Forecasting daily cash receipts and disbursements : a general statistical approach

Includes bibliographical references (p. 21-22)

Profiles of cash flow components

Includes bibliographical references (p. 20-22)

Charles W. Bolen Recital Series: Sarah Gentry, Violin; Paul Borg, Piano; Angelo Favis, Guitar; August 19, 2009

Kemp Recital HallAugust 19, 2009Wednesday Evening7:00 p.m

Faculty Recital:Sarah Gentry, Violin

Kemp Recital Hall Tuesday Evening August 26, 2003 8:00p.m

Evaluation of Key Spatiotemporal Learners for Print Track Anomaly Classification Using Melt Pool Image Streams

Recent applications of machine learning in metal additive manufacturing (MAM) have demonstrated significant potential in addressing critical barriers to the widespread adoption of MAM technology. Recent research in this field emphasizes the importance of utilizing melt pool signatures for real-time defect prediction. While high-quality melt pool image data holds the promise of enabling precise predictions, there has been limited exploration into the utilization of cutting-edge spatiotemporal models that can harness the inherent transient and sequential characteristics of the additive manufacturing process. This research introduces and puts into practice some of the leading deep spatiotemporal learning models that can be adapted for the classification of melt pool image streams originating from various materials, systems, and applications. Specifically, it investigates two-stream networks comprising spatial and temporal streams, a recurrent spatial network, and a factorized 3D convolutional neural network. The capacity of these models to generalize when exposed to perturbations in melt pool image data is examined using data perturbation techniques grounded in real-world process scenarios. The implemented architectures demonstrate the ability to capture the spatiotemporal features of melt pool image sequences. However, among these models, only the Kinetics400 pre-trained SlowFast network, categorized as a two-stream network, exhibits robust generalization capabilities in the presence of data perturbations.Comment: This work has been accepted to IFAC for publication under a Creative Commons Licence CC-BY-NC-N

Individually Unique Body Color Patterns in Octopus (Wunderpus photogenicus) Allow for Photoidentification

Studies on the longevity and migration patterns of wild animals rely heavily on the ability to track individual adults. Non-extractive sampling methods are particularly important when monitoring animals that are commercially important to ecotourism, and/or are rare. The use of unique body patterns to recognize and track individual vertebrates is well-established, but not common in ecological studies of invertebrates. Here we provide a method for identifying individual Wunderpus photogenicus using unique body color patterns. This charismatic tropical octopus is commercially important to the underwater photography, dive tourism, and home aquarium trades, but is yet to be monitored in the wild. Among the adults examined closely, the configurations of fixed white markings on the dorsal mantle were found to be unique. In two animals kept in aquaria, these fixed markings were found not to change over time. We believe another individual was photographed twice in the wild, two months apart. When presented with multiple images of W. photogenicus, volunteer observers reliably matched photographs of the same individuals. Given the popularity of W. photogenicus among underwater photographers, and the ease with which volunteers can correctly identify individuals, photo-identification appears to be a practical means to monitor individuals in the wild

Evaluation of polygenic risk scores for ovarian cancer risk prediction in a prospective cohort study.

BACKGROUND: Genome-wide association studies have identified >30 common SNPs associated with epithelial ovarian cancer (EOC). We evaluated the combined effects of EOC susceptibility SNPs on predicting EOC risk in an independent prospective cohort study. METHODS: We genotyped ovarian cancer susceptibility single nucleotide polymorphisms (SNPs) in a nested case-control study (750 cases and 1428 controls) from the UK Collaborative Trial of Ovarian Cancer Screening trial. Polygenic risk scores (PRSs) were constructed and their associations with EOC risk were evaluated using logistic regression. The absolute risk of developing ovarian cancer by PRS percentiles was calculated. RESULTS: The association between serous PRS and serous EOC (OR 1.43, 95% CI 1.29 to 1.58, p=1.3×10-11) was stronger than the association between overall PRS and overall EOC risk (OR 1.32, 95% CI 1.21 to 1.45, p=5.4×10-10). Women in the top fifth percentile of the PRS had a 3.4-fold increased EOC risk compared with women in the bottom 5% of the PRS, with the absolute EOC risk by age 80 being 2.9% and 0.9%, respectively, for the two groups of women in the population. CONCLUSION: PRSs can be used to predict future risk of developing ovarian cancer for women in the general population. Incorporation of PRSs into risk prediction models for EOC could inform clinical decision-making and health management

Greenway pedestrian and cycle bridges from repurposed wind turbine blades

Greenways are long-distance walking and cycling routes, often developed along the routes of disused railways. Greenways therefore are a means of repurposing underused infrastructure to provide sustainable transport. They also offer benefits for leisure activities, rural development and tourism. The network of greenways in the Republic of Ireland is projected to grow to 240 km by 2022, and a further 800 km of long-distance pathways has been proposed. The Irish government announced â ¬64m in funding for greenway projects in 2020, with further commitments to sustainable transport spending in the 2020 Programme for Government. In Northern Ireland there is 1,000 km of abandoned former transport routes with the potential for development as greenways. Many of the proposed greenway routes will need extensive works. In many cases, bridges and overpasses are in poor condition and will require complete reconstruction. Alongside the repurposing of disused railways as sustainable transport routes, there is an opportunity to reuse another type of repurposed infrastructure to create functional and attractive new bridges on greenways: end-of-life decommissioned wind turbine blades. Wind turbine blades are made of durable, lightweight and strong fibre-reinforced polymer (FRP) materials. They are difficult to recycle by conventional methods, but are ideally suited to repurposing. A US-Ireland-Northern Ireland initiative, the Re-Wind network, has created designs for several new artefacts from repurposed wind turbine blades, including a pedestrian bridge. In this paper we will show the advantages of the blade bridge design for deployment on greenways, show details of the testing and design of the worldâ s first repurposed greenway blade bridge, scheduled for installation on the Midleton-Youghal Greenway in Co. Cork in 2021, and outline the environmental and social advantages of using repurposed FRP blades in new infrastructure such as bridges. The paper also discusses the future expected flow of end-of-life blades from decommissioned wind turbines in Ireland and how this can be aligned with repurposing opportunities