Results 111 to 120 of about 550,997 (415)
American Journal of Botany, EarlyView.Abstract Premise Many angiosperms have evolved specialized systems that promote pollination by specific taxa. Therefore, plant distributions may be limited by the local abundance of their specialist pollinators. In eastern North America, Lobelia cardinalis is thought to be pollinated solely by Archilochus colubris, the only hummingbird species found in
Matthew L. Coffey, Andrew M. Simons
wiley +1 more source
Applying pollen DNA metabarcoding to the study of plant–pollinator interactions
Applications in Plant Sciences, 2017 Premise of the study: To study pollination networks in a changing environment, we need accurate, high-throughput methods. Previous studies have shown that more highly resolved networks can be constructed by studying pollen loads taken from bees, relative
K. Bell +7 more
semanticscholar +1 more source
Expanding the Tyrosine Kinase Domain of CSF1R? A Case Report From an Adult‐Onset Leukoencephalopathy
American Journal of Medical Genetics Part A, EarlyView.ABSTRACT Adult‐onset leukoencephalopathy with axonal spheroids and pigmented glia (ALSP), also termed hereditary diffuse leukoencephalopathy with spheroids‐1 (HDLS1), results from mutations in the CSF1R gene and leads to progressive leukoencephalopathy.
Piervito Lopriore +11 more
wiley +1 more source
Pollen13K: A Large Scale Microscope Pollen Grain Image Dataset [PDF]
arXiv, 2020 Pollen grain classification has a remarkable role in many fields from medicine to biology and agronomy. Indeed, automatic pollen grain classification is an important task for all related applications and areas. This work presents the first large-scale pollen grain image dataset, including more than 13 thousands objects.
arxiv
Robust Pollen Imagery Classification with Generative Modeling and Mixup Training [PDF]
arXiv, 2021 Deep learning approaches have shown great success in image classification tasks and can aid greatly towards the fast and reliable classification of pollen grain aerial imagery. However, often-times deep learning methods in the setting of natural images can suffer generalization problems and yield poor performance on unseen test distribution.
arxiv
PLoS ONE, 2017 The least understood aspects of the nutritional needs of bees are the elemental composition of pollen and the bees’ need for a stoichiometrically balanced diet containing the required proportions of nutrients. Reduced plant diversity has been proposed as
Michał Filipiak +6 more
semanticscholar +1 more source
Effects of post-translational modifications catalysed by pollen transglutaminase on the functional properties of microtubules and actin filaments [PDF]
, 2009 TGases (transglutaminases) are a class of calcium-dependent enzymes that catalyse the interactions between acyl acceptor glutamyl residues and amine donors, potentially making crosslinks between proteins.
Bonner, PLR +4 more
core
Angewandte Chemie International Edition, Accepted Article.Global demand to reduce polymer waste and microplastics pollution has increased in recent years, prompting further research, development, and wider use of biodegradable and biobased polymers (BBPs). BBPs have emerged as promising alternatives to conventional plastics, with the potential to mitigate the environmental burdens of persistent plastic waste.
Sara T. R. Velasquez +5 more
wiley +1 more source
Pollen Histochemistry and Pollen : Ovule Ratios in Zingiberaceae [PDF]
Annals of Botany, 2004 Pollen grains of 37 species from 11 genera in the family Zingiberaceae were examined to assess qualitatively starch or lipid contents; the pollen grain and ovule numbers per flower and pollen : ovule ratios were also counted and calculated. Pollen : ovule ratios were studied to reveal patterns of variation in the Zingiberaceae.Freshly open flowers with
Zhongyi Chen +2 more
openaire +3 more sources
Unsupervised Representations of Pollen in Bright-Field Microscopy [PDF]
arXiv, 2019 We present the first unsupervised deep learning method for pollen analysis using bright-field microscopy. Using a modest dataset of 650 images of pollen grains collected from honey, we achieve family level identification of pollen. We embed images of pollen grains into a low-dimensional latent space and compare Euclidean and Riemannian metrics on these
arxiv