Third Blog Post

At this point, my research is near complete. I have collected all of my data and am now in the analytical stage. One of the most central questions that my survey inquired about was the “environmental background” of the participant. The environmental background of a person is the extent to which they have engaged with the physical and conceptual principles of the environment and environmentalism. These experiences vary greatly, as conveyed in the survey responses. Some participants identified the location in which they grew up, such as rural areas or on farm land, as their background in environmentalism. Others indicated that they pursued Environmental Science or a related discipline for their college degree, and counted this as their background. 

So now, I am taking the data I have gathered and comparing the survey answers against each other. I am trying to find similarities and frequencies in the survey responses. This is the method that I used to reach the conclusion that I mentioned before. In addition to connecting simple themes, there is a lot of thought that must going in to figuring out what this all means. This not only requires pulling from my own experience, but also from the texts that I have read to prepare for this research. One tool that my mentor taught me was writing out a web of my data to discover connections and more in depth meanings of the survey answers. This helps to lay out all of the information in front of you so that you can then begin to process and analyze the data.

I found success in that my thesis questioned opened the doors for more conclusions to be drawn. For example, I am finding that it is not only direct experience that influences people to compost, but indirect experiences as well. For example, some participants indicated that they grew up composting their food scraps at home, or that they had volunteered at a garden or farm that composts. This is considered direct. Others indicated experiences that range from having recycled other types of waste in the past to experiences that involve broader interaction with the environment, environmental volunteerism, or environmental education. I am considering these indirect experiences.

Blog #3: Progress and Reflection

Recently my research lab has unfortunately experienced contamination of the machinery responsible for creating the NGM plates used in my project. The machinery was contaminated with E. coli, which is the bacteria used in C. elegans research so fortunately the source of contamination was discovered. While the equipment was being sterilized, my project consisted of increasing amounts of literature review. I wish to understand the nematode life cycle and metabolism as best as I can, as well as known interactions between the worm and M. tuberculosis. One paper, entitled “The nematode Caenorhabditis elegans displays a chemotaxis behavior to tuberculosis-specific ordorants” has given major insights into the way the nematode reacts to specific volatile organic compounds (VOCs) produced by M. tuberculosis. The researchers plated a sample of worms onto a plate containing a sample of a known VOC produced by the bacteria as well as a control substance where the effect on the nematode is known. The behavior of the nematodes were then tracked for an hour. The data consisted of reactions to different concentrations of four know VOCs as well as a calculated chemotaxis index value. A follow up experiment I plan on performing is observing the effect the VOCs have on nematodes lacking the gene responsible for olfaction.

Working with Dr. Marcello has been an amazing experience. Fortunately our schedules are very compatible so we are able to meet very frequently. Any questions that arise while I’m in lab are quickly answered and serve as a fantastic learning experience that will assist me in my future career. Dr. Marcello has also ordered C. elegans mutants, one of which lack the daf2 gene and the other will lack a key gene in the olfactory mechanism. These mutants are key to my project and I cannot wait to begin experiments.

I am fortunate this semester to have had the opportunity to submit a research abstract to the Eastern Colleges Science Conference. Attending this conference will serve as an experience opportunity that will aid me in my career as well as a catalyst for my research.

Blog #3 Combining Docking, Molecular Dynamics Simulation, and Free Energy Calculation to Improve the Accuracy of Virtual Screening of Drug Candidates Against HIV Integrase

Our group is honored to present a poster at the 38th Annual Meeting of the Society of Fellows on March 9, 2019.

The poster we presented includes an introduction section, graphs to show potential of mean force method (PMF) for computing binding free energy, steps for double decoupling method (DDM) for computing binging free energy, and a conclusion section. Our results suggest that quinoline binds 5′ end with a somewhat higher affinity.

It was an amazing experience to discuss our research with other faculty and student researchers.

Blog 3: Effects of Support Provision

 

 

We are now in the final stretch of our research, and our focus has shifted from the preliminary stages of planning to the real grind of preparation. We have now been approved by the International Review Board and have formulated questions which both effectively gather the necessary information while retaining the ethical boundaries and respect for our participants. Professor Gosnell and I have decided to focus our topic of provisional support via social media to a few more specific topics. These include memory and retention of support provision as well as an interactive component which will allow participants to further delve into their own, personal experience with support provision and how they may be effected by it. In a further step Dr. Gosnell and I have considered the concept of an interactive component in which students will have the opportunity to participate in a theoretical posting which they can provide support for in real time. This will allow participants to evaluate how they might react when prompted to provide support over an online forum. We have narrowed our studies to focus most specifically on Facebook, which is most frequently used to address social or emotional topics, and additionally included a few prompts about the use of Instagram, which has quickly become one of the most used platforms for digital exchange.

The biggest challenge that Dr. Gosnell and I have been faced with is maintaining focus on the important aspects of our research rather than becoming more vague, but widely inclusive. This was a concept I struggled with as there was so much to explore on this topic since so little research has been carried out before. Past research has richly explored the concept of support, but only in the ways in which it effected those receiving support and the concept of capitalization. This method of study will allow us to further understand the way in which we as people are affected by the support we provide. I am very much looking forward to further analyzing the effects of support provision hands-on. We plan to begin running our participant sessions within the next week, which will allow us time to make any minor tweaks and changes necessary to collect the most applicable data possible.

Blog Post 3

It is widely known that honey is antimicrobial. However, there are many different kinds of honey and the antimicrobial properties differ amongst them. Dr. Rizzo and I have been experimenting to determine the best honey to focus our research on. We sent out samples containing both raw honey and Manuka honey to LIU Post, where the antimicrobial factors of the samples are tested using the zone diameter of inhibition technique. When tested alone, the raw honey gave a value of 1.1 for the diameter, which is the minimum diameter needed to be considered antimicrobial. This showed us that raw honey itself was not as effective as Manuka honey, so we are now starting to focus on using different brands of Manuka Honey. In order to understand why there was such a difference in the effects of the pure honey samples, I conducted a literature search. The reason for the difference in antimicrobial effectiveness between these two honeys comes from their composition. Raw honey is a peroxide honey, while Manuka honey is non-peroxide. For peroxide honey, peroxide and polyphenols contribute most to the antimicrobial properties of the honey. For honey that is non-peroxide, the main antimicrobial component is methylglyoxal, with polyphenols also being important. Although it is present in all honeys, methylglyoxal is much more concentrated in Manuka honey, which has stronger antimicrobial properties than peroxides.

In addition to determining the most effective honey, we have also been experimenting to find the most effective essential oil to mix the honey with. It has been determined that cinnamon cassia is definitely the most effective among the oils. In the first set of samples I prepared and had tested, I mixed a 3:1:1 ratio of honey, oil, and aloe vera gel, respectively. This gave values of 3.5 and 2.2 when tested against the growth of S. aureus and E. Coli. I consulted Dr. Rizzo with these results and we decided to test the effect when we increased the concentration of the cinnamon cassia oil, and thus the aloe vera gel. In the next set of samples, I prepared a sample of a 3:2:2 ratio of manuka honey to cinnamon cassia oil to aloe, respectively. This gave values of 4 for S. aureus and 3.6 for E. Coli, both of which show a very high antimicrobial factor.

We are still working on testing the longevity of these surfaces. I made a large amount of one sample and sent a potion to LIU Post. I have some stored in the research lab, which we will be sending out in increments each month. This data will give us information on the integrity and antimicrobial efficacy of the material over time. We are also beginning to test the change in antimicrobial effects when different oils are mixed into one sample. In addition, the use of plant powders will also be implemented into the samples.

Pollution and Cultures: Data Collection (US)

Preview

The research has been conducting a survey focusing on the environmental views of students from two cultures: US and China. Previously, the researcher has collected over 130 responses from students in Chongqing, China. Accordingly, this semester the research will concentrate on distributing surveys and collecting data from students in New York City, United States of America. The survey contains both quantitative and qualitative questions.

Sample

So far, the researcher has collected data from 50 students who are English native language speakers at Pace New York Campus. Their average age is 21 years old. 65% of them are female, while around 34% are male respondents. Additionally, 38% of the responses have been living in New York City one years and below, while around 52% have lived in the city for over 2 years. Accordingly, 35 out of 50 students are studying at Pace campus less than 2 years, while around 35% of them have been on campus for over 3 years. Among all, Art and Humanities discipline has occupied the most of the sample.

Data Analysis

In the survey, it asks which goal the city should prioritize in terms of development, 39 out of 50 respondents choose “environmental protection” over “economy” as its priority. When it comes to specific reasons, many address that economy and environment are intertwined, indicating that good environmental protection could be the foundation for economy growth. Some even go further claiming that without a good environment, economy would not matter so much. Furthermore, “survival” becomes a common addressing issue in their statement. The answers express the respondents’ uncertainty of whether people will continue to live on the planet if we do not prioritize environment. In addition to that, the respondents who choose economy over environment does not necessarily mean they do not care about the nature. For instance, one respondent expresses that he “[loves] the environment”, but “people will be less willing to protect the environment if they don’t have enough money.” The beliefs like “without economy we can’t help environment” are common shared among the respondents.

Half of the respondents choose to prioritize “local” environmental protection, while the rest choose “global” first. For those who choose “local”, they believe that starting from small parts can eventually lead to the changes in larger structures. In other words, they tend to believe that starting from local issues is one of the strategies leading to the formation of global environmental principle. On the other hand, the rest of 50% respondents claim that local initiatives are not enough; because everyone shares the same planet, individualized principle is not sufficient in succeeding environmental efforts.

Conclusion

The US students have already shared some similarities with the students in China. They both address concerns on “survival” on the planet; health and wellbeing are the most frequent theme appearing in their statements. For instance, they both identify air pollution as the most pressing issue. Simultaneously, the researcher finds quotes about “breathing in the clean air” from both groups, despite of their differences in native languages.

One of the results that the researcher finds it interesting is that US students tend to talk more negatively about their country taking responsibility in global environmental efforts.

 (Do you think your country has done well in taking responsibility of global environmental protection? — US students response)

As the graph shows, 20 out of 50 respondents think US is done poorly, while 12 respondents believe it “terrible”; only 18 respondents believe US is above average.

(Do you think your country has done well in taking responsibility of global environmental protection? — Chinese students response)

As for Chinese students, the majority of them think China’s global environmental efforts are “on average”, and there are 39 out of 132 respondents think China is doing “good”. It might be due to the factors which we have not yet measured, such as differences in shared public discourse in environment from both cultures.

So far, the researcher has identified some similarities and differences between the students from US and China, but it needs to further analysis and more data collection. Thus, the researcher will continue on collecting responses on a larger scale.

Blog 3: Leading Factors & Further Reports

The project analyzes how the selected explanatory factors affect tuition and fees by using simple regression models. The main variables of interest include: tuition and fees in year t, GDP in year t from CPI, enrolled students in year t, household debt in year t, interest rate in year t, earnings difference in year t, where t is the time index, in years. The regression derived and used in the empirical investigation is given by: Y(t) = -466.7 + 1.86X1(t) – 3.01X3(t) + 5.26X4(t) + 0.52X6(t) + 0.90X7(t) + e(t). In line with the literature, the regression model shows five significant factors that drive tuition: general inflation; federal government, state, and local government support per enrolled student; household debt as a percentage of GDP; financial sector debt as a percentage of GDP; difference between the mean earnings. Thus, we can divide the right-hand-side into the following groups: general inflation, effects from taxpayer support, effects from leverage, and the earnings difference. The time-series data used all starts at 100. The data represents the most significant factors affecting college tuition and the causes of students accept federal financial aid. Each factor is considered due to how each has the ability to change over time, further explaining how college tuition and federal financial aid change over time.

The model demonstrates that the strongest effect is from the leverage and the second strongest from the taxpayer support. The parameters for the household debt relative to the GDP and the financial sector debt relative to the GDP indicate that leverage in the economy drives tuition. Since the leverage depends on credit markets, tuition and fees depend also on the markets. If households and financial institutions are able to get large loans at low prices, their leverage rises as we have seen during the last 25 years. This credit rise has driven multiple things and tuition is just one example of that. During 1987 – 2017 household debt relative to the GDP rose by 107% and financial sector debt relative to the GDP by 552%. By this model, these changes increased tuition and fees by 848%. On the other hand, when the support per enrolled student increases then tuition and fees fall, i.e., colleges change tuition and fees partly in order to compensate fluctuations in taxpayer support. Between 1987 and 2017 the support per enrolled student rose 246% and, by this model this decreased tuition and fees by 740%. Thus, the support from taxpayers eliminated most of the effects from the leverage.

College inflation is also highly sensitive with respect to the general inflation. During 1987-2017 CPI rose by 218% and, according to the model, this pushed tuition and fees up by 406%. Finally, the earnings difference raises the value of the education and this way also tuition and fees. Between 1987 and 2017 the earnings difference increased by 324% and raised tuition and fees by 292%.

This project used a regression model to explore what affects the rise in college tuition over the period of 1987-2017. In addition, the project assessed the Bennett Hypothesis, which states that the rise in college tuition is due in-part by the rise in federal financial aid offered. The results indicate that the factors of tuition and fees, GDP from CPI, enrolled students, household debt, interest rate, earnings difference in year t, all affect the rise in college tuition. While the Bennett Hypothesis was also considered, it showed to not have as great of an impact on the price of tuition as the other factors did. The correlation between the factors tested and the rise in college tuition gave an R-squared value of 99.7%.

Looking forward, there are two trends: US households and financial institutions are deleveraging, their debt levels with respect to GDP fall and taxpayer support rises and, therefore, the support per enrolled student increases. Both of these trends should decrease college inflation.

Future research should explore how different geographical regions affect college tuition in the area and how much people are willing accept in financial aid moving from the geographical location that they reside to the geographical location that they are attending college. This would allow researchers to develop a better understanding of how tuition prices change based on the permanent residency demographic of students and how financial aid changes from one geographical location to the next.

Blog Post #3: Solved for some coefficients

The past couple of weeks have been interesting. At this point in time, I understand the Sage programming language completely (for the domain of my research), which has allowed for faster progress. I tested the roots that Professor Fastenberg had done earlier, such as the sections when r=1, 2, 3, 7, 10, and 12. All of her roots worked, but since my Sage code differed from Professor Fastenberg’s previous code in Maple, I also discovered other roots. Additionally, by using the solve(…) function in Sage, it allowed me to solve each of the coefficients for the values necessary. The main issue that we encountered at this moment in time is that the roots that Sage puts out in the solve function are approximate. Our goal is to get the exact value, such as in terms of radicals. I tried searching the Sage information database for increased functionality regarding exact roots, but the engine has limits in this regard. Therefore, I need to devise another method to solve for exact roots, probably through a more complex algorithm.

In the upcoming weeks, I will be developing that new algorithm and working on solving for the coefficients of the higher powers of the functions. Another issue that I encountered was that at higher powers, the solve function becomes computationally inefficient. This means that the solver times out, due to the fact that it deals with an insanely large amount of roots, leading to an exponential growth in time.

Blog #3

Austin Goodman

Blog Post #3

March 11th, 2019

The project Animating Nature: The Art of the Moving Image from Conservation to Climate Change has been moving along. We are currently in the process of compiling research and corresponding summaries while curating my report. We have maintained a close communication as Professor Williamson aids in organization and creating timelines. However, as the semester goes on and work builds, research halts at times. We have teamed up to collaborate on work of Professor Williamson’s own that ties directly into this research allowing for me to gain access and experience. A challenge is staying on task. While our research has little precedent, I find myself traveling down roads that venture too far from our point. I am looking forward to finally culminating this research into something that I am proud of and will be an effective resource. I have not yet met with Rivkin, however, intend to do so in April.

Blog 3: The Impact of Agriculture on Water Quality in Southern Trinidad (Continued)

My field work in Southern Trinidad has come to an end. From January 15th-23rd I have conducted my last set of macroinvertebrate sampling for my research. After getting all my sediment samples, I added ethanol to kill off any decomposing bacteria and to preserve any macroinvertebrates. Because these organisms are small and there is a lot of sediment left in the collected samples (even after rinsing them through a net), I had to carefully look through each sample and individually extract all the macroinvertebrates. I spent an average of two hours sifting and observing each of the 6 samples. Between the collection and processing of these samples, macroinvertebrate samples are much more challenging than collecting and processing water samples! I really enjoyed doing it, though. These organisms are incredibly interesting and diverse. As of now, I am currently working on my final research paper. With my maroinvertebrate results, river water analyses, and fecal coliform tests, I have enough information to start drawing conclusions with the help of my mentor, Dr. Monica Palta. I am set out to answer my big question: What is the impact of agriculture on water quality in Southern Trinidad?

 

This research project has so far has had a major impact on me. The research project itself is trying to figure out how agriculture can affect water quality and stream organisms. Seeing that human activities can affect nature and ecology, is not new to me, but new to many of the local people of Southern Trinidad that live on and use these rivers. As an environmental science major and a person of Trinidadian heritage, completing this research project is just the first step for me in my career goal of developing meaningful solutions to environmental problems that affect undeserved communities of people. The fact that people I know and care about are the ones impacted by the particular environmental problems affecting rivers in Southern Trinidad makes my project of particular importance to me. The feeling of success and fulfillment I receive after completing every experiment is what motivates me to want to wake up every day and continue to do this for a living.