Digital Commons Network^™

Replicating Associative Learning Of Rodents With A Neuromorphic Robot In An Open-Field Arena, Tianze Liu, Kang Jun Bai, Hongyu An

Michigan Tech Publications

This study emulates associative learning in rodents by using a neuromorphic robot navigating an open-field arena. The goal is to investigate how biologically inspired neural models can reproduce animal-like learning behaviors in real-world robotic systems. We constructed a neuromorphic robot by deploying computational models of spatial and sensory neurons onto a mobile platform. Different coding schemes—rate coding for vibration signals and population coding for visual signals—were implemented. The associative learning model employs 19 spiking neurons and follows Hebbian plasticity principles to associate visual cues with favorable or unfavorable locations. Our robot successfully replicated classical rodent associative learning behavior by memorizing …

Inverse Problem Of Class Of Delay Differential Equations And Fast Estimation Of Parameters, Ibrahim Makki Khalil, Jehan Mohammed Khudhir

Baghdad Science Journal

This article introduces an integral representation formula to solve delay nonlinear ordinary differential equations (DDEs) as an improvment to the method proposed by Tyukin I, et al. of solving a class of ordinary differential equations. The integral formula depends on the parameters of the systems explicitly as nonlinear parameterized computable functions. It features both linear and nonlinear equations and show an effective form for estimating unknown parameters. Solutions of DDEs are represented as sums of computable integrals which are implicitly dependent on the initial condition and the unknown parameters. This allows invoking parallel computational streams using Matlab tools of sums …

Numerical Solution Of Distributed Order Fractional Differential Equations Using Spectral Mittag-Leffler Weight Function Based On Chelyshkov Polynomials, Abdulrazzaq T. Abed, Ekhlass S. Al-Rawi

Baghdad Science Journal

In many studies, spectral methods based on one of the orthogonal polynomials and weighted residual methods (WRMs) have been used to convert the distributed-order fractional differential equation (DOFDEs) into a system of linear or nonlinear algebraic equations, and then solve this system to obtain the approximate solution. In this paper, a numerical method is presented for solving DOFDEs. The approximate solution is imposed as an orthogonal Chelyshkov polynomial with unknown coefficients. The required coefficients are obtained using WRMs, which transform the DOFDEs into a system of algebraic coefficients. The Mittag-Leffler function is proposed as a suitable weight function. The method …

Improving Golden Eagle Optimization Algorithm Through Using Wavelet Mutation, Ebtehal Talib, Abeer Salim Jamil, Nidaa Flaih Hassan

Baghdad Science Journal

The Golden Eagle Optimization (GEO) algorithm is another amazing nature inspired optimization algorithm based on the foraging behavior of the Golden Eagles. GEO is an excellent behavioral model of how Golden Eagles interact with one another while searching for prey, consisting of a population of virtual “eagles” that together represent potential solutions to the optimization problem. The “eagles” interact with one another and together communicate and move as a single unit towards something, in this case the optimal solution. In this paper, we expand upon this idea with a new version of the GEO algorithm, called Wavelet Mutation Golden Eagle …

Cancer Detection Framework Using Cellular Automata Based Segmentation And Deep Learning, Rupashri Barik, Nazma B J Naskar, Aleena Swetapadma

Baghdad Science Journal

Image processing plays vital role in medical sciences. Medical image processing reduces diagnosis time and cost. Early detection of cancer may reduce life risk. Earlier works on cancer detection mostly focused on specific organs and imaging modalities. This work aims a generalized framework for detecting tumors in various organs by analyzing different imaging modalities. Here, Cellular Automata helps in image segmentation through region growing, and deep learning algorithms made performance analysis in terms of accuracy and loss. Analyzing CT-Scan, MRI images of brain, breast, lungs, the proposed framework may assist to detect the region of mass being developed. Proposed CA-based …

Accelerating Face Mask Detection Training Model Based On Multi-Gpus And Multi-Core Cpu, Ammar Hussein Jassim, Nada Hussain Ali, Ahmed Al-Taie, Doaa Mohammad Majed

Baghdad Science Journal

Modern machine-learning applications require GPUs, and modern platforms can leverage numerous GPUs on one or more machines to increase performance. Contemporary deep-learning models are too huge for CPU or GPU training. Training these models with many GPUs without performance degradation is necessary to train them rapidly and maximize GPU consumption. Thus, training deep convolutional neural networks (DCNN) with multiple GPUs has become necessary for improving training. Therefore, we presented a parallel design and development of an efficient model for enhancing face mask CNN performance and improving resource efficiency. This DCNN model is a parallel training system over multiple GPUs, a …

Advancing Political Science With Machine Learning: A Gaussian Process Approach, Yehu Chen

McKelvey School of Engineering Graduate Student Theses & Dissertations

The proliferation of data in recent decades including including survey, image and text data, has significantly transformed the landscape of political science research. Machine learning methods have played an instrumental role in analyzing these datasets, yet their application poses challenges in areas where political concepts are not directly measurable or the primary focus of inference is causality. In addition, the essence of machine learning algorithms being trained for prediction performance in a black-boxed manner, makes their outputs hardly interpretable and even unappreciated. This dissertation addresses these issues by proposing a novel methodological framework that employs Gaussian Process (GP) models, a …

Leadership In Open Innovation: Strategies For Effective Crisis Management In Malaysia, Mosharrof Hosen, Irfan Hameed, Rajat Subhra Chatterjee, Mosaddek Hossain, Hafiz Mudassir Rehman

Plymouth Business School

The study of crisis management is vital for developing effective strategies that address the unique challenges posed by socio-political and environmental contexts. Despite its importance, there is a notable lack of research on crisis management across various sectors in Malaysia. This highlights the need for comprehensive studies considering the country's challenges and strategies. Through the lens of dynamic capabilities theory, this research aims to fill the gap in existing literature by focusing on Malaysia's distinct socio-economic and cultural dynamics, which may influence the effectiveness of crisis management strategies. Data were collected from 310 employees of Malaysian manufacturing companies and analyzed …

Determination Of Mitoxantrone In Environmental Waters: A Spectrophotometric Method With Preconcentration By Salt Saturated Pipette-Tip Micro Solid Phase Extraction Using Molecularly Imprinted Polymer, Sayyed Hossein Hashemi, Massoud Kaykhaii, Ahmad Jamali Keikha, Mina Esmailiun

Turkish Journal of Chemistry

In this research, a fast and simple spectrophotometric method is presented for mitoxantrone determination in various aqueous samples. It utilizes preconcentration by salt saturated pipette-tip micro solid phase extraction with a selective molecularly imprinted polymer adsorbent packed in a micropipette tip. Prior to sample loading, they were saturated with a mixture of NaCl, Mg (NO3)2.6H2O and KNO3 salts, enhancing extraction efficiency by 27.5% compared to salt-free conditions. Key microextraction parameters (amount of molecularly imprinted polymer, sample pH, eluent type/volume, and adsorption/desorption cycles) were optimized using response surface methodology and one-variable-at-a-time methods. The method achieves a low detection limit (0.2 μg …

Physical And Chemical Characterization Of Recycled Glass Sand For Environmental Restoration, Shehbaz Ahmad, Julie P. Vanegas, Nicholas Borne, Natalia Butler, Toby Mendels, Leah A. Michaeloff, Diego Molina, Mary Salvaggio, Samantha Tamayo, Franziska Trautmann

Physics & Astronomy Faculty Publications

Introduction

We rely on coastal resources for food, water, and energy. However, over 75% of U.S. coastlines are eroding. Concurrently, the U.S. recycles less glass than other developed countries, landfilling hundreds of millions of tons every year. Recycled glass sand has many potential benefits over natural sand for combatting land loss; for example, it can be produced with controlled particle size to better resist erosion, making it an excellent—and underutilized—material for environmental restoration.

Objectives

This research compares the physical and chemical properties of recycled glass sand to natural sands (beach and dredge) from the U.S. Gulf Coast to assess environmental …

Cover And Contents

Turkish Journal of Chemistry

No abstract provided.

Which Adolescents Benefit Most From Positive Psychology Interventions: Examining The Common Factors Of Therapeutic Change, Nicolette Bauermeister

USF Tampa Graduate Theses and Dissertations

The literature has found positive psychology interventions to be effective at improving the subjective well-being of youth (Tejada-Gallardo et al., 2020). Further research is needed to identify variables such as common factors of change that could be contributing to whether youth report improved outcomes after participating in a positive psychology intervention. This study examined common factors of therapeutic change as predictors for outcomes such as positive affect, negative affect, and life satisfaction, which are components of subjective well-being. This dissertation aimed to fill the gap in the literature regarding common factors of change as predictors of outcomes in school-based positive …

Perception Of Florida Political Actions By Higher Education, Matt Vanover Vanover

Electronic Theses and Dissertations Archive

This qualitative dissertation examines the impact of recent political actions in Florida on higher education, specifically exploring how these developments have influenced tenured, public university professors' teaching practices, student interactions, and research agendas. Guided by the theoretical framework of social constructionism and employing narrative inquiry as the methodological approach, the study captures the lived experiences of six tenured faculty members at public universities across the state. The findings indicate that Florida’s political actions of Governor Ron DeSantis and a Republican-led legislature may have led to changes in the academic landscape. Professors report self-censorship in the classroom, limited discussions of controversial …

Quality Improvement Project Reducing Pediatric Anesthesia In Magnetic Resonance Imaging: The Role Of Preparedness And Education, Rachel Turner

Doctor of Nursing Practice Projects

Pediatric hematology-oncology patients undergo general anesthesia (GA) for various medical procedures, including magnetic resonance imaging (MRI) scans. Overexposure to GA increases the potential for long-term neurocognitive effects in pediatric patients. Despite the growing research literature on GA-related neurotoxicity and the Food and Drug Administration's (FDA) warnings, advanced practice providers (APP) often lack the knowledge to advocate for and support reductions in pediatric GA use. The Doctor of Nurse Practice (DNP) quality improvement (QI) project aimed to reduce unnecessary GA in pediatric hematology-oncology patients undergoing MRI scans by addressing the primary clinic APPs' knowledge deficits through interprofessional education (IPE). Structured in …

"Mattering" Is The Foundation Of Identifying 'What Matters' In Patient Care, Kieran Green, John Downey, Sheena Asthana, Joanne Watson

School of Nursing and Midwifery

No abstract provided.

Molecular Landscape Of Sex- And Modality-Specific Exercise Adaptation In Human Skeletal Muscle Through Large-Scale Multi-Omics Integration, Macsue Jacques, Shanie Landen, Adam P. Sharples, Andrew Garnham, Ralf Schittenhelm, Joel Steele, Aino Heikkinen, Elina Sillanpää, Miina Ollikainen, James Broatch, Navabeh Zarekookandeh, Ola Hanson, Ola Ekström, Olof Asplund, Séverine Lamon, Sarah E. Alexander, Cassandra Smith, Carlie Bauer, Mary N. Woessner, Itamar Levinger, Andrew E. Teschendorff, Linn Gillberg, Ida Blom, Jørn Wulff Helge, Nicholas Harvey, Larisa M. Haupt

Research outputs 2022 to 2026

We investigated the molecular mechanisms of exercise adaptations in human muscle by integrating genome, methylome, transcriptome, and proteome data from over 1,000 participants (2,340 muscle samples). We identified distinctive signatures associated with maximal oxygen consumption (VO2max), and multi-omics integration uncovered five key genes as robust exercise markers across layers, with transcription factors functioning as activators, synergizing with DNA methylation to regulate gene expression. Minimal sex differences were observed, while modality-specific analysis highlighted distinct pathways for aerobic and resistance exercise, contrasting with muscle disuse patterns. Finally, we created a webtool, OMAx, featuring our individual omics and integration analysis. These findings provide …

Hegemonic Entrepreneurial Masculinities In Patriarchal Contexts: Exploring Men's Entrepreneurship In War-Torn Territories, Doaa Althalathini, Theodore A. Khoury, Nick Rumens

Business Faculty Publications and Presentations

This article examines how the war-torn context in Iraq has affected men’s entrepreneurship and entrepreneurial masculinities. Drawing on the entrepreneurship masculinities literature, Connell’s notion of hegemonic masculinity and in-depth interviews with 21 Iraqi men entrepreneurs, this article demonstrates the complex interplay between entrepreneurship, masculinity and patriarchal dynamics in the context of wars and economic instability in Iraq. Study findings show how Iraqi men often turn to entrepreneurship out of necessity to meet patriarchal expectations of them as primary providers for their families. We contribute to the literature on entrepreneurship, men and masculinities by demonstrating how entrepreneurship not only serves as …

Modeling Reemergence Of Vaccine-Eliminated Infectious Diseases Under Declining Vaccination In The Us, Mathew V Kiang, Kate M Bubar, Yvonne Maldonado, Peter J Hotez, Nathan C Lo

Faculty, Staff and Students Publications

Importance: Widespread childhood vaccination has eliminated many infectious diseases in the US. However, vaccination rates are declining, and there are ongoing policy debates to reduce the childhood vaccine schedule, which may risk reemergence of previously eliminated infectious diseases.

Objective: To estimate the number of cases and complications in the US under scenarios of declining childhood vaccination for measles, rubella, poliomyelitis, and diphtheria.

Design, setting, and participants: A simulation model was used to assess the importation and dynamic spread of vaccine-preventable infectious diseases across 50 US states and the District of Columbia. The model was parameterized with data on area-specific estimates …

Trends In The Incidence Of Ovarian Cancer Among Premenopausal And Postmenopausal Women In The United States, 2001 To 2021, Victor Adekanmbi, Abbey B Berenson, Batul Shakir, Christine D Hsu, Thao N Hoang, Itunu O Sokale, Tolulope T Sajobi, Fangjian Guo

Faculty, Staff and Students Publications

Background: Ovarian cancer remains the deadliest and leading cause of gynecological cancer-associated mortality in the US. The aim of this study was to characterize the trends in the incidence of ovarian cancer between premenopausal and postmenopausal women to inform future targeted interventions.

Methods: This population-based cross-sectional study analyzed data from the US Cancer Statistics (USCS) database, which covered the whole of the US population between 2001 and 2021. Joinpoint regression was used to compute the average annual percentage change (APC) with 95% confidence interval (CI) and age-standardized incidence rates per 1,000,000 population.

Results: The results showed that the IR of …

Accounting For Stillbirths In Maternal Health Metrics: A Cross-Country Analysis Research In Context, Ursula Gazeley, Hallie Eilerts-Spinelli, Joshua Wilde, Hannah Blencowe, Li Liu, Wendy Graham, Veronique Filippi

Publications, Reports and Presentations

Background: Live birth is only one of four potential pregnancy outcomes, alongside stillbirth, miscarriage, and induced abortion. While morbidity and mortality associated with all pregnancy outcomes are included in the numerator of many maternal metrics, often only live births are included in the denominator. This inconsistency makes interpreting trends challenging and may exacerbate the deprioritisation of monitoring other pregnancy outcomes. We assess the effect of using (1) total births (live births and stillbirths) or (2) total pregnancies (total births plus miscarriages/induced abortions) as the denominator on estimates of maternal and pregnancy-related mortality ratios (MMR and PRMR). Methods: Using data from …

Religious Identity, Linked Fate, And Political Ideology: Explaining Civil Rights Philanthropy Among Muslim And Jewish Americans, Rafeel Wasif, Afshan Paarlberg, Shariq Siddiqui, David King

Public Administration Faculty Publications and Presentations

Social identity theory predicts that individuals prefer to give to people with the same identity as themselves. However, individuals have multiple identities that interact simultaneously. For instance, religion is an essential identity for many individuals, particularly those from racialized minority groups, such as Muslims and Jews, who are often discriminated against due to these identities. Moreover, individuals like to support faith-based causes. However, they may also feel that they have a linked fate identity, where they perceive a commonality with other persecuted minorities due to similar experiences of discrimination. Moreover, political ideology is another vital identity marker for many individuals. …

Cholesterol Metabolism Regulated By Camkk2-Creb Signaling Promotes Castration-Resistant Prostate Cancer, Chenchu Lin, Thomas L Pulliam, Jenny J Han, Jiaqian Xu, Carlos Vera Recio, Sandi R Wilkenfeld, Yan Shi, Manoj Kushwaha, Sarah Bench, Eduardo Ruiz, Sanjanaa Senthilkumar, Jayasurya Dileep, Peter D A Shepherd, Nora M Navone, Albert R Klekers, Elizabeth M Whitley, Michael M Ittmann, Livia S Eberlin, Wenyi Wang, Daniel E Frigo

Faculty, Staff and Student Publications

Castration-resistant prostate cancer (CRPC) remains an incurable disease in need of improved treatments. CAMKK2 is an emerging therapeutic target whose oncogenic effects in prostate cancer have, to date, been largely attributed to its activation of AMP-activated protein kinase (AMPK). Here, we demonstrate that CAMKK2 promotes prostate cancer growth through an alternative downstream pathway involving CAMKI and CREB. Unbiased transcriptomics identify CREB-mediated transcription as a CAMKK2-regulated process, findings that we validate using diverse molecular, genetic, and pharmacological approaches in vitro and in vivo. CAMKK2 promotes CREB phosphorylation/activation through CAMKIα independently of AMPK, CAMKIV, or other CAMKI isoforms. Functionally, the CREB family …

Metabolic Control Of Glycosylation Forms For Establishing Glycan-Dependent Protein Interaction Networks, Xingyu Liu, Li Yi, Zongtao Lin, Siyu Chen, Shunyang Wang, Ying Sheng, Carlito B Lebrilla, Benjamin A Garcia, Yixuan Xie

2020-Current year OA Pubs

Protein-protein interactions (PPIs) are crucial for comprehending the molecular mechanisms and signaling pathways underlying diverse biological processes and disease progression. However, investigating PPIs involving membrane proteins is challenging due to the complexity and heterogeneity of glycosylation. To tackle this challenge, we developed an approach termed glycan-dependent affinity purification coupled with mass spectrometry (GAP-MS), specifically designed to characterize changes in glycoprotein PPIs under varying glycosylation conditions. GAP-MS integrates metabolic control of glycan profiles in cultured cells using small molecules referred to as glycan modifiers with affinity purification followed by mass spectrometry analysis (AP-MS). Here, GAP-MS was applied to characterize and compare …

Apolipoprotein M Attenuates Age-Related Macular Degeneration Phenotypes Via Sphingosine-1-Phosphate Signaling And Lysosomal Lipid Catabolism, Tae Jun Lee, Andrea Santeford, Kristen M Pitts, Carla Valenzuela Ripoll, Ryo Terao, Zhen Guo, Mualla Ozcan, Dagmar Kratky, Christina Christoffersen, Ali Javaheri, Rajendra S Apte

2020-Current year OA Pubs

Age-related macular degeneration (AMD) is a leading cause of blindness in people over 50. AMD and cardiovascular disease share risk factors including age, impaired lipid metabolism, and extracellular lipid deposition. Because of its importance in age-related diseases, we hypothesize that apolipoprotein M (ApoM), a lipocalin that binds sphingosine-1-phosphate (S1P), might restore lipid homeostasis and retinal function in AMD. In support, we find that human patients with AMD demonstrate significantly reduced ApoM compared to controls. In mice with impaired retinal cholesterol efflux, ApoM improves retinal pigment epithelium (RPE) function and lipotoxicity in an S1P- and S1P receptor 3-dependent manner. Ultrastructural evidence …

A Road Map For Uniform, Comprehensive Long-Term Follow-Up After Curative Therapy For Sickle Cell Disease, Shalini Shenoy, Julie Kanter, Adetola Kassim, Courtney Fitzhugh, Elizabeth Stenger, Monica Bhatia, Lydia Pecker, Lakshmanan Krishnamurti, Allison A King

2020-Current year OA Pubs

An increasing number of allogeneic transplant and autologous gene modification transplant therapies seek to eradicate sickle hemoglobin and the consequent hemolysis, vasculopathy, functional compromise, morbidity, and mortality. Because these modalities are used in parallel, it is important to be able to define the spectrum and stability of correction, long-term effects, and the pros and cons of each modality. A comparison between interventions that will be sought by providers and patients undergoing intervention requires uniform assessments that evaluate disease- and intervention-related effects for informed decision-making. This expert summary outlines a pathway to functional evaluations with timing recommendations, provides broad management guidelines, …

Tune-Able, Piezoelectric Acoustic Source, Baker Hughes Company

Defensive Publications Series

Piezo-electric devices are widely used, in static as well as dynamic applications. This invention disclosure is concerned with dynamic applications, that involve the use of a piezo stack. A piezo stack is an electro-mechanical device that converts electrical in mechanical energy or vice versa. It is characterized by one or more resonance frequencies that depend on the physical properties of the piezo stack. However, these properties depend on how the piezo stack is configured exactly. Since this configuration can be changed ‘on the fly’ (i.e., during operation), we can use one single piezo stack to operate at different resonance frequencies. …

Proactive Personal Safety Systems Using Artificial Intelligence, Sumukh Ashok Shevde, Kamran Mustafa, Abhijit Adsule

Defensive Publications Series

This document describes techniques that enable a mobile computing device (e.g., a smartphone, smart watch, wearable device, augmented reality glasses, vehicle infotainment system, etc.) to generate context data (e.g., location data, movement patterns, audio data, biometrics, traffic hazards, recent crimes, etc.) for use by a proactive personal safety system. The proactive personal safety system may include an intelligent software agent (e.g., artificial intelligence (AI), machine learning model, etc.) hosted locally on the mobile computing device, on a companion device (e.g., tethered smartphone), on a cloud server, etc. The mobile computing device may continuously monitor diverse environmental factors and user behavior …

Thermochemical Conversion Of Oily Sludge, Composition, Hazards, And Treatment Strategies: An Overview, Mahmod A. Abdulqader

AUIQ Complementary Biological System

Oily sludge (OS) is considered one of the most complex by-products produced in the petroleum industry as an unwanted. This work aims to provide a comprehensive review focused on the dangers of stockpiled OS, its sources and contents, as well as its complex composition. This study also analyzes the global annual generation and stockpiling quantities of OS. Therefore, the thermochemical conversion, hydrothermal carbonization (HTC) char produced via HTC called hydrochar, pyrolysis (PY) char produced via PY named pyro-char, and microwave (MW) processes, while the char produced MW labeled micro-char. In conclusion, this study will facilitate researchers and provide a clear …

University As A Platform: Systems And Platform Thinking For Business Model Innovation And Ai Transformation In Higher Education, Evangelos Katsamakas, Oleg V. Pavlov

Northeast Journal of Complex Systems (NEJCS)

Higher education institutions (HEIs), such as colleges and universities, face many challenges and competitive pressures and must innovate. How can ideas from complexity and a systems approach help a HEI understand how it creates value and potentially drive business model innovation? This article provides a university-as-a-platform (UaaP) framework that integrates platform thinking and systems thinking to help HEIs think about value creation, innovation, and the design of new business models. Platform thinking is used to provide a platform conceptualization of the university and define the framework's main elements. A HEI creates value by facilitating the participation and value-creating interactions of …

Agent-Based Modeling To Stress Test New York State Healthcare Robustness, Brandon Bedenbedner

Northeast Journal of Complex Systems (NEJCS)

This study presents an agent-based model (ABM) to assess the resilience of New York State’s healthcare system during public health crises. The model simulates patient interactions, disease spread, and resource allocation, identifying critical vulnerabilities and evaluating strategies to avoid system collapse. Simulation results indicate that with just 10\% of the population infected, hospitals statewide can reach full capacity within ten days, causing significant care delays and an estimated 32,104 deaths within a 30-day period.

Sensitivity analysis revealed infection rates, base mortality, and travel-related delays as primary drivers of system outcomes. These findings highlight the critical need for expanded surge capacity, …