264 research outputs found
Network segregation in a model of misinformation and fact checking
Misinformation under the form of rumor, hoaxes, and conspiracy theories
spreads on social media at alarming rates. One hypothesis is that, since social
media are shaped by homophily, belief in misinformation may be more likely to
thrive on those social circles that are segregated from the rest of the
network. One possible antidote is fact checking which, in some cases, is known
to stop rumors from spreading further. However, fact checking may also backfire
and reinforce the belief in a hoax. Here we take into account the combination
of network segregation, finite memory and attention, and fact-checking efforts.
We consider a compartmental model of two interacting epidemic processes over a
network that is segregated between gullible and skeptic users. Extensive
simulation and mean-field analysis show that a more segregated network
facilitates the spread of a hoax only at low forgetting rates, but has no
effect when agents forget at faster rates. This finding may inform the
development of mitigation techniques and overall inform on the risks of
uncontrolled misinformation online
Defect Perturbations in Landau-Ginzburg Models
Perturbations of B-type defects in Landau-Ginzburg models are considered. In
particular, the effect of perturbations of defects on their fusion is analyzed
in the framework of matrix factorizations. As an application, it is discussed
how fusion with perturbed defects induces perturbations on boundary conditions.
It is shown that in some classes of models all boundary perturbations can be
obtained in this way. Moreover, a universal class of perturbed defects is
constructed, whose fusion under certain conditions obey braid relations. The
functors obtained by fusing these defects with boundary conditions are twist
functors as introduced in the work of Seidel and Thomas.Comment: 46 page
The Heat Kernel on AdS_3 and its Applications
We derive the heat kernel for arbitrary tensor fields on S^3 and (Euclidean)
AdS_3 using a group theoretic approach. We use these results to also obtain the
heat kernel on certain quotients of these spaces. In particular, we give a
simple, explicit expression for the one loop determinant for a field of
arbitrary spin s in thermal AdS_3. We apply this to the calculation of the one
loop partition function of N=1 supergravity on AdS_3. We find that the answer
factorizes into left- and right-moving super Virasoro characters built on the
SL(2, C) invariant vacuum, as argued by Maloney and Witten on general grounds.Comment: 46 pages, LaTeX, v2: Reference adde
Looking backward: From Euler to Riemann
We survey the main ideas in the early history of the subjects on which
Riemann worked and that led to some of his most important discoveries. The
subjects discussed include the theory of functions of a complex variable,
elliptic and Abelian integrals, the hypergeometric series, the zeta function,
topology, differential geometry, integration, and the notion of space. We shall
see that among Riemann's predecessors in all these fields, one name occupies a
prominent place, this is Leonhard Euler. The final version of this paper will
appear in the book \emph{From Riemann to differential geometry and relativity}
(L. Ji, A. Papadopoulos and S. Yamada, ed.) Berlin: Springer, 2017
Effects of deletion of the Streptococcus pneumoniae lipoprotein diacylglyceryl transferase gene lgt on ABC transporter function and on growth in vivo
Lipoproteins are an important class of surface associated proteins that have diverse roles and frequently are involved in the virulence of bacterial pathogens. As prolipoproteins are attached to the cell membrane by a single enzyme, prolipoprotein diacylglyceryl transferase (Lgt), deletion of the corresponding gene potentially allows the characterisation of the overall importance of lipoproteins for specific bacterial functions. We have used a Δlgt mutant strain of Streptococcus pneumoniae to investigate the effects of loss of lipoprotein attachment on cation acquisition, growth in media containing specific carbon sources, and virulence in different infection models. Immunoblots of triton X-114 extracts, flow cytometry and immuno-fluorescence microscopy confirmed the Δlgt mutant had markedly reduced lipoprotein expression on the cell surface. The Δlgt mutant had reduced growth in cation depleted medium, increased sensitivity to oxidative stress, reduced zinc uptake, and reduced intracellular levels of several cations. Doubling time of the Δlgt mutant was also increased slightly when grown in medium with glucose, raffinose and maltotriose as sole carbon sources. These multiple defects in cation and sugar ABC transporter function for the Δlgt mutant were associated with only slightly delayed growth in complete medium. However the Δlgt mutant had significantly reduced growth in blood or bronchoalveolar lavage fluid and a marked impairment in virulence in mouse models of nasopharyngeal colonisation, sepsis and pneumonia. These data suggest that for S. pneumoniae loss of surface localisation of lipoproteins has widespread effects on ABC transporter functions that collectively prevent the Δlgt mutant from establishing invasive infection
Biodiversity Loss and the Taxonomic Bottleneck: Emerging Biodiversity Science
Human domination of the Earth has resulted in dramatic changes to global and local patterns of biodiversity. Biodiversity is critical to human sustainability because it drives the ecosystem services that provide the core of our life-support system. As we, the human species, are the primary factor leading to the decline in biodiversity, we need detailed information about the biodiversity and species composition of specific locations in order to understand how different species contribute to ecosystem services and how humans can sustainably conserve and manage biodiversity. Taxonomy and ecology, two fundamental sciences that generate the knowledge about biodiversity, are associated with a number of limitations that prevent them from providing the information needed to fully understand the relevance of biodiversity in its entirety for human sustainability: (1) biodiversity conservation strategies that tend to be overly focused on research and policy on a global scale with little impact on local biodiversity; (2) the small knowledge base of extant global biodiversity; (3) a lack of much-needed site-specific data on the species composition of communities in human-dominated landscapes, which hinders ecosystem management and biodiversity conservation; (4) biodiversity studies with a lack of taxonomic precision; (5) a lack of taxonomic expertise and trained taxonomists; (6) a taxonomic bottleneck in biodiversity inventory and assessment; and (7) neglect of taxonomic resources and a lack of taxonomic service infrastructure for biodiversity science. These limitations are directly related to contemporary trends in research, conservation strategies, environmental stewardship, environmental education, sustainable development, and local site-specific conservation. Today’s biological knowledge is built on the known global biodiversity, which represents barely 20% of what is currently extant (commonly accepted estimate of 10 million species) on planet Earth. Much remains unexplored and unknown, particularly in hotspots regions of Africa, South Eastern Asia, and South and Central America, including many developing or underdeveloped countries, where localized biodiversity is scarcely studied or described. ‘‘Backyard biodiversity’’, defined as local biodiversity near human habitation, refers to the natural resources and capital for ecosystem services at the grassroots level, which urgently needs to be explored, documented, and conserved as it is the backbone of sustainable economic development in these countries. Beginning with early identification and documentation of local flora and fauna, taxonomy has documented global biodiversity and natural history based on the collection of ‘‘backyard biodiversity’’ specimens worldwide. However, this branch of science suffered a continuous decline in the latter half of the twentieth century, and has now reached a point of potential demise. At present there are very few professional taxonomists and trained local parataxonomists worldwide, while the need for, and demands on, taxonomic services by conservation and resource management communities are rapidly increasing. Systematic collections, the material basis of biodiversity information, have been neglected and abandoned, particularly at institutions of higher learning. Considering the rapid increase in the human population and urbanization, human sustainability requires new conceptual and practical approaches to refocusing and energizing the study of the biodiversity that is the core of natural resources for sustainable development and biotic capital for sustaining our life-support system. In this paper we aim to document and extrapolate the essence of biodiversity, discuss the state and nature of taxonomic demise, the trends of recent biodiversity studies, and suggest reasonable approaches to a biodiversity science to facilitate the expansion of global biodiversity knowledge and to create useful data on backyard biodiversity worldwide towards human sustainability
The positive and negative impact of an intergenerational digital technology education programme on younger people’s perceptions of older adults
In order to meet the technological needs of older adults, and ensure digital inclusion, it is important for digital technology designers to accurately assess and understand older adults’ needs and requirements, free from the influence of societal assumptions of their capabilities. This study evaluated the impact of an intergenerational digital technology education programme on younger adults’ stereotypes of older people. Using an experimental design, results show that compared to a control group, students taking part in the programme subsequently rated older adults as more friendly but less competent. Practical implications for developing intergenerational education programmes are discussed
Memory and synaptic plasticity are impaired by dysregulated hippocampal O-GlcNAcylation
O-GlcNAcylated proteins are abundant in the brain and are associated with neuronal functions and neurodegenerative diseases. Although several studies have reported the effects of aberrant regulation of O-GlcNAcylation on brain function, the roles of O-GlcNAcylation in synaptic function remain unclear. To understand the effect of aberrant O-GlcNAcylation on the brain, we used Oga+/- mice which have an increased level of O-GlcNAcylation, and found that Oga+/- mice exhibited impaired spatial learning and memory. Consistent with this result, Oga+/- mice showed a defect in hippocampal synaptic plasticity. Oga heterozygosity causes impairment of both long-term potentiation and long-term depression due to dysregulation of AMPA receptor phosphorylation. These results demonstrate a role for hyper-O-GlcNAcylation in learning and memory.ope
Production and characterization of murine models of classic and intermediate maple syrup urine disease
BACKGROUND: Maple Syrup Urine Disease (MSUD) is an inborn error of metabolism caused by a deficiency of branched-chain keto acid dehydrogenase. MSUD has several clinical phenotypes depending on the degree of enzyme deficiency. Current treatments are not satisfactory and require new approaches to combat this disease. A major hurdle in developing new treatments has been the lack of a suitable animal model. METHODS: To create a murine model of classic MSUD, we used gene targeting and embryonic stem cell technologies to create a mouse line that lacked a functional E2 subunit gene of branched-chain keto acid dehydrogenase. To create a murine model of intermediate MSUD, we used transgenic technology to express a human E2 cDNA on the knockout background. Mice of both models were characterized at the molecular, biochemical, and whole animal levels. RESULTS: By disrupting the E2 subunit gene of branched-chain keto acid dehydrogenase, we created a gene knockout mouse model of classic MSUD. The homozygous knockout mice lacked branched-chain keto acid dehydrogenase activity, E2 immunoreactivity, and had a 3-fold increase in circulating branched-chain amino acids. These metabolic derangements resulted in neonatal lethality. Transgenic expression of a human E2 cDNA in the liver of the E2 knockout animals produced a model of intermediate MSUD. Branched-chain keto acid dehydrogenase activity was 5–6% of normal and was sufficient to allow survival, but was insufficient to normalize circulating branched-chain amino acids levels, which were intermediate between wildtype and the classic MSUD mouse model. CONCLUSION: These mice represent important animal models that closely approximate the phenotype of humans with the classic and intermediate forms of MSUD. These animals provide useful models to further characterize the pathogenesis of MSUD, as well as models to test novel therapeutic strategies, such as gene and cellular therapies, to treat this devastating metabolic disease
Analysing How People Orient to and Spread Rumours in Social Media by Looking at Conversational Threads
As breaking news unfolds people increasingly rely on social media to stay abreast of the latest updates. The use of social media in such situations comes with the caveat that new information being released piecemeal may encourage rumours, many of which remain unverified long after their point of release. Little is known, however, about the dynamics of the life cycle of a social media rumour. In this paper we present a methodology that has enabled us to collect, identify and annotate a dataset of 330 rumour threads (4,842 tweets) associated with 9 newsworthy events. We analyse this dataset to understand how users spread, support, or deny rumours that are later proven true or false, by distinguishing two levels of status in a rumour life cycle i.e., before and after its veracity status is resolved. The identification of rumours associated with each event, as well as the tweet that resolved each rumour as true or false, was performed by journalist members of the research team who tracked the events in real time. Our study shows that rumours that are ultimately proven true tend to be resolved faster than those that turn out to be false. Whilst one can readily see users denying rumours once they have been debunked, users appear to be less capable of distinguishing true from false rumours when their veracity remains in question. In fact, we show that the prevalent tendency for users is to support every unverified rumour. We also analyse the role of different types of users, finding that highly reputable users such as news organisations endeavour to post well-grounded statements, which appear to be certain and accompanied by evidence. Nevertheless, these often prove to be unverified pieces of information that give rise to false rumours. Our study reinforces the need for developing robust machine learning techniques that can provide assistance in real time for assessing the veracity of rumours. The findings of our study provide useful insights for achieving this aim
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