Physical Sciences and Mathematics Commons^™

Assessing Wood Jam Formation In The South Fork Elk River In Headwaters Forest Reserve, California, Grant D. Bruchacek, Mark W. Buckton, Gus R. Figueroa, Kevin J. Hill

Undergraduate Scholarship

Salmonids are considered keystone species and play an integral role in the health of river ecosystems. Many of these species are federally recognized as threatened due to habitat loss and degradation. Large woody debris in streams and rivers creates suitable refugia and spawning habitat for salmonid species. Between 2021-2023 the Bureau of Land Management placed approximately 200 pieces of wood into the South Fork Elk River, as part of their accelerated recruitment program in an effort to reintroduce habitat complexity. A survey was conducted on a stretch of the Elk River to gather information on the size, type, composition, and …

A Cotyledon-Based Virus-Induced Gene Silencing (Cotyledon-Vigs) Approach To Study Specialized Metabolism In Medicinal Plants, Yongliang Liu, Ruiqing Lyu, Joshua Singleton, Barunava Patra, Sitakanta Pattanaik, Ling Yuan

Plant and Soil Sciences Faculty Publications

Background Virus-induced gene silencing (VIGS) is widely used in plant functional genomics. However, the efficiency of VIGS in young plantlets varies across plant species. Additionally, VIGS is not optimized for many plant species, especially medicinal plants that produce valuable specialized metabolites.

Results We evaluated the efficacy of five-day-old, etiolated seedlings of Catharanthus roseus (periwinkle) for VIGS. The seedlings were vacuum-infiltrated with Agrobacterium tumefaciens GV3101 cells carrying the tobacco rattle virus (TRV) vectors. The protoporphyrin IX magnesium chelatase subunit H (ChlH) gene, a key gene in chlorophyll biosynthesis, was used as the target for VIGS, and we observed yellow cotyledons 6 …

Enhancing 21 U.S.C. §§ 355, 356, And 360 To Encompass Artificial Intelligence-Based Drug Design And Manufacturing Methods, Aj Tsang

Michigan Technology Law Review

Despite newfound attention to how artificial intelligence (AI) may accelerate pharmaceutical development, federal regulators may find that current statutes are ambiguous or silent about their applicability to AI-based drug design and manufacturing methods. This poses a serious problem in the era of Loper Bright and the Major Questions Doctrine. As federal agencies struggle to adjust to courts’ growing demand for Congress to craft clear, explicit, and express delegations of authority, this note develops a statutory framework in which the Food and Drug Administration (FDA) would have more flexibility to regulate the use of AI in advanced drug manufacturing. Guided by …

Braving The Elements: Loss Of Metals From Mardi Gras Beads Due To Handling And Weathering, Thomas O. Carmichael, Ruth H. Carmichael

Gulf and Caribbean Research

The largest Mardi Gras celebrations in the U.S. are found along the Gulf of Mexico coast. With increasing awareness of and concern for environmental and human health risks due to pollution from Mardi Gras celebrations, there is a need for studies to quantify potential harms. We conducted a 2—part study to determine whether use—related handling and weathering of common Mardi Gras beaded necklaces results in loss of potentially harmful metals to the environment at levels of ecological or human health concern. Our data indicate that weathering and use—related handling can cause metals to be shed from the metallic coating of …

Applying The Disaster Risk Assessment Framework To Sargassum Inundation In Barbados, A. Karima Degia, Micaela Small, Hazel A. Oxenford

Gulf and Caribbean Research

Episodic influxes of pelagic Sargassum into the Caribbean result in inundation of coastlines with significant negative impacts to the environment, society, and economy. The spatial complexities of this issue demand a strategy that combines spatial planning with an analytical framework that can systematically unpack the underlying factors to inform effective management. We test the application of the United Nations Disaster Risk Reduction (UNDRR) conceptual framework for disaster risk assessment to Sargassum inundation, with a focus on the hazard and exposure components of risk, using Barbados, a Caribbean Small Island Developing State (SIDS), as a case study. We first consider in …

Summer Research Fellowship Project Descriptions 2024, Clark Science Center's Summer Research Fellows Program

SURF Abstracts (Women in Science)

A summary of research done by Smith College’s 2024 Summer Research Fellowship (SURF) Program participants. Ever since its 1967 start, SURF has been a cornerstone of Smith’s science education. Supervised by faculty mentor-advisors drawn from the Clark Science Center and connected to its eighteen science, mathematics, and engineering departments and programs and associated centers and units. At summer’s end, SURF participants were asked to summarize their research experiences for this publication.

Evaluation Of Physicochemical Properties Of Chicken Sausages Containing Whey Protein Isolate And Guar Gum, Nur Hamizah Hamid, Namasivayam Navaranjan

ASEAN Journal on Science and Technology for Development

The present work aims to evaluate the physicochemical properties and proximate composition of adding whey protein isolate (WPI) and guar gum (GG) as emulsion gels in chicken sausages formulated with different fat percentages. The fat reduction resulted in products having lower moisture content (p

Preliminary Study On The Effects Of Vinegar As Pre- Treatment For The Oven-Drying Of Pacific Yellowtail Emperor (Lethrinus Atkinsoni) Fillets, Nurisa A. Suhaili, Rafael S. Jamih, Normina A. Abubakar, Jaro O. Ajik, Merilyn Q. Amlani

ASEAN Journal on Science and Technology for Development

This study aimed to assess the impact of various vinegar compositions used as pre-treatment for Pacific Yellowtail Emperor (PYE) fillets during the oven-drying process, with a focus on moisture content and optimal drying conditions. Two types of commercially available vinegar, Superior Vinegar and Datu Puti Vinegar, were compared, and different drying temperatures were evaluated. The investigation revealed that the drying temperature significantly influenced the moisture content of the dried PYE fillets. Among the tested temperatures (40°C, 60°C, and 80°C), the most favorable outcome in terms of moisture content was achieved when fillets were dried at 80°C for a duration of …

Application Of Three Of Selected Medicinal Plant Extracts In Brunei Darussalam To Improve Shelf Life Of Poultry Product, Hazirah Abd Hamid, Namasivayam Navaranjan, Zohrah Sulaiman, Aida Maryam Binti Hj Basri

ASEAN Journal on Science and Technology for Development

Abstract. Bioactive compounds from plant derived in food application become increasingly in demand due to natural and nutritionally safe products. Due to some issues concerning food safety on the excessive use of synthetic preservatives; the present study aims to investigate the natural alternatives to synthetic antimicrobial food additives. The chicken meat’s shelf life was studied by adopting bio-based antimicrobial agents using three of selected native medicinal plants; P. betle, A. catechu, and A. tricolor, against common foodborne pathogens; E. coli, P. aeruginosa, S. aureus, and Salmonella spp. The overall results revealed that, all study extracts possessed antioxidant properties by DPPH …

Byproducts Of Tropical Marine Processing As A Candidate For Industrial Food Ingredients: An Appraisal On Macro And Micronutrients, Abdul Aziz Jaziri, Hajariah Hasanuddin, Rossita Shapawi, Ruzaidi Azli Mohd Mokhtar, Wan Norhana Md. Noordin, Masmunira Rambli, Nurul Huda

ASEAN Journal on Science and Technology for Development

Tropical marine fish is a main raw material for surimi processing plants, including golden threadfin bream (Nemipterus virgatus Houttuyn, 1782) and swallowtail dwarf monocle bream (Parascolopsis eriomma Jordan & Richardson, 1909). After processing, more than 60% of fish are considered as byproducts (i.e., head, viscera, skin, bones, fins and scale), and tend to discard due to poor-utilization. Hence, this paper aims to evaluate macro- and micro-nutrients derived from golden threadfin bream (GTB) and swallowtail dwarf monocle bream (SDMB). The higher content of protein (25.31 ± 0.81%) was observed in the skin part of GTB, followed by the flesh (21.26 ± …

Release Behavior Of Butterfly Pea Anthocyanins From Sago Starch Micro-Composite Films Under Food Stimulants, Afiqah Nabihah Ahmad, Eng Tong Phuah, Namasivayam Navaranjan, Syazana Abdullah Lim

ASEAN Journal on Science and Technology for Development

This study investigates the release behaviour of Butterfly Pea (BP) anthocyanins from Sago starch micro-composite (SMC) films in the presence of food stimulants. To comprehensively describe the release profiles of BP from SMC, six well-established kinetic release models were employed which includes Korsmeyer-Peppas, zero-order, first-order, second-order, Higuchi, and Hixson-Crowell models. These models played a crucial role in examining how the release fraction changes over time, facilitating a comprehensive understanding of the release kinetics of BP anthocyanins. Our data analysis revealed a strong conformity with the Korsmeyer-Peppas model, suggesting its applicability in describing the release of BP anthocyanins from SMC. The …

A Gold Mine: The Importance Of Information And Communication Technology (Ict) On Bank Liquidity In Asia And The Pacific, Sarmila Udin, Imbarine Bujang, Nancy Chiuh Noemi

ASEAN Journal on Science and Technology for Development

Financial systems are the entities in charge of promoting, growing, and enhancing economic growth and development. To be viable in the market, financial institutions must maintain enough liquid assets to meet any unforeseen demand from customers at any time needed. Currently, banks are pursuing cutting-edge technologies to survive and thrive in an ever-changing market environment. This paper aims to examine the relationship between information and communication technology (ICT), macroeconomics and bank liquidity risk in Asia and the Pacific. The research took place between 2012 and 2018 and the nations were chosen based on data availability; as a result, the sample …

Interest Rate Mismatches In Indian Banking: Causes, Strategies, And Implications, Baba Gnanakumar P, M.K. Baby, Ulaganathan Subramanian

ASEAN Journal on Science and Technology for Development

Despite the global trend of rising interest rates, India's Reserve Bank (RBI) has adopted a unique approach, emphasizing a rate pause and a solid anti-inflation stance. This unconventional strategy has sometimes led to periods of credit expansion, even during monetary tightening measures implemented by the RBI. One significant consequence of these policies is the widening gap between deposit and lending rates within the Indian banking sector. This research study aims to comprehensively analyze the implications of interest rate mismatches among Indian banks in this context. Specifically, the investigation focuses on the challenges posed by deposit and lending rate mismatches and …

Debunking Indian Neo-Banks' Customer Effort Score And Esg Values, Baba Gnanakumar P, Ulaganathan Subramanian, M.K. Baby

ASEAN Journal on Science and Technology for Development

Neo-banks in India are harnessing data analytics to address ESG risks, collaborating with various stakeholders, and striving to promote ESG values. Their endeavours not only enhance the customer experience but also contribute to a more sustainable and ethical financial system, with the potential to reduce the carbon footprint as digital banking gains traction in India. We examine whether ESG-rated banks can diminish customer effort and improve the overall customer experience, ultimately encouraging greater participation in sustainable financial practices. We employ text mining to analyse 2156 reviews of ESG-rated banks' digital services, from which we derive the Customer Effort Score. We …

Rule-In-Use For Community-Based Springs Management Faces Land Use Pressures: Lesson Learned From Manggarai District, Bernadinus Steni, Hariadi Kartodihardjo, Soeryo Adiwibowo, Ruchyat Deni Djakapermana

The Indonesian Journal of Socio-Legal Studies

The struggle for water is one of the greatest immediate risks of the climate crisis. Therefore, the institutional challenge of water management is increasingly urgent and requires a number of consensuses to succeed, including community-based natural resource management (CBNRM). A key challenge to the traditional consensus for water conservation is the increasing need for land conversion due to population growth, which in turn deflects decision-making power away from traditional institutions towards external decision-makers such as regional governments. Using Ostrom's conceptual framework of rules of use, this research examines shifting spring water management in the context of Kabupaten Manggarai. The paper …

Combating Cyberbullying On Social Media: A Machine Learning Approach With Text Analysis On Twitter, Amir Alipour Yengejeh

Data Science and Data Mining

The popularity of the electronic mobile devices along with social media as well as networking websites have been tremendously increased in the recent year. Most people around the world daily engage in the variety of cyberspace additives. Even though the users can take most advantages of these system such as exchange the idea and information, being sociable, and enjoyments, they might be faced with such adverse behaviors such as toxicity, bullying, extremism, and cruelty. The recent statistics reports that such mentioned behaviors has been noticeably grown on the cyberspace such that can threaten the individuals and even any community. Thus, …

Xgboost Hyperberd Model Using Steam Platform, Yuh-Haur Chen

Data Science and Data Mining

This project investigates game pricing strategies in the Steam market using an XGBoost model, drawing motivation from Professor Xie's lecture, and presenting findings through a density plot that delineates two primary pricing strategies. A free-to-play approach, indicated by a significant hot spot, is adopted by developers focusing on post-purchase revenues through DLC, aesthetic purchases, and in-game transactions. This sailing strategy includes community-centric developers aiming to distribute their games for player engagement rather than profit.

The project illustrates the effectiveness of advanced modeling techniques in handling complex datasets, with significant predictive accuracy reflected by a reduced MSE from 0.3472 to 0.1397. …

Machine Learning Approaches For Cyberbullying Detection, Roland Fiagbe

Data Science and Data Mining

Cyberbullying refers to the act of bullying using electronic means and the internet. In recent years, this act has been identifed to be a major problem among young people and even adults. It can negatively impact one’s emotions and lead to adverse outcomes like depression, anxiety, harassment, and suicide, among others. This has led to the need to employ machine learning techniques to automatically detect cyberbullying and prevent them on various social media platforms. In this study, we want to analyze the combination of some Natural Language Processing (NLP) algorithms (such as Bag-of-Words and TFIDF) with some popular machine learning …

Advancing Cancer Classifcation Through Machine Learning Analysis Of Rna-Seq Gene Expression Data, Emil Agbemade, Amina Issoufou Anaroua, Dimitri Bamba

Data Science and Data Mining

This study delves into the classifcation of various cancer types using the RNA-Seq (HiSeq) PANCAN dataset from the UCI Machine Learning Repository, which encompasses a rich collection of gene expression data across multiple tumor samples. To improve cancer diagnosis and treatment, our methodology confronts the challenges inherent in high-dimensional datasets, such as the Hughes Effect and the Curse of Dimensionality, through innovative feature selection methods and machine learning approaches. A key component of our strategy includes the use of tree-based algorithms, particularly Random Forest, to refine the dataset to seventy genes of utmost relevance for tumor classifcation, and the application …

Bootstrap Regression For Investigating Macroeconomics Factors Affecting Usa Home Prices, Benedict Kongyir, Emil Agbemade

Data Science and Data Mining

This study investigates the impact of macroeconomic indicators on US home prices, underscoring the importance of understanding these dynamics due to their signifcant socioeconomic consequences. Utilizing a dataset from Kaggle, originally collected by FRED, the research examines variables like the Consumer Price Index, Population, Unemployment, GDP, Stock Prices, Income, and Mortgage Rate to discern their efect on housing market fuctuations. The analysis identifes multicollinearity among predictors, necessitating a shift from traditional multiple linear regression to a more robust bootstrap regression method due to violations of parametric assumptions. Key fndings reveal that Real Disposable Income is a signifcant predictor of home …

Predicting Superconducting Critical Temperature Using Regression Analysis, Roland Fiagbe

Data Science and Data Mining

This project estimates a regression model to predict the superconducting critical temperature based on variables extracted from the superconductor’s chemical formula. The regression model along with the stepwise variable selection gives a reasonable and good predictive model with a lower prediction error (MSE). Variables extracted based on atomic radius, valence, atomic mass and thermal conductivity appeared to have the most contribution to the predictive model.

Optimizing Ai With Advanced Data Structuring: A Comparative Analysis Of K-Means And Gmm Clustering Techniques, Amir Alipour Yengejeh

Data Science and Data Mining

This study presents a detailed comparison of Kmeans and Gaussian Mixture Model (GMM) clustering algorithms, illustrating their unique capabilities and limitations across various synthetic datasets. By utilizing metrics such as the Adjusted Rand Index (ARI) and Normalized Mutual Information (NMI), the research provides nuanced insights into how these algorithms handle datasets with varying structures and complexities. For instance, while both K-means and GMM show robust performance on well-separated clusters, GMM demonstrates a distinct advantage in scenarios with overlapping clusters or unbalanced data distributions. Conversely, K-means excels in identifying clear, distinct groupings, highlighting its utility in simpler clustering contexts. This study …

Extreme Ungrading: Rewilding The Classroom Through Human-Centered Design, Johanna Brewer

Computer Science: Faculty Publications

Assessment in computer science education has grown reliant on rigid rubrics and intensive exams, a practice that yields capable yet compliant coders. In this article, I explore how we might use human-centered design to reexamine contemporary pedagogy and redesign our classrooms to cultivate a different type of programmer, one with a more critically engaged eye. Inspired by the ethos of agile development, I offer an alternative evaluation paradigm: Extreme Ungrading. Exploring results of a two-year case study applying this method to a software engineering class, this article distills actionable guidelines for enhancing learning outcomes through inclusive course development, and seeks …

Predicting Viral Rumors And Vulnerable Users With Graph-Based Neural Multi-Task Learning For Infodemic Surveillance, Xuan Zhang, Wei Gao

Research Collection School Of Computing and Information Systems

In the age of the infodemic, it is crucial to have tools for effectively monitoring the spread of rampant rumors that can quickly go viral, as well as identifying vulnerable users who may be more susceptible to spreading such misinformation. This proactive approach allows for timely preventive measures to be taken, mitigating the negative impact of false information on society. We propose a novel approach to predict viral rumors and vulnerable users using a unified graph neural network model. We pre-train network-based user embeddings and leverage a cross-attention mechanism between users and posts, together with a community-enhanced vulnerability propagation (CVP) …

Quantifying The Competitiveness Of A Dataset In Relation To General Preferences, Kyriakos Mouratidis, Keming Li, Bo Tang

Research Collection School Of Computing and Information Systems

Typically, a specific market (e.g., of hotels, restaurants, laptops, etc.) is represented as a multi-attribute dataset of the available products. The topic of identifying and shortlisting the products of most interest to a user has been well-explored. In contrast, in this work we focus on the dataset, and aim to assess its competitiveness with regard to different possible preferences. We define measures of competitiveness, and represent them in the form of a heat-map in the domain of preferences. Our work finds application in market analysis and in business development. These applications are further enhanced when the competitiveness heat-map is used …

Efficient Privacy-Preserving Spatial Data Query In Cloud Computing, Yinbin Miao, Yutao Yang, Xinghua Li, Linfeng Wei, Zhiquan Liu, Robert H. Deng

Research Collection School Of Computing and Information Systems

With the rapid development of geographic location technology and the explosive growth of data, a large amount of spatial data is outsourced to the cloud server for reducing the local high storage and computing burdens, but at the same time causes security issues. Thus, extensive privacy-preserving spatial data query schemes have been proposed. Most of the existing schemes use Asymmetric Scalar-Product-Preserving Encryption (ASPE) to encrypt data, but ASPE has proven to be insecure against known plaintext attack. And the existing schemes require users to provide more information about query range and thus generate a large amount of ciphertexts, which causes …

Conversational Localization: Indoor Human Localization Through Intelligent Conversation, Sheshadri Smitha, Kotaro Hara

Research Collection School Of Computing and Information Systems

We propose a novel sensorless approach to indoor localization by leveraging natural language conversations with users, which we call conversational localization. To show the feasibility of conversational localization, we develop a proof-of-concept system that guides users to describe their surroundings in a chat and estimates their position based on the information they provide. We devised a modular architecture for our system with four modules. First, we construct an entity database with available image-based floor maps. Second, we enable the dynamic identification and scoring of information provided by users through our utterance processing module. Then, we implement a conversational agent that …

Conceptthread: Visualizing Threaded Concepts In Mooc Videos, Zhiguang Zhou, Li Ye, Lihong Cai, Lei Wang, Yigang Wang, Yongheng Wang, Wei Chen, Yong Wang

Research Collection School Of Computing and Information Systems

Massive Open Online Courses (MOOCs) platforms are becoming increasingly popular in recent years. Online learners need to watch the whole course video on MOOC platforms to learn the underlying new knowledge, which is often tedious and time-consuming due to the lack of a quick overview of the covered knowledge and their structures. In this paper, we propose ConceptThread , a visual analytics approach to effectively show the concepts and the relations among them to facilitate effective online learning. Specifically, given that the majority of MOOC videos contain slides, we first leverage video processing and speech analysis techniques, including shot recognition, …

Mathematical Modeling Of Microscale Biology In Polyelectrolyte Brushes, William J. Ceely

CGU Theses & Dissertations

Biological macromolecules including nucleic acids, proteins, and glycosaminoglycans are typically anionic and can span domains of up to hundreds of nanometers and even micron length scales. The structures exist in crowded environments that are dominated by multivalent electrostatic interactions that can be modeled using mean-field continuum approaches that represent underlying molecular nanoscale biophysics. In this thesis, we develop such models for polyelectrolyte brushes using both steady state modified Poisson-Boltzmann models and transient modified Poisson-Nernst-Planck models that incorporate important ion-specific (Hofmeister) effects. The transient model enables observation of the relative physical effects as an initial non-equilibrium state relaxes to the steady …

Exploring Loss Functions In Machine Learning, Yujie Wang

CGU Theses & Dissertations

The loss function plays a critical role in machine learning. It is fundamental in training, evaluating, and optimizing machine learning models, directly impacting their effectiveness and efficiency in solving specific tasks. We explore three new loss functions and their applications. Softmax Cross-Entropy Loss, stands as a prevalent choice in neural network classification tasks. It treats all misclassifications uniformly. However, multi-class classification problems often have many semantically similar classes. We should expect that these semantically similar classes will have similar parameter vectors. We introduce a weighted loss function, the tree loss as a drop-in replacement for the cross entropy loss. The …