Comparación entre el análisis 2-D y el Método de la Densidad de Fuerzas (discreto) para el equilibrio en estructuras de membrana

This paper deals with the equilibrium problem of a membrane, presenting a comparison between the well-known 1-D discrete Force Density Method, using spatial cable networks as membrane surface approximations, and the 2-D continuous analysis of such a surface. Although Force Density is a practical and powerful method in structural membrane design, it will be checked that the 2-D continuous analysis is not only more accurate and general but necessary for new structural membrane applications such as footbridges. In this way, once summarized the discrete Density Force Method, the continuous approach is presented. Then, a comparison process between both methods is proposed, being developed for specific membrane examples. Finally, some conclusions are pointed out.Este trabajo analiza el problema del equilibrio de una membrana y propone una comparación entre el conocido Método de la Densidad de Fuerzas, discreto y unidimensional (1-D), que aproxima la superficie de la membrana mediante una red espacial de cables, y el método continuo y bidimensional (2-D) sobre la propia superficie. Aunque el Método de la Densidad de Fuerzas representa una estrategia práctica y útil en el diseño de estructuras de membrana, se comprobará que el análisis continuo bidimensional no solo es más preciso y general sino que es más fiable, especialmente en aquellos casos en los que la membrana es el mismo tablero de una estructura portante (por ejemplo, una pasarela). En particular, una vez resumido el Método de la Densidad de Fuerzas, se planteará el problema continuo del equilibrio de membrana. A continuación se definirá un proceso de comparación entre ambos métodos, analizándolo por medio de ejemplos concretos. Finalmente, se señalarán algunas conclusiones

A Structural Parametrization of the Brain Using Hidden Markov Models Based Paths in Alzheimer's Disease

The usage of biomedical imaging in the diagnosis of dementia is increasingly widespread. A number of works explore the possibilities of computational techniques and algorithms in what is called Computed Aided Diagnosis. Our work presents an automatic parametrization of the brain structure by means of a path generation algorithm based on Hidden Markov Models. The path is traced using information of intensity and spatial orientation in each node, adapting to the structural changes of the brain. Each path is itself a useful way to extract features from the MRI image, being the intensity levels at each node the most straightforward. However, a further processing consisting of a modification of the Gray Level Co-occurrence Matrix can be used to characterize the textural changes that occur throughout the path, yielding more meaningful values that could be associated to the structural changes in Alzheimer's Disease, as well as providing a significant feature reduction. This methodology achieves high performance, up to 80.3\% of accuracy using a single path in differential diagnosis involving Alzheimer-affected subjects versus controls belonging to the Alzheimer's Disease Neuroimaging Initiative (ADNI).TIC218, MINECO TEC2008-02113 and TEC2012-34306 projects, Consejería de Economía, Innovación, Ciencia y Empleo de la Junta de Andalucía P09-TIC-4530 and P11-TIC-71

Photocatalytic hydrogen evolution using bi-metallic (Ni/Pt) Na2Ti3O7 whiskers: Effect of the deposition order

Photocatalytic hydrogen production through ethanol photo-reforming using Na2Ti3O7 whiskers increases if the sodium titanate is decorated with well-known metallic catalysts such as Ni and Pt. Whereas wet impregnation with nickel gives only a slight increase in the activity, photo-deposition of Pt increased the H2 production by more than one order of magnitude. Through the combination of both co-catalysts (Ni and Pt) a superior performance in terms of H2 production is further observed. However, hydrogen yield is largely enhanced (almost three-fold), up to 778 μmol·g−1·h−1, if the Pt is photo-deposited on the surface of the catalyst before wet impregnation with Ni species (NTO/Pt/Ni) compared to H2 yield (283 μmol·g−1·h−1) achieved with the catalyst prepared in the reverse order (NTO/Ni/Pt). Structural, morphological, optical, and chemical characterization was carried out in order to correlate physicochemical properties with their photocatalytic activity. The X-ray photoelectron spectroscopy (XPS) results show a higher concentration of Pt2+ species if this metallic layer is under the nickel oxide layer. Moreover, X-ray diffraction patterns (XRD) show that Na2Ti3O7 surface is modified for both metal decoration processes

Mammalian Adaptation of an Avian Influenza A Virus Involves Stepwise Changes in NS1

Influenza A viruses (IAVs) are common pathogens of birds that occasionally establish endemic infections in mammals. The processes and mechanisms that result in IAV mammalian adaptation are poorly understood. The viral non-structural 1 (NS1) protein counteracts the interferon (IFN) response, a central component of the host-species barrier. We characterised the NS1 proteins of equine influenza virus (EIV), a mammalian IAV lineage of avian origin. We showed that evolutionary distinct NS1s counteract the IFN response using different and mutually exclusive mechanisms: while the NS1s of early EIVs block general gene expression by binding to the cellular polyadenylation specific factor 30 (CPSF30), NS1s from more evolved EIVs specifically block the induction of IFN-stimulated genes by interfering with the JAK/STAT pathway. These contrasting anti-IFN strategies are associated with two mutations that appeared sequentially and became rapidly selected during EIV evolution, highlighting the importance of evolutionary processes on immune evasion mechanisms during IAV adaptation

Periodogram Connectivity of EEG Signals for the Detection of Dyslexia

Electroencephalography (EEG) signals provide an important source of information of brain activity at different areas. This information can be used to diagnose brain disorders according to different activation patterns found in controls and patients. This acquisition technology can be also used to explore the neural basis of less evident learning disabilities such as Developmental Dyslexia (DD). DD is a specific difficulty in the acquisition of reading skills not related to mental age or inadequate schooling, whose prevalent is estimated between 5% and 12% of the population. In this paper we propose a method to extract discriminative features from EEG signals based on the relationship among the spectral density at each channel. This relationship is computed by means of different correlation measures, inferring connectivity-like markers that are eventually selected and classified by a linear support vector machine. The experiments performed shown AUC values up to 0.7, demonstrating the applicability of the proposed approach for objective DD diagnosis

Exposure to Bisphenol A and Phthalates during Pregnancy and Ultrasound Measures of Fetal Growth in the INMA-Sabadell Cohort

Background: Prenatal exposure to bisphenol A (BPA) and phthalates may affect fetal growth; however, previous findings are inconsistent and based on few studies. Objectives: We assessed whether prenatal exposure to BPA and phthalates was associated with fetal growth in a Spanish birth cohort of 488 mother–child pairs. Methods: We measured BPA and eight phthalates [four di(2-ethylhexyl) phthalate metabolites (DEHPm), mono-benzyl phthalate (MBzP), and three low-molecular-weight phthalate metabolites (LMWPm)] in two spot-urine samples collected during the first and third trimester of pregnancy. We estimated growth curves for femur length (FL), head circumference (HC), abdominal circumference (AC), biparietal diameter (BPD), and estimated fetal weight (EFW) during pregnancy (weeks 12–20 and 20–34), and for birth weight, birth length, head circumference at birth, and placental weight. Results: Overall, results did not support associations of exposure to BPA or DEHPm during pregnancy with fetal growth parameters. Prenatal MBzP exposure was positively associated with FL at 20–34 weeks, resulting in an increase of 3.70% of the average FL (95% CI: 0.75, 6.63%) per doubling of MBzP concentration. MBzP was positively associated with birth weight among boys (48 g; 95% CI: 6, 90) but not in girls (–27 g; 95% CI: –79, 25) (interaction p-value = 0.04). The LMWPm mono-n-butyl phthalate (MnBP) was negatively associated with HC at 12–20 pregnancy weeks [–4.88% of HC average (95% CI: –8.36, –1.36%)]. Conclusions: This study, one of the first to combine repeat exposure biomarker measurements and multiple growth measures during pregnancy, finds little evidence of associations of BPA or phthalate exposures with fetal growth. Phthalate metabolites MBzP and MnBP were associated with some fetal growth parameters, but these findings require replication

Anosmin-1 over-expression increases adult neurogenesis in the subventricular zone and neuroblast migration to the olfactory bulb

New subventricular zone (SVZ)-derived neuroblasts that migrate via the rostral migratory stream are continuously added to the olfactory bulb (OB) of the adult rodent brain. Anosmin-1 (A1) is an extracellular matrix protein that binds to FGF receptor 1 (FGFR1) to exert its biological effects. When mutated as in Kallmann syndrome patients, A1 is associated with severe OB morphogenesis defects leading to anosmia and hypogonadotropic hypogonadism. Here, we show that A1 over-expression in adult mice strongly increases proliferation in the SVZ, mainly with symmetrical divisions, and produces substantial morphological changes in the normal SVZ architecture, where we also report the presence of FGFR1 in almost all SVZ cells. Interestingly, for the first time we show FGFR1 expression in the basal body of primary cilia in neural progenitor cells. Additionally, we have found that A1 over-expression also enhances neuroblast motility, mainly through FGFR1 activity. Together, these changes lead to a selective increase in several GABAergic interneuron populations in different OB layers. These specific alterations in the OB would be sufficient to disrupt the normal processing of sensory information and consequently alter olfactory memory. In summary, this work shows that FGFR1-mediated A1 activity plays a crucial role in the continuous remodelling of the adult OB.This research was supported by grants from the Spanish Ministerio de Economía, Innovación y Competitividad MINECO (SAF2009-07842, ADE10-0010, RD07-0060-2007, RD12-0032-12 and SAF2012-40023 to FdC; and BFU2010-18284 to JMG-V), FISCAM (Gobierno de Castilla-La Mancha, Spain—Grant Number PI2007-66), the Junta de Castilla y León (Spain, to EW), and from the Fundación Eugenio Rodríguez Pascual (Spain) to FdC. DGG and VMB were PhD students hired by Gobierno de Castilla-La Mancha (MOV2010-JI/11 and MOV2007-JI/19, respectively). FdCS is a CSIC staff scientist in special permission hired by SESCAM (Gobierno de Castilla-La Mancha, Spain). PFE was a researcher hired by SESCAM (Gobierno de Castilla-La Mancha) and ADE10-0010.Peer reviewe

Computational approaches to explainable artificial intelligence: Advances in theory, applications and trends

Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted in complex and non-linear artificial neural systems, excel at extracting high-level features from data. DL has demonstrated human-level performance in real-world tasks, including clinical diagnostics, and has unlocked solutions to previously intractable problems in virtual agent design, robotics, genomics, neuroimaging, computer vision, and industrial automation. In this paper, the most relevant advances from the last few years in Artificial Intelligence (AI) and several applications to neuroscience, neuroimaging, computer vision, and robotics are presented, reviewed and discussed. In this way, we summarize the state-of-the-art in AI methods, models and applications within a collection of works presented at the 9th International Conference on the Interplay between Natural and Artificial Computation (IWINAC). The works presented in this paper are excellent examples of new scientific discoveries made in laboratories that have successfully transitioned to real-life applications.MCIU - Nvidia(UMA18-FEDERJA-084