Physical Sciences and Mathematics Commons^™

Recent Advances In Electrochemical Impedance Spectroscopy-Based Pathogenic Bacteria Sensing, Tao Chen, Yuan-Hong Xu, Jing-Hong Li

Journal of Electrochemistry

Pathogenic bacteria have been throwing great threat on human health for thousands of years. Their real-time monitoring is in urgent need as it could effectively halt the spread of pathogenic bacteria and thus reducing the risk to human health. Up till now, diverse technologies such as electrochemistry, optics, piezoelectricity and calorimetry have been developed for bacteria sensing. Therein, electrochemical impedance spectroscopy (EIS)-based sensors show great potential in point-of-care bacterial analysis because of their low-cost, short read-out time, good reproducibility, and portable equipment construction. In this review, we will primarily summarize the typical applications of electrochemical impedance technology in bacteria sensing …

An Aptamer-Based Microelectrode With Tunable Linear Range For Monitoring Of K+ In The Living Mouse Brain, Yuan-Dong Liu, Jia-Run Li, Li-Min Zhang, Yang Tian

Journal of Electrochemistry

Potassium ion (K⁺) is widely involved in several physiopathological processes, and its abnormal changes are closely related to the occurrence of brain diseases of cerebral ischemia. In vivo acquirement of K⁺ variation is significant to understand the roles of K⁺ playing in brain functions. A microelectrode based on single-stranded DNA aptamers was developed for highly selective detection of K⁺ in brain, in which the aptamer probes were designed to contain an aptamer part for specific recognition of K⁺, an alkynyl group used for stable confinement of aptamer probe on the gold surface, and …

Unraveling The Neural Basis Of Emotions: Advancing Understanding With Ecologically Valid Paradigms And High-Resolution Intracranial Eeg, Tiankang Xie

Dartmouth College Ph.D Dissertations

Background

Emotion arises from integrating information about the external world with memories of past experiences, current homeostatic states, and future goals. They play a vital role in regulating our thoughts, feelings and behaviors, significantly impacting our mental health. Thus, it is important to understand the neurobiological mechanisms that give rise to emotions. While there has been considerable work investigating the neural basis of emotions, progress has been hampered by several methodological limitations. For example, prior work has relied on relatively simple and isolated stimuli, which often fail to effectively capture the dynamic and multifaceted nature of emotional experiences in real-life …

System-Characterized Artificial Intelligence Approaches For Cardiac Cellular Systems And Molecular Signature Analysis, Ziqian Wu

Dartmouth College Ph.D Dissertations

The dissertation presents a significant advancement in the field of cardiac cellular systems and molecular signature systems by employing machine learning and generative artificial intelligence techniques. These methodologies are systematically characterized and applied to address critical challenges in these domains. A novel computational model is developed, which combines machine learning tools and multi-physics models. The main objective of this model is to accurately predict complex cellular dynamics, taking into account the intricate interactions within the cardiac cellular system. Furthermore, a comprehensive framework based on generative adversarial networks (GANs) is proposed. This framework is designed to generate synthetic data that faithfully …

Internal Yoneda Ext Groups, Central H-Spaces, And Banded Types, Jarl Gunnar Taxerås Flaten

Electronic Thesis and Dissertation Repository

We develop topics in synthetic homotopy theory using the language of homotopy type theory, and study their semantic counterparts in an ∞-topos. Specifically, we study Grothendieck categories and Yoneda Ext groups in this setting, as well as a novel class of central H-spaces along with their associated bands. The former are fundamental notions from homological algebra that support important computations in traditional homotopy theory. We develop these tools with the goal of supporting similar computations in our setting. In contrast, our results about central H-spaces and bands are new, even when interpreted into the ∞-topos of spaces.

In Chapter …

N–((2–Acetylphenyl)Carbamothioyl)Benzamide: Synthesis, Crystal Structure Analysis, And Theoretical Studies, Akin Oztaslar, Hakan Arslan

Karbala International Journal of Modern Science

N–((2–Acetylphenyl)carbamothioyl)benzamide has been synthesized and characterized. The molecular conformation of the investigated compound is stabilized by C16–H16B⋅⋅⋅O2ⁱ (i: 1+x, y, z) intermolecular and C14–H14⋅⋅⋅S1, N2–H2⋅⋅⋅O2, and N2–H2⋅⋅⋅O1 intramolecular H–bonds. All DFT calculations have been implemented at the B3LYP level with the 6–311G(d,p) basis set. The optimized molecular structure parameters have been compared with the experimental one in the solid phase. The energy gap, global chemical reactivity descriptor parameters, MEP, Fukui functions, DoS, NLO, and NBO analysis were also computed and investigated. The intermolecular interactions and their energies are evaluated using Hirshfeld surface and energy framework analyses. To determine …

Eutectic Formation And Cutaneous Wound Healing By Binary Allantoin- Octadecenedioic Acid System, Syed Waqar Hussain Shah, Farah Ali, Iram Bibi, Kashif Ali, Neelam Pervaiz, Mariyum Yousaf

Karbala International Journal of Modern Science

Eutectic formation in allantoin-octadecenedioic acid system (AOM) has been studied. The binary phase diagram revealed the existence of eutectic at X_allantoin = 0.7. Dioic acid caused disruption of network in allantoin and induced defects, ultimately causing the reduction in crystallinity as shown by XRD and SEM analysis. The thermal stability in TGA graphs of allantoin was negligibly altered after mixture formation. Classical hydrogen bonding and alkyl interactions were predicted using software Avogadro and BIOVIA Discovery Studio. The functionalities involved in interactions taking place in the system were studied through in-depth FT-IR spectroscopy. The eutectic showed efficacy for cutaneous wound …

Applications Of Uavs In Mine Industry: A Scoping Review, Dang Tuyet Minh, Nguyen Ba Dung

Journal of Sustainable Mining

In recent years, a variety of technologies have improved mining operations. One of them is the Unmanned Aerial Vehicles (UAVs), the emerging technology that has been changing the mining process, boosting mining safety and productivity. The main purpose of this paper is to review the applications of UAVs in the mining industry based on the results of 113 research papers over the past twelve years, from 2010 to May 2022. The potential applications of UAVs in the mining industry are broad. Based on the paper identified, eight categories are used to classify UAV applications in the mining sector. The reviewed …

Structural Mapping Of The Base Stacks Containing Post-Transcriptionally Modified Bases In Rna, Zakir Ali, Sarabjeet Kaur, Teagan Kukhta, Abd Al-Aziz A Abu-Saleh, Ayush Jhunjhunwala, Abhijit Mitra, John F. Trant, Purshotam Sharma

Chemistry and Biochemistry Publications

Post-transcriptionally modified bases play vital roles in many biochemical processes involving RNA. Analysis of the non-covalent interactions associated with these bases in RNA is crucial for providing a more complete understanding of the RNA structure and function; however, the characterization of these interactions remains understudied. To address this limitation, we present a comprehensive analysis of base stacks involving all crystallographic occurrences of the most biologically relevant modified bases in a large dataset of high-resolution RNA crystal structures. This is accompanied by a geometrical classification of the stacking contacts using our established tools. Coupled with quantum chemical calculations and an analysis …

Exploring The Genotypic And Phenotypic Differences Distinguishing Lactobacillus Jensenii And Lactobacillus Mulieris, Adriana Ene, Swarnali Banerjee, Alan J. Wolfe, Catherine Putonti

Mathematics and Statistics: Faculty Publications and Other Works

Lactobacillus crispatus, Lactobacillus gasseri, Lactobacillus iners, and Lactobacillus jensenii are dominant species of the urogenital microbiota. Prior studies suggest that these Lactobacillus species play a significant role in the urobiome of healthy females. In our prior genomic analysis of all publicly available L. jensenii and Lactobacillus mulieris genomes at the time (n = 43), we identified genes unique to these two closely related species. This motivated our further exploration here into their genotypic differences as well as into their phenotypic differences. First, we expanded genome sequence representatives of both species to 61 strains, including publicly available …

Incorporation Of Carbon Dioxide Production And Transport Module Into A Soil-Plant-Atmosphere Continuum Model, Sahila Beegum, Wenguang Sun, Dennis Timlin, Zhuangji Wang, David Fleisher, Vangimalla R. Reddy, Chittaranjan Ray

Nebraska Water Center: Faculty Publications

Carbon dioxide release from agricultural soils is influenced by multiple factors, including soil (soil properties, soil-microbial respiration, water content, temperature, soil diffusivity), plant (carbon assimilation, rhizosphere respiration), atmosphere (climate, atmospheric carbon dioxide), etc. Accurate estimation of the carbon dioxide (CO₂) fluxes in the soil and soil respiration (CO₂ flux between soil and atmosphere) requires a process-based modeling approach that accounts for the influence of all these factors. In this study, a module for CO₂ production via root and microbial respiration and diffusion-based carbon dioxide transport is developed and integrated with MAIZSIM (a process-based maize crop growth …

Can You Answer This? - Exploring Zero-Shot Qa Generalization Capabilities In Large Language Models, Saptarshi Sengupta, Shreya Ghosh, Preslav Nakov, Prasenjit Mitra

Natural Language Processing Faculty Publications

The buzz around Transformer-based Language Models (TLMs) such as BERT, RoBERTa, etc. is well-founded owing to their impressive results on an array of tasks. However, when applied to areas needing specialized knowledge (closed-domain), such as medical, finance, etc. their performance takes drastic hits, sometimes more than their older recurrent/convolutional counterparts. In this paper, we explore zero-shot capabilities of large language models for extractive Question Answering. Our objective is to examine the performance change in the face of domain drift, i.e., when the target domain data is vastly different in semantic and statistical properties from the source domain, in an attempt …

Wildlife Ecological Risk Assessment In The 21st Century: Promising Technologies To Assess Toxicological Effects, Barnett A. Rattner, Thomas G. Bean, Val R. Beasley, Philippe Berny, Karen M. Eisenreich, John E. Elliott, Margaret L. Eng, Phyllis C. Fuchsman, Mason D. King, Rafael Mateo, Carolyn B. Meyer, Jason M. O'Brien, Christopher J. Salice

United States Geological Survey: Staff Publications

Despite advances in toxicity testing and the development of new approach methodologies (NAMs) for hazard assessment, the ecological risk assessment (ERA) framework for terrestrial wildlife (i.e., air‐breathing amphibians, reptiles, birds, and mammals) has remained unchanged for decades. While survival, growth, and reproductive endpoints derived from whole-animal toxicity tests are central to hazard assessment, nonstandard measures of biological effects at multiple levels of biological organization (e.g., molecular, cellular, tissue, organ, organism, population, community, ecosystem) have the potential to enhance the relevance of prospective and retrospective wildlife ERAs. Other factors (e.g., indirect effects of contaminants on food supplies and infectious disease processes) …

Adversarial Alignment For Source Free Object Detection, Qiaosong Chu, Shuyan Li, Guangyi Chen, Kai Li, Xiu Li

Machine Learning Faculty Publications

Source-free object detection (SFOD) aims to transfer a detector pre-trained on a label-rich source domain to an unlabeled target domain without seeing source data. While most existing SFOD methods generate pseudo labels via a source-pretrained model to guide training, these pseudo labels usually contain high noises due to heavy domain discrepancy. In order to obtain better pseudo supervisions, we divide the target domain into source-similar and source-dissimilar parts and align them in the feature space by adversarial learning. Specifically, we design a detection variance-based criterion to divide the target domain. This criterion is motivated by a finding that larger detection …

Enabling Third Layer Bitcoin Applications Using Lightning Network, Ahmet Kurt

FIU Electronic Theses and Dissertations

When Bitcoin was introduced in 2009, it created a big sensation in the world as it was first of its kind. Since then, a lot of different cryptocurrencies were proposed. Today, cryptocurrencies can be used to pay for goods and services similar to using cash or credit cards. However, none of them could replace or supersede Bitcoin in usage or market capitalization. Current market conditions still imply that it will stay the same way. However, Bitcoin suffers from very low transaction per second (TPS) which limits its usability on large scale. There have been numerous proposals to increase its scalability …

Corruption-Tolerant Algorithms For Generalized Linear Models, Bhaskar Mukhoty, Debojyoti Dey, Purushottam Kar

Machine Learning Faculty Publications

This paper presents SVAM (Sequential Variance-Altered MLE), a unified framework for learning generalized linear models under adversarial label corruption in training data. SVAM extends to tasks such as least squares regression, logistic regression, and gamma regression, whereas many existing works on learning with label corruptions focus only on least squares regression. SVAM is based on a novel variance reduction technique that may be of independent interest and works by iteratively solving weighted MLEs over variance-altered versions of the GLM objective. SVAM offers provable model recovery guarantees superior to the state-of-the-art for robust regression even when a constant fraction of training …

Structural Mapping Of The Base Stacks Containing Post-Transcriptionally Modified Bases In Rna, Zakir Ali, Sarabjeet Kaur, Teagan Kukhta, Abd Al-Aziz A Abu-Saleh, Ayush Jhunjhunwala, Abhijit Mitra, John F. Trant, Purshotam Sharma

Chemistry and Biochemistry Publications

Post-transcriptionally modified bases play vital roles in many biochemical processes involving RNA. Analysis of the non-covalent interactions associated with these bases in RNA is crucial for providing a more complete understanding of the RNA structure and function; however, the characterization of these interactions remains understudied. To address this limitation, we present a comprehensive analysis of base stacks involving all crystallographic occurrences of the most biologically relevant modified bases in a large dataset of high-resolution RNA crystal structures. This is accompanied by a geometrical classification of the stacking contacts using our established tools. Coupled with quantum chemical calculations and an analysis …

Solving The Cable Equation, A Second-Order Time Dependent Pde For Non-Ideal Cables With Action Potentials In The Mammalian Brain Using Kss Methods, Nirmohi Charbe

Master's Theses

In this thesis we shall perform the comparisons of a Krylov Subspace Spectral method with Forward Euler, Backward Euler and Crank-Nicolson to solve the Cable Equation. The Cable Equation measures action potentials in axons in a mammalian brain treated as an ideal cable in the first part of the study. We shall subject this problem to the further assumption of a non-ideal cable. Assume a non-uniform cross section area along the longitudinal axis. At the present time, the effects of torsion, curvature and material capacitance are ignored. There is particular interest to generalize the application of the PDEs including and …

Waste Treatment Facility Location For Hotel Chains, Dolores R. Santos-Peñate, Rafael R. Suárez-Vega, Carmen Florido De La Nuez

ITSA 2022 Gran Canaria - 9th Biennial Conference: Corporate Entrepreneurship and Global Tourism Strategies After Covid 19

Tourism generates huge amounts of waste. About half of the waste generated by hotels is food and garden bio-waste. This bio-waste can be used to make compost and pellets. In turn, pellets can be used as an absorbent material in composters and as an energy source. We consider the problem of locating composting and pellet-making facilities so that the bio-waste generated by a chain of hotels can be managed at or close to the generation points. An optimization model is applied to locate the facilities and allocate the waste and products, and several scenarios are analysed. The study shows that, …

Instagram Travel Influencers Coping With Covid-19 Travel Disruption, Andrei Kirilenko, Katarzyna Emin, Karen Tavares

ITSA 2022 Gran Canaria - 9th Biennial Conference: Corporate Entrepreneurship and Global Tourism Strategies After Covid 19

A significant portion of today’s marketing is done through social media influencers, that is, through bloggers with established online credibility in a certain area who are recognized and followed by a sizable online audience. In the travel and hospitality industry, the influencer marketing is primarily done through Instagram due to its emphasis on visual images rather than texts. Covid-19 related travel restrictions and shrinking social media advertisement in travel industry have heavily impacted travel influencers, reducing their income and forcing many out of business. We present the outcomes of a study of the top 150 online travel influencers. The analysis …

Methods Of Magneto-Optical Spectroscopy And Analysis For Porphyrins And Polymer Thin-Films, Emigdio E. Turner

Chemistry and Chemical Biology ETDs

This dissertation describes the construction of two high precision magneto-polarimeters for performing Faraday rotation and Magnetic Circular Dichroism (MCD) measurements of polymer thin-films. There is a focus in materials science on the development of thin-film magneto-optically active materials. These materials could allow for the construction of a thin-film optical diode, an important device for next-generation photonic technology. Upon completion of the Faraday rotation spectrometer, two publications were generated from Faraday rotation measurements of novel polymer thin-film materials.

With growing interest by materials scientists in magneto-optically active transition-metal containing materials, an MCD spectrometer was constructed to study these materials. This spectrometer …

Stability-Based Generalization Analysis For Mixtures Of Pointwise And Pairwise Learning, Jiahuan Wang, Jun Chen, Hong Chen, Bin Gu, Weifu Li, Xin Tang

Machine Learning Faculty Publications

Recently, some mixture algorithms of pointwise and pairwise learning (PPL) have been formulated by employing the hybrid error metric of “pointwise loss + pairwise loss” and have shown empirical effectiveness on feature selection, ranking and recommendation tasks. However, to the best of our knowledge, the learning theory foundation of PPL has not been touched in the existing works. In this paper, we try to fill this theoretical gap by investigating the generalization properties of PPL. After extending the definitions of algorithmic stability to the PPL setting, we establish the high-probability generalization bounds for uniformly stable PPL algorithms. Moreover, explicit convergence …

Ultracold Neutral Plasma Evolution In An External Magnetic Field, Chanhyun Pak

Theses and Dissertations

We study the expansion velocity and ion temperature evolution of ultracold neutral plasmas (UNPs) of calcium atoms under the influence of a uniform magnetic field that ranges up to 200 G. In the experiments, we use a magneto-optical trap (MOT) to capture the neutral atoms and laser-induced fluorescence (LIF) to take images of the plasma. We vary the magnetic field strengths and the initial electron temperatures and observe the plasma evolution in time. We compare the ion temperature evolution to the theory introduced in the paper by Pohl et. al. [Phys. Rev. A 70, 033416 (2004)]. The evolution of the …

Skin Permeation Studies Of Chromium Species - Evaluation Of A Reconstructed Human Epidermis Model., L Hagvall, M Munem, M Hoang Philipsen, M Dowlatshahi Pour, Yolanda S. Hedberg, P Malmberg

Chemistry Publications

A reconstructed human epidermis (RHE) model, the EpiDerm, was investigated and compared to human skin ex vivo regarding tissue penetration and distribution of two chromium species, relevant in both occupational and general exposure in the population. Imaging mass spectrometry was used in analysis of the sectioned tissue. The RHE model gave similar results compared to human skin ex vivo for skin penetration of Cr

Class-Independent Regularization For Learning With Noisy Labels, Rumeng Yi, Dayan Guan, Yaping Huang, Shijian Lu

Computer Vision Faculty Publications

Training deep neural networks (DNNs) with noisy labels often leads to poorly generalized models as DNNs tend to memorize the noisy labels in training. Various strategies have been developed for improving sample selection precision and mitigating the noisy label memorization issue. However, most existing works adopt a class-dependent softmax classifier that is vulnerable to noisy labels by entangling the classification of multi-class features. This paper presents a class-independent regularization (CIR) method that can effectively alleviate the negative impact of noisy labels in DNN training. CIR regularizes the class-dependent softmax classifier by introducing multi-binary classifiers each of which takes care of …

Said-Ball Polynomials For Solving Linear Systems Of Ordinary Differential Equations, Mubark Al-Subaai Dr., Ahmes Saleh Kherd

Emirates Journal for Engineering Research

Said-Ball polynomials with collocation method are used to numerically solve a system of linear ordinary differential equations. The matrix forms of Said-Ball polynomials of the solution, derivatives, and conditions are done. The linear system of ordinary differential equations with appropriate conditions is reduced to the linear algebraic equations system with unknown Said-Ball coefficients. Solving the resulting system determines the coefficients of Said-Ball polynomials. By Substituting these values in the polynomial, we get the problem's exact and approximate solutions. The obtaining numerical results show the proposed method's accuracy and reliability when compared with the other works and exact solutions

Graphprompt: Graph-Based Prompt Templates For Biomedical Synonym Prediction, Hanwen Xu, Jiayou Zhang, Zhirui Wang, Shizhuo Zhang, Megh Bhalerao, Yucong Liu, Dawei Zhu, Sheng Wang

Computer Vision Faculty Publications

In the expansion of biomedical dataset, the same category may be labeled with different terms, thus being tedious and onerous to curate these terms. Therefore, automatically mapping synonymous terms onto the ontologies is desirable, which we name as biomedical synonym prediction task. Unlike biomedical concept normalization (BCN), no clues from context can be used to enhance synonym prediction, making it essential to extract graph features from ontology. We introduce an expert-curated dataset OBO-syn encompassing 70 different types of concepts and 2 million curated concept-term pairs for evaluating synonym prediction methods. We find BCN methods perform weakly on this task for …

Re: Approval For The Request For Change Bg-2023-01 To Final Bpsou Hydrocarbon Sampling And Treatability Study, Quality Assurance Project Plan (Qapp) (Dated May 15, 2023), Nikia Greene

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Comments For The Draft Residential Metals Abatement Program – Interior School Dust – Investigation Summary Report – Emerson Elementary (May 22, 2023), Nikia Greene

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Exploratory Data-Driven Models For Water Quality: A Case Study For Tampa Bay Water, Sandra Sekyere

USF Tampa Graduate Theses and Dissertations

Water, a crucial resource for sustaining life, covers approximately 70% of the earth's surface. Nonetheless, the quality of water is deteriorating rapidly due to the rapid growth of urban areas and industries, which is a worrying trend causing harm to human health and the ecosystem. Water quality forecasting has a key role in water resources management by enabling effective pollution control, ecosystem monitoring, and decision-making.

Previously, traditional statistical models were used to forecast water quality, but they were unable to examine the non-linear relationships between water quality parameters, and they assumed that all datasets were distributed normally. This study uses …