Physical Sciences and Mathematics Commons^™

Acoustic Signatures Of Habitat Types In The Miombo Woodlands Of Western Tanzania, Sheryl Vanessa Amorocho, Dante Francomano, Kristen M. Bellisario, Ben Gottesman, Bryan C. Pijanowski

The Summer Undergraduate Research Fellowship (SURF) Symposium

The Miombo Woodlands of Tanzania comprise several habitat types that are home to a great number of flora and fauna. Understanding their responses to increasing human disturbance is important for conservation, especially in places where people depend so directly on their local ecosystem services to survive. Soundscapes are a powerful approach to study complex biomes undergoing change. The sounds emitted by soniferous fauna characterize the acoustic profile of the landscapes they inhabit such that habitats with the highest acoustic abundance are considered as the most diverse and possibly more ecologically resilient. However, acoustic variability within similar habitat types may pose …

Evaluation Of Radiation And Design Criteria For A Lunar Habitat, Hayley E. Bower, Daniel Gomez, Antonio Bobet, Julio A. Ramirez, Shirley J. Dyke, H. Jay Melosh

The Summer Undergraduate Research Fellowship (SURF) Symposium

Extraterrestrial habitation has long been the object of science fiction, and experts in the fields of science and engineering have proposed many designs for a lunar base. The research conducted has focused on either structural stability, radiation protection, or meteorite-impact vulnerabilities, but rarely have these been considered together. The Resilient ExtraTerrestrial Habitats (RETH) project aims to design a lunar habitat from a hazards perspective, considering general degradation, meteorite impacts, seismic activity, radiation exposure, thermal extremes, and geomagnetic storms in addition to the physiological, psychological, and sociological aspects of astronauts living in such a habitat. Several members of the RETH team …

Optimization And Control Of Production Of Graphene, Atharva Hans, Nimish M. Awalgaonkar, Majed Alrefae, Ilias Bilionis, Timothy S. Fisher

The Summer Undergraduate Research Fellowship (SURF) Symposium

Graphene is a 2-dimensional element of high practical importance. Despite its exceptional properties, graphene’s real applications in industrial or commercial products have been limited. There are many methods to produce graphene, but none has been successful in commercializing its production. Roll-to-roll plasma chemical vapor deposition (CVD) is used to manufacture graphene at large scale. In this research, we present a Bayesian linear regression model to predict the roll-to-roll plasma system’s electrode voltage and current; given a particular set of inputs. The inputs of the plasma system are power, pressure and concentration of gases; hydrogen, methane, oxygen, nitrogen and argon. This …

Visually Analyzing The Impacts Of Essential Air Service Funding Decisions, Rohan Kashuka, Chittayong Surakitbanharn, Calvin Yau, David S. Ebert

The Summer Undergraduate Research Fellowship (SURF) Symposium

Essential Air Service (EAS) is a U.S. government subsidy program which ensures maintenance of commercial airline services in small deregulated communities. The program’s budget currently is around $250 million annually, which is used as subsidy for airlines to maintain a minimal level of scheduled air service in relatively smaller airports. It is evident that 2% of the FAA budget is being spent to maintain air service in smaller communities, but there is not enough evidence to prove that all the current decisions made by Congress about EAS are advantageous. To understand these decisions, 15 years of data produced by the …

Exploration Of A Unique Uranium Mediated Carbon-Carbon Radical Coupling Reaction, Zhengjia Tong, Caleb J. Tatebe, John J. Kiernicki, Matthias Zeller, Suzanne C. Bart

The Summer Undergraduate Research Fellowship (SURF) Symposium

Designing an efficient nuclear fuel cycle has motivated decades of research on aqueous phase uranium chemistry. As such, studies are often limited by the formation of unreactive uranium oxides and/or solubility issues. Carrying out reactions in non-aqueous solvents addresses said problems and enables explorations into previously unattainable reactivity and fundamental properties of uranium. One such feat is the syntheses of uranium alkyls, as they permit research into bond interactions between uranium and carbon. Considering uranium’s oxophilicity, we investigated the relatively understudied uranium(III) alkyls—both their reactivity and reaction mechanism—towards oxygen-containing reagents. In an inert atmosphere, various uranium alkyl complexes were treated …

Temperature-Dependent Exciton Dynamics Of Superacid Treatment In Monolayers Of The Metal Dichalcogenide Mos2, Mingwei Zhou, Long Yuan, Jordan Snaider, Libai Huang

The Summer Undergraduate Research Fellowship (SURF) Symposium

To improve optoelectronic semiconductor materials, one of the most efficient research areas is the two-dimensional (2D) transition-metal dichalocogenides (TMDCs). It has been shown that organic nonoxidizing superacid bis(trifluoromethane)sulfonamide (TFSI) treatment of molybdenum disulfide (MoS₂) monolayer could uniformly enhance its photoluminescence by more than two orders of magnitude and also extend the lifetime of excitons. This could greatly improve the efficiency of the solar energy usage, but the mechanism behind it has not been fully understood. Extreme low temperatures (approximately 7K), which slow the surface exciton mobility, were applied to investigate the changes of treated MoS₂ monolayer surfaces. …

Ocean Wind Speed Measurement Using Wideband Gnss-R Signals, Brandon J. Kozel, Han Zhang, James L. Garrison, Benjamin Nold

The Summer Undergraduate Research Fellowship (SURF) Symposium

The use of Global Navigation Satellite System-Reflectometry (GNSS-R) for remote sensing of ocean wind speeds has been explored for nearly two decades and has become an important passive remote sensing technique for verification of hurricane formation models. To obtain wind speed measurements, reflected GNSS signals are first cross-correlated with locally generated copies to construct delay-doppler maps (DDMs). Through statistical models, DDMs can provide information about the mean-square slope (MSS) of the ocean surface, which is related to wind speed. Previous studies have focused on legacy signals such as GPS L1. However, it is expected that the MSS relationship with ocean …

How Strongly Do Oysters Stick?, Nicolás M. Morato, Andrés M. Tibabuzo, Jonathan J. Wilker

The Summer Undergraduate Research Fellowship (SURF) Symposium

Biological adhesives are a type of interfacial material that has incredible potential to generate new biomimetic compounds that can replace current strong, but toxic, adhesives. Therefore, a study of the chemical composition and mechanical properties of those bio-adhesives is necessary. However, in the case of oysters, despite known chemical characterization of the adult’s adhesive, there are almost no studies on its mechanical properties. Furthermore, there is no available information on the adhesive properties of spat (oysters in their larvae state). Herein, we present the first mechanical characterization of the spat adhesive, measuring its adhesion strength by hydrodynamic determination using a …

Hazard Assessment Of Meteoroid Impact For The Design Of Lunar Habitats, Herta Paola Montoya, Shirley Dyke, Julio A. Ramirez, Antonio Bobet, H. Jay Melosh, Daniel Gomez

The Summer Undergraduate Research Fellowship (SURF) Symposium

The design of self-sustaining lunar habitats is a challenge primarily due to the Moon’s lack of atmospheric protection and hazardous environment. To assure safe habitats that will lead to further lunar and space exploration, it is necessary to assess the different hazards faced on the Moon such as meteoroid impacts, extreme temperatures, and radiation. In particular, meteoroids pose a risk to lunar structures due to their high frequency of occurrence and hypervelocity impact. Continuous meteoroid impacts can harm structural elements and vital equipment compromising the well-being of lunar inhabitants. This study is focused on the hazard conceptualization and quantification of …

Applying Machine Learning To Computational Chemistry: Can We Predict Molecular Properties Faster Without Compromising Accuracy?, Hanjing Xu, Pradeep Gurunathan, Lyudmila Slipchenko

The Summer Undergraduate Research Fellowship (SURF) Symposium

Non-covalent interactions are crucial in analyzing protein folding and structure, function of DNA and RNA, structures of molecular crystals and aggregates, and many other processes in the fields of biology and chemistry. However, it is time and resource consuming to calculate such interactions using quantum-mechanical formulations. Our group has proposed previously that the effective fragment potential (EFP) method could serve as an efficient alternative to solve this problem. However, one of the computational bottlenecks of the EFP method is obtaining parameters for each molecule/fragment in the system, before the actual EFP simulations can be carried out. Here we present a …

Mobility Characteristics Of Azithromycin In Soil, Ryan Minter, Jihyun Kim, Linda Lee

The Summer Undergraduate Research Fellowship (SURF) Symposium

The presence of pharmaceutical and personal care products (PPCPs) in the environment has become a widespread problem in recent decades. Azithromycin, a macrolide antibiotic commonly prescribed for infections in humans, has been detected in waste treatment plant discharge and surface waters across the world. Data on the mobility characteristics of azithromycin in soil is scarce, and further studies must be performed to explore the potential for azithromycin leaching to groundwater or becoming available for plant uptake. In this study, azithromycin sorption isotherms were measured on eight soils varying in pH, organic carbon content, and clay content. Soil was equilibrated with …

Raman Spectroscopy Of Oxygen Evolution Catalysts And Psii Manganese Model Compounds, Sergei Shmakov, Daniel A. Hartzler, Alireza Karbakhsh Ravari, Yulia Pushkar

The Summer Undergraduate Research Fellowship (SURF) Symposium

Photosynthesis is the basis of life on earth, and oxygen evolution catalysts are key components of this complicated, yet not fully understood process. Photosystem II, a large membrane bound pigment-protein complex, is the key system that facilitates oxygenic photosynthesis via the oxygen evolving complex (a natural oxygen evolving catalyst). It is a key component in oxygen producing catalysts, which can be used in fields such as energy production and biomimetic catalysts. The oxygen evolution cycle, or Kok cycle going within it is still not studied completely. In this project, we were studying the vibrational (and structural) state of a Manganese …

Development Of A Water Quality Status And Trend Detection Tool*, Ruchir Aggarwal, Valeria Mijares, Margaret W. Gitau

The Summer Undergraduate Research Fellowship (SURF) Symposium

Water Quality Index (WQI) models have been developed since the early 1970s. They present a means by which water quality status and trends can be compared across time and space on the basis of a composite value computed using existing water quality data. There is a need for a tool that can bring the different water quality parameters together and calculate the WQIs so as to facilitate data use in predictive modeling and water quality management. We are developing a software tool that can be used by water quality managers and others with different technical backgrounds to calculate WQI of …

Machine Learning In Xenon1t Analysis, Dillon A. Davis, Rafael F. Lang, Darryl P. Masson

The Summer Undergraduate Research Fellowship (SURF) Symposium

In process of analyzing large amounts of quantitative data, it can be quite time consuming and challenging to uncover populations of interest contained amongst the background data. Therefore, the ability to partially automate the process while gaining additional insight into the interdependencies of key parameters via machine learning seems quite appealing. As of now, the primary means of reviewing the data is by manually plotting data in different parameter spaces to recognize key features, which is slow and error prone. In this experiment, many well-known machine learning algorithms were applied to a dataset to attempt to semi-automatically identify known populations, …

Using P-Band Signals Of Opportunity Radio Waves For Root Zone Soil Moisture Remote Sensing, Phillip H. Lipinski, Benjamin R. Nold, James L. Garrison

The Summer Undergraduate Research Fellowship (SURF) Symposium

Retrieval of Root Zone Soil Moisture (RZSM) is important for understanding the carbon cycle for use in climate change research as well as meteorology, hydrology, and precision agriculture studies. A current method of remote sensing, GNSS-R uses GPS signals to measure soil moisture content and vegetation biomass, but it is limited to 3-5 cm of soil penetration depth. Signals of Opportunity (SoOp) has emerged as an extension of GNSS-R remote sensing using communication signals. P-band communication signals (370 MHz) will be studied as an improved method of remote sensing of RZSM. P-band offers numerous advantages over GNSS-R, including stronger signal …

Structure-Force Field Generator For Molecular Dynamics Simulations, Carlos M. Patiño, Lorena Alzate, Alejandro Strachan

The Summer Undergraduate Research Fellowship (SURF) Symposium

Atomistic and molecular simulations have become an important research field due to the progress made in computer performance and the necessity of new and improved materials. Despite this, first principle simulations of large molecules are still not possible because the high computational time and resources required. Other methods, such as molecular dynamics, allow the simplification of calculations by defining energy terms to describe multiple atom interactions without compromising accuracy significantly. A group of these energy terms is called a force field, and each force field has its own descriptions and parameters. The objective of this project was to develop a …

Predictive Power And Validity Of Connectome Predictive Modeling: A Replication And Extension, Michael Wang, Joaquin Goni, Enrico Amico

The Summer Undergraduate Research Fellowship (SURF) Symposium

Neuroimaging, particularly functional magnetic resonance imaging (fMRI), is a rapidly growing research area and has applications ranging from disease classification to understanding neural development. With new advancements in imaging technology, researchers must employ new techniques to accommodate the influx of high resolution data sets. Here, we replicate a new technique: connectome-based predictive modeling (CPM), which constructs a linear predictive model of brain connectivity and behavior. CPM’s advantages over classic machine learning techniques include its relative ease of implementation and transparency compared to “black box” opaqueness and complexity. Is this method efficient, powerful, and reliable in the prediction of behavioral measures …

Predicting Locations Of Pollution Sources Using Convolutional Neural Networks, Yiheng Chi, Nickolas D. Winovich, Guang Lin

The Summer Undergraduate Research Fellowship (SURF) Symposium

Pollution is a severe problem today, and the main challenge in water and air pollution controls and eliminations is detecting and locating pollution sources. This research project aims to predict the locations of pollution sources given diffusion information of pollution in the form of array or image data. These predictions are done using machine learning. The relations between time, location, and pollution concentration are first formulated as pollution diffusion equations, which are partial differential equations (PDEs), and then deep convolutional neural networks are built and trained to solve these PDEs. The convolutional neural networks consist of convolutional layers, reLU layers …

How To Enhance Interdisciplinary Competence—Interdisciplinary Problem-Based Learning Versus Interdisciplinary Project-Based Learning, Mirjam Brassler, Jan Dettmers

Interdisciplinary Journal of Problem-Based Learning

Interdisciplinary competence is important in academia for both employability and sustainable development. However, to date, there are no specific interdisciplinary education models and, naturally, no empirical studies to assess them. Since problem-based learning (PBL) and project-based learning (PjBL) are learning approaches that emphasize students’ collaboration, both pedagogies seem suitable to enhance students’ interdisciplinary competence. Based on the principle of constructive alignment and four instructional principles on interdisciplinary learning, this paper proposes that students profit more from interdisciplinary PBL (iPBL) than interdisciplinary PjBL (iPjBL). A pre-post study was conducted with a sample of 95 students participating in iPBL and 183 students …

A Pattern Approach To Examine The Design Space Of Spatiotemporal Visualization, Chen Guo

Department of Computer Graphics Technology Degree Theses

Pattern language has been widely used in the development of visualization systems. This dissertation applies a pattern language approach to explore the design space of spatiotemporal visualization. The study provides a framework for both designers and novices to communicate, develop, evaluate, and share spatiotemporal visualization design on an abstract level. The touchstone of the work is a pattern language consisting of fifteen design patterns and four categories. In order to validate the design patterns, the researcher created two visualization systems with this framework in mind. The first system displayed the daily routine of human beings via a polygon-based visualization. The …

Mathematical Description And Mechanistic Reasoning: A Pathway Toward Stem Integration, Paul J. Weinberg

Journal of Pre-College Engineering Education Research (J-PEER)

Because reasoning about mechanism is critical to disciplined inquiry in science, technology, engineering, and mathematics (STEM) domains, this study focuses on ways to support the development of this form of reasoning. This study attends to how mechanistic reasoning is constituted through mathematical description. This study draws upon Smith’s (2007) characterization of mathematical description of scientific phenomena as ‘‘bootstrapping,’’ where negotiating the relationship between target phenomena and represented relations is fundamental to learning. In addition, the development of mathematical representation presents a viable pathway towards STEM integration. In this study, participants responded to an assessment of mechanistic reasoning while cognitive interviews …

The Introduction Of Informal Cooperative Learning Into Our Programming Laboratories, Guity Ravai, Ludmila Nunes, Ronald Erdei

IMPACT Presentations

Presented at the Women in Engineering ProActive Network (WEPAN) Change Leader Forum: Creating a Mindset for Action in Westminster, CO, USA

Datasets On The Genomic Positions Of The Mll1 Morphemes, The Zfp57 Binding Site, And Zfbs-Morph Overlaps In The Build Mm9 Of The Mouse Genome, Minou Bina, Phillip Wyss, Xiaohui C. Song

Department of Chemistry Faculty Publications

While MLL1 activates gene expression in most tissues, ZFP57 represses transcription. MLL1 selectively interacts with a group of nonmethylated DNA sequences known as the MLL1 morphemes. ZFP57 associates with a methylated hexamer (ZFBS), dispersed in the genomic DNA segments known as Imprinted Control Regions (ICRs) and germline Differentially Methylated Regions (gDMRs), to maintain allele-specific gene repression. We have identified a set of composite DNA elements (ZFBS-Morph overlaps) that provides the sequence context of ZFBS in the canonical ICRs/gDMRs. This report provides tables listing the nucleotide sequences of the MLL1 morphemes and ZFBS-Morph overlaps. The report also offers links to the …

Learning To Identify Depth Edges In Real-World Images With 3d Ground Truth, Krista A. Ehinger, Kevin T. Joseph, Wendy J. Adams, Erich W. Graf, James H. Elder

MODVIS Workshop

No abstract provided.

A Single Shape From Multiple Cues: How Local And Global Information Organizes Shape Inference, Benjamin Kunsberg, Steven W. Zucker

MODVIS Workshop

No abstract provided.

Shape Features Underlying The Perception Of Liquids, Jan Jaap R. Van Assen, Pascal Barla, Roland W. Fleming

MODVIS Workshop

No abstract provided.

Scoring Scene Symmetry, Morteza Rezanejad, John D. Wilder, Sven Dickinson, Allan Jepson, Dirk B. Walther, Kaleem Siddiqi

MODVIS Workshop

No abstract provided.

Can Cone Signals In The Wild Be Predicted From The Past?, David H. Foster, Iván Marín-Franch

MODVIS Workshop

In the natural world, the past is usually a good guide to the future. If light from the sun and sky is blue earlier in the day and yellow now, then it is likely to be more yellow later, as the sun's elevation decreases. But is the light reflected from a scene into the eye as predictable as the light incident upon the scene, especially when lighting changes are not just spectral but include changes in local shadows and mutual reflections? The aim of this work was to test the predictability of cone photoreceptor signals in the wild over the …

Role Of The Cost Of Plasticity In Determining The Features Of Fast Vision In Humans., Maria M. Del Viva Phd, Renato Budinich M. Sc, Laura Palmieri M. Sc, Vladimir S Georgiev Phd, Giovanni Punzi Phd

MODVIS Workshop

No abstract provided.

Large-Scale Discovery Of Visual Features For Object Recognition, Drew Linsley, Sven Eberhardt, Dan Shiebler, Thomas Serre

MODVIS Workshop

A central goal in vision science is to identify features that are important for object and scene recognition. Reverse correlation methods have been used to uncover features important for recognizing faces and other stimuli with low intra-class variability. However, these methods are less successful when applied to natural scenes with variability in their appearance.

To rectify this, we developed Clicktionary, a web-based game for identifying features for recognizing real-world objects. Pairs of participants play together in different roles to identify objects: A “teacher” reveals image regions diagnostic of the object’s category while a “student” tries to recognize the object. Aggregating …