852 research outputs found
Topological Quintessence
A global monopole (or other topological defect) formed during a recent phase
transition with core size comparable to the present Hubble scale, could induce
the observed accelerating expansion of the universe. In such a model,
topological considerations trap the scalar field close to a local maximum of
its potential in a cosmologically large region of space. We perform detailed
numerical simulations of such an inhomogeneous dark energy system (topological
quintessence) minimally coupled to gravity, in a flat background of initially
homogeneous matter. We find that when the energy density of the field in the
monopole core starts dominating the background density, the spacetime in the
core starts to accelerate its expansion in accordance to a \Lambda CDM model
with an effective inhomogeneous spherical dark energy density parameter
\Omega_\Lambda(r). The matter density profile is found to respond to the global
monopole profile via an anti-correlation (matter underdensity in the monopole
core). Away from the monopole core, the spacetime is effectively
Einstein-deSitter (\Omega_\Lambda(r_{out}) -> 0) while at the center
\Omega_\Lambda(r ~ 0) is maximum. We fit the numerically obtained expansion
rate at the monopole core to the Union2 data and show that the quality of fit
is almost identical to that of \Lambda CDM. Finally, we discuss potential
observational signatures of this class of inhomogeneous dark energy models.Comment: Accepted in Phys. Rev. D (to appear). Added observational bounds on
parameters. 10 pages (two column revtex), 6 figures. The Mathematica files
used to produce the figures of this study may be downloaded from
http://leandros.physics.uoi.gr/topquin
Second Harmonic Generation Microscopy: A Tool for Quantitative Analysis of Tissues
Second harmonic generation (SHG) is a secondâorder nonâlinear optical process produced in birefringent crystals or in biological tissues with nonâcentrosymmetric structure such as collagen or microtubules structures. SHG signal originates from two excitation photons which interact with the material and are âreconvertedâ to form a new emitted photon with half of wavelength. Although theoretically predicted by Maria GöpertâMayer in 1930s, the experimental SHG demonstration arrived with the invention of the laser in the 1960s. SHG was first obtained in ruby by using a high excitation oscillator. After that starting point, the harmonic generation reached an increasing interest and importance, based on its applications to characterize biological tissues using multiphoton microscopes. In particular, collagen has been one of the most often analyzed structures since it provides an efficient SHG signal. In late 1970s, it was discovered that SHG signal took place in threeâdimensional optical interaction at the focal point of a microscope objective with high numerical aperture. This finding allowed researchers to develop microscopes with 3D submicron resolution and an in depth analysis of biological specimens. Since SHG is a polarizationâsensitive nonâlinear optical process, the implementation of polarization into multiphoton microscopes has allowed the study of both molecular architecture and fibrilar distribution of typeâI collagen fibers. The analysis of collagenâbased structures is particularly interesting since they represent 80% of the connective tissue of the human body. On the other hand, more recent techniques such as pulse compression of laser pulses or adaptive optics have been applied to SHG microscopy in order to improve the visualization of features. The combination of these techniques permit the reduction of the laser power required to produce efficient SHG signal and therefore photoâtoxicity and photoâdamage are avoided (critical parameters in biomedical applications). Some pathologies such as cancer or fibrosis are related to collagen disorders. These are thought to appear at molecular scale before the micrometric structure is affected. In this sense, SHG imaging has emerged as a powerful tool in biomedicine and it might serve as a nonâinvasive early diagnosis technique
Superpixel-Based Optic Nerve Head Segmentation Method of Fundus Images for Glaucoma Assessment
Glaucoma disease is the second leading cause of blindness in the world. This progressive ocular neuropathy is mainly caused by uncontrolled high intraocular pressure. Although there is still no cure, early detection and appropriate treatment can stop the disease progression to low vision and blindness. In the clinical practice, the gold standard used by ophthalmologists for glaucoma diagnosis is fundus retinal imaging, in particular optic nerve head (ONH) subjective/manual examination. In this work, we propose an unsupervised superpixel-based method for the optic nerve head (ONH) segmentation. An automatic algorithm based on linear iterative clustering is used to compute an ellipse fitting for the automatic detection of the ONH contour. The tool has been tested using a public retinal fundus images dataset with medical expert ground truths of the ONH contour and validated with a classified (control vs. glaucoma eyes) database. Results showed that the automatic segmentation method provides similar results in ellipse fitting of the ONH that those obtained from the ground truth experts within the statistical range of inter-observation variability. Our method is a user-friendly available program that provides fast and reliable results for clinicians working on glaucoma screening using retinal fundus images
Collagen organization, polarization sensitivity and image quality in human corneas using second harmonic generation microscopy
In this paper, a Second-Harmonic-Generation (SHG) microscope was used to study the relationship between collagen structural arrangement, image quality and polarization sensitivity in human corneas with different organizations. The degree of order (or alternatively, the Structural Dispersion, SD) was quantified using the structure tensor method. SHG image quality was evaluated with different objective metrics. Dependence with polarization was quantified by means of a parameter defined as polarimetric modulation, which employs polarimetric SHG images acquired with four independent polarization states. There is a significant exponential relationship between the quality of the SHG images and the SD of the samples. Moreover, polarization sensitivity strongly depends on collagen arrangement. For quasi- or partially organized specimens, there is a polarization state that noticeably improves the image quality, providing additional information often not seen in other SHG images. This does not occur in non-organized samples. This fact is closely related to polarimetric modulation, which linearly decreases with the SD. Understanding in more detail the relationships that take place between collagen distribution, image quality and polarization sensitivity brings the potential to enable the development of optimized SHG image acquisition protocols and novel objective strategies for the analysis and detection of pathologies related to corneal collagen disorders, as well as surgery follow-ups
Surface wave control for large arrays of microwave kinetic inductance detectors
Large ultra-sensitive detector arrays are needed for present and future
observatories for far infra-red, submillimeter wave (THz), and millimeter wave
astronomy. With increasing array size, it is increasingly important to control
stray radiation inside the detector chips themselves, the surface wave. We
demonstrate this effect with focal plane arrays of 880 lens-antenna coupled
Microwave Kinetic Inductance Detectors (MKIDs). Presented here are near field
measurements of the MKID optical response versus the position on the array of a
reimaged optical source. We demonstrate that the optical response of a detector
in these arrays saturates off-pixel at the dB level compared to the
peak pixel response. The result is that the power detected from a point source
at the pixel position is almost identical to the stray response integrated over
the chip area. With such a contribution, it would be impossible to measure
extended sources, while the point source sensitivity is degraded due to an
increase of the stray loading. However, we show that by incorporating an
on-chip stray light absorber, the surface wave contribution is reduced by a
factor 10. With the on-chip stray light absorber the point source response
is close to simulations down to the dB level, the simulation based on
an ideal Gaussian illumination of the optics. In addition, as a crosscheck we
show that the extended source response of a single pixel in the array with the
absorbing grid is in agreement with the integral of the point source
measurements.Comment: accepted for publication in IEEE Transactions on Terahertz Science
and Technolog
La educaciĂłn de la II RepĂșblica: Palmira PlĂĄ
Palmira PlĂĄ nace en Cretas (Teruel) en 1914. Poco a poco va descubriendo su gran vocaciĂłn: ser maestra. A lo largo de este siglo vivirĂĄ las penurias de la Guerra Civil, el exilio a Francia y en consecuencia su miseria asĂ como el conflicto de la Segunda Guerra Mundial. Es en este paĂs donde perderĂĄ a uno de los grandes amores de su vida, Paco PonzĂĄn, quien serĂĄ asesinado por los nazis. MĂĄs tarde se encontrarĂĄ con Adolfo Jimeno, con quien se casarĂĄ y marcharĂĄ a Venezuela, donde podrĂĄ disfrutar de su labor como maestra. Es aquĂ donde fundarĂĄ el Instituto Calicanto. VolverĂĄ a España para seguir educando participando a su vez en polĂtica
Sound Levels Forecasting in an Acoustic Sensor Network Using a Deep Neural Network
[EN] Wireless acoustic sensor networks are nowadays an essential tool for noise pollution monitoring and managing in cities. The increased computing capacity of the nodes that create the network is allowing the addition of processing algorithms and artificial intelligence that provide more information about the sound sources and environment, e.g., detect sound events or calculate loudness. Several models to predict sound pressure levels in cities are available, mainly road, railway and aerial traffic noise. However, these models are mostly based in auxiliary data, e.g., vehicles flow or street geometry, and predict equivalent levels for a temporal long-term. Therefore, forecasting of temporal short-term sound levels could be a helpful tool for urban planners and managers. In this work, a Long Short-Term Memory (LSTM) deep neural network technique is proposed to model temporal behavior of sound levels at a certain location, both sound pressure level and loudness level, in order to predict near-time future values. The proposed technique can be trained for and integrated in every node of a sensor network to provide novel functionalities, e.g., a method of early warning against noise pollution and of backup in case of node or network malfunction. To validate this approach, one-minute period equivalent sound levels, captured in a two-month measurement campaign by a node of a deployed network of acoustic sensors, have been used to train it and to obtain different forecasting models. Assessments of the developed LSTM models and Auto regressive integrated moving average models were performed to predict sound levels for several time periods, from 1 to 60 min. Comparison of the results show that the LSTM models outperform the statistics-based models. In general, the LSTM models achieve a prediction of values with a mean square error less than 4.3 dB for sound pressure level and less than 2 phons for loudness. Moreover, the goodness of fit of the LSTM models and the behavior pattern of the data in terms of prediction of sound levels are satisfactory.This work was partially supported by the Fundacion Seneca del Centro de Coordinacion de la Investigacion de la Region de Murcia under Project 20813/PI/18.Navarro, JM.; MartĂnez-España, R.; Bueno-Crespo, A.; Cecilia-Canales, JM.; MartĂnez, R. (2020). Sound Levels Forecasting in an Acoustic Sensor Network Using a Deep Neural Network. Sensors. 20(3):1-16. https://doi.org/10.3390/s20030903S116203Hornikx, M. (2016). Ten questions concerning computational urban acoustics. Building and Environment, 106, 409-421. doi:10.1016/j.buildenv.2016.06.028Murphy, E., & King, E. A. (2010). 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(2017). A Big Data Framework for Urban Noise Analysis and Management in Smart Cities. Acta Acustica united with Acustica, 103(4), 552-560. doi:10.3813/aaa.919084LĂ€ngkvist, M., Karlsson, L., & Loutfi, A. (2014). A review of unsupervised feature learning and deep learning for time-series modeling. Pattern Recognition Letters, 42, 11-24. doi:10.1016/j.patrec.2014.01.008Che, Z., Purushotham, S., Cho, K., Sontag, D., & Liu, Y. (2018). Recurrent Neural Networks for Multivariate Time Series with Missing Values. Scientific Reports, 8(1). doi:10.1038/s41598-018-24271-9Kim, H.-G., & Kim, J. Y. (2017). Environmental sound event detection in wireless acoustic sensor networks for home telemonitoring. China Communications, 14(9), 1-10. doi:10.1109/cc.2017.8068759Luque, A., Romero-Lemos, J., Carrasco, A., & Barbancho, J. (2018). Improving Classification Algorithms by Considering Score Series in Wireless Acoustic Sensor Networks. 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Genetic mapping of microsatellite markers around the arcelin bruchid resistance locus in common bean
The deployment in common beans (Phaseolus vulgaris L.) of arcelin-based bruchid resistance could help reduce post-harvest storage losses to the Mexican bean weevil [(Zabrotes subfasciatus (Boheman)]. Arcelin is a member of the arcelin-phytohemagglutinin-α-amylase inhibitor (APA) family of seed proteins, which has been extensively studied but not widely used in bean breeding programs. The purpose of this study was to evaluate microsatellite markers for genetic analysis of arcelin-based bruchid resistance and to determine the orientation of markers and the rate of recombination around the APA locus. A total of 10 previously developed microsatellites and 22 newly developed markers based on a sequenced BAC from the APA locus were screened for polymorphism and of these 15 were mapped with an F(2) population of 157 individuals resulting from a susceptible Ă resistant cross of SEQ1006 Ă RAZ106 that segregated for both the arcelin 1 allele and resistance to the bruchid, Z. subfasciatus. Microsatellites derived from APA gene sequences were linked within 0.8 cM of each other and were placed relative to the rest of the b04 linkage group. In a comparison of genetic to physical distance on the BAC sequence, recombination was found to be moderate with a ratio of 125 kb/cM, but repressed within the APA locus itself. Several markers were predicted to be very effective for genetic studies or marker-assisted selection, based on their significant associations with bruchid resistance and on low adult insect emergence and positions flanking the arcelin and phytohemagglutinin genes
The microbiome of the uropygial secretion in hoopoes is shaped along the nesting phase
Microbial symbiont acquisition by hosts may determine the effectiveness of the mutualistic relationships. A mix of vertical and horizontal transmission may be advantageous for hosts by allowing plastic changes of microbial communities depending on environmental conditions. Plasticity is well known for gut microbiota but is poorly understood for other symbionts of wild animals. We here explore the importance of environmental conditions experienced by nestling hoopoes (Upupa epops) during the late nesting phase determining microbiota in their uropygial gland. In cross-fostering experiments of 8 days old nestlings, âsibling-siblingâ and âmother-offspringâ comparisons were used to explore whether the bacterial community naturally established in the uropygial gland of nestlings could change depending on experimental environmental conditions (i.e., new nest environment). We found that the final microbiome of nestlings was mainly explained by nest of origin. Moreover, cross-fostered nestlings were more similar to their siblings and mothers than to their stepsiblings and stepmothers. We also detected a significant effect of nest of rearing, suggesting that nestling hoopoes acquire most bacterial symbionts during the first days of life but that the microbiome is dynamic and can be modified along the nestling period depending on environmental conditions. Estimated effects of nest of rearing, but also most of those of nest of origin are associated to environmental characteristics of nests, which are extended phenotypes of parents. Thus, natural selection may favor the acquisition of appropriated microbial symbionts for particular environmental conditions found in nests.Support by funding was provided by Spanish Ministerio de EconomĂa y Competitividad, European funds (FEDER) (CGL2013-48193-C3-1-P, CGL2013-48193-C3-2-P), and Junta de AndalucĂa (P09-RNM-4557). AM-G had a predoctoral grant from the Junta de AndalucĂa (P09-RNM-4557).Peer reviewe
Femtosecond infrared intrastromal ablation and backscattering-mode adaptive-optics multiphoton microscopy in chicken corneas
The performance of femtosecond (fs) laser intrastromal ablation was evaluated with backscattering-mode adaptive-optics multiphoton microscopy in ex vivo chicken corneas. The pulse energy of the fs source used for ablation was set to generate two different ablation patterns within the corneal stroma at a certain depth. Intrastromal patterns were imaged with a custom adaptive-optics multiphoton microscope to determine the accuracy of the procedure and verify the outcomes. This study demonstrates the potential of using fs pulses as surgical and monitoring techniques to systematically investigate intratissue ablation. Further refinement of the experimental system by combining both functions into a single fs laser system would be the basis to establish new techniques capable of monitoring corneal surgery without labeling in real-time. Since the backscattering configuration has also been optimized, future in vivo implementations would also be of interest in clinical environments involving corneal ablation procedures
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