Computer Sciences Commons^™

Interpretable Deep Learning Models For Trustworthy Prediction Of Enzyme Functions, Louis Dumontet

UNLV Theses, Dissertations, Professional Papers, and Capstones

Trustworthy prediction of enzyme function from protein sequences remains a central challenge in computational biology, particularly when annotated data are limited, imbalanced, or incomplete. This dissertation develops interpretable deep learning methods for enzyme discovery and enzyme function prediction from amino acid sequences. First, it introduces PEPIC, an interpretable convolutional neural network for substrate-level prediction of hydrolytic plastic-degrading enzymes. Using curated and expanded sequence datasets, PEPIC improved predictive performance over benchmark methods, identified sequence regions aligned with catalytic and substrate-binding residues, and supported the discovery and experimental validation of a previously uncharacterized PET-degrading enzyme. Second, this dissertation investigates the integration of …

Phase-Preserving Machine Learning Forecasting Of Nonlinear Predator–Prey Dynamics, Saira Batool, Muhammad Imran, Brett Mckinney

Biology and Medicine Through Mathematics Conference

No abstract provided.

Agentic Scientific Machine Learning For Autonomous Model Discovery In Systems Pharmacology, Nazanin Ahmadi, George Karniadakis

Biology and Medicine Through Mathematics Conference

No abstract provided.

A Gis Analysis Of The Relationship Between Ndvi Value, Slope, And Aspect Of The Terrain Of The Prairie Restoration Project, Basil Lund

2026 Symposium

The Prairie Restoration Project (PRP) encompasses 115 acres of land on the west side of the EWU campus. The goal of the PRP is to restore what was once a section of wheat farm back to its original Palouse prairie state. Here, I am using publicly available satellite data to examine some potential variables affecting the health of wheat plants planted in the years 2009 to 2017. I have used 4-band aerial imagery to create a map of NDVI values within the bounds of the PRP, which visualizes the near-infrared wavelengths that are reflected by healthy, chlorophyll-rich plants. I have …

Predicting And Decoding Allosteric Binding Sites Using Protein Language Models And Structure-Based Machine Learning: An Energy Landscape-Guided Explainable Ai Framework, Kamila Riedlová, Vít Skrhák, William G. Gatlin, Max Ludwick, Lucas Turano, Marian Novotný, David Hoksza, Gennady M. Verkhivker

Mathematics, Physics, and Computer Science Faculty Articles and Research

Computational prediction of allosteric binding sites in protein structures remains a persistent challenge, as these regulatory pockets evade detection by both sequence-based and structure-based algorithms. Both computational and physical origins of this predictive asymmetry remain insufficiently understood. In this study, we systematically examine the determinants of binding site predictability using a dual framework that integrates a fine-tuned protein language model and the structure-based method P2Rank as complementary tools probing a diverse data set of 453 human kinases, together with a physics-based interpretability layer derived from energy landscape frustration analysis. Both predictors exhibit a sharp and reproducible dichotomy on protein kinases, …

Volume 17, Christian O’Neill, Kyara Greene, Savva Sidorov, Laura Bisaillon, Luke Clemmer, Hannah Gordon, Kitt Benson, Taylor Blount, Rachel Danzitz, Nicholas Duellman, Chase Gionis, Hima Fernando, Seth Franzyshen, Onyx Gonzalez, Bryan Lin, Samantha Start, Ysabel Wells, Maggie Duncan

Incite: The Journal of Undergraduate Scholarship

Introduction Dr. Amorette Barber, Director, Office of Student Research

From the Editor Dr. Hannah Dudley-Shotwell

Cover Artist’s Statement Maggie Duncan

On Mentoring Dr. Yulia Uryadova

Ukrainian Resistance in the Face of Russification: Nestor Makhno and Anarchism

by Christian O’Neill

Life Vest by Kyara Greene

Isolation and 16S rRNA Identification of Bacteria from Fire Department Connection Pipe by Savva Sidorov

The Effectiveness of Planned Exercise in Reducing ADHD Symptoms in Children by Laura Bisaillon & Luke Clemmer

Linguistic Analysis on Confidence and Communication Strategies with Disparities Between Sign Fluency and Hearing Impairment by Hannah Gordon

Freedmen in Indian Territory by Kitt …

Ai-Driven Multispectral Drone Monitoring For Afforestation In Arid Environments, Hesham Morgan, Ali Elgendy, Brandon Tran, Tamer Ismail, Mohamed M. Moursy, Yehya Kh. Shehadeh, Ahmed Elgharib, Ahmed Abdullah Al-Dughairi, Ali El Mubarak, Khaled Allam Harhash, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Monitoring large-scale afforestation projects in arid and semi-arid environments requires accurate, high-resolution, and repeatable methods to assess tree survival and growth. In this study, we integrated unmanned aerial vehicle (UAV) multispectral imaging with an advanced object detection framework to evaluate vegetation establishment in the Shuayb Al-Budai afforestation site, part of the Imam Turki bin Abdullah Royal Natural Reserve, Kingdom of Saudi Arabia (KSA). Multispectral datasets were acquired using a MicaSense Altum-PT sensor and processed through a masked Region-based Convolutional Neural Network (RCNN) with two backbone architectures: ResNet-101 and VGG19-BN. The Mask R-CNN–ResNet-101 model achieved superior performance, with an overall accuracy …

Solarvale: Exploring Australian Ecology And Culture Through Serious Game Design, Ping-I (Adam) Ho, Elliot Birch

Imaginings: creative practice and inquiry

This research examines how a serious game (Gee, 2007): Solarvale: Tale of the Sun Root (Birch et al., 2024), developed by students from SAE University College addresses the importance of ecological conservation and cultural awareness specifically in relation to the Australian landscape. While some Australian serious games, such as Catchment Detox (2008), Paperbark (2018), and Bleached Az (2019) engage with similar themes, few titles integrate storytelling with interactive ecological environments and cultural awareness in a way that encourages players to reflect on their own role and actions—which is the central focus of Solarvale. Drawing on the concepts from serious …

Isolation, Identification And Antibiotic-Resistance Profiling Of Bacteria Isolated From Mobile Phone Surfaces In Karbala., Kawkab Abdullah Alsaadi, Zahraa Raheem Murshidy, Dhuha Ali Hussein, Sura Abd Ali Kadhim, Kawakib Aboudi Hanoon

Karbala International Journal of Modern Science

Due to the diverse environments that mobile phones are exposed to via human handling they become reservoirs of microorganisms. The objective of the current study was to determine the level and character of bacterial contamination on mobile phones by identifying bacterial strains, and the degree of antimicrobial susceptibility. A cross-sectional study was conducted from April to July 2025 where phones belonging to 115 individuals were randomly chosen from various departments and units at Kerbala University and swabbed. The VITEK 2 automated system was used to identify bacterial taxa and test for antimicrobial susceptibility, and 50 of the swabs exhibited bacterial …

High Performance Ae-Cnn Model Enhanced Via Gaussian Augmentation For Rssi-Dependent Indoor Positioning In Wireless Sensor Networks, Kahlaa K. Al-Nassrawy, Ghaidaa A Al-Sultany

Karbala International Journal of Modern Science

Precise indoor positioning system remains a significant challenge within Wireless Sensor Networks (WSNs) due to the instability and noise sensitivity of Received Signal Strength Indicator (RSSI) data. This paper proposes an advanced hybrid deep learning framework designed for 2D indoor localization, utilizing RSSI measurements to predict human or object position. Furthermore, to enhance the robustness of the model against signal variance and promote its generalization capability under this uncertainty, a data augmentation strategy is applied using three methods: Gaussian Noise Injection (GNI), Gaussian Mixture Model (GMM), and Bayesian Gaussian Mixture Model (BGMM). The purpose of data augmentation is to simulate …

Inc3vits Model: A Hybrid Architecture To Accelerate And Reduce Complexity For The Deepvariant Model For Variant Calling, Mustafa Al-Saffar, Sura Z. Al Rashid

Karbala International Journal of Modern Science

Deep learning has revolutionized genomic variant calling, yet the computational cost of current systems continues to limit scalability. We present a controlled efficiency study of DeepVariant-style pileup architectures under identical training and inference conditions, comparing architectural downsizing with a hybrid CNN–local attention design. Inc3ViTs pairs a streamlined InceptionV3 stem with a lightweight local attention head based on patch tokenization and windowed self-attention, enabling a direct comparison with a CNN-only reduced Inception baseline. Across whole-genome and whole-exome short-read datasets, Inc3ViTs reduces training time by ~40–50% and reduces inference runtime relative to the original DeepVariant. The CNN-only baseline indicates that most speedups …

The Efficacy Of Manganese Sulfate As A Negative Contrast Agent For Magnetic Resonance Cholangiopancreatography, Zainab Abdulla Mankhi

Karbala International Journal of Modern Science

The current study aims to find an alternate oral contrast media for use in magnetic resonance cholangiopancreatography (MRCP) that satisfies the following criteria, the greatest imaging quality safety, no or few side effects, and low cost. The present study created an oral contrast agent sample (solution) by dissolving a one tablet of manganese sulfate supplement (taken daily dose) in 200 ml of distilled water. Thirty-three volunteers assessed the sample using MRCP examine pre and post contrast. By evaluating the signal intensity to compute contrast (C), signal to noise ratios (SNR), and contrast to noise ratio (CNR), the resulting MR images …

Dna Barcoding Of Eight Freshwater Fish Species (Order Siluriformes) From The River Ravi, Pakistan, Hafiz Muhammad Ashraf, Hafiz Abdullah Shakir, Muhammad Irfan, Shaukat Ali, Chaman Ara, Noor Khan, Muhammad Khan, Abdul Qadir, Muhammad Zafar Saleem

Karbala International Journal of Modern Science

Pakistan's freshwater bodies host significant fish species, but molecular identification is still in its infancy, necessitating the use of morphological and molecular DNA barcoding techniques. The study confirmed the species of the order Siluriformes found in the River Ravi, Pakistan, using DNA extracted from muscle tissue, sequenced for the COI gene, and obtained accession and Barcode Index Numbers from GenBank and BOLD databases. In the BLAST search, identities ranged from 99.23–100% and 99.52–100% in the GenBank and BOLD databases, respectively. The study revealed that the Kimura 2-Parameter genetic distance increased from lower to higher taxonomic levels: within species (0.00%) < within genus (15.17%) < within family (19.77%). The study estimated average nucleotide differences (104.964) and nucleotide diversity (0.16099) but found Tajima's neutrality test to be statistically insignificant. The neighbor-joining tree displayed closely linked species under a node, whereas divergent species were grouped under distinct nodes. The COI gene-based DNA barcoding aids in Pakistan's fish resource inventory, monitoring, and management, providing valuable input for traditional methods.

Eco-Assisted Ultrasonic Synthesis, Characterization, And Electrical Conductivity Study Of Polyaniline/ Silica@Fe3o4 Q1 Nanocomposites, Ali Salim Shaway, Kholoud Dham Khamkheem, Jawad Kadhim Abaies, Athra G. Sager

Karbala International Journal of Modern Science

وفي هذه الدراسة الصوتية، أصبحت السيليكا المُنتجة بأكسيد الحديد (Fe₃O₄) ومركبات نانوية قائمة على البولي أنيلين مُطعّم بنسبة 5-15% من السيليكا المُعزز للحديد (Fe₃O₄). وأكملت نهائيا ماء أنيلين والمركبات العلمية المتنوعة الارتباط باستخدام تقنيات FT-IR وUV-Vis وXRD وSEM وTEM. وأحدثت نتائج XRD أن حجم جسيمات البولينج أنيلين الناي (PANI) يبلغ 55.5. مكثف هذا الحجم إلى 45.2 عند تطعيم بولي أنيلين بنسبة 15% وزناً من السيليكا المُغلفة بأكسيد الحديد (Fe₃O₄) مُحضّرة بطريقة جيدة بشكل جيد، مما يميل إلى التمدد بشكل ثابت في تشكيل المركب المتباين المنظم. ضاقت النطاق البصري من 3.2 إلى 2.5 إلكترون فولت مع زيادة نسبة المطعّم، مما يشير …

Anti-Inflammatory And Insulin-Modulating Effects Of Tithonia-Curcuma-Moringa (Tcm) Formulation In Type 2 Diabetes: An Experimental Study In Mice, Rif’Atul Hawani Burhan, Nabila Shafa Yumna Salsabila, Devita Zulfa Pratama, La Tazkia Aulia Wibowo, Yulian Ervin Maulana, Moh Dliyauddin, Noviana Dwi Lestari, Agung Pramana Warih Marhendra, Aris Soewondo, Hideo Tsuboi, Muhaimin Rifa’I

Karbala International Journal of Modern Science

Type 2 diabetes is a chronic metabolic disorder characterized by hyperglycemia and chronic inflammation. This study investigated the anti-inflammatory and insulin-modulating effects of Tithonia-Curcuma-Moringa (TCM) formulation in type 2 diabetes model. Male BALB/c mice were divided into six groups: normal control, type 2 diabetes control, metformin treatment, and three TCM formulation treatment groups with three different dose combinations. Type 2 diabetes was induced using a high-fat diet combined with streptozotocin injection, supported by sucrose administration. After 21 days of treatment, the spleen and pancreas were isolated for flow cytometry analysis. The results showed that the expression levels of …

Dissecting The Etiology Of Alcohol Use Disorder By An Integrative Heritable Component Approach, Ivy Garrenton

Computer Science Theses & Dissertations

Alcohol Use Disorder (AUD) is a pervasive condition characterized by complex interplay among genetic, phenotypic, and environmental factors. Although previous studies have identi fied genetic loci associated with alcohol consumption, these efforts have not captured the genetic heterogeneity and gene-environment interactions underlying AUD pathogenesis. To address this critical gap, we developed a novel statistical methodology that integrates phenotypic, genotypic, and environmental data through an environmentally modified Genetic Relationship Matrix (GRM) to derive AUD-related traits with enhanced heritability.

This approach demonstrated superior performance in both simulated and real-world datasets. Traits derived using the environmentally modified GRM exhibited significantly higher estimated heritability …

The Effects Of Affordability And Quality Of Care On Utilization Of Primary Healthcare Among Rural Residents In Twifo Ati-Morkwaa District, Ghana: A Qualitative Study, Peter Ansah Boakye, Francis Tei-Nartey, Gideon Owusu

Michigan Tech Publications

Objective: This qualitative study examines how affordability and quality of care influence the utilization of primary healthcare (PHC) services among rural residents in the Twifo Ati-Morkwaa District, Ghana. While Ghana has implemented policies such as CHPS and NHIS to improve access, subjective experiences of rural residents regarding total costs of care and perceived quality remain underexplored. Methods: We conducted a qualitative cross-sectional study between April and September 2024 using purposive and snowball sampling. Ten gender-segregated focus group discussions (FGDs; n = 90 residents) and six in-depth interviews (IDIs) with PHC providers were conducted. Data were collected in Twi, transcribed and …

Polyherbal Phytochemicals As Multi-Target Inhibitors Of Key Breast Cancer Proteins: A Computational Approach, Nadia Wahyuningsih, Nashi Widodo, Sri Rahayu, Muhaimin Rifa’I

Karbala International Journal of Modern Science

Breast cancer is a primary worldwide health concern, and conventional therapies often cause side effects. This study was performed to investigate the therapeutic potential of a polyherbal formulation containing Curcuma longa, Phyllanthus niruri, Ziziphus mauritiana, Nigella sativa, and Annona muricata as multi-target inhibitors against breast cancer protein targets using molecular docking and molecular dynamics in silico approach. Bioactive compounds were analyzed using Liquid Chromatography High-Resolution Mass Spectrometry (LC-HRMS) to identify the extract's phytochemicals. The compounds were examined for drug-likeness, membrane permeability, bioactivity, and toxicity. The inhibitory ability against the proto-oncogene pathway, which is commonly dysregulated and mutated in breast cancer, …

Synthesis And Characterization Of Ti-Enhanced F75/Ha Functionally Graded Materials Fabricated By Powder Metallurgy, Afrah M. Al Hussainey, Aseel Mustafa, Randa Kamel Hussain

Karbala International Journal of Modern Science

Functionally graded materials (FGMs) are a highly advanced class of biomaterials with graded structure and properties, enabling the fabrication of physiologically and mechanically compatible materials for use in various medical devices. This study aims to produce a functional-grade material based on a cobalt-chromium-molybdenum alloy (F75) reinforced with 4% titanium (Ti) and hydroxyapatite (HA). This will enhance the material's mechanical properties, corrosion resistance, and bioactivity, making it suitable for use as a bone substitute. The natural eggshells were washed, burnt, and chemically processed to form hydroxyapatite with a Ca/P proportion of 1.67. FTIR showed that phosphate and OH groups were separate, …

The Application, Construction, And Validation Of Hidden Markov Model Profiles For Carbonic Anhydrase Enzymes, Samuel F. Kaplan

Master's Theses

Carbonic anhydrases (CAs) catalyze the reversible hydration of CO2 and have evolved independently at least eight times, resulting in structurally distinct enzyme families (α, β, γ, δ, ζ, η, θ, ι). Traditional sequence alignment methods struggle to classify these convergently evolved proteins because their sequential similarity does not reliably indicate functional or evolutionary relationships. Many CA sequences in public databases are annotated generically without family assignments, and prior computational approaches have focused predominantly on the three well characterized families (α, β, γ), leaving the five recently discovered classes without robust classification tools. Family level assignment is often a prerequisite for …

Cerebral Documents And Algorithmic Sensemaking: Searching For Expressions In Human And Artificial Cognitive Collaborations, Rebekah L. Cowell

Proceedings from the Document Academy

Generative Artificial Intelligences (AIs) and current advanced large language models (LLMs) are algorithmically designed to generate text-based conversations as conversational agents (CAs), by replicating human language and conversational communication. Pairing human cognition with generative computationally coded cognition. We have never been here before: cerebral and artificial information collaborations and processing producing expressions that may or may not become visible as second-hand/secondary source documents.

Sensemaking or sense(un)making is a unique autonomous human drive cognitively, our information processing is sensemaking in action and expressions and articulations are evidence of the sensemaking cycle. Documentation [expressed or articulated through various mediums] are a product …

Molecular Detection Of Genes Encoded For Biofilm Formation In Bacteria Isolated From The Oral Cavity Of Patients, Tebarek Al-Taei, Ali A. Al-Hisnawi

Karbala International Journal of Modern Science

Background: A biofilm is a collection of the microbial cells attached to the surface that are encased in a matrix of extracellular polymers. Biofilm formation creates a physical and chemical barrier that prevents antibiotics from reaching bacterial cells, resulting in treatment failure and reinfection. The present study aimed to investigate the biofilm formation in bacteria isolated from the oral cavity of patients.

Methods: In this study, 150 bacterial isolates were obtained from tooth and gum surface swabs of male and female patients of different ages who visited specialized centers and dental clinics in Babylon City after they were clinically diagnosed …

Discovery Of Horsfieldia Macrothyrsa Bioactives With Cytotoxic Effects On Breast Cancer Cells Through In Vitro And Docking Analyses, Megawati Megawati, Akhmad Darmawan, Agus Budiawan Naro Putra, Kartika Dyah Palupi, Marissa Angelina, Ahmad Randy, Siska Andrina Kusumastuti, Faris Hermawan, Sumi Hudiyono

Karbala International Journal of Modern Science

This study investigated the phytochemical constituents and biological activities of Horsfieldia macrothyrsa leaves to identify their bioactive compounds. Methanol extracts were fractionated using n-hexane and ethyl acetate, followed by silica gel column chromatography with a stepwise polarity gradient. From 100 g of powdered leaves, three major    compounds were successfully isolated from the ethyl acetate fraction: 1-(2,4,6-trihydroxyphenyl)dodecan-1-one (1), sesamin (2), and β-sitosterol (3). Their chemical structures were confirmed using UV, IR, LC–MS/MS, and NMR  spectroscopy. Biological activities of the fractions and isolates were evaluated through DPPH antioxidant assays, α-glucosidase inhibition for antidiabetic activity, MTT …

Cellscout: Visual Analytics For Mining Biomarkers In Cell State Discovery, Rui Sheng, Zelin Zang, Jiachen Wang, Yan Luo, Zixin Chen, Yan Zhou, Shaolun Ruan, Huamin Qu

Research Collection School Of Computing and Information Systems

Cell state discovery is crucial for understanding biological systems and enhancing medical outcomes. A key aspect of this process is identifying distinct biomarkers that define specific cell states. However, difficulties arise from the co-discovery process of cell states and biomarkers: biologists often use dimensionality reduction to visualize cells in a two-dimensional space. Then they usually interpret visually clustered cells as distinct states, from which they seek to identify unique biomarkers. However, this assumption is often this assumption often fails to hold due to internal inconsistencies in a cluster, making the process trial-and-error and highly uncertain. Therefore, biologists urgently need effective …

Modulation Of Hypothalamic–Limbic Circuits Regulating Appetite In Response To Health Lifestyle In Obese Adults, Nour Shakir Rezaieg, Muthanna M. Awad

Karbala International Journal of Modern Science

Background: Overeating leads to obesity a low-grade inflammatory disease. In this context, aguati-related neuropeptide (AgRP) and ghrelin are pivotal players in appetite regulation, while chemerin is an adipose tissue-secreted adipokine that contributes to low-grade inflammation associated with obesity. Objective: This study used a healthy lifestyle program designed for each obese participant to identify diet-related neuro-hormonal changes in appetite regulation. Design, Setting, and Participants: This a longitudinal quasi-experimental controlled study was conducted from 1^st December 2024, to 30^th July 2025, at University of Anbar. The sample included 100 participants, 50 obese (weight between 100–140 kg) and 50 healthy participants …

Evaluation Of Mcf-7 Breast Cancer Cell Cytotoxic And Antioxidant Activities Of Peptide Fractions From Symbiotic Bacteria Of Jellyfish Catostylus Sp., Eka Sry Wahyuni, Ahyar Ahmad, Muhammad Nasrum Massi, Sofa Fajriah, Randi Rimpung, Muh. Akbar Ardiputra, Harningsih Karim, Irda Handayani

Karbala International Journal of Modern Science

Marine-derived symbiotic microorganisms are recognized as a promising source of bioactive compounds with potential therapeutic applications, yet research on jellyfish-associated bacteria remains limited. This study examines the bioactivity of peptide fractions derived from symbiotic bacteria isolated from the jellyfish Catostylus sp., collected from the coastal waters of South Sulawesi, Indonesia, with a focus on their anticancer and antioxidant properties. Following sample collection, the symbiont bacteria were isolated, enzymatically hydrolyzed, and purified before their biological activity was evaluated. Preliminary cytotoxicity screening using the brine shrimp lethality assay revealed that the extracellular peptide fraction (5–10 kDa) and intracellular peptide fraction (3–5 kDa) …

Antibacterial Peptides From Soybean (Glycine Max (L.) Merr.) With In Silico Study Against Escherichia Coli Bacteria, Dian Riana Ningsih, Ely Setiawan, Purwati Purwati, Zusfahair Zusfahair, Anita Hindayanti Rukmana

Karbala International Journal of Modern Science

Bioactive peptides are produced from soy milk protein hydrolysis using trypsin. The research began with the preparation and separation of soy milk protein, followed by fractionation using ammonium sulphate, protein hydrolysis, and SDS-PAGE analysis of protein hydrolysates. Fractions exhibiting the highest degree of hydrolysis were further fractionated by SPE and tested to determine the antibacterial activity Staphylococcus aureus and Escherichia coli. The peptide sequence of the active peptide as an antibacterial was identified, employing LC-HRMS. The mode of action between active peptides and bacterial membran was analysed using molecular dynamics (MD) simulation. The findings displayed that F15 contained the highest …

Sperm-Associated Antigen 6 (Spag6) As A Potential Marker Of Sperm Function In Diagnosing Male Infertility, Ibtisam A. Al-Ali,, Kawkab A. Alsaadi

Karbala International Journal of Modern Science

Background: While male infertility has become a significant global health concern, conventional analysis of semen has not made progress in the detection of contraindicated molecular biomarkers, such as sperm-associated antigen 6 (SPAG6), which is a protein involved in axonemal structure and flagellar motility.

Hypothesis: Expression of SPAG6 correlates with sperm motility and structural integrity. This means that its dysregulation may serve as a molecular indicator of impaired sperm performance.

Methods: A comprehensive review of recent studies was conducted with a focus on SPAG6’s molecular characteristics, expression patterns in normal versus abnormal spermatozoa, and the role it plays in motility-related …

Optimized Co2 Gas Sensing With Sns:Sm2o3/N-Si Nanocomposites Fabricated Via Spray Pyrolysis, Wasan A. Khalaf, Mays A. Hammadi, Mohammed J. Alsultani, Yahya R. Hathal, Mohammed O. Salman

Karbala International Journal of Modern Science

In this work, tin sulfide:samarium oxide (SnS:Sm₂O₃) composite films were deposited using a spray pyrolysis technique for room-temperature CO₂ gas sensing. X-ray diffraction (XRD) confirmed a polycrystalline SnS nature of orthorhombic-phase crystallinity at 10 at.% Sm ions, while 20 at.% Sm induced Sm₂O₃ as a separate phase. Field emission-scanning electron microscopy (FE-SEM) induced uniform grains and increased the surface roughness, enhancing gas adsorption. UV-visible absorbance revealed band-gap narrowing. Fourier transform infrared spectroscopy (FTIR) analysis revealed vibrational band shifts, confirming the structural modifications. Gas-sensing measurements demonstrated 5.72%, 19.65%, and 9.65% for pure SnS, …

A Hybrid Response Surface Methodology And Machine Learning Framework For Quantifying Effects Of Physicochemical Parameters On Pfas Distribution, Harsh V. Patel, Jazmin Green, Hyoshin Park, Stephanie Luster-Teasley Pass, Renzun Zhao

Engineering Management & Systems Engineering Faculty Publications

Predicting PFAS adsorption across diverse adsorbents and environmental matrices remains challenging because adsorbent physicochemical properties, PFAS molecular descriptors, and operational conditions simultaneously influence adsorption. This study develops and evaluates a unified hybrid modeling framework that integrates Response Surface Model (RSM) with machine-learning algorithms to quantify how six key variables, surface area, Log K_ow, pH_pzc, pK_a, log dose, and log-initial concentration, affect PFAS distribution coefficients (Log K_d). A data set of more than 1000 adsorption observations spanning 15 PFAS compounds, multiple adsorbent types, and a broad operational range was compiled and preprocessed using …