Hoppin’ and Froggin’ Through the Rainforest

Hoppin’ and Froggin’ Through the Rainforest

            I spent my summer X-Sig experience with Professor Caldwell in Panama studying red-eyed treefrogs’ territorial behaviors and how they influence mating success.

Background:

Agalychnis callidryas, more commonly known as red-eyed treefrogs, are abundant in Neotropics. Males of this species tend to be found within the vegetation surrounding a given pond. From within these areas, they call for mates, and will fight off other male frogs of the same species using aggressive signals and even wrestling (Pyburn, 1970). These conflicts can last for many hours, sometimes stretching into the next day, which causes the frogs to miss the chance to mate (Caldwell et al., 2010). One likely reason that frogs may forgo mating during these long aggressive contests is that the calling site is held for an extended period of time. If this holds true, the frog loses one night of mating but gains a territory from which to court females on subsequent nights. The duration of time a male holds a territory has never been tested.

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Male red-eyed tree frog

Goals:

With this study I seek to answer two main questions: (1) Do red-eyed tree frog males hold their territories for multiple, consecutive nights, (2) Does the length of time they hold a territory influence mating success? I also wanted to determine whether the physical properties of males are correlated with their territorial behavior.

Procedure:

All of the field work and experimentation for this project is being performed at the Smithsonian Tropical Research Institute in Gamboa, Panama. Our main site is known as the “Experimental Pond” (“EP”). This is a large, concrete pond that is at the edge of the rainforest. It is full of various species of frog, caiman, and snakes, including the venomous fer de lance, the occasional anteater, basilisks, adorable kinkajous peering down from the trees, and every once and a while, an armadillo.

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Caiman at the Experimental  Pond

As my focus is on monitoring territoriality and mating success of male red-eyed treefrogs, tracking individual frogs is a necessity. To do this, I tag them with an 8 millimeter PIT tag right under their skin. Once a frog is tagged, I seal the wound with veterinary glue that becomes solid in    water(perfect for frogs).

Before tagging a new male, I take some measurements. I weigh him and measure his snout vent length (nose to cloaca) and right tibulofibular length (a measure of limb length). This allows me to look at which physical factors may contribute to success in mating or holding territory.

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Male with measurement tools

 

 

 

 

 

 

Each night, I conduct my first census tat 8:30 PM, using a handheld PIT tag reader to scan each frog and record his unique identification number and the exact location from which he was calling.

 

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Scanning male for PIT tag

The aim of this first check is to record the initial positions of males and any calling or aggressive behaviors as they first reach the pond. Any previously unmarked frogs are collected and tagged. At 11 PM, I conduct a second census, as calling activity is dying down, and most females have already selected a mate. So, across nights I have a record of where males are, who they are fighting with, and who gets to mate. With these data, I should be able to answer some important questions about what determines mating success in red-eyed treefrogs.

 

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The entire town of Gamboa and the Panama Canal as seen from the Canopy Tower

My X-Sig Experience, Beyond Research:

Tucked into the rainforest about 40 minutes outside of Panama City is the beautiful and wonderful town of Gamboa. In this town you will find many creative and unique people ranging from canal workers to scientists to bed and breakfast owners. The people are incredibly interesting and each one is more friendly than the last. This helped me to never feel lonely or homesick.

Coupled with the amazing people is an amazing atmosphere, full of flora and fauna one would never see on the East Coast of the States. One gets breathtaking experiences such as, feeding tamarin monkeys, waking up to parrots and toucans, and getting to hold a basilisk.

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Feeding tamarin monkeys

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Holding a basilisk

 

 

 

 

 

 

 

I never run out of things to do in Gamboa. When I’m not conducting research at the pond, there is the Summit Zoo, the Panama Canal, Panama City, the glamorous pool, the Canopy Tower, numerous hiking trails, and, of course, the Smithsonian Tropical Research Institute. Within the Smithsonian there are many events held, some scientific and some purely social. There are weekly seminars from an international cast of researchers, smaller talks on animal behavior experiments, educational classes such as a Statistics in R course I attended, women in science meetings, countless potlucks and barbecues, and Chiva buses. All of these adventures are shared with other researchers, interns, and graduate students from all over the world. It truly is a biologist’s paradise.

There are also opportunities trips farther away. Gamboa is surrounded by many beaches. I got the opportunity to take a trip to Playa Blanca on the Atlantic side of Panama with 13 other researchers, some PhD students, some interns, and some volunteers.  It was one of the most awesome days of my life. That is the beauty of Gamboa: it is full of hard working biologists, but when the work day is done everyone gets together and has a great time.

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The view on the boat to Playa Blanca

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The awesome Playa Blanca crew

 

This year in Panama was exciting due to the nation being in the World Cup. The nation as a whole erupted in pride and celebration after scoring their first ever goal in the World Cup. The World Cup allowed for lots of fun outings to watch the game with friends in the city. We got to watch the finals in the beautiful Casco Viejo, one of my favorite areas in Panama.

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The breathtaking and incredible Casco Viejo view

Facts and Skills Learned

  • How to work with a caiman in close proximity and staring at you
  • PIT tagging
  • Running is harder in the tropics
  • Frog and snake identification
  • Red-eyed treefrogs are adorable
  • Deer can, at times, be more aggressive than crocodiles
  • Identifying animals by the glow of their eyes in a headlamp
  • Working at night instead of during the day
  • Always look where you step
  • Basic data analysis in R
  • Tamarin monkeys love to be fed bananas
  • Overcoming language barriers when I’ve never had any Spanish language training
  • Moving away from everything I know to an unfamiliar place for 2 months is not as difficult as one would expect
  • Panama is incredible!

Thank you, Panama! I will miss you greatly and always appreciate what you have taught me.

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The crazy Panama City skyline

Sources:

Caldwell, M. S., et al. (2010). “Vibrational signaling in the agonistic interactions of red-  eyed treefrogs.” Current Biology 20(11): 1012-1017.

Pyburn, W. F. (1970). Breeding behavior of the leaf-frogs Phyllomedusa callidryas and Phyllomedusa dacnicolor in Mexico. Copeia, 209-218.

 

 

 

Fun with Android

The Android logo. android.com

As part of our X-SIG program, we we are working on education research and developing educational tools for future students. We split our efforts between finding the best ways to help people understand novel programming concepts, and building the most effective tools to implement those approaches. To explain, we’ll have to provide a little bit of background.

Background – Nathanael Epps and Jordan McShan

The homework assignments in CS111 courses involve making apps for Android, as it provides an intuitive entry point for students to familiarize themselves with the basics of programming. Working from the very beginning with the CS department’s custom-built graphics tools allows them to directly see how their code is working, and learn some of the common practices and expectations of programming languages in an unimposing context. In general, when you want to write an app for a given platform, you would normally use the provided Application Programming Interface, or API*. However, the Android API is large and complex, which is good for those who need fine-grained control over their app, but can be a hurdle to those new to programming. In the context of an intro-level computer science course, the focus of the homework should be less on learning the ins and outs of a particular software or programming language, and more focused on programming concepts. Focusing on concepts as opposed to focusing on any one specific language allows a student to pick up the skills necessary to learn any programming language or work with the latest software. So, to get around this issue, the CS department created their own API that uses the Android API but makes it substantially easier for the intro students (the hiding of details of operation and exposure of what’s essential is a concept called abstraction in computer science.) So, those who take the CS111 courses get the best of both worlds- they’re easily able to write apps for Android, and also able to focus on learning important concepts that will be applicable no matter the programming language or technology. Over the course of eight weeks, we have been focused on adding features and improving the code base.

Adding Features and General Improvements – Nathanael Epps

A Hangman game built using the CS department’s library

Over the last few weeks, my focus has been to learn about the Android API and learn the API of the department so I can add to and improve it. During the course of the first week, I familiarized myself with the Android API by writing a simple tic-tac-toe app, using the Android API and not the department’s code. Although I initially felt like I was banging my head against the wall trying to learn to use the monolithic code base that is the Android API, I eventually began making progress and was able to create an app that plays intelligently against the user. During the second week, I familiarized myself with the department’s API by doing some of the homework from CS 111. I was able to see firsthand why working with an easier-to-use API makes the lives of the students substantially easier. Also, I completed the XSig ethics course. During the third week, I started on new features. I added code that allowed students to play sequences of notes easily, and started working on some code that would allow students to read CSV data files from the internet. During the fourth week, I finished the CSV reading code, and started on code to allow students to use the camera from their apps. I also added a feature that would allow students to use location services of the device to get the phone’s location. During the fifth week, I continued camera usage code, and enabled bluetooth emulation and tested it with a two-player tic-tac-toe app. Also, I started looking at changing the build system. What’s a build system, you ask? Let me explain.

The Gradle build tool’s logo. gradle.org

Certain programming languages, like Java, C, C++, and a lot of others, are said to be compiled, which (basically) means it has to be turned from the source code that people can read and write to the 1’s and 0’s that the computer can understand. If you have a Java program composed of multiple files, they have to all be compiled separately and then are bundled into a .jar file. This can be a painstaking process to do for each and every file of your project, so what a build system will do is let you write a script that tells the build system what to do, and then you can compile your whole project in a single command. While build systems differ, this is the general idea.

Currently, CS111 projects are built using a build system called Ant. I’m in the process of switching a project from using Ant to a newer, shinier build system called Gradle, which is the build system Google uses to build Android apps.

Porting the code to iOS – Jordan McShan

A Blackjack game built using the CS department’s library

    While Nate and I spent our first week and a half in much the same way, familiarizing ourselves first with the Android API and then with the the CS department’s one, our paths soon diverged. The college’s API was built exclusively for Android devices, and my goal was to expand that system to work with other operating systems like iOS. Apple, however, does not use Java as an accepted programming language on their devices, and that was the challenge.

I needed a way to take the code that students would write in one language, and translate it into another. The good news is that such a tool already exists, an impressively dynamic, capable system called Multi-OS Engine, or MOE. It allows developers to write code in Java, which MOE then converts to an Apple-accepted language when the program runs, allowing programmers to write for Apple devices without ever needing to see another language or the work happening behind the scenes.

Concept image for Multi-OS Engine’s model for developing on multiple systems. https://multi-os-engine.org/

What has made my work so interesting is that neither MOE’s creator nor anyone else has published significant documentation on how it works, leaving me in the curious position of reverse-engineering it. I find myself often looking for how to do things in the Apple language, Objective-C, so that I can probe MOE for something similar, and then experimenting with that to find how it works. Though the names in Objective-C are often similar to MOE’s Java tools, the ways one interacts with them are often radically different. It took nearly two days of researching, testing, and digging through old snippets of example code in order to display a circle on the screen of my iPhone. But oh, what a beautiful circle it was when at last it appeared. Finally cracking the code on how to display to the screen was equivalent to a dam being broken, and within a couple hours I had implemented all the rest of the CS API’s drawing tools.

After that, it has just been a matter of continuing to expand the iOS library, working in a strange twilight zone where my code is technically one language and conceptually another. I have since added all the functionality present in the Android version of the code, and have begun implementing brand-new features as well. This includes an ID system that allows students to interact with shapes they have drawn on the screen.

Most recently, I started writing a program that allows students to add images and audio to their program without needing to go through Apple’s user interface. As a long-time Windows user, I find myself continually baffled by design choices made at every layer of the Apple experience, but none more so than the fact that they designed their programming interface to require manually clicking and dragging things every time you want to show a different image. My program now circumvents that need. The largest piece of the puzzle remaining now is putting all of these different tools together and making them work as cleanly as possible. The program where the students write their code is not configured to build and run it by default, so we will need to modify it to create the right kind of project, manipulate the customized files as needed, and and hide all the complicated intermediate steps behind the scenes, allowing students to focus on the important parts.

Effect of Textures and Motion on 3D Shape Perception in Visualization

A key objective in visualization research is to design and implement algorithms to effectively communicate scientific data so that the essential features of the data can be understood intuitively and accurately.
The accurate perception of shape and surface details is crucial for correctly interpreting the images.
Previous research has shown that humans can perceive three-dimensional shape from two-dimensional images using the pictorial cues present in the images.
For example, shading is a pictorial cue that can be very effective in conveying three-dimensional shape. However, shading alone is not optimal for all purposes, since shading does not provide sufficient detail of local shape when the viewers zoom in on a part of the object (As shown in Figure 1 below).

Figure 1: Global View V.S. Local View

Previous studies have shown that using an appropriate texture can provide improved perception of the shape of an object:

Figure 2: Visual Perception of Smoothly Curved Surfaces from Double-Projected Contour Patterns

As we saw from Figure 2, for example, image a provides better shape perception then image d, so texture in image a is more appropriate then the one in image d.

Previous studies have also found that the first principal direction textures improve perception of 3D shapes best. The first principal direction of a vertex on a surface is the greatest curvature at that point. Figure 3 is another image with four different textures where the top left one uses first principal direction, the top right on uses isomorphic texture, the bottom left one has swirly texture and the bottom right one applies uniform texture.

Figure 3: Different kinds of Textures on same Image

In our project, we consider the impact of motion on the accuracy of shape perception. Structure-from-motion provides a strong shape cue and we hope to evaluate its effect on shape perception by comparing the accuracy obtained through motion of a textured object itself, and through the motion of texture on a stationary object. The project goal for this eight-week research is to create moving texture in which the texture elements follow principal directions.

We started with simple 3D shapes for testing: ellipse, cylinder, and saddle. We extended our testing to complex shapes such as a spline terrain.

Figure 4 and 5 show the visualization of the cylinder and simple terrain models using their triangular faces. The library we use for drawing shapes (as well as their textures which will show later) in python is named pyglet.

Figure 4: Triangle Surface for Cylinder

Figure 5: Triangle Surface for Spline

We then added the first principal direction textures to each surface (as shown in the following two figures). Principal direction lines for each point are in yellow color:

Figure 6: Triangle Surface + 1st Principal Direction for Cylinder

Figure 7: Triangle Surface + 1st Principal Direction for Spline

Furthermore, we added motion to the first principal direction textures. See Figure 8 and 9 for the results:

Figure 8: Triangle Surface + moving 1st principal Direction Texture for Cylinder

Figure 9: Triangle Surface + moving 1st principal Direction Texture for Spline

We have attempted to use a non-photorealistic rendering (NPR) technique to create better images. Figure 10 and 11 show the same cylinder and spline shapes with moving lines along the first principal directions (colored in purple).

Figure 10: Triangle Surface + moving 1st principal Direction Texture for Cylinder

Figure 11: Triangle Surface + moving 1st principal Direction Texture for Spline

In our current algorithm, one stroke is created for each triangle and for a large model we may end up with too many strokes that are too close to each other. In order to more evenly spaced them out, we apply a clustering algorithm which groups triangles on the surface based on the nearness. Figure 12 and 13 show color coded clusters on a half cylinder model and a spline model .

Figure 12: Color coded clusters on half cylinder model

Figure 13: Color coded clusters on spline model

Figure 14 and 15 show moving textures with one stroke per cluster on a half cylinder model. For each cluster, the stroke that was closest to the centroid of the cluster would be picked.

Figure 14: One stroke per cluster on half cylinder model with its own color

Figure 15: One stroke per cluster on half cylinder model with  uniform color

Figure 16 and 17 show moving textures with one stroke per cluster on a spline model. The strokes are picked the same way as explained above.

Figure 16: One stroke per cluster on spline model with its own color

Figure 17: One stroke per cluster on spline model with uniform color

Future work of this research includes improving the moving textures on complex models that have many changing directions as well as designing and running a user study to compare the performance of human observers on shape perception tasks under two different motion conditions: the motion of a textured object itself, and  the motion of texture on a stationary object.

The Whatley Lab: From Happy Biofilm Partners to the Dynamics of Antimicrobials

Elli Vickers ‘20

Bacteria are small microbes that are usually studied in the planktonic state (free-floating cells). But in nature, bacteria often aggregate into structures called biofilms, clumps of bacteria that stick to a surface and secrete a protective matrix of sugars and proteins. These biofilms protect the bacteria from antibiotics, which is a huge issue for human health! Many drug-resistant infections are due to biofilms. Our lab explores how biofilms form, interact, and communicate in the hopes of better understanding how to treat biofilm-related infections.Screen Shot 2018-07-22 at 1.45.19 PM

Scanning electron microscopy images of planktonic (left) and biofilm (right) cells. On the left are planktonic (free-floating) Mycoplasma bovis cells from Chen et al. 2018. On the right is a biofilm with Microbacterium oxydans and Chryseobacterium hispalense, taken by our very own Sarah DiDomenico! We can see how complex and impenetrable the biofilm is compared to the planktonic cells.

Our lab previously identified a novel biofilm between Microbacterium oxydans and Chryseobacterium hispalense. These two microbes are found in the skin and gut microbiomes, in soil, and in water systems. In fact, we swabbed a drinking water fountain (in Science Center!) and isolated these two microbes growing in a synergistic biofilm. This interaction is synergistic because while neither partner forms much biofilm alone, the two partners together form tons of biofilm! This synergism is sustained for over 200 hours.

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That’s a water fountain in Science Center. We swabbed the fountain, streaked onto R2A agar (yummy bacteria nutrients), and found these orange and yellow colonies of bacteria! The whiter colonies are Microbacterium, while Chryseobacterium produces that orange pigment. Yes, those bacteria came from your water fountain.

We want to explore this biofilm synergism because while Microbacterium and Chryseobacterium alone are not pathogenic to humans, they are often found in polymicrobial biofilms (often containing pathogens) that can contaminate hospital water systems and lead to infections in surgical patients. Understanding how these two microbes interact and communicate may help us fight these stubborn aquatic biofilms.

My goal this summer is to quantify the expression of different genes in Chryseobacterium when it is alone versus paired with Microbacterium. Our genes are encoded by DNA but are expressed by RNA, which is then translated into proteins that make us who we are! Earlier this summer, I isolated the total RNA from Chryseobacterium alone and partnered with Microbacterium. We sent this off to be sequenced. The results will compare the RNA levels (gene expression) between the two conditions (Chryseobacterium alone versus with Microbacterium). This will give us a sense of what genes are differentially expressed when Chryseobacterium meets Microbacterium.

Once we have a sense of what systems are important for this partner synergism, I will use quantitative PCR to absolutely quantify the expression of genes of interest to us. PCR (polymerase chain reaction) is basically replicating DNA in a test tube instead of in our cells! Quantitative PCR incorporates fluorescence into each strand of DNA that is replicated – more fluorescence builds up as the DNA is replicated with each cycle of qPCR. We can detect that fluorescence and use it to quantify gene expression! If we take RNA from Chryseobacterium alone versus paired with Microbacterium, we can amplify genes of interest in Chryseobacterium and use qPCR to compare their expression in the presence and absence of Microbacterium.

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This is a plot of qPCR amplification. With every cycle (X axis), more DNA is replicated, so more fluorescence builds up (Y axis). The colorful lines represent all of the samples that I am running in a single qPCR reaction! Some samples amplify earlier, indicating that there is more RNA of these genes because they are more highly expressed under these conditions.

Currently, I am working on quantifying expression of the Type IX Secretion System (T9SS). Bacteria have many systems to move proteins from the cell to the environment, and the T9SS is a novel secretion system only found in relatives of Chryseobacterium. Its main function is in bacterial motility, but it also has links to colonization and biofilm formation! Our lab has previously identified that our Chryseobacterium isolate contains many T9SS genes. My current project is to use qPCR to quantify expression of these T9SS genes when Chryseobacterium is alone versus paired with Microbacterium to see if the T9SS is involved in our partner synergism.

 

Sarah DiDomenico ‘19

Exploring the role of dinB in the bacterial response to quinolones

Quinolones are a class of antibiotics used in pharmacology and agriculture that act as topoisomerase inhibitors. We are interested in studying how quinolones kill cells because a greater understanding will lead to better development of antibiotics in the future. This is critical especially with the rise of antibiotic resistance.

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Figure 1. Schematic representation of how SCCs lead to cell death.

We know that quinolones kill bacteria by binding to topoisomerases, a protein found on actively replicating DNA that helps to relax the DNA as it unwinds. The quinolone bound to the topoisomerase creates a stabilized cleavage complex (SCC). SCCs lead to the generation of double strand breaks (DSBs) which leads to cell death. However, we do not know how exactly SCCs cause double strand breaks. Some scientists believe that SCCs can cause double strand breaks without DNA replication occuring. We believe that SCCs can only cause double strand breaks when new DNA is being synthesized.

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Figure 2. Subunits of Polymerase III. Arrow indicates the subunit interaction of interest.

Previous research (by Dr. Whatley) explored the role of the epsilon subunit of Polymerase III, the protein responsible for synthesizing new DNA, in DSB generation. Traditionally, the epsilon subunit was believed to only be responsible for proofreading newly synthesized DNA. In other words, if a T was matched with a C, epsilon could cut out the C and replace it with the correct match, A. Dr. Whatley found that epsilon is also responsible for stabilizing the interaction of the alpha and beta subunits of Polymerase III (Figure 2). To explain how SCCs caused DSBs she developed the Replication Run-Off model. We believe that the processive replisome encounters the SCC causing stalled replication, dissociation of the complex, and release of double stranded DNA.

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Figure 3. Comparing the growth of E. coli mutants to Wildtype in the presence of norfloxacin.

To test this model, Dr. Whatley created a weak and a strong mutant, which had a weaker or stronger epsilon-beta interaction compared to Wildtype. These mutants were treated with norfloxacin, a quinolone, and allowed to grow. The growth of the mutants in the presence of norfloxacin aligns with the predictions based on the replication run-off model. The weak mutant is less sensitive to norfloxacin compared to Wild type due to the weak epsilon-beta interaction causing Pol III to encounter fewer SCCs and create fewer DSBs. The strong mutant is more sensitive to norfloxacin compared to Wild type due to the strong epsilon-beta interaction causing Pol III to encounter more SSCs and generate more more DSBs.

This summer, I am expanding on this project by exploring the role of dinB in the bacterial response to quinolones. dinB is a gene that encodes for Polymerase IV, an error prone polymerase that performs Translesion DNA Synthesis (TLS). This polymerase is able to replicate past damage that Pol III can not. To test if dinB contributes to the survival of our epsilon mutants, we deleted dinB to test how the weak and strong mutants would act without it. The mutants without dinB were treated with norfloxacin and allowed to grow. These results were compared to the results of the growth assay performed on the mutants with dinB. The weak mutant without dinB grew much less than the weak mutant with dinB, which was expected because the damage experienced by the strain without dinB could not be rescued by Pol IV. Additionally, the strong mutant without dinB survived less than the strong mutant with dinB, which was not expected due to the hypothesized inaccessibility of the B-clamp in this strong mutant. Thus,we predicted that Pol IV could have an additional role other than TLS, or may access the clamp differently in these mutants.

I tested for other roles of dinB in the bacterial response to quinolones. One experiment I performed was a B-galactosidase assay to measure SOS response. The SOS response is the cell’s reaction to DNA damage. We expect dinB to prevent the SOS response from occurring because it is able to rescue endogenous damage. I treated the bacteria with norfloxacin and let it grow. Then I added a chemical that is converted to a yellow color by an enzyme present during the SOS response. I use the amount of yellow produced over time as a direct measure of levels of SOS response. Comparing the levels of SOS produced by the different mutants will reveal other possible roles of Pol IV (dinB).

Bats, Frogs, Beetles, and Flies, Oh My! The Trillo Lab’s Trek into the Rainforest of Gamboa, Panama

Bats, Frogs, Beetles, and Flies, Oh My! The Trillo Lab’s Trek into the Rainforest of Gamboa, Panama

The Canal Zone Life: Cargo Ships and Canopy Covers

Gamboa is a small town about an hour from Panama city, packed with scientists working at the Smithsonian Tropical Research Institute (STRI). Many of the people you encounter walking through Gamboa smile at you, say hi and then go back to excavating ant nests, collecting frog foam nests, mistnetting for birds, or setting up insect traps. Everyone is doing some kind of exciting research on tropical plants and animals. This place is a biology student’s dream! There is a strong sense of community among the people here, all united by science, that makes this area so hospitable to biology newcomers. We interact with fellow interns, graduate students, postdocs, faculty and staff scientists on a daily basis. We attend weekly talks given by researchers presenting their findings to the rest of the community. Some topics have included phenotypic plasticity in hatching tadpoles of red-eye treefrogs, vibrational eavesdropping of frog-biting midges, cognitive mapping in poison dart frogs, and genomic variation and aggression in hybrids of jacana birds species. Other cool activities have included taking a workshop in R statistics and attending bi-weekly Women in Science meetings. Dr Trillo gave a talk in one of these Women in Science meetings a couple of weeks ago, and Taylor will be leading a discussion for the next meeting, the same day this blog is posted!

Being right next to the Panama Canal is a unique experience as well. It’s not uncommon to see huge cargo ships carrying large containers on our way to the field. So what do we do in this magical town of Gamboa? We are currently working on two different projects, so we are bat-frog-fly researchers by night and beetle researchers by day!

Boattreck into forest

On the left, a cargo ship as it passes through the canal, on the right our nightly trek into the forest

The Bats, the frogs, and the flies – our night gig:

Túngara frogs, or Engystomops pustulosus, are an important part of the ecology of the rainforest, providing a source of food for many animals including the fringe-lipped bat, Trachops cirrhosus, and various species of snakes, herons, and other frogs. They are also often subject to parasitism from frog-biting midges of the Corethrella genus. These frogs breed in ponds or puddles, with the males producing calls to attract the females to them. One of the more interesting facts about this frog is that it has the ability to call in two different ways: a simple call, where a single whine is produced, and a complex call, consisting of the whine with the addition of another note, referred to as the chuck. Females prefer males that produce complex calls over those who only call with this whine. However, while this proves advantageous for males in terms of sexual selection, it does not come without a cost – complex calls are also more favorable for predators and parasites, increasing the male’s risk of being discovered and eaten or parasitized. The hourglass treefrog, Dendropsophus ebraccatus, is known to occupy the same ponds for breeding, which raises questions about the effects of the presence of the highly attractive túngara frogs on predation and parasitism risk for hourglass treefrogs. In a paper published in 2016, Dr. Trillo concluded that hourglass treefrogs had higher rates of parasitism by midges when the túngara frogs were calling nearby. This effect was called Collateral Damage.

Question and experimental design: This year, we want to better understand the mechanisms behind this collateral damage. Our focus is on the effects that túngara frog calling density might have on the predation and parasitism faced by hourglass treefrogs. Is the collateral damage of túngara attracting parasites to hourglass treefrogs enhanced or reduced with an increase in túngara calling density? To do this, we carry out field phonotaxis experiments. We set up speakers that play calls of both types of frogs and use IR lights and video cameras to record the frequency of bat visitations to these speakers. We also collect Corethrella flies attracted to the calls with tanglefoot traps on top of the speaker. We have three different treatments for each of seven sites: (1)“EE” treatment – a speaker playing the calls of an hourglass treefrog next to a speaker with another hourglass treefrog call, (2)“TC” treatment – a speaker playing the calls of an hourglass treefrog next to a speaker playing complex túngara calls, and (3)“MTC” treatment – a speaker playing the calls of an hourglass treefrog accompanied by five speakers playing complex túngara calls. Every day, we store all videos for later analysis and the count the number of midges that came to each speaker.

B and T on Bridge

Brian Ruether ‘19 and Taylor Derick ‘20 waiting on a bridge above el Río Frijole for a phonotaxis experiment to finish.

The Beetles – our day gig: Our second project looks at the ecology of anti-predator chemical defenses in tortoise beetle larvae.

Background: This study stems from the ‘escape and radiate’ hypothesis, which states that when organisms evolve a new defense mechanism to combat their predators, they become free of enemies, which allows them to conquer new niches, speciate, and diversify.  Once predators eventually evolve ways to combat these defenses, the prey will evolve a novel defense again, thus repeating the cycle.  This hypothesis has been previously evaluated in herbivore-plant interactions, but less is known about its relevance to predator-herbivore interactions. This year, we will be continuing last year’s research to specifically test if it is more effective for a prey species to evolve a chemical defense with a broad effectiveness against a motley of different predators, or to evolve a chemical defense with a narrow range of effectiveness to combat a single dominating predatory species. We chose tortoise beetles to answer this question because the larvae of several tortoise beetles can be impressive warriors! Using a telescoping anus, they wave around shields that include fecal matter to defend themselves both physically and chemically.  It is thought that the chemicals in their shields are derived from a variety of compounds found in the plants that they eat. Our plan is to evaluate the effect of different defensive compounds found in the larvae’s shields and see how effective they are on different insect predators.

Larvae on Leaf

alternans larvae munching away on a leaf. Orange arrow indicates shield, blue arrow indicates larvae. It’s hard for a predator to attack when a larva is covered by such a large shield!

Question and experimental design:  We paint mealworms, a neutral prey item, with different shield-derived chemical-compounds and present them to each of four different predators.  We can then assess which chemicals provide a broad-spectrum defense against a variety of different predators and/or which chemicals provide a narrower defense against a single variety of predator. Our predators include preying mantises (Acanthops falcata and Oxyopsis gracilis), golden silk spiders (Nephila clavipes), true bugs of the family Reduviidae, and Azteca ants.  We have finally collected and housed our predators and will begin the predator bioassay trials next week!  We are excited to see what happens!

Mantis

A dead-leaf or boxer mantis, Acanthops falcata

Everyday Life in the Field: Working on different projects means coming up the the most efficient ways to conduct our research and troubleshooting so that we can maximize our data collection for the two months that we are here. So every day is quite different! However, daily life can typically include things like:

Ø Waking up to the sound of parrots and parakeets serenading you in the early morning

Ø Feeding the local tamarin monkeys (they really like apples and bananas)

Ø Counting lots of Corethrella flies from the night before!!

Ø Collecting predators for the beetle chemistry experiment

Ø Going to hear a “frog talk” or a Tupper talk

Ø Going out at night for the phonotaxis experiments

Ø Getting bit by mosquitoes while hiking through the breathtaking rainforest to set up the speakers!

Monkey and Taylor

Taylor feeding the tamarins one morning!

Unexpected Encounters: Sometimes while waiting for the treatments to finish, we run into some amazing tropical animals that are out in the forest! Our highlights so far include capybaras, a caiman, a coati, night monkeys, various kinds of snakes, anteaters, armadillos, and sloths! The forest is wide awake at night and booming with activity, sometimes involving wild cicada attacks (a cicada flew at Taylor’s face and has quite possibly traumatized her), frog catching (Brian’s excellent handling of Leptodactylus pentodactylus frogs), and even interrupting the filming of a horror movie! The most important thing to remember is that the forest throws unexpected challenges at you (like tree falls that block your way back to town and back up traffic for 2 hours), but you have to learn to be flexible and roll with the punches (what do you do? you walk around the tree to get ready for field work on time!).

Coati

A hungry coati we encountered on our way to work!

When we take a break from science, we can go hiking or biking in the rainforest, or go to the beach. Doing things like grocery shopping and picking up equipment requires us to go across the bridge into the city, leading to another observation that, according to Taylor, Panama traffic is way worse than New Jersey traffic! Although the traffic can be frustrating, it helps to have a great group of people to talk to while you wait! It’s also common to encounter torrential downpours, and we’ve learned to accept that rain comes quite irregularly, and we embrace getting drenched (as long as we don’t have equipment with us)!

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Approaching rain viewed from the canopy tower, the highest point in Gamboa.

We are so grateful that every day we get to wake up to the amazing life of field biologists-in-training and want to express our gratitude to Dr. Trillo and Dr. Caldwell for letting us tag along and experience all that we can in the short time that we are here!

 

The Age of Phage

Though you may not have heard of them before, bacteriophage are all around us. They’re in the ground we walk on, the ocean we swim in, even in the rain! These little viruses are thought to be the most numerous organisms on the face of the Earth, with an estimated 10^31 of them all around our planet. Even if you added up every single other life form (so all of the people, blades of grass, bacterial cells, everything), there are still more phage!

So, what are these creatures? They’re viruses that specifically infect bacteria, which they do because they can’t reproduce on their own. This inability to reproduce by themselves spurned a huge debate within the phage community about whether they are living or not. The Delesalle lab likes to give them the benefit of the doubt!! They inject their DNA into a bacterial cell, and then their DNA can integrate into the bacteria’s genome, or they can take over cellular machinery to replicate their own DNA. At some point, phage will typically lyse its host bacteria – once it’s replicated enough, it breaks apart the host so it can get back into the environment and look for more bacterial hosts to infect.

One big reason why researchers are so interested in phage is that they could potentially be more effective at fighting infections than antibiotic drugs are. With a regular antibiotic, a resistant bacteria colony could emerge over time and the antibiotic would no longer be effective. Unlike an antibiotic drug, phage can evolve. Numerous studies have found phage evolving with their bacterial hosts, making it difficult for a completely resistant bacteria strain to emerge. The reason phage are not in your local CVS is twofold.  First, due to phage’s specificity, an effective medication would need to have many different phage. At the current stage of phage research, there are not enough studied phage for such a treatment. Secondly, because one of the major benefits of phage is their ability to evolve with their hosts, it is difficult for the FDA to effectively regulate them. However, the reality is that phage are safe when administered properly, and are already used to prevent infection in food items such as lettuce and cow meat.

While some labs across the nation focus more on the medical applications of phage, we are interested in looking at the evolutionary capabilities of phage! This summer we’re aiming to isolate novel phage from soil samples our lab collected from the American Southwest in previous years. Once we isolate phage, we can get their DNA sequenced, and use comparative genomics to determine why some are able to infect more strains of bacteria than others. Understanding how slight genetic differences impact the host range of a phage is key to understanding how to use the phage. Finding slight genetic differences in otherwise similar phage also lets us perform future evolutionary studies!

 

A Day in the Life of the Lab:

Usually, we start off our day by looking at our petri plates from the day before. Because we need bacteria to grow in order for our phage to replicate, we let our plates sit in the incubator overnight. Because phage kill (or eat, nom nom) the bacteria around them, the little holes (“plaques”) where the light shines through are where phage are present. Different phage make different types of plaques, which can help us to tell them apart!

We also spend most mornings making media that we can use to grow and plate our phage/bacteria combinations.

Madeleine & Sam begin the lengthy process of making agar plates in order to give our phage and bacteria a home.

For current and future experiments, we need to know the specific concentrations of our stock bacteria strains. Most of them we know, but when we grow up more bacteria (like we did this week), we need to do serial dilutions to find the concentration. This is the process of repeatedly diluting the bacteria in order to count colony forming units.  However, this process has a lot of room for inconsistency and contamination, meaning that one strain of bacteria may take many tries to accurately complete.

                                         A cereal dilution

The rest of the day usually consists of working with different concentrations of various strains of phage and bacteria that will eventually be combined so we can observe their interactions on the petri plate the following day.

Aside from wet lab work, our days are also interspersed with bioinformatics work. This can be done after isolating and obtaining a DNA sequence from phage we isolate in lab. With sequence in hand, we can analyze the individual genes that compose each unique phage genome while also comparing each entire phage genome to the genomes of all other phage in online databases (that we try to add to on a regular basis). Each phage we isolate and annotate adds another drop of water to our knowledge of phage (all the phage are like an ocean so we have a ways to go).

What’s Wrong with Being Confident?

Our society expects us to display confidence in order to succeed. Some people internalize this pressure much more than others, with young adults demonstrating high levels of the personality trait called effortlessly perfect self-presentation. Someone high in effortlessly perfect self-presentation not only feels a need to appear perfect, but also to appear to have achieved perfection naturally, without any reason for effort or self-doubt. News stories have suggested that pressures to appear effortlessly perfect are associated with mental health problems such as depression and anxiety in college students. However, little data actually exist on this issue.

The research question the personality lab has been studying is whether there may be a cost to always being encouraged to be confident when you are not feeling your best. We suspected that the need to present constant self-confidence may lead people to criticize and judge themselves for the negative emotions that they experience under stress, rather than approaching these situations with self-compassion. Self-compassion is the concept of being kind to yourself, practicing mindfulness, and reminding yourself that it is part of being human to have flaws and make mistakes. Most importantly, self-compassion implies that you not be too harsh on yourself, especially when you’re struggling.

In our study, we had participants fill out a number of personality questionnaires. Following this, participants were asked to complete a five-minute writing task in one of three conditions, where they were primed to think about the importance of self-confidence, self-compassion, or a neutral condition. The neutral control prompt involved writing about a place to eat around Gettysburg.

After the five minutes were up, participants were presented with a very difficult series of puzzles. The experimenter was required to sit alongside the participant in complete silence as the participant struggled with the puzzles. Shortly after, the participant completed a few more questionnaires about their feelings of self-compassion and mood at that moment.

After running more participants this summer, we started analyzing the data. First, we were required to do data coding, which consisted of deciding whether participants’ written responses to the priming task fulfilled our criteria for inclusion. Many participants had to be excluded from data analysis because their responses were not relevant to the prompt.

For our data analysis, we ran regression analyses to statistically test the significance of the interaction between priming condition and effortlessly perfect self-presentation predicting change in state self-compassion after the puzzle task. We found a significant two-way interaction; the results are presented in the figure below:

As shown in the graph, there is a statistically significant interaction between priming condition and effortlessly perfect self-presentation predicting state self-compassion. Specifically, participants who were low in effortlessly perfect self-presentation showed no significant differences in state self-compassion, regardless of priming condition.  However, among participants who were high in effortlessly perfect self-presentation, those who were primed to focus on the importance of self-confidence showed significantly lower state self-compassion compared to those participants who were primed to focus on self-compassion or food (neutral).

These results have a few implications. For one, this empirically shows that when you remind a person who strives to appear effortlessly perfect that it is important to be confident in themselves to succeed, the end result is that they beat themselves up and blame themselves for not being confident enough when success doesn’t come easily.

Ultimately, this shows that placing too much emphasis on self-confidence can come at a cost to  self-compassion. While popular belief proposes that self-confidence is related to success, leadership, and more competence, our research shows that it does not prepare you well for coping with setbacks. This is particularly relevant in college students, in which they feel pressured to exert confidence for success and are otherwise seen as inferior if they do not exhibit this self-confidence. College students are likely to face failure, rejection, and other very challenging situations in their careers, so it is important that we emphasize more self-compassion than self-confidence to better prepare them to cope.

Personality Lab Research Assistants:

Cindy Campoverde

Jackson Guyton

Stella Nicolaou

Snailed it!

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Follow @snails_and_friends on Instagram for your daily dose of snails!


The Adventurous Souls of the Snail Lab:

Kelsey DiPenta, the “Parafilm & Plate Pouring Prodigy”

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Kelsey is the youngest member of the lab and arguably the cutest and most genuine soul found on campus. Being a Biology major, she can almost always be found in the science center, either pouring plates or taking a power nap on the couches. Her spontaneity is 100% contagious. She doubles as a generous chauffeur who will ALWAYS drive you anywhere, whether to Rita’s down the street or an hour away. Despite her allergy to cats and dogs, Kelsey has aspirations of owning several cats of her own. Whether in lab or around campus, Kelsey always will brighten your day.

Sarahrose Jonik, the “Life of the Lab”

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Sarahrose Jonik (a.k.a. Sayro, Troublemaker #1, or The Life of the Lab) ensures that the snail lab stays on its toes. When she’s not maneuvering snails like an absolute champ or rocking boot pants in the field, she entertains the lab by belting out the Krusty Krab pizza song. No one will ever really know how she manages to keep her white kicks so crisp and clean, or how she can keep her energy up while being a dedicated biology student and softball star. Her star power on the field is matched only by her star power during epic drum solos in Rock Band.

 Courtney Ward, the Ray of Sunshine 

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Courtney is the lab’s resident BMB major, and is the girl to go to if you ever need any life advice. Courtney brightens up the snail lab, both with her colorful leggings and sunshiny attitude. Her cooking skills are absolutely impeccable, establishing the best gourmet meals a college student could prepare. Whether it be in the game Cooking Mama or in the Appleford kitchen, she is always creating something delicious. One look at her chickpea cookie dough or her chicken salad will leave your mouth-watering. Courtney also has a very active lifestyle, which is reflected in her job at the Den and her love of yoga and zumba.

 Dr. Peter Fong, our Fearless Leader 

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As a pioneer in aquatic toxicology and dog enthusiast, Dr. Fong has been an absolute privilege to work with. He is extremely devoted and passionate about his work and all things invertebrate. You can almost always catch him with his best friend, Messi, a beautiful golden retriever. He frequents the Covered Bridge as his prime fishing location and does anything he can to avoid mowing the lawn. It has been a wonderful summer in Snail Lab and we will never forget our Fearless Leader!

Check out his some of his recent work here.


A Day in the Life for us Snail Folk:

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SPOILER ALERT: These are mussels. They were all dead.

Every day, the bright-eyed individuals of McCreary 212 fell into a routine revolving around snails. We set up hundreds of finger bowls filled with water, collected the snails, waited for them to get comfy in their new home, treated the snails, waited an hour for the drugs to kick in, collected the data for each individual snail, and repeated this process.

We were not deterred by the absence of living mussels in the Magothy river which put a hold on one experiment, OR the extremely high stream levels which prevented crayfish collection. Instead we turned to what we knew best–MORE snails.

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Who took these pictures you ask? No one! #selfiemode

Snail Assay

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We named every snail to make them feel more at home #nobias

The main focus of this toxicology lab is on the induced effects that pharmaceuticals & other industrial chemicals commonly found in the environment have on specific behaviors of aquatic invertebrates. We were particularly focused on the marine and freshwater snails, Ilyanassa obsoleta and Leptoxis carinata respectively.

The tricyclic antidepressants, imipramine, chlomipramine and amitriptyline, were tested on the snails at varying concentrations to determine if they have a significant impact on the righting behavior of these creatures. The righting reflex is the snail’s ability to re-orient itself after being knocked on its back by natural forces, or by pesky student researchers with a blunt pair of forceps.

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Crayfish Assay

During the last week in lab, the snail experts began crayfish experimentation. It was a unanimous agreement that snails are preferred over the violent tendencies of the crayfish. Their righting behavior when exposed to methoxychlor, a pesticide commonly found in the environment, was observed. All creatures were safely returned to their homes in the wild.


Important Life Lessons Learned in Snail Lab:

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Sayro & Kelsey showing proper dish stacking technique #21isthelimit

  • How to siphon gasoline (handy)
  • How to short-sheet a bed (useful prank)
  • How to create a galaxy in coffee with cream (fun when bored)
  • And most importantly… How to properly stack dishes! –>

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The 8 Week Journey Described Through Song:

Life Is A Highway – The adventures we embarked on in Snail Lab are those that will last a lifetime

Jeopardy Theme Song – No explanation needed, we work with snails.

Toxic, Britney Spears – … well, we work in a toxicology lab #drugs

Sweet Escape – Despite the fact that some snails can take 45 minutes to right themselves, they have an amazing talent for escaping their bowls in record timing.

Country Road, Take Me Home – Its been real. Snail Lab, OUT! ❤

Birds of a Feather Fun

This summer we have been working on research with Professor Neller. We have been utilizing machine learning to create an efficient solver of his game Birds of a Feather. Birds of a Feather is a solitaire game consisting of a four by four grid of standard playing cards. The goal is to consolidate the grid of cards into one single stack. To do this, you can move cards that are in the same row or column if they are also the same or adjacent rank or same suit. These rules result in many solvable states of the puzzle. However, in some cases, the puzzle can have unsolvable states, which result from a card or multiple cards that cannot be consolidated with another card. A typical day in our lab consists of us working at our computers in Glatfelter Hall. We’re usually working with Java, but in order to do some probabilistic calculations, we use R.

A basic brute force search algorithm blindly searches. In terms of Birds of a Feather, a brute force search algorithm searches if the puzzle is solvable or not without direction. Our goal, this summer, has been to speed up the search algorithm by giving it direction. We have been giving the searcher “strategies” or heuristics to achieve this efficiency. Imagine if you were playing any game without a strategy in mind. Every move you made in the game would be made without considering the next. Success would rely solely on random chance. The brute force search is just that. The heuristics, as you would imagine, improve the efficiency of our search algorithm by giving it a strategy for search.

Our heuristics attempt to lead the searcher to what is most likely a solvable state of a puzzle. The heuristic we have had the most success with this summer is what we call “total flockability.” In short, a card’s flockability is determined as the amount of cards it can be consolidated with on the board without considering the row and column restrictions. Total flockability is defined as the sum of the flockability of each card on the board. This heuristic says that board states with higher flockability are more likely to be solvable, so when we search, the searcher prefers the board state with the highest flockability. There are many other heuristics that can be used, this is just one example.

Another method we have used is to prune our search by determining if it will be fruitless to search something prior to actually searching it. One example of this is checking for “odd birds”. An odd bird is a situation where a card cannot be consolidated with any other card, or, in other words, a card that has a flockability of 0. If there is a card on the board that cannot be consolidated with another card, then there is no possible way to consolidate into a single stack; therefore, search will be fruitless. This saves a lot of wasted time since a blind search will go into a path with no solution while our search will avoid this fruitless path.

We have not finished our work yet, but we are currently developing a search that considers multiple heuristics through the use of statistics. Through statistical analysis, we can determine which heuristics are the most predictive of solvability. If each heuristic is given a weighting from 0 to 1, then as a sum, they can be used as a heuristic. By making our searcher be able to consider more heuristics at once, it can more quickly solve a puzzle.

 

The Searcher

This part of the description is basic and does not require a computer science background for understanding. The searcher operates by taking the original board state, the cards dealt out in a 4 by 4, and then creating the state of every possible move from that state, or, in other words, creating a board for every single card that you can move on your first move. First it checks if any of those moves are already unsolvable. If it is solvable, then it calculates a heuristic for each one of these states. Then whichever board, by the heuristic, is the most promising, we expand. This means we find all of the boards that result from making all the possible moves from that board. This process repeats until we do or do not find a solvable state. If we did, then the search was over and the board is solvable. If we did not, it searched every possible state and concludes that it is unsolvable.

This part of the description will most likely only make sense if you have a background in computer science. The searcher is a selective depth-first search that utilizes a queue, a stack and a priority queue. First, a node is taken off the queue. If closed, a hash set, already contains this state, then we skip searching it as it would be redundant; otherwise, we add it’s string form to closed and continue the search. If this node is the goal, then we assign it to be the goal node and return true. Otherwise, we expand the node. Then we prune the search by only adding nodes that pass various tests. This avoids unnecessarily checking nodes that are guaranteed to not be the goal node since we already know they are not. Each child that is not pruned has its compareVal, a value used for sorting the priority queue, calculated and then is added to the priority queue. We continue this process until the queue is not empty.

 

Next we iterate through the priority queue, pushing each node onto the stack. The priority queue is organized so that the element that is first is the last element that, according to theheuristic, we want to search. Therefore, the last element, is the most promising node to be pushed onto the stack, so it will be the first node searched. If the stack is not empty, then we pop a node from the stack and offer it to the queue. If the stack is still not empty and the next node on the stack has an equivalent compareVal to the previous node, then we also add that to the queue. We continue this process until there is no longer a tie or the amounts of nodes added to the queue is equal to numTies. If the queue is empty after, then the search is over and we return false; otherwise, start the algorithm from the beginning.

But what are we doing other than playing the game? I wish we could just play the game all day in our lab, but, we are doing even more interesting and challenging things than that. What we are focusing on are the ways to implement how we could solve the puzzle better. We work on designing and exploring many features or behaviors within the game that would help us better understand whether or not a particular puzzle is solvable/unsolvable and what makes it so. Designing these features can be challenging, and sometimes the best you could do is take a guess and hope that it workss. So far, we have worked on implementing around 10 features and have tried to look into how such features would correlate to solvability; how much impact would they have on making a puzzle solvable or unsolvable, measured in terms of probability. The measure of such impact is a heavy computational task, and it is basically a simulation of thousands of possible moves that we might make in the puzzle and analysis on how well we could solve the puzzle if we follow a certain feature/features or a combination of two or more features. We have accumulated more than a G.B of data so far from those simulations and it is just getting bigger and bigger. We are nurturing the data that we get just like our little baby, and for the time being what we can do is just hope that our baby will love us back as it grows older.

 

A day in our computer lab

 

This summer we’ve all had a great time learning more about the field of artificial intelligence through our research. It has definitely been a positive learning experience, and we hope to use these skills that we’ve learned both throughout the rest of our time here at Gettysburg and beyond.

 

 

Exploring Galaxy Cluster Dynamics in Phase Space

This summer, I experienced my first real taste of what scientific research is all about. Having done nothing of the sort prior to this summer, it took a while to get the wheels rolling. I was thrown into an unknown environment working with unknown tools to explore an area of science I knew nothing about. But that is exactly what research is for.

In Dr. Johnson’s lab this summer, I was tasked with exploring the dynamics of a simulated galaxy merger in an effort to understand the dynamics of large-scale structures in our universe. The simulation in question was performed in the late 2000’s by Dr. Zuhone, an Astrophysicist working for the Harvard-Smithsonian Center for Astrophysics in Massachusetts[1]. His simulations were aimed at capturing the effect that a galaxy merger would have on dark matter, which is collisionless, meaning that interactions with other particles have very little to no effect on the system as a whole. The reason that we can model galaxies in a similar way is because both dark matter and galaxies are collisionless and therefore their dynamics should be the same in the event of a merger. The data I worked with was only a small chunk of the enormous and numerous simulations performed by Dr. Zuhone. I was given the xyz-positional and velocity data of one-hundred thousand “galaxies”. My goal was to track these galaxies throughout the merger simulation and plot them in what is known as phase space. Phase space plotting is a method used to plot higher dimensional data in lower dimensions. For instance, when trying to understand the dynamics of three-dimensional space, a phase space plot can show it more plainly in two-dimensions.

My goal in research this summer was to begin to understand some of the dynamics of fourth-dimensional space using this phase space plotting method. The entirety of my work this summer has been on Python. I have been writing a program that gathers, groups, normalizes, and plots the simulation data. This process did give me an incredible opportunity to enter the research world and get a taste of what full time research would be like, at least from a computational standpoint.

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Figure 1. Final working code in Python

The most important part of this research are the graphs and figures I’m able to produce. Phase plots are not as straightforward as normal plots would seem. This plotting style is particularly useful in the plotting and analysis of light curves. The process of creating the plot is somewhat confusing and unnatural. To start, it’s important to understand what the data I dealt with looked like. Of the hundred-thousand “galaxies” previously mentioned, about fifty-one percent came from one cluster while the remaining forty-nine came from the other. My goal was to see if “galaxies” from either cluster exhibited any dynamical differences. The data I received for the merger simulation stretched over seventy-one timesteps, so I had to track the “galaxies” throughout the merger. My program was designed to take an equal amount of randomly chosen “galaxies” from each cluster and gather their position and velocity data over time.

Even though seventy-one time steps is quite a lot, one issue that came up was that they were not all sequential. Some time steps data had been corrupted and therefore lost. I needed to interpolate twelve missing time steps, which was done using linear interpolation. Once all the data was compiled, interpolated, and subsequently normalized, I grouped my data by variable. Then I grouped the values into successive groups of three. These groups of three values then acted as the x, y, and z-coordinates for my phase diagram. This section from a paper by Nada Jevtic illustrates it very clearly.

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I used this method of plotting with my simulation data to create plots like this. Position measurements have been normalized and are in units of cm. Velocity measurements have also been normalized and are units of cm/s.
X-Position: (two separate sets of 10 “galaxies”)

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Red lines: Cluster 1

Blue lines: Cluster 2
X-Velocity: (same sets of 10 “galaxies”)

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I am now at the analysis stage of my research and plan to have an in-depth analysis of all of the graphs over the coming weeks prior to our return to campus in August. Dr. Johnson has given me and the rest of the students in the lab a good bit of independence so that we develop troubleshooting and problem-solving skills on our own, instead of relying on others as a crutch. Even though the eight weeks are just about over, I’m excited to continue my research at home as well as through the upcoming school year.

But now I must talk about the only reason I chose to do research this summer. The mystical ancient art of hacky-sacking, foot-bagging, etc. There are few schools throughout not only the United States but the world that study the art. Dr. Johnson’s hack circle appears from the outsider’s perspective to be nothing more than people in a circle kicking a bag full of assorted beads. But once you enter the circle, your entire world changes for the better. You learn patience, teamwork, how to succeed with style and smack talk, and most importantly how to fail while simultaneously looking like you’ve forgotten how to use your legs.

Hacking offer’s a reprieve from the constricting world of Python(bonus pts for the pun). Hacking is a time to reflect on yourself and what you’ve done, what you still have to do and is great to refocus yourself because you just lost half an hour kicking a sack around. For me hacking has been a stress-free environment that I can use to clear my head and get revitalized for the rest of the day. As an unexpected but welcome bonus, I have also learned basic teleportation and levitation from my time studying at the Johnson School of Hacking. I have learned the proper form of arms above the shoulders and to always look for “fours” and “elevens”. Hacking is both an incredibly individual activity as well as a group activity. It has taught me that to succeed you can’t rely on one person, even if they’re as good as Dr. Kerney, and that focusing on working as a team is the best way to solve any and every problem. Working off of each other’s strengths and weaknesses to form a cohesive and functioning machine is what being a team and being a researcher is all about. I can’t, and most definitely do not, know everything there is to know about research, my field, or physics in general. But I know that to succeed it’s going to take a lot of work from me but also, a lot of faith in others.

~Hayden Hall

Really important link : https://www.youtube.com/watch?v=czTksCF6X8Y

[1] https://arxiv.org/abs/1004.3820