879 resultados para false acceptance


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In an exploration of intellectual property and fashion, this article examines the question of the intermediary liability of online auction-houses for counterfeiting. In the United States, the illustrious jewellery store, Tiffany & Co, brought a legal action against eBay Inc, alleging direct trademark infringement, contributory trademark infringement, false advertising, unfair competition and trademark dilution. The luxury store depicted the online auction-house as a pirate bazaar, a flea-market and a haven for counterfeiting. During epic litigation, eBay Inc successfully defended itself against these allegations in a United States District Court and the United States Court of Appeals for the Second Circuit. Tiffany & Co made a desperate, unsuccessful effort to appeal the matter to the Supreme Court of the United States. The matter featured a number of interventions from amicus curiae — Tiffany was supported by Coty, the Fashion Designer's Guild, and the International Anticounterfeiting Coalition, while eBay was defended by publicly-spirited civil society groups such as Electronic Frontier Foundation, Public Citizen, and Public Knowledge as well as Yahoo!, Google Inc, Amazon.com, and associations representing telecommunications carriers and internet service providers. The litigation in the United States can be counterpointed with the fusillade of legal action against eBay in the European Union. In contrast to Tiffany & Co, Louis Vuitton triumphed over eBay in the French courts — claiming its victory as vindication of the need to protect the commercial interests and cultural heritage of France. However, eBay has fared somewhat better in a dispute with L’Oréal in Great Britain and the European Court of Justice. It is argued that, in a time of flux and uncertainty, Australia should follow the position of the United States courts in Tiffany & Co v eBay Inc. The final part examines the ramifications of this litigation over online auction-houses for trade mark law reform and consumer rights; parallel disputes over intermediary liability and safe harbours in the field of copyright law and the Anti-Counterfeiting Trade Agreement 2010. The conclusion calls for a revision of trade mark law, animated by a respect for consumers’ rights and interests in the electronic marketplace.

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An artistic controversy over a group of landscape painters called the Daubists provided impetus for copyright law reform in Australia in the early 1990's. In the first exhibition of Daubism in 1991 driller Jet Armstrong painted a crop circle over a painting of the Olgas by Charles Bannon - an artist, print-maker, and the father of the State Premier at the time, John Bannon. He called the resulting work, Crop Circles on a Bannon Landscape. Armstrong also inserted an inverted crucifix over a painting of the Flinders Ranges by Bannon, and renamed the work The Crop Circle Conspiracy Landscape. In response, Bannon took legal action against Armstrong in the Federal Court of Australia on the grounds of false attribution and defamation. He won an interlocutory injunction against Armstrong and the gallery, but then reached a settlement with the Daubists. An anonymous buyer purchased the work for $650 on the condition that it was returned to the painter. In his fight against the Daubists, Bannon received help and support from the National Association for the Visual Arts (NAVA). This professional group used the controversy to campaign for the reform of copyright law - in particular, the need for a moral rights regime. The artistic controversy over the Daubists was a catalyst for the introduction of the Copyright Amendment (Moral Rights) Act 2000 (Cth) in Australia. It offers an illuminating case study of the operation of copyright law in the visual arts.

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This study empirically examines the motivators that influence a consumer’s intentions to use mobile banking. A web-based survey was employed to collect data from 348 respondents, split across Thailand and Australia. Data were analysed by employing exploratory and confirmatory factor analyses, path and invariance analyses. The findings indicate that for Australian consumers, perceived ease of use, perceived usefulness and perceived risk were the primary determinants of mobile banking adoption. For Thai consumers, the main factors were perceived usefulness, perceived risk and social influence. National culture was found to impact key antecedents that lead to adoption of m-banking. Interestingly, the actual variance explained by this study’s model was higher in Australia than for Thailand, suggesting future research of m-banking adoption in emerging Asian cultures. The findings of this research give banking organisations a foundational model that can be used to support m-banking implementation. This study is perhaps the first to examine and compare the intention to adopt m-banking across Thai and Australian consumers, and responds to calls for additional research that generalises m-banking and m-services acceptance across cultures. This study has proposed and validated additional constructs that are not present in the original SST Intention to Use model.

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The NTRK1 gene (also known as TRKA) encodes a high-affinity receptor for NGF, a neurotrophin involved in nervous system development and myelination. NTRK1 has been implicated in neurological function via links between the T allele at rs6336 (NTRK1-T) and schizophrenia risk. A variant in the neurotrophin gene, BDNF, was previously associated with white matter integrity in young adults, highlighting the importantce of neurotrophins to white matter development. We hypothesized that NTRK1-T would relate to lower fractional anisotropy in healthy adults. We scanned 391 healthy adult human twins and their siblings (mean age: 23.6 ± 2.2 years; 31 NTRK1-T carriers, 360 non-carriers) using 105-gradient diffusion tensor imaging at 4 tesla. We evaluated in brain white matter how NTRK1-T and NTRK1 rs4661063 allele A (rs4661063-A, which is in moderate linkage disequilibrium with rs6336) related to voxelwise fractional anisotropy-acommondiffusion tensor imaging measure of white matter microstructure. We used mixed-model regression to control for family relatedness, age, and sex. The sample was split in half to test reproducibility of results. The false discovery rate method corrected for voxelwise multiple comparisons. NTRK1-T and rs4661063-A correlated with lower white matter fractional anisotropy, independent of age and sex (multiple-comparisons corrected: false discovery rate critical p=0.038 forNTRK1-Tand0.013 for rs4661063-A). In each half-sample, theNTRK1-T effectwasreplicated in the cingulum, corpus callosum, superior and inferior longitudinal fasciculi, inferior fronto-occipital fasciculus, superior corona radiata, and uncinate fasciculus. Our results suggest that NTRK1-T is important for developing white matter microstructure.

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The NTRK3 gene (also known as TRKC) encodes a high affinity receptor for the neurotrophin 3'-nucleotidase (NT3), which is implicated in oligodendrocyte and myelin development. We previously found that white matter integrity in young adults is related to common variants in genes encoding neurotrophins and their receptors. This underscores the importance of neurotrophins for white matter development. NTRK3 variants are putative risk factors for schizophrenia, bipolar disorder, and obsessive-compulsive disorder hoarding, suggesting that some NTRK3 variants may affect the brain.To test this, we scanned 392 healthy adult twins and their siblings (mean age, 23.6. ±. 2.2. years; range: 20-29. years) with 105-gradient 4-Tesla diffusion tensor imaging (DTI). We identified 18 single nucleotide polymorphisms (SNPs) in the NTRK3 gene that have been associated with neuropsychiatric disorders. We used a multi-SNP model, adjusting for family relatedness, age, and sex, to relate these variants to voxelwise fractional anisotropy (FA) - a DTI measure of white matter integrity.FA was optimally predicted (based on the highest false discovery rate critical p), by five SNPs (rs1017412, rs2114252, rs16941261, rs3784406, and rs7176429; overall FDR critical p=. 0.028). Gene effects were widespread and included the corpus callosum genu and inferior longitudinal fasciculus - regions implicated in several neuropsychiatric disorders and previously associated with other neurotrophin-related genetic variants in an overlapping sample of subjects. NTRK3 genetic variants, and neurotrophins more generally, may influence white matter integrity in brain regions implicated in neuropsychiatric disorders.

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We extended genetic linkage analysis - an analysis widely used in quantitative genetics - to 3D images to analyze single gene effects on brain fiber architecture. We collected 4 Tesla diffusion tensor images (DTI) and genotype data from 258 healthy adult twins and their non-twin siblings. After high-dimensional fluid registration, at each voxel we estimated the genetic linkage between the single nucleotide polymorphism (SNP), Val66Met (dbSNP number rs6265), of the BDNF gene (brain-derived neurotrophic factor) with fractional anisotropy (FA) derived from each subject's DTI scan, by fitting structural equation models (SEM) from quantitative genetics. We also examined how image filtering affects the effect sizes for genetic linkage by examining how the overall significance of voxelwise effects varied with respect to full width at half maximum (FWHM) of the Gaussian smoothing applied to the FA images. Raw FA maps with no smoothing yielded the greatest sensitivity to detect gene effects, when corrected for multiple comparisons using the false discovery rate (FDR) procedure. The BDNF polymorphism significantly contributed to the variation in FA in the posterior cingulate gyrus, where it accounted for around 90-95% of the total variance in FA. Our study generated the first maps to visualize the effect of the BDNF gene on brain fiber integrity, suggesting that common genetic variants may strongly determine white matter integrity.

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A major challenge in neuroscience is finding which genes affect brain integrity, connectivity, and intellectual function. Discovering influential genes holds vast promise for neuroscience, but typical genome-wide searches assess approximately one million genetic variants one-by-one, leading to intractable false positive rates, even with vast samples of subjects. Even more intractable is the question of which genes interact and how they work together to affect brain connectivity. Here, we report a novel approach that discovers which genes contribute to brain wiring and fiber integrity at all pairs of points in a brain scan. We studied genetic correlations between thousands of points in human brain images from 472 twins and their nontwin siblings (mean age: 23.7 2.1 SD years; 193 male/279 female).Wecombined clustering with genome-wide scanning to find brain systems withcommongenetic determination.Wethen filtered the image in a new way to boost power to find causal genes. Using network analysis, we found a network of genes that affect brain wiring in healthy young adults. Our new strategy makes it computationally more tractable to discover genes that affect brain integrity. The gene network showed small-world and scale-free topologies, suggesting efficiency in genetic interactions and resilience to network disruption. Genetic variants at hubs of the network influence intellectual performance by modulating associations between performance intelligence quotient and the integrity of major white matter tracts, such as the callosal genu and splenium, cingulum, optic radiations, and the superior longitudinal fasciculus.

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In the present study, items pre-exposed in a familiarization series were included in a list discrimination task to manipulate memory strength. At test, participants were required to discriminate strong targets and strong lures from weak targets and new lures. This resulted in a concordant pattern of increased "old" responses to strong targets and lures. Model estimates attributed this pattern to either equivalent increases in memory strength across the two types of items (unequal variance signal detection model) or equivalent increases in both familiarity and recollection (dual process signal detection [DPSD] model). Hippocampal activity associated with strong targets and lures showed equivalent increases compared with missed items. This remained the case when analyses were restricted to high-confidence responses considered by the DPSD model to reflect predominantly recollection. A similar pattern of activity was observed in parahippocampal cortex for high-confidence responses. The present results are incompatible with "noncriterial" or "false" recollection being reflected solely in inflated DPSD familiarity estimates and support a positive correlation between hippocampal activity and memory strength irrespective of the accuracy of list discrimination, consistent with the unequal variance signal detection model account.

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Modern non-invasive brain imaging technologies, such as diffusion weighted magnetic resonance imaging (DWI), enable the mapping of neural fiber tracts in the white matter, providing a basis to reconstruct a detailed map of brain structural connectivity networks. Brain connectivity networks differ from random networks in their topology, which can be measured using small worldness, modularity, and high-degree nodes (hubs). Still, little is known about how individual differences in structural brain network properties relate to age, sex, or genetic differences. Recently, some groups have reported brain network biomarkers that enable differentiation among individuals, pairs of individuals, and groups of individuals. In addition to studying new topological features, here we provide a unifying general method to investigate topological brain networks and connectivity differences between individuals, pairs of individuals, and groups of individuals at several levels of the data hierarchy, while appropriately controlling false discovery rate (FDR) errors. We apply our new method to a large dataset of high quality brain connectivity networks obtained from High Angular Resolution Diffusion Imaging (HARDI) tractography in 303 young adult twins, siblings, and unrelated people. Our proposed approach can accurately classify brain connectivity networks based on sex (93% accuracy) and kinship (88.5% accuracy). We find statistically significant differences associated with sex and kinship both in the brain connectivity networks and in derived topological metrics, such as the clustering coefficient and the communicability matrix.