Digital Commons Network^™

Dna Origami-Assisted Regioselective Organization Of Anisotropic Gold Nanotriangle Clusters, Wenyan Liu, Prashant Gupta, Yuwei Zhang, Krishna Thapa, Srikanth Singamaneni, Risheng Wang

Chemistry Faculty Research & Creative Works

The manipulation of anisotropic nanoparticles, such as gold nanorods and nano prisms, has attracted great attention in nanotechnology due to their sensitive geometry-dependent properties. However. traditional synthesis and assembly methods for these particles face challenges in size uniformity and higher-order structuring. To address these limitations, this study presents a strategy using DNA origami triangles, not just as templates, but as encapsulating agents for gold nanotriangles (AuNTs). This method enables the construction of diverse nanoparticle clusters with precisely controlled distance and orientation. The formed clusters exhibit unique optical characteristics, demonstrated by UV-visible spectroscopy and supported by finite-difference time domain (FDTD) simulations. …

Selected Trace Element Uptake By Rice Grain As Affected By Soil Arsenic, Water Management And Cultivar -A Field Investigation, Eric M. Farrow, Jianmin Wang, Honglan Shi, John Yang, Bin Hua, Baolin Deng

Chemistry Faculty Research & Creative Works

Accumulation of arsenic (As) in rice grain was reported in many regions of the world, including the United States, which has been a threat to human health. This field research investigated the grain As accumulation and its relationship with the uptake of selenium (Se), molybdenum (Mo), and cadmium (Cd) in soils with and without monosodium methane arsonate (MSMA) amended, as effects of selected rice cultivars and water management. Results indicated that MSMA increased the accumulation of As and Se but decreased Mo for all six cultivars under four irrigation management. MSMA also increased grain-Cd in some cultivars. In no MSMA-amended …

High-Capacity Anode For Sodium-Ion Batteries Using Hard Carbons Derived From Polyurea-Cross-Linked Silica Xerogel Powders, Santhoshkumar Sundaramoorthy, Rushi U. Soni, Stephen Yaw Owusu, Sutapa Bhattacharya, A. B.M.Shaheen Ud Doulah, Vaibhav A. Edlabadkar, Chariklia Sotiriou-Leventis, Amitava Choudhury

Chemistry Faculty Research & Creative Works

In this article, we demonstrated carbon aerogel-silica composites derived from polyurea-cross-linked silica xerogel powders (C-PUA@silica) as anodes for Na-ion batteries. These xerogel-derived hard carbons with embedded silica showed a stable high capacity. Of the several hard carbon samples derived at different temperatures, the pyrolyzed sample at 800 °C (C-PUA@silica-800) showed a high capacity of 236 mAh/g at a current density of 10 mA/g and a stable cycle-life at 200 mAh/g. The galvanostatic charge-discharge curves displayed a sloping voltage profile reminiscent of the adsorption mechanism of Na+ storage. On the other hand, higher temperature-pyrolyzed samples at 1300 °C (C-PUA@silica-1300) displayed a …

Boosting The Microbial Electrosynthesis Of Formate By Shewanella Oneidensis Mr-1 With An Ionic Liquid Cosolvent, Ashwini Dantanarayana, Wassim El Housseini, Kevin Beaver, Monica Brachi, Timothy P. Mcfadden, Shelley D. Minteer

Chemistry Faculty Research & Creative Works

Microbial electrosynthesis (MES) is a rapidly growing technology at the forefront of sustainable chemistry, leveraging the ability of microorganisms to catalyze electrochemical reactions to synthesize valuable compounds from renewable energy sources. The reduction of CO₂ is a major target application for MES, but research in this area has been stifled, especially with the use of direct electron transfer (DET)-based microbial systems. The major fundamental hurdle that needs to be overcome is the low efficiency of CO₂ reduction largely attributed to minimal microbial access to CO₂ owing to its low solubility in the electrolyte. With their tunable physical …

Causal Disentangled Recommendation Against User Preference Shifts, Wenjie Wang, Xinyu Lin, Liuhui Wang, Fuli Feng, Yunshan Ma, Tat‑Seng Chua

Research Collection School Of Computing and Information Systems

Recommender systems easily face the issue of user preference shifts. User representations will become outof-date and lead to inappropriate recommendations if user preference has shifted over time. To solve theissue, existing work focuses on learning robust representations or predicting the shifting pattern. Therelacks a comprehensive view to discover the underlying reasons for user preference shifts. To understand thepreference shift, we abstract a causal graph to describe the generation procedure of user interaction sequences.Assuming user preference is stable within a short period, we abstract the interaction sequence as a set ofchronological environments. From the causal graph, we find that the changes …

Hardware-Assisted Live Kernel Function Updating On Intel Platforms, Lei Zhou, Fengwei Zhang, Kevin Leach, Xuhua Ding, Zhenyu Ning, Guojun Wang, Jidong Xiao

Research Collection School Of Computing and Information Systems

Traditional kernel updates such as perfective maintenance and vulnerability patching requires shutting the system down, disrupting continuous execution of applications. Enterprises and researchers have proposed various live updating techniques to patch the kernel with lower downtime to reduce the loss of useful uptime. However, existing kernel live update techniques either rely on specific support from the target OS, or are deployed in virtualized environments (i.e., systems running in virtual machines). In this article we present KShot , a hardware-assisted live and secure kernel function update mechanism for native operating systems. By leveraging x86 SMM and Intel SGX, KShot runs in …

Effects Of Mindfulness And Emotion Regulation On Aesthetics: A Theoretical Model From Hedonic Perspective Of Processing Fluency, Geng-Bao Lin, Fiona Fui-Hoon Nah, Choon Ling Sia

Research Collection School Of Computing and Information Systems

Research has shown that processing fluency positively impacts perceived aesthetics, with pleasure mediating the relationship. Considering the important role of pleasure, we propose studying the role of emotion regulation in moderating the mediated relationship from processing fluency to perceived aesthetics. Based on our hypotheses, individuals’ emotion regulation strategies are expected to have moderating effects on the relationship between processing fluency and perceived aesthetics such that cognitive reappraisal positively moderates the relationship from processing fluency to pleasure, and expressive suppression negatively moderates the relationship from pleasure to perceived aesthetics. Trait mindfulness is also expected to influence perceived aesthetics through emotion regulation …

Affinity Uncertainty-Based Hard Negative Mining In Graph Contrastive Learning, Chaoxi Niu, Guansong Pang, Ling Chen

Research Collection School Of Computing and Information Systems

Hard negative mining has shown effective in enhancing self-supervised contrastive learning (CL) on diverse data types, including graph CL (GCL). The existing hardness-aware CL methods typically treat negative instances that are most similar to the anchor instance as hard negatives, which helps improve the CL performance, especially on image data. However, this approach often fails to identify the hard negatives but leads to many false negatives on graph data. This is mainly due to that the learned graph representations are not sufficiently discriminative due to oversmooth representations and/or non-independent and identically distributed (non-i.i.d.) issues in graph data. To tackle this …

Continual Learning, Fast And Slow, Quang Anh Pham, Chenghao Liu, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

According to the Complementary Learning Systems (CLS) theory (McClelland et al. 1995) in neuroscience, humans do effective continual learning through two complementary systems: a fast learning system centered on the hippocampus for rapid learning of the specifics, individual experiences; and a slow learning system located in the neocortex for the gradual acquisition of structured knowledge about the environment. Motivated by this theory, we propose DualNets (for Dual Networks), a general continual learning framework comprising a fast learning system for supervised learning of pattern-separated representation from specific tasks and a slow learning system for representation learning of task-agnostic general representation via …

Remote Multi-Person Heart Rate Monitoring With Smart Speakers: Overcoming Separation Constraint, Ngoc Doan Thu Tran, Dong Ma, Rajesh Krishna Balan

Research Collection School Of Computing and Information Systems

Heart rate is a key vital sign that can be used to understand an individual’s health condition. Recently, remote sensing techniques, especially acoustic-based sensing, have received increasing attention for their ability to non-invasively detect heart rate via commercial mobile devices such as smartphones and smart speakers. However, due to signal interference, existing methods have primarily focused on monitoring a single user and required a large separation between them when monitoring multiple people. These limitations hinder many common use cases such as couples sharing the same bed or two or more people located in close proximity. In this paper, we present …

Flow Regimes In Bubble Columns With And Without Internals: A Review, Ayat N. Mahmood, Amer A. Abdulrahman, Laith S. Sabri, Abbas J. Sultan, Hasan Shakir Majdi, Muthanna H. Al-Dahhan

Chemical and Biochemical Engineering Faculty Research & Creative Works

Hydrodynamics characterization in terms of flow regime behavior is a crucial task to enhance the design of bubble column reactors and scaling up related methodologies. This review presents recent studies on the typical flow regimes established in bubble columns. Some effort is also provided to introduce relevant definitions pertaining to this field, namely, that of "void fraction" and related (local, chordal, cross-sectional and volumetric) variants. Experimental studies involving different parameters that affect design and operating conditions are also discussed in detail. In the second part of the review, the attention is shifted to cases with internals of various types (perforated …

Thermal Decomposition And Kinetic Parameters Of Three Biomass Feedstocks For The Performance Of The Gasification Process Using A Thermogravimetric Analyzer, Rania Almusafir, Joseph D. Smith

Chemical and Biochemical Engineering Faculty Research & Creative Works

Thermogravimetric analysis (TGA) is a powerful technique and useful method for characterizing biomass as a non-conventional fuel. A TGA apparatus has been utilized to experimentally investigate the impact of biomass feedstock diversity on the performance of the gasification of hardwood (HW), softwood (SW) pellets, and refuse-derived fuel (RDF) materials. The solid conversion rate and the volatile species formation rate have been estimated to quantify the rates of devolatilization for each material. In addition, the combustion kinetic characteristics of the three biomass feedstocks were investigated using TGA at different heating rates, and a thermal kinetic analysis was conducted to describe the …

Guiding Undergraduate Researchers In The Virtual World: Mentoring Experiences Of Globally Distributed Students, Emily Faulconer, Brent Terwilliger, Robert Deters, Kelly George

Publications

The advancement of technology has led to an increase in undergraduate students pursuing degrees online. The translation of undergraduate research to the online environment is relatively new, though gaining momentum, partly due to the COVID-19 pandemic. Mentoring is a key undergraduate research support, particularly for those engaged online, as it fosters a supportive environment for online students to develop their skills and knowledge in their field of study. This study aims to explore the positive impacts of mentoring undergraduate research for fully online students. A single case study methodology was used, with interview data collected from four research mentees completing …

Acalypha Indica Aqueous Leaf Extract As Potential Nematicide Against The Root-Knot Nematode, Meloidogyne Incognita: In Vitro And Molecular Docking Studies, Altaf Khan, Manar Fawzi Bani Mfarrej, Fohad Mabood Husain, Qamar Zia, Mohd Adil, Mohammed Arshad, Khalid Umar, Niraj Kumar Jha, Pieter Malan, Soumya Pandit, Faheem Ahmad

All Works

Root-knot nematode (RKN) (Meloidogyne incognita) is a major plant parasitic nematode that severely damages crops, leading to significant yield losses and substantial economic impact globally. This study aims to investigate an environmentally sustainable biological strategy for mitigating parasitic populations of the root-knot nematode, M. incognita. Specifically, the research focuses on assessing the nematicidal efficacy of Acalypha indica against M. incognita mortality and second-stage juveniles’ (J2) hatching under controlled in vitro conditions. A. indica leaf aqueous extract was applied at varying concentrations (250, 500, 750, and 1000 ppm) to J2s and egg masses of M. incognita. Notably, at 1000 ppm, a …

Investigating The Environmental Impact Of Tesla’S Electric Vehicles Compared To Fossil Fuel Vehicles., Bayezid Han Kulak

Business ETD Collections

Emphasizing production techniques, emissions, and competitive strategies, this project examines the environmental effects of Tesla's electric vehicles (EVs) relative to conventional internal combustion engine (ICE) automobiles. Leading in the EV market as the automotive sector moves toward sustainable practices is Tesla. Still, evaluating the environmental advantages of Tesla cars calls for a thorough investigation going beyond zero tailpipe pollution. This paper looks at the high energy consumption and environmental effects related to the manufacturing of Tesla batteries including cobalt and lithium mining. Emphasizing less greenhouse gas emissions than ICE vehicles, it also assesses the total emissions of Tesla vehicles over …

Analyzing The Impact Of Negative Publicity About Employee Turnover On Customer Loyalty: A Case Study Of Amazon., Nyambane Abedinego Nyambwengi

Business ETD Collections

This study examines the effect of negative publicity regarding employee turnover on customer loyalty, focusing on Amazon. Using in-depth interviews and surveys, the research highlights how social media platforms, particularly Facebook, and digital communication have facilitated the spread of negative information about Amazon's high employee turnover. While findings suggest that persistent negative media coverage could erode customer confidence over time, no statistical correlation between high turnover, negative publicity, and customer loyalty was established due to an insufficient sample size. The study recommends robust public relations strategies to protect corporate reputation and contributes to the understanding of how internal organisational issues …

Investigating Drought Response And Paleoclimate Potential Of A New Network Of White Oak Chronologies In Western Kentucky, Usa, Audrey J. Heichelbech, Maegen L. Rochner, Megan Gibson

Undergraduate Research Events

In Kentucky, historic and paleo-climate data are limited, and current understanding of long-term climate change in the state relies on instrumental data spanning only 1895-present. Proxy data are necessary to extend the temporal and spatial span of climate information. One potential proxy source for Kentucky is tree ring data, but currently, only four such datasets are publicly available on the International Tree Ring Data Bank (ITRDB). Archaeological and archival timber sources may help to fill in this gap. In the 1940s, Florence Hawley-Ellis, the first woman dendrochronologist, collected samples of white oak (Quercus alba L.) from four counties in western …

Critical Conversations Of Engaging Withthe Amte Standards, Eva Thanheiser, Jennifer Bay-Williams, Richard Velasco, Liza Bondurant

Mathematics and Statistics Faculty Publications and Presentations

This article is based on an opening plenary session at the Association of Mathematics Teacher Educators (AMTE) 2024 conference in Orlando, Florida, USA. The authors, who delivered the plenary in a panel format, focus specifically on the AMTE standard indicator that addresses power and privilege. This article is the product of the five authors reflecting on their panel and discussing its contents—in the form of this manuscript—with an external Open Reviewer. The result is a “quintalog” of the five authors in critical conversation with each other about their own reflections on the ways in which mathematics teacher educators and the …

The Attitudes And Practices Of United Arab Emirates Consumers Towards Food Waste: A Nationwide Cross-Sectional Study, Lynne Kennedy, Samir Safi, Tareq M. Osaili, Ala Al Rajabi, Ayesha Alblooshi, Dima Al Jawarneh, Ahmed Al Kaabi, Fakhra Al Rubaei, Maitha Albreiki, Maryam Alfadli, Aseilah Alhefeiti, Moez Al Islam Ezzat Faris, Kholoud Allaham, Sameeha Junaidi, Moien A.B. Khan

All Works

Background: Reducing global food waste is an international environmental, health, and sus-tainability priority. Although significant reductions have been achieved across the food chain, progress by UAE households and consumers remain inadequate. This study seeks to understand the association between consumer attitudes, knowledge, and awareness relating to food waste practice of residents living in the UAE. to help inform policy and action for addressing this national priority. Methods: A cross-sectional study was conducted using a validated semi-structured online questionnaire through stratified sampling (n =1052). The Spearman correlation coefficient was performed to determine the correlations. Two independent regression analysis were used to …

Petrologic And Geochemical Constraints On The Pre-Eruptive Storage Conditions Of Magmas Erupted During The ~12.5 Ka Flare Up Of Medicine Lake Volcano, Ca, Regina M. Khoury

Cal Poly Humboldt theses and projects

The Medicine Lake Volcano (MLV) system in the California Cascades is composed of a large shield volcano with numerous basaltic to rhyolitic vents on and around the flanks, many of which are aligned with N-S trending normal faults. A significant portion of the post-glacial volcanic activity at MLV is comprised of the ~12.5 ka “flare up” eruptions of basalt and basaltic andesite magmas from seven discrete flank vents. Prior work documented surface areas (0.02-198 km²), volumes (0.0001-4.35 km³), and eruption styles (Hawaiian to Strombolian; Donnelly-Nolan, 2010) of the ~12.5 ka deposits. This study uses new geologic …

The Anti-Inflammatory And Antioxidant Effects Of Melissa Officinalis (Lemon Balm)On Paracetamol Induced Hepatotoxicity In Broiler Chickens, Ghada A. Abou Zead, Sara T. Elazab, Azza E. Hassan, Ahmed I. Ateya, Magdy S. Amer

Mansoura Veterinary Medical Journal

background : This study aimed to investigate the hepatoprotective effects of Melissa officinalis (M officinalis) against paracetamol N-acetyl-p-aminophenol (APAP)-induced hepatotoxicity in broiler chickens. METHODS: A total of 48 one-day-old cobb healthy chicks were divided into four groups of (12 chicks). The control group received a basal diet for 21 days, while the APAP group received APAP at 2 g/kg body weight daily from the 15th day onwards and until the termination of the experiment; M officinalis + APAP group was offered a 10 g/kg diet for 2 weeks followed by APAP for one week; and the APAP + M officinalis …

Enhancing Security And Performance In Vehicular Adhoc Networks: A Machine Learning Approach To Combat Adversarial Attacks, Mustafa Abdulfattah Habeeb, Yahya Layth Khaleel, Ahmed Raheem Abdulnabi

Mesopotamian Journal of Computer Science

Integrating Machine Learning (ML) techniques into Vehicular Adhoc Networks (VANETs) provides promising features in autonomous driving and ITS applications. In this paper, DSRC data is used to evaluate the effectiveness of different ML models, including Naive Bayes, Random Forest, KNN, and Gradient Boosting, in normal and adversarial scenarios. Since the dataset is relatively imbalanced, the Synthetic Minority Over-sampling Technique (SMOTE) is employed for sampling, and defensive distillation for improving model resilience to adversarial perturbations. From the results, it is clear that models such as Gradient Boosting and Random Forest show high accuracy in both cases, thus showing the potential of …

Distribution System Losses Allocation Based On Circuit Theory With Distributed Generation, Ahmed S. Abdelkader, Ibrahim I. Mansy, Abdelfattah A. Eladl

Mansoura Engineering Journal

Electricity energy is the most convenient and efficient form of energy transmission and conversion. Nonetheless, losses take place while electrical power is traveling from power stations through transmission and distribution networks to the loads. Despite the high efficiency of electrical transmission and distribution networks, the huge amounts of power moving through these networks make the financial loss due to the lost energy very high and its management becomes a critical consideration for both utility providers and regulatory bodies. The efficient management of losses encompasses two major functions: the first is running the system in a way that minimizes the losses; …

A Decision-Making Approach To Reduce The Risk Of Measurement Uncertainty For Product Size, Mostafa Awadalla Sedeek, Fatma Abdallah Elerian, Ossama Badie Abouelatta, Mona. A. Aboueleaz

Mansoura Engineering Journal

The measurement uncertainty has a significant impact on quality control processes. This is particularly true of standards that are assessed to determine if a product is compliant. This ambiguity introduces two potential risks of decision-making: accepting a non-conventional product (the consumer's risk) or rejecting a conventional product (the producer's risk). This investigation explores the potential for false decisions caused by measurement errors in product assessments. By studying data near the control limits, a greater understanding of the manufacturing process is intended to facilitate informed decision-making, and guide the implementation of effective quality control methods. The investigation highlights the importance of …

Minimizing The Production Cost Of The Cam-Follower Profile Using Shape Optimization Techniques, Khaled Ahmed, Magdy Samuel, Rania Mostafa

Mansoura Engineering Journal

The study of shape optimization techniques in structural products helps in reducing mechanical stresses and vibrations in related mechanical elements, such as cam follower mechanisms. This, in turn, has a positive impact on cost savings in the manufacturing process and enhances production quality and reliability. The point of view in this research depends on the idea of minimizing the total production cost while ensuring good functional performance of the cam profile during the shape-manufacturing optimization problem-solving process. The investigation of the impact of changing the motion type of a cam, such as Uniform Velocity Motion (UVM) and Simple Harmonic Motion …

The Impact Of Performance Based Funding On Institutional Financial Priorities In Public Two-Year And Four-Year Institutions, Ebony T. Spearman

Master's Theses and Doctoral Dissertations

This dissertation examines the impact of performance-based funding (PBF) policies on institutional financial priorities at 2-and 4-year colleges and universities. PBF is a policy mechanism used by states to incentivize higher education institutions to achieve specific performance outcomes, such as increased graduation and retention rates, by tying a portion of institutional funding to these outcomes. This research aims to determine the efficacy of PBF policies on institutional change and outcomes. More specifically, this research seeks to find the extent to which colleges and universities subjected to PBF policies change their financial priorities and how, if at all, these changes impact …

2024-2025 Undergraduate Catalog, Morehead State University. Registrar's Office.

Morehead State Catalog Archive

2024-2025 undergraduate catalog for Morehead State University.

Using Unsupervised Learning Methods In Extracting Features For Classifying Rice Varieties From Rice Grains Images., Kevin Anthony Martinez

ICT

Rice, a staple food for nearly half of the global population, requires accurate classification of its varieties to ensure food quality, support agricultural trade, and enhance yield optimisation. Traditional manual classification methods are time-intensive and error-prone, prompting this study's exploration of unsupervised learning for feature extraction from rice grain images. The research tested classifiers on 75,000 rice samples across five classes, with 15,000 samples per class.

The study's DCGAN-CNN model achieved the highest classification accuracy of 99.67%. However, the PCA-CNN model underperformed, with only 20% accuracy, due to implementation errors. Recommendations for improvement include optimising model parameters such as learning …

A Comparative Study On Feature Extraction Techniques For The Discrimination Of Frontotemporal Dementia And Alzheimer's Disease With Electroencephalography In Resting-State Adults, Utkarsh Lal, Arjun Vinayak Chikkankod, Luca Longo

Articles

Early-stage Alzheimer's disease (AD) and frontotemporal dementia (FTD) share similar symptoms, complicating their diagnosis and the development of specific treatment strategies. Our study evaluated multiple feature extraction techniques for identifying AD and FTD biomarkers from electroencephalographic (EEG) signals. We developed an optimised machine learning architecture that integrates sliding windowing, feature extraction, and supervised learning to distinguish between AD and FTD patients, as well as from healthy controls (HCs). Our model, with a 90% overlap for sliding windowing, SVD entropy for feature extraction, and K-Nearest Neighbors (KNN) for supervised learning, achieved a mean F1-score and accuracy of 93% and 91%, 92.5% …

A Contribution To The Exploration Of The Chemical Durability, Thermal Stability, And Structural Ability Of Glasses From The Fe2o3-K2o-Moo3-P2o5 Quaternary System, Asmae Er-Rafai, Yasmina Alaoui, Mohamed Laourayed, Mohamed Ounacer, Mouloud El Moudane, Mohammed Sajieddine, Abdelkbir Bellaouchou

Journal of Metals, Materials and Minerals

The relationships between the properties and structure of xFe2O3-(40-x)K2O-10MoO3-50P2O5 glasses have been reported in this paper. Homogeneous glasses are formed for different Fe2O3 contents. The density and molar volume evolution of these glasses shows that Fe2O3 acts as a glass former and strengthens the structural bonds of the glass. Experimental 57Fe Mössbauer spectroscopy graphs suggest the existence of divalent Iron (FeII) and trivalent Iron (FeIII). The boost in chemical durability agrees with the growth in glass transition temperature due to more powerful bonding in the structural network. P-O-Fe bonds replace P-O-P bonds when Fe2O3 is present in the phosphate network.