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Item Identifying housekeeping gene promoters in deer tick, Ixodes scapularis(2019) Chana, Randeep; Cruz, Omar G.; Pham, Michael; Harrell, Robert; Gulia-Nuss, MonikaIxodes scapularis is a major vector of the bacterium, Borrelia burgdorferi, the main pathogen responsible for Lyme Disease. However, understanding of the acquisition and spread of tick-borne diseases has been hampered by the lack of transgenic tools. These tools include fluorescent markers under the control of housekeeping gene promoters as visual markers for successful genetic transformation. The development of constructs with I. scapularis-specific gene promoters will also be useful for expression of pathogen-targeting gene products. More specifically, once these promoters are developed and confirmed, we can utilize these promoters to express RNAi to knockdown genes of interest for vector capacity and pathogen acquisition. Additionally, promoters can be used to drive recombinant protein expression, including fluorescent gene expression. Developing fluorescent reporters will be useful as markers of successful genetic transformation. This will enable fast sorting of transgenic individuals by fluorescence while avoiding the need for regular DNA sequencing of individual progeny. During this project, I intend on identifying promoters of housekeeping genes and validating them via green fluorescent protein reporter assay in an Ixodes scapularis cell line.Item An Updated Chronology from Hunter Creek(2019) Caggegi, Andrea; Vegliò, Lorenzo; Csank, AdamDendrochronology is one of the most important environmental recording techniques for a variety of natural processes and a monitor for human-caused changes to the environment such as pollution and contamination. The ethymology of the word dendrochronology comes from Ancient Greek, dendro means tree and chronology means the study of time. In fact, this technique allows you to examine events through time that are recorded in the tree-ring structure or can be dated by tree rings. Because the tree becomes the instrument for environmental monitoring, it serves as a long-term bioindicator that extends for the lifetime of the tree. In this respect, dendrochronology can be applied to very old trees to provide long-term records of past temperature, rainfall, fire, insect outbreaks, landslides, hurricanes, and ice storms. Trees record any environmental factor that directly or indirectly limits a process that affects the growth of ring structures from one season to the next, making them a useful monitor for a variety of events. In the library at University of Nevada (Reno) there are several tree core samples collected in 1934 and 1935. This summer I revisited some of the sites of these collections and in particular some groups of trees located along Hunter Creek canyon, a desert area characterized by very steep slopes and very tolerant tree species such as Pinus ponderosa Douglas and Pinus jeffreyi Murray. This allowed me to update the chronologies of the tree core samples in the library and restore their historic streamflow with a focus on the driest and warmer periods.Item Chemical nociception in Wild-type and dYPEL3 Drosophila larva mutants(2019) Zito, Nicholas; Kim, Jung HwanDrosophila larval nociception is widely used for studying various basic circuit mechanisms. Traditionally, the behavioral assay for Drosophila nociception relied on either optogenetic or physical stimulation. The behavioral response upon chemical stimulation has not been widely used due to high levels of variability. We found that larva require co-stimulation with blue light to exhibit consistent nociceptive behavior upon a noxious chemical stimulation using allyl isothiocyanate (AITC). Introducing constant blue light illumination during AITC treatment greatly increased the consistency of behavioral output. dYPEL3 mutations have been identified in a number of neurological symptoms in human patients. We used our refined AITC-induced larval nociceptive behavior and found a reduction in nociceptive behavior in dYPEL3 mutants. Currently, larval nociceptive behavior is quantified by manual scoring. We are working to develop automatic quantitation of nocicieptive behavior using machine-learning techniques from software such as DeepLabCut (DLC). Going forward, we plan on using these machine-learning techniques such as DLC to automatically quantify nociceptive behavior to further study the effects of dYPEL3 mutations on nociceptive circuit development.Item Improving People Detecting Infrastructures for the Purpose of Modeling Human Behavior(2019) Bessho, Tomohide; Feil-Seifer, David J.; Palmer, AndrewIncorporating robots into our everyday lives requires robots to have the ability to act and behave as humans. One method of reciprocating human behavior into these robots is through intent recognition. Collecting interpersonal navigation data in a variety of environments will lead to more effective models of human behavior. We will fuse camera and laser sensor data to detect human poses while simultaneously locating their relative positions and movements. This information can apply to better understand intent recognition and autonomous navigation behavior generation.Item Hierarchical Task Learning Through Human Demonstration(2019) Boyd, Taylor; Zagainova, Maiya; Blankenburg, Janelle; Nicolescu, Monica N.; Feil-Seifer, DavidIn order for robots to carry out a task sequence, it must be translated in such a way that they can understand. One way this can be done is by using a task tree representation. Currently this method does not allow robots and humans to collaborate without interruption as hard coding of the task tree is required. One solution to this is to enable robots to construct task trees themselves. After observing a human demonstrate a repeated series of tasks, the robot would then use the different sequences to build and store a corresponding hierarchical task tree representation. The accuracy of the constructed task tree can be validated through the comparison of the robot's completion of the task and the human's original demonstration as well as the robot's ability to complete the task in more ways than one. Upon validation, this process will allow human-robot interactions to remain continuous and enable those without a computer science background to collaborate with robots as well.