Characterization of Alternaria alternata and Alternaria scrophulariae Brown Spot in Colombian quinoa (Chenopodium quinoa). [PDF]
J Fungi (Basel), 2023 Fonseca-Guerra IR +2 more
europepmc +1 more source
Changes in fungal taxonomy: mycological rationale and clinical implications. [PDF]
Clin Microbiol Rev, 2023 Borman AM, Johnson EM.
europepmc +1 more source
A RARE MITOSPORIC FUNGI FROM GHATANJI (M.S.) INDIA
, 2014 M. A. Shahezad M. A. Shahezad
openalex +1 more source
LIST OF FRESHWATER MITOSPORIC FUNGI OF MADHYA PRADESH
, 2016 Suhas A. Chaudhari V. R. Patil and B. D. Borse Suhas A. Chaudhari V. R. Patil and B. D. Borse
openalex +1 more source
Recent Developments in the Application of Inorganic Nanomaterials and Nanosystems for the Protection of Cultural Heritage Organic Artifacts. [PDF]
Nanomaterials (Basel), 2022 Fistos T, Fierascu I, Fierascu RC.
europepmc +1 more source
Contribución al estudio de la flora micológica del Desert de les Palmes (Castelló) [PDF]
, 2007 Contribución al estudio de la flora micológica del Desert de les Palmes (Castelló). En esta primera aportación se citan 95 especies, 2 formas y 5 variedades de hongos que fructifican en el Desierto de las Palmas, Castellón, España: 2 Mixomicetes, 3 ...
Miguel Torrejón Herrero
core +3 more sources
The genus Rachicladosporium: introducing new species from sooty mould communities and excluding cold adapted species. [PDF]
Sci Rep, 2023 Piątek M +3 more
europepmc +1 more source
Exploring the mycobiota of bromeliads phytotelmata in Brazilian Campos Rupestres. [PDF]
Braz J Microbiol, 2023 Dos Santos VL +6 more
europepmc +1 more source
New records of lichens and lichenicolous fungi from the Ural Mountains, Russia [PDF]
, 2011 A total of 53 taxa of lichens and lichenicolous fungi are first reported from the Ural Mountains (Republic Bashkortostan, Russia). Nine lichen species, Anema decipiens, Bagliettoa parmigera, Diplotomma hedinii, Heteroplacidium compactum, H. zamenhofianum,
Urbanavichene, Irina +1 more
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No Train, all Gain: Self-Supervised Gradients Improve Deep Frozen Representations [PDF]
arXivThis paper introduces FUNGI, Features from UNsupervised GradIents, a method to enhance the features of transformer encoders by leveraging self-supervised gradients. Our method is simple: given any pretrained model, we first compute gradients from various self-supervised objectives for each input.
arxiv