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Buddhism For Thinkers, Chang-Seong Hong, Sun Kyeong Yu

MSU Authors Collection

This book is an introduction to Buddhist philosophy. It uses the methods of analytic philosophy to approach the major topics of Buddhism.

An Exploration Of Factors That Influence A Clinical Supervisor's Decision To Address The Personal Development And Dispositions Of Supervisees, Kirsten K. Hagen

Psychology

Research suggests that addressing a supervisee’s personal factors in clinical supervision is critical to developing their therapeutic capacities (Aponte, 1994; Krug and Schneider, 2016; Southern, 2007; Zorga et al., 2001). However, little is known about the factors contributing to clinical supervisors’ decisions to address supervisees’ personal development and dispositions in clinical supervision, despite their importance in supervisees’ professional development. The purpose of this grounded theory study was to discern the nuanced narratives of clinical supervisors and construct a theory of factors related to their decisions regarding whether to address or not address the personal development and dispositions of supervisees in …

Ligand Substitution Versus Dna-Binding Affinity : ǂB Syntheses, Structures, And In Vitro Anticancer Activities Of Pt(Ch₃)₂I₂{2,2'-Bipy-N,N'-(Ch₃)₂} (N,N' = 4,4'; 5,5'; 6,6'), Shadrach Stitz

Chemistry and Biochemistry

In chemotherapeutic treatment for leukemia, the drug cisplatin is highly effective. However, there is an immense need for cisplatin analogues that are more clinically viable. Cancer cell assay studies have shown that the platinum(IV) complex Pt(CH₃)₂I₂{2,2'-bipyridine} exhibits significant anticancer activity against the human breast cancer cell line ZR-75-1, with an EC50 (effective concentration 50%) concentration of 6.1 μM— substantially lower than that of cisplatin (16.4 μM). To explore the unknown structure-activity relationship between DNA binding and anti-cancer activity, three isomers — Pt(CH₃)₂I₂{2,2'-bipy-n,n'-(CH₃)₂} where n,n’ = 4,4’; 5,5’; 6,6’— were synthesized. The intent was to demonstrate decreased cytotoxicity as complex-DNA steric …

The Transformational Learning By Web-Conferencing Circuit Board: A Conceptual Model Outlining The Conditions That Facilitate Transformation In Synchronous Spaces, Rachel L. Reilly

Communication

As synchronous technologies and high-speed internet have become more accessible, opportunities for learning in web-conferencing settings have also increased. Despite the ubiquity of learning experiences taking place over web-conferencing, there is a lack of research on what makes for effective adult learning in synchronous settings from learners’ perspectives. Moreover, there are few studies examining how transformational learning—learning that changes an adult’s mindset, beliefs, or perceptions—occurs in web-conferencing settings. This qualitative study explores the conditions through which transformational learning occurs in web-conferencing settings. It includes the perspectives of adult learners (all at least eighteen years old) who have participated in a …

Understanding Secondary Atmospheric Chemistry In Extremely Cold And Dark Environments Through Hydroxymethanesulfonate (Hms) Measurements In Wintertime Fairbanks, Alaska, James R. Campbell

Chemistry and Biochemistry

Fairbanks, Alaska is a subarctic city that regularly violates PM2.5 air quality standards in the winter, exacerbated by strong wintertime inversion layers and wood stove heating. While primary sources of PM2.5 in Fairbanks have been studied extensively, secondary chemistry remains not well understood. Here, we focus on the aqueous secondary product hydroxymethanesulfonate (HMS), a major sulfur(IV) particulate species, to help understand what drives secondary pollution in Fairbanks. In 2020 and 2021, we used a particle-into-liquid sampler coupled with ion chromatography (PILS-IC) to measure HMS and sulfate concentrations. We report that HMS concentrations are high compared to other highly polluted regions …

Alaska Earthquake Center Quarterly Review January-March 2025, Heather Mcfarlin, Will Dienstfrey, Alexandra Farrell, Beth Grassi, Stephen Holtkamp, Nate Murphy, Elisabeth Nadin, Carolyn Parcheta, Angelica Stabs, Michael West

Alaska Earthquake Center Reports

This series of technical quarterly reports from the Alaska Earthquake Center (AEC) includes detailed summaries and updates on Alaska seismicity, the AEC seismic network and stations, fieldwork, our online presence, public outreach, and lists publications and presentations by AEC staff. Multiple AEC staff members contributed to this report.

Design And Development Of Deep Learning Based Generic Platform For Promoting Precision Agriculture, Srilakshmi A

Theses and Dissertations

Precision agriculture also referred as precision farming or smart farming, is an innovative approach to agricultural management that leverages technology and data to optimize various aspects of the farming process. This approach aims to make farming more effective, sustainable, and profitable by affording farmers with the application tools and information they need to make more informed decisions.

Precision agriculture combines elements of agriculture, technology, and data science to enhance crop production, and resource utilization. Precision agriculture techniques can be highly effective in leaf disease detection within crop fields. Machine learning has been developed incredibly across multiple domains and shown it …

Factors Influencing The Performance Of Farmer-Producer Organizations (Fpos) And Their Societal Impact In Tamil Nadu, Arjune S

Theses and Dissertations

Farmer Producer Organizations (FPOs) are formed mainly for the farmers to have better institutional access to acquire them. They are also under the inspiration of the director's abstinence and the incentive of getting more money. These are socio-psychological individual differences and thus of importance to markets, the perception of markets, and market relevance of group interaction. Self-esteem, attitude to participation in group activities, and willingness to participate in these types of activities are of some significance for his/her performance because they have an effect on their performance afterward.

Farmer social empowerment increased but not farmer economic empowerment did so much …

Hindcasting The Occurrence Time Of Major Earthquakes Using Machine Learning And Time Series Analysis, Rubidha Devi D

Theses and Dissertations

An earthquake is an intense shaking of the ground that typically occurs when tectonic plates move beneath the surface of the Earth. Scientists analyze historical seismic records and geophysical and atmospheric signs to build models estimating the probability of major earthquakes by detecting patterns and anomalies in data such as ground deformation and seismic waves. This study would help in predicting earthquakes to minimize risks of people and buildings.

The present study investigates the devastating earthquakes along the Chilean subduction zone in South America, linking non-seismic data to machine learning predictions of Outgoing Longwave Radiation (OLR) and Relative Humidity (RH) …

Computational Studies On The Major Antioxidant Enzymes Of Wuchereria Bancrofti Towards The Development Of Anti Filarial Leads, Sureshan M

Theses and Dissertations

Lymphatic filariasis (LF), or elephantiasis, is a mosquito-borne parasitic disease affecting the lymphatic system, primarily in tropical and subtropical regions. It is the second leading cause of long-term disability and a neglected tropical disease. According to WHO, LF threatens 882 million people in 44 countries, with over 9 billion treatments administered. The disease is caused by three nematodes: Wuchereria bancrofti (90% of cases worldwide, including India), Brugia malayi (10% in Southeast and Eastern Asia), and Brugia timori (found in Timor and nearby islands). Lymphatic filariasis (LF) is an ancient disease that continues to challenge scientists and physicians. Current treatments include …

Management Concepts In Shishupalavadha, Sathyanarayanan V

Theses and Dissertations

Management of organizations, people, and entities has been a subject matter of great interest today. Schools of business and management were established in the West about 125 years ago, and countries in other parts of the world, including India, simply followed these practices. Consequently, there is a widespread feeling today that management concepts originated in the West. All Indian business schools teach management concepts propounded by Western scholars in the last 100 years or so.

Going by the first principles, whenever multiple people, resources, entities, and institutions are involved, there is a requirement for Management. This implies that management as …

Hindcasting The Occurrence Time Of Major Earthquakes Using Machine Learning And Time Series Analysis, Rubidha Devi D

Theses and Dissertations

An earthquake is an intense shaking of the ground that typically occurs when tectonic plates move beneath the surface of the Earth. Scientists analyze historical seismic records and geophysical and atmospheric signs to build models estimating the probability of major earthquakes by detecting patterns and anomalies in data such as ground deformation and seismic waves. This study would help in predicting earthquakes to minimize risks of people and buildings. The present study investigates the devastating earthquakes along the Chilean subduction zone in South America, linking non-seismic data to machine learning predictions of Outgoing Longwave Radiation (OLR) and Relative Humidity (RH) …

Artificial Intelligence-Based Adaptive Data-Driven Techniques For Disruption Prediction In Tokamak, Priyanka M

Theses and Dissertations

Tokamaks are nuclear fusion reactors designed to generate sustainable energy by confining plasma, yet plasma disruptions remain a major obstacle as they can damage reactor components and interrupt fusion reactions. Addressing this challenge requires reliable models that can classify plasma discharges and predict disruptions in advance. This thesis develops machine learning and deep learning approaches to improve both classification and forecasting.The first contribution is a semi-supervised active learning framework, Nearest Margin-Ranked Batch Mode Active Learning (NM-RBMAL), integrated with an ensemble model.

Unlike traditional classifiers that operate on static training data, this approach continuously adapts to new plasma conditions, reducing model …

Ai Based Early Detection Of Hormonal Imbalance And Poly-Cystic Ovary Syndrome In Young Women, Reka S

Theses and Dissertations

A hormonal disorder, Poly-Cystic Ovary Syndrome (PCOS) usually affects women during the reproductive age. It is characterised by imbalances in hormones, particularly a rise in the female body's androgen level (male hormone) and enlarged ovaries with small cysts. PCOS can cause ovarian cysts, weight gain, acne, excessive hair growth, insulin resistance, and irregular menstrual cycles along with other health problems. While the exact origin of PCOS is uncertain and its symptoms are unclear, diagnosing PCOS in real-world conditions is a difficult task. Therefore, prompt and precise PCOS diagnosis is essential for efficient treatment and for averting long-term issues.

Clinicians typically …

Metal-Organic Frameworks And Nanostructured Materials For Environmental Applications, Arunkumar G

Theses and Dissertations

The global population and economic development are experiencing rapid growth. Concurrently, environmental challenges such as global warming, soil, water, and air pollution are also rising. Each year, approximately 700,000 tonnes of products are generated from 100,000 tonnes of commercial dyes. Following their use, these dyes are often released into water bodies.

This contamination of water and land results in the formation of mutagenic and carcinogenic substances harmful to living organisms. Therefore, it is imperative to treat industrial wastewater to enable its recycling for various applications. Parallelly, the vehicles are becoming indispensable to human life modern world's urbanization and advancement.

The …

Perspectives On Northern Gulf Of Alaska Freshwater Pathways, Wind, And Linkages To Phytoplankton Biomass, Isaac Reister

Oceanography

The biologically productive northern Gulf of Alaska continental shelf receives freshwater from surrounding watersheds and wind stress from atmospheric pressure systems. A better characterization of the relationship between wind and salinity spatiotemporal variability is important for understanding the fate of freshwater and its ecological importance. In Chapter 2, I analyzed 25 years of northern Gulf of Alaska hydrographic data to reveal mid-shelf and shelf­ break freshwater pathways that impact stratification, currents, and freshwater distribution. Process studies of the Copper River plume’s propagation towards the shelf-break and beyond inform ecological function on the northern Gulf of Alaska shelf and productivity in …

Exploring The Intersection Of Race And Native Speakerism In English Language Teaching: Experiences Of Black African Teachers In Turkey, John Ayodeji Odudele

Linguistics

Research on race and native speaker status in language teaching provides little insight into the experiences of Black African English teachers (BAETs) in the diaspora. To address this gap, this study examines how aspects of BAETs' positionalities - such as race and native speaker status create challenges in their professional and societal lives in Turkey. Data from twelve semi­ structured interviews of BAETs were analyzed using thematic analysis. Findings suggest that race­ related challenges trump language-related ones and that Blackness fundamentally shapes outsiders’ perception and value of BAETs’ linguistic expertise. Even when BAETs possess the same or superior qualifications as …

Ddx219.2 Social Media Content Creation Example 7, Sae University College

Exemplars

This project involved creating a suite of social media content tailored to the student’s chosen creative project. The work is exemplary for its consistent visual style, platform-specific content design, and alignment with the strategic goals defined on Project 1.

Social Thought From The Ruins: Quixote’S Dinner Party, David A. Westbrook

Books

Through stories, conversations, and essays, this book pursues interwoven critical and philosophical inquiries into the nature of the contemporary in the North Atlantic, asking how are we to live as intellectuals, individually and in community? Social Thought From the Ruins: Quixote’s Dinner Party is the product of informal discussion and academic work done over the last two decades among an international group of social scientists. An extended critique of academic life today and the context of our own thinking, this book interrogates aspects of our modernity, with its pervasive sense of crisis and uncertainty, and the difficulty of thinking clearly …

Factors Affecting Nest And Brood Survival Of Rock Ptarmigan (Lagopus Muta) In Interior Alaska, Robert Wiltzen

Biological Sciences

Rock ptarmigan (Lagopus muta) are a circumpolar species endemic to high elevations and latitudes of North America and are common throughout Alaska. The r- selected life history of ptarmigan indicates that reproduction and specifically nest and brood survival is the most important component of population growth. However, factors affecting these population parameters have not been studied extensively or intensively, since there have only been three studies done in Alaska. Rock ptarmigan exhibit population fluctuations, which may be caused by changes in reproduction and survival due to predation and weather events. Warming climatic patterns and shifts in the range of their …

Investigation Of Dependency Parsing Techniques For Digital Document Analysis Through Deep Learning Approach, Rekah D Ms

Theses and Dissertations

Digital document dependency parsing is a significant task in natural language processing. Dependency parsing supports verification of the grammatical correctness of a sentence besides enabling extraction of relevant documents. Inappropriate extraction of features may result in falsely parsing a document, leading to decreased accuracy. Machine learning methods have been employed to perform feature extraction. However, selecting pertinent features was never achieved which minimizes the time consumption and overhead.

Hence, novel machine learning and deep learning techniques have been designed in our work for accurate and computationally efficient digital document analytics through dependency parsing. Four different contributions have been proposed for …

Cyclone Intensity Prediction In The Bay Of Bengal Using Deep Learning Methods, Senthil Kumar J

Theses and Dissertations

The Bay of Bengal region's coastlines have been badly devastated by tropical cyclones, as the region experiences an average of five to six cyclones per year, with about two to three of these intensifying into tropical storms or severe cyclones. Thus it necessitates to study the accurate and efficient forecasting of their intensity to improve preparedness and response to natural disasters. The present study compares and examines three distinct approaches to cyclone intensity prediction using historical datasets from 1998 to 2020: hybrid optimisation, deep learning-based, and empirical approaches.The predicted accuracy, computational effectiveness, and feasibility for real-time scenarios of each model …

Design And Development Of Machine Learning And Deep Learning Based Algorithms For Cyberattacks Detection, Abiramasundari S

Theses and Dissertations

E-mail is the fastest mode of communication. It is amongst the most commonly used modes of communication and can be used for both legal and illegal purposes. Many elements that could be useful in detecting email fraud are constantly being investigated. Phishing assaults in which thieves use Internet to trick consumers into visiting fake websites are very common and are causing significant harm to victims. Several methods of filtering phishing emails have been devised but a solution to the problem still evades. One of the attacks addressed in this research is email phishing. Machine learning is a popular and efficient …

Investigations Of Secure Memory For Vlsi Based Crypto System, Vijay Sai R Mr

Theses and Dissertations

Semiconductor technology is growing very rapidly in their architectural developments, involving the usage of processor and memory. Presence of memory, in general is a vital commodity in various devices which are almost embedded into human activity, from robust work stations to handy mobile phones. Security of data stored in memory is very important, and hence, observation must be made that these valuable data should not be thwarted by malicious means. Security in cache memory is a major issue in memory related applications such as smart cards and bio-metric implementations.

Cache, is a small and limited memory located between central processing …

Geol 12 Natural Disasters Syllabus, Anestoria Shalkowski

Open Educational Resources

Hazards are events which have the capabilities to damage property and or life. Understanding natural hazards and how these can become disasters are important in reducing the impacts of such events. This syllabus provides a description of the material to be examined and the expected student outcomes upon completion of the course.

Development Of Low-Profile Wideband Microstrip Antennas For Cubesat Phased-Array Applications, Mitchell R. Hay

Engineering

CubeSat missions rely heavily on effective communication systems in order to transmit and receive large amounts of data quickly and efficiently. The total throughput is limited by the capacity of the channel - a quantity dependent upon the signal quality and bandwidth of the link. Volume and power constraints on a CubeSat impede overall capacity in a fixed bandwidth channel. Phased-array antennas provide a more power efficient solution to improving signal quality by optimizing the spatial properties of the link, rather than broadcasting higher signal power over a broader area through power amplification alone. In order to take advantage of …

Effects Of Eogo In Metakaolin-Based Geopolymer, Chaewon Lee, Hoyoung Lee, Jinwoo An, Boo Hyun Nam

Civil Engineering Faculty Publications

Geopolymer concrete uses a geopolymer binder instead of traditional Portland cement; thus, it reduces carbon emissions by a significant amount. In this study, Edge-Oxidized Graphene Oxide (EOGO), a carbon-based nanomaterial, was added into a metakaolin-based geopolymer, and its effect on the mechanical and rheological properties of the mixture was investigated. EOGO was added into the mixture at 0% (control), 0.1%, 0.5%, and 1% of the metakaolin mass. Several experiments were conducted to characterize the properties of the metakaolin–EOGO (MKGO) geopolymer, including its compressive strength, free–free resonance column (FFRC), void content, water absorption, setting time, flow, and rheology. It was found …

Seasonal Predictability Of Sea Ice And Boreal Fire In Alaska, Cecilia Borries-Strigle

Atmospheric Sciences

Attribution studies have shown that warming Arctic temperatures have led to a substantial loss of sea ice and an increase in large wildfire seasons. With wildfire and sea ice decline impacting everyday life by disrupting transportation or damaging infrastructure, for example, a clear need for skillful forecasts at seasonal timescales has emerged. This dissertation addresses critical challenges in seasonal prediction for wildfire and sea ice in Alaska. The first study evaluates outlooks of Buildup Index derived from three seasonal forecasts to assess their skill in predicting fire conditions. Forecast skill is greatest during the wind (April 1-June 10) and drought …

Reanalysis And (Near) Real-Time Inversion Of Deformation Observations At Alaskan Volcanoes, Mario Fernando Angarita Vargas

Geosciences

Forecasting volcanic eruptions remains challenging due to the complexity and limited understand­ing of volcanic processes. However, recent studies have shown that integrating multidisciplinary data from past eruptions can improve forecasts for monitored volcanoes. The PREEVENTS project addresses this challenge identifying patterns prior, during or following volcanic eruptions on mul­tidisciplinary data. The project considers four disciplines: Geodesy, Petrology, Seismology and Gas/Geochemistry. This dissertation contributes with two novel tools to analyze geodetic data. The first tool exploits the amplitude from SAR imagery to quantify morphology changes during erup­tions. The tool has been verified with a synthetic case and validated with a dome …

Toward Multidisciplinary Volcanic Eruption Models And Forecasts In Alaska: Contributions From Automated Seismic And Acoustic Signal Detection, Darren Tan

Geosciences

Explosive, ash-generating volcanic eruptions pose an increasing threat to a growing, globally connected population. Accurate forecasts of volcanic eruptions remain challenging due to the complex­ity of volcanic systems, but recent multidisciplinary synthesis efforts have proven effective. The National Science Foundation Prediction of and Resilience against Extreme Events (PREEVENTS) project aims to re-analyze and combine multidisciplinary observations at eight Alaska volcanoes to develop eruption forecast models. Leading the seismology and infrasound discipline, this dis­sertation details the development of automated tools capable of producing high-resolution catalogs of volcanic unrest signals from continuous seismic and acoustic data. By leveraging these catalogs and synthesizing …