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Structural Studies Provide Insight on the Fate of 1,5-Dithiacanes: Two Electron Reversible Oxidation versus Irreversible Oxidation
No full textFile types are Excel, Word, and fchk. Total file size is 86 MB, and contains 17 files
Technoblade Never Dies
Get PDFAro AdventurerTechnoblade Never Dies, 2022Fandom: Technoblade, the Minecraft YouTuberTextN/ACollection of the Author
Rating: Teen and UpTags: Technoblade, main character death, reader insert, gender neutral reader, Technoblade x Reader, Fantasy AU?
Author\u27s Notes: This whole piece was written in one sitting. Although I later made a few edits for the sake of additional clarity or nuances of word choice, it is nearly in the same state it was in on the night I wrote it
Monitoring Hydrocarbons in Air Using Adaptive Multivariate Sensor Signal Processing and Analysis of Humidity Effects
No full textVolatile organic hydrocarbons such as BTEX (benzene, toluene, ethylbenzene, xylenes), commonly released into the ambient environment from sources such as gasoline or household products, are known to be hazardous to human health. As a result, real-time monitoring of such compounds in ambient environments is required for safety. Gas sensors with high sensitivity, sufficient selectivity, and fast response times are needed for effective monitoring of the environment. This dissertation addresses some challenges in environmental monitoring using gas sensors, especially with multi-analyte mixtures in the presence of humidity. This work uses sensor arrays with multivariable sensing parameters (sensitivity and response time constant) with three different polymer-plasticizer blend coatings, each partially selective to BTEX compounds. Using multivariable sensor parameters drastically increases the probability of detection and accuracy of quantification while decreasing the probability of misidentification. Adaptive multivariate sensor signal processing was used to extract recognition and concentrations from the rapid transient sensor response to multi-analyte mixtures. The approach combines principal component analysis (PCA) and Levenberg-Marquardt (LM) modified exponentially weighted-recursive least squares estimation (EW-RLSE) algorithm for analyte identification and quantification (down to 3 μg/L for all target analytes) from the mixture responses. A slightly higher detection limit was obtained for benzene due to its high vapor pressure. Using PCA, excellent cluster separation for single analytes was achieved, and with the LM modified EW-RLSE, correct identification of target analytes (including common interferents) was obtained from mixtures. Accurate concentration estimations also require a minimum data sampling rate. A sampling time of no more than 1 s resulted in concentration errors of approximately ±5% for BTEX analyte mixtures, with up to 6 compounds, using the proposed algorithm. In real-world applications, changes in humidity pose a challenge to the functionality of most sensor systems. This dissertation also investigates the effect of humidity on the coated shear-horizontal surface acoustic wave (SH-SAW) sensor on analyte detection. Addressing this challenge is key to efficient design of the proposed polymer-plasticizer blend coated gas sensor systems. For single analytes and multi-analyte mixtures, the LM modified EW-RLSE algorithm resulted in accurate concentration estimation in a relative humidity range up to 65%
The Mental Health Management of Individuals in Sex Work
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This dissertation examines the mental health implications and experiences of individuals engaged in sex work, employing a constructivist grounded theory approach to explore the nuanced realities of this marginalized population. Through in-depth interviews with sex workers, this study reveals the complex interplay of positive aspects (enjoyment and empowerment), and the negative (severe risks faced by individuals in this field, including verbal abuse, physical violence, and sexual assault). The findings underscore the critical need for a holistic and nuanced understanding of sex work, challenging prevalent stereotypes and emphasizing the importance of ongoing consent, communication, and respect for sex workers\u27 boundaries. Participants in this study represented a diverse group of individuals in sex work. Gender identities for participants included cisgender women, transgender woman, and agender. Participants engaged in a range of forms of sex work including prostitution, phone sex services, exotic dancing/stripping, among other forms. 90% of participants identified as black/African American with 10% identifying as white/Caucasian. In accordance with grounded theory, participants had the opportunity to review transcripts, and make additions if needed. The transcripts were then analyzed by the dissertation team via initial coding, focused coding, and theoretical coding. Constant comparative methods and memo-writing were employed by the dissertation team. The implications for practice and policy are shared, including suggestions that mental health practitioners should adopt a trauma-informed approach and that policymakers should prioritize the decriminalization of sex work. The integration of sexuality courses in mental health graduate programs is also proposed to enhance understanding and support for this population. Future research directions are identified, emphasizing the need for longitudinal studies on mental health outcomes, resilience factors, and the impact of legal and cultural contexts on sex workers\u27 well-being. This dissertation contributes to the burgeoning discourse on sex work and mental health, advocating for comprehensive, inclusive, and culturally competent approaches to support the well-being, agency, and rights of sex workers. It calls for a reevaluation of societal, legal, and healthcare practices to better accommodate the needs of individuals engaged in sex work, urging a shift towards more equitable and inclusive mental health support systems
Understanding of AI-Aided Reality Capture Data for the Development of BIM Modeling for Building Façade Inspections
No full textThe demand for building façade inspection continuously increases across the United States. Currently, an inspection is done manually during which an inspector must work in an unsafe environment. Recent advancements of drone, digital twin, and AI technologies make it possible to automate the building façade inspection operation and produce an editable as-is digital façade condition model for a better façade inspection as well as documentation.
This dissertation presents the research results of the development of the Scan4Façade3DBIM, which is a fully automatic reality capture (RC) data analytics technology designed for as-is building façade condition and defect BIM modeling using drone photograph and photogrammetric point clouds. The workflow of Scan4Façade3DBIM starts with raw data preprocessing, followed by the cropped single building point cloud going through (building) Point Cloud Alignment, (wall plane) Point Cloud Separation, (wall plane) Point Cloud to (wall plane) Orthoimage, (wall plane section) Orthoimage Separation, (walls, elements and defections) Coordinate Conversion, and (walls, elements, and defections) 3D and BIM Modeling using the developed point cloud and image understanding algorithms, functions and tools. AI-aided image pixelwise segmentation is used to recognize the targeted façade elements and defections. The extracted walls, façade elements and defections, and their geometrical information are saved into a four-level data structure of Wall List, Wall Coordinates, Element Boxes and Defection Location and Dimension, and Irregular Element/Defection Counters in the optimized table-like formatted plain text files. In addition, Dynamo for Revit script is developed for automatic creating the building façades and defections as an editable Revit BIM model.
Comprehensive case studies and experiments were conducted on different styles of buildings with 3D point clouds that were generated from different photogrammetry software with different drone-captured oblique photos. In addition, synthetic building points were used to analyze Scan4Façade3DBIM’s performance in terms of the point cloud quality (i.e., thickness). The results showed Scan4Façade3DBIM could accurately determine wall footprints even though the point cloud had a noise of 0.5 meters. The results of this research have advanced the knowledge of automatic generation of editable as-is façade+defect digital records from the RC data (i.e., 3D building point cloud and 2D defect oblique photos), which is a critical step to automate the building façade inspection using drone, digital twin, and AI technologies
Figure 2
No full textControl and mutant cortex glial cells (CGs) raw image files are attached. They are in .nd2 format- Fig 2(a-d) CG glial cell volumes of control and mutant brains are plotted in graph and statistical analysis is included in prism file.- Fig 2e Comparison of the number of morphologically different CGs in control and mutant brains is plotted and statistical analysis is performed (prism file)- Fig 2f The imageJ calculations are also attached