Blind hyperspectral unmixing using an Extended Linear Mixing Model to address spectral variability

International audienceThe Linear Mixing Model is often used to perform Hyperspec-tral Unmixing because of its simplicity, but it assumes that a single spectral signature can be completely representative of an endmember. However, in many scenarios, this assumption does not hold since many factors such as illumination conditions and intrinsic variability of the endmembers have consequences on the spectral signatures of the materials. In this paper, we propose a simple yet flexible algorithm to unmix hyperspectral data using a recently proposed Extended Linear Mixing Model. This model allows a pixelwise variation of the endmembers, which leads to consider scaled versions of reference endmember spectra. The results on synthetic data show that the proposed technique outperforms other methods aimed at tackling spectral variability, and provides an accurate estimation of endmember variability along the observed scene thanks to the scaling factors estimation, provided the abundance of the corresponding material is sufficient

From local to global unmixing of hyperspectral images to reveal spectral variability

International audienceThe linear mixing model is widely assumed when unmixing hyperspectral images, but it cannot account for endmembers spectral variability. Thus, several workarounds have arisen in the hyperspectral unmixing literature, such as the extended linear mixing model (ELMM), which authorizes endmembers to vary pixelwise according to scaling factors, or local spectral unmixing (LSU) where the unmixing process is conducted locally within the image. In the latter case however, results are difficult to interpret at the whole image scale. In this work, we propose to analyze the local results of LSU within the ELMM framework, and show that it not only allows to reconstruct global endmembers and fractional abundances from the local ones, but it also gives access to the scaling factors advocated by the ELMM. Results obtained on a real hyperspectral image confirm the soundness of the proposed methodology

Blind hyperspectral unmixing using an Extended Linear Mixing Model to address spectral variability

International audienceSpectral Unmixing is one of the main research topics in hyperspectral imaging. It can be formulated as a source separation problem whose goal is to recover the spectral signatures of the materials present in the observed scene (called endmembers) as well as their relative proportions (called fractional abundances), and this for every pixel in the image. A Linear Mixture Model is often used for its simplicity and ease of use but it implicitly assumes that a single spectrum can be completely representative of a material. However, in many scenarios, this assumption does not hold since many factors, such as illumination conditions and intrinsic variability of the endmembers, induce modifications on the spectral signatures of the materials. In this paper, we propose an algorithm to unmix hyperspectral data using a recently proposed Extended Linear Mixing Model. The proposed approach allows a pixelwise spatially coherent local variation of the endmembers, leading to scaled versions of reference endmembers. We also show that the classic nonnegative least squares, as well as other approaches to tackle spectral variability can be interpreted in the framework of this model. The results of the proposed algorithm on two different synthetic datasets, including one simulating the effect of topography on the measured reflectance through physical modelling, and on two real datasets, show that the proposed technique outperforms other methods aimed at addressing spectral variability, and can provide an accurate estimation of endmember variability along the scene thanks to the scaling factors estimation

Las matemáticas en la investigación desarrollada desde la Escuela Politécnica de Cuenca

Con este capítulo se pretende hacer un recorrido por las líneas investigadoras que han llevado a cabo los profesores que actualmente desempeñan su labor docente e investigadora en el Departamento de Matemáticas de la Escuela Politécnica de Cuenca. La investigación ha ido cambiando en función de los profesores implicados en el departamento, por lo que entendemos que esta no sigue una única línea de trabajo pero creemos que es de calidad. Así pues, se expone brevemente la investigación realizada por los profesores Dr. Miguel Ángel López Guerrero y Dra. Raquel Martínez Lucas donde se comentan las líneas de investigación desarrolladas en sus respectivas tesis doctorales, la colaboración en diferentes proyectos de investigación y las colaboraciones con otros profesores de la escuela. También se presentan algunos de los artículos más relevantes publicados por estos profesore

Action semantics at the bottom of the brain: Insights from dysplastic cerebellar gangliocytoma

Recent embodied cognition research shows that access to action verbs in shallow-processing tasks becomes selectively compromised upon atrophy of the cerebellum, a critical motor region. Here we assessed whether cerebellar damage also disturbs explicit semantic processing of action pictures and its integration with ongoing motor responses. We evaluated a cognitively preserved 33-year-old man with severe dysplastic cerebellar gangliocytoma (Lhermitte-Duclos disease), encompassing most of the right cerebellum and the posterior part of the left cerebellum. The patient and eight healthy controls completed two semantic association tasks (involving pictures of objects and actions, respectively) that required motor responses. Accuracy results via Crawford's modified t-tests revealed that the patient was selectively impaired in action association. Moreover, reaction-time analysis through Crawford's Revised Standardized Difference Test showed that, while processing of action concepts involved slower manual responses in controls, no such effect was observed in the patient, suggesting that motor-semantic integration dynamics may be compromised following cerebellar damage. Notably, a Bayesian Test for a Deficit allowing for Covariates revealed that these patterns remained after covarying for executive performance, indicating that they were not secondary to extra-linguistic impairments. Taken together, our results extend incipient findings on the embodied functions of the cerebellum, offering unprecedented evidence of its crucial role in processing non-verbal action meanings and integrating them with concomitant movements. These findings illuminate the relatively unexplored semantic functions of this region while calling for extensions of motor cognition models.Fil: Cervetto Manciameli, Sabrina Fabiana. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; Argentina. Universidad de la República; UruguayFil: Abrevaya, Sofia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; ArgentinaFil: Martorell Caro, Miguel Angel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; ArgentinaFil: Kozono, Giselle. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; ArgentinaFil: Muñoz, Edinson. Universidad de Santiago de Chile; ChileFil: Ferrari, Jesica. Instituto de Neurología Cognitiva; ArgentinaFil: Sedeño, Lucas. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; ArgentinaFil: Ibáñez Barassi, Agustín Mariano. Australian Research Council; Australia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; Argentina. Universidad Autónoma del Caribe; Colombia. Universidad Adolfo Ibañez; ChileFil: García, Adolfo Martín. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; Argentina. Universidad Nacional de Cuyo; Argentin

Liquidez, en el contexto de la COVID-19, en empresas cerveceras, periodos: del 2018 al 2021

El presente estudio buscó analizar de manera comparativa la liquidez, en el contexto de la COVID-19, en las empresas cerveceras para los periodos 2018 al 2021; por medio de una metodología de enfoque cuantitativo, de nivel descriptivo comparativo y diseño no experimental, con aplicación del análisis documental como técnica a una muestra no probabilística de 48 estados de resultados. Los resultados exponen resultados no significativos (0,05<) para todos los ratios de liquidez y además diferencias de medias negativas de -0,394, -0,391 y -0,086 para los ratios de liquidez corriente, severa y absoluta de manera respectiva, lo cual indica un incremento del periodo prepandémico a durante la pandemia; en el caso del capital de trabajo, se encontró una disminución del ratio, expresado en la diferencia promedio de S/142,381.71. Se concluye que no existe una diferencia significativa de los ratios de liquidez para el grupo de empresas cerveceras peruanas, entre los periodos antes y durante la COVID19

Deciphering Strawberry Ripening by Tissue Specific Gene Regulatory Networks

During ripening, fruits undergo a number of metabolic and physiological changes leading to softening and improvement of characters such as flavor and palatability. Insights into transcriptome changes during strawberry fruit ripening have been reported, but always using either complete fruits in the analysis or separating achenes and the fleshy part (receptacle). However, the receptacle is composed of heterogeneous cell types, each of them with different characteristics and functions. Hence, transcriptomic studies performed so far may have lost important regulatory elements which expression is low but important in a specific cell-type specific. In our study, we use Laser Capture Microdissection (LCM) technique for the isolation of cells from specific tissue types such as the epidermis, vascular bundles, cortex, and pith. Transcriptome profiling of these tissue types was performed by RNAseq. A gene co-expression analysis was performed by Weighted Correlation Network Analysis (WGCNA). Ontology analysis of each module showed wax biosynthesis as the main biological pathway enriched at the red epidermis specific module. In order to elucidate the putative regulatory elements that control the synthesis of waxes in this tissue, a Gene Regulatory Network (GRN) was generated using GENIST (de Luis Balaguer, 2017). As a result, we have identified a set of transcription factors that might regulate the expression of eceriferum genes and a fatty acid elongase necessary for wax biosynthesis in ripe epidermis. Ultimately, our results open the possibility of implementing novel targeted breeding approaches. Moreover, this work shows that LCM followed by RNAseq is a powerful tool that can be used to clarify the regulatory scenario of tissue-specific biological processes during strawberry ripening.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Implementación de la Transformada Discreta Wavelet en un sistema embebido para el análisis de registros electronistagmográficos

En el presente trabajo se describe el diseño y desarrollo de un sistema embebido basado en un microcontrolador de 32 bits, cuyo objetivo es determinar si la patología vertiginosa que sufre un paciente se debe al Sistema Nervioso Central (SNC) o al aparato vestibular. El software desarrollado para efectuar el análisis implementa la Transformada Discreta Wavelet (DWT), a fin de poder determinar la energía de los detalles de registros electronistagmográficos. Los resultados fueron comparados con los obtenidos con el software Matlab 7.0 instalado en una computadora personal. Se observo que los valores relativos de energías fueran similares, con la ventaja de tener un sistema fácilmente portable. La importancia de este desarrollo radica en que el método tradicional para efectuar este diagnóstico está basado en la observación de los registros en papel por parte de un especialista experimentado.Centro de Técnicas Analógico-Digitale

A New Extended Linear Mixing Model to Address Spectral Variability

International audienceSpectral variability is a phenomenon due, to a grand extend, to variations in the illumination and atmospheric conditions within a hyperspectral image, causing the spectral signature of a material to vary within a image. Data spectral fluctuation due to spectral variability compromises the linear mixing model (LMM) sum-to-one constraint, and is an important source of error in hyperspectral image analysis. Recently, spectral variability has raised more attention and some techniques have been proposed to address this issue, i.e. spectral bundles. Here, we propose the definition of an extended LMM (ELMM) to model spectral variability and we show that the use of spectral bundles models the ELMM implicitly. We also show that the constrained least squares (CLS) is an explicit modelling of the ELMM when the spectral variability is due to scaling effects. We give experimental validation that spectral bundles (and sparsity) and CLS are complementary techniques addressing spectral variability. We finally discuss on future research avenues to fully exploit the proposed ELMM