Now showing items 1-20 of 477

    • Stock Price Prediction Using Sentiment Analysis and LSTM

      Carter, Caymen (2022-05)
      This work presents multiple Long Short-Term Memory neural networks used in con- junction with sentiment analysis to predict stock prices over time. Multiple datasets and input features are used on a LSTM model to decipher which features produce the best output predictions and if there is correlation to the sentiment of posts and the rising of a stock. This project uses embedding based sentiment analysis on a dataset collected from Kaggle which includes over one million posts made on the subreddit r/wallstreetbets. This subreddit recently came under fire by the media with the shorting of Gamestop in the stock market. It was theorized that this subreddit was working as a collective to drive up the price of multiple stock, therefore hurting large corporations such as hedge funds that had large short positions on multiple stocks.
    • Application of Resistive Random Access Memory (RRAM) For Non-Von Neumann Computing

      Rafiq, Sarah (2022-05)
      The movement of data between physically separated memory and processing units in conventional computing systems (the so-called von Neumann architecture) incurs significant costs in energy and latency. This is known as the von Neumann bottleneck. With the advent of the Internet of Things (IoT) and edge computing, computing systems are also becoming significantly power limited. In this work, hafnium oxide resistive random access memory (ReRAM) integrated with 65nm CMOS technology on a 300 mm wafer platform was assessed to carry out two novel non-von Neumann computing applications that processes data within memory and avoid excessive data movement. These computing applications are based on regulating the flow of sneak path currents in memory arrays to perform computation, called flow-based computing, and detecting degree of association (correlation) between binary processes in an unsupervised manner using the ReRAM non-volatile accumulative behavior, termed as temporal correlation detection. Electrical characterization of hafnium oxide ReRAM arrays was conducted for multi-level resistance states for flow-based computing, which was then investigated for two functions, approximate edge detection and XOR Boolean logic, through both experiments and simulation. The effect of device non-idealities was also evaluated. A trade-off between the flow-based output resistance ratio and the variability of flow-based outputs was found for different patterned binary resistance Roff/Ron ratios. For the second non-von Neumann application, the feasibility of ReRAM as a non-volatile candidate device was investigated with an empirical ReRAM model through simulation. Experimental ReRAM analog incremental switching data, from both SET and RESET regimes, was also evaluated on the modified temporal correlation detection algorithm, where the RESET regime resulted in better performance. The ReRAM based implementation yielded 36,000-53,000 vi times lower energy consumption than similar implementation with phase change memory for 25 binary processes, and a speed-up of computation time by 1,600-2,100 times than that of a CPU-based implementation using 1xPOWER8 CPU. 1xPOWER8 CPU is a CPU available on the IBM* Power* System S822LC system, the POWER8 system series, where the CPU was run for 1 thread. In summary, hafnium oxide ReRAM based on 65nm CMOS technology has been evaluated for two non-von Neumann computing applications, and the effect of device non-idealities has also been assessed. These ReRAM in-memory computing applications show the promising potential of ReRAM in overcoming the von-Neumann bottleneck.
    • A dual to the death: using novel host-directed antivirals to promote death of HCMV-infected myeloid cells through apoptosis and necroptosis

      Chan, Gary; Cheung, Jennifer (2022-06)
      Human cytomegalovirus (HCMV) is a ubiquitous member of the betaherpesvirus family, with seroprevalence rates ranging from 40-100% worldwide. Although primary infection is asymptomatic in most immunocompetent patients, HCMV is a significant cause of morbidity and mortality in the immunosuppressed and immunonaїve, including transplant recipients, patients with AIDS, and developing fetuses in utero. The diverse clinical presentations of HCMV are attributable to the pervasive systemic dissemination and extensive cellular tropism of the virus. Peripheral blood monocytes are believed to be the key cells responsible for HCMV dissemination from the initial site of infection to distant organ systems. Monocytes are normally short-lived, surviving for only 48 h in circulation before undergoing apoptosis. Previous work from our lab has shown that HCMV circumvents the short lifespan of monocytes by inducing a noncanonical activation of Akt to upregulate the expression of antiapoptotic proteins, thereby prolonging survival of infected monocytes. HCMV promotes survival in the absence of viral replication and lytic gene expression, rendering current direct-acting antivirals ineffective against quiescently infected monocytes. There are currently no antivirals that target quiescent or latent HCMV infection. We hypothesize that targeting host proteins that are essential for HCMV's induction of monocyte survival mechanisms will reduce viability of infected monocytes, ultimately reducing systemic viral dissemination. The studies in this thesis investigate novel host-directed antivirals targeted at two different cellular factors and their efficacy against quiescent HCMV infection in monocytes. The first host protein under scrutiny as an antiviral target is Sirtuin 2 (Sirt2), an NAD+-dependent deacetylase. Treatment with novel Sirt2 inhibitors promoted death of HCMV-infected monocytes as a cellular antiviral defense response through two concurrent regulated death pathways: apoptosis and necroptosis. HCMV has developed mechanisms to impede both death pathways, but inhibition of Sirt2 relieves the viral obstructions on both pathways by disrupting HCMV's unique phosphorylation on Akt. The second host protein targeted as a potential antiviral strategy is Mcl-1, an antiapoptotic member of the Bcl-2 family of proteins. HCMV-infected monocytes are dependent on Akt-dependent upregulation of Mcl-1 for survival during early infection. Treatment with Mcl-1 inhibitors blocked interaction between Mcl-1 and proapoptotic protein Bak, reducing viability of infected monocytes. Subsequent testing of Mcl-1 inhibitors in an ex vivo skin organ culture system resulted in a decrease in HCMV-infected cells that crawled out of the skin tissue, suggesting that Mcl-1 inhibition may reduce viral dissemination. Our studies lay down the groundwork for the investigation of novel host-directed antivirals, an approach that successfully targets quiescent HCMV infection in peripheral blood monocytes for the first time. Expanding the study of host-directed antivirals may bring the field one step closer to the possibility of a comprehensive antiviral regimen that is effective against all stages of viral infection.
    • Rational design of a genetically encoded fluorescent protein color switch using a modular, entropy-driven mechanism

      Loh, Stewart; John, Anna (2022-06)
      Engineered protein conformational switches have applications in cellular and in vitro biosensing, molecular diagnostics and artificial signaling systems in synthetic biology. They broadly consist of an input module and an output module that communicate via a conformational change. The overarching goal of this thesis is to tackle two major challenges in protein switch design - signal transduction, by coupling a target recognition domain to an output domain to produce a robust change in signal in addition to modularity, which allows the facile creation of sensors binding novel targets. Here, we attempted to test a rational design strategy that exploits two key protein engineering principles (1) loop entropy, by which long insertions into a loop of a host protein destabilizes the host due to an entropic cost associated with loop closure unless the inserted sequence adopts a folded structure; and (2) alternate frame folding (AFF), which allows a protein - green fluorescent protein variants(GFP), in this case - to switch between two mutually exclusive folds. Toward this goal, we first studied the effect of loop entropy at two different insertion sites in a GFP variant (chapter 2) using a well-characterized ribose binding protein as the input domain. We provide stability measurements using circular dichroism and fluorescence data to support our hypothesis of the application of the loop entropy principle in a GFP beta barrel scaffold. To provide a proof-of-concept of the combination of loop entropy and the AFF mechanism in a genetically encodable GFP scaffold, we chose an unstable, circularly permuted FK506-binding protein (cpFKBP) as the input recognition domain and inserted it in one of the two mutually exclusive folds of the GFP-AFF fusion protein (chapter 3). Upon addition of ligand, binding induced folding of the cpFKBP domain effects a conformational change in which the tenth beta strand of GFP exchanges, replacing Thr203 (green state) with Tyr203 (yellow state). We confirmed this mechanism in vitro by a ratiometric change in fluorescence output and observed that the process is slow and irreversible. We elucidate the biophysical principles underlying this mechanism by using denaturant and temperature to modulate the relative populations of the two folds in vitro. We also observed a faster and higher intensiometric response in mammalian cells which may be attributed to an alternate mechanism. We then harnessed this intensiometric response in a single fold of the fluorescent protein combined with a previously engineered monobody scaffold capable of binding a variety of targets (chapter 4). Altogether this work may have the potential to create a novel class of fluorescent protein biosensors comparable to existing single fluorescent protein-based biosensors currently available.
    • Targeting SHIP paralogs to promote microglial effector function in the CNS

      Thomas, Stephen J.; Pedicone, Chiara (2022-06)
      The two SH2-containing inositol 5'-phosphatases , SHIP1 (INPP5D) and SHIP2 (INPPL1), play an essential role in modulation of cellular signaling by transforming the PI3K product PI(3,4,5)P3 into PI(3,4)P2. PI3K signaling triggers activation of downstream signaling cascades that drive survival, effector functions, differentiation, and proliferation. SHIP1 can also mask the cytoplasmic tails of key receptors or their adaptor proteins such as DAP12, thus preventing PI3K recruitment to Trem2, a critical receptor for microglial function. Several GWAS studies correlated single nucleotide polymorphisms (SNPs) in INPP5D with Alzheimer's Disease (AD). However, it remains unclear whether these SNPs are deleterious or protective in AD and how they alter SHIP1 protein expression. SHIP2 overexpression has also been correlated with AD, suggesting that both SHIP1 and SHIP2 might be therapeutic targets. To study how SHIP1 and SHIP2 modulate microglial functions we used small molecule inhibitors and agonists of these enzymes. In our initial study we found that both SHIP paralogs are expressed in murine microglia and that Pan- SHIP1/2 inhibition increases lysosomal size and enhances microglial phagocytosis of Ab1-42 fibrils and dead neurons using both flow cytometry and confocal microscopy. Our lead Pan-SHIP1/2 inhibitor, K161, showed Blood Brain Barrier penetration as detected in the cerebral cortex of treated mice with mass spectrometry. K161 treatment of WT mice showed no difference in microglial frequency or lysosomal content in vivo; however, we observed a significant 2 increase in Ab1-42 and dead neurons phagocytosis ex vivo in microglia in K161- treated mice versus controls. Subsequently, we discovered a novel and highly potent SHIP1 selective agonist (K306) via artificial intelligence guided computational screening. We found that K306 can reduce the release of inflammatory cytokines in macrophages and microglial cells stimulated with LPS or Ab1-42. Interestingly, K306 didn't alter microglial phagocytic uptake of cargo, but did promote degradation of phagocytosed lipid-laden cargo - defining a novel role of SHIP1 in degradation of lipid cargo in microglia. These results highlight the importance of SHIP1 and SHIP2 in microglial biology and their modulation as therapeutics in different stages of neurodegenerative disease where microglia play a major role, such as AD.
    • Complexity of mental geometry for 3D pose perception

      Guo, Crystal (2022-06-13)
      Biological visual systems rely on pose estimation of three-dimensional (3D) objects to understand and navigate the surrounding environment, but the neural computations and mechanisms for inferring 3D poses from 2D retinal images are only partially understood, especially for conditions where stereo information is insufficient. We previously presented evidence that humans use the geometrical back-transform from retinal images to infer the poses of 3D objects lying centered on the ground. This model explained the almost veridical estimation of poses in real scenes and the illusory rotation of poses in obliquely viewed pictures, including the pointing at you phenomenon. Here we test this model for 3D objects in more varied configurations and find that it needs to be augmented. Five observers estimated poses of inclined, floating, or off-center 3D sticks in each of 16 different poses displayed on a monitor viewed straight or obliquely. Pose estimates in scenes and pictures showed remarkable accuracy and agreement between observers, but with a systematic fronto-parallel bias for oblique poses. When one end of an object is on the ground while the other is inclined up, the projected retinal orientation changes substantially as a function of inclination, so the back-transform derived from the object’s projection to the retina is not unique unless the angle of inclination is known. We show that observers’ pose estimates can be explained by the back-transform from retinal orientation only if it is derived for close to the correct inclination. The same back-transform explanation applies to obliquely viewed pictures. There is less change in retinal orientations when objects are floated or placed off-center but pose estimates can be explained by the same model, making it more likely that observers use internalized perspective geometry to make 3D pose inferences while actively incorporating inferences about other aspects of object placement.
    • Feasibility and applicability of a clinical assessment of both the ON and OFF pathways in patients with glaucoma and controls.

      Moore-Stoll, Veronica (2022-05-03)
      "Purpose: To assess the feasibility and clinical utility of a head-mounted, On/Off perimetry test and to investigate the effect of early to moderate glaucoma on reaction time and accuracy to ON and OFF perimetric stimuli. Methods: We tested one eye each of 9 patients with early to moderate primary open angle glaucoma (mean = 71.88 years, std = 5.17), 9 visually-normal control patients of a similar age (mean = 63.88 years, std = 5.17 ) , and 9 visually-normal optometry students (ages 22-25 years). We used a head mounted display equipped with an eye tracker (HTC VIVE embedded Tobii). Custom software (Unity, version 2017) was used to create the stimuli and a library provided by Tobii Pro was used to measure eye movements at 120 Hz. Stimulus size changed as a function of eccentricity using a power law relationship: stimulus size= minimum scale*(eccentricity/5)^α. Eye movements were restricted to a central circle with a 2.5 degree radius. Stimulus contrast was initially set to 100%. A single test comprised of 579 trials, including 51 catch trials, presented at 90 different positions in the visual field. Each test location was repeated 3 times for both light and dark stimuli, with 6 repeats in each of two blind spot positions. Results: Our results demonstrate asymmetry between the two achromatic visual transduction pathways. These results support previous findings that dark targets elicit a faster and more accurate response than light targets, when presented on binary background noise. Our results extend previous work by demonstrating that the two pathways remain asymmetrical in eccentricities up to 30 degree from fixation. We also show that the relationship between the percentage of correct responses for ON pathway and OFF pathway stimuli follows a power function, wherein glaucoma and controls overlap (R2=0.842) . This overlap decreases when we quantify only the subthreshold (unseen) increment targets in a linear relationship (R2=0.7074). All controls had less than 12% of subthreshold increment targets whereas the percentage of subthreshold targets was higher for 75% of the glaucoma subjects, even in early stages of the disease. CONCLUSION We have demonstrated that ON/OFF perimetry is feasible in a VR environment and confirmed an asymmetry between the ON and OFF pathways in patients with glaucoma and control patients in both central and peripheral visual fields. We measured on-pathway deficits in patients with limited loss of visual sensitivity which may improve detection of early disease. Future work will focus on optimizing stimulus parameters to improve the sensitivity and specificity of this test."
    • Effects Of Correcting Fixation Disparity On Digital Eye Strain

      Saksena, Sanjana (2022-04-20)
      Digital Eye Strain (DES) is a widespread and highly prevalent condition whose incidence appears to be rising during the present pandemic. It comprises a range of visual and ocular symptoms which occur after viewing a digital screen for an extended period of time. Previous work from our laboratory has shown the magnitude of fixation disparity to be the only clinical parameter that is significantly correlated with DES symptoms. Therefore, this study sought to determine whether correcting the underlying fixation disparity will significantly reduce DES symptoms. Thirty young, visually-normal students were required to read randomly generated words from a digital tablet device for 20 minutes. Three different trials were performed, with the subject wearing either: (i) the prism that corrected their fixation disparity, (ii) the same magnitude of prism as for condition (i) but with the opposite base direction or (iii) a near addition lens that corrected the fixation disparity. Immediately after the reading task, subjects rated their ocular and visual symptoms on a questionnaire. There was no significant difference between the mean symptom scores for the three conditions. However, this may be due, in part, to the small number of subjects encountered with large values of fixation disparity. Future studies should further examine the range of oculomotor responses associated with DES in order to provide appropriate treatment options.
    • Generating Facial Character: A Systematic Method Accumulating Expressive Histories

      Jofre, Ana (MIT Press, 2022-04)
      The author presents a method to simulate facial character development by accumulating an expressive history onto a face. The model analytically combines facial features from Paul Ekman’s seven universal facial expressions using a simple Markov chain algorithm. The output is a series of 3D digital faces created in Blender with Python. The results show that systematically imprinting features from emotional expressions onto a neutral face transforms it into one with distinct character. This method could be applied to creative works that depend on character creation, ranging from figurative sculpture to game design, and allows the creator to incorporate chance into the creative process. The author demonstrates the method’s application to sculpture with ceramic casts of generated faces.
    • Library renovation: From setbacks to success.

      Wells, Elaine (Research Caucus of the Medical Library Association, 2021-02-25)
      The journey started at a 2016 meeting of the college’s Learning Resources Committee, which I chair as Library Director, A student representative casually commented that our Library looked “dated”. Not that we actually WERE dated, we have electronic resources, 24/7 remote access, printers, scanners, wireless, and a state-of-the-art Library Management System. However, through the eyes of our young student, the Library looked “like something from the 1970s.” Anyone who has lived through that decade’s will know that was not meant as a compliment. The student’s criticism prompted the Dean of Academic Affairs, who sat in on the meeting, to ask when the Library had had its last “facelift.” That was an easy one to answer - as far as I knew…never. And I’ve been here over 20 years. Just like that, a renovation was born. How hard could this be? I would query the students on what a suitable update might look like, get a budget, buy some new furniture, and go back to the business of being a librarian rather than an interior designer. Spoiler alert: not so fast.
    • Crowdsourcing Image Extraction and Annotation: Software Development and Case Study

      Jofre, Ana; Berardi, Vincent; Brennan, Kathleen P.J.; Cornejo, Aisha; Bennett, Carl; Harlan, John (Digital Humanities Quarterly, 2020-03)
      We describe the development of web-based software that facilitates large-scale, crowdsourced image extraction and annotation within image-heavy corpora that are of interest to the digital humanities. An application of this software is then detailed and evaluated through a case study where it was deployed within Amazon Mechanical Turk to extract and annotate faces from the archives of Time magazine. Annotation labels included categories such as age, gender, and race that were subsequently used to train machine learning models. The systemization of our crowdsourced data collection and worker quality verification procedures are detailed within this case study. We outline a data verification methodology that used validation images and required only two annotations per image to produce high-fidelity data that has comparable results to methods using five annotations per image. Finally, we provide instructions for customizing our software to meet the needs for other studies, with the goal of offering this resource to researchers undertaking the analysis of objects within other image-heavy archives.
    • Faces extracted from Time Magazine 1923-2014

      Jofre, Ana; Berardi, Vincent; Bennett, Carl; Reale, Michael; Cole, Josh (Journal of Cultural Analytics, 2020-03-16)
      We present metadata of labeled faces extracted from a Time magazine archive that contains 3,389 issues ranging from 1923 to 2012. The data we are publishing consists of three subsets: Dataset 1) the gender labels and image characteristics for each of the 327,322 faces that were automatically-extracted from the entire Time archive, Dataset 2) a subset of 8,789 faces from a sample of 100 issues that were labeled by Amazon Mechanical Turk (AMT) workers according to ten dimensions (including gender) and used as training data to produce Dataset 1, and Dataset 3) the raw data collected from the AMT workers before being processed to produce Dataset 2.
    • What’s in a Face? Gender Representation of Faces in Time, 1940s-1990s

      Jofre, Ana; Cole, Josh; Berardi, Vincent; Bennett, Carl; Reale, Michael (Journal of Cultural Analytics, 2020-03-16)
      We extracted 327,322 faces from an archive of Time magazine containing 3,389 issues dating from 1923 to 2014, classified the gender of each extracted face, and discovered that the proportion of female faces contained within this archive varied in interesting ways over time. The proportion of female faces first peaked in the mid-to-late 1940s. This was followed by a dip lasting from the mid-1950s to the early 1960s. The 1970s saw another peak followed by a dip over the course of the 1980s. Finally, we see a slow and steady rise in the proportion of female faces from the early 1990s onwards. In this paper, we seek to make sense of these variations through an interdisciplinary framework drawing on psychology, visual studies (in particular, photography theory), and history. Through a close reading of our Time archive from the 1940s through the 1990s, we conclude that the visual representation of women in Time magazine correlates with attitudes toward women in both the historical context of the era and the textual content of the magazine.
    • Color Transparency: Geometry, Motion, Color, Scission, and Induction

      Huang, Zhehao (2024-03-30)
      Objects that pass light through are considered transparent, and we generally expect that the light coming out will match the perceived color of the object. However, when the object is placed on a colored surface, the light coming back to our eyes becomes a composite of surface, illumination, and transparency properties. Despite that, we can often perceive separate overlaid and overlaying layers differing in colors. How neurons separate the information to extract the transparent layer remains unknown, but physical characteristics of transparent filters generate geometrical and color features in retinal images which could provide cues for separating layers. We estimated the relative importance of such cues in a perceptual scale for transparency, using stimuli in which X or T-junctions, different relative motions, and color consistency, cooperated or competed in forced-preference psychophysics experiments. Maximum-likelihood Thurstone scaling revealed some new results: moving X-junctions increased transparency compared to static X-junctions, but moving T-junctions decreased transparency compared to static T-junctions by creating the percept of an opaque patch. However, if the motion of a filter uncovered a dynamically changing but stationary pattern, sharing common fate with the surround but forming T-junctions, the probability of seeing transparency was almost as high as for moving X-junctions, despite the stimulus being physically improbable. In addition, geometric cues overrode color inconsistency to a great degree. Finally, a linear model of transparency perception as a function of relative motions between filter, overlay, and surround layers, contour continuation, and color consistency, quantified a hierarchy of latent influences on when the filter is seen as a separate transparent layer. Previous measurements of color scission have limitations. The color adjustment to match the target color is relatively accurate but time consuming and suffers from long time adaptation bias. Force-choice judgment is quick and free from adaptation effect, but the selection of choices can be the source of bias. We examine the observers’ ability to estimate filter color with transparency with our improved method: we ask observers to make a judgement of the transparency region being red or green (or, blue/yellow). By doing this we found the neutral point of the filter that the observers think colorless. The result showed that, in color consistent conditions, though biased by the background or individual preference, the observers’ measured neutral filter settings were close to the colorless filter, showing relatively good color scission. In the color inconsistent conditions, the observers matched the overlaid region to a neutral color, as if the observers were attributing the average color of the overlaid region completely to the transparency. Veridicality of scission varied little in the color consistent conditions, despite the large variation in degree of perceived transparency. An exception to the rule that only one color is seen at every retinotopic location happens when a bounded colored transparency or spotlight is seen on a differently colored surface. Despite the spectrum of the light from each retinotopic location being an inextricable multiplication of illumination, transmission, and reflectance spectra, we seem to be able to scission the information into background and transparency/spotlight colors. Visual cues to separating overlay and overlaid layers have been enumerated, but neural mechanisms that extract veridical colors for overlays have not been identified. Here, we demonstrate that spatial induction contributes to color scission by shifting the color of the overlay toward the actual color of the filter. By alternating filter and illumination spectra, we present naturalistic simulations where isomeric disks appear to be covered by filters/spotlights of near veridical colors, depending solely on the surrounding illumination.
    • Face Recognition and Emotion Identification

      Andriamanalimanana, Bruno R.; Thesis Advisor; Spetka, Scott; Thesis Committee; Chiang, Chen-Fu; Thesis Committee; Lagwankar, Akshara Avadhut (2021-05)
      While face recognition has been around in one form or another since the 1960s, recent technological developments have led to a wide proliferation of this technology. This technology is no longer seen as something out of science fiction movies like Minority Report. With the release of the iPhone X, millions of people now literally have face recognition technology in the palms of their hands, protecting their data and personal information. While mobile phone access control might be the most recognizable way face recognition is being used, it is being employed for a wide range of use cases including preventing crime, protecting events and making air travel more convenient. This project focuses on various advanced Python libraries to improve the face recognition accuracy such as OpenCV, Sklearn, face_recognition. The project understands the data and model, train it for further usage. The real time videos are considered for evaluating the results. Further the project glances the emotion recognition algorithms using CV2, Seaborn. The areas of the human faces are highlighted according to different emotions. The large data sets (fer2013, Olivetti faces) are used for training and testing the data sets. PCA, leave one out cross validation, grid search CV, machine learning pipelines, CNN models are used to estimate and increase the accuracy. The project is executed in Anaconda environment Jupyter Notebook. As the data sets are huge Google Collaboratory is used for execution.
    • sxRNA Switches: Hypothesis Through Automated Design Via a Genetic Algorithm Approach

      Tenenbaum, Scott; Chair; Melendez, J.A.; Cady, Nathaniel; Fasullo, Michael; Begley, Thomas; Doyle, Francis J., II (2021-12)
      The following document is meant to represent an overview of my work on structurally interacting RNA (sxRNA), which has already resulted in three publications with another two in preparation. Where appropriate, some text and data from these publications have been reproduced here. Ribonucleic Acid (RNA) is one of the fundamental macromolecules present in living systems. It can be found in all cells as varying length polymer chains composed of four primary bases (adenine, cytosine, guanine, uracil) capable of numerous modifications. Though generally characterized as an information carrier, RNA is a versatile molecule that exhibits both intra and inter-strand base pairing to form complex structures. Similar to protein, the particular shape of an RNA structure in combination with some degree of sequence specificity, can dictate its function (RNA binding protein recognition sites, ribozyme activity, aptameric affinity, etc.). Structurally interacting RNA (sxRNA) is a molecular switch technology that exploits predictable intermolecular RNA base pairing to form an otherwise absent functional structure in one RNA strand when it interacts with a specific, targeted second strand. Originally proposed as a potential regulatory mechanism in natural systems, we used characteristics of predicted pairings in that context to engineer purely synthetic sxRNA switches that have been successfully tested. There are many non-coding RNAs associated with pathological conditions, the ability to use these as triggers for sxRNA opens the door to potential applications ranging from diagnostics to therapeutics. Furthermore, other prospective triggers (including those synthetically designed) may allow use of the technology as a molecular tool for a variety of purposes including as an alternative to antibiotic selection in cell line development. The typical trigger sequences targeted by sxRNA switches are at least 20 bases in length. Combinatorial options with regard to structure positioning and base composition produce an enormous number of potential sxRNA sequences for any given target. Exhaustively examining these for feasible candidates (i.e., analyzing predicted interactions with unintended targets) is computationally impossible with current systems. Evolutionary computing is a subfield of artificial intelligence (AI) that has been inspired by biology. Genetic algorithms are a type of evolutionary algorithm and apply operators (such as recombination and mutation) to find candidate solutions to an optimization problem. The presented dissertation will describe the original sxRNA research as well as the development and testing of a genetic algorithm that automates the production of new sxRNA switch candidates. This algorithm takes into consideration factors that were previously impossible to account for in manual designs.
    • Multicyclic Loss for Multidomain Image-to-Image Translation

      Reale, Michael, Chair; Confer, Amos; Andriamanalimanana, Bruno; Schneider, Ethan H.
      GANs developed to Translate an Image’s style between different domains often only care about the initial translation, and not the ability to further translate upon an image This can cause issues where, if one would want to generate upon an image and then further on, change that image even more that person may come into issues. This creates a ”gap” between the base images and the generated images, and in this paper a Multicyclic Loss is presented, where the Neural Network also trains on further translations to images that were already translated. iv