmentation and to provide robust and reliable classification results. First multiple cells in a field of focus were identified using a pretrained CNN called Cellpose. After identifying the location of each cell in the image a python script was created to crop out each cell into individual .tif files. After careful annotation, a CNN was …

A Review Of Threat Vectors To Dna Sequencing Pipelines, Tyler Rector

Cybersecurity Undergraduate Research Showcase

Bioinformatics is a steadily growing field that focuses on the intersection of biology with computer science. Tools and techniques developed within this field are quickly becoming fixtures in genomics, forensics, epidemiology, and bioengineering. The development and analysis of DNA sequencing and synthesis have enabled this significant rise in demand for bioinformatic tools. Notwithstanding, these bioinformatic tools have developed in a research context free of significant cybersecurity threats. With the significant growth of the field and the commercialization of genetic information, this is no longer the case. This paper examines the bioinformatic landscape through reviewing the biological and cybersecurity threats within …

Software Jimenae Allows Efficient Dynamic Simulations Of Boolean Networks, Centrality And System State Analysis, Martin Kaltdorf, Tim Breitenbach, Stefan Karl, Maximilian Fuchs, David Komla Kessie, Eric Psota, Martina Prelog, Edita Sarukhanyan, Regina Ebert, Franz Jakob, Gudrun Dandekar, Muhammad Naseem, Chunguang Liang, Thomas Dandekar

All Works

The signal modelling framework JimenaE simulates dynamically Boolean networks. In contrast to SQUAD, there is systematic and not just heuristic calculation of all system states. These specific features are not present in CellNetAnalyzer and BoolNet. JimenaE is an expert extension of Jimena, with new optimized code, network conversion into different formats, rapid convergence both for system state calculation as well as for all three network centralities. It allows higher accuracy in determining network states and allows to dissect networks and identification of network control type and amount for each protein with high accuracy. Biological examples demonstrate this: (i) High plasticity …

Regulation Of Regeneration In Arabidopsis Thaliana, Md Khairul Islam, Sai Teja Mummadi, Sanzhen Liu, Hairong Wei

Michigan Tech Publications, Part 2

We employed several algorithms with high efficacy to analyze the public transcriptomic data, aiming to identify key transcription factors (TFs) that regulate regeneration in Arabidopsis thaliana. Initially, we utilized CollaborativeNet, also known as TF-Cluster, to construct a collaborative network of all TFs, which was subsequently decomposed into many subnetworks using the Triple-Link and Compound Spring Embedder (CoSE) algorithms. Functional analysis of these subnetworks led to the identification of nine subnetworks closely associated with regeneration. We further applied principal component analysis and gene ontology (GO) enrichment analysis to reduce the subnetworks from nine to three, namely subnetworks 1, 12, and 17. …

An Overview Of Elements And Relations: Aspects Of A Scientific Metaphysics, Martin Zwick

Systems Science Faculty Publications and Presentations

A talk on my book, Elements and Relations: Aspects of a Scientific Metaphysics. Book description:

This book develops the core proposition that systems theory is an attempt to construct an “exact and scientific metaphysics,” a system of general ideas central to science that can be expressed mathematically. Collectively, these ideas would constitute a non-reductionist “theory of everything” unlike what is being sought in physics. Inherently transdisciplinary, systems theory offers ideas and methods that are relevant to all of the sciences and also to professional fields such as systems engineering, public policy, business, and social work. To demonstrate the generality …

Green Synthesized Silver Nanoparticles-Based Sensing For Monitoring Water Pollution: An Updated Review, Muhamad Allan Serunting, Muhammad Ali Zulfikar, Henry Setiyanto, Dian Ayu Setyorini, Vienna Saraswaty

Karbala International Journal of Modern Science

Water is a basic human need and has been heavily contaminated. Therefore, it becomes a concern to remove the pollutant and monitor its quality. The removal methods include precipitation, filtration, adsorption, and photodegradation. Meanwhile, the monitoring can be done by measuring and analyzing the contaminant using spectrophotometry and chromatography. Nevertheless, those methods usually need a complicated preparation, and are expensive. Thus, a simple method is necessary to overcome these drawbacks by developing a sensor. In recent years, the sensor performance has been enhanced by using nanomaterials, such as silver nanoparticles (AgNPs). AgNPs can be synthesized using plant extracts through a …

Synthesis And Characterization Of Zirconium Oxide Nanoparticles Using Z. Officinale And S. Aromaticum Plant Extracts For Antibacterial Application, M. J. Tuama, M. F. A. Alias

Karbala International Journal of Modern Science

Abstract The dramatic rise in bacterial infections and increased resistance to conventional antibiotics has led to the exploration of biologically derived nanomaterials to counteract bacterial activity. Nanotechnology, which deals with materials at the atomic or molecular level, is a promising way to achieve this goal. Zirconium oxide nanoparticles (ZrO2NPs) have shown strong antibacterial effects due to the increased surface-to-volume ratio at the nanoscale. This study focused on the production of ZrO2NPs in an environmentally friendly manner, which included extracts from Zingiber officinale (ginger), where G-ZrO2NPs were produced, and Syzygium aromaticum (clove), which produced S-ZrO2NPs. Various techniques were used, such as …

Motif-Cluster: A Spatial Clustering Package For Repetitive Motif Binding Patterns, Mengyuan Zhou

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Previous efforts in using genome-wide analysis of transcription factor binding sites (TFBSs) have overlooked the importance of ranking potential significant regulatory regions, especially those with repetitive binding within a local region. Identifying these homogenous binding sites is critical because they have the potential to amplify the binding affinity and regulation activity of transcription factors, impacting gene expression and cellular functions. To address this issue, we developed an open-source tool Motif-Cluster that prioritizes and visualizes transcription factor regulatory regions by incorporating the idea of local motif clusters. Motif-Cluster can rank the significant transcription factor regulatory regions without the need for experimental …

Depaul Digest

DePaul Magazine

College of Education Professor Jason Goulah fosters hope, happiness and global citizenship through DePaul’s Institute for Daisaku Ikeda Studies in Education. Associate Journalism Professor Jill Hopke shares how to talk about climate change. News briefs from DePaul’s 10 colleges and schools: Occupational Therapy Standardized Patient Program, Financial Planning Certificate program, Business Education in Technology and Analytics Hub, Racial Justice Initiative, Teacher Quality Partnership grant, Intimate Partner Violence and Brain Injury collaboration, School of Music Career Closet, Sports Photojournalism course, DePaul Migration Collaborative’s Solutions Lab, Inclusive Screenwriting courses. New appointments: School of Music Dean John Milbauer, College of Education Dean Jennifer …