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Articles 20791 - 20820 of 291657
Full-Text Articles in Physical Sciences and Mathematics
Advancements Of A Vibration-Based Sound Power Method For Direct And Indirect Applications, Ian Charles Bacon
Advancements Of A Vibration-Based Sound Power Method For Direct And Indirect Applications, Ian Charles Bacon
Theses and Dissertations
This dissertation advances the Vibration-Based Sound Power (VBSP) method for measuring the sound power of vibrating structures, expanding its applicability to a wider range of geometries and acoustic environments. The research addresses limitations of traditional sound power measurement techniques by developing an alternative method that achieves near Precision (Grade 1) accuracy while maintaining feasibility for in situ testing under uncontrolled acoustic conditions. After reviewing the current VBSP method in Unit 1, Unit 2 introduces stitching techniques for Scanning Laser Doppler Vibrometer (SLDV) measurements, enabling accurate 3D scans and extending the method to complex geometries. Experimental validation is provided for baffled …
Electronic Relaxation Pathways In Thio-Acridone And Thio-Coumarin: Two Heavy-Atom-Free Photosensitizers Absorbing Visible Light, Chris Acquah, Sean Hoehn, Sarah Krul, Sourav Kanti Seth, Eric Lee, Carlos E. Crespo-Hernández
Electronic Relaxation Pathways In Thio-Acridone And Thio-Coumarin: Two Heavy-Atom-Free Photosensitizers Absorbing Visible Light, Chris Acquah, Sean Hoehn, Sarah Krul, Sourav Kanti Seth, Eric Lee, Carlos E. Crespo-Hernández
Faculty Scholarship
Heavy-atom-free photosensitizers (HAF-PSs) have emerged as a new class of photosensitizers aiming to broaden their applicability and versatility across various fields of the photodynamic therapy of cancers. The strategy involves replacing the exocyclic oxygen atoms of the carbonyl groups of established biocompatible organic fluorophores with sulfur, thereby bathochromically shifting their absorption spectra and enhancing their intersystem crossing efficiencies. Despite these advancements, the photophysical attributes and electronic relaxation mechanisms of many of these HAF-PSs remain inadequately elucidated. In this study, we investigate the excited state dynamics and photochemical properties of two promising HAF-PSs, thio-coumarin and thio-acridone. Employing a combination of steady-state …
Leveraging Quantitative Systems Pharmacology For Dose Optimization In Oncology Drug Development, Blerta Shtylla
Leveraging Quantitative Systems Pharmacology For Dose Optimization In Oncology Drug Development, Blerta Shtylla
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Myc And Egr1 Expression In Colorectal Cancer Cells With An Oncogenic Mutation In Ctnnb1 And Normal P53, Sophia Vickers, Erick Spears, Phd
Myc And Egr1 Expression In Colorectal Cancer Cells With An Oncogenic Mutation In Ctnnb1 And Normal P53, Sophia Vickers, Erick Spears, Phd
Science University Research Symposium (SURS)
Cancer is often initiated by genetic alterations that affect cellular proliferation, survival, and differentiation. Colorectal cancers are specifically initiated and driven by mutations affecting the Wnt signaling pathway and mutations in the CTNNB1 gene are the second most common of these mutations found in colorectal cancers. Among these, mutations in the CTNNB1 gene, encoding β-catenin, frequently lead to dysregulated Wnt signaling, a hallmark of colorectal cancer. The proto-oncogene MYC and the early growth response gene EGR1 are known to be critical downstream effectors of several oncogenic pathways. MYC is a known β-catenin target gene and under certain cellular contexts, EGR1 …
Assessing Methane Emissions And Soil Carbon Stocks In The Camargue Coastal Wetlands: Management Implications For Climate Change Regulation, Maite Martínez-Eixarch, Pere Masqué, Anna Lafratta, Paul Lavery, Samuel Hilaire, Lluís Jornet, Cyrille Thomas, Arnaud Boisnard, Néstor Pérez-Méndez, Carles Alcaraz, Columba Martínez-Espinosa, Carles Ibáñez, Patrick Grillas
Assessing Methane Emissions And Soil Carbon Stocks In The Camargue Coastal Wetlands: Management Implications For Climate Change Regulation, Maite Martínez-Eixarch, Pere Masqué, Anna Lafratta, Paul Lavery, Samuel Hilaire, Lluís Jornet, Cyrille Thomas, Arnaud Boisnard, Néstor Pérez-Méndez, Carles Alcaraz, Columba Martínez-Espinosa, Carles Ibáñez, Patrick Grillas
Research outputs 2022 to 2026
Coastal wetlands are crucial in climate change regulation due to their capacity to act as either sinks or sources of carbon, resulting from the balance between greenhouse gas (GHG) emissions, mainly methane (CH4), and soil carbon sequestration. Despite the paramount role of wetlands in climate regulation few studies investigate both aspects. The Camargue is one of the largest wetlands in Europe, yet the ways in which environmental and anthropic factors drive carbon dynamics remain poorly studied. We examined GHG emissions and soil organic carbon (SOC) stocks and accumulation rates in twelve representative wetlands, including two rice fields, to gain insights …
Teaching With Pedagogy And Empathy, Mamoona Muzammil, Muzammil Arshad, Washain Muzammil
Teaching With Pedagogy And Empathy, Mamoona Muzammil, Muzammil Arshad, Washain Muzammil
School of Integrative Biological & Chemical Sciences (Formerly Dept. of Chemistry)
Mental illness is common and can affect anyone. Each year the University welcomes students with Mental Health Issues. One in four adults in the US will experience a mental illness in their lifetime, however according to a NUS survey, eight out of ten students will experience a mental illness while in higher education. For some student’s mental illness can be a lifelong disability. Others can experience short term issues that emerge around difficult or stressful life events, while some students may be more at risk of experiencing mental illness in relation to their ethnicity, gender, sexuality or socio-economic background. Although …
Kreig: Gaining Insight Into Epidemics Through Use Of Mathematical Modeling, Christina Edholm
Kreig: Gaining Insight Into Epidemics Through Use Of Mathematical Modeling, Christina Edholm
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Shevtsov: Growing Pains And Growing Gains: The Arizona Experience, Tynan Lazarus, Jane Shevtsov
Shevtsov: Growing Pains And Growing Gains: The Arizona Experience, Tynan Lazarus, Jane Shevtsov
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Early Ctdna Kinetics As A Dynamic Biomarker Of Cancer Treatment Response, Aaron Li, Emil Lou, Kevin Leder, Jasmine Foo
Early Ctdna Kinetics As A Dynamic Biomarker Of Cancer Treatment Response, Aaron Li, Emil Lou, Kevin Leder, Jasmine Foo
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
A Paradigm For Ecological Dynamics In Predator-Prey Systems: Applications To Climate Change, Grayson D. Adams, Aditi Ghosh Dr.
A Paradigm For Ecological Dynamics In Predator-Prey Systems: Applications To Climate Change, Grayson D. Adams, Aditi Ghosh Dr.
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Poverty And Its Geospatial Association With Access To Hiv Treatment In Malawi, Zvifadzo Matsena Zingoni, Justin Okano, Joan Ponce, Luckson Dullie, Sally Blower
Poverty And Its Geospatial Association With Access To Hiv Treatment In Malawi, Zvifadzo Matsena Zingoni, Justin Okano, Joan Ponce, Luckson Dullie, Sally Blower
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Kreig: Quantifying The Relationship Between Sars-Cov-2 Viral Load And Infectiousness, Aurelien Marc
Kreig: Quantifying The Relationship Between Sars-Cov-2 Viral Load And Infectiousness, Aurelien Marc
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Shevtsov: Teaching Modeling To First-Year Life Science Students: The Ucsc Experience, Martin H. Weissman
Shevtsov: Teaching Modeling To First-Year Life Science Students: The Ucsc Experience, Martin H. Weissman
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Simulating Interventions To Improve Reproducibility In Scientific Publications, Ben G. Fitzpatrick
Simulating Interventions To Improve Reproducibility In Scientific Publications, Ben G. Fitzpatrick
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Kreig: Examining Affinity Maturation And Antigenic Drift With An Agent-Based Model, Jasmine Af Kreig, Jannatul Ferdous, Ruian Ke, Ruy M. Ribeiro
Kreig: Examining Affinity Maturation And Antigenic Drift With An Agent-Based Model, Jasmine Af Kreig, Jannatul Ferdous, Ruian Ke, Ruy M. Ribeiro
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Modelling Saccharomyces Cerevisiae For The Production Of Fermented Beverages, Paul A. Valle Dr., Yolocuauhtli Salazar Dr., Luis N. Coria Dr., Oscar N. Soto Dr., Jesus B. Paez Dr.
Modelling Saccharomyces Cerevisiae For The Production Of Fermented Beverages, Paul A. Valle Dr., Yolocuauhtli Salazar Dr., Luis N. Coria Dr., Oscar N. Soto Dr., Jesus B. Paez Dr.
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Network Analysis Of Progress In Mathematics Research, Anna Singley
Network Analysis Of Progress In Mathematics Research, Anna Singley
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
From Ecology To Modeling Apps - Newts, Crayfish, And Slopes, Timothy Lucas
From Ecology To Modeling Apps - Newts, Crayfish, And Slopes, Timothy Lucas
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Bodine: Exploring The Versatility Of Agent-Based Modeling In Netlogo: Lessons From Education And Research, Anne E. Yust
Bodine: Exploring The Versatility Of Agent-Based Modeling In Netlogo: Lessons From Education And Research, Anne E. Yust
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Bayesian Networks And Machine Learning For Predicting Breast Cancer Growth From In Vitro Cell Count Data, Widodo Samyono
Bayesian Networks And Machine Learning For Predicting Breast Cancer Growth From In Vitro Cell Count Data, Widodo Samyono
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Seshaiyer: Data-Driven Machine Learning Framework To Predict Dynamics Of Infectious Diseases Incorporating Human Behavior, Alonso Gabriel Ogueda Oliva, Dr. Padmanabhan Seshaiyer
Seshaiyer: Data-Driven Machine Learning Framework To Predict Dynamics Of Infectious Diseases Incorporating Human Behavior, Alonso Gabriel Ogueda Oliva, Dr. Padmanabhan Seshaiyer
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Bodine: Enhancing Netlogo3d Simulations: Computational Efficiency And Online Accessibility Of A Pain Model, Rachael Miller Neilan
Bodine: Enhancing Netlogo3d Simulations: Computational Efficiency And Online Accessibility Of A Pain Model, Rachael Miller Neilan
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Modeling Opioid Addiction In Hand Surgery Patients, Eli Goldwyn, Grace Bowman, Kathryn Montovan, Julie Blackwood
Modeling Opioid Addiction In Hand Surgery Patients, Eli Goldwyn, Grace Bowman, Kathryn Montovan, Julie Blackwood
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Modeling The Synergistic Interplay Between Malaria Dynamics And Economic Growth, Ruijun Zhao, Hope Enright, Calistus Ngonghala, Olivia Prsoper
Modeling The Synergistic Interplay Between Malaria Dynamics And Economic Growth, Ruijun Zhao, Hope Enright, Calistus Ngonghala, Olivia Prsoper
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Seshaiyer: Understanding Non-Linear Dynamics Of Interacting Subpopulations And Implicit Human Behavior Using Physics-Informed Neural Networks, Naima Aubry-Romero, Alonso Ogueda-Oliva, Padmanabhan Seshaiyer
Seshaiyer: Understanding Non-Linear Dynamics Of Interacting Subpopulations And Implicit Human Behavior Using Physics-Informed Neural Networks, Naima Aubry-Romero, Alonso Ogueda-Oliva, Padmanabhan Seshaiyer
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Harvesting Modulation In Three Species Food Chains Using A Robust Control Approach, Hector Puebla, Mariana Rodriguez-Jara, Priti Kumar Roy
Harvesting Modulation In Three Species Food Chains Using A Robust Control Approach, Hector Puebla, Mariana Rodriguez-Jara, Priti Kumar Roy
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Predicting And Monitoring Immune Checkpoint Inhibitor Therapy Using Artificial Intelligence In Pancreatic Cancer, Guangbo Yu, Zigeng Zhang, Aydin Eresen, Qiaoming Hou, Farideh Amirrad, Sha Webster, Surya M. Nauli, Vahid Yaghmai, Zhuoli Zhang
Predicting And Monitoring Immune Checkpoint Inhibitor Therapy Using Artificial Intelligence In Pancreatic Cancer, Guangbo Yu, Zigeng Zhang, Aydin Eresen, Qiaoming Hou, Farideh Amirrad, Sha Webster, Surya M. Nauli, Vahid Yaghmai, Zhuoli Zhang
Pharmacy Faculty Articles and Research
Pancreatic cancer remains one of the most lethal cancers, primarily due to its late diagnosis and limited treatment options. This review examines the challenges and potential of using immunotherapy to treat pancreatic cancer, highlighting the role of artificial intelligence (AI) as a promising tool to enhance early detection and monitor the effectiveness of these therapies. By synthesizing recent advancements and identifying gaps in the current research, this review aims to provide a comprehensive overview of how AI and immunotherapy can be integrated to develop more personalized and effective treatment strategies. The insights from this review may guide future research efforts …
Holistic & Socially Just Admissions Procedures In An Artificially Intelligent (Ai) World, Lucinda Bratini, Ali Cunningham Abbott, Tracy N. Baker
Holistic & Socially Just Admissions Procedures In An Artificially Intelligent (Ai) World, Lucinda Bratini, Ali Cunningham Abbott, Tracy N. Baker
Faculty and Staff Publications & Presentations
In our ever-evolving social context, the counseling profession continues to center social justice and decolonial praxis in training programs. Simultaneously, we remain attuned to shifts in machine learning and artificial intelligence (AI) which require us to adjust and grow. This roundtable discussion shares the development of a holistic admissions review (HAR) pilot process, which incorporates relational, diversity and social justice values alongside AI innovations and current CACREP considerations.
Identifiability And Convergence Behavior For Markov Chain Monte Carlo Using Multivariate Probit Models, Xiao Zhang
Identifiability And Convergence Behavior For Markov Chain Monte Carlo Using Multivariate Probit Models, Xiao Zhang
Michigan Tech Publications
Multivariate probit models have been popularly utilized to analysis multivariate ordinal data. However, the identifiable multivariate probit models entail the covariance matrix for the underlying multivariate normal variables to be a correlation matrix, which brings a rigorous task to conduct efficient statistical analysis. Parameter expansion to make the identifiable model to be non-identifiable has been inevitably explored. However, the effect of the expanded parameters on the convergence of Markov chain Monte Carlo (MCMC) is seldomly investigated; in addition, the comparison of MCMC developed based on the identifiable model and that based on the non-identifiable model is hardly ever explored, especially …
Comparison Of Efficient Deep Learning Architectures For Lactobacillus Species Identification, Dea Aisyah Rusmawati, Ishak Ariawan, Afrinal Firmanda
Comparison Of Efficient Deep Learning Architectures For Lactobacillus Species Identification, Dea Aisyah Rusmawati, Ishak Ariawan, Afrinal Firmanda
Karbala International Journal of Modern Science
Identifying microorganism species, such as Lactobacillus, is essential in ensuring the food products' quality and safety. Traditional laboratory practice requires expert knowledge and experience, but the method is expensive and time-consuming due to complex sample preparation. Faster, more accurate, and cheaper computational methods, such as transfer learning technology, are needed for the Lactobacillus species classification. The technique has been effective in a variety of image recognition contexts. Deep learning architecture can also be applied as an innovative strategy for digital image-based identification. Therefore, this research aims to compare several deep-learning architectures in classifying bacterial strains of Lactobacillus. The four architectures …