Fractional signal processing: scale conversion

In Proceedings of the “ECCTD '01 - European Conference on Circuit Theory and Design, Espoo, Finland, August 2001Scale conversion of discrete-time signals are studied taking as base the fractional discrete-time system theory. Some simulation results to illustrate the behaviour of the algorithms will be presented. A new algorithm for performing the zoom transform is also described

Fractional discrete-time signal processing: scale conversion and linear prediction

Nonlinear Dynamics, Vol. 29A generalisation of the linear prediction for fractional steps is reviewed, widening well-known concepts and results. This prediction is used to derive a causal interpolation algorithm. A reconstruction algorithm for the situation where averages are observed is also presented. Scale conversion of discrete-time signals is studied taking as base the fractional discrete-time system theory. Some simulation results to illustrate the behaviour of the algorithms will be presented. A new algorithm for performing the zoom transform is also described

Primeiro relato e colonização diferencial de espécies de Passiflora pelo biótipo B de Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae) no Brasil

This note is the first report of Bemisia tabaci (Gennadius) biotype B colonizing passionvine in Brazil. We examined the colonization of nine Passiflora species by a wild B type population under greenhouse conditions. P. amethystina Mikan was the most preferred species for oviposition and colonization, whereas P. suberosa L., P. coriacea Juss. and two commercially cultivated species, P. alata Curtis and P. edulis Sims f. flavicarpa Degener, were mostly uncolonised. P. morifolia Mast., P. cincinnata Mast., P. foetida L. and P. caerulea L. showed intermediate levels of colonization. Such differential colonization might suggest some degree of resistance by certain Passiflora species or oviposition preference by B. tabaci.Esse trabalho descreve pela primeira vez a ocorrência do aleirodídeo Bemisia tabaci (Gennadius) biótipo B colonizando maracujazeiros no Brasil. Também foi examinada a colonização de nove espécies de Passiflora pelo inseto em condições de telado. P. amethystina Mikan foi a espécie de maior preferência para oviposição e colonização, enquanto P. suberosa L., P. coriacea Juss. e duas espécies cultivadas comercialmente, P. alata Curtis e P. edulis Sims f. flavicarpa Degener, foram pouco colonizadas pelo aleirodídeo. P. morifolia Mast., P. cincinnata Mast., P. foetida L. e P. caerulea L. exibiram níveis intermediários de colonização. Esses resultados sugerem que certas espécies de Passiflora exibem diferentes graus de resistência à colonização ou preferência para oviposição de B. tabaci biótipo B

Integration of magnetoresistive biochips on a CMOS circuit

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One sixth of Amazonian tree diversity is dependent on river floodplains

Amazonia's floodplain system is the largest and most biodiverse on Earth. Although forests are crucial to the ecological integrity of floodplains, our understanding of their species composition and how this may differ from surrounding forest types is still far too limited, particularly as changing inundation regimes begin to reshape floodplain tree communities and the critical ecosystem functions they underpin. Here we address this gap by taking a spatially explicit look at Amazonia-wide patterns of tree-species turnover and ecological specialization of the region's floodplain forests. We show that the majority of Amazonian tree species can inhabit floodplains, and about a sixth of Amazonian tree diversity is ecologically specialized on floodplains. The degree of specialization in floodplain communities is driven by regional flood patterns, with the most compositionally differentiated floodplain forests located centrally within the fluvial network and contingent on the most extraordinary flood magnitudes regionally. Our results provide a spatially explicit view of ecological specialization of floodplain forest communities and expose the need for whole-basin hydrological integrity to protect the Amazon's tree diversity and its function.Naturali

Co-limitation towards lower latitudes shapes global forest diversity gradients

The latitudinal diversity gradient (LDG) is one of the most recognized global patterns of species richness exhibited across a wide range of taxa. Numerous hypotheses have been proposed in the past two centuries to explain LDG, but rigorous tests of the drivers of LDGs have been limited by a lack of high-quality global species richness data. Here we produce a high-resolution (0.025° × 0.025°) map of local tree species richness using a global forest inventory database with individual tree information and local biophysical characteristics from ~1.3 million sample plots. We then quantify drivers of local tree species richness patterns across latitudes. Generally, annual mean temperature was a dominant predictor of tree species richness, which is most consistent with the metabolic theory of biodiversity (MTB). However, MTB underestimated LDG in the tropics, where high species richness was also moderated by topographic, soil and anthropogenic factors operating at local scales. Given that local landscape variables operate synergistically with bioclimatic factors in shaping the global LDG pattern, we suggest that MTB be extended to account for co-limitation by subordinate drivers

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time, and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space. While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes, vast areas of the tropics remain understudied. In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity, but it remains among the least known forests in America and is often underrepresented in biodiversity databases. To worsen this situation, human-induced modifications 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, 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