Physical Sciences and Mathematics Commons^™

Destiny Functional Theory (Dft) Study Of Water Autoionization In Solvated Clusters, Kurt Kolasinski, Alex M. Salkowski

Chemistry Faculty Publications

We have implemented a cluster-continuum method using density functional theory (DFT) to model water clusters and various charged species derived from water. Two aims of this study are to determine the minimal basis required for proper modeling of water autoionization and the minimum number of explicit water molecules that are required to properly model the energetics of solvation. The thermodynamics of water autoionization converge following a modified power law to deliver chemically accurate values of the Gibbs energy change for autoionization with tractably small clusters. Convergence is slower and not exponential as assumed in previous work. We identify the n …

Q-Rational Functions And Interpolation With Complete Nevanlinna–Pick Kernels, Daniel Alpay, Paula Cerejeiras, Uwe Kaehler, Baruch Schneider

Mathematics, Physics, and Computer Science Faculty Articles and Research

In this paper we introduce the concept of matrix-valued q-rational functions. In comparison to the classical case, we give different characterizations with principal emphasis on realizations and discuss algebraic manipulations. We also study the concept of Schur multipliers and complete Nevanlinna–Pick kernels in the context of q-deformed reproducing kernel Hilbert spaces and provide first applications in terms of an interpolation problem using Schur multipliers and complete Nevanlinna–Pick kernels.

Method Of Selecting The Optimal Variant Of Mine Closure With The Possibility Of Capturing Methane From Underground Excavations, Marian Turek, Małgorzata Magdziarczyk

Journal of Sustainable Mining

The article presents a method of selecting the optimal option for the closure of a coal mine, from which it is planned to capture the methane remaining in the goaf and deposit it for many years for its economic use. Using the example of several options for the closure of one of the mines, for which the evaluation criteria have been defined, and the weights of their relevance have been determined, it is described how to create a special algorithm for the selection of the optimal option.

The Environment Of Glaciovolcanic Caves And Their Value As Planetary Analogues, Christian Stenner, Lee J. Florea, Linda Sobolewski, Andreas Pflitsch, Morgan Cable, Roberto Anitori, Richard E. Davis, Kathleen Graham, Glyn Williams-Jones

FRONTIERS UNBOUND: Exploring Extreme Environments

No abstract provided.

The Ecology Of Chemosynthesis In Submerged Coastal Caves, Robert Scharping, Michael Casso, Isabel Schaal, Paul Henderson, James Garey, Matthew Charette, John Pohlman, Stefan Sievert

FRONTIERS UNBOUND: Exploring Extreme Environments

No abstract provided.

Euler Archive Spotlight: Ed Sandifer's Influence, Erik Tou

Euleriana

The Euler Archive owes its existence to the work and enthusiasm of C. Edward Sandifer. In this issue, we give a history of Ed's work and influence on the creation and growth of the Euler Archive.

Translating Scientific Latin Texts With Artificial Intelligence: The Works Of Euler And Contemporaries, Sylvio R. Bistafa

Euleriana

The major hindrance in the study of earlier scientific literature is the availability of Latin translations into modern languages. This is particularly true for the works of Euler who authored about 850 manuscripts and wrote a thousand letters and received back almost two thousand more. The translation of many of these manuscripts, books and letters have been published in various sources over the last two centuries, but many more have not yet appeared. Fortunately, nowadays, artificial intelligence (AI) translation can be used to circumvent the challenges of translating such substantial number of texts. To validate this tool, benchmark tests have …

On The Vibration Of Strings: An English Translation Of Leonhard Euler’S `Sur La Vibration Des Cordes' (E140), Reilly R. Fortune

Euleriana

We present an English translation of E140 - 'Sur la Vibration des cordes.'

About The Cases In Which The Formula X^4+Mxxyy+Y^4 Can Be Reduced To A Square, Georg Ehlers

Euleriana

Euler continues a previous study on the title Quartic (E696) with a new approach. His starting point here is the observation that, when the title Quartic is solved for m, the resulting fraction becomes an integer when z=ax^2y^2-(x^2±y^2). He provides many quadratic forms for m that allow special solutions, and tables for |m|≤200. Even though the tables are known today to be incomplete, they allow an insight into the enormous amount of work that was needed for their compilation.

The interest in the title Quartic predates Euler, and the fact that he resumed the study indicates a …

Ed Sandifer: A Running Mathematician And Mathematical Runner, Rick Cleary

Euleriana

Historian of mathematics C. Edward Sandifer was an outstanding marathon runner as well as a first rate mathematician. This note is a review of Prof. Sandifer's athletic successes, and a look at the attributes that he brought to both his professional and running careers.

How Ed Did It - A Memorial Conference To Honor Ed Sandifer, Lawrence D'Antonio

Euleriana

I look back at the virtual conference from February 2023 that was organized to honor the memory of the historian of mathematics Ed Sandifer, who had died in August 2022. The program of the conference is given at the end of the article.

Looking Back And Looking Forward, Christopher Goff, Erik Tou

Euleriana

An introduction to the contents in Issue 2, Volume 4 of Euleriana.

Deep Learning Approach In Melanoma Stage Classification, Frank Lemba Lemba, Clopas Kwenda

African Conference on Information Systems and Technology

Accurate and efficient classification of melanoma stages is crucial for effective treatment planning and improved patient outcomes. Traditional diagnostic methods are often time-consuming and subjective, highlighting the need for advanced computational approaches. This study proposes a self-supervised learning framework combined with a convolutional neural network (CNN) to classify melanoma stages more effectively. Initially, features are extracted from unlabeled skin images using pre-trained VGG16 and ResNet50 models. These features are combined and reduced in dimensionality using Principal Component Analysis (PCA). Subsequently, K-means and DBSCAN clustering is applied to pseudo-label the data, providing a foundation for pre-training a CNN model. This pre-trained …

High Mountain Ecosystems And Snow Cover In A Changing Climate: For Better Or For Worse, Philippe Choler

FRONTIERS UNBOUND: Exploring Extreme Environments

No abstract provided.

Trends From 20 Years Of Artificial Intelligence In Financial Services In Africa, Nthabiseng Moela, Lerato Matlala, Jackie Ma, Dipuo Maphutha, Hossana Twinomurinzi

African Conference on Information Systems and Technology

The need for financial inclusion in Africa, particularly for marginalised groups like women and small businesses, highlights the importance of leveraging Artificial Intelligence (AI). This study provides a bibliometric analysis of AI's integration into African financial services from 2003 to 2023. The key results show a significant increase in AI use, particularly in fraud detection, credit risk prediction, and stock market volatility forecasting, with 49% of the research coming from South Africa, Nigeria, and Tunisia. However, areas like financial development management, inflation control, and gender disparities in loan access remain underexplored. The emphasis has been on the technical implementation of …

Some Studies On Mathematical Morphology In Remotely Sensed Data Analysis, Geetika Barman

Doctoral Theses

The application of Mathematical Morphology (MM) techniques has proven to be beneficial in the extraction of shapebased and texture-based features during remote sensing image analysis. The characteristics of these techniques, such as nonlinear adaptability and comprehensive lattice structure, make them useful for contextual spatial feature analysis. Despite the advancements, there are still persistent challenges, including the curse of dimensionality, maintaining spatial correlation, and the adaptability of morphological operators in higher dimensions. The focus of this thesis is to explore the potential of MM-based methods to analyse spatial features in addressing these challenges, specifically in the context of spatialcontextual feature analysis …

Carbon Isotope Budget Indicates Biological Disequilibrium Dominated Ocean Carbon Storage At The Last Glacial Maximum, Anne Willem Omta

Faculty Scholarship

Understanding the causes of the ~90 ppmv atmospheric CO2 swings between glacial and interglacial climates is an important open challenge in paleoclimate research. Although the regularity of the glacial-interglacial cycles hints at a single driving mechanism, Earth System models require many independent physical and biological processes to explain the full observed CO2 signal. Here we show that biologically sequestered carbon in the ocean can explain an atmospheric CO2 change of 75 ± 40 ppmv, based on a mass balance calculation using published carbon isotopic measurements. An analysis of the carbon isotopic signatures of different water masses indicates similar regenerated carbon …

A Systematic Study Of Planetary Envelope Growth With 3d Radiation-Hydrodynamics Simulations, Avery Bailey, James M. Stone, Jeffrey Fung

Physics & Astronomy Faculty Research

In the core accretion model of planet formation, envelope cooling regulates the accretion of material and ultimately sets the time-scale to form a giant planet. Given the diversity of planet-forming environments, opacity uncertainties, and the advective transport of energy by three-dimensional (3D) recycling flows, it is unclear whether one-dimensional models can adequately describe envelope structure and accretion in all regimes. Even in 3D models, it is unclear whether approximate radiative transfer methods sufficiently model envelope cooling, particularly at the planetary photosphere. To address these uncertainties, we present a suite of 3D radiation-hydrodynamics simulations employing methods that directly solve the transfer …

Re: Comment Letter For Draft Bpsou 2023 Site-Wide Surface Water Data Summary Report (Dated May 31, 2024), Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

A Correspondence Between Deep Boltzmann Machines And P-Adic Statistical Field Theories, Wilson A. Zuniga-Galindo

School of Mathematical & Statistical Sciences Faculty Publications

There is a strong interest in studying the correspondence between Euclidean quantum fields and neural networks. This correspondence takes different forms depending on the type of networks considered. In this work, we study this correspondence in the case of deep Boltzmann machines (DBMs) having a tree-like topology. We use p-adic numbers to encode this type of topology. A p-adic continuous DBM is a statistical field theory (SFT) defined by an energy functional on the space of square-integrable functions defined on a p-adic N-dimensional ball. The energy functionals are non-local, meaning they depend on the interaction of all the neurons forming …

Institutional Data Repositories Are Vital, Jen Darragh, Mikala R. Narlock, Halle Burns, Peter A. Cerda, Wind Cowles, Leslie M. Delserone, Seth Erickson, Joel Herndon, Heidi Imker, Lisa R. Johnston, Sherry Lake, Michael Lenard, Alicia Hofelich Mohr, Jennifer Moore, Jonathan Petters, Brandie Pullen, Shawna Taylor, Briana Wham

University of Nebraska-Lincoln Libraries: Faculty Publications

As funding agencies and publishers reiterate research data sharing expectations (1), many higher-education institutions have demonstrated their commitment to the long-term stewardship of research data by connecting researchers to local infrastructure, with dedicated staffing, that eases the burden of data sharing. Institutional repositories are an example of this investment (2). They provide support for researchers in sharing data that might otherwise be lost: data without a disciplinary repository, data from projects with limited funding, or data that are too large to sustainably store elsewhere. The staffing and technical infrastructure provided by institutional repositories ensures responsible access to information while considering …

Improvement And Evaluation Of Multiple Imputation By Heckman's One-Step Mle For Binary Mnar Outcomes And Various Types Of Mar Covariates, Xin W. Shore

Mathematics & Statistics ETDs

Missing data is inevitable in clinical epidemiology. It becomes one of the major challenges in the analyses and can potentially undermine the validity of results and conclusions. Although methods for handling missing data with mechanisms of missing completely at random (MCAR) or missing at random (MAR) have been widely researched, methods adapted for the missing not at random (MNAR) mechanism are less studied. Galimard et al. (2018) have derived a method to use multiple imputation by Heckman's One-Step ML Estimation for binary MNAR outcome and continuous MAR covariates (MIHEml). This dissertation focuses on updating MIHEml in terms of …

Review Of Data Bias In Healthcare Applications, Atharva Prakash Parate, Aditya Ajay Iyer, Kanav Gupta, Harsh Porwal, P. C. Kishoreraja, R. Sivakumar, Rahul Soangra

Physical Therapy Faculty Articles and Research

In the area of medical artificial intelligence (AI), data bias is a major difficulty that affects several phases of data collection, processing, and model building. The many forms of data bias that are common in AI in healthcare are thoroughly examined in this review study, encompassing biases related to socioeconomic status, race, and ethnicity as well as biases in machine learning models and datasets. We examine how data bias affects the provision of healthcare, emphasizing how it might worsen health inequalities and jeopardize the accuracy of AI-driven clinical tools. We address methods for reducing data bias in AI and focus …

Alphafold2 Modeling And Molecular Dynamics Simulations Of The Conformational Ensembles For The Sars-Cov-2 Spike Omicron Jn.1, Kp.2 And Kp.3 Variants: Mutational Profiling Of Binding Energetics Reveals Epistatic Drivers Of The Ace2 Affinity And Escape Hotspots Of Antibody Resistance, Nishank Raisinghani, Mohammed Alshahrani, Grace Gupta, Gennady M. Verkhivker

Mathematics, Physics, and Computer Science Faculty Articles and Research

AlphaFold2-based atomistic predictions of structures and conformational ensembles of the SARS-CoV-2 spike complexes with the host receptor ACE2 for the most dominant Omicron variants JN.1, KP.1, KP.2 and KP.3 to examine the mechanisms underlying the role of convergent evolution hotspots in balancing ACE2 binding and antibody evasion. Using the ensemble-based mutational scanning of the spike protein residues and computations of binding affinities, we identified binding energy hotspots and characterized the molecular basis underlying epistatic couplings between convergent mutational hotspots. The results suggested the existence of epistatic interactions between convergent mutational sites at L455, F456, Q493 positions that protect and restore …

Enhancing Cardiomyocyte Resilience To Ischemia-Reperfusion Injury: The Therapeutic Potential Of An Indole-Peptide-Tempo Conjugate (Iptc), Shanshan Hou, Xin Yan, Xiang Gao, Steffen Jockusch, K. Michael Gibson, Zhiying Shan, Lanrong Bi

Michigan Tech Publications

Ischemia/reperfusion (I/R) injury leads to apoptosis and extensive cellular and mitochondrial damage, triggered by the early generation and subsequent accumulation of mitochondrial reactive oxygen species (mtROS). This condition not only contributes to the pathology of I/R injury itself but is also implicated in a variety of other diseases, especially within the cardiovascular domain. Addressing mitochondrial oxidative stress thus emerges as a critical therapeutic target. In this context, our study introduces an indole-peptide-tempo conjugate (IPTC), a compound designed with dual functionalities: antioxidative properties and the ability to modulate autophagy. Our findings reveal that IPTC effectively shields H9C2 cardiomyocytes against hypoxia/reoxygenation (H/R) …

Luminescence, Esr And Cl Characterisation Of Quartz Extracted From Granite Source Rocks And The Derived Sediments Used For Provenance Studies, Daniela Constantin, Aditi Dave, Serban Grecu, Zuzanna Kabacińska, Mihai Ducea, Petru Urdea, Alida Timar-Gabor

FRONTIERS UNBOUND: Exploring Extreme Environments

No abstract provided.

Revisiting The Chronology Of Loess In North America By Using Sar-Osl And Pirir Protocols, Anca Avram

FRONTIERS UNBOUND: Exploring Extreme Environments

No abstract provided.

Preliminary Analysis Of Quartz Using Scanning Electron Microscopy Techniques, Serban Constantin Grecu, Alida Timar-Gabor

FRONTIERS UNBOUND: Exploring Extreme Environments

No abstract provided.

20 Years Of Repo Interest Rate Determination Using Ai: Global Trends And Africa, Takalani Rasalanavho, Henry Hondo, Kevin Julius, Marius Alembong, Sikelela Madonsela, Hossana Twinomurinzi

African Conference on Information Systems and Technology

This study investigated the application of artificial intelligence (AI) in determining repo interest rates, which play a vital role in guiding monetary policy, controlling inflation, and ensuring economic stability. Through a bibliometric review of research from 2004 to 2024, the findings highlight AI's transformative impact, particularly in forecasting, optimising repo rate decisions, and improving risk assessment for more effective monetary policy. However, the study also identifies a significant gap in AI usage for repo rate determination in African countries, with contributions largely limited to Ghana, Nigeria, Egypt, and South Africa. This underrepresentation poses a risk of Africa falling behind in …

Hraunrásir: Exploring And Studying The Steaming Lava Tubes Of Fagradalsfjall Volcano (Iceland), Francesco Sauro, Riccardo Pozzobon, Martina Cappelletti, Bogdan P. Onac, Ana Zelia Miller, Groq Birkefeldt Moller Pedersen, Tommaso Santagata

FRONTIERS UNBOUND: Exploring Extreme Environments

No abstract provided.