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2026

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Leader-Follower Formation-Based Leader Velocities Estimation Via Adaptive-Τ Tustin Differentiator, Zeyad A. Karam, Mohammed Y. Hassan, Amjad J. Humaidi Oct 2026

Leader-Follower Formation-Based Leader Velocities Estimation Via Adaptive-Τ Tustin Differentiator, Zeyad A. Karam, Mohammed Y. Hassan, Amjad J. Humaidi

Iraqi Journal of Computers, Communications, Control and Systems Engineering

This work develops a leader–follower formation for differential-drive mobile robots with an explicit estimator for the leader's velocities. Firstly, a leader robot position-variance-adaptive, under-rate-limited differentiator provides forward speed and yaw-rate estimate for the leader velocities, using exponentially weighted increment variances that drive a convex one-sided mapping to provide adaptive time constants for this estimator. Secondly, the control stack couples three layers: first layer, a nonlinear body-frame kinematic law for leader tracking, with orientation corrections handled via a smooth bounded function sin(eθ)/eθ to eliminate singularities near zero error. Second layer, a formation-preserving follower controller based on …

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Adaptive Intelligent H-Infinity Controller Design For Mimo Nonlinear Systems Under Asymmetric Input Saturation, Mohammed Qasim, Hazem I. Ali, Omar Farouq Lutfy Oct 2026

Adaptive Intelligent H-Infinity Controller Design For Mimo Nonlinear Systems Under Asymmetric Input Saturation, Mohammed Qasim, Hazem I. Ali, Omar Farouq Lutfy

Iraqi Journal of Computers, Communications, Control and Systems Engineering

This paper details the design of a robust adaptive intelligent guaranteed cost H-infinity controller, tailored for MIMO nonlinear systems subject to external disturbances, parametric uncertainties, and asymmetric input saturation constraints. The adaptive intelligent part of the proposed controller consists of a Radial Basis Function Neural Network (RBFNN) with bounded output to respect saturation constraints and a robust adaptive law for RBFNN weights estimation. This part serves to estimate the system's uncertain nonlinearities and external disturbances. The guaranteed cost H-infinity is designed based on Linear Matrix Inequalities (LMIs) to address the system parameter uncertainties and bounded RBFNN estimation errors, as well …

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Enhancing Gru With Long-Short Attention: A Case Study Of Saudi Stock Market Prediction, Hussein Samma, Qusay Shihab Hamad, Ali Salem Bin Sama, Adnan Bakather, Khaled Alhashash Oct 2026

Enhancing Gru With Long-Short Attention: A Case Study Of Saudi Stock Market Prediction, Hussein Samma, Qusay Shihab Hamad, Ali Salem Bin Sama, Adnan Bakather, Khaled Alhashash

Iraqi Journal of Computers, Communications, Control and Systems Engineering

Predicting stock market movements accurately is a challenging task due to the inherent complexity and volatility of financial markets. In recent years, deep learning techniques, particularly the Gated Recurrent Unit (GRU), have shown promising results in financial time series prediction. However, capturing the most relevant information from large volumes of data remains a critical challenge for improving prediction accuracy. This work introduces an attention-enhanced GRU model for forecasting the Saudi stock market. The proposed model integrates attention mechanisms to dynamically prioritize different input patterns, enabling the network to focus on the most relevant information for prediction. Two types of attention …

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Generative Artificial Intelligence-Driven Augmentation With Deep Feature Fusion Model For Rare Disease Detection And Classification, V. Kavitha Oct 2026

Generative Artificial Intelligence-Driven Augmentation With Deep Feature Fusion Model For Rare Disease Detection And Classification, V. Kavitha

Iraqi Journal of Computers, Communications, Control and Systems Engineering

Rare disease detection focuses on identifying rare health conditions that affect a tiny fraction of people. Detection is challenging because symptoms are often ambiguous and information is limited. In recent years, retinal diseases have become a serious problem worldwide. Progressing a computer-assisted diagnosis (CAD) method is highly beneficial and functional for ophthalmologists. Proper detection and treatment can save eye vision. Deep learning (DL) has advanced across various scientific fields and is leveraged for numerous healthcare tasks. This research presents a Generative Artificial Intelligence-Assisted Adaptive Feature Fusion Network for Rare Retinal Disease Detection (GAIAFF-RRDD) technique assists ophthalmologists by allowing early and …

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Glycemia Regulation In Type 1 Diabetes Using Artificial Pancreas Systems: One Decade Review Of Positive Control Approaches, Luay Thamir Rasheed, Ahmed Sabah Al-Araji, Taghreed Mohammadridha Oct 2026

Glycemia Regulation In Type 1 Diabetes Using Artificial Pancreas Systems: One Decade Review Of Positive Control Approaches, Luay Thamir Rasheed, Ahmed Sabah Al-Araji, Taghreed Mohammadridha

Iraqi Journal of Computers, Communications, Control and Systems Engineering

An artificial pancreas (AP) is a biomedical device that mimics the natural glucose-regulation process carried out by a healthy pancreas. This device consists of three parts: a continuous glucose monitor (CGM), a control algorithm, and an insulin pump. These three parts work together by continuously monitoring blood glucose concentration (BGC) and adjusting insulin delivery to maintain normoglycemia while minimizing the occurrence of hypoglycemia and hyperglycemia. While several review studies have addressed control strategies for AP systems, limited attention has been given to the fundamental positivity constraint of insulin delivery and its systematic impact on controller design and performance. This paper …

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Power-Efficient Target Tracking And Coverage In Under-Provisioned Wireless Visual Sensor Networks, Muna M. Jawad Oct 2026

Power-Efficient Target Tracking And Coverage In Under-Provisioned Wireless Visual Sensor Networks, Muna M. Jawad

Iraqi Journal of Computers, Communications, Control and Systems Engineering

Due to their ability to detect the physical environment, directional sensors have attracted a lot of attention in wireless visual sensor networks (WVSN). These sensors perform two key functions: communication and sensing. A WVSN comprises numerous configurable limited fields of view sensors, comprising distinct angular sectors, arranged with multiple targets randomly scattered in the same surrounding region. Therefore, there is a critical need to improve the network's lifetime and reduce power demand while providing complete target coverage. This paper looks at under-resourced visual networks with an inadequate number of sensors to match applications' needs and develops a viable model to …

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Improving Performance For Dco-Ofdm Based Vlc Via Convolutional Coding And Viterbi Decoding, Maha F. Shatti, Samir M. Hameed, Atheer A. Sabri Oct 2026

Improving Performance For Dco-Ofdm Based Vlc Via Convolutional Coding And Viterbi Decoding, Maha F. Shatti, Samir M. Hameed, Atheer A. Sabri

Iraqi Journal of Computers, Communications, Control and Systems Engineering

The reliability of Visible Light Communication (VLC) is affected by several parameters, the most significant being high peak-to-average power ratio(PAPR) and nonlinear distortion. This study presents an adaptive direct current O-OFDM (DCO-OFDM) based VLC system as a solution, which integrates error correction the Convolutional coding and Viterbi decoding (by hard and soft decision methods) with a PAPR reduction technique that combines Vandermonde-like Matrix (VLM) precoding with a nonlinear companding transform (NCT). This proposed system enhances resistance to channel impairments, thereby reducing BER while maintaining the gains of PAPR reduction. Moreover, examined the system under realistic VLC propagation conditions both Line …

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A Triple-Verification Framework For Swift, Real-Time Detection Of Anomalous Sensor Readings In Large-Scale Iot Systems, Taha E. Al-Jarakh, Inas Jawad Kadhim, Ayad Al-Dujaili, Eduardo Campos Mercado Oct 2026

A Triple-Verification Framework For Swift, Real-Time Detection Of Anomalous Sensor Readings In Large-Scale Iot Systems, Taha E. Al-Jarakh, Inas Jawad Kadhim, Ayad Al-Dujaili, Eduardo Campos Mercado

Iraqi Journal of Computers, Communications, Control and Systems Engineering

Due to the massive expansion of Internet of Things systems and the variety of anomalous data resulting from faulty sensors, cyberattacks, or communication failures, it has become difficult to handle this type of data. Although current machine learning and statistical analysis techniques offer high accuracy in detecting anomalies, these methods alone are not sufficient for handling massive amounts of data in real-time. Therefore, the idea arose to propose a Triple-Verification Framework to detect and block anomalous data. The first stage of the framework acts as a firewall to block incoming messages from blocklisted/unauthorized sensors or carrying unknown schemes. In the …

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Energy-Efficient Resource Allocation In Cloud Service Management Via Significant Feature Ranking With Recurrent Network Model, C. Arun, S. Santhoshkumar, J. Jegathesh Amalraj, T. Suresh Oct 2026

Energy-Efficient Resource Allocation In Cloud Service Management Via Significant Feature Ranking With Recurrent Network Model, C. Arun, S. Santhoshkumar, J. Jegathesh Amalraj, T. Suresh

Iraqi Journal of Computers, Communications, Control and Systems Engineering

The increasing adoption of cloud computing (CC) produces a notable growth in data centres, resulting in severe financial, environmental, and operational problems. To mitigate these issues, energy-efficient resource allocation strategies have been developed as a key solution for enhancing energy utilization while ensuring high performance and reliability. In this framework, machine learning (ML) enables the implementation of dynamic and intelligent approaches for effective resource utilization. In this paper, we focus on the Scalable Hybrid Feature Ranking Framework for Energy-Efficient Resource Allocation (SHFRF-EERA) approach in Cloud Service Management Systems. The novelty of the proposed model lies in the integration of hybrid …

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A Corpus Linguistics-Driven Hybrid Deep Representation Framework Incorporating Majority Voting For Enhanced Automatic Spoken Language Identification, Lubin Balasubramanian, J. Uthayakumar, Niranjana Kumara M, Sariga Arjunan Oct 2026

A Corpus Linguistics-Driven Hybrid Deep Representation Framework Incorporating Majority Voting For Enhanced Automatic Spoken Language Identification, Lubin Balasubramanian, J. Uthayakumar, Niranjana Kumara M, Sariga Arjunan

Iraqi Journal of Computers, Communications, Control and Systems Engineering

Spoken Language Identification (SLID) is a well-researched area. It has previously been recognized as a crucial first stage in every multi-lingual speech recognition system. Latest developments in artificial intelligence (AI) and deep learning (DL) are used to highly strengthen the performance of SLID systems, allowing them to perform a crucial part in mainstream applications The gathered speaker utterances have been entered into the DL network for training phase. The language equivalent to the great posterior probability is then recognized as the target language. This study introduces an Enhancing Automatic Spoken Language Identification with Corpus Linguistics and Ensemble Deep Representation (EASLI-CLEDR) …

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Learning Opportunities 2026/2027, Illinois Math And Science Academy Oct 2026

Learning Opportunities 2026/2027, Illinois Math And Science Academy

Course Catalogs

The graduation requirements of the Illinois Mathematics and Science Academy are established by the IMSA Board of Trustees. Each semester, students must take a minimum of five academic courses (2.5 credits) for a letter grade (not Pass/Fail), not including Fine Arts or Wellness courses. Students may enroll in a maximum of eight academic opportunities each semester, including academic courses, Fine Arts and Wellness courses, and Experiential programs. The College and Academic Counselor approves enrollment for students in all courses and experiences.

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Exploring The Significance Of Kenya's Indigenous And Emerging Blue Foods For Sustainable Aquaculture Development. A Review, Jonathan Munguti, Mavindu Muthoka, Domitila Kyule, Esther Magondu, Kevin Obiero, Jimmy Mboya, Menaga Meenakshisundaram, Tanga M. Chrysantus, Gerald Kwikiriza, Francis K. Njonge Oct 2026

Exploring The Significance Of Kenya's Indigenous And Emerging Blue Foods For Sustainable Aquaculture Development. A Review, Jonathan Munguti, Mavindu Muthoka, Domitila Kyule, Esther Magondu, Kevin Obiero, Jimmy Mboya, Menaga Meenakshisundaram, Tanga M. Chrysantus, Gerald Kwikiriza, Francis K. Njonge

All Peer-Reviewed Publications

Kenya's aquaculture sector is at a pivotal stage, transitioning from a historical reliance on Nile tilapia and African catfish toward a more diversified production portfolio that integrates indigenous and emerging freshwater and marine species. This shift is increasingly recognized as essential to enhance climate resilience, food security, and ecosystem health. This systematic review synthesizes more than two decades (2000 to 31st January, 2026) of peer-reviewed literature to evaluate the biological suitability, culture performance, and socio-ecological roles of underutilized native taxa, including Ningu (Labeo victorianus), Jipe tilapia (Oreochromis jipe), freshwater prawns (Macrobrachium spp.), rabbitfish (Siganus sutor), marine-acclimatized Nile tilapia, mud crab …

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Check Out The Library, 2026 Fall Issue, Cal Poly Humboldt Library Oct 2026

Check Out The Library, 2026 Fall Issue, Cal Poly Humboldt Library

Library Publications

Issue 21

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Revisiting Her2-Negative Breast Cancer In The Era Of Her2-Low And Her2-Ultralow Expression: Assessment Of Interobserver Variability, Xiao Huang, Sarah Anderson, Valeria Dal Zotto, Shuko Harada, Andrea G. Kahn, Meiling Zhou, Kui Zhang, Kanako Okamoto, Shi Wei Oct 2026

Revisiting Her2-Negative Breast Cancer In The Era Of Her2-Low And Her2-Ultralow Expression: Assessment Of Interobserver Variability, Xiao Huang, Sarah Anderson, Valeria Dal Zotto, Shuko Harada, Andrea G. Kahn, Meiling Zhou, Kui Zhang, Kanako Okamoto, Shi Wei

Michigan Tech Publications

BACKGROUND: HER2-low and HER2-ultralow expressions have recently emerged as actionable targets in breast cancer (BC). However, data remain limited regarding the consistency of immunohistochemistry (IHC) scoring when both categories are considered. This study aimed to evaluate interobserver variability in assessing HER2-negative BC, with particular focus on the reproducibility of HER2-low and -ultralow classifications. METHODS: A total of 389 consecutive HER2-negative BC cases were re-evaluated by six pathologists with varying experience (1-20 years). The panel included dedicated breast pathologists, general pathologists routinely covering breast services, and a surgical pathology fellow in training. HER2 expression was categorized as HER2-null (no staining), -ultralow, …

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From Homes To Classrooms: Cultural Wisdom As A Guide For Stem Lesson Planning, Miriam Ortiz, Uma Ganesan, Angela Chapman, William Medina-Jerez, Ruby Lynch Arroyo, Mourat Tchoshanov Oct 2026

From Homes To Classrooms: Cultural Wisdom As A Guide For Stem Lesson Planning, Miriam Ortiz, Uma Ganesan, Angela Chapman, William Medina-Jerez, Ruby Lynch Arroyo, Mourat Tchoshanov

Teaching and Learning Faculty Publications

This article describes innovative elementary science instructional approaches based on cultural wisdom developed by preservice teachers enrolled in a teacher preparation program at a university in the U.S.-Mexico border region. As a part of a larger study, three Latina preservice elementary teachers were a part of a teacher residency in conducting community interviews and reflection activities to uncover cultural backgrounds that could inform culturally relevant STEM lesson planning, centering on family and home knowledge. This project began with family interviews during winter break and culminated in lesson planning and implementation during their science methods course in the spring semester. The …

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First Evaluation Of Contrast-Enhanced Micro-Xct As A Tool For Organismal And Reproductive Trait Observations In Corals Based On Scans Of Thesea Nivea Deichmann, 1936, Erin E. Easton Oct 2026

First Evaluation Of Contrast-Enhanced Micro-Xct As A Tool For Organismal And Reproductive Trait Observations In Corals Based On Scans Of Thesea Nivea Deichmann, 1936, Erin E. Easton

School of Earth, Environmental, & Marine Sciences Faculty Publications

Micro-X-ray computed tomography (micro-XCT) with contrast enhancement is considered a non-destructive tool that is increasingly being applied to explore the internal and external structures of vertebrates and invertebrates. Although micro-XCT has been applied to corals to study skeletal features, contrast enhancement has not been applied to evaluate the utility for visualization of soft tissue structures in corals. This study is the first to evaluate the utility of contrast enhancement to visualize internal and external features, including soft tissue features, of octocorals. Contrast staining of a Thesea nivea specimen with 2.5% Lugol's iodine permitted visualization of soft tissues with sufficient density …

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Ai Student Survey 2026 Oct 2026

Ai Student Survey 2026

AI Survey Datasets

Student survey conducted by the University of Memphis AI Pedagogy Taskforce on generative AI.

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Ai Pedagogy Faculty Survey 2025 Prelim Data Results Oct 2026

Ai Pedagogy Faculty Survey 2025 Prelim Data Results

AI Survey Datasets

Faculty survey on AI knowledge and usage conducted in 2025 by University of Memphis AI Pedagogy Taskforce.

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Sociological Theory Meets Generative Ai: A Pedagogical Guide, Kimberly Murray Oct 2026

Sociological Theory Meets Generative Ai: A Pedagogical Guide, Kimberly Murray

The Journal of Public and Professional Sociology

This paper considers the relationship between sociology and generative AI (GenAI) as a phenomenon that may be studied using common sociological concepts and theories, including the Sociological Imagination, Structural Functionalism, Conflict Theory, and Symbolic Interactionism, which are considered foundational to the discipline of sociology. Within each section are contemporary examples of GenAI and how they connect to sociology. This paper benefits a wide audience, as students, faculty, and those who use these theories and concepts in practice settings may adopt them within a variety of contexts, including the classroom, a scholarly presentation, a workshop, or a training opportunity. Sources include …

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Mutation-Based Multi-Agent Test Case Update, Dawei Tian, Jiakun Liu, Yun Peng, Yichen Zhang, Jianlei Chi, Jun Sun, Xiaohong Su Oct 2026

Mutation-Based Multi-Agent Test Case Update, Dawei Tian, Jiakun Liu, Yun Peng, Yichen Zhang, Jianlei Chi, Jun Sun, Xiaohong Su

Research Collection School Of Computing and Information Systems

Modern software systems evolve rapidly under CI/CD practices, where tests are critical for quality. However, substantial code changes often render existing test cases obsolete, causing pipeline disruptions, reduced productivity, and compromised quality. Recent automatic test update approaches leverage LLMs to refine test cases via execution feedback and exact-matching context retrieval, prioritizing executability and line coverage but suffering three limitations: (1) neglecting test assertion adequacy, weakening fault detection; (2) relying on coarse line coverage instead of specific uncovered lines/branches; (3) using exact-matching retrieval, which fails for LLM hallucinated queries. To address these, we propose MuMuTestUp, a mutation-guided multi-agent framework with three …

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Ddor: Delta Debugging For Explainable Overrefusal Testing And Repair, Qinyan Zhou, Peixin Zhang, Jun Sun, Haonan Zhang, Dongxia Wang Oct 2026

Ddor: Delta Debugging For Explainable Overrefusal Testing And Repair, Qinyan Zhou, Peixin Zhang, Jun Sun, Haonan Zhang, Dongxia Wang

Research Collection School Of Computing and Information Systems

While safety alignment and guardrails help large language models (LLMs) avoid harmful outputs, they can also induce overrefusal, i.e., unwarranted rejection of benign queries that merely appear risky. We present DDOR (Delta Debugging for OverRefusal), a fully automated and explainable framework for overrefusal testing and repair in a black-box setting, where only model inputs and outputs are accessible and internal safety mechanisms remain opaque. DDOR applies delta debugging to localize minimal refusal-triggering fragments (mRTFs) that provide phrase-level, explainable evidence for why a refusal occurs. Conditioned on these mRTFs, DDOR generates diverse, context-rich prompts and performs multi-oracle validation to filter intrinsically …

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¡Somos Más! The Latino Vote And The Strength Of Democracy In Massachusetts, Phillip Granberry, Rafael M. Pérez Medina, Carlos Muñoz-Cadilla, Fabián Torres-Ardila, Karla Corres Oct 2026

¡Somos Más! The Latino Vote And The Strength Of Democracy In Massachusetts, Phillip Granberry, Rafael M. Pérez Medina, Carlos Muñoz-Cadilla, Fabián Torres-Ardila, Karla Corres

Gastón Institute Publications

This report identifies important characteristics of Latinos, including their age, citizenship, registration, and turnout. Because data on Latino voters in Massachusetts are limited, the report highlights opportunities for future qualitative research to understand Latino voters' motivations. The first of several reports on this research will soon follow, examining the ecosystem of Latino-serving civic organizations and the grassroots efforts that support Latino voter turnout.

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Size-Tunable Tellurium Quantum Dots By Glancing Angle Deposition, S. M. Sayem, Salim Hussain, Fernando Maia De Oliveira, Ranjitha Kumarapuram Hariharalakshmanan, Gregory Guisbiers, Tansel Karabacak Oct 2026

Size-Tunable Tellurium Quantum Dots By Glancing Angle Deposition, S. M. Sayem, Salim Hussain, Fernando Maia De Oliveira, Ranjitha Kumarapuram Hariharalakshmanan, Gregory Guisbiers, Tansel Karabacak

Faculty Scholarship

Tellurium has a unique helical crystal arrangement and pronounced anisotropy that influence its electronic and optical properties at the nanoscale. This study reports the synthesis of pure tellurium quantum dots (Te QDs) on silicon wafer using glancing angle deposition (GLAD). Quasi-hemispherical dots with lateral sizes ranging from 9 to 28 nm and vertical dimensions of 6 to 10 nm were produced as a function of the deposition duration. A comparison of the dot sizes with the Bohr radii of the charge carriers indicated a regime of strong to intermediate confinement. Structural analyses confirmed the polycrystalline nature and trigonal phase of …

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Quantum Mechanics, Non-Locality, And The Space Discreteness Hypothesis, Wilson A. Zuniga-Galindo Oct 2026

Quantum Mechanics, Non-Locality, And The Space Discreteness Hypothesis, Wilson A. Zuniga-Galindo

School of Mathematical & Statistical Sciences Faculty Publications

The space discreteness hypothesis asserts that the nature of space at short distances is radically different from that at large distances. Based on the Bronstein inequality, here, we use a totally disconnected topological space X as a model for the physical space at short distances. However, we consider the time as a real variable. In this framework, the Dirac–von Neumann formalism can be used. This discreteness hypothesis implies that given two different points in space, there is no continuous curve (a world line) joining them. Consequently, this hypothesis is not compatible with the theory of relativity. We propose R×(R×X)3 as …

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State: The Magazine Of Illinois State University, Fall 2026, Illinois State University, University Marketing And Communications Oct 2026

State: The Magazine Of Illinois State University, Fall 2026, Illinois State University, University Marketing And Communications

State: The Magazine of Illinois State University (1999-present)

Illinois State University alumni magazine

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Study Of A Nonlinear Delayed Parabolic Model For Prion Disease Dynamics With The Unfolded Protein Response, Gangadhara Boregowda, Laurent Pujo-Menjouet, Zhaosheng Feng, Michael R. Lindstrom Oct 2026

Study Of A Nonlinear Delayed Parabolic Model For Prion Disease Dynamics With The Unfolded Protein Response, Gangadhara Boregowda, Laurent Pujo-Menjouet, Zhaosheng Feng, Michael R. Lindstrom

School of Mathematical & Statistical Sciences Faculty Publications

Prion diseases are neurodegenerative disorders characterized by the dynamic spread of misfolded toxic proteins in the brain. In this process, the normal cellular prion protein (PrPC) produced by neurons misfolds into a toxic form known as scrapie prion protein (PrPSc). These misfolded proteins propagate through the brain by converting healthy prions into their toxic form. This biological mechanism can be modeled by a system of nonlinear parabolic partial differential equations, accompanied by a nonlinear delayed integral boundary condition. Our primary objective is to establish the existence of nonnegative classical solutions to this system. Furthermore, we derive a priori estimates for …

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Adolescent Health Across Asia Pacific, 2000–23: A Systematic Analysis For The Global Burden Of Disease Study 2023, Gbd 2023 Asia Pacific Adolescent Health Collaborators, Karly I. Cini, Dorothea Dumuid, Iffat Abbsar, Luo Li, Diandra Amandita Priambodo, Bhoomadevi A, Muhammad Ahmed Abdullah, Abdullah, Richard Gyan Aboagye, Swetha Acharya, Isaac Yeboah Addo, Nurudeen A. Adegoke, Ripon Kumar Adhikary, Usha Adiga, Mohd Adnan, Qorinah Estiningtyas Sakilah Adnani, Obed Adonteng-Kissi, Ebenezer Afrifa-Yamoah, Fransisca Handy Agung, Aqeel Ahmad, Khabir Ahmad, Naved Ahmad, Tauseef Ahmad, Jahanzaib Mian Ahmed, Mushood Ahmed, Shahzaib Ahmed, Kasuni H.M. Akalanka, Muhammad Nadeem Akhtar, Wole Akosile Oct 2026

Adolescent Health Across Asia Pacific, 2000–23: A Systematic Analysis For The Global Burden Of Disease Study 2023, Gbd 2023 Asia Pacific Adolescent Health Collaborators, Karly I. Cini, Dorothea Dumuid, Iffat Abbsar, Luo Li, Diandra Amandita Priambodo, Bhoomadevi A, Muhammad Ahmed Abdullah, Abdullah, Richard Gyan Aboagye, Swetha Acharya, Isaac Yeboah Addo, Nurudeen A. Adegoke, Ripon Kumar Adhikary, Usha Adiga, Mohd Adnan, Qorinah Estiningtyas Sakilah Adnani, Obed Adonteng-Kissi, Ebenezer Afrifa-Yamoah, Fransisca Handy Agung, Aqeel Ahmad, Khabir Ahmad, Naved Ahmad, Tauseef Ahmad, Jahanzaib Mian Ahmed, Mushood Ahmed, Shahzaib Ahmed, Kasuni H.M. Akalanka, Muhammad Nadeem Akhtar, Wole Akosile

Peninsula Medical School

Background: The Asia Pacific region is home to more than half of the world's 1·93 billion adolescents (aged 10–24 years). Addressing adolescent health in this region is of global importance, but to date a systematic analysis of key contributors to disease in adolescents has not been done, which is a barrier to responsive action. This systematic analysis of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2023 aims to provide a comprehensive assessment of adolescent health across the Asia Pacific region, at both the subregional and national levels, encompassing burden of disease, mortality, and prevalence of adolescent …

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Blue Carbon Ecosystems As Climate Solutions: Sequestration Across Coastal And Marine Environments, Allison K. White, Richard J. Kline, Md. Saydur Rahman Oct 2026

Blue Carbon Ecosystems As Climate Solutions: Sequestration Across Coastal And Marine Environments, Allison K. White, Richard J. Kline, Md. Saydur Rahman

School of Earth, Environmental, & Marine Sciences Faculty Publications

Blue carbon ecosystems (BCEs) such as mangroves, salt marshes, and seagrasses, sequester significant amounts of CO2 from the atmosphere. These ecosystems capture and store carbon in biomass and sediments over long periods. Other marine ecosystems, including the open ocean, kelp forests, bivalve reefs, and coral reefs, have been excluded from the BCEs, but they have the potential to serve as crucial blue carbon sinks or to support adjacent BCEs. Climate change, however, poses severe threats to these ecosystems. Rising sea levels, increasing temperatures, and ocean acidification can lead to habitat loss, reduced biodiversity, and impaired carbon sequestration capacity. Consequently, anthropogenic …

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Microwave Spectrum And Iodine Nuclear Quadrupole Coupling Constants Of Difluorodiiodomethane, Cf2i2, Michael J. Carrillo, Michael J. Tubergen, Garry S. Grubbs, S. A. Cooke, Stewart E. Novick Oct 2026

Microwave Spectrum And Iodine Nuclear Quadrupole Coupling Constants Of Difluorodiiodomethane, Cf2i2, Michael J. Carrillo, Michael J. Tubergen, Garry S. Grubbs, S. A. Cooke, Stewart E. Novick

Chemistry Faculty Research & Creative Works

The high-resolution rotational spectrum of difluoro diiodomethane is reported for the first time. A molecular-beam broadband Fourier transform microwave spectrometer recorded the spectrum over the frequency range of 5.9–18.1 GHz. The rotational constants, centrifugal distortion constants, nuclear quadrupole coupling constants, and nuclear spin-rotation constants for the two equivalent iodine nuclei were determined from fitting 1378 hyperfine transitions of 163 rotational transitions: A = 2743.79691(18)MHz, B = 587.83103(5) MHz, C = 528.72470(5) MHz, χaa = −1213.287(6) MHz, χbb – χcc = −885.210(5) MHz, and χab = 1437.721(5) MHz. 31 dipole-forbidden/quadrupole-allowed transitions, arising from the large nuclear quadrupole coupling effect of iodine, …

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Iot-Enabled Smart Durian Harvesting: An Integrated Platform For Real-Time Orchard Monitoring And Sustainable Harvest Management, Norisan Abd Karim, Nur Carmilla Abdullah Muhammad Shafiq, Nur’Aina Daud, Syibrah Naim, Syaheerah Lebai Lutfi Oct 2026

Iot-Enabled Smart Durian Harvesting: An Integrated Platform For Real-Time Orchard Monitoring And Sustainable Harvest Management, Norisan Abd Karim, Nur Carmilla Abdullah Muhammad Shafiq, Nur’Aina Daud, Syibrah Naim, Syaheerah Lebai Lutfi

Malaysian Journal of Computing (MJoC)

Durian harvesting requires timely monitoring to ensure that fallen fruits are collected promptly, thereby reducing quality deterioration and potential economic losses. Traditional orchard monitoring relies heavily on manual inspection, making the process time-consuming, labour-intensive, and inefficient, particularly in large orchards. The Internet of Things (IoT) technology has been widely used in smart agriculture to manage orchards, but there are very few existing systems that combine real-time durian fall detection with a mobile application that sends immediate notifications, automatic image capture of fall events, and orchard management functions. This study develops an Integrated IoT-Based Smart Orchard Platform for real-time durian harvest …

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