6,700 research outputs found

    The Concept of a Smart Action – Results from Analyzing Information Systems Literature

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    In recent years, the term \u27smartness\u27 has entered widespread use in research and daily life. It has emerged with various applications of the Internet of Things, such as smart homes and smart factories. However, rapid technological development and careless use of the term mean that, in information systems (IS) research, a common understanding of smartness has not yet been established. And while it is recognized that smartness encompasses more than the use of impressive information technology applications, a unified conceptualization of how smartness is manifested in IS research is lacking. To this end, we conducted a structured literature review applying techniques from Grounded Theory. We found that smartness occurs through actions, in which smart things and individuals interact, process information, and make data-based decisions that are perceived as smart. Building on these findings, we propose the concept of a \u27smart action\u27 and derive a general definition of smartness. Our findings augment knowledge about how smartness is formed, offering a new perspective on smartness. The concept of a smart action unifies and increases understanding of \u27smartness\u27 in IS research. It supports further research by providing a concept for describing, analyzing, and designing smart actions, smart devices, and smart services

    A review of technical factors to consider when designing neural networks for semantic segmentation of Earth Observation imagery

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    Semantic segmentation (classification) of Earth Observation imagery is a crucial task in remote sensing. This paper presents a comprehensive review of technical factors to consider when designing neural networks for this purpose. The review focuses on Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Generative Adversarial Networks (GANs), and transformer models, discussing prominent design patterns for these ANN families and their implications for semantic segmentation. Common pre-processing techniques for ensuring optimal data preparation are also covered. These include methods for image normalization and chipping, as well as strategies for addressing data imbalance in training samples, and techniques for overcoming limited data, including augmentation techniques, transfer learning, and domain adaptation. By encompassing both the technical aspects of neural network design and the data-related considerations, this review provides researchers and practitioners with a comprehensive and up-to-date understanding of the factors involved in designing effective neural networks for semantic segmentation of Earth Observation imagery.Comment: 145 pages with 32 figure

    Decision-making with gaussian processes: sampling strategies and monte carlo methods

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    We study Gaussian processes and their application to decision-making in the real world. We begin by reviewing the foundations of Bayesian decision theory and show how these ideas give rise to methods such as Bayesian optimization. We investigate practical techniques for carrying out these strategies, with an emphasis on estimating and maximizing acquisition functions. Finally, we introduce pathwise approaches to conditioning Gaussian processes and demonstrate key benefits for representing random variables in this manner.Open Acces

    Swift: A modern highly-parallel gravity and smoothed particle hydrodynamics solver for astrophysical and cosmological applications

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    Numerical simulations have become one of the key tools used by theorists in all the fields of astrophysics and cosmology. The development of modern tools that target the largest existing computing systems and exploit state-of-the-art numerical methods and algorithms is thus crucial. In this paper, we introduce the fully open-source highly-parallel, versatile, and modular coupled hydrodynamics, gravity, cosmology, and galaxy-formation code Swift. The software package exploits hybrid task-based parallelism, asynchronous communications, and domain-decomposition algorithms based on balancing the workload, rather than the data, to efficiently exploit modern high-performance computing cluster architectures. Gravity is solved for using a fast-multipole-method, optionally coupled to a particle mesh solver in Fourier space to handle periodic volumes. For gas evolution, multiple modern flavours of Smoothed Particle Hydrodynamics are implemented. Swift also evolves neutrinos using a state-of-the-art particle-based method. Two complementary networks of sub-grid models for galaxy formation as well as extensions to simulate planetary physics are also released as part of the code. An extensive set of output options, including snapshots, light-cones, power spectra, and a coupling to structure finders are also included. We describe the overall code architecture, summarize the consistency and accuracy tests that were performed, and demonstrate the excellent weak-scaling performance of the code using a representative cosmological hydrodynamical problem with \approx300300 billion particles. The code is released to the community alongside extensive documentation for both users and developers, a large selection of example test problems, and a suite of tools to aid in the analysis of large simulations run with Swift.Comment: 39 pages, 18 figures, submitted to MNRAS. Code, documentation, and examples available at www.swiftsim.co

    PLACING THE EVOLUTIONARY HISTORY OF \u3ci\u3eDESMOGNATHUS\u3c/i\u3e SALAMANDERS IN CONTEXT: A PHYLOGEOGRAPHIC APPROACH

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    Patterns of genetic variation do not arise in a vacuum but are instead shaped by the interplay between evolutionary forces and ecological constraints. Here, I use a phylogeographic approach to examine the role that ecology played in lineage divergence in the Desmognathus quadramaculatus species complex (Family: Plethodontidae), which consists of three nominal species: D. quadramaculatus, D. marmoratus, and D. folkertsi. Previous phylogenetic studies have shown that individuals from these species do not form clades based on phenotype. My approach to reconciling phylogenetic discordance was two-fold, using (1) genome-wide markers to provide insight into the relationships among lineages and (2) geographic and climate data to provide context for patterns of genetic diversity. First, I obtained genome-wide nuclear markers using double-digest restriction-site associated DNA sequencing (ddRAD) to examine whether two morphologically divergent species, D. marmoratus and D. quadramaculatus, represent independently evolving lineages. Phylogenetic, population structure, and model testing analyses all confirmed that D. marmoratus and D. quadramaculatus do not group based on phenotype. Instead, I found that there were two cryptic genetic lineages (Nantahala and Pisgah) that each contained both phenotypes. Additionally, ecological niche modeling showed that the two genetic lineages primarily occupy geographic areas with significantly different climates, suggesting that climate may have played a role in divergence. Next, I assembled loci from publicly available sequencing data using a draft transcriptome of Desmognathus fuscus as a reference to assess the three nominal species in the quadramaculatus species complex across their entire range. I used phylogenetic and population structure analyses, alongside haplowebs and conspecificity matrices, to determine if the loci supported the hypothesis that the phenotypes represent multiple independently evolving lineages within the broader genetic clades found in the previous chapter. I found that the loci were not informative enough to determine whether the phenotypes had a genetic basis in Pisgah, but did support genetic divergence between phenotypes in Nantahala. Finally, I used ecological niche models (ENMs) and resistance modeling to place the genetic results and phenotypic diversity within the context of time and space. I found that though the quadramaculatus and marmoratus phenotypes were nearly indistinguishable in niche space in the present day, they were projected to occupy different geographic areas in the past and future. The southern portion of the study area had areas of high habitat suitability from the Last Glacial Maximum (~22 kya) to the present, which aligns with the higher genetic divergence between groups in Nantahala. Anthropogenic land use changes reduced habitat availability but likely did not drive genetic divergence in the past, and may be of more consequence to genetic diversity than climate change over the next 50 years. Like many taxa that underwent adaptive radiations, the evolutionary history of Desmognathus has been obfuscated by high rates of within-species phenotypic diversity and shared morphology between distantly related lineages. My findings emphasize the importance of interrogating complex patterns of genetic variation within the context of the dynamic, heterogeneous landscapes in which they arise

    Advances in Methane Production from Coal, Shale and Other Tight Rocks

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    This collection reports on the state of the art in fundamental discipline application in hydrocarbon production and associated challenges in geoengineering activities. Zheng et al. (2022) report an NMR-based method for multiphase methane characterization in coals. Wang et al. (2022) studied the genesis of bedding fractures in Ordovician to Silurian marine shale in the Sichuan basin. Kang et al. (2022) proposed research focusing on the prediction of shale gas production from horizontal wells. Liang et al. (2022) studied the pore structure of marine shale by adsorption method in terms of molecular interaction. Zhang et al. (2022) focus on the coal measures sandstones in the Xishanyao Formation, southern Junggar Basin, and the sandstone diagenetic characteristics are fully revealed. Yao et al. (2022) report the source-to-sink system in the Ledong submarine channel and the Dongfang submarine fan in the Yinggehai Basin, South China Sea. There are four papers focusing on the technologies associated with hydrocarbon productions. Wang et al. (2022) reported the analysis of pre-stack inversion in a carbonate karst reservoir. Chen et al. (2022) conducted an inversion study on the parameters of cascade coexisting gas-bearing reservoirs in coal measures in Huainan. To ensure the safety CCS, Zhang et al (2022) report their analysis of available conditions for InSAR surface deformation monitoring. Additionally, to ensure production safety in coal mines, Zhang et al. (2022) report the properties and application of gel materials for coal gangue control

    Ciguatoxins

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    Ciguatoxins (CTXs), which are responsible for Ciguatera fish poisoning (CFP), are liposoluble toxins produced by microalgae of the genera Gambierdiscus and Fukuyoa. This book presents 18 scientific papers that offer new information and scientific evidence on: (i) CTX occurrence in aquatic environments, with an emphasis on edible aquatic organisms; (ii) analysis methods for the determination of CTXs; (iii) advances in research on CTX-producing organisms; (iv) environmental factors involved in the presence of CTXs; and (v) the assessment of public health risks related to the presence of CTXs, as well as risk management and mitigation strategies

    Living Labor

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    For much of the twentieth century, the iconic figure of the U.S. working class was a white, male industrial worker. But in the contemporary age of capitalist globalization new stories about work and workers are emerging to refashion this image. Living Labor examines these narratives and, in the process, offers an innovative reading of American fiction and film through the lens of precarious work. It argues that since the 1980s, novelists and filmmakers—including Russell Banks, Helena Víramontes, Karen Tei Yamashita, Francisco Goldman, David Riker, Ramin Bahrani, Clint Eastwood, Courtney Hunt, and Ryan Coogler—have chronicled the demise of the industrial proletariat, and the tentative and unfinished emergence of a new, much more diverse and perilously positioned working class. In bringing together stories of work that are also stories of race, ethnicity, gender, and colonialism, Living Labor challenges the often-assumed division between class and identity politics. Through the concept of living labor and its discussion of solidarity, the book reframes traditional notions of class, helping us understand both the challenges working people face and the possibilities for collective consciousness and action in the global present

    Air pollution, nanotoxicity and neurodegeneration; exploring the relationship between environmental metallic nanoparticles and human health

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    Air pollution and Alzheimer’s disease (AD) are two of the largest global health issues faced by society today; air pollution is a recognised risk factor for AD. Particulate matter (PM) is a major component of air pollution and refers to the solid and liquid particulates of varying sizes and compositions that are resuspended in the air. Of these particles, metallic particles in the nanometre range (ultrafine, UFPs; < 0.1 µm) are particularly hazardous due to their pervasiveness, ability to penetrate all major organs in the human body, and ability to generate both inflammatory and oxidative stress responses in humans. Magnetite (Fe3O4) nanoparticles (MNPs) and related iron oxides may be of relevance to neurodegeneration. MNPs are found within PM, typically in association with toxic metals, and have been found throughout the human brain, including in association with senile plaques (a key pathological hallmark of AD). MNPs have also been shown to accelerate amyloid beta (Aβ) toxicity and aggregation. MNPs have previously been quantified in a handful of studies to compare AD and control tissue, with mixed results. Improved understanding of the development of AD, the toxic effects of air pollution (especially magnetite and metals), and the relationship between these two phenomena would be highly beneficial to global health. In order to explore the potential causal link between air pollution and AD, two approaches were taken; metallic and magnetic quantification of post-mortem human brain tissue via superconducting quantum interference device (SQUID) magnetometry and inductively couple plasma mass spectrometry (ICP-MS), and exploration of the cytotoxic effects of ultrafine roadside dust particles (UF-RDPs) on human lung epithelial cells (Calu-3) using different in vitro assays. The concentration of magnetite (measured as magnetic remanence, SIRM) in human brain tissue was not statistically different when comparing AD cases to aged-matched controls. Similarly, there were no differences in metal content between the two groups. Principal component analysis grouped the metals into four components, which are potentially indicators of pollution sources: (1) traffic-related and crustal, (2) fuel oil combustion, (3) biological and tyre/brake wear, and (4) catalytic converters and dental alloys. The distributions of magnetite and metals were heterogenous across different individuals. Significantly lower concentrations of both MNPs and metals were reported in UK samples, compared topreviously reported Mexico City samples. Differences were also seen when comparing the in vitro response to UF-RDPs from three contrasting cities; Lancaster UF-RDPs increased cell viability, whilst Mexico City UF-RDPs were the most toxic and induced the highest amount of oxidative stress (ROS production), and Birmingham UF-RDPs were the most pro-inflammatory. These responses are not fully reflected in conventional mass metrics like PM10, as although the greatest cytotoxicity and ROS production was seen with Mexico City UF-RDPs (highest PM10 exposure), the strongest pro-inflammatory responses were seen in response to Birmingham UF-RDPs and a potentially tumorigenic or fibrosis related increase in cell viability was seen in response to Lancaster UF-RDPs despite the lower PM10 and PM2.5 exposures in the UK cities. There is a need for localised air pollution limits which use biologically relevant metrics that address particle size and cover non-exhaust emission sources of PM like road dust to minimize the health risks of air pollution exposure. Overall, this work demonstrates the presence of exogenous, pollution-derived metals and magnetic nanoparticles within the human brain. Highly reactive and toxic metals and MNPs may exert toxic effects in the brain and have been causally linked to neurodegeneration and AD. The geriatric blood-brain barrier is likely compromised allowing for universal incursion in both AD and age-matched controls, so the use of younger highly exposed individuals such as Mexico City urbanites is critical to identify any changes in metal/magnetic content in the brain decades prior to the presentation of AD. Clear differences were seen across geographical locations when looking at absolute concentrations of MNPs, as well as the composition and induced biological effects of UF-RDPs from different cities. It is thus important to focus on highly localised air pollution regulations to mitigate risk to human health
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