Small Science: A Tool and Tips for Converting Food Science Demonstrations into Public Inquiry Experiences

Small-scale science activities provide an opportunity for engagement of diverse, large audiences at settings such as 4-H fairs. We present practical information for implementation of small-scale food science experiences in the Extension education context. Our focus is description of a tool for adaptation of activities for inquiry-based learning and tips for miniaturization of activities to save on costs and resources

Essays in banking and macroeconomics

My dissertation consists of three essays covering aspects of macroeconomics and financial economics. In “Settling Up on Securitization: Principles, Payoffs, and Precedent,” cowritten with Prof. King, we investigate the subprime mortgage-backed securities of the 2000s through the lens of Federal Housing Finance Agency lawsuits resulting in settlements and trials recovering billions of dollars to Fannie Mae and Freddie Mac, which had invested in these securities. We find that in some cases the GSE investors received compensation exceeding the economic damages they had suffered on securities purchased, that this was in part motivated by state securities law rather than federal, and that the FHFA v. Nomura case brought new securities law precedent unfavorable to defendants based on a macroeconomic argument. In “How Do You Solve a Problem Like Nomura? Remedies for Securities Fraud with Market-level Consequences,” I use discrete and continuous action models to examine incentives and market outcomes of the Nomura policy change in a securities market with multiple interacting issuers choose the quality of securities they issue. Its main conclusion is that, post-Nomura, issuers improve underwriting quality when poor underwriting brings negative macroeconomic effects, improving outcomes for investors and issuers. However, this conclusion is sensitive to market structure and investors’ information sets. While the precedent addresses information frictions, it does not resolve other externality problems leading to degraded underwriting quality. In “Heterogeneity in an Infinite-horizon Banking Model” I take an off-the-shelf model of an economy with a banking system featuring endogenous bank runs and extend it to investigate the presence of multiple banks with distinct histories and prospects. I employ perfect-foresight analysis to examine the effect of differential productivity shocks on the economy’s banks, spillovers between banking systems, and circumstances where bank runs are possible and analyze intermediation patterns among banks at steady state. The major result is that heterogeneity between banks increases the threshold productivity shock permitting bank runs but can lead to protracted income divergence between consumers associated with different banks

Nickel-Catalyzed Mizoroki-Heck Reaction of Aryl Sulfonates and Chlorides with Electronically Unbiased Terminal Olefins: High Selectivity for Branched Products

Achieving high selectivity in the Heck reaction of electronically unbiased alkenes has been a longstanding challenge. Using a nickel-catalyzed cationic Heck reaction, we were able to achieve excellent selectivity for branched products (≥19:1 in all cases) over a wide range of aryl electrophiles and aliphatic olefins. A bidentate ligand with a suitable bite angle and steric profile was key to obtaining high branched/linear selectivity, whereas the appropriate base suppressed alkene isomerization of the product. Although aryl triflates are traditionally used to access the cationic Heck pathway, we have shown that, by using triethylsilyl trifluoromethanesulfonate, we can effect a counterion exchange of the catalytic nickel complex, such that cheaper and more stable aryl chlorides, mesylates, tosylates, and sulfamates can be used to yield the same branched products with high selectivity.National Institute of General Medical Sciences (U.S.) (NIGMS (GM62755))National Institutes of Health (U.S.) (NIH Postdoctoral Fellowship)National Science Foundation (U.S.) (NSF Graduate Research Fellowship

SniffyArt: The Dataset of Smelling Persons

Smell gestures play a crucial role in the investigation of past smells in the visual arts yet their automated recognition poses significant challenges. This paper introduces the SniffyArt dataset, consisting of 1941 individuals represented in 441 historical artworks. Each person is annotated with a tightly fitting bounding box, 17 pose keypoints, and a gesture label. By integrating these annotations, the dataset enables the development of hybrid classification approaches for smell gesture recognition. The datasets high-quality human pose estimation keypoints are achieved through the merging of five separate sets of keypoint annotations per person. The paper also presents a baseline analysis, evaluating the performance of representative algorithms for detection, keypoint estimation, and classification tasks, showcasing the potential of combining keypoint estimation with smell gesture classification. The SniffyArt dataset lays a solid foundation for future research and the exploration of multi-task approaches leveraging pose keypoints and person boxes to advance human gesture and olfactory dimension analysis in historical artworks.Comment: 10 pages, 8 figure

Variability of major fatty acid contents in Luxembourg dairy cattle

Common human health concerns and imminent needs for more sustainable nutrition patterns require from dairy industry and farmers a. o. a closer look at milk fatty acid (FA) profile. Therefore up to date calibration equations using mid-infrared (MIR) spectrometry were developed permitting the estimation of FA contents in bovine milk. The aim of this study was to estimate the variability of the major FA from data collected during the Luxembourg routine milk recording. A total of 148,296 milk samples with MIR-spectra were collected from October 2007 to January 2009 on 36,522 cows belonging to 5 breeds in 718 herds and scanned by Foss MilkoScan FT6000. The contents of saturated FA, monounsaturated FA, omega-9, short chain FA, medium chain FA, and long chain FA were obtained using Belgian MIR calibration equations. Analyzes were done by a multi-trait multi-lactation animal mixed models. Fixed effects were herd*test date, lactation stage lactation number, age*lactation number, and breed effect. Random effects were herd*year of calving, permanent environment within and across lactation, animal effect, and residual effect. Breed differences as well as lactation effects were observed. Our results showed moderate heritability values suggesting the existence of a FA genetic variability. The variability of the first Luxembourg breeding values was large enough to develop selection tools for improving the nutritional quality of bovine milk fat.Peer reviewe

Multimodal and Multilingual Understanding of Smells using VilBERT and mUNITER

We evaluate state-of-the-art multimodal models to detect common olfactory references in multilingual text and images in the scope of the Multimodal Understanding of Smells in Texts and Images (MUSTI) at Mediaeval’22. The goal of the MUSTI Subtask 1 is to classify paired text and images as to whether they refer to the same smell source or not. We approach this task as a Visual Entailment problem and evaluate the performance of the English model ViLBERT and the multilingual model mUNITER on MUSTI Subtask 1. Although base VilBERT and mUNITER models perform worse than a dummy baseline, fine-tuning these models improve performance significantly in almost all scenarios. We find that fine-tuning mUNITER with SNLI-VE and MUSTI train data performs better than other configurations we implemented. Our experiments demonstrate that the task presents some challenges, but it is by no means impossible. Our code is available on https://github. com/Odeuropa/musti-eval-baselines

Seeing Smell: Sourcing Olfactory Imagery Using Artificial Intelligence

How can artificial intelligence help to “see” smells in works of art? This article discusses the ways in which the Horizon 2020 Odeuropa project uses computer vision to search for olfactory imagery in digital heritage collections. It provides a literature review of the latest approaches to researching smell in art, and outlines the methodology for mining digital collections. It also raises questions about what it means to source smell in digital archives, the challenges encountered when working with the technology, and its possibilities. It concludes with a case study illustrating the potential of such an approach, where computer vision was used to find perfumed gloves in works of art, resulting in an olfactory guided tour of Museum Ulm

Identification of small interfering RNA targeting Signal Transducer and Activator of Transcription 6: Characterisation and selection of candidates for pre-clinical development

The interleukin (IL)-13 pathway and its associated transcription factor, signal transducer and activator of transcription 6 (STAT6), have been clearly implicated in the pathogenesis of bronchial asthma. We have developed a system to effectively screen the STAT6 gene for targeting with small interfering (si) RNA molecules. By incorporating an in silico and in vitro screening system we were able to identify fourteen siRNA molecules suitable for pre-clinical drug development. Furthermore, we were able to demonstrate that modification of certain siRNAs, designed to improve in vivo longevity, was possible without significant loss of target knockdown efficacy and that the siRNA produced by our selection process did not induce demonstrable interferon responses. These data suggest that several STAT6-targeting siRNA suitable for pre-clinical development are available for potential use in the treatment of asthma

Exact λ-numbers of generalized Petersen graphs of certain higher-orders and on Möbius strips

AbstractAn L(2,1)-labeling of a graph G is an assignment f of nonnegative integers to the vertices of G such that if vertices x and y are adjacent, |f(x)−f(y)|≥2, and if x and y are at distance two, |f(x)−f(y)|≥1. The λ-number of G is the minimum span over all L(2,1)-labelings of G. A generalized Petersen graph (GPG) of order n consists of two disjoint copies of cycles on n vertices together with a perfect matching between the two vertex sets. By presenting and applying a novel algorithm for identifying GPG-specific isomorphisms, this paper provides exact values for the λ-numbers of all GPGs of orders 9, 10, 11, and 12. For all but three GPGs of these orders, the λ-numbers are 5 or 6, improving the recently obtained upper bound of 7 for GPGs of orders 9, 10, 11, and 12. We also provide the λ-numbers of several infinite subclasses of GPGs that have useful representations on Möbius strips