The Electron-Ion Collider (EIC), a state-of-the-art facility for studying the strong force, is expected to begin commissioning its first experiments in 2028. This is an opportune time for artificial ...intelligence (AI) to be included from the start at this facility and in all phases that lead up to the experiments. The second annual workshop organized by the AI4EIC working group, which recently took place, centered on exploring all current and prospective application areas of AI for the EIC. This workshop is not only beneficial for the EIC, but also provides valuable insights for the newly established ePIC collaboration at EIC. This paper summarizes the different activities and R&D projects covered across the sessions of the workshop and provides an overview of the goals, approaches and strategies regarding AI/ML in the EIC community, as well as cutting-edge techniques currently studied in other experiments.
News or Noise? The Missing Link Chahrour, Ryan; Jurado, Kyle
The American economic review,
07/2018, Letnik:
108, Številka:
7
Journal Article
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The literature on belief-driven business cycles treats news and noise as distinct representations of agents’ beliefs. We prove they are empirically the same. Our result lets us isolate the importance ...of purely belief-driven fluctuations. Using three prominent estimated models, we show that existing research understates the importance of pure beliefs. We also explain how differences in both economic environment and information structure affect the estimated importance of pure beliefs.
Abstract
We propose a model in which the emergence of a single dominant currency is driven by the need to finance international trade. The model generates multiple stable steady states, each ...characterized by a different dominant asset, consistent with the historical durability of real-world currency regimes. The persistence of regimes is caused by a positive interaction between the returns to saving in an asset and the use of that asset for financing trade. A calibrated version of the model shows that the welfare gains of dominance are substantial, but accrue primarily during the transition to dominance. We perform several counterfactual experiments to assess potential threats to the dollar’s continued dominance.
Abstract
Time series methods for identifying structural economic disturbances often require disturbances to satisfy technical conditions that can be inconsistent with economic theory. We propose ...replacing these conditions with a less restrictive condition called recoverability, which only requires that the disturbances can be inferred from the observable variables. As an application, we show how shifting attention to recoverability makes it possible to construct new identifying restrictions for technological and expectational disturbances. In a vector autoregressive example using post-war U.S. data, these restrictions imply that independent disturbances to expectations about future technology are a major driver of business cycles.
Although autism has a clear genetic component, the high genetic heterogeneity of the disorder has been a challenge for the identification of causative genes. We used homozygosity analysis to identify ...probands from nonconsanguineous families that showed evidence of distant shared ancestry, suggesting potentially recessive mutations. Whole-exome sequencing of 16 probands revealed validated homozygous, potentially pathogenic recessive mutations that segregated perfectly with disease in 4/16 families. The candidate genes (UBE3B, CLTCL1, NCKAP5L, ZNF18) encode proteins involved in proteolysis, GTPase-mediated signaling, cytoskeletal organization, and other pathways. Furthermore, neuronal depolarization regulated the transcription of these genes, suggesting potential activity-dependent roles in neurons. We present a multidimensional strategy for filtering whole-exome sequence data to find candidate recessive mutations in autism, which may have broader applicability to other complex, heterogeneous disorders.
•Complementary ICP-MS application in proteomics for absolute protein quantification.•Summarising the pros and cons of stable isotope labelling methods in mass spectrometry.•Explaining novel Isobaric ...peptide termini labelling (IPTL).•Reviewing OxICAT (oxidation state determination using ICAT).•Reviewing the Tandem Mass Tag Reagent family.
Mass-spectrometry based proteomics has evolved as a promising technology over the last decade and is undergoing a dramatic development in a number of different areas, such as; mass spectrometric instrumentation, peptide identification algorithms and bioinformatic computational data analysis. The improved methodology allows quantitative measurement of relative or absolute protein amounts, which is essential for gaining insights into their functions and dynamics in biological systems. Several different strategies involving stable isotopes label (ICAT, ICPL, IDBEST, iTRAQ, TMT, IPTL, SILAC), label-free statistical assessment approaches (MRM, SWATH) and absolute quantification methods (AQUA) are possible, each having specific strengths and weaknesses. Inductively coupled plasma mass spectrometry (ICP-MS), which is still widely recognised as elemental detector, has recently emerged as a complementary technique to the previous methods. The new application area for ICP-MS is targeting the fast growing field of proteomics related research, allowing absolute protein quantification using suitable elemental based tags. This document describes the different stable isotope labelling methods which incorporate metabolic labelling in live cells, ICP-MS based detection and post-harvest chemical label tagging for protein quantification, in addition to summarising their pros and cons.
Abstract
We formalize the idea that house price changes may drive rational waves of optimism and pessimism in the economy. In our model, a house price increase caused by aggregate disturbances may be ...misinterpreted as a sign of higher local permanent income, leading households to demand more consumption and housing. Higher demand reinforces the initial price increase in an amplification loop that drives comovement in output, labour, residential investment, land prices, and house prices even in response to aggregate supply shocks. The qualitative implications of our otherwise frictionless model are consistent with observed business cycles and it can explain the economic impact of apparently autonomous changes in sentiment without resorting to non-fundamental shocks or nominal rigidity.
Advances in genetic tools and sequencing technology in the past few years have vastly expanded our understanding of the genetics of neurodevelopmental disorders. Recent high-throughput sequencing ...analyses of structural brain malformations, cognitive and neuropsychiatric disorders, and localized cortical dysplasias have uncovered a diverse genetic landscape beyond classic Mendelian patterns of inheritance. The underlying genetic causes of neurodevelopmental disorders implicate numerous cell biological pathways critical for normal brain development.
The postnatal neurodevelopmental disorder Rett syndrome (RTT) is caused by mutations in the gene encoding methyl-CpG binding protein 2 (MeCP2), a transcriptional repressor involved in chromatin ...remodeling and the modulation of RNA splicing.
MECP2 aberrations result in a constellation of neuropsychiatric abnormalities, whereby both loss of function and gain in
MECP2 dosage lead to similar neurological phenotypes. Recent studies demonstrate disease reversibility in RTT mouse models, suggesting that the neurological defects in
MECP2 disorders are not permanent. To investigate the potential for restoring neuronal function in RTT patients, it is essential to identify MeCP2 targets or modifiers of the phenotype that can be therapeutically modulated. Moreover, deciphering the molecular underpinnings of RTT is likely to contribute to the understanding of the pathogenesis of a broader class of neuropsychiatric disorders.
The novel coronavirus disease 2019 (COVID-19) has impacted many countries across all inhabited continents, and is now considered a global pandemic, due to its high rate of infectivity. Research ...related to this disease is pivotal for assessing pathogenic characteristics and formulating therapeutic strategies. The aim of this paper is to explore the activity and trends of COVID-19 research since its outbreak in December 2019.
We explored the PubMed database and the World Health Organization (WHO) database for publications pertaining to COVID-19 since December 2019 up until March 18, 2020. Only relevant observational and interventional studies were included in our study. Data on COVID-19 incidence were extracted from the WHO situation reports. Research output was assessed with respect to gross domestic product (GDP) and population of each country.
Only 564 publications met our inclusion criteria. These articles came from 39 different countries, constituting 24% of all affected countries. China produced the greatest number of publications with 377 publications (67%). With respect to continental research activity, Asian countries had the highest research activity with 434 original publications (77%). In terms of publications per million persons (PPMPs), Singapore had the highest number of publications with 1.069 PPMPs. In terms of publications per billion-dollar GDP, Mauritius ranked first with 0.075.
COVID-19 is a major disease that has impacted international public health on a global level. Observational studies and therapeutic trials pertaining to COVID-19 are essential for assessing pathogenic characteristics and developing novel treatment options.
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