2,105 research outputs found
A new hybrid in the genus Cynara L. (Asteraceae): C. x gaditana Blanca & Sánchez Carrión, nothosp. nov.
Un nuevo híbrido en el género Cynara L. (Asteraceae): C. x gaditana Blanca & Sánchez Carrión, nothosp. nov.
A new hybrid in the genus Cynara L. (Asteraceae): C. x gaditana Blanca & Sánchez Carrión, nothosp. nov.Palabras clave. Cynara, Asteraceae, corología, híbrido, Cádiz, España.Key words:.Cynara, Asteraceae, chorology, hybrid, Cádiz, Spain
Circumpapillary OCT-Focused Hybrid Learning for Glaucoma Grading Using Tailored Prototypical Neural Networks
Glaucoma is one of the leading causes of blindness worldwide and Optical
Coherence Tomography (OCT) is the quintessential imaging technique for its
detection. Unlike most of the state-of-the-art studies focused on glaucoma
detection, in this paper, we propose, for the first time, a novel framework for
glaucoma grading using raw circumpapillary B-scans. In particular, we set out a
new OCT-based hybrid network which combines hand-driven and deep learning
algorithms. An OCT-specific descriptor is proposed to extract hand-crafted
features related to the retinal nerve fibre layer (RNFL). In parallel, an
innovative CNN is developed using skip-connections to include tailored residual
and attention modules to refine the automatic features of the latent space. The
proposed architecture is used as a backbone to conduct a novel few-shot
learning based on static and dynamic prototypical networks. The k-shot paradigm
is redefined giving rise to a supervised end-to-end system which provides
substantial improvements discriminating between healthy, early and advanced
glaucoma samples. The training and evaluation processes of the dynamic
prototypical network are addressed from two fused databases acquired via
Heidelberg Spectralis system. Validation and testing results reach a
categorical accuracy of 0.9459 and 0.8788 for glaucoma grading, respectively.
Besides, the high performance reported by the proposed model for glaucoma
detection deserves a special mention. The findings from the class activation
maps are directly in line with the clinicians' opinion since the heatmaps
pointed out the RNFL as the most relevant structure for glaucoma diagnosis
Automatic Segmentation of the Retinal Nerve Fiber Layer by Means of Mathematical Morphology and Deformable Models in 2D Optical Coherence Tomography Imaging
[EN] Glaucoma is a neurodegenerative disease process that leads to progressive damage of the optic nerve to produce visual impairment and blindness. Spectral-domain OCT technology enables peripapillary circular scans of the retina and the measurement of the thickness of the retinal nerve fiber layer (RNFL) for the assessment of the disease status or progression in glaucoma patients. This paper describes a new approach to segment and measure the retinal nerve fiber layer in peripapillary OCT images. The proposed method consists of two stages. In the first one, morphological operators robustly detect the coarse location of the layer boundaries, despite the speckle noise and diverse artifacts in the OCT image. In the second stage, deformable models are initialized with the results of the previous stage to perform a fine segmentation of the boundaries, providing an accurate measurement of the entire RNFL. The results of the RNFL segmentation were qualitatively assessed by ophthalmologists, and the measurements of the thickness of the RNFL were quantitatively compared with those provided by the OCT inbuilt software as well as the state-of-the-art methods.This work was partially funded by Spanish National projects AES2017-PI17/00771 and AES2017-PI17/00821 (Instituto de Salud Carlos III), PID2019-105142RB-C21 (AI4SKIN) (Spanish Ministry of Economy and Competitiveness), PTA2017-14610-I (State Research Spanish Agency), regional project 20901/PI/18 (Fundacion Seneca) and Polytechnic University of Valencia (PAID-01-20).Berenguer-Vidal, R.; Verdú-Monedero, R.; Morales-Sánchez, J.; Sellés-Navarro, I.; Del Amor, R.; García-Pardo, JG.; Naranjo Ornedo, V. (2021). Automatic Segmentation of the Retinal Nerve Fiber Layer by Means of Mathematical Morphology and Deformable Models in 2D Optical Coherence Tomography Imaging. Sensors. 21(23):1-30. https://doi.org/10.3390/s21238027S130212
A Grammatical Approach to the Modeling of an Autonomous Robot
Virtual Worlds Generator is a grammatical model
that is proposed to define virtual worlds. It integrates the
diversity of sensors and interaction devices, multimodality and a
virtual simulation system. Its grammar allows the definition and
abstraction in symbols strings of the scenes of the virtual world,
independently of the hardware that is used to represent the world
or to interact with it. A case study is presented to explain how to
use the proposed model to formalize a robot navigation system
with multimodal perception and a hybrid control scheme of the
robot. The result is an instance of the model grammar that
implements the robotic system and is independent of the sensing
devices used for perception and interaction. As a conclusion the
Virtual Worlds Generator adds value in the simulation of virtual
worlds since the definition can be done formally and
independently of the peculiarities of the supporting devices
UrbanWater And WatERP: Decision Support Systems For Efficient And Integrated Water Resources Management
In this work we present UrbanWater and WatERP, two EU-FP7 projects with the common objective of designing and developing innovative ICT solutions to integrate real-time knowledge on water demand and supply across water distribution networks. On one hand, WatERP proposes to develop a web-based Open Management Platform (OMP) supported by real-time knowledge on water supply and demand, enabling the entire water distribution system to be viewed in an integrated and customized way. The OMP provides inferred information regarding water supplies, flows, water consumption patterns, water losses, distribution efficiency, and water supply and demand forecasts to the user. This information is stored in a Water Data Warehouse using semantics and open standards (such as WaterML 2.0) which are defined in the ontology developed to ensure interoperability and maximize usability. In addition, external linkages to costs, energy factors, control systems, data acquisition systems, external models, forecasting systems and new data sources are made available for easy integration into the system. On the other hand, UrbanWater proposes to develop an ICT-based platform for efficient and integrated management of urban water resources, incorporating weather prediction and water availability data, household consumption data, and water distribution among others. Its design corresponds to a highly flexible Spatial Decision Support System capable of connecting manifold data sources and data processing modules that enable to (i) effectively estimate water demand in urban water areas to manage water distribution networks in an efficient way; (ii) reduce waste of water and economic losses associated to leakages; (iii) smoothen daily water demand peaks in order to save costs; and (iv) provide an off-line and on-line operation framework that allows defining scenarios of availability and demand to test specific strategies for the distribution network operation
An arsRB resistance operon confers tolerance to arsenite in the environmental isolate Terribacillus sp. AE2B 122
Terribacillus sp. AE2B 122 is an environmental strain isolated from olive-oil agroindustry wastes. This strain displays resistance to arsenic, one of the most ubiquitous carcinogens found in nature. Terribacillus sp. AE2B 122 possesses an unusual ars operon, consisting of the transcriptional regulator (arsR) and arsenite efflux pump (arsB) but no adjacent arsenate reductase (arsC) locus. Expression of arsR and arsB was induced when Terribacillus was exposed to sub-lethal concentrations of arsenate. Heterologous expression of the arsB homologue in Escherichia coliarsRBC demonstrated that it conferred resistance to arsenite and reduced the accumulation of arsenic inside the cells. Two members of the arsC-like family (Te3384 and Te2854) found in the Terribacillus genome were not induced by arsenic, but their heterologous expression in E. coli Delta arsC and Delta arsRBC increased the accumulation of arsenic in both strains. We found that both Te3384 and Te2854 slightly increased resistance to arsenate in E. coli Delta arsC and Delta arsRBC, possibly by chelation of arsenic or by increasing the resistance to oxidative stress. Finally, arsenic speciation assays suggest that Terribacillus is incapable of arsenate reduction, in agreement with the lack of an arsC homologue in the genome
Thermal and catalytic pyrolysis of a real mixture of post-consumer plastic waste: An analysis of the gasoline-range product
In this work, the thermal and catalytic pyrolysis of different types of plastic waste and a real mixture were investigated in a fixed-bed reactor over different catalysts (CaO, MgO, HY, HZSM-5). Important differences in gas, liquid, and solid yields were found as a function of polymer type. The highest gas yield was obtained with expanded polystyrene (52.3%), and the maximum oil production with high-impact polystyrene (55.5%), while polypropylene film led to the highest char release (17.5%). Regarding the composition of the liquid oil, high-impact polystyrene showed the highest yield of gasoline-range product (426 g per kg of pyrolyzed plastic), mainly composed of aromatics compounds (90%). The addition of catalysts increased the gas yield to the detriment of the oil produced. The effect was more evident for zeolite-type catalysts, i.e., the gas yield raised from 43.3 (non-catalytic) to 51.5% (HZSM-5). Low influence on the oil composition, i.e., gasoline-range product, was detected. This can be explained by the fast deactivation of catalysts because of coke deposition. Only an increase in the fraction of gasoline in liquid oil was observed when low-cost catalysts (CaO and MgO) were used, without significant changes in the composition of this product
Transdiagnostic neurocognitive deficits in patients with type 2 diabetes mellitus, major depressive disorder, bipolar disorder, and schizophrenia: a 1-year follow-up study
Background
Neurocognition impairments are critical factors in patients with major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SZ), and also in those with somatic diseases such as type 2 diabetes mellitus (T2DM). Intriguingly, these severe mental illnesses are associated with an increased co-occurrence of diabetes (direct comorbidity). This study sought to investigate the neurocognition and social functioning across T2DM, MDD, BD, and SZ using a transdiagnostic and longitudinal approach.
Methods
A total of 165 participants, including 30 with SZ, 42 with BD, 35 with MDD, 30 with T2DM, and 28 healthy controls (HC), were assessed twice at a 1-year interval using a comprehensive, integrated test battery on neuropsychological and social functioning.
Results
Common neurocognitive impairments in somatic and psychiatric disorders were identified, including deficits in short-term memory and cognitive reserve (p < 0.01, η²p=0.08–0.31). Social functioning impairments were observed in almost all the disorders (p < 0.0001; η²p=0.29–0.49). Transdiagnostic deficits remained stable across the 1-year follow-up (p < 0.001; η²p=0.13–0.43) and could accurately differentiate individuals with somatic and psychiatric disorders (χ² = 48.0, p < 0.0001).
Limitations
The initial sample size was small, and high experimental mortality was observed after follow-up for one year.
Conclusions
This longitudinal study provides evidence of some possible overlap in neurocognition deficits across somatic and psychiatric diagnostic categories, such as T2DM, MDD, BD, and SZ, which have high comorbidity. This overlap may be a result of shared genetic and environmental etiological factors. The findings open promising avenues for research on transdiagnostic phenotypes of neurocognition in these disorders, in addition to their biological bases
Distribución de los suelos del sector noroccidental de Sierra Nevada. Granada
En el levantamiento de suelos del sector Noroccidental de Sierra Nevada, se han cartografiado y descrito 15 unidades básicas de suelos y 4 unidades misceláneas de tierras. Se analizan los controles edafogenéticos de las unidades, la extensión areal de las mismas y los caracteres más destacables de los suelos modales. Los inceptisoles ocupan el 47,8% del total del área, las unidades misceláneas el 25,8%, los entisoles el 23,2% y los mollisoles el 3,2%. Las unidades mayoritarias (Xerumbrept típico y éntico, Criumbrept típico y éntico) se desarrollan sobre rocas ácidas, en pendientes entre 15% a 55% y hasta 2.800 m. de altitud, bajo vegetación de matorral.In a soil survey of the Northwest area of Sierra Nevada, fifteen soil units
and four miscelaneous units have been mapped and described. Pedogenic controls, areal extension and the most important characteristics of these units have been analized.
The 47,8"10 of the total area are inceptisols, 25,8% are miscelaneous
units, 2 3,2% are entisols and 3.2% are mollisols.
Typic Xerumbrept, entic Xerumbrept, typic Cryumbrept and entic
Cryumprept are the most extrensive units. These are developed on acidic roe k
with a slope between 15 to 55%, under bush vegetation and so far as 2.800 m.
of limit altitude
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