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Canine Aggression & the Brain: How Neuroplasticity Could Be Used to Understand & Treat Aggressive Dogs
No full textCanine aggression is a major issue in the fields of both animal welfare and public health. Dog bites create many problems for human health, and aggressive dogs often end up relinquished to shelters or euthanized. The goal of this paper is to bring light to the lack of successful treatments for aggressive dogs and to propose a new way of looking at the issue through a neurological lens. Current treatments for canine aggression include behavior management techniques and medications prescribed for general behavior issues that often do not treat the underlying causes of the aggression. Aggression in the mammalian brain is centered between three brain regions: the amygdala, the hypothalamus, and the medial prefrontal cortex. Brain circuitry between these three regions processes fear, stress, and adverse experiences and affects behavioral responses. Developing treatments including both medication and behavioral management techniques that target these brain areas may be promising when it comes to treating aggressive dogs more successfully and lessening the negative impacts of canine aggression for dogs and humans alike
The Anomalous Zeeman Effect
No full textPieter Zeeman won the Nobel prize for experimentally observing that when a magnetic field is introduced, the spectral lines observed from sodium appear to broaden. Further experiments showed that many of these broadened lines eventually resolved into triplets of lines, as they expected, but some of them resolved into pairs of doublets or sextets. This strange behavior became known as the anomalous Zeeman effect. It took the physics community 24 years to give a mathematical description of these spectral lines, and even then, this description was developed empirically. In this paper, we use quantum mechanics to provide the theoretical underpinning for these observations. We begin by making a foray into classical mechanics, special relativity, and electromagnetic theory to derive the proper form for the Hamiltonian. Then we show how the fine structure and then Zeeman effects split the energy levels of hydrogen. Then we discuss the required time dependent perturbation theory to predict the observed spectral lines
Anthropogenic Noise Modulation of the Avian Gut Microbiome Drives Phenotypic Differentiation Between Urban and Rural Environments.
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The Impacts of Arctic Warming on Vegetation and Migratory Caribou (Rangifer tarandus): The Case for Ecological Mismatch
No full textBreaking the Binary: Evaluating Gender Inclusivity in Neural Coreference Algorithms
No full textThe task of coreference resolution algorithms is to, given a text document, detect spans of word that refer to the same person, or entity. Recent development within the field of coreference resolution has focussed on methods employing neural networks and deep learning (Clark & Manning 2016, Lee et al. 2017, 2018, Barhom et al. 2019, Joshi et al. 2019, Kirstain et al. 2021). One key consideration in the development of these language processing models is how their output might be biased with regards to gender. Prior research has established that coreference models, like many other applications of natural language processing, exhibit bias across the binary masculine-feminine gender divide (Rudinger et al. 2018; Webster et al. 2018; Stanovsky et al. 2019; Levy et al. 2021; Savoldi et al. 2021). However, the bias of these systems in transgender, gender-nonbinary, and genderqueer contexts is not well-studied (Cao & Daumé III, 2020). In this study, I use the gender-inclusive GICoref dataset (Cao & Daumé III, 2020) to evaluate the performance of recent neural coreference models in a gender-inclusive setting. I demonstrate that the gender-inclusivity of coreference algorithms has indeed improved over the last seven years, although they still underperform in gender-inclusive settings compared to the standard test environments
A Molecular Perspective on Ammonia Chemistry in Atmospheric Water Droplets
Get PDFSmall scale chemical processes define familiar atmospheric systems such as smog, weather, and clouds. Dr. Joseph Francisco’s work uses computational chemistry to provide molecular level insights into the small scale processes that inform our understanding of the larger scale systems. We present two computational studies exploring ammonia transport and ion-pair formation at the air-water interface. These examples offer molecular perspectives on particle nucleation and ammonia cycling
International R&D Spillovers, Trade, and Welfare
No full textThis paper investigates whether R&D expenditure has positive externalities at the international level: does R&D spending in one country increase productivity in other countries? Using data from 37 developed countries over the past 30 years, I examine whether these spillovers exist, whether trade is the primary mechanism through which they occur, and the impact of R&D expenditure on social welfare. Using panel cointegration methods I find that international R&D spillovers exist and weak, but inconclusive, evidence that those spillovers occur through trade. I find little evidence that these spillovers have significant effects on social welfare within the geographies and timeframe encompassed by my data, although domestic R&D expenditure is significantly associated with social welfare. This paper expands on the existing literature in two ways. Firstly, I examine international R&D spillovers using a larger dataset and higher quality data. Secondly, I novelly provide a quantitative estimate of the welfare impacts of R&D expenditure, forging a connection between international R&D spillovers and new literature on the links between trade, innovation, and welfar
Generalization of Attention and Working Memory Skills from Cognition Training Games by Elderly Clients: Does Lumosity Really Work?
No full textOlder adults typically experience cognitive decline in attention and working memory. Because lifespan has been extended due to better medical practices in America, it has become crucial to identify ways to maintain cognitive abilities and prevent decline such that the larger group of aging adults are more resilient. Brain-training apps could be an easily accessible and cost-effective method to do so provided that they can improve cognitive abilities more generally. However, it is unclear that practice on particular games from brain apps actually improve general cognitive skills in terms of real life applications. The present study investigated whether practice with the brain-training app, Lumosity ®, improves attention and memory when assessing older adults in a more traditional method. Using a within-subject design, five participants (between the ages of 60 and 73) were tested for improvements in attention and memory using a Visual Search and Sternberg Memory test before and after they participated in 2 weeks of Lumosity training. Results of the study revealed that Lumosity scores significantly improved over the course of 2 weeks. Moreover, generalized attention significantly improved in follow up assessment for low-distractor environments, but not in high-distraction environments. Working memory also improved in the Lumosity game but did not show cohesive improvements in assessment. The findings suggest that attention to less cluttered visual stimuli may be improved through training, especially for older adults who start their training early, but memory is harder to improve, but may occur in individuals based on their age and their initial abilities
