Digital Commons Network^™

A Proposed Image Scaling Technique By Using Bezier Curve, Rafal Ali Sameer

Baghdad Science Journal

The process of resizing a digital image using geometrical transformation without changing the quality of image is known as image scaling or image resizing. Image processing such as digital image scaling has a wide range of applications on computer, mobile, and other digital devices. This paper proposes a digital image resizing (scaling) approach and explaining how the algorithms have been modified to meet accuracy and performance. Bezier curve have been used in previous works for processing in various fields while in this paper Bezier curve equations used to resize the digital image (scaling-up or scaling-down). The idea of using Bezier …

Eeg Eye Blink Artifacts Removal With Wavelet Denoising And Bandpass Filtering, Ebtesam N. Alshemmary, Bushra K. Hilal, Azmi Sh. Abdulbaqi, Mohammed A. Ahmed, Zhentai Lu

Baghdad Science Journal

Many data sources can be analyzed using Wavelet Transforms (WT), a mathematical technique frequently used for extracting information from them. Although WT was effective at Blind Source Separation (BSS), it had some limitations, such as signal loss. The problem has been addressed with the introduction of a joint algorithm that combines WT with Frequency Domain Filtering (BPF). Wavelet Denoising Technique (WDT) and Band-Pass Filtering (BPF) are employed in this research to propose an innovative algorithm for combining advanced wavelet transform methods. Combining these two techniques helps reduce eye flutter in electroencephalograms (EEGs).FP1 signals produced by eye movement are filtered out …

Preparation And Characterization Of Nanocomposite Textile Filter For Separation Of The Oil/Water Mixture Using Pa-Pva Blends Reinforced With Carbon Nanoparticles, Rusul Mohamed Darweesh, Balqees Mohamed Al-Dabbag, Hanaa Jawad Kadhim

Baghdad Science Journal

The electrospinning technique used to prepare a nano fibre filter under limited conditions involves (20 kV applied voltage, 15 cm gap distance, 1 ml/h: flow rate, and 0.4 mm needle diameter). Several tests for prepared materials were conducted including [scanning electron microscopy (SEM-EDX), Fourier Transform Infrared (FTIR), contact angle, and particle size analysis]. As well as, the characterization of the water/oil mixture was tested before the filtration process and after it. According to the SEM data, smooth and homogeneous nanofibers with an approximate diameter of 350 nm and open porosity morphology were produced using the electrospinning approach. The liquid particles …

Estimation Of Copula Density Using The Wavelet Transform, Fatimah Hashim Falhi, Munaf Yousif Hmood

Baghdad Science Journal

This paper proposes a new method to estimate the copula density function using wavelet decomposition as a nonparametric method, to obtain more accurate results and address the issue of boundary effects that nonparametric estimation methods suffer from. The wavelet method is an automatic method for dealing with boundary effects because it does not take into Consideration whether the time series is stationary or nonstationary. To estimate the copula density function, simulation was used to generate data using five different copula functions, such as Gaussian, Frank, Tawn, Rotation Tawn, and Joe copulas. With five different sample sizes at three positive correlation …

Charting The Unknown: First Passage Time Probabilities For Pearson Diffusion Process And Application To Options Risk Management, Saswat Patra, Malay Bhattacharyya

American Business Review

The first passage time probabilities have applications in many fields, including Finance, Marketing, Economics, Physics, and Statistics. In this paper, we study the first passage time probabilities for a Pearson diffusion process and obtain the lower and upper bounds of the first passage time density. We show that the density may be approximated by the upper bound with an error of approximately five percent. We present an application by modelling the profit and loss function of the S&P 500, FTSE 100 and DAX 40 index options using a Pearson diffusion process. Further, we establish the relation between first passage time …

Full Issue

Swiss American Historical Society Review

No abstract provided.

Product Perspective From Fuzzy To Neutrosophic Graph Extension- A Review Of Literature, G. Vetrivel, M. Mullai, G. Rajchakit

Neutrosophic Systems with Applications

This review article consolidates and tabulates research on the product operations done in fuzzy, intuitionistic fuzzy, and neutrosophic graphs. This article encompasses the previous product discussions on fuzzy graphs and their extensions. This article aims to list the origin, structural properties, applications, etc. done by the researchers and academicians using the product behavior of two graphs on the fuzzified environment. This review provides a clear understanding of enhancements of product approach on graphs from fuzzy to neutrosophic kind.

A Neutrosophic Model For Measuring Evolution, Involution, And Indeterminacy In Species: Integrating Common And Uncommon Traits In Environmental Adaptation, Antonios Paraskevas, Michael Madas

Neutrosophic Systems with Applications

In 2017, Professor F. Smarandache introduced the Neutrosophic Theory of Evolution, Involution, and Indeterminacy (or Neutrality) (NToEIaI). He concluded that every theory of evolution is characterized by a certain degree of truth, indeterminacy, and untruth, as in neutrosophic logic. In this perspective, he raised several open questions on evolution, neutrality, and involution that required further research effort. Very recently, in 2024, Smarandache conducted research, from a soft sciences/philosophical viewpoint, on identifying and studying common parts in uncommon things and uncommon parts in common things emphasizing the complexity and interconnectedness of concepts within the context of neutrosophy. In this article, we …

Some Similarity Measures On Generalized Interval-Valued Intuitionistic Fuzzy Soft Expert Sets And Their Applications In Medical Diagnosis, Afshan Qayyum, Noreen Mushtaq, Tanzeela Shaheen, Wajid Ali, Florentin Smarandache

Neutrosophic Systems with Applications

In recent years, the application of fuzzy sets has gained significant attraction in various fields, including medical diagnosis, due to their ability to manage uncertainties and imprecise information. This paper focuses on the comparative analysis of similarity measures within the realm of Generalized Interval-Valued Intuitionistic Fuzzy Soft Expert Sets (GIVIFSESs) and explores their application in the domain of medical diagnosis. Most of the important topics in fuzzy set theory are the similarity measures between the generalizations of fuzzy set theory. Similarity measures are a crucial tool which was used in data science. In this process, we measure how much the …

Toxic Battery: Pollution As A Dignitary Tort, Amber Polk

Articles

No abstract provided.

Physiochemical, Bio, Thermal, And Non-Thermal Processing Of Major And Minor Millets: A Comprehensive Review On Antinutritional And Antioxidant Properties, Suhan Bheemaiah Balyatanda, N.A. Nanje Gowda, Jeyamkondan Subbiah, Snehasis Chakraborty, P.V. Vara Prasad, Kaliramesh Siliveru

Food Science Faculty Publications and Presentations

Millets are recognized as future foods due to their abundant nutrition and resilience, increasing their value on the global stage. Millets possess a broad spectrum of nutrients, antinutrients, and antioxidants, making it imperative to understand the effects of various processing methods on these components. Antinutritional factors interfere with the digestibility of macro-nutrients and the bioavailability and bio accessibility of minerals. This necessitates methods to reduce or eliminate antinutrients while improving nutritive and antioxidant value in food. This review aims to elucidate the rationale behind processing choices by evaluating the scientific literature and examining the mechanisms of processing methods, categorized as …

Deciphering Rodent Behavior: Unraveling Complex Decision-Making Through High-Throughput Data Analysis In Behavioral Neuroscience, Atanu Giri

Open Access Theses & Dissertations

Understanding the effects of substance use on decision-making is critical for both clinical andtranslational research. In this thesis, I present two complementary studies that explore decision- making behavior in rodents with a focus on alcohol consumption and novel experimental frame- works. The first study examines the impact of acute alcohol consumption on decision-making in a behavioral approach-avoidance task. Rats were presented with a concurrent choice of consuming alcohol and sucrose mixtures across four distinct concentrations, allowing for the analysis of ap- proach or avoidance behavior. Sex-dependent differences emerged, with male rats demonstrating a significantly higher tendency to approach higher alcohol …

The Long Unwind: British Columbia Court Of Appeal Litigation Activity 1995–2022, Donald J. Netolitzky

UBC Law Review

No abstract provided.

An Overview Of Ancillary Services Provided By Vehicle-To-Grid Systems, Fazel Mohammadi, Mahmood Mirhashemi

Electrical & Computer Engineering and Computer Science Faculty Publications

Vehicle-to-Grid (V2G) systems are emerging as a pivotal technology in modern power systems, offering a range of ancillary services that enhance the stability and reliability of power systems. This paper provides an overview of the key ancillary services provided by V2G systems, highlighting their role in grid modernization. Technical challenges, economic implications, and policy considerations associated with the deployment of V2G systems are explored to assess their potential impact on advancing a more resilient and sustainable energy infrastructure.

Search For An Ev-Scale Sterile Neutrino Using Improved High-Energy 𝜈𝜇 Event Reconstruction In Icecube, Karen Andeen

Physics Faculty Research and Publications

This Letter presents the result of a 3+1 sterile neutrino search using 10.7 yr of IceCube data. We analyze atmospheric muon neutrinos that traverse the Earth with energies ranging from 0.5 to 100 TeV, incorporating significant improvements in modeling neutrino flux and detector response compared to earlier studies. Notably, for the first time, we categorize data into starting and throughgoing events, distinguishing neutrino interactions with vertices inside or outside the instrumented volume, to improve energy resolution. The best-fit point for a 3+1 model is found to be at sin2⁡(2⁢𝜃24)=0.16 and Δ⁢𝑚241 =3.5  eV2, which agrees with previous iterations of this …

Enterococcus Faecium: Evolution, Adaptation, Pathogenesis And Emerging Therapeutics, Yahan Wei, Dennise Palacios Araya, Kelli L. Palmer

School of Podiatric Medicine Publications

The opportunistic pathogen Enterococcus faecium colonizes humans and a wide range of animals, endures numerous stresses, resists antibiotic treatment and stubbornly persists in clinical environments. The widespread application of antibiotics in hospitals and agriculture has contributed to the emergence of vancomycin-resistant E. faecium, which causes many hospital-acquired infections. In this Review, we explore recent discoveries about the evolutionary history, the environmental adaptation and the colonization and dissemination mechanisms of E. faecium and vancomycin-resistant E. faecium. These studies provide critical insights necessary for developing novel preventive and therapeutic approaches against vancomycin-resistant E. faecium and also reveal the intricate interrelationships …

Bridging Human And Machine Intelligence: Reverse-Engineering Radiologist Intentions For Clinical Trust And Adoption, Akash Awasthi, Ngan Le, Zhigang Deng, Rishi Agrawal, Carol C. Hu, Hien Van Nguyen

Computer Science and Computer Engineering Faculty Publications and Presentations

In the rapidly evolving landscape of medical imaging, the integration of artificial intelligence (AI) with clinical expertise offers unprecedented opportunities to enhance diagnostic precision and accuracy. Yet, the "black box" nature of AI models often limits their integration into clinical practice, where transparency and interpretability are important. This paper presents a novel system leveraging the Large Multimodal Model (LMM) to bridge the gap between AI predictions and the cognitive processes of radiologists. This system consists of two core modules, Temporally Grounded Intention Detection (TGID) and Region Extraction (RE). The TGID module predicts the radiologist's intentions by analyzing eye gaze fixation …

Visual Causal Question And Answering With Knowledge Graph Link Prediction, Utkarshani Jaimini, Cory Henson, Amit Sheth

Publications

The ability to answer causal questions is important for any system that requires robust scene under- standing. In this demonstration, we develop a prototype system that leverages our causal link prediction framework, CausalLP. CausalLP framework uses a visual causal knowledge graph and associated knowledge graph embedding for two visual causal question and answering tasks- (i) causal explanation and (ii) causal prediction. In the live demonstration sessions, the participants will be invited to test the efficiency and effectiveness of the system for visual causal question and answering.

Conjugative Transfer Of The Incn Plasmid Pkm101 Is Mediated By Dynamic Interactions Between The Trak Accessory Factor And Trai Relaxase, Yang Grace Li, Annika Breidenstein, Ronnie P-A Berntsson, Peter J Christie

Faculty, Staff and Student Publications

Conjugative dissemination of mobile genetic elements (MGEs) among bacteria is initiated by assembly of the relaxosome at the MGE’s origin-of-transfer (oriT) sequence. A critical but poorly defined step of relaxosome assembly involves recruitment of the catalytic relaxase to its DNA strand-specific nicking site within oriT. Here, we present evidence by AlphaFold modeling, affinity pulldowns, and in vivo site-directed photocrosslinking that the TraK Ribbon-Helix-Helix DNA-binding protein recruits TraI to oriT through a dynamic interaction in which TraI’s C-terminal unstructured domain (TraICTD) wraps around TraK’s C-proximal tetramerization domain. Upon relaxosome assembly, conformational changes disrupt this contact, and TraICTD instead …

Genie: Enhancing Information Management In The Restaurant Industry Through Ai-Powered Chatbot, Megha Gupta, Venkatasai Dheekonda, Mohammad Masum

Faculty Research, Scholarly, and Creative Activity

In the dynamic restaurant industry, we introduce "Genie," an AI-powered chatbot, represents an advancement in customer service efficiency through technological innovation. Designed to enhance restaurant operations including order processing, reservations, and FAQs management, Genie leverages advanced Natural Language Processing (NLP) techniques. By converting input queries into word embeddings and applying a sophisticated tag classification system, Genie precisely interprets customer intents and generates accurate responses, thereby markedly improving the dining experience. Our thorough examination of various word embeddings and classifiers—Word2Vec, Glove, BERT, Gaussian Naive Bayes, XGB, Artificial Neural Networks (ANN), and Recurrent Neural Networks—revealed that the combination of Word2Vec and ANN …

Chasing The Albino Pygmy Giraffe, Charles H. Haddad

School of Communication and Journalism Faculty Publications

It's never a good sign when someone is knocking on the door of your hotel room at seven in the morning. That's especially true if you have been schlepping eight college students across Western China, as I had been for the past week. I now heard in this soft rapping the death knell of my fledgling professorial career. Wrapping a ratty, threadbare pillow around my head, I tried to shut out the insistent rapping. Of course, that didn't work. Bad news has a way of butting in.

So begins my novel “Chasing the Albino Pygmy Giraffe.” It is a laugh-aloud …

Car-Redirected Natural Killer T Cells Demonstrate Superior Antitumor Activity To Car-T Cells Through Multimodal Cd1d-Dependent Mechanisms, Gloria Delfanti, Ourania Tsahouridis, Caroline Marnata Pellegry, Manuela Zingarelli, Gatphan Atassi, Mark G Woodcock, Giulia Casorati, Paolo Dellabona, William Y Kim, Linjie Guo, Barbara Savoldo, Ageliki Tsagaratou, J Justin Milner, Leonid S Metelitsa, Gianpietro Dotti

Faculty, Staff and Students Publications

Human natural killer T (NKT) cells have been proposed as a promising cell platform for chimeric antigen receptor (CAR) therapy in solid tumors. Here we generated murine CAR-NKT cells and compared them with CAR-T cells in immune-competent mice. Both CAR-NKT cells and CAR-T cells showed similar antitumor effects in vitro, but CAR-NKT cells showed superior antitumor activity in vivo via CD1d-dependent immune responses in the tumor microenvironment. Specifically, we show that CAR-NKT cells eliminate CD1d-expressing M2-like macrophages. In addition, CAR-NKT cells promote epitope spreading and activation of endogenous T cell responses against tumor-associated neoantigens. Finally, we observed that CAR-NKT cells …

Genomic Analysis Of Intracranial And Subcortical Brain Volumes Yields Polygenic Scores Accounting For Variation Across Ancestries, Zuriel Ceja, Jackson G Thorp, Ingrid Agartz, Saud Alhusaini, David Ames, Philippe Amouyel, Ole A Andreassen, Konstantinos Arfanakis, Alejandro Arias-Vasquez, Nicola J Armstrong, Lavinia Athanasiu, Mark E Bastin, Alexa S Beiser, David A Bennett, Joshua C Bis, Marco P M Boks, Dorret I Boomsma, Henry Brodaty, Jan K Buitelaar, Ralph Burkhardt, Wiepke Cahn, Vince D Calhoun, Owen T Carmichael, Mallar Chakravarty, Qiang Chen, Christopher R K Ching, Sven Cichon, Benedicto Crespo-Facorro, Fabrice Crivello, Anders M Dale, George Davey Smith, Eco J C De Geus, Philip L De Jager, Greig I De Zubicaray, Stéphanie Debette, Charles Decarli, Chantal Depondt, Sylvane Desrivières, Srdjan Djurovic, Stefan Ehrlich, Susanne Erk, Thomas Espeseth, Guillén Fernández, Irina Filippi, Simon E Fisher, Debra A Fleischman, Evan Fletcher, Myriam Fornage, Andreas J Forstner, Clyde Francks, Barbara Franke, Tian Ge, Aaron L Goldman, Hans J Grabe, Robert C Green, Oliver Grimm, Nynke A Groenewold, Oliver Gruber, Vilmundur Gudnason, Asta K Håberg, Unn K Haukvik, Andreas Heinz, Derrek P Hibar, Saima Hilal, Jayandra J Himali, Beng-Choon Ho, David F Hoehn, Pieter J Hoekstra, Edith Hofer, Wolfgang Hoffmann, Avram J Holmes, Georg Homuth, Norbert Hosten, M Kamran Ikram, Jonathan C Ipser, Clifford R Jack, Neda Jahanshad, Erik G Jönsson, Rene S Kahn, Ryota Kanai, Marieke Klein, Maria J Knol, Lenore J Launer, Stephen M Lawrie, Stephanie Le Hellard, Phil H Lee, Hervé Lemaître, Shuo Li, David C M Liewald, Honghuang Lin, W T Longstreth, Oscar L Lopez, Michelle Luciano, Pauline Maillard, Andre F Marquand, Nicholas G Martin, Jean-Luc Martinot, Karen A Mather, Venkata S Mattay, Katie L Mcmahon, Patrizia Mecocci, Ingrid Melle, Andreas Meyer-Lindenberg, Nazanin Mirza-Schreiber, Yuri Milaneschi, Thomas H Mosley, Thomas W Mühleisen, Bertram Müller-Myhsok, Susana Muñoz Maniega, Matthias Nauck, Kwangsik Nho, Wiro J Niessen, Markus M Nöthen, Paul A Nyquist, Jaap Oosterlaan, Massimo Pandolfo, Tomas Paus, Zdenka Pausova, Brenda W J H Penninx, G Bruce Pike, Bruce M Psaty, Benno Pütz, Simone Reppermund, Marcella D Rietschel, Shannon L Risacher, Nina Romanczuk-Seiferth, Rafael Romero-Garcia, Gennady V Roshchupkin, Jerome I Rotter, Perminder S Sachdev, Philipp G Sämann, Arvin Saremi, Muralidharan Sargurupremraj, Andrew J Saykin, Lianne Schmaal, Helena Schmidt, Reinhold Schmidt, Peter R Schofield, Markus Scholz, Gunter Schumann, Emanuel Schwarz, Li Shen, Jean Shin, Sanjay M Sisodiya, Albert V Smith, Jordan W Smoller, Hilkka S Soininen, Vidar M Steen, Dan J Stein, Jason L Stein, Sophia I Thomopoulos, Arthur W Toga, Diana Tordesillas-Gutiérrez, Julian N Trollor, Maria C Valdes-Hernandez, Dennis Van T Ent, Hans Van Bokhoven, Dennis Van Der Meer, Nic J A Van Der Wee, Javier Vázquez-Bourgon, Dick J Veltman, Meike W Vernooij, Arno Villringer, Louis N Vinke, Henry Völzke, Henrik Walter, Joanna M Wardlaw, Daniel R Weinberger, Michael W Weiner, Wei Wen, Lars T Westlye, Eric Westman, Tonya White, A Veronica Witte, Christiane Wolf, Jingyun Yang, Marcel P Zwiers, M Arfan Ikram, Sudha Seshadri, Paul M Thompson, Claudia L Satizabal, Sarah E Medland, Miguel E Rentería

Faculty, Staff and Student Publications

Subcortical brain structures are involved in developmental, psychiatric and neurological disorders. Here we performed genome-wide association studies meta-analyses of intracranial and nine subcortical brain volumes (brainstem, caudate nucleus, putamen, hippocampus, globus pallidus, thalamus, nucleus accumbens, amygdala and the ventral diencephalon) in 74,898 participants of European ancestry. We identified 254 independent loci associated with these brain volumes, explaining up to 35% of phenotypic variance. We observed gene expression in specific neural cell types across differentiation time points, including genes involved in intracellular signaling and brain aging-related processes. Polygenic scores for brain volumes showed predictive ability when applied to individuals of diverse …

Living Christianly: Under The Lordship Of Christ, Everything Matters, Leah A. Zuidema

Faculty Work Comprehensive List

"I want to proclaim that Jesus is Lord, and when I say that the Lordship of Christ matters in every area of life, I want to be ready with specific examples about what it means to live Christianly."

Posting about working towards Christ-centered renewal in all areas of life from In All Things, an online hub that offers insight into maintaining a faithful and orthodox Reformed Christian worldview while fearlessly engaging in every aspect of contemporary life—until all is made new.

Living Christianly

Exploring The Human Side Of Math, Mike Janssen

Faculty Work Comprehensive List

"Abstract mathematics is an important way to better understand and marvel at the beauty and intricacy of God’s creation."

Posting about ­­­­­­­­experiences in math research from In All Things, an online hub that offers insight into maintaining and faithful and orthodox Reformed Christian worldview while fearlessly engaging in every aspect of contemporary life – until all is made new.

Exploring the Human Side of Math

Environmental Law In Trump’S Second Term, Michael B. Gerrard

Faculty Scholarship

Donald Trump’s victory in the Nov. 5, 2024 election and Republican control of both the Senate and the House (if that happens) will mean a reversal of much of the environmental progress under the Biden administration, just as the 2016 election reversed large parts of the Obama environmental legacy. However, rapid advances in the technology and economics of clean energy have created a momentum that can be slowed but not stopped. States can adopt their own stronger standards despite what happens in Washington, with a few exceptions, and can use their procurement power and their pension funds’ investment clout to …

Techniques For Modeling Ocean Soundscapes: Detailed Description For Wind Contributionsa, Martin Siderius, Michael A. Ainslie, John Gebbie, Alexandra Schäfke, N Ross Chapman, Bruce Martin, Kay L. Gemba

Electrical and Computer Engineering Faculty Publications and Presentations

Wind over the ocean creates breaking waves that generate air-filled bubbles, which radiate underwater sound. This wind-generated sound is a significant component of the ocean soundscape, and models are essential for understanding and predicting its impact. Models for predicting sound pressure level (SPL) from wind have been studied for many years. However, the terminology and definitions behind modeling approaches have not been unified, and ambiguity has led to differences in predicted SPL. The 2022 Ambient Sound Modeling Workshop was organized to compare ambient sound modeling approaches from different researchers. The main goal of the workshop was to quantify differences in …

Toward A Responsible Future: Recommendations For Ai-Enabled Clinical Decision Support, Russell Leftwich, Eileen Koski, Amanda L Joseph, Monica Lopez-Gonzalez, Lee A Fleisher, Kimberly Nolen, Sayon Dutta, Deborah R Levy, Amy Price, Paul J Barr, Jonathan D Hron, Baihan Lin, Gyana Srivastava, Nuria Pastor, Unai Sanchez Luque, Tien Thi Thuy Bui, Reva Singh, Tayler Williams, Mark G Weiner, Tristan Naumann, Dean F Sittig, Gretchen Purcell Jackson, Yuri Quintana

Faculty, Staff and Student Publications

BACKGROUND: Integrating artificial intelligence (AI) in healthcare settings has the potential to benefit clinical decision-making. Addressing challenges such as ensuring trustworthiness, mitigating bias, and maintaining safety is paramount. The lack of established methodologies for pre- and post-deployment evaluation of AI tools regarding crucial attributes such as transparency, performance monitoring, and adverse event reporting makes this situation challenging.

OBJECTIVES: This paper aims to make practical suggestions for creating methods, rules, and guidelines to ensure that the development, testing, supervision, and use of AI in clinical decision support (CDS) systems are done well and safely for patients.

MATERIALS AND METHODS: In May …

2024 November, Morehead State University. Office Of Communications & Marketing.

Morehead State Press Release Archive, 1961 to the Present

Press releases for November of 2024.

Ai And Data Science For Public Policy, Kenneth Benoit

Research Collection School of Social Sciences

Artificial intelligence (AI) and data science are reshaping public policy by enabling more data-driven, predictive, and responsive governance, while at the same time producing profound changes in knowledge production and education in the social and policy sciences. These advancements come with ethical and epistemological challenges surrounding issues of bias, transparency, privacy, and accountability. This special issue explores the opportunities and risks of integrating AI into public policy, offering theoretical frameworks and empirical analyses to help policymakers navigate these complexities. The contributions explore how AI can enhance decision-making in areas such as healthcare, justice, and public services, while emphasising the need …