Statistical methods for bullet matching

Despite being an accepted and established forensic science practice, the process of matching bullets to determine whether they were fired from the same gun barrel has come under fairly intense scrutiny in recent years. This began in earnest in 2009 with a National Academy of Sciences report questioning the scientific validity of these methods. Further criticisms were made in a 2016 report by the President\u27s Council of Advisors on Science and Technology (PCAST). After PCAST determined that there has only been one appropriately designed study to assess the accuracy of bullet matching methods, the report concluded that [T]he current evidence falls short of the scientific criteria for foundational validity. The report also outlines a way forward by noting A second—and more important—direction is . . . to convert firearms analysis from a subjective method to an objective method. This thesis attempts to take steps towards that goal. It begins by describing an automatic algorithm for matching bullet lands, and assesses this algorithm on the James Hamby study data. These ideas are then generalized in order to increase the prediction accuracy, determine operator effects in bullet scanning, handle the case of bullet land degradation, and apply to full bullet matches. Finally, a modern web-based database and software system for bullet matching is introduced, allowing for more seamless collaboration in the research community for assessing and improving these algorithms

Genes repressed after DNA damage in Acinetobacter baumannii are co-regulated by UmuDAb and DdrR

UmuDAb and DdrR coregulate error-prone polymerases in the multi-drug resistant opportunistic pathogen, Acinetobacter baumannii, by repressing polymerase expression until after DNA damage. New evidence indicates that these proteins may also regulate other genes that are repressed following DNA damage. We performed an in silico analysis of RNA-Seq data from wild-type, ddrR, and umuDAb mutant strains to examine the expression levels of genes repressed after DNA damage. We used two different algorithms to analyze Cuffnorm- and HTSeq normalized gene counts. This analysis revealed nineteen (CuffDiff) or twenty-nine (DESeq2) genes repressed in wild-type cells that were derepressed after DNA damage in either one or both of the mutant strains. The proteins encoded by these genes include an induced acetoin metabolism operon, a putative YfbU family member (often required for MazF-mediated cell death after DNA damage), RlpA (a septal ring lytic transglycosylase), and a putative cold-shock protein. We carried out RT-qPCR verification of the RNA-Seq data and found that these genes are dysregulated after DNA damage, indicating DdrR and UmuDAb’s regulatory functions. Upon completion of RT-qPCR, we will construct strains containing mutations in these genes to test if DdrR and UmuDAb co-regulate these repressed genes. This will aid us in our understanding of how their downregulation may be involved in the pathogen’s response to DNA damage-induced stress.https://scholarworks.moreheadstate.edu/celebration_posters_2022/1005/thumbnail.jp

Genes involved in cell division in Acinetobacter baumannii are coregulated by UmuDAb and DdrR

In the presence of DNA damage, the multi-drug resistant bacteria Acinetobacter baumannii employs the proteins UmuDAb and DdrR to repress the expression of error-prone polymerases.https://scholarworks.moreheadstate.edu/celebration_posters_2022/1010/thumbnail.jp

Image-Based Sorghum Head Counting When You Only Look Once

Modern trends in digital agriculture have seen a shift towards artificial intelligence for crop quality assessment and yield estimation. In this work, we document how a parameter tuned single-shot object detection algorithm can be used to identify and count sorghum heads from aerial drone images. Our approach involves a novel exploratory analysis that identified key structural elements of the sorghum images and motivated the selection of parameter-tuned anchor boxes that contributed significantly to performance. These insights led to the development of a deep learning model that outperformed the baseline model and achieved an out-of-sample mean average precision of 0.95

Teacher enactment of the Geospatial Inquiry cycle in classrooms following scaled up professional learning and development

The current study examined the effects of a nationally scaled up Professional Learning and Development (PLD) model on teachers’ classroom implementation of the Geospatial Inquiry instructional framework. Geospatial Inquiry is defined as: asking and answering a research question through the analysis and communication of data that is linked to a geographic location on, above, or near Earth. These data are often represented visually via maps and explored with geospatial technologies. It also examined the relationships between Geospatial Inquiry Teacher Workshop (GITW) implementation and teacher implementation of the Geospatial Inquiry Cycle. Situated cognition provided a theoretical framework for the design, development, and implementation of the GITWs and lessons. Surveys, technology assessments, lessons, and artifacts were analysed using a-priori coding, descriptive statistics, and a generalised linear modelling approach that included hierarchical analysis. Results indicated teachers implemented Geospatial Inquiry lessons with integrity to the principles of Geospatial Inquiry and utilised research-based pedagogical practices. Format of GITWs (e.g. face-to-face or blended) resulted in differences during teachers’ lesson implementation. In addition, whether GITWs were delivered by an individual facilitator or a team of facilitators impacted teachers’ lessons. The findings have several implications for the design and scaling of PLD

Strategic analysis for the MER Cape Verde approach

The Mars Exploration Rover Opportunity has recently completed a two year campaign studying Victoria Crater. The campaign culminated in a close approach of Cape Verde in order to acquire high resolution imagery of the exposed stratigraphy in the cliff face. The close approach to Cape Verde provided significant challenges for every subsystem of the rover as the rover needed to traverse difficult, un-characterised terrain and approach a cliff face with the potential of blocking out solar energy and communications with Earth. In this paper we describe the strategic analyses performed by the science and engineering teams so that we could successfully achieve the science objectives while keeping the rover safe

Good practice in food-related neuroimaging

The use of neuroimaging tools, especially functional magnetic resonance imaging, in nutritional research has increased substantially over the past 2 decades. Neuroimaging is a research tool with great potential impact on the field of nutrition, but to achieve that potential, appropriate use of techniques and interpretation of neuroimaging results is necessary. In this article, we present guidelines for good methodological practice in functional magnetic resonance imaging studies and flag specific limitations in the hope of helping researchers to make the most of neuroimaging tools and avoid potential pitfalls. We highlight specific considerations for food-related studies, such as how to adjust statistically for common confounders, like, for example, hunger state, menstrual phase, and BMI, as well as how to optimally match different types of food stimuli. Finally, we summarize current research needs and future directions, such as the use of prospective designs and more realistic paradigms for studying eating behavior