State-of-the-art techniques for calculating spectral functions in models for correlated materials

The dynamical mean field theory (DMFT) has become a standard technique for the study of strongly correlated models and materials overcoming some of the limitations of density functional approaches based on local approximations. An important step in this method involves the calculation of response functions of a multiorbital impurity problem which is related to the original model. Recently there has been considerable progress in the development of techniques based on the density matrix renormalization group (DMRG) and related matrix product states (MPS) implying a substantial improvement to previous methods. In this article we review some of the standard algorithms and compare them to the newly developed techniques, showing examples for the particular case of the half-filled two-band Hubbard model.Comment: 8 pages, 4 figures, to be published in EPL Perspective

Diabetes mellitus remission in a cat with hyperadrenocorticism after cabergoline treatment

A 7-year-old spayed female domestic shorthair cat weighing 5kg was referred with polyuria, polydipsia, lethargy, abdominal distension and dermatologic abnormalities. Diabetes mellitus was diagnosed and treatment was started with a diet for diabetic cats and insulin glargine (1IU q12h SC). Hyperadrenocorticism (HAC) was suspected and diagnosed based on clinical signs, increased urinary cortisol:creatinine ratio, lack of suppression on low-dose dexamethasone suppression test and abdominal ultrasonography demonstrating bilateral adrenal enlargement. Oral cabergoline (10μg/kg every other day) was initiated. After the second administration of cabergoline, the cat suffered from clinical hypoglycemia and no longer required insulin. One month after insulin withdrawal, blood work and urine analysis results showed normoglycemia, a normal serum fructosamine concentration (244μmol/l) and normal urine analysis without glycosuria. Diabetic remission persisted until its death 7 months later. In addition, cabergoline treatment was associated with improvement in clinical signs such as lethargy, seborrhea, alopecia and abdominal distension.Fil: Miceli, Diego Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental. Fundación de Instituto de Biología y Medicina Experimental. Instituto de Biología y Medicina Experimental; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Veterinarias. Hospital Escuela; Argentina. Universidad Maimónides. Centro de Ciencias Veterinarias; ArgentinaFil: Zelarayán, Gabriela S. Veterinaria Paraná; ArgentinaFil: García, Jorge D. Universidad de Buenos Aires. Facultad de Ciencias Veterinarias. Hospital Escuela; ArgentinaFil: Fernández, Viviana. Universidad Maimónides. Centro de Ciencias Veterinarias; ArgentinaFil: Ferraris, Sergio. Universidad Maimónides. Centro de Ciencias Veterinarias; Argentin

Measurement of the Drell-Yan cross section in pp collisions at √s = 7 TeV

Journal of High Energy Physics 2011.10 (2011): 007 reproduced by permission of Scuola Internazionale Superiore di Studi Avanzati (SISSA)The Drell-Yan differential cross section is measured in pp collisions at √s = 7TeV, from a data sample collected with the CMS detector at the LHC, corresponding to an integrated luminosity of 36 pb-1. The cross section measurement, normalized to the measured cross section in the Z region, is reported for both the dimuon and dielectron channels in the dilepton invariant mass range 15-600 GeV. The normalized cross section values are quoted both in the full phase space and within the detector acceptance. The effect of final state radiation is also identified. The results are found to agree with theoretical prediction

Oligomerización de receptores acoplados a proteína G y enfermedad de Parkinson

La enfermedad de Parkinson es una condición neurodegenerativa del sistema nervioso central que puede aparecer en la madurez pero cuya incidencia aumenta dramáticamente en la tercera edad. Por este motivo, en las sociedades industrializadas, donde la esperanza de vida es alta, la enfermedad tiene un elevado coste socio-económico. El origen de la patología radica en la pérdida selectiva de neuronas dopaminérgicas de una región concreta de los ganglios basales. En consecuencia, se produce un desequilibrio neuroquímico (ej.; glutama to/dopamina/adenosina) que afecta en última instancia a los procesos controlados por los ganglios basales (ej.; el control motor, la cognición, las emociones y el aprendizaje). Recientemente, se ha demostrado que los receptores acoplados a proteína G pueden expresarse en la membrana plasmática como homodímeros y heterómeros. Estos complejos oligoméricos pueden funcionar como procesadores computacionales dinámicos, modulando la señalización celular y por tanto el flujo de información a través de los circuitos neuronales. Así, desde un punto de vista cuantitativo y/o cualitativo la señal generada por la estimulación de un receptor concreto del heterómero puede ser diferente de aquella obtenida mediante la coestimulación de los diferentes integrantes del complejo. Este nuevo concepto, además de exhortar la reinterpretación de la farmacodinámica clásica de receptores acoplados a proteína G, impulsará el diseño de nuevas terapias basadas en la combinación de fármacos cuya diana sean los oligómeros de receptores, por ejemplo, el oligómero formado por los receptores de glutamato, dopamina y adenosina en el tratamiento de la enfermedad de Parkinson

Modelling stand biomass fractions in Galician Eucalyptus globulus plantations by use of different LiDAR pulse densities

Aims of study: To evaluate the potential use of canopy height and intensity distributions, determined by airborne LiDAR, for the estimation of crown, stem and aboveground biomass fractions. To assess the effects of a reduction in LiDAR pulse densities on model precision. Area of study: The study area is located in Galicia, NW Spain. The forests are representative of Eucalyptus globulus stands in NW Spain, characterized by low-intensity silvicultural treatments and by the presence of tall shrub. Material and methods: Linear, multiplicative power and exponential models were used to establish empirical relationships between field measurements and LiDAR metrics. A random selection of LiDAR returns and a comparison of the prediction errors by LiDAR pulse density factor were performed to study a possible loss of fit in these models. Main results: Models showed similar goodness-of-fit statistics to those reported in the international literature. R2 ranged from 0.52 to 0.75 for stand crown biomass, from 0.64 to 0.87 for stand stem biomass, and from 0.63 to 0.86 for stand aboveground biomass. The RMSE/MEAN · 100 of the set of fitted models ranged from 17.4% to 28.4%. Models precision was essentially maintained when 87.5% of the original point cloud was reduced, i.e. a reduction from 4 pulses m–2 to 0.5 pulses m–2. Research highlights: Considering the results of this study, the low-density LiDAR data that are released by the Spanish National Geographic Institute will be an excellent source of information for reducing the cost of forest inventories

A simple one-pot oxidation protocol for the synthesis of dehydrohedione from Hedione

A new method for the oxidation of Hedione 1 to dehydrohedione 2, a high value intermediate in the flavour and fragrance industry, has developed based upon one pot α-chlorination-elimination sequence which can be readily scaled. The spontaneous elimination of the α-chloro in methanol was unprecedented and has allowed for the oxidation, typically performed in multiple steps/reactions, to be carried out as a one-pot protocol. A continuous flow process for performing the reaction utilising sulfuryl chloride has also demonstrated allowing for steady, safe evolution of SO2 gas during the reaction

Weakly-supervised detection of AMD-related lesions in color fundus images using explainable deep learning

[Abstract]: Background and Objectives: Age-related macular degeneration (AMD) is a degenerative disorder affecting the macula, a key area of the retina for visual acuity. Nowadays, AMD is the most frequent cause of blindness in developed countries. Although some promising treatments have been proposed that effectively slow down its development, their effectiveness significantly diminishes in the advanced stages. This emphasizes the importance of large-scale screening programs for early detection. Nevertheless, implementing such programs for a disease like AMD is usually unfeasible, since the population at risk is large and the diagnosis is challenging. For the characterization of the disease, clinicians have to identify and localize certain retinal lesions. All this motivates the development of automatic diagnostic methods. In this sense, several works have achieved highly positive results for AMD detection using convolutional neural networks (CNNs). However, none of them incorporates explainability mechanisms linking the diagnosis to its related lesions to help clinicians to better understand the decisions of the models. This is specially relevant, since the absence of such mechanisms limits the application of automatic methods in the clinical practice. In that regard, we propose an explainable deep learning approach for the diagnosis of AMD via the joint identification of its associated retinal lesions. Methods: In our proposal, a CNN with a custom architectural setting is trained end-to-end for the joint identification of AMD and its associated retinal lesions. With the proposed setting, the lesion identification is directly derived from independent lesion activation maps; then, the diagnosis is obtained from the identified lesions. The training is performed end-to-end using image-level labels. Thus, lesion-specific activation maps are learned in a weakly-supervised manner. The provided lesion information is of high clinical interest, as it allows clinicians to assess the developmental stage of the disease. Additionally, the proposed approach allows to explain the diagnosis obtained by the models directly from the identified lesions and their corresponding activation maps. The training data necessary for the approach can be obtained without much extra work on the part of clinicians, since the lesion information is habitually present in medical records. This is an important advantage over other methods, including fully-supervised lesion segmentation methods, which require pixel-level labels whose acquisition is arduous. Results: The experiments conducted in 4 different datasets demonstrate that the proposed approach is able to identify AMD and its associated lesions with satisfactory performance. Moreover, the evaluation of the lesion activation maps shows that the models trained using the proposed approach are able to identify the pathological areas within the image and, in most cases, to correctly determine to which lesion they correspond. Conclusions: The proposed approach provides meaningful information—lesion identification and lesion activation maps—that conveniently explains and complements the diagnosis, and is of particular interest to clinicians for the diagnostic process. Moreover, the data needed to train the networks using the proposed approach is commonly easy to obtain, what represents an important advantage in fields with particularly scarce data, such as medical imaging.Xunta de Galicia; ED481B-2022-025Xunta de Galicia; ED431C 2020/24Xunta de Galicia; IN845D 2020/38Xunta de Galicia; ED481A 2021/140Xunta de Galicia; ED431G 2019/01This work was funded by Instituto de Salud Carlos III, Government of Spain, and the European Regional Development Fund (ERDF) of the European Union (EU) through the DTS18/00136 research project; Ministerio de Ciencia e Innovación, Government of Spain, through RTI2018-095894-B-I00 and PID2019-108435RB-I00 research projects; Axencia Galega de Innovación (GAIN), Xunta de Galicia, ref. IN845D 2020/38; Conselleria de Cultura, Educación e Universidade, Xunta de Galicia, through Grupos de Referencia Competitiva, ref. ED431C 2020/24, the predoctoral grant ref. ED481A 2021/140, and the postdoctoral grant ref. ED481B-2022-025; CITIC, Centro de Investigación de Galicia ref. ED431G 2019/01, is funded by Conselleria de Educación, Universidade e Formación Profesional, Xunta de Galicia, through the ERDF (80%) and Secretaria Xeral de Universidades (20%)

Aportes para una lectura integrada del patrimonio natural y cultural

La presente propuesta surge a partir del trabajo realizado en el Módulo “Práctica Integradora Con Trabajo De Campo” de la Maestría en Valoración del Patrimonio Natural y Cultural de la Universidad Católica de Salta. El objetivo del mismo consiste en una propuesta de lectura e interpretación del paisaje para la valoración de los elementos patrimoniales que lo componen, desde una mirada integradora, relacionando paisaje y territorio. Se realiza a partir de una secuencia de miradores a lo largo de un itinerario que inicia en la quebrada de Escoipe hasta llegar la localidad de Cachi. Este trabajo pretende ayudar a señalar las potencialidades del paisaje, los aportes de los valores que surgen y se proyectan en el territorio a través del patrimonio, sus manifestaciones y significados. Intenta a su vez aportar una mirada integradora de los distintos elementos que conforman y constituyen al paisaje como patrimonio cultural y natural.Tópico 3: Gestión del Patrimonio. Planificación y Gestión sustentable de los paisajes. Aspectos teóricos y metodológicos

Environmental drivers of the distribution of the order Pleuronectiformes in the Northern Spanish Shelf

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