MILES extended: Stellar population synthesis models from the optical to the infrared

We present the first single-burst stellar population models which covers the optical and the infrared wavelength range between 3500 and 50000 Angstrom and which are exclusively based on empirical stellar spectra. To obtain these joint models, we combined the extended MILES models in the optical with our new infrared models that are based on the IRTF (Infrared Telescope Facility) library. The latter are available only for a limited range in terms of both age and metallicity. Our combined single-burst stellar population models were calculated for ages larger than 1 Gyr, for metallicities between [Fe/H] = -0.40 and 0.26, for initial mass functions of various types and slopes, and on the basis of two different sets of isochrones. They are available to the scientific community on the MILES web page. We checked the internal consistency of our models and compared their colour predictions to those of other models that are available in the literature. Optical and near infrared colours that are measured from our models are found to reproduce the colours well that were observed for various samples of early-type galaxies. Our models will enable a detailed analysis of the stellar populations of observed galaxies.Comment: 9 pages, 10 figures, published in A&

The star formation activity in cosmic voids

Using a sample of cosmic voids identified in the Sloan Digital Sky Survey Data Release 7, we study the star formation activity of void galaxies. The properties of galaxies living in voids are compared with those of galaxies living in the void shells and with a control sample, representing the general galaxy population. Void galaxies appear to form stars more efficiently than shell galaxies and the control sample. This result cannot be interpreted as a consequence of the bias towards low masses in underdense regions, as void galaxy subsamples with the same mass distribution as the control sample also show statistically different specific star formation rates. This highlights the fact that galaxy evolution in voids is slower with respect to the evolution of the general population. Nevertheless, when only the star-forming galaxies are considered, we find that the star formation rate is insensitive to the environment, as the main sequence is remarkably constant in the three samples under consideration. This fact implies that environmental effects manifest themselves as fast quenching mechanisms, while leaving the non-quenched galaxies almost unaffected, as their star formation activity is largely regulated by the mass of their halo. We also analyse galaxy properties as a function of void-centric distance and find that the enhancement in the star formation activity with respect to the control sample is observable up to a radial distance 1.5Rvoid. This result can be used as a suitable definition of void shells. Finally, we find that larger voids show an enhanced star formation activity in the shells with respect to their smaller counterparts, which could be related to the different dynamical evolution experienced by voids of different size

A statistical approach for rain intensity differentiation using Meteosat Second Generation-Spinning Enhanced Visible and InfraRed Imager observations

Abstract. This study exploits the Meteosat Second Generation (MSG)–Spinning Enhanced Visible and Infrared Imager (SEVIRI) observations to evaluate the rain class at high spatial and temporal resolutions and, to this aim, proposes the Rain Class Evaluation from Infrared and Visible observation (RainCEIV) technique. RainCEIV is composed of two modules: a cloud classification algorithm which individuates and characterizes the cloudy pixels, and a supervised classifier that delineates the rainy areas according to the three rainfall intensity classes, the non-rainy (rain rate value < 0.5 mm h-1) class, the light-to-moderate rainy class (0.5 mm h−1 ≤ rain rate value < 4 mm h-1), and the heavy–to-very-heavy-rainy class (rain rate value ≥ 4 mm h-1). The second module considers as input the spectral and textural features of the infrared and visible SEVIRI observations for the cloudy pixels detected by the first module. It also takes the temporal differences of the brightness temperatures linked to the SEVIRI water vapour channels as indicative of the atmospheric instability strongly related to the occurrence of rainfall events. The rainfall rates used in the training phase are obtained through the Precipitation Estimation at Microwave frequencies, PEMW (an algorithm for rain rate retrievals based on Atmospheric Microwave Sounder Unit (AMSU)-B observations). RainCEIV's principal aim is that of supplying preliminary qualitative information on the rainy areas within the Mediterranean Basin where there is no radar network coverage. The results of RainCEIV have been validated against radar-derived rainfall measurements from the Italian Operational Weather Radar Network for some case studies limited to the Mediterranean area. The dichotomous assessment related to daytime (nighttime) validation shows that RainCEIV is able to detect rainy/non-rainy areas with an accuracy of about 97% (96%), and when all the rainy classes are considered, it shows a Heidke skill score of 67% (62%), a bias score of 1.36 (1.58), and a probability of detection of rainy areas of 81% (81%)

Newborns' preference for face-relevant stimuli: effects of contrast polarity

There is currently no agreement as to how specific or general are the mechanisms underlying newborns' face preferences. We address this issue by manipulating the contrast polarity of schematic and naturalistic face-related images and assessing the preferences of newborns. We find that for both schematic and naturalistic face images, the contrast polarity is important. Newborns did not show a preference for an upright face-related image unless it was composed of darker areas around the eyes and mouth. This result is consistent with either sensitivity to the shadowed areas of a face with overhead (natural) illumination and/or to the detection of eye contact

Combined MW-IR Precipitation Evolving Technique (PET) of convective rain fields

This paper describes a new multi-sensor approach for convective rain cell continuous monitoring based on rainfall derived from Passive Microwave (PM) remote sensing from the Low Earth Orbit (LEO) satellite coupled with Infrared (IR) remote sensing Brightness Temperature (TB) from the Geosynchronous (GEO) orbit satellite. The proposed technique, which we call Precipitation Evolving Technique (PET), propagates forward in time and space the last available rain-rate (RR) maps derived from Advanced Microwave Sounding Units (AMSU) and Microwave Humidity Sounder (MHS) observations by using IR TB maps of water vapor (6.2 μm) and thermal-IR (10.8 μm) channels from a Spinning Enhanced Visible and Infrared Imager (SEVIRI) radiometer. PET is based on two different modules, the first for morphing and tracking rain cells and the second for dynamic calibration IR-RR. The Morphing module uses two consecutive IR data to identify the motion vector to be applied to the rain field so as to propagate it in time and space, whilst the Calibration module computes the dynamic relationship between IR and RR in order to take into account genesis, extinction or size variation of rain cells. Finally, a combination of the Morphing and Calibration output provides a rainfall map at IR space and time scale, and the whole procedure is reiterated by using the last RR map output until a new MW-based rainfall is available. The PET results have been analyzed with respect to two different PM-RR retrieval algorithms for seven case studies referring to different rainfall convective events. The qualitative, dichotomous and continuous assessments show an overall ability of this technique to propagate rain field at least for 2–3 h propagation time

Molecular analysis of endocrine disruption in hornyhead turbot at wastewater outfalls in southern california using a second generation multi-species microarray.

Sentinel fish hornyhead turbot (Pleuronichthysverticalis) captured near wastewater outfalls are used for monitoring exposure to industrial and agricultural chemicals of ~ 20 million people living in coastal Southern California. Although analyses of hormones in blood and organ morphology and histology are useful for assessing contaminant exposure, there is a need for quantitative and sensitive molecular measurements, since contaminants of emerging concern are known to produce subtle effects. We developed a second generation multi-species microarray with expanded content and sensitivity to investigate endocrine disruption in turbot captured near wastewater outfalls in San Diego, Orange County and Los Angeles California. Analysis of expression of genes involved in hormone [e.g., estrogen, androgen, thyroid] responses and xenobiotic metabolism in turbot livers was correlated with a series of phenotypic end points. Molecular analyses of turbot livers uncovered altered expression of vitellogenin and zona pellucida protein, indicating exposure to one or more estrogenic chemicals, as well as, alterations in cytochrome P450 (CYP) 1A, CYP3A and glutathione S-transferase-α indicating induction of the detoxification response. Molecular responses indicative of exposure to endocrine disruptors were observed in field-caught hornyhead turbot captured in Southern California demonstrating the utility of molecular methods for monitoring environmental chemicals in wastewater outfalls. Moreover, this approach can be adapted to monitor other sites for contaminants of emerging concern in other fish species for which there are few available gene sequences

Bending properties in oxidized porous silicon waveguides

The greatest limit in high-speed communications between different circuit blocks is due to the delays introduced by metal interconnections. Knock-down wire communication bottleneck is, therefore, one of the best goals that current research could reach in the held of fast electronics. A possible solution is to build fast optical links and even better if the technology is based on silicon. To attain these ends, we have made studies into possibility to fabricate optical waveguide based on oxidized porous silicon. In the last few years, such a device: was realized and characterized. Waveguiding in the visible and in the near infrared was demonstrated, With propagation losses of about 3-5 dB/cm for a light with a wavelength of 632.8 nm. Moreover, a design feature of an integrated waveguide based on oxidized porous silicon is that it offers a spontaneous bending of the waveguiding layer at its ends. The edge bending is provided by a convex camber of a leading edge of forming porous silicon. This bending can be exploited to promote a vertical light output with no use of any additional devices. The paper discusses the properties of edge bending, evaluation of the light losses depending on the radius of curvature, and analysis of possibilities to reduce these losses. (C) 2001 Elsevier Science Ltd. All rights reserved

Sustainable water use for rice agro-ecosystems in northern Italy

I n the Mediterranean basin, rice is cultivated over an area of 1,300,000 hectares. The most important rice-producing countries are Italy and Spain in Europe (72% of the EU production; 345,000 ha), and Egypt and Turkey among the extra-EU countries (almost totality of the production; 789,000 ha). Traditionally, rice is grown under continuous flooding; thus, it requires much more irrigation than non-ponded crops. The MEDWATERICE project (PRIMA-Section 2-2018; https://www.medwaterice.org/) aims at exploring sustainability of innovative rice irrigation management solutions, in order to reduce rice water consumption and environmental impacts, and to extend rice cultivation outside of traditional paddy areas to meet the escalating demand. Within the MEDWATERICE project, irrigation management options to address the main site-specific problems are being tested for each rice areas involved in the project (IT, ES, PT, EG, TR). Case studies are being conducted in pilot farms, with the involvement of Stake-Holder Panels (SHPs) in each country. Data collected at the farm level will be extrapolated to the irrigation district level, to support water management decisions and policies. Moreover, indicators for quantitative assessment of environmental, economic and social sustainability of the irrigation options will be defined. This work illustrates the first year of results for the Italian Case Study (Lomellina area, Pavia) at the pilot farm scale. This area is characterized by a growing water scarcity in drought years in many districts. Within the farm managed by the National Rice Research Center (CRR), in the agricultural season 2019 the experimentation was conducted in six plots of about 20 m x 80 m each, with two replicates for each of the following water regimes: i) water-seeded rice with continuous flooding (WFL), ii) dry-seeded rice with continuous flooding from the 3-4 leaf stage (DFL), and iii) water seeded-rice with alternate wetting and drying from fertilization at the tillering stage (AWD). One out of the two replicates of each treatment was instrumented with: water inflow and outflow meters, set of piezometers, set of tensiometers and water tubes for the irrigation management in the AWD plots. A soil survey was conducted before the agricultural season (EMI sensor and physico-chemical analysis of soil samples). Periodic measurements of crop biometric parameters (LAI, crop height, crop rooting depth) were performed. Moreover, nutrients (TN, NO3, PO4, K) and two widely used pesticides (Sirtaki \u2013 a.i. Clomazone; Tripion E \u2013 a.i. MCPA) were measured in irrigation water (inflow and outflow), groundwater, and porous cups installed at two soil depths (20 and 70 cm, above and below the plough pan). Finally, rice grain yields and quality (As and Cd in the grain) were determined. First results in terms of cumulative water balance components (rainfall, irrigation inflow and outflow, difference in soil and ponding water storage, evapotranspiration, net percolation), water application efficiency (evapotranspiration over net water input), and water productivity (grain production over net water input), will be presented and discussed. Results of a 1D Richard-equation-based numerical simulation model applied to generalize results obtained under the different irrigation regimes will be moreover illustrated

Validation of satellite OPEMW precipitation product with ground-based weather radar and rain gauge networks

Abstract. The Precipitation Estimation at Microwave Frequencies (PEMW) algorithm was developed at the Institute of Methodologies for Environmental Analysis of the National Research Council of Italy (IMAA-CNR) for inferring surface rain intensity (sri) from satellite passive microwave observations in the range from 89 to 190 GHz. The operational version of PEMW (OPEMW) has been running continuously at IMAA-CNR for two years. The OPEMW sri estimates, together with other precipitation products, are used as input to an operational hydrological model for flood alert forecast. This paper presents the validation of OPEMW against simultaneous ground-based observations from a network of 20 weather radar systems and a network of more than 3000 rain gauges distributed over the Italian Peninsula and main islands. The validation effort uses a data set covering one year (July 2011–June 2012). The effort evaluates dichotomous and continuous scores for the assessment of rain detection and quantitative estimate, respectively, investigating both spatial and temporal features. The analysis demonstrates 98% accuracy in correctly identifying rainy and non-rainy areas; it also quantifies the increased ability (with respect to random chance) to detect rainy and non-rainy areas (0.42–0.45 Heidke skill score) or rainy areas only (0.27–0.29 equitable threat score). Performances are better than average during summer, fall, and spring, while worse than average in the winter season. The spatial–temporal analysis does not show seasonal dependence except over the Alps and northern Apennines during winter. A binned analysis in the 0–15 mm h−1 range suggests that OPEMW tends to slightly overestimate sri values below 6–7 mm h−1 and underestimate sri above those values. With respect to rain gauges (weather radars), the correlation coefficient is larger than 0.8 (0.9). The monthly mean difference and standard deviation remain within ±1 and 2 mm h−1 with respect to rain gauges (respectively −2–0 and 4 mm h−1 with respect to weather radars)