Arpinia fusispora Hohmeyer,un inusual miembro de la familia Pyronemataceae Corda, hallado en la provincia de León

Arpinia fusispora Hohmeyer, un inusual membre de la família Pyronemataceae Corda, trobat a la província de León (Espanya). Oferim en aquest treball la descripció i l'iconografia basades en l'estudi la nostra recol·lecció d'aquesta espècie rara de l'ordre de les pezizals. També assenyalem la preferència d'aquesta espècie per sòls forestals eutrofitzats.Arpinia fusispora Hohmeyer, un inusual miembro de la familia Pyronemataceae Corda, hallado en la provincia de León. En esta breve nota damos cuenta de la recolección, en la montaña de la provincia de León, de Arpinia fusispora Hohmeyer, un raro pezizal escasamente citado en el continente europeo. Señalamos también la posible preferencia de este taxon por suelos forestales eutrofizados.Arpinia fusispora Hohmeyer, an unusual member of the family Pyronemataceae Corda, recorded at the province of León (Spain). This paper includes an original description and iconography of Arpinia fusispora Hohmeyer, a rare european ascomycete species of the order Pezizales. The spanish collection seems to point a preference for eutrophic forest soil

Arpinia fusispora Hohmeyer,un inusual miembro de la familia Pyronemataceae Corda, hallado en la provincia de León

Arpinia fusispora Hohmeyer, un inusual membre de la família Pyronemataceae Corda, trobat a la província de León (Espanya). Oferim en aquest treball la descripció i l'iconografia basades en l'estudi la nostra recol·lecció d'aquesta espècie rara de l'ordre de les pezizals. També assenyalem la preferència d'aquesta espècie per sòls forestals eutrofitzats.Arpinia fusispora Hohmeyer, an unusual member of the family Pyronemataceae Corda, recorded at the province of León (Spain). This paper includes an original description and iconography of Arpinia fusispora Hohmeyer, a rare european ascomycete species of the order Pezizales. The spanish collection seems to point a preference for eutrophic forest soil.Arpinia fusispora Hohmeyer, un inusual miembro de la familia Pyronemataceae Corda, hallado en la provincia de León. En esta breve nota damos cuenta de la recolección, en la montaña de la provincia de León, de Arpinia fusispora Hohmeyer, un raro pezizal escasamente citado en el continente europeo. Señalamos también la posible preferencia de este taxon por suelos forestales eutrofizados

Marcelleina parvispora (Ascomycota, Pezizales), a new Marcelleina species from Catalonia (Spain)

Marcelleina parvispora (Ascomycota, Pezizales), a new Marcelleina species from Catalonia (Spain). Marcelleina parvispora sp. nov. (Pezizales, Ascomycota) is described as a new ascomycete species from Catalonia (NE of continental Spain). This first Spanish collection belongs to a new, apparently saprotrophic species that grows in Eucalyptus sp. plantations. A comparison is made with related European species of MarcelleinaMarcelleina parvispora sp. nov. (Pezizales, Ascomycota), una nueva especie de ascomicete, aparentemente saprobia en plantaciones de Eucalyptus sp., procedente de Cataluña (NE de España continental). La descripción se acompaña de fotografías macro y microscópicas de sus singulares caracteres y de su comparación con algunas especies europeas próximas

Primer registro ibérico de un hongo mediterráneo escasamente citado: Pseudoomphalina umbrinopurpurascens (Maire) Contu

Primera citació ibèrica d'un fong mediterrani poc citat: Pseudoomphalina umbrinopurpurascens (Maire) Contu Troballa a Catalunya de Pseudoomphalina umbrinopurpurascens (Maire) Contu, un estrany fong meridional del qual només existeixen cites prèvies en el nord d'Àfrica i sud d'Itàlia.First Iberian record of a scarcely cited mediterranean fungus: Pseudoomphalina umbrinopurpurascens (Maire) Contu. Finding in Catalonia of Pseudoomphalina umbrinopurpurascens (Maire) Contu, a rare southern fungus rarely cited in the world, of which there are only previous citations in North Africa and southern Italy.Primer registro ibérico de un hongo mediterráneo escasamente citado: Pseudoomphalina umbrinopurpurascens (Maire) Contu. Hallazgo en Cataluña de Pseudoomphalina umbrinopurpurascens Maire) Contu, un raro hongo meridional del que sólo existen citas previas en el norte de África y sur de Italia

Pixel Features for Self-organizing Map Based Detection of Foreground Objects in Dynamic Environments

Among current foreground detection algorithms for video sequences, methods based on self-organizing maps are obtaining a greater relevance. In this work we propose a probabilistic self-organising map based model, which uses a uniform distribution to represent the foreground. A suitable set of characteristic pixel features is chosen to train the probabilistic model. Our approach has been compared to some competing methods on a test set of benchmark videos, with favorable results.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Super-resolution of 3D Magnetic Resonance Images by Random Shifting and Convolutional Neural Networks

Enhancing resolution is a permanent goal in magnetic resonance (MR) imaging, in order to keep improving diagnostic capability and registration methods. Super-resolution (SR) techniques are applied at the postprocessing stage, and their use and development have progressively increased during the last years. In particular, example-based methods have been mostly proposed in recent state-of-the-art works. In this paper, a combination of a deep-learning SR system and a random shifting technique to improve the quality of MR images is proposed, implemented and tested. The model was compared to four competitors: cubic spline interpolation, non-local means upsampling, low-rank total variation and a three-dimensional convolutional neural network trained with patches of HR brain images (SRCNN3D). The newly proposed method showed better results in Peak Signal-to-Noise Ratio, Structural Similarity index, and Bhattacharyya coefficient. Computation times were at the same level as those of these up-to-date methods. When applied to downsampled MR structural T1 images, the new method also yielded better qualitative results, both in the restored images and in the images of residuals.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Ruhlandiella reticulata comb. nov. y Ruhlandiella truncata comb. nov. (Ascomycota, pezizales). Nuevas combinaciones para dos raras especies semihipogeas, eucaliptícolas y pirófilas de origen austral: Muciturbo reticulatus y Muciturbo truncatus

Ruhlandiella truncata and Ruhlandiella reticulata, new combinations for Muciturbo truncatus P.H.B. Talbot and Muciturbo reticulatus P.H.B. Talbot, two rare australasian semihypogeous, carbonicolous and eucalypticolous fungi recorded in Valencia and Asturias (Spain).El presente trabajo da cuenta de la recolección en Valencia y Asturias de dos raras especies semihipogeas australes, pirófilas y eucaliptícolas: Ruhlandiella truncata y Ruhlandiella reticulata, nuevas combinaciones para Muciturbo truncatus P.H.B. Talbot y Muciturbo reticulatus P.H.B. Talbot

Motion Detection by Microcontroller for Panning Cameras

Motion detection is the first essential process in the extraction of information regarding moving objects. The approaches based on background difference are the most used with fixed cameras to perform motion detection, because of the high quality of the achieved segmentation. However, real time requirements and high costs prevent most of the algorithms proposed in literature to exploit the background difference with panning cameras in real world applications. This paper presents a new algorithm to detect moving objects within a scene acquired by panning cameras. The algorithm for motion detection is implemented on a Raspberry Pi microcontroller, which enables the design and implementation of a low-cost monitoring system.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Skin lesion classification by ensembles of deep convolutional networks and regularly spaced shifting

Skin lesions are caused due to multiple factors, like allergies, infections, exposition to the sun, etc. These skin diseases have become a challenge in medical diagnosis due to visual similarities, where image classification is an essential task to achieve an adequate diagnostic of different lesions. Melanoma is one of the best-known types of skin lesions due to the vast majority of skin cancer deaths. In this work, we propose an ensemble of improved convolutional neural networks combined with a test-time regularly spaced shifting technique for skin lesion classification. The shifting technique builds several versions of the test input image, which are shifted by displacement vectors that lie on a regular lattice in the plane of possible shifts. These shifted versions of the test image are subsequently passed on to each of the classifiers of an ensemble. Finally, all the outputs from the classifiers are combined to yield the final result. Experiment results show a significant improvement on the well-known HAM10000 dataset in terms of accuracy and Fscore. In particular, it is demonstrated that our combination of ensembles with test-time regularly spaced shifting yields better performance than any of the two methods when applied alone.This work is partially supported by the Ministry of Science, Innovation and Universities of Spain under grant RTI2018-094645-B-I00, project name Automated detection with low-cost hardware of unusual activities in video sequences. It is also partially supported by the Autonomous Government of Andalusia (Spain) under project UMA18-FEDERJA-084, project name Detection of anomalous behavior agents by deep learning in low-cost video surveillance intelligent systems. All of them include funds from the European Regional Development Fund (ERDF). It is also partially supported by the University of Malaga (Spain) under grants B1-2019_02, project name Self-Organizing Neural Systems for Non-Stationary Environments, and B1-2019_01, project name Anomaly detection on roads by moving cameras. The authors thankfully acknowledge the computer resources, technical expertise and assistance provided by the SCBI (Supercomputing and Bioinformatics) center of the University of Málaga. They also gratefully acknowledge the support of NVIDIA Corporation with the donation of two Titan X GPUs. The authors acknowledge the funding from the Universidad de Málaga. Funding for open access charge: Universidad de Málaga / CBUA

Color Space Selection for Self-Organizing Map Based Foreground Detection in Video Sequences

The selection of the best color space is a fundamental task in detecting foreground objects on scenes. In many situations, especially on dynamic backgrounds, neither grayscale nor RGB color spaces represent the best solution to detect foreground objects. Other standard color spaces, such as YCbCr or HSV, have been proposed for background modeling in the literature; although the best results have been achieved using diverse color spaces according to the application, scene, algorithm, etc. In this work, a color space and color component weighting selection process is proposed to detect foreground objects in video sequences using self-organizing maps. Experimental results are also provided using well known benchmark videos.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech