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"Foley, Sean"
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Changing Saudi Arabia : art, culture, and society in the Kingdom
Explores the role of Saudi Arabia's arts movement in promoting progressive social reform in the kingdom.
Book
Sex, Drugs, and Bitcoin
Cryptocurrencies are among the largest unregulated markets in the world. We find that approximately one-quarter of bitcoin users are involved in illegal activity. We estimate that around $76 billion of illegal activity per year involve bitcoin (46% of bitcoin transactions), which is close to the scale of the U.S. and European markets for illegal drugs. The illegal share of bitcoin activity declines with mainstream interest in bitcoin and with the emergence of more opaque cryptocurrencies. The techniques developed in this paper have applications in cryptocurrency surveillance. Our findings suggest that cryptocurrencies are transforming the black markets by enabling “black e-commerce.”
Journal Article
Pleural Space Infections
Pleural space infections have been a well-recognized clinical syndrome for over 4000 years and continue to cause significant morbidity and mortality worldwide. However, our collective understanding of the causative pathophysiology has greatly expanded over the last few decades, as have our treatment options. The aim of this paper is to review recent updates in our understanding of this troublesome disease and to provide updates on established and emerging treatment modalities for patients suffering from pleural space infections. With that, we present a review and discussion synthesizing the recent pertinent literature surrounding the history, epidemiology, pathophysiology, diagnosis, and management of these challenging infections.
Journal Article
3D Cloud Masking Across A Broad Swath Using Multi-Angle Polarimetry and Deep Learning
Understanding the 3-dimensional structure of clouds is of crucial importance to modeling our changing climate. Active sensors, such as radar and lidar, provide accurate vertical cloud profiles, but are mostly restricted to along-track sampling. Passive sensors can capture a wide swath, but struggle to see beneath cloud tops. In essence, both types of products are restricted to two dimensions: as a cross-section in the active case, and an image in the passive case. However, multi-angle sensor configurations contain implicit information about 3D structure, due to parallax and atmospheric path differences. Extracting that implicit information can be challenging, requiring computationally expensive radiative transfer techniques. Machine learning, as an alternative, may be able to capture some of the complexity of a full 3D radiative transfer solution with significantly less computational expense. In this work, we make three contributions towards understanding 3D cloud structure from multi-angle polarimetry. First, we introduce a large-scale, publicly available dataset that fuses existing cloud products into a format more amenable to machine learning. This dataset treats multi-angle polarimetry as an input, and radar-based vertical cloud profiles as an output. Second, we describe and evaluate strong baseline machine learning models based that predict these profiles from the passive imagery. Notably, these models are trained only on center-swath labels, but can predict cloud profiles over the entire passive imagery swath. Third, we leverage the information-theoretic nature of machine learning to draw conclusions about the relative utility of various sensor configurations, including spectral channels, viewing angles, and polarimetry. These findings have implications for Earth-observing missions such as NASA’s Plankton, Aerosol, Cloud-ocean Ecosystem (PACE) and Atmosphere Observing System (AOS) missions, as well as in informing future applications of computer vision to atmospheric remote sensing.
Journal Article
Policy Options for the World's Primary Forests in Multilateral Environmental Agreements
We identify policies that would provide a solid foundation in key international negotiations to ensure that primary forests persist into the 21st Century. A novel compilation of primary forest cover and other data revealed that protection of primary forests is a matter of global concern being equally distributed between developed and developing countries. Almost all (98%) of primary forest is found within 25 countries with around half in five developed ones (USA, Canada, Russia, Australia, and NZ). Only ∼22% of primary forest is found in IUCN Protected Areas Categories I–VI, which is approximately 5% of preagriculture natural forest cover. Rates of deforestation and forest degradation are rapid and extensive, and the long‐term integrity of primary forest cannot be assumed. We recommend four new actions that could be included in climate change, biodiversity, and sustainable development negotiations: (1) recognize primary forests as a matter of global concern within international negotiations; (2) incorporate primary forests into environmental accounting; (3) prioritize the principle of avoided loss; and (4) universally accept the important role of indigenous and community conserved areas. In the absence of specific policies for primary forest protection, their unique biodiversity values and ecosystem services will continue to erode.
Journal Article
A computational investigation of COVID-19 transmission inside hospital wards and associated costs
The COVID-19 pandemic has placed a particular burden on hospitals: from intra-hospital transmission of the infections to reduced admissions of non-COVID-19 patients. There are also high costs associated with the treatment of hospitalised COVID-19 patients, as well as reductions in revenues due to delayed and cancelled treatments. In this study we investigate computationally the transmission of COVID-19 inside a hospital ward that contains multiple-bed bays (with 4 or 6 beds) and multiple single-bed side rooms (that can accommodate the contacts of COVID-19-positive patients). The aim of this study is to investigate the role of 4-bed bays vs. 6-bed bays on the spread of infections and the hospital costs. We show that 4-bed bays are associated with lower infections only when we reduce the discharge time of some patients from 10 days to 5 days. This also leads to lower costs for the treatment of COVID-19 patients. In contrast, 6-bed bays are associated with reduced hospital waiting lists (especially when there are also multiple side rooms available to accommodate the contacts of COVID-19-positive patients identified inside the 6-bed bays).
Journal Article
