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Spatiotemporal Machine Learning for Wildfire Spread Behavior Prediction
No full textWildfire is one of the most destructive ecological processes of our natural world. It is an integral part of our ecosystem, and the life cycle of many species depend on it for propagation. In order to manage fire, we must understand its behavior and properly model the condition of the surrounding ecosystem. Predicting wildfire behavior is essential to effectively managing the wildland environment. Wildland management includes suppressing fires where necessary, promoting them where advantageous, all while protecting people, property, and resources. Fire behavior is influenced by the interplay of many factors. Topography, fuel type and load, wind, humidity, and temperature all effect the direction and rate of growth of wildland fires. Wildfires can create their own weather, amplifying the effects prior fire behavior have on future fire behavior. Spatiotemporal machine learning techniques may be utilized to model complex real-world fire behavior dynamics and produce accurate predictions. Anticipating wildfire behavior is the first step to effectively managing its effects. Leveraging the ability of deep learning models to infer future fire behavior from past fire behavior is a novel approach to wildfire behavior prediction. Spatiotemporal modeling has proven effective at accurately predicting wildfire spread behavior days and weeks in advance. Current performance is limited by the availability of high-resolution, high frequency data. As remote-sensing data improves, and the availability of computational resources grows, temporal-spatial modeling of wildfire spread behavior will contribute more to effective wildland management practices
Voice Stress Analysis - "Some Evidence?"
No full textThis article provides background information on Voice Stress Analyzers (VSAs), including discussion of the theories which form the basis for their operation. The manufacturers’ claims regarding their ability to detect deception are evaluated in light of reported scientific studies testing the accuracy of the machines. A beneficial side effect to the use of such devices, regardless of their actual ability to detect deception, is reviewed. This article then reviews the position as to the use and admissibility of VSAs taken by courts in reported decisions from across the nation in a variety of legal proceedings
Enhancing Human-Robot Collaboration Through a Multi-Module Interaction Framework With Sensor Fusion: Object Recognition, Verbal Communication, User(s) of Interest Detection, Gesture and Gaze Recognition
Get PDFWith the increasing presence of robots in our daily lives, it is crucial to design interaction interfaces that are natural, easy to use, and meaningful for a wide range of robotic tasks. This is important not only to enhance the user experience but also to increase task reliability by providing supplementary, task-specific contextual information if needed. Motivated by these goals, we propose a multi-modal framework consisting of multiple independent modules. These modules take advantage of multiple sensors (e.g. image, sound, depth) and can be used separately or in combination for effective human-robot collaborative interaction. We identified and implemented four key components of an effective human-robot collaborative setting, which include: (1) determining Object(s) of Interest location and pose, (2) extracting intricate information from verbal instructions, (3) resolving User(s) of Interest (UOI), and (4) providing gesture recognition and gaze estimation to facilitate natural and intuitive interactions. The system uses a feature-detector-descriptor approach for object recognition and a homography-based technique for planar pose estimation and a deep multi-task learning model to extract intricate task parameters from verbal communication. The User(s) of Interest (UOI) is detected by estimating facing state and active speakers. The framework also includes gesture detection and gaze estimation modules, which are combined with verbal instruction components to form structured commands for robotic entities. Experiments were conducted to assess the performance of these interaction interfaces, and the results demonstrated the effectiveness of the proposed approach
The Characterization and Analysis of Lanthanide-Ligand Complexes in Aqueous Solution
No full textThe rare earth elements (REEs) primarily consist of the lanthanides; they occur naturally in ores around the world and have a wide range of important technological applications. REEs are key components of electronics from semiconductors to permanent magnets, and they are involved in multiple green energy implementations like windmills and electric vehicles. REEs present an array of fluorescent and luminescent properties, and they are also used in medical imaging. Lanthanides are difficult to separate from each other due to their similar chemical and physical properties, which leads to separation processes with high environmental impacts. Solvent extraction using ligands is a primary method for isolating lanthanides through chelation, by forming lanthanide-ligand complexes soluble in organic solvents. After solvent extraction, REEs are stripped from the ligands with acid, which changes the solution pH and the protonation state of the complex. Most ligands used in solvent extraction have poor selectivity for particular lanthanides. Lanthanide-ligand complexes are present in many applications of REEs, e.g., magnetic resonance imaging contrast agents, chelation therapy, and lanthanide separations. The binding between a lanthanide and ligand, which can be quantified by a stability constant, depends on the structure of the lanthanide-ligand complex in solution and the structure of the ligand. Resolving the structures of lanthanide-ligand complexes is challenging due to the lability of the ions and to the large coordination spheres that can accommodate many binding partners; however, structures can be resolved using computation to model the geometries and chemical make-up in solution. From resolved structures, thermodynamic and electrostatic properties can be predicted. The first chapter of this work is an introduction that provides background information and highlights the relevance of the work, while the second chapter explains the computational approach implemented in later chapters. The third chapter of this work describes how classical molecular dynamics simulations and ab initio molecular dynamics simulations are used to determine the structure of Eu 3+ complexed with ethylenediaminetetraacetic acid (EDTA) in all protonation states in aqueous solution. Simulations show agreement with experimental structures and validate the predicted structures and the computational approach. The fourth chapter of this work includes studies on the structure, binding, and electron density of the Nd 3+ and Dy 3+ complexes with a macrocyclic chelator (macropa) and a glycine-functionalized macropa. There is quantitative agreement between relative free energies of binding from experiment and relative binding energies from computation. Electrostatic analyses based on the electronic structure of the optimized geometries explain the binding behavior and trends in stability constants. The fifth chapter of this work details studies on the binding of the Gd 3+ ion to another cyclic ligand (DOTA) and its variations. With the Gd-DOTA complex as reference, computational relative binding energies were compared to experimental relative free energies of binding, and there is good agreement between computation and experiment with all the DOTA-based ligands. Electrostatic analyses were also done, and the electron density of the Gd 3+ ion in the Gd-ligand complexes shows a direct relationship to the electrostatic energies of the coordination bonds in the Gd-ligand complex, where a greater electron density in the ion results in more stable complexes
Numu (Northern Paiute) Place Names: Retention and Reclamation of Place Name Knowledge in Kooyooe Pa'a Panunadu (Pyramid Lake, Nevada)
No full textThis research examines how place name knowledge has been passed down generationally within the ancestral homelands of the Kooyooe Tukadu (Cui-ui Eaters) from Kooyooe Pa'a Panundu (Pyramid Lake, Nevada) and how this knowledge contributes to the retention and reclamation of Numu place names. As a member of the Pyramid Lake Paiute Tribe, I have an inherent connection to my homelands and this research is designed to uplift Numu (Northern Paiute) place names and narratives. The foundation of this research is framed within Indigenous methodologies and as a critique of settler-colonial imposed place naming processes, with its direct role in the erasure of Numu communities. As a speaker of the Kooyooe Tukadu dialect, I document current and past language revitalization efforts and emphasize the fluidity and adaptability of Numu yadooa (Northern Paiute language). From a decolonial lens, I examine the history of mapping and how settler land theft led to the violent application of settler place names within Kooyooe Pa'a Panunadu. Despite settler domination, Numu communities continue to communicate place names and the knowledge attached to them, both orally and in written form. This continues a cultural tradition that extends at least as far back as the Numu map created by Captain Dave Numana in 1885. In efforts to document place name retention, knowledge keepers from the Pyramid Lake Paiute Tribe share their knowledge and stories of Numu place names, Numu connection to the land, and their hopes for retaining Numu identity for future generations. In conclusion, Numu place name knowledge systems are actively being reclaimed on the individual and community level and can further expand by returning names to the land, increasing Numu-centered mapping approaches, and speaking Numu yadooa in our ancestral homelands
Association of Reported Dietary Fiber and Hyperkalemia in the Chronic Kidney Disease (CKD) Population
No full textAmong the chronic kidney disease (CKD) population, hyperkalemia is a life-threatening complication, affecting 9.6% of individuals when blood potassium levels exceed 5 mEq/L. People with CKD have historically been advised to manage hyperkalemia risk with a low-potassium diet. Managing dietary potassium intake in the CKD population is challenging due to the lack of evidence-based guidelines, which often leads to restrictions on potassium-rich foods such as fruits and vegetables that are also rich in dietary fiber. It has been proposed that dietary fiber may help to reduce hyperkalemia by decreasing potassium absorption or enhancing its excretion through stool, or both. The association of dietary fiber with plasma potassium levels and hyperkalemia risk has not been tested yet. Therefore, this cross-sectional observational study aims to investigate primarily the association between reported dietary fiber intake and hyperkalemia in the hemodialysis (HD) population; and secondarily the association of hyperkalemia with other sociodemographic (e.g., age, sex) and clinical data variables (e.g., DM, HTN), as well as assess the frequency of hyperkalemia for them. For the study design, 14 participants met all the inclusion (adults under HD) and exclusion criteria (any gastrointestinal disorders, clinically unstable, and non-English speaking) and had dietary, sociodemographic, and clinical data available. Dietary data was collected using a 3-day food record, sociodemographic data by a questionnaire, and other clinical data from their medical records. Analyzing the nutritional data by Nutrition Data System for Research (NDSR) and using statistical software to assess the relationship, no direct association was observed between reported dietary fiber intake and hyperkalemia. Other variables were also not associated with this complication of CKD. By analyzing the blood potassium levels in the last 12 months, the frequency of hyperkalemia in the HD population was approximately once every five instances. This study offers preliminary insights into dietary fiber intake and hyperkalemia risk in the HD population, showing that while low fiber intake and higher frequency of hyperkalemia are common, no association was found between them. Highlight the potential to improve dietary fiber intake and lower hyperkalemia risk, which underscores the need for a more comprehensive observational study to investigate this hypothesis further
Development of a Novel Humidification-Dehumidification Solar Distillation System Prototype
No full textThis thesis explores a novel solar distillation unit designed to be sufficiently simple and cost-effective that an individual with modest skill and means could reproduce it and use it to distill water. The design centers around solar heated air which heats and evaporates water in a moisturizer filter. Subsequently the nearly saturated air is cooled in an air-to-water heat exchanger, condensing vapor for collection. Two different heat rejection systems were considered and tested, appropriate for different seasons. A system was built and tested at the Desert Research Institute in Reno Nevada, which features abundant sunshine throughout the year. A mathematical model initially predicted a reasonable estimated distilled water collection. However, the system as built and tested contained a design flaw which was identified only after testing was completed, namely that air velocity through the heat exchanger-condenser blew suspended atomized water droplets past the collection area and returned them to the solar collector, bypassing useful collection and diminishing the apparent system efficiency. A second mathematical model correctly estimated both the expected distilled water collection and also the realized product. The approach can deliver more distilled product than a sloping glass passive solar still, but more research is required for a proper demonstration
Sensorimotor synchronization with rhythms is influenced by stimulus properties and individual differences
No full textSensorimotor synchronization (SMS) refers to the temporal coordination of an external stimulus with motor movement. Dancing to music, playing sports, or verbally communicating fundamentally depends on synchronizing one’s actions with rhythmic sensory stimuli. The current project aims to better establish the stimulus- and participant-specific factors that influence SMS. We first examined how the modality and rhythmic deviation of a stimulus, along with the synchronizer’s level of musicality, impacted SMS. Utilizing a finger-tapping task and three sensory modalities (visual, auditory, and tactile), we manipulated rhythmic deviation by varying the temporal position, intensity, and availability of cues across four deviation levels. Additionally, we administered the Goldsmiths Musical Sophistication Index (Gold-MSI) questionnaire to determine our participants' musical familiarity and aptitude. While we found that SMS to external rhythmic stimuli was significantly more precise for auditory and tactile than for visual sequences, participants could still synchronize well with visual flashes. Further, we found SMS consistency significantly decreased in all modalities with increased rhythmic deviation, suggesting that rhythmic deviation directly relates to SMS difficulty. A significant correlation between Gold-MSI scores and SMS consistency in the most rhythmically deviant level suggests that rhythmic synchronization performance is also affected by the musical general sophistication of the synchronizer. Combined, our results suggested that SMS is influenced by stimulus- and participant-specific differences irrespective of stimulus modality. Subsequently, we examined how participants’ imagery and perceptual abilities affect visual SMS performance using a synchronization-continuation finger-tapping task with a visual stimulus. We quantified participants’ SMS consistency in both synchronization (with visual cues) and continuation (without visual cues) phases. Participants also completed the Gold-MSI and imagery questionnaires and performed a rhythm perception task assessing their ability to detect temporal perturbations in the visual rhythm. We found significant effects of trial phase and auditory imagery on SMS consistency, suggesting that participants performed SMS more consistently while the guiding visual stimulus was present and that the higher one’s auditory imagery ability, the better their SMS while continuing with unguided rhythm. In addition, one’s rhythm perception accuracy significantly correlated with SMS consistency during the synchronization phase, and we found no correlation between rhythm perception and auditory imagery control. In our final study we further examined the contribution of imagery to SMS performance by testing proficient imagers and including auditory or visual distractors during the continuation phase. While visual distractors had minimal effect, SMS consistency was significantly worse when auditory distractors were presented. Electroencephalography (EEG) analysis revealed stronger neural entrainment at the beat-related frequency with visual or auditory distractors than without distractors. Neural entrainment to the beat frequency positively correlated with SMS consistency in the presence of visual distractors, suggesting the potential utilization of auditory imagery and its role in supporting SMS performance. During continuation with auditory distractors, the neural entrainment showed an occipital electrode distribution suggesting the involvement of visual imagery. Unique to SMS continuation with auditory distractors, neural and sub-vocal (measured with electromyography) entrainment were found at the three-beat pattern frequency. In this most difficult condition, proficient imagers employed both beat- and pattern-related imagery strategies. However, this combination was not enough to restore SMS consistency to the same level observed with visual or no distractors. Our results suggest that proficient imagers effectively utilized beat-related imagery in one modality when imagery in another modality was limited. Taken together, findings from this dissertation project highlight important factors that influence SMS, providing insight into the development of SMS- and imagery-related training methods and interventions
How Do Gig Workers Experience Their Work Environment? A Person-Gig Fit Perspective
No full textGig workers operate within environments that structurally differ from those of traditional organizational workers. They perceive their fit with their work environment differently than traditional organizational workers do. Existing measures assessing gig workers' perceptions of person-environment fit are broad, and some items may not be applicable to gig workers due to the unique environmental contexts of gig work. To better capture how gig workers fit with their work environment, I develop a valid and reliable measure specifically assessing gig workers' perceived fit with their gig work and platform. First, I specify a conceptual framework for a measure encompassing five fit perceptions commonly experienced by gig workers�"perceived interest fit, perceived goal fit, perceived value fit, perceived demand-ability fit, and perceived need-supply fit. Items are then generated and refined through testing by several subject matter experts (i.e., Ph.D. students) and a group of naïve participants in Study 1, providing evidence for the content validity of the measure of person-gig fit (P-G fit). The investigation of the factor structure of the items surviving Study 1 is conducted through exploratory factor analysis (EFA) in Study 2. Confirmatory factor analysis (CFA) and tests of convergent validity, discriminant validity, and concurrent validity of P-G fit are carried out in Study 3