71 research outputs found
Structural studies of cytidine repressor and catabolite activator protein
No full textThe Escherichia Coli Catabolite Activator Protein (CAP) activates DNA transcription at more than a hundred promoters. Cytidine Repressor (CytR), in conjunction with two CAP dimers, acts as a repressor of DNA transcription at the deoP2 promoter. In the first part of this work, we describe a method by which a (CAP)[subscript] 2-CytR-DNA complex can be prepared for structural studies. In the second part of this project, we describe the crystallization of what was initially
intended to be a (CAP)[subscript] 2-DNA complex in order to study the effects of two CAP dimers on transcription at an artificially constructed promoter containing tandem CAP binding sites. Upon structure determination of the crystal, we observed that while there was no DNA present, the protein had bound multiple Co[superscript]2+ and SO2−/4 ligands. We provide an analysis of the crystal structure and present a possible explanation for the absence of DNA in the structure.M.S.Includes bibliographical referencesby Ramya Rangesh Ra
Knot theory addendum
No full textAt Right Angles met up with author Ramya to discuss her article on Knot Theory. Over coffee at Starbucks, Ramya adeptly made sense of a tangled bunch of wool which I had carried with me to try and see if Knot Theory could help me untangle the web
Water mass classification using band ratios
No full textThe Hudson River plume has been the topic of consideration and observation in order to try and understand the physical, chemical and biological behavior of the plume which is a key component of the oceanography of the Mid-Atlantic Bight (MAB) region off the east coast of the United States. One approach towards understanding the chlorophyll production for the plume would be to make use of satellite data to measure the optical ocean color properties of these waters. In this direction classifying the water masses of the Hudson River plume according to these optical properties would be an interesting method of analyzing the satellite data for the purpose of understanding and identifying the physical and biological changes and the correlation between them in this region.
The first step is to design and implement a water mass classification algorithm in the LaTTE (Lagrangian Transport and Transformation Experiment) region of the MAB. It takes about 1-2 weeks for the nutrients from the freshwater from the Hudson Estuary to be dissipated and mixed with the open ocean. This classification algorithm is developed using ocean color data from the Sea viewing WIde Field of view Sensor (SeaWiFS). The algorithm is validated by overlaying ship salinity tracks on the classified water masses to show that salinity values change at the boundaries of the classified regions, due to the mixing and export of freshwater across the shelf.
We analyze global Sea Surface Temperature (SST) data collected over the years 1995-2005 for summer and winter in order to find coastal estuarine ecosystems that may display similar behavior as the Hudson River Estuary. Looking at the seasonal variation in this data, we observe that the regions of MAB and the East Asian coast are found to have strikingly similar seasonal behavior.
This leads into the third and the last step of the process which involves applying the water mass classification algorithm to ocean color data from eastern coastal Asia. It is observed that the algorithm well in the seas of Okhotsk, Japan and East China where it is able to identify plume water and non river water.M.S.Includes bibliographical references (p. 86-92)
Sentiment analysis of big data with intensity analysis by rule engine, 2015
No full textThe use of social media is an emerging way for the public to express their views on companies and other organizations. The success of these entities can depend on a positive presence on social media, leading to an increasing interest in understanding public opinion expressed there. This thesis presents a method for gathering and storing a large number of social media posts, analyzing the sentiments expressed, and further classifying the specific emotions conveyed. The social media platform Twitter was used as a source of millions of publicly viewable posts. The big data software tools Twitter4j, Apache Hadoop, and Apache Hive were used to gather and store these posts. These were then classified as communicating a positive, negative, or neutral sentiment through the technique of sentiment analysis, performed using the tool Lingpipe. To further identify the particular emotions expressed in the Tweet, a rule engine, specifically the DROOLS software, was used
Study of health franchises in resource limited settings
No full textThesis (S.M. in Technology and Policy)--Massachusetts Institute of Technology, Engineering Systems Division, Technology and Policy Program, 2009.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student submitted PDF version of thesis.Includes bibliographical references (p. 62-64).Billions of dollars are spent to develop drugs for infectious diseases in developing countries. How will these drugs along with clinical services be delivered to the patients who currently do not have access to them? Health franchises have been around since early 1990s, creating networks of shops and clinics that provide specialized care to low income individuals. This thesis attempts to understand the underlying mechanisms of successful health franchises. Two cases are taken into consideration, CFWshops in Kenya and Mi Farmacita Nacional (MFN) in Mexico. Both are pharmaceutical shops with small clinics attached to them. The two cases were examined through a framework derived from successful commercial franchises and franchise theory. The elements that were addressed include operational structure, marketing strategy, product and service offerings, monitoring of businesses, and financial structure. CFWshops and MFN had some stark differences in how they addressed each of these elements. Unlike typical commercial franchises, health franchises aim to provide social benefits to the population. This goal requires franchises to not only create a business strategy to be financially sustainable and take advantage of networks, but also show health improvements in the community. The success of a health franchise is dependent on the health impacts it provides because its mission is not to generate a profit for the stakeholders but rather the value added to the customer by providing access that was not there before.(cont.) The comparative case analysis suggests several key recommendations. Health innovations in resource limited settings should create networks with other public and private health groups to leverage existing knowledge and best practices. This reduces cost and time of learning and allows businesses to utilize existing channels to provide access for drugs and services to individuals who currently are not receiving them.by Ramya Sankar.S.M.in Technology and Polic
Aetiology, Management and Prognosis of Jaundice in Adult Patients With Acute Severe Intestinal Failure
No full textSelection of suitable biomass conservation process techniques: a versatile approach to normal wiggly interval-valued hesitant fuzzy set using multi-criteria decision making
No full textAbstract A country that relies on developing industrialization and GDP requires a lot of energy. Biomass is emerging as one of the possible renewable energy resources that may be used to generate energy. Through the proper channels, such as chemical, biochemical, and thermochemical processes, it can be turned into electricity. In the context of India, the potential sources of biomass can be broken down into agricultural waste, tanning waste, sewage, vegetable waste, food, meat waste, and liquor waste. Each form of biomass energy so extracted has advantages and downsides, so determining which one is best is crucial to reaping the most benefits. The selection of biomass conversion methods is especially significant since it requires a careful study of multiple factors, which can be aided by fuzzy multi-criteria decision-making (MCDM) models. This paper proposes the normal wiggly interval-valued hesitant fuzzy-based decision-making trial and evaluation laboratory model (DEMATEL) and the Preference Ranking Organization METHod for Enrichment of Evaluations II (PROMETHEE) for assessing the problem of determining a workable biomass production technique. The proposed framework is used to assess the production processes under consideration based on parameters such as fuel cost, technical cost, environmental safety, and C O 2 emission levels. Bioethanol has been developed as a viable industrial option due to its low carbon footprint and environmental viability. Furthermore, the superiority of the suggested model is demonstrated by comparing the results to other current methodologies. According to comparative study, the suggested framework might be developed to handle complex scenarios with many variables
Motivating, your way: Tailoring your fitness journey
No full textA significant cardiovascular health risk is insufficient physical activity. The World Health Organization recommends 150 minutes of strenuous physical activity every week. Inadequate physical activity increases the risk of chronic diseases and other health conditions like cholesterol and obesity. This thesis researches the role of data monitoring as a persuasion strategy in monitoring a user’s progress in their journey to becoming more physically active and how it can be leveraged to decrease the risk of cardiovascular diseases. Specifically, the focus of the thesis is to determine the effectiveness of expert-generated tailored messages to motivate a user in their physical activity behaviour. We designed the content of the messages by adapting an existing ontology for tailoring motivational messages in the context of physical activity. Messages were then generated by experts through a scenario-based feedback generation process, where the scenarios were tailored to a user’s mood, self-efficacy and progress. The design of these tailored messages was tested against generic messages to determine which type of message was more motivating to the user. An experiment was conducted by recruiting crowd workers who were asked to rate the motivational levels of the two message types with respect to a given scenario. The results of the experiment supported the initial hypothesis that messages tailored to mood, self-efficacy and progress are more motivating than generic messages. Additionally, we have shown a systematic and reproducible way to obtain motivating messages. We have also provided a dataset of motivational messages that can be used during various stages of a user’s physical activity intervention, along with a set of scenarios representing different levels of a user’s state (mood, self-efficacy and progress)
Incidence of perforated gastrojejunal anastomotic ulcers after laparoscopic gastric bypass for morbid obesity and role of laparoscopy in their management
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