Theoretical results on a weightless neural classifier and application to computational linguistics

WiSARD é um classificador n-upla, historicamente usado em tarefas de reconhecimento de padrões em imagens em preto e branco. Infelizmente, não era comum que este fosse usado em outras tarefas, devido á sua incapacidade de arcar com grandes volumes de dados por ser sensível ao conteúdo aprendido. Recentemente, a técnica de bleaching foi concebida como uma melhoria à arquitetura do classificador n-upla, como um meio de coibir a sensibilidade da WiSARD. Desde então, houve um aumento na gama de aplicações construídas com este sistema de aprendizado. Pelo uso frequente de corpora bastante grandes, a etiquetação gramatical multilíngue encaixa-se neste grupo de aplicações. Esta tese aprimora o mWANN-Tagger, um etiquetador gramatical sem peso proposto em 2012. Este texto mostra que a pesquisa em etiquetação multilíngue com WiSARD foi intensificada através do uso de linguística quantitativa e que uma configuração de parâmetros universal foi encontrada para o mWANN-Tagger. Análises e experimentos com as bases da Universal Dependencies (UD) mostram que o mWANN-Tagger tem potencial para superar os etiquetadores do estado da arte dada uma melhor representação de palavra. Esta tese também almeja avaliar as vantagens do bleaching em relação ao modelo tradicional através do arcabouço teórico da teoria VC. As dimensões VC destes foram calculadas, atestando-se que um classificador n-upla, seja WiSARD ou com bleaching, que possua N memórias endereçadas por n-uplas binárias tem uma dimensão VC de exatamente N (2n − 1) + 1. Um paralelo foi então estabelecido entre ambos os modelos, onde deduziu-se que a técnica de bleaching é uma melhoria ao método n-upla que não causa prejuízos à sua capacidade de aprendizado.WiSARD é um classificador n-upla, historicamente usado em tarefas de reconhecimento de padrões em imagens em preto e branco. Infelizmente, não era comum que este fosse usado em outras tarefas, devido á sua incapacidade de arcar com grandes volumes de dados por ser sensível ao conteúdo aprendido. Recentemente, a técnica de bleaching foi concebida como uma melhoria à arquitetura do classificador n-upla, como um meio de coibir a sensibilidade da WiSARD. Desde então, houve um aumento na gama de aplicações construídas com este sistema de aprendizado. Pelo uso frequente de corpora bastante grandes, a etiquetação gramatical multilíngue encaixa-se neste grupo de aplicações. Esta tese aprimora o mWANN-Tagger, um etiquetador gramatical sem peso proposto em 2012. Este texto mostra que a pesquisa em etiquetação multilíngue com WiSARD foi intensificada através do uso de linguística quantitativa e que uma configuração de parâmetros universal foi encontrada para o mWANN-Tagger. Análises e experimentos com as bases da Universal Dependencies (UD) mostram que o mWANN-Tagger tem potencial para superar os etiquetadores do estado da arte dada uma melhor representação de palavra. Esta tese também almeja avaliar as vantagens do bleaching em relação ao modelo tradicional através do arcabouço teórico da teoria VC. As dimensões VC destes foram calculadas, atestando-se que um classificador n-upla, seja WiSARD ou com bleaching, que possua N memórias endereçadas por n-uplas binárias tem uma dimensão VC de exatamente N (2n − 1) + 1. Um paralelo foi então estabelecido entre ambos os modelos, onde deduziu-se que a técnica de bleaching é uma melhoria ao método n-upla que não causa prejuízos à sua capacidade de aprendizado

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Neotropical freshwater fisheries : A dataset of occurrence and abundance of freshwater fishes in the Neotropics

The Neotropical region hosts 4225 freshwater fish species, ranking first among the world's most diverse regions for freshwater fishes. Our NEOTROPICAL FRESHWATER FISHES data set is the first to produce a large-scale Neotropical freshwater fish inventory, covering the entire Neotropical region from Mexico and the Caribbean in the north to the southern limits in Argentina, Paraguay, Chile, and Uruguay. We compiled 185,787 distribution records, with unique georeferenced coordinates, for the 4225 species, represented by occurrence and abundance data. The number of species for the most numerous orders are as follows: Characiformes (1289), Siluriformes (1384), Cichliformes (354), Cyprinodontiformes (245), and Gymnotiformes (135). The most recorded species was the characid Astyanax fasciatus (4696 records). We registered 116,802 distribution records for native species, compared to 1802 distribution records for nonnative species. The main aim of the NEOTROPICAL FRESHWATER FISHES data set was to make these occurrence and abundance data accessible for international researchers to develop ecological and macroecological studies, from local to regional scales, with focal fish species, families, or orders. We anticipate that the NEOTROPICAL FRESHWATER FISHES data set will be valuable for studies on a wide range of ecological processes, such as trophic cascades, fishery pressure, the effects of habitat loss and fragmentation, and the impacts of species invasion and climate change. There are no copyright restrictions on the data, and please cite this data paper when using the data in publications

Measurement of the Branching Fraction of B0→J/ψπ0B^{0} \rightarrow J/\psi \pi^{0} Decays

International audienceThe ratio of branching fractions between $B^{0} \rightarrow J/\psi \pi^{0}$ and $B^{+} \rightarrow J/\psi K^{*+}$ decays is measured with proton-proton collision data collected by the LHCb experiment, corresponding to an integrated luminosity of 9 fb$^{-1}$. The measured value is $\frac{\mathcal{B}_{B^{0} \rightarrow J/\psi \pi^{0}}}{\mathcal{B}_{B^{+} \rightarrow J/\psi K^{*+}}} = (1.153 \pm 0.053 \pm 0.048 ) \times 10^{-2}$, where the first uncertainty is statistical and the second is systematic. The branching fraction for $B^{0} \rightarrow J/\psi \pi^{0}$ decays is determined using the branching fraction of the normalisation channel, resulting in $\mathcal{B}_{B^{0} \rightarrow J/\psi \pi^{0}} = (1.670 \pm 0.077 \pm 0.069 \pm 0.095) \times 10^{-5}$, where the last uncertainty corresponds to that of the external input. This result is consistent with the current world average value and competitive with the most precise single measurement to date

First observation of Λb0→Σc(∗)++D(∗)−K−\Lambda_{b}^{0} \rightarrow \Sigma_c^{(*)++} D^{(*)-} K^{-} decays

International audienceThe four decays, $\Lambda_{b}^{0} \rightarrow \Sigma_c^{(*)++} D^{(*)-} K^{-}$, are observed for the first time using proton-proton collision data collected with the LHCb detector at a centre-of-mass energy of $13\,\rm{TeV}$, corresponding to an integrated luminosity of $6\,\rm{fb}^{-1}$. By considering the $\Lambda_b^0 \rightarrow \Lambda_c^{+} \overline{D}^0 K^{-}$ decay as reference channel, the following branching fraction ratios are measured to be, $$\frac{\cal{B} (\Lambda_{b}^{0} \rightarrow \Sigma_{c}^{++} \rm{D}^{-} {K}^{-})}{\cal{B}(\Lambda_{b}^{0} \rightarrow \Lambda_c^{+} \rm \overline{D}^0 {K}^{-})} = {0.282}\pm{0.016}\pm{0.016}\pm{0.005}, \frac{\cal{B}(\Lambda_{b}^{0} \rightarrow \Sigma_{c}^{*++} \rm {D}^{-} {K}^{-})}{\cal{B}(\Lambda_{b}^{0} \rightarrow \Sigma_c^{++} \rm {D}^{-} {K}^{-})} = {0.460}\pm{0.052}\pm{0.028}, \frac{\cal{B}(\Lambda_{b}^{0} \rightarrow \Sigma_{c}^{++} \rm {D}^{*-} {K}^{-})}{\cal{B}(\Lambda_{b}^{0} \rightarrow \Sigma_c^{++} \rm {D}^{-} {K}^{-})} = {2.261}\pm{0.202}\pm{0.129}\pm{0.046}, \frac{\cal{B}(\Lambda_{b}^{0} \rightarrow \Sigma_{c}^{*++} \rm D^{*-} K^{-})}{\cal{B}(\Lambda_{b}^{0} \rightarrow \Sigma_c^{++} \rm D^{-} K^{-})} = {0.896}\pm{0.137}\pm{0.066}\pm{0.018},$$ where the first uncertainties are statistical, the second are systematic, and the third are due to uncertainties in the branching fractions of intermediate particle decays. These initial observations mark the beginning of pentaquark searches in these modes, with more data set to become available following the LHCb upgrade

Search for the Bs0→μ+μ−γB_s^0 \rightarrow \mu^+\mu^-\gamma decay

International audienceA search for the fully reconstructed $B_s^0 \rightarrow \mu^+\mu^-\gamma$ decay is performed at the LHCb experiment using proton-proton collisions at $\sqrt{s}=13$ TeV corresponding to an integrated luminosity of $5.4\,\mathrm{fb^{-1}}$. No significant signal is found and upper limits on the branching fraction in intervals of the dimuon mass are set \begin{align} {\cal B}(B_s^0 \rightarrow \mu^+\mu^-\gamma) < 4.2\times10^{-8},~&m(\mu\mu)\in[2m_\mu,~1.70]\,\mathrm{GeV/c^2} ,\nonumber {\cal B}(B_s^0 \rightarrow \mu^+\mu^-\gamma) < 7.7\times10^{-8},~&m(\mu\mu)\in[1.70,~2.88]\,\mathrm{GeV/c^2},\nonumber {\cal B}(B_s^0 \rightarrow \mu^+\mu^-\gamma) < 4.2\times10^{-8},~&m(\mu\mu)\in[3.92 ,~m_{B_s^0}]\,\mathrm{GeV/c^2},\nonumber \end{align} at 95% confidence level. Additionally, upper limits are set on the branching fraction in the $[2m_\mu,~1.70]\,\mathrm{GeV/c^2}$ dimuon mass region excluding the contribution from the intermediate $\phi(1020)$ meson, and in the region combining all dimuon-mass intervals