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Full-Text Articles in Physical Sciences and Mathematics

Threats From Climate Change Are Increasing For Natural World Heritage Sites, Martin Falk, Eva Hagsten Apr 2024

Threats From Climate Change Are Increasing For Natural World Heritage Sites, Martin Falk, Eva Hagsten

GSTC Academic Symposium - In conjunction with the GSTC Global Conference Sweden April 23, 2024

The aim of the paper is to analyse the occurrence and intensity of threats to Natural World Heritage Sites from climate change as assessed by IUCN experts. The data comes from the Conservation Outlook Assessment database, which covers 250 sites for three time periods (2014, 2017 and 2020). The threat of climate change is broadly defined and includes temperature extremes, rapidly disappearing glaciers, coral bleaching, droughts, desertification, rising temperatures and rising sea levels. Simultaneous probit and ordered models with individual site effects are used to analyse the occurrence and intensity of both a perceived actual and a potential threat.

The …


Türkiye's Sustainable Tourism Transformation: An Overview, Mustafa Sogut Apr 2024

Türkiye's Sustainable Tourism Transformation: An Overview, Mustafa Sogut

GSTC Academic Symposium - In conjunction with the GSTC Global Conference Sweden April 23, 2024

Türkiye has initiated a paradigm shift in its tourism industry, marked by a collaboration with the Global Sustainable Tourism Council (GSTC), renowned for setting robust sustainability standards. The agreement, initiated in 2022, prioritizes sustainability commitment, commencing with formulating national program criteria and certification bodies training. The initial phase is targeted for completion by the end of 2023, with subsequent stages progressively implemented by 2025, ultimately aiming to meet all international standards by 2030.

This strategic move aims to position Turkey prominently in sustainable tourism, aligning with the goals of The Paris Agreement. Turkey has proactively steered its tourism industry towards …


A Machine Learning Model Of Perturb-Seq Data For Use In Space Flight Gene Expression Profile Analysis, Liam F. Johnson, James Casaletto, Lauren Sanders, Sylvain Costes Mar 2024

A Machine Learning Model Of Perturb-Seq Data For Use In Space Flight Gene Expression Profile Analysis, Liam F. Johnson, James Casaletto, Lauren Sanders, Sylvain Costes

Graduate Industrial Research Symposium

The genetic perturbations caused by spaceflight on biological systems tend to have a system-wide effect which is often difficult to deconvolute it into individual signals with specific points of origin. Single cell multi-omic data can provide a profile of the perturbational effects, but does not necessarily indicate the initial point of interference within the network. The objective of this project is to take advantage of large scale and genome-wide perturbational datasets by using them to train a tuned machine learning model that is capable of predicting the effects of unseen perturbations in new data. Perturb-Seq datasets are large libraries of …


Characterization Of Biological Particles Using An Integrated Hyperspectral Imaging And Machine Learning, Kaeul Lim, Arezoo Ardekani Mar 2024

Characterization Of Biological Particles Using An Integrated Hyperspectral Imaging And Machine Learning, Kaeul Lim, Arezoo Ardekani

Graduate Industrial Research Symposium

Hyperspectral imaging (HSI) is a promising modality in medicine with many potential applications. This study focuses on developing a label-free lipid nanoparticle characterization method using a convolutional neural network (CNN) analysis of HSI images. The HSI data, hypercube, consists of a series of images acquired at different wavelengths for the same field of view, providing continuous spectra information for each pixel. Three distinct liposome samples were collected for analysis. Advanced image preprocessing and classification methods for HSI data were developed to differentiate liposomes based on their material compositions. Our machine learning-based classification method was able to distinguish different liposome types …


Modelling The "Bottom-Up" Development Pattern Of Tar Spot Disease In Corn, Brenden Lane, Joaquín Guillermo Ramírez-Gil, Carlos Góngora-Canul, Mariela Sofia Fernandez Campos, Andres Cruz-Sancan, Fidel E. Jiménez-Beitia, Alex G. Acosta-Guatemal, Wily Sic, C. D. Cruz Mar 2024

Modelling The "Bottom-Up" Development Pattern Of Tar Spot Disease In Corn, Brenden Lane, Joaquín Guillermo Ramírez-Gil, Carlos Góngora-Canul, Mariela Sofia Fernandez Campos, Andres Cruz-Sancan, Fidel E. Jiménez-Beitia, Alex G. Acosta-Guatemal, Wily Sic, C. D. Cruz

Graduate Industrial Research Symposium

In 2015, the corn-infecting pathogen Phyllachora maydis (causal agent of tar spot disease) was reported for the first time in the United States. The disease has since spread across the US, causing major yield losses. In 2021 alone, 5.88 million metric tons (231.3 million bushels) of US corn yield were lost to this disease, costing an estimated US$1.25 billion. Though fungicides can protect against these agroeconomic losses, application timing can be difficult to optimize because our understanding of tar spot dynamics is still evolving. The current view is that tar spot typically develops bottom-up through a repeating infection cycle. Because …


Geospatial Analysis Of Agricultural Potential In The United States, Diana Febrita Mar 2024

Geospatial Analysis Of Agricultural Potential In The United States, Diana Febrita

Graduate Industrial Research Symposium

Traditionally, the agriculture sector is responsible for providing food and crop products. However, the role of agriculture has expanded beyond its traditional function. It is the main sector that contributes to the provision of food, income, employment, environmental protection, and local economic development. Reflecting on the roles of agriculture, understanding the potential of agriculture in the United States is crucial to discovering the prospects and challenges. This study will briefly discuss the agricultural potential in the United States based on the five assets, including natural capital, financial capital, human capital, physical capital, and social capital. To identify the states with …


Sepsis Treatment: Reinforced Sequential Decision-Making For Saving Lives, Dipesh Tamboli, Jiayu Chen, Kiran Pranesh Jotheeswaran, Denny Yu, Vaneet Aggarwal Mar 2024

Sepsis Treatment: Reinforced Sequential Decision-Making For Saving Lives, Dipesh Tamboli, Jiayu Chen, Kiran Pranesh Jotheeswaran, Denny Yu, Vaneet Aggarwal

Graduate Industrial Research Symposium

Sepsis, a life-threatening condition triggered by the body's exaggerated response to infection, demands urgent intervention to prevent severe complications. Existing machine learning methods for managing sepsis struggle in offline scenarios, exhibiting suboptimal performance with survival rates below 50%. Our project introduces the "PosNegDM: Reinforcement Learning with Positive and Negative Demonstrations for Sequential Decision-Making" framework utilizing an innovative transformer-based model and a feedback reinforcer to replicate expert actions while considering individual patient characteristics. A mortality classifier with 96.7% accuracy guides treatment decisions towards positive outcomes. The PosNegDM framework significantly improves patient survival, saving 97.39% of patients and outperforming established machine learning …


Accuracy Of Nitrate Hysteresis And Flushing For Agricultural Watersheds In The Midwest, Noah Rudko, Sara K. W. Mcmillian, Jane Frankenberger, François Birgand Mar 2024

Accuracy Of Nitrate Hysteresis And Flushing For Agricultural Watersheds In The Midwest, Noah Rudko, Sara K. W. Mcmillian, Jane Frankenberger, François Birgand

Graduate Industrial Research Symposium

Storm event-based metrics, such as hysteresis (HI) and flushing (FI), are used to differentiate nitrate pathways and sources, which is essential for watershed management. Estimations of these event-based metrics typically use high frequency (15-minute – hourly) measurements, but daily data are also used due to their greater availability. To date, there has been no study assessing how using lower frequency samples affect the accuracy of HI and FI, which could skew interpretation of potential nutrient pathways and sources. We used continuous measurements of nitrate collected at 9 watersheds throughout the Midwest spanning 448 storms. HI and FI were estimated from …


Comparative Life Cycle Assessment Of Copper Production, Xiaohan Wu Mar 2024

Comparative Life Cycle Assessment Of Copper Production, Xiaohan Wu

Graduate Industrial Research Symposium

Copper demand will surge significantly in the context of global renewable energy technology implementation, but its production is an energy-intensive process. It is crucial to choose the best production method to reduce environmental damage in terms of the enormous copper supply. This research develops a multi-criteria life cycle assessment model for the three main copper production routes- pyrometallurgy, hydrometallurgy, and bioleaching. We complied material and energy flow data to assess each route's life cycle greenhouse gas (GHG) emissions, cost, and resource efficiency. Results indicate bioleaching emits the least GHG emissions (4.09 kg-CO2 eq/kg copper) among the three routes. Hydrometallurgy is …


Online Class-Incremental Learning For Real-World Food Image Classification, Siddeshwar Raghavan, Jiangpeng He, Fengqing Zhu Mar 2024

Online Class-Incremental Learning For Real-World Food Image Classification, Siddeshwar Raghavan, Jiangpeng He, Fengqing Zhu

Graduate Industrial Research Symposium

Food image classification is essential for monitoring health and tracking dietary in image-based dietary assessment methods. However, conventional systems often rely on static datasets with fixed classes and uniform distribution. In contrast, real-world food consumption patterns, shaped by cultural, economic, and personal influences, involve dynamic and evolving data. Thus, it requires the classification system to cope with continuously evolving data. Online Class Incremental Learning (OCIL) addresses the challenge of learning continuously from a single-pass data stream while adapting to the new knowledge and reducing catastrophic forgetting. Experience Replay (ER) based OCIL methods store a small portion of previous data and …


Digitizing Delphi: Educating Audiences Through Virtual Reconstruction, Kate Koury Jan 2024

Digitizing Delphi: Educating Audiences Through Virtual Reconstruction, Kate Koury

The Journal of Purdue Undergraduate Research

Implementing a 3D model into a virtual space allows the general public to engage critically with archaeological processes. There are many unseen decisions that go into reconstructing an ancient temple. Analysis of available materials and techniques, predictions of how objects were used, decisions of what sources to reference, puzzle piecing broken remains together, and even educated guesses used to fill gaps in information often go unobserved by the public. This work will educate users about those choices by allowing the side-by-side comparison of conflicting theories on the reconstruction of the Tholos at Delphi, which is an ideal site because of …


Promises And Risks Of Applying Ai Medical Imaging To Early Detection Of Cancers, And Regulation For Ai Medical Imaging, Yiyao Zhang Jan 2024

Promises And Risks Of Applying Ai Medical Imaging To Early Detection Of Cancers, And Regulation For Ai Medical Imaging, Yiyao Zhang

The Journal of Purdue Undergraduate Research

No abstract provided.


The Impact Of Accessible Data On Cyberstalking, Elise Kwan Jan 2024

The Impact Of Accessible Data On Cyberstalking, Elise Kwan

The Journal of Purdue Undergraduate Research

No abstract provided.


Model Selection Through Cross-Validation For Supervised Learning Tasks With Manifold Data, Derek Brown Jan 2024

Model Selection Through Cross-Validation For Supervised Learning Tasks With Manifold Data, Derek Brown

The Journal of Purdue Undergraduate Research

No abstract provided.


The Effects Of Wildfire Aerosol Emissions On Air Quality, Emma Braun, Audrey Shirley Jan 2024

The Effects Of Wildfire Aerosol Emissions On Air Quality, Emma Braun, Audrey Shirley

The Journal of Purdue Undergraduate Research

No abstract provided.


Upleft: Pick Up Leftovers, Uplift Those In Need, Veronica Galles Jan 2024

Upleft: Pick Up Leftovers, Uplift Those In Need, Veronica Galles

The Journal of Purdue Undergraduate Research

No abstract provided.


Characterizing Differential Reflectivity Calibration Dependence On Environmental Temperature Using The X-Band Teaching And Research Radar (Xtrra): Looking For A Relationship Between Temperature And Differential Reflectivity Bias, Emma Miller Jan 2024

Characterizing Differential Reflectivity Calibration Dependence On Environmental Temperature Using The X-Band Teaching And Research Radar (Xtrra): Looking For A Relationship Between Temperature And Differential Reflectivity Bias, Emma Miller

The Journal of Purdue Undergraduate Research

Calibration scans are important for the maintenance of data and the quality of the information that radars output. In this study we looked for a temperature dependency in a full year’s worth of differential reflectivity (ZDR) calibration scan data collected by the X-band Teaching and Research Radar (XTRRA) located near the Purdue University campus. In a vertically pointing calibration scan, the radar scans the drops from below while rotating. From this angle, the overall shape will be circular, which corresponds to a ZDR value of approximately 0 dB. To process the data for the year 2021, a Python script was …


Machine Learning Of Big Data: A Gaussian Regression Model To Predict The Spatiotemporal Distribution Of Ground Ozone, Jerry Gu Jan 2024

Machine Learning Of Big Data: A Gaussian Regression Model To Predict The Spatiotemporal Distribution Of Ground Ozone, Jerry Gu

The Journal of Purdue Undergraduate Research

Tracking pollution levels on the ground is important to the environment and public health. One of the pollutants of concern is ozone, which, at high concentrations, can cause respiratory and cardiovascular problems. The National Center for Atmospheric Research (NCAR) has published valuable ozone data obtained from ground-based sensors installed at selected locations. Because it is unfeasible to measure the exact ozone levels everywhere at any time, it would be valuable to predict the temporal-spatial distributions of ozone concentration based on existing data. This would help us better understand the patterns and trends in the data and make better decisions to …


A Computational Profile Of Invasive Lionfish In Belize: A New Insight On A Destructive Species, Joshua E. Balan Jan 2024

A Computational Profile Of Invasive Lionfish In Belize: A New Insight On A Destructive Species, Joshua E. Balan

The Journal of Purdue Undergraduate Research

Since their discovery in the region in 2009, invasive Indonesian-native lionfish have been taking over the Belize Barrier Reef. As a result, populations of local species have dwindled as they are either eaten or outcompeted by the invaders. This has led to devastating losses ecologically and economically; massive industries in the local nations, such as fisheries and tourism, have suffered greatly. Attempting to combat this, local organizations, from nonprofits to ecotourism companies, have been manually spear-hunting them on scuba dives to cull the population. One such company, Reef Conservation Institute (ReefCI), operating out of Tom Owens Caye outside of Placencia, …


Clouds In The Ancient Lunar Atmosphere: Water Ice Nucleation On Aerosol Simulants, Mariana C. Aguilar Jan 2024

Clouds In The Ancient Lunar Atmosphere: Water Ice Nucleation On Aerosol Simulants, Mariana C. Aguilar

The Journal of Purdue Undergraduate Research

Today’s moon is vastly different from what it was 3 billion years ago. At that time, it was home to a collisional atmosphere formed through massive amounts of volcanism, releasing enough subsurface gas to sustain surface pressures of up to 1 kPa. Observations of our solar system have taught us that all dense atmospheres are host to clouds and aerosols, and we expect the Moon’s to be no different. Knowing when, where, and under what conditions cloud particles form is important for understanding the evolution of the lunar atmosphere, how it reacted to temperature gradients, and how it cycled volatiles. …


Deep Learning Approaches For Chaotic Dynamics And High-Resolution Weather Simulations In The Us Midwest, Vlada Volyanskaya, Kabir Batra, Shubham Shrivastava Dec 2023

Deep Learning Approaches For Chaotic Dynamics And High-Resolution Weather Simulations In The Us Midwest, Vlada Volyanskaya, Kabir Batra, Shubham Shrivastava

Discovery Undergraduate Interdisciplinary Research Internship

Weather prediction is indispensable across various sectors, from agriculture to disaster forecasting, deeply influencing daily life and work. Recent advancement of AI foundation models for weather and climate predictions makes it possible to perform a large number of predictions in reasonable time to support timesensitive policy- and decision-making. However, the uncertainty quantification, validation, and attribution of these models have not been well explored, and the lack of knowledge can eventually hinder the improvement of their prediction accuracy and precision. Our project is embarking on a two-fold approach leveraging deep learning techniques (LSTM and Transformer) architectures. Firstly, we model the Lorenz …


Les Expositions Turnus, Une Page D’Histoire Transnationale Des Beaux-Arts En Suisse À La Fin Du Xixe Siècle. Et Comment Découvrir Les Humanités Numériques, Béatrice Joyeux-Prunel Dec 2023

Les Expositions Turnus, Une Page D’Histoire Transnationale Des Beaux-Arts En Suisse À La Fin Du Xixe Siècle. Et Comment Découvrir Les Humanités Numériques, Béatrice Joyeux-Prunel

Artl@s Bulletin

Cet article présente le travail de la classe d’introduction aux humanités numériques de l’Université de Genève sur les expositions Turnus en Suisse à partir des années 1840. Près de 50 catalogues ont été retranscrits, décrits et structurés à l’aide de scripts Python, puis géolocalisés. Les données ont été ajoutées à BasArt, le répertoire mondial de catalogues d’expositions d’Artl@s (https://artlas.huma-num.fr/map). Elles permettent de mieux comprendre les premières années de ces expositions et leurs dynamiques locales, fédérales et internationales. Le Turnus fut une plaque tournante pour les artistes suisses, voire un tremplin vers le marché européen de l’art.


Closing The Gap: Leveraging Aes-Ni To Balance Adversarial Advantage And Honest User Performance In Argon2i, Nicholas Harrell, Nathaniel Krakauer Nov 2023

Closing The Gap: Leveraging Aes-Ni To Balance Adversarial Advantage And Honest User Performance In Argon2i, Nicholas Harrell, Nathaniel Krakauer

CERIAS Technical Reports

The challenge of providing data privacy and integrity while maintaining efficient performance for honest users is a persistent concern in cryptography. Attackers exploit advances in parallel hardware and custom circuit hardware to gain an advantage over regular users. One such method is the use of Application-Specific Integrated Circuits (ASICs) to optimize key derivation function (KDF) algorithms, giving adversaries a significant advantage in password guessing and recovery attacks. Other examples include using graphical processing units (GPUs) and field programmable gate arrays (FPGAs). We propose a focused approach to close the gap between adversarial advantage and honest user performance by leveraging the …


Complex Impacts Of Wars On Global Sustainable Development In A Metacoupled World, Qutu Jiang, Zhenci Xu, Yuanzheng Cui, Jianguo Liu Oct 2023

Complex Impacts Of Wars On Global Sustainable Development In A Metacoupled World, Qutu Jiang, Zhenci Xu, Yuanzheng Cui, Jianguo Liu

I-GUIDE Forum

Wars and armed conflicts have had profound impacts on local and global sustainable development in an interconnected world. However, evidence on the impacts of wars is fragmented and little attention has been paid to the impacts on the 17 UN’s Sustainable Development Goals (SDGs), a unifying framework for achieving global sustainable development. This perspective synthesizes the scattered information to provide a holistic analysis and highlight the applications of remote sensing in assessing the impacts of wars on global sustainable development in a metacoupling world. Wars have complex impacts on all 17 SDGs, which cascade beyond conflict zones and spillover to …


Geospatial Data Integration Middleware For Exploratory Analytics Addressing Regional Natural Resource Grand Challenges In The Us Mountain West, Shannon Albeke, Nicholas Case, Samantha Ewers, Jeffrey Hamerlinck, William Kirkpatrick, Jerod Merkle, Luke Todd Oct 2023

Geospatial Data Integration Middleware For Exploratory Analytics Addressing Regional Natural Resource Grand Challenges In The Us Mountain West, Shannon Albeke, Nicholas Case, Samantha Ewers, Jeffrey Hamerlinck, William Kirkpatrick, Jerod Merkle, Luke Todd

I-GUIDE Forum

This paper describes CyberGIS-based research and development aimed at improving geospatial data integration and visual analytics to better understand the impact of regional climate change on water availability in the U.S. Rocky Mountains. Two Web computing applications are presented. DEVISE - Derived Environmental Variability Indices Spatial Extractor, streamlines utilization of environmental data for better-informed wildlife decisions by biologists and game managers. The WY-Adapt platform aims to enhance predictive understanding of climate change impacts on water availability through two modules: “Current Conditions” and “Future Scenarios”. It integrates high-resolution models of the biophysical environment and human interactions, providing a robust framework for …


Large-Scale Google Street View Images For Urban Change Detection, Fangzheng Lyu, Xinlin Ma, Yan Song, Eric Zhu, Shaowen Wang Oct 2023

Large-Scale Google Street View Images For Urban Change Detection, Fangzheng Lyu, Xinlin Ma, Yan Song, Eric Zhu, Shaowen Wang

I-GUIDE Forum

Urbanization has entered a new phase characterized by urban changes occurring at a micro-scale and “under the roof”, as opposed to external modifications. These changes, known as urban retrofitting, involve the incorporation of novel technologies or features into pre-existing systems to promote sustainability. Given the limitations of remote sensing images in identifying such urban changes, novel tools need to be developed for detecting urban retrofitting. In this study, we first build a pipeline to collect large-scale time-series urban street view images from Google Street View in Mecklenburg County, North Carolina. And we examine the feasibility of utilizing the acquired dataset …


Deep Q-Learning Framework For Quantitative Climate Change Adaptation Policy For Florida Road Network Due To Extreme Precipitation, Orhun Aydin Oct 2023

Deep Q-Learning Framework For Quantitative Climate Change Adaptation Policy For Florida Road Network Due To Extreme Precipitation, Orhun Aydin

I-GUIDE Forum

Climate change-induced extreme weather and increasing population are increasing the pressure on the global aging road networks. Adaptation requires designing interventions and alterations to the road networks that consider future dynamics of flooding and increased traffic due to the growing population. This paper introduces a reinforcement learning approach to designing interventions for Florida's road network under future traffic and climate projections. Three climate models and a tide and surge model are used to create flooding and coastal inundation projections, respectively. The optimal sequence of decisions for adapting Florida's road network to minimize flooding-related disruptions is solved by using a graph-based …


Graph Transformer Network For Flood Forecasting With Heterogeneous Covariates, Jimeng Shi, Vitalii Stebliankin, Zhaonan Wang, Shaowen Wang, Giri Narasimhan Oct 2023

Graph Transformer Network For Flood Forecasting With Heterogeneous Covariates, Jimeng Shi, Vitalii Stebliankin, Zhaonan Wang, Shaowen Wang, Giri Narasimhan

I-GUIDE Forum

Floods can be very destructive causing heavy damage to life, property, and livelihoods. Global climate change and the consequent sea-level rise have increased the occurrence of extreme weather events, resulting in elevated and frequent flood risk. Therefore, accurate and timely flood forecasting in coastal river systems is critical to facilitate good flood management. However, the computational tools currently used are either slow or inaccurate. In this paper, we propose a Flood prediction tool using Graph Transformer Network (FloodGTN) for river systems. More specifically, FloodGTN learns the spatio-temporal dependencies of water levels at different monitoring stations using Graph Neural Networks (GNNs) …


Solving Geospatial Problems Under Extreme Time Constraints: A Call For Inclusive Geocomputational Education, Coline C. Dony Oct 2023

Solving Geospatial Problems Under Extreme Time Constraints: A Call For Inclusive Geocomputational Education, Coline C. Dony

I-GUIDE Forum

To prepare our next generation to face geospatial problems that have extreme time constraints (e.g., disasters, climate change) we need to create educational pathways that help students develop their geocomputational thinking skills. First, educators are central in helping us create those pathways, therefore, we need to clearly convey to them why and in which contexts this thinking is necessary. For that purpose, a new definition for geocomputational thinking is suggested that makes it clear that this thinking is needed for geospatial problems that have extreme time constraints. Secondly, we can not further burden educators with more demands, rather we should …


Curriculum Design Of Artificial Intelligence And Sustainability In Secondary School, Jinyi Cai, Mei-Po Kwan, Chunyu Hou, Dong Liu, Yeung Yam Oct 2023

Curriculum Design Of Artificial Intelligence And Sustainability In Secondary School, Jinyi Cai, Mei-Po Kwan, Chunyu Hou, Dong Liu, Yeung Yam

I-GUIDE Forum

Artificial Intelligence is revolutionizing numerous sectors with its transformative power, while at the same time, there is an increasing sense of urgency to address sustainability challenges. Despite the significance of both areas, secondary school curriculums still lack comprehensive integration of AI and sustainability education. This paper presents a curriculum designed to bridge this gap. The curriculum integrates progressive objectives, computational thinking competencies and system thinking components across five modules—awareness, knowledge, interaction, empowerment and ethics—to cater to varying learner levels. System thinking components help students understand sustainability in a holistic manner. Computational thinking competencies aim to cultivate computational thinkers to guide …