Digital Commons Network^™

Artificial Intelligence For The Detection Of Acute Myeloid Leukemia From Microscopic Blood Images; A Systematic Review And Meta-Analysis, Feras Al-Obeidat, Wael Hafez, Asrar Rashid, Mahir Khalil Jallo, Munier Gador, Ivan Cherrez-Ojeda, Daniel (Centro De Investigación De Salud Pública Y Epidemiología Clínica Simancas-Racines, , Universidad Ute, Quito, Ecuador , Universidad Ute, Quito, Ecuador

All Works

Leukemia is the 11th most prevalent type of cancer worldwide, with acute myeloid leukemia (AML) being the most frequent malignant blood malignancy in adults. Microscopic blood tests are the most common methods for identifying leukemia subtypes. An automated optical image-processing system using artificial intelligence (AI) has recently been applied to facilitate clinical decision-making. To evaluate the performance of all AI-based approaches for the detection and diagnosis of acute myeloid leukemia (AML). Medical databases including PubMed, Web of Science, and Scopus were searched until December 2023. We used the “metafor” and “metagen” libraries in R to analyze the different models used …

Re: Approval Letter For The Butte Priority Soils Operable Unit (Bpsou) Draft Residential Metals Abatement Program Investigation Summary Report (Non‐Residential Parcels – Indoor Dust) – Cccs Gym Annex (Dated October 4, 2024), Molly Roby

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Butte Priority Soils Operable Unit (Bpsou) Final Bpsou Insufficiently Reclaimed Sites Belle Of Butte (Bres No. 8 & Ur-39) Remedial Action Work Plan (Rawp) Request For Change Ir- 2024-Ra-01, Mike Mcanulty

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Advanced Machine Learning Techniques For Cardiovascular Disease Risk Prediction, Godfred Ahenkroa Kesse

Data Science and Data Mining

of mortality, necessitating advanced predictive models to aid early detection and prevention. This study explores the application of machine learning techniques, including Lo- gistic Regression, K-Nearest Neighbors (KNN), Random Forest, and XGBoost, to predict CVD risk using a dataset of 69,997 observations encompassing demographic, clinical, and lifestyle factors. Data preprocessing involved one-hot encoding of cat- egorical variables and scaling to ensure compatibility with all models. Model performance was evaluated using metrics such as accuracy, precision, recall, F1-score, and AUC-ROC. Among the models, XGBoost demonstrated the highest accuracy at 74%, leveraging its gradient-boosting framework to effectively handle feature interactions and imbalanced …

Predicting Blood Glucose Levels: A Linear Regression Approach For Non-Invasive Monitoring, Godfred Ahenkroa Kesse

Data Science and Data Mining

Accurate monitoring of blood glucose levels is vital for the management of diabetes, a chronic condition affecting millions worldwide. This study explores a linear regression approach to estimate glucose levels non-invasively using a dataset enriched with demographic, physiological, and sensor-based variables. Following rigorous data preparation, including normalization and encoding, a Box-Cox transformation was applied to address violations of regression assumptions, stabilizing variance and improving model validity. Stepwise selection and hypothesis testing were employed to refne the model, retaining signifcant predictors such as AGE, GENDER, HEARTRATE, and DIABETIC, while excluding variables like NIR Reading and LAST EATEN for their minimal contribution. …

Classification And Evaluation Of Machine Learning Algorithms On The Mnist Dataset, Felix Yeboah

Data Science and Data Mining

This paper discusses the use of machine learning algorithms in classifying the MNIST handwritten dataset. The MNIST dataset consists of 28x28 grayscale handwritten images with 10 classes from 0 to 9. The dataset was normalized by scaling the pixel values to a range between 0 and 1 by dividing each pixel value by 255. We compare and evaluate the K-nearest Neighbor and Naive Bayes algorithm based on performance metrics such as accuracy, error rate, f1-score, and precision. The K-nearest Neighbor algorithm achieved better performance in all the evaluation criteria.

Exhibit 2 “Basement Iswp” 122 W. Daly St. Butte, Mt 59701 January 16, 2025 Database Residential Identifier: R-00845, Butte-Silver Bow Department Of Reclamation And Environmental Services

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Racial Disparities Of Type 2 Diabetes Through Exercise: The Multi-Ethnic Study Of Atherosclerosis, Tong Xia, Roch A. Nianogo, Qingzhao Yu, Tamara Horwich, Preethi Srikanthan, Kosuke Inoue, Matthew Allison, Zuo-Feng Zhang, Karol E. Watson, Liwei Chen

School of Public Health Faculty Publications

Introduction: Persistent racial and ethnic disparities exist for Type 2 diabetes in the U.S. Racial and ethnic minorities have a higher risk of Type 2 diabetes, and studies suggest that they engage in less exercise than White population. This study examined whether and to what degree racial differences in Type 2 diabetes were explained by exercise. Methods: Adults aged 45–84 years without Type 2 diabetes at baseline (2000–2002) were included from the Multi-Ethnic Study of Atherosclerosis cohort and followed through 2020. Associations between race and Type 2 diabetes were examined using multivariable Cox proportional hazard regression. The effects of exercise …

Nrdp Comments On Bp-Atlantic Richfield (Bp-Ar’S) Draft Materials Management Plan And Associated Documents At Butte Priority Soils Operable Unit Of The Silver Bow Creek/Butte Area Superfund Site, Jim Ford

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Meditation In Qualitative Research For Bracketing And Beyond, Katalin Grajzel

Research Methods and Statistics: Graduate Student Scholarship

In this study, I recounted my experience using mantra meditation during a phenomenological study for the purposes of bracketing. The efficacy and purpose of bracketing have been debated from Husserl (1931), whose aimed was to achieve objectivity, to Heidegger (1962) who advocated for immersion of the researcher, through the French school (Merleau-Ponty, 1964) of middle ground, by whom bracketing was seen as the process to unearth and suspend biases for the better understanding of participants’ experiences (Arsel, 2017; Creswell & Creswell, 2017; Creswell & Poth, 2016; Fischer & Guzel, 2023). In this study, however, I propose another approach to bracketing …

Connotation, Research Status, And Development Directions Of Clean Coal Geology In China, Tang Yuegang, Wang Shaoqing, Wang Xiaoshuai, Guo Xin, Wang Yafeng, Xue Liping, Harold H. Schobert

Coal Geology & Exploration

Objective The exploration and assessment of low-carbon, zero-emission, and maximized utilization of coal resources, emerge as a focus of coal geology in the 21st century. [Research Advances] Based on the research content of coals and coal geology, along with the domestic and international development trends of clean coal technology (CCT), this study defines clean coal geology in the broad and narrow sense. Clean coal geology in the narrow sense focuses on the geological and geochemical issues related to efficiency enhancement and emission reduction in coal processing and utilization. In contrast, clean coal geology in the broad sense emphasizes …

A Novel Mu-Metal Based Weak Magnetic Energy Harvester For Self-Powered Monitoring Of Power Grid Assets, Arsalan Habib Khawaja, Hassan Pervaiz, Dongsheng Cai, Jian Li, Qi Huang

Turkish Journal of Electrical Engineering and Computer Sciences

This paper presents a novel magnetic field driven contactless energy harvester with improved flux concentration capabilities for potential utilization in Power system monitoring where stray magnetic field is abundant and readily available. The designed harvester employs multilayered Mu-Metal based cone shaped core to maximize magnetic flux density. To achieve the final design, this work investigates magnetic flux concentration ability of various geometries and material properties in magnetic flux conditions typical to overhead 11 kV power distribution circuits. Impact of layers in core-coil region of harvesting coil on magnetic flux concentration is evaluated by means of Finite Element analysis. Resultantly, the …

Advanced Prediction Of Events And Temporal Expressions In Medical Text Using The Jena Api: Integrating Ontologies And Deep Learning, Hafida Tiaiba, Lyazid Sabri, Okba Kazar

Turkish Journal of Electrical Engineering and Computer Sciences

The automatic recognition of medical concepts and temporal expressions in narrative clinical text enhances the utility of electronic health records (EHRs) and supports clinical decision-making and research. However, challenges arise due to the complexity of medical language, ambiguity of terms, and variability in expression. To address these issues, the use of medical ontologies significantly improves data management in healthcare. A novel approach integrates various medical ontologies covering drugs, symptoms, diseases, anatomy, disease drivers, and food, and with convolutional neural networks (CNNs) -including Standard, Transposed, and Separable convolution models (CONSEPTR)- to extract both medical events (e.g., clinical departments, treatments, problems) and …

Machine Learning Models Approach For The Quantitative Classification Of Ferricyanide Compound Using Electrochemical Detection With Cpe-Fe3o4nps, Süleyman Aşir, Nemah Abu Shama, Najya Maroof Saleem, Devri̇m Kayali, Kami̇l Di̇mi̇li̇ler

Turkish Journal of Electrical Engineering and Computer Sciences

Most common electrochemical analysis techniques used to evaluate enzymes, proteins, and heavy metals over a wide potential range include electrochemical impedance EIS, differential pulse voltammetry DPV, and square wave voltammetry SQWV. Machine leaning algorithms MLA are employed to classify the Potassium ferricyaniyde K3Fe(CN)6 concentrations using a modified carbon paste electrode CPE embedded with iron (II, III) oxide (Fe3O4) NPs. The CV, DPV, and SQWV voltametric data collected from all K3Fe(CN)6 concentrations were used as input data to the machine learning algorithms. Signaling current of K3Fe(CN)6 concentrations improved at Fe3O4 modified with nanoparticles NPs CPE in a comparison with the unmodified …

Local Dynamic Analysis Of The Covid-19 Mathematical Model Based On Discrete-Time Predator-Prey Population Model, Fi̇gen Kangalgi̇l, Ni̇lüfer Topsakal, Özge Kuzucu

Turkish Journal of Mathematics

In this article, the local dynamics of a discrete-time Covid-19 pandemic model based on the Lotka Volterra model with topological classifications, bifurcation analysis and chaos control are investigated. It is shown that under some parametric conditions, the discrete-time Covid-19 pandemic model has two equilibrium points. With linear stability theory, local dynamics are investigated with topological classifications about the equilibrium points of the discrete-time Covid-19 epidemic model. In addition, the existence of a Neimark-Sacker bifurcation at the internal equilibrium point is proved and this bifurcation is analysed using explicit criteria. Furthermore, the chaos in the discrete Covid-19 pandemic model is also …

Improving Rupture Status Prediction For Intracranial Aneurysms Using Wall Shear Stress Informatics, Jingfeng Jiang, Mostafa Rezaeitaleshmahalleh, Jinshan Tang, Joseph Gemmette, Aditya Pandey

Michigan Tech Publications

BACKGROUND: Wall shear stress (WSS) plays a crucial role in the natural history of intracranial aneurysms (IA). However, spatial variations among WSS have rarely been utilized to correlate with IAs' natural history. This study aims to establish the feasibility of using spatial patterns of WSS data to predict IAs' rupture status (i.e., ruptured versus unruptured). METHODS: "Patient-specific" computational fluid dynamics (CFD) simulations were performed for 112 IAs; each IA's rupture status was known from medical records. Recall that CFD-simulated hemodynamics data (wall shear stress and its derivatives) are located on unstructured meshes. Hence, we mapped WSS data from an unstructured …

Associations Between Social Determinants Of Health And Mental Health Disorders Among U.S. Population: A Cross-Sectional Study, S. Tanarsuwongkul

Faculty Publications

Aims

The impact of social determinants of health (SDOH) on mental health is increasingly realized. A comprehensive study examining the associations of SDOH with mental health disorders has yet to be accomplished. This study evaluated the associations between five domains of SDOH and the SDOH summary score and mental health disorders in the United States.

Methods

We analyzed data from a diverse group of participants enrolled in the All of Us research programme, a research programme to gather data from one million people living in the United States, in a cross-sectional design. The primary exposure was SDOH based on Healthy …

Ferrate(Vi) Transformation Of Nitrogen In Secondary Wastewater Effluent: Implications For Water And Nutrient Management, Qiufeng Lin, Zepei Tang, Hussein I. Abdel Shafy, Yang Deng

Department of Earth and Environmental Studies Faculty Scholarship and Creative Works

Ferrate(VI) is a promising chemical agent for wastewater treatment. While targeting various contaminants, it can inevitably react with different water matrix constituents such as nitrogen (N) species. However, the reactions of ferrate(VI) with wastewater N compounds remain poorly understood. This study explores ferrate(VI)-mediated transformations of different N species in a secondary wastewater effluent. Ferrate(VI) oxidation minimally abated total dissolved nitrogen (TDN), while oxidizing dissolved organic nitrogen (DON) into dissolved inorganic nitrogen (DIN), primarily nitrate nitrogen (NO3--N), without noticeably altering ammonia nitrogen (NH3-N) levels. Consequently, ferrate(VI) treatment increased the fraction of bioavailable, soil-leachable NO3--N while lowering the portion of less bioaccessible …

Making The Most Of Artificial Intelligence And Large Language Models To Support Collection Development In Health Sciences Libraries, Ivan Portillo, David Carson

Library Articles and Research

This project investigated the potential of generative AI models in aiding health sciences librarians with collection development. Researchers at Chapman University’s Harry and Diane Rinker Health Science campus evaluated four generative AI models—ChatGPT 4.0, Google Gemini, Perplexity, and Microsoft Copilot—over six months starting in March 2024. Two prompts were used: one to generate recent eBook titles in specific health sciences fields and another to identify subject gaps in the existing collection. The first prompt revealed inconsistencies across models, with Copilot and Perplexity providing sources but also inaccuracies. The second prompt yielded more useful results, with all models offering helpful analysis …

Identifying The Effect Of Architecture Morphology On Wind Fields And Pm2.5 Dispersion At The Urban Block Scale Via A Combined Scheme, Bin Guo, Lu Li, Xiaowei Zhu, Zheng Wang, Miaoyi Chen, Lin Pei, Tengyue Guo

Mechanical and Materials Engineering Faculty Publications and Presentations

This study explores the potential of architecture morphology to mitigate PM2.5 pollution through enhanced urban ventilation. Despite the recognized influence of building designs on wind and air pollution distribution at the urban block scale, specific mechanisms remain poorly understood. To address this gap, we have developed an integrative approach combining in-situ observations, Geographic Information System (GIS), Remote Sensing (RS), Computational Fluid Dynamics (CFD), and statistical modeling. Here, CFD simulates the flow field and PM2.5 dispersion, using in-situ observations for turbulence model selection. GIS quantify architecture morphology parameters to establish accurate CFD boundary conditions, ensuring simulations reflect real-world conditions and precise …

Butte Reduction Works (Brw) Phase Ii Interim Demolition Plan Construction Drawings And Floodplain Encroachment Analysis, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

01.13.2025 Ored Connect, Liz Williamson

ORED Newsletter

NIH Public Access Policy Update

Procurement Information for Award Spending online course announcement

National Sea Grant Law Center funding

Using Nanotechnology To Achieve Sustainability In Interior Residential Spaces, Neveen Youssef Azmy, Esraa Tarek Abu-El Azm, Ahmed Ahmed Rizk, Walaa Abou El-Haggag Mehanna

Journal of Engineering Research

Major scientific and technological developments characterize the present time. One notable achievement is the nano revolution, which has greatly influenced various areas of life Nanotechnology is characterized by using very small particles of materials, either alone or by processing them to create new materials with remarkable properties. Hence, nanotechnology offers promising economic solutions and products to achieve a reliable and sustainable environment. Architecture has great potential to benefit from this technology to achieve sustainability and improve indoor environment quality. Given the proliferation of residential buildings in urban areas, where people spend most of their time, it is necessary to integrate …

Evaluating Lidar Technology In Iphone Mobiles For 2d Mapping Applications, Nasr Mohammady Saba, Salem Salama Saleh

Journal of Engineering Research

Abstract- LiDAR (Light Detection and Ranging) technology has revolutionized mapping applications, offering enhanced precision and accuracy in spatial data collection. The integration of LiDAR technology in the latest iPhone models, beginning with the iPhone 12 Pro, has introduced new capabilities for 2D data measurement and plan creation directly on the mobile device. The iPhone 12 Pro and 12 Pro Max models support LiDAR techniques within their mobile phone cameras, enhancing the performance of various applications such as Measurements and Photos. LiDAR operates by emitting pulsed light waves into the surrounding space, which bounce off nearby objects and return to the …

Experimental And Numerical Investigation For Optimum Design Of Hydraulic Steel Gates, Basma Hassan Mohamed Eng, Ahmed Mohamed Anwer Dr, Hanan Eltobgy Prof., Gamal Helmy El-Saeed Prof

Journal of Engineering Research

Conventionally, steel gates are widely used in hydraulic structures for their superior mechanical properties in sustaining hydrostatic pressure. Maintenance and operational costs should be considered while studying the feasibility of these gates. In the current research, three prototype steel gates with different configurations were prepared and examined experimentally. The three gates have the same surface dimensions of (width x height) equal to (1.0 x 1.25 m). The first steel gate represents a typical traditional gate made of skin plate and stiffened laterally using standard steel channels and will be kept for comparison. The second gate represents a standard thicker plate …

Performance And Emissions Characteristics Of Multi-Cylinder Direct Injection Diesel Engine Fuelled With Diesel/Biodiesel And Toluene Additives, Hagar Alm-Eldin Bastawissi, Medhat Elkelawy Prof. Dr. Eng., Mohammed Osama Elsamadony Dr. Eng., Moustafa Ghazaly Eng.

Journal of Engineering Research

This study explores the impact of using a diesel, biodiesel, and toluene additive fuel blend in a multi-cylinder direct injection diesel engine, focusing on both performance and emissions characteristics. Biodiesel, made from renewable sources like vegetable oils, is often added to diesel to reduce reliance on fossil fuels and improve combustion due to its higher oxygen content. In this work, a 45% biodiesel blend (B45) led to significant reductions in particulate matter (PM) emissions by up to 40% compared to conventional diesel. Additionally, carbon monoxide (CO) and hydrocarbon (HC) emissions decreased by up to 30% and 25%, respectively, due to …

Effect Of Dual-Fuelled Cng And Gasoline On Spark Ignition Engine Performance And Emissions Behaviors At Different Loads, Medhat Elkelawy Prof. Dr, Eng., M.M. Bassuoni Prof. Dr., Hagar Alm-Eldin Bastawissi, Saied I. Haiba Eng.

Journal of Engineering Research

Engine emissions are one of numerous factors that have detrimentally affected the environment, such as global warming, which is the result of growing exhaust gases, practically carbon dioxide (CO2). These emissions have substantially influenced researchers to develop strategic initiatives to minimize the carbon contents of fuels. The purpose of this research is to investigate the characteristics of internal combustion (SI) engines fueled by gasoline and compressed natural gas (CNG) blends. The experiments are performed using a HONDA 4-stroke, single-cylinder, and air-cooled SI engine. Five CNG concentrations are evaluated, the concentrations range from 0.5 to 2.5 L/min with a 0.5 L/min …

A Quantitative Analysis Of The Commercial-Additive Effects On Diesel Engine Combustion And Emissions Characteristics, Medhat Elkelawy Prof. Dr. Eng., Hagar Alm-Eldin Bastawissi Prof. Dr. Eng., E. A. El Shenawy Prof. Dr., Mahmoud Mohamed Soliman Mahmoud Mohamed Mahmoud Soliman

Journal of Engineering Research

Petroleum fuel prices fluctuate in response to global political and economic issues. Government regulations should be followed when it comes to engine emissions, as these dangerous pollutants have a negative impact on the environment. One such effect is global warming, which raises global temperatures. The purpose of this study is to develop the additives for use as a fuel mix with diesel fuel, which will be used to feed the diesel engine of a single cylinder, four strokes. The engine will be tested experimentally with varying loads at fixed speed of 1500 rpm, using blends of [(5% PRETSONE additive + …

Design And Implementation Of A Low-Cost Educa-Tional Robot For Engineering Curriculums, Diana Refaat Henry Jacob, Ashraf Mohamed Hafez, Mohamed Tarek Elawa

Journal of Engineering Research

The role of educational robots is becoming increasingly important. Many commercial educational robots differ in their abilities and price. In general, the cost of these robots presents the main cause of their limited use in the teaching process, especially in countries with limited financial resources. This work attempts to solve this problem by designing and implementing an educational robot with a limited budget. The robot was initially intended to serve higher education students' needs, especially in engineering curriculums but can be extended to other application areas. This work presents robot hardware functional blocks, mechanical struc-ture design, and 3D printing implementation. …

A Greening The Diesel: Vegetable Oil Biodiesel Blends For Cleaner Emissions And Improved Direct Injection Diesel Engine Performance, Medhat Elkelawy Prof. Dr, Eng., Hagar Alm-Eldin Bastawissi, E. A. El Shenawy Prof. Dr., Mustafa Mohamed Ouda

Journal of Engineering Research

In this study, we conducted comprehensive experiments to assess and compare the performance of pure diesel fuel against biodiesel produced from corn oil in various blend ratios (15/85, 30/70, 45/55, and 60/40) in a conventional four-stroke, direct-injection diesel engine, fuel is injected directly into the combustion chamber at the end of the compression stroke, allowing for efficient combustion and power generation over four distinct phases: intake, compression, power, and exhaust. Each fuel blend was tested at an engine speed of 16,000 rpm across different load conditions (low, medium, and high). Key performance metrics, including volumetric fuel consumption, exhaust smoke, and …