Mid-infrared Data Research Articles

Genetic correlations of mid-infrared-predicted milk fatty acid groups with milk production traits

The objective of this research was to estimate the genetic correlations between milk mid-infrared-predicted fatty acid groups and production traits in first-parity Canadian Holsteins. Contents of short-chain, medium-chain, long-chain, saturated, and unsaturated fatty acid groupings in milk samples can be predicted using mid-infrared spectral data for cows enrolled in milk recording programs. Predicted fatty acid group contents were obtained for 49,127 test-day milk samples from 10,029 first-parity Holstein cows in 810 herds. Milk yield, fat and protein yield, fat and protein percentage, fat-to-protein ratio, and somatic cell score were also available for these test days. Genetic parameters were estimated for the fatty acid groups and production traits using multiple-trait random regression test day models by Bayesian methods via Gibbs sampling. Three separate 8- or 9-trait analyses were performed, including the 5 fatty acid groups with different combinations of the production traits. Posterior standard deviations ranged from <0.001 to 0.01. Average daily genetic correlations were negative and similar to each other for the fatty acid groups with milk yield (-0.62 to -0.59) and with protein yield (-0.32 to -0.25). Weak and positive average daily genetic correlations were found between somatic cell score and the fatty acid groups (from 0.25 to 0.36). Stronger genetic correlations with fat yield, fat and protein percentage, and fat-to-protein ratio were found with medium-chain and saturated fatty acid groups compared with those with long-chain and unsaturated fatty acid groups. Genetic correlations were very strong between the fatty acid groups and fat percentage, ranging between 0.88 for unsaturated and 0.99 for saturated fatty acids. Daily genetic correlations from 5 to 305 d in milk with milk, protein yield and percentage, and somatic cell score traits showed similar patterns for all fatty acid groups. The daily genetic correlations with fat yield at the beginning of lactation were decreasing for long-chain and unsaturated fatty acid groups and increasing for short-chain fatty acids. Genetic correlations between fat percentage and fatty acids were increasing at the beginning of lactation for short- and medium-chain and saturated fatty acids, but slightly decreasing for long-chain and unsaturated fatty acid groups. These results can be used in defining fatty acid traits and breeding objectives.

Symposium review: Building a better cow—The Australian experience and future perspectives

Genomic selection has led to opportunities for developing new breeding values that rely on phenotypes in dedicated reference populations of genotyped cows. In Australia, it has been applied to 2 novel traits: feed efficiency, which was released in 2015 as feed saved breeding values, and heat tolerance genomic breeding values, released for the first time in 2017. Feed saved is already included in the national breeding objective, which is focused on profitability and designed to be in line with farmer preferences. Our future focus is on traits associated with animal health, either directly or in combination with predictor traits, such as mid-infrared spectral data and, into the future, automated data capture. Although it is common for many evaluated traits to have genomic reliabilities ranging between 60 and 75%, many new, genomic information-only traits are likely to have reliabilities of less than 50%. Pooling of phenotype data internationally and investing in maintenance of reference populations is one option to increase the reliability of these traits; the other is to apply improved genomic prediction methods. For example, advances in the use of sequence data, in addition to gene expression studies, can lead to improved persistence of genomic breeding values across breeds and generations and potentially lead to greater reliabilities. Lower genomic reliabilities of novel traits could reduce the overall index reliability. However, provided these traits contribute to the overall breeding objective (e.g., profit), they are worth including. Bull selection tools and personalized genetic trends are already available, but increased access to economic and automatic capture farm data may see even better use of data to improve farm management and selection decisions.

LOFAR/H-ATLAS: the low-frequency radio luminosity–star formation rate relation

Radio emission is a key indicator of star-formation activity in galaxies, but the radio luminosity-star formation relation has to date been studied almost exclusively at frequencies of 1.4 GHz or above. At lower radio frequencies the effects of thermal radio emission are greatly reduced, and so we would expect the radio emission observed to be completely dominated by synchrotron radiation from supernova-generated cosmic rays. As part of the LOFAR Surveys Key Science project, the Herschel-ATLAS NGP field has been surveyed with LOFAR at an effective frequency of 150 MHz. We select a sample from the MPA-JHU catalogue of SDSS galaxies in this area: the combination of Herschel, optical and mid-infrared data enable us to derive star-formation rates (SFRs) for our sources using spectral energy distribution fitting, allowing a detailed study of the low-frequency radio luminosity--star-formation relation in the nearby Universe. For those objects selected as star-forming galaxies (SFGs) using optical emission line diagnostics, we find a tight relationship between the 150 MHz radio luminosity ($L_{150}$) and SFR. Interestingly, we find that a single power-law relationship between $L_{150}$ and SFR is not a good description of all SFGs: a broken power law model provides a better fit. This may indicate an additional mechanism for the generation of radio-emitting cosmic rays. Also, at given SFR, the radio luminosity depends on the stellar mass of the galaxy. Objects which were not classified as SFGs have higher 150-MHz radio luminosity than would be expected given their SFR, implying an important role for low-level active galactic nucleus activity.

Quasar Photometric Redshifts and Candidate Selection: A New Algorithm Based on Optical and Mid-infrared Photometric Data

Abstract We present a new algorithm to estimate quasar photometric redshifts (photo-zs), by considering the asymmetries in the relative flux distributions of quasars. The relative flux models are built with multivariate Skew-t distributions in the multidimensional space of relative fluxes as a function of redshift and magnitude. For 151,392 quasars in the SDSS, we achieve a photo-z accuracy, defined as the fraction of quasars with the difference between the photo-z z p and the spectroscopic redshift z s , within 0.1, of 74%. Combining the WISE W1 and W2 infrared data with the SDSS data, the photo-z accuracy is enhanced to 87%. Using the Pan-STARRS1 or DECaLS photometry with WISE W1 and W2 data, the photo-z accuracies are 79% and 72%, respectively. The prior probabilities as a function of magnitude for quasars, stars, and galaxies are calculated, respectively, based on (1) the quasar luminosity function, (2) the Milky Way synthetic simulation with the Besançon model, and (3) the Bayesian Galaxy Photometric Redshift estimation. The relative fluxes of stars are obtained with the Padova isochrones, and the relative fluxes of galaxies are modeled through galaxy templates. We test our classification method to select quasars using the DECaLS g, r, z, and WISE W1 and W2 photometry. The quasar selection completeness is higher than 70% for a wide redshift range , and a wide magnitude range mag. Our photo-z regression and classification method has the potential to extend to future surveys. The photo-z code will be publicly available.

Post-wildfire Erosion in Mountainous Terrain Leads to Rapid and Major Redistribution of Soil Organic Carbon

Catchments impacted by wildfire typically experience elevated rates of post-fire erosion and formation and deposition of pyrogenic carbon (PyC). To better understand the role of erosion in post-fire soil carbon dynamics, we determined distribution of soil organic carbon in different chemical fractions before and after the Gondola fire in South Lake Tahoe, CA. We analyzed soil samples from eroding and depositional landform positions in control and burned plots pre- and post-wildfire (in 2002, 2003, and 10-years post-fire in 2013). We determined elemental concentrations, stable isotope compositions, and biochemical composition of organic matter (OM) using mid-infrared (MIR) spectroscopy for all of the samples. A subset of samples was analyzed by 13C cross polarization magic angle spinning nuclear magnetic resonance spectroscopy (CPMAS 13C-NMR). We combined the MIR and CPMAS 13C-NMR data in the Soil Carbon Research Program partial least squares regression model to predict distribution of soil carbon into three different fractions: 1) particulate, humic, and resistant organic matter fractions representing relatively fresh larger pieces of OM, 2) fine, decomposed OM, and 3) pyrogenic C, respectively. Samples from the post-fire eroding landform position showed no major difference in soil organic carbon (SOC) fractions one year post-fire. The depositional samples, however, had increased concentrations of all SOC fractions, particularly the fraction that resembles PyC, one year post-fire (2002), which had a mean of 160 g/kg compared with burned hillslope soils, which had 84 g/kg. The increase in all SOC fractions in the post-fire depositional landform position one year post-fire indicates significant lateral mobilization of the eroded PyC. In addition, our NMR analyses revealed a post-fire increase in both the aryl and O-aryl carbon compounds in the soils from the depositional landform position, indicating increases in soil PyC concentrations post-fire. After 10 years, the C concentration from all three fractions declined in the depositional landform position to below pre-fire levels likely due to further erosion or elevated rates of decomposition. Thus, we found, at this site, that both fire and erosion exert significant influence on the distribution of PyC throughout a landscape and its long-term fate in the soil system.

A pilot study on fingerprinting Leishmania species from the Old World using Fourier transform infrared spectroscopy

Leishmania species are protozoan parasites and the causative agents of leishmaniasis, a vector borne disease that imposes a large health burden on individuals living mainly in tropical and subtropical regions. Different Leishmania species are responsible for the distinct clinical patterns, such as cutaneous, mucocutaneous, and visceral leishmaniasis, with the latter being potentially fatal if left untreated. For this reason, it is important to perform correct species identification and differentiation. Fourier transform infrared spectroscopy (FTIR) is an analytical spectroscopic technique increasingly being used as a potential tool for identification of microorganisms for diagnostic purposes. By employing mid-infrared (MIR) spectral data, it is not only possible to assess the chemical structures but also to achieve differentiation supported by multivariate statistic analysis. This work comprises a pilot study on differentiation of Leishmania species of the Old World (L. major, L. tropica, L. infantum, and L. donovani) as well as hybrids of distinct species by using vibrational spectroscopic fingerprints. Films of intact Leishmania parasites and their deoxyribonucleic acid (DNA) were characterized comparatively with respect to their biochemical nature and MIR spectral patterns. The strains’ hyperspectral datasets were multivariately examined by means of variance-based principal components analysis (PCA) and distance-based hierarchical cluster analysis (HCA). With the implementation of MIR spectral datasets we show that a phenotypic differentiation of Leishmania at species and intra-species level is feasible. Thus, FTIR spectroscopy can be further exploited for building up spectral databases of Leishmania parasites in view of high-throughput analysis of clinical specimens.Graphical abstractFor Leishmania species discrimination, sample films of intact parasites and their extracted DNA were analyzed by FTIR micro-spectroscopy. Hyperspectral datasets that comprise mid-infrared fingerprints were submitted to multivariate analysis tools such as principal components analysis (PCA) and hierarchical cluster analysis (HCA).

Compressed H3S: inter-sublattice Coulomb coupling in a high-TC superconductor

Upon thermal annealing at or above room temperature (RT) and at high hydrostatic pressure P ~ 155 GPa, sulfur trihydride H3S exhibits a measured maximum superconducting transition temperature TC ~ 200 K. Various theoretical frameworks incorporating strong electron–phonon coupling and Coulomb repulsion have reproduced this record-level TC. Of particular relevance is that experimentally observed H–D isotopic correlations among TC, P, and annealed order indicate an H–D isotope effect exponent α limited to values ⩽ 0.183, leaving open for consideration unconventional high-TC superconductivity with electronic-based enhancements. The work presented herein examines Coulombic pairing arising from interactions between neighboring S and H species on separate interlaced sublattices constituting H3S in the Imm structure. The optimal value of the transition temperature is calculated from TC0 = Λe2/ζ, with Λ = 0.007465 Å, inter-sublattice S–H separation spacing ζ = a0/, interaction charge linear spacing = a0 (3/σ)1/2, average participating charge fraction σ = 3.43 ± 0.10 estimated from calculated H-projected electron states, and lattice parameter a0 = 3.0823 Å at P = 155 GPa. The resulting value of TC0 = 198.5 ± 3.0 K is in excellent agreement with transition temperatures determined from resistivity (196–200 K onsets, 190–197 K midpoints), susceptibility (200 K onset), and critical magnetic fields (203.5 K by extrapolation). Analysis of mid-infrared reflectivity data confirms the expected correlation between boson energy and ζ−1. Suppression of TC below TC0, correlating with increasing residual resistance for < RT annealing, is treated in terms of scattering-induced pair breaking. Correspondences between H3S and layered high-TC superconductor structures are also discussed, and a model considering Compton scattering of virtual photons of energies ⩽ e2/ζ by inter-sublattice electrons is introduced, illustrating that Λ ∝ ƛC, where ƛC is the reduced electron Compton wavelength.

On the inner disc structure of MWC480: evidence for asymmetries?

Studying the physical conditions structuring the young circumstellar disks is required for understanding the onset of planet formation. Of particular interest is the protoplanetary disk surrounding the Herbig star MWC480. The structure and properties of the circumstellar disk of MWC480 are studied by infrared interferometry and interpreted from a modeling approach. New observations are driving this study, in particular some recent Very Large Telescope Interferometer (VLTI)/MIDI data acquired in December 2013. Our one-component disk model could not reproduce simultaneously all our data: the Spectral Energy Distribution, the near-infrared Keck Interferometer data and the mid-infrared data obtained with the MIDI instrument. In order to explain all measurements, one possibility is to add an asymmetry in our one-component disk model with the assumption that the structure of the disk of MWC480 has not varied with time. Several scenarios are tested, and the one considering the presence of an azimuthal bright feature in the inner component of the disk model provides a better fit of the data. (In this study, we assumed that the size of the outer disk of MWC480 to be 20 au since most of the near and mid-IR emissions come from below 20 au. In our previous study (Jamialahmadi et al. 2015), we adopted an outer radius of 80 au, which is consistent with the value found by previous studies based on mm observations).

Galactic supernova remnant candidates discovered by THOR

There is a considerable deficiency in the number of known supernova remnants (SNRs) in the Galaxy compared to that expected. Searches for extended low-surface brightness radio sources may find new Galactic SNRs, but confusion with the much larger population of HII regions makes identifying such features challenging. SNRs can, however, be separated from HII regions using their significantly lower mid-infrared (MIR) to radio continuum intensity ratios. We use the combination of high-resolution 1-2 GHz continuum data from The HI, OH, Recombination line survey of the Milky Way (THOR) and lower-resolution VLA 1.4 GHz Galactic Plane Survey (VGPS) continuum data, together with MIR data from the Spitzer GLIMPSE, Spitzer MIPSGAL, and WISE surveys to identify SNR candidates. To ensure that the candidates are not being confused with HII regions, we exclude radio continuum sources from the WISE Catalog of Galactic HII Regions, which contains all known and candidate H II regions in the Galaxy. We locate 76 new Galactic SNR candidates in the THOR and VGPS combined survey area of 67.4deg>l>17.5deg, |b|<1.25deg and measure the radio flux density for 52 previously-known SNRs. The candidate SNRs have a similar spatial distribution to the known SNRs, although we note a large number of new candidates near l=30deg, the tangent point of the Scutum spiral arm. The candidates are on average smaller in angle compared to the known regions, 6.4'+/-4.7' versus 11.0'+/-7.8', and have lower integrated flux densities. If the 76 candidates are confirmed as true SNRs, for example using radio polarization measurements or by deriving radio spectral indices, this would more than double the number of known Galactic SNRs in the survey area. This large increase would still, however, leave a discrepancy between the known and expected SNR populations of about a factor of two.

The earliest phases of high-mass star formation, as seen in NGC 6334 by Herschel-HOBYS

Aims. To constrain models of high-mass star formation, the Herschel-HOBYS key program aims at discovering massive dense cores (MDCs) able to host the high-mass analogs of low-mass prestellar cores, which have been searched for over the past decade. We here focus on NGC 6334, one of the best-studied HOBYS molecular cloud complexes. Methods. We used Herschel/PACS and SPIRE 70−500 μm images of the NGC 6334 complex complemented with (sub)millimeter and mid-infrared data. We built a complete procedure to extract ~0.1 pc dense cores with the getsources software, which simultaneously measures their far-infrared to millimeter fluxes. We carefully estimated the temperatures and masses of these dense cores from their spectral energy distributions (SEDs). We also identified the densest pc-scale cloud structures of NGC 6334, one 2 pc × 1 pc ridge and two 0.8 pc × 0.8 pc hubs, with volume-averaged densities of ~105 cm-3. Results. A cross-correlation with high-mass star formation signposts suggests a mass threshold of 75 M⊙ for MDCs in NGC 6334. MDCs have temperatures of 9.5−40 K, masses of 75−1000 M⊙, and densities of 1 × 105−7 × 107 cm-3. Their mid-infrared emission is used to separate 6 IR-bright and 10 IR-quiet protostellar MDCs while their 70 μm emission strength, with respect to fitted SEDs, helps identify 16 starless MDC candidates. The ability of the latter to host high-mass prestellar cores is investigated here and remains questionable. An increase in mass and density from the starless to the IR-quiet and IR-bright phases suggests that the protostars and MDCs simultaneously grow in mass. The statistical lifetimes of the high-mass prestellar and protostellar core phases, estimated to be 1−7 × 104 yr and at most 3 × 105 yr respectively, suggest a dynamical scenario of high-mass star formation. Conclusions. The present study provides good mass estimates for a statistically significant sample, covering the earliest phases of high-mass star formation. High-mass prestellar cores may not exist in NGC 6334, favoring a scenario presented here, which simultaneously forms clouds, ridges, MDCs, and high-mass protostars.

The VLA-COSMOS 3 GHz Large Project: Multiwavelength counterparts and the composition of the faint radio population

(abridged) We study the composition of the faint radio population selected from the VLA-COSMOS 3GHz Large Project. The survey covers a 2.6sq.deg. area with a mean rms of ~2.3uJy/b, cataloging 10830 sources (>5sigma). Combining these radio data with optical, near-infrared (UltraVISTA), mid-infrared (Spitzer/IRAC) data, and X-ray data (Chandra), we find counterparts to radio sources for ~93% of the radio sample (in the areas of the COSMOS field not affected by saturated or bright sources in the optical to NIR bands), reaching out to z<6. We further classify the sources as star forming galaxies or AGN based on various criteria, such as X-ray luminosity, observed MIR color, UV-FIR spectral-energy distribution, rest-frame NUV-optical color corrected for dust extinction, and radio-excess relative to that expected from the hosts' star-formation rate. We separate the AGN into sub-samples dominated by low-to-moderate and moderate-to-high radiative luminosity AGN, candidates for high-redshift analogues to local low- and high-excitation emission line AGN, respectively. We study the fractional contributions of these sub-populations down to radio flux levels of ~11uJy at 3GHz (or ~20uJy at 1.4GHz assuming a spectral index of -0.7). We find that the dominant fraction at 1.4GHz flux densities above ~200uJy is constituted of low-to-moderate radiative luminosity AGN. Below densities of ~100uJy the fraction of star-forming galaxies increases to ~60%, followed by the moderate-to-high radiative luminosity AGN (~20%), and low-to-moderate radiative luminosity AGN (~20%). Based on this observational evidence, we extrapolate the fractions down to sensitivities of the SKA. Our estimates suggest that at the faint flux limits to be reached by the SKA1 surveys, a selection based only on radio flux limits can provide a simple tool to efficiently identify samples highly (>75%) dominated by star-forming galaxies.

The ATLASGAL survey: The sample of young massive cluster progenitors

The progenitors of high-mass stars and clusters are still challenging to recognise. Only unbiased surveys, sensitive to compact regions of high dust column density, can unambiguously reveal such a small population of particularly massive and cold clumps. Here we study a flux limited sample of compact sources from the ATLASGAL survey to identify a sample of candidate progenitors of massive clusters in the inner Galaxy. Sensitive mid-infrared data at 21-24 $\mu$m from the WISE and MIPSGAL surveys were explored to search for embedded objects, and complementary spectroscopic data were used to investigate their stability and star formation activity. Based on such ancillary data we identify an unbiased sample of infrared-quiet massive clumps in the Galaxy that potentially represent the earliest stages of massive cluster formation. An important fraction of this sample consists of sources that have not been studied in detail before. Comparing their properties to clumps hosting more evolved embedded objects, we find that they exhibit similar physical properties in terms of mass and size, suggesting that infrared-quiet massive clumps are not only capable of forming high-mass stars, but likely also follow a single evolutionary track leading to the formation of massive clusters. The majority of the sources are not in virial-equilibrium, suggesting collapse on the clump scale. This is in line with the low number of infrared-quiet massive clumps and earlier findings that star formation, in particular for high-mass objects is a fast, dynamic process. We propose a scenario in which massive clumps start to fragment and collapse before their final mass is accumulated indicating that strong self-gravity and global collapse is needed to build up rich clusters and the most massive stars.

Prediction of milk fatty acid content with mid-infrared spectroscopy in Canadian dairy cattle using differently distributed model development sets

The fatty acid profile of milk is a prevailing issue due to the potential negative or positive effects of different fatty acids to human health and nutrition. Mid-infrared spectroscopy can be used to obtain predictions of otherwise costly fatty acid phenotypes in a widespread and rapid manner. The objective of this study was to evaluate the prediction of fatty acid content for the Canadian dairy cattle population from mid-infrared spectral data and to compare the results produced by altering the partial least squares (PLS) model development set used. The PLS model development sets used to develop the predictions were reference fatty acids expressed as (1) grams per 100 g of fatty acid, (2) grams per 100 g of milk, (3) the natural logarithmic transform of grams per 100 g of milk, and (4) subsets of samples randomly selected by removing excess records around the mean to present a more uniform distribution, repeated 10 times. Gas chromatography measured fatty acid concentration and spectral data for 2,023 milk samples of 373 cows from 4 breeds and 44 herds were used in the model development. The coefficient of determination of cross-validation (Rcv2) increased when fatty acids were expressed on a per 100 g of milk basis compared with on a per 100 g of fat basis for all examined fatty acids. The logarithmic transformation used to create a more Gaussian distribution in the development set had little effect on the prediction accuracy. The individual fatty acids C12:0, C14:0, C16:0, C18:0, C18:1n-9 cis, and saturated, monounsaturated, unsaturated, short-chain, medium-chain, and long-chain fatty acid groups had (Rcv2) greater than 0.70. When model development was performed with subsets of the original samples, slight increases in (Rcv2) values were observed for the majority of fatty acids. The difference in (Rcv2) between the top- and bottom-performing prediction equation across the different subsets for a single predicted fatty acid was on average 0.055 depending on which samples were randomly selected to be used in the PLS model development set. Predictions for fatty acids with high accuracies can be used to monitor fatty acid contents for cows in milk recording programs and possibly for genetic evaluation.

Nanoscale modeling of electro-plasmonic tunable devices for modulators and metasurfaces.

The interest in plasmonic electro-optical modulators with nanoscale footprint and ultrafast low-energy performance has generated a demand for precise multiphysics modeling of the electrical and optical properties of plasmonic nanostructures. We perform combined simulations that account for the interaction of highly confined nearfields with charge accumulation and depletion on the nanoscale. Validation of our numerical model is done by comparison to a recently published reflective meta-absorber. The simulations show excellent agreement to the experimental mid-infrared data. We then use our model to propose electro-optical modulation of the extinction cross-section of a gold dimer nanoantenna at the telecom wavelength of 1550 nm. An ITO gap-loaded nanoantenna structure allows us to achieve a normalized modulation of 45% at 1550 nm, where the gap-load design circumvents resonance pinning of the structure. Resonance pinning limits the performance of simplistic designs such as a uniform coating of the nanoantenna with a sheet of indium tin oxide, which we also present for comparison. This large value is reached by a reduction of the capacitive coupling of the antenna arms, which breaks the necessity of a large volume overlap between the charge distribution and the optical nearfield. A parameter exploration shows a weak reliance on the exact device dimensions, as long as strong coupling inside the antenna gap is ensured. These results open the way for a new method in electro-optical tuning of plasmonic structures and can readily be adapted to plasmonic waveguides, metasurfaces and other electro-optical modulators.

Evaluating regression-kriging for mid-infrared spectroscopy prediction of soil properties in western Kenya

In this study, the utility of regression-kriging was investigated in building prediction models for soil properties using mid-infrared (7498 to 600cm−1) spectral data for soil samples collected from Nyando, Nzoia and Yala catchment areas in Kenya, sampled at 0–20cm and 20–50cm depths. Using a systematic technique, 158 samples were selected for analysis of a number of soil properties of interest using wet chemistry methods. We randomly divided the dataset into two groups: 118 samples in the calibration and 40 samples in the holdout validation set. The calibration set was first used to develop partial least squares regression (PLS) models for all the soil properties. Residuals from these models were used to generate semivariograms, which revealed a strong spatial dependence as determined by the ratio of nugget to sill for nitrogen, 9%; Al, 12%; and B, 36%, but with weak spatial dependence for exchangeable Ca (ExCa), 100%; and carbon, 76%. The fitted theoretical semivariograms were used to fit regression-kriging models. Lastly, both the PLS and regression-kriging models were assessed with the validation set and their prediction performance evaluated by R2 and root mean square error (RMSE). The results showed that regression kriging method gave lower RMSE values for all the evaluated soil properties except for ExCa, B and exchangeable acidity, with the best predictions, compared with the PLS model, obtained for ExMg (R2, 0.93 vs 0.88; RMSE, 6.1 vs 8.4cmolckg−1) and total nitrogen (R2=0.92 vs R2=0.74; RMSE, 0.11%, RMSE=0.2%). In this study, regression-kriging, which takes into account spatial variation normally ignored by other methods, improved use of infrared spectroscopy for predicting soil properties.

THE CURRENT STATUS OF THE AKARI MID-INFRARED ALL-SKY DIFFUSE MAPS

We are creating all-sky diffuse maps from the AKARI mid-infrared survey data with the two photometric bands centered at wavelengths of 9 and <TEX>$18{\mu}m$</TEX>. The AKARI mid-infrared diffuse maps achieve higher spatial resolution and higher sensitivity than the IRAS maps. In particular, the <TEX>$9{\mu}m$</TEX> data are unique resources as an all-sky tracer of the emission of polycyclic aromatic hydrocarbons (PAHs). However, the original data suffer many artifacts. Thus, we have been developing correction methods. Among them, we have recently improved correction methods for the non-linearity and the reset anomaly of the detector response. These corrections successfully reduce the artifact level down to <TEX>$0.1MJy\;sr^{-1}$</TEX> on average, which is essential for discussion on faint extended emission (e.g., the Galactic PAH emission). We have also made progress in the subtraction of the scattered light caused in the camera optics. We plan to release the improved diffuse maps to the public within a year.

Star Formation In Nearby Clouds (SFiNCs): X-Ray and Infrared Source Catalogs and Membership

Abstract The Star Formation in Nearby Clouds (SFiNCs) project is aimed at providing a detailed study of the young stellar populations and of star cluster formation in the nearby 22 star-forming regions (SFRs) for comparison with our earlier MYStIX survey of richer, more distant clusters. As a foundation for the SFiNCs science studies, here, homogeneous data analyses of the Chandra X-ray and Spitzer mid-infrared archival SFiNCs data are described, and the resulting catalogs of over 15,300 X-ray and over 1,630,000 mid-infrared point sources are presented. On the basis of their X-ray/infrared properties and spatial distributions, nearly 8500 point sources have been identified as probable young stellar members of the SFiNCs regions. Compared to the existing X-ray/mid-infrared publications, the SFiNCs member list increases the census of YSO members by 6%–200% for individual SFRs and by 40% for the merged sample of all 22 SFiNCs SFRs.

Orion revisited

This paper continues our study of the foreground population to the Orion molecular clouds. The goal is to characterize the foreground population north of NGC 1981 and to investigate the star formation history in the large Orion star-forming region. We focus on a region covering about 25 square degrees, centered on the $\epsilon$ Orionis supergiant (HD 37128, B0\,Ia) and covering the Orion Belt asterism. We used a combination of optical (SDSS) and near-infrared (2MASS) data, informed by X-ray (\textit{XMM-Newton}) and mid-infrared (WISE) data, to construct a suite of color-color and color-magnitude diagrams for all available sources. We then applied a new statistical multiband technique to isolate a previously unknown stellar population in this region. We identify a rich and well-defined stellar population in the surveyed region that has about 2\,000 objects that are mostly M stars. We infer the age for this new population to be at least 5\, Myr and likely $\sim10$\,Myr and estimate a total of about 2\,500 members, assuming a normal IMF. This new population, which we call the Orion Belt population, is essentially extinction-free, disk-free, and its spatial distribution is roughly centered near $\epsilon$ Ori, although substructure is clearly present. The Orion Belt population is likely the low-mass counterpart to the Ori OB Ib subgroup. Although our results do not rule out Blaauw's sequential star formation scenario for Orion, we argue that the recently proposed blue streams scenario provides a better framework on which one can explain the Orion star formation region as a whole. We speculate that the Orion Belt population could represent the evolved counterpart of an Orion nebula-like cluster.

The Bok globule BHR 160: structure and star formation

BHR 160 is a virtually unstudied cometary globule within the Sco OB4 association in Scorpius at a distance of 1600pc. It is part of a system of cometary clouds which face the luminous O star HD155806. BHR 160 is special because it has an intense bright rim. We attempt to derive physical parameters for BHR 160 and to understand its structure and the origin of its peculiar bright rim. BHR 160 was mapped in the $^{12}$CO, $^{13}$CO and C$^{18}$O (2-1) and (1-0) and CS (3-2) and (2-1) lines. These data, augmented with stellar photometry derived from the ESO VVV survey, were used to derive the mass and distribution of molecular material in BHR 160 and its surroundings. Archival mid-infrared data from the WISE satellite was used to find IR excess stars in the globule and its neighbourhood. An elongated 1' by 0.6' core lies adjacent to the globule bright rim. $^{12}$CO emission covers the whole globule, but the $^{13}$CO, C$^{18}$O and CS emission is more concentrated to the core. The $^{12}$CO line profiles indicate the presence of outflowing material near the core, but the spatial resolution of the mm data is not sufficient for a detailed spatial analysis. The BHR 160 mass estimated from the C$^{18}$O mapping is 100$\pm$50Msun(d/1.6kpc)$^2$ where d is the distance to the globule. Approximately 70 percent of the mass lies in the dense core. The total mass of molecular gas in the direction of BHR 160 is 210$\pm$(d/1.6kpc)$^2$ Msun when estimated from the more extended VVV NIR photometry. We argue that the bright rim of BHR 160 is produced by a close-by early B-type star, HD 319648, that was likely recently born in the globule. This star is likely to have triggered the formation of a source, IRS 1, that is embedded within the core of the globule and detected only in Ks and by WISE and IRAS.

Radio and infrared study of the star-forming region IRAS 20286+4105

A multi-wavelength investigation of the star forming complex IRAS 20286+4105, located in the Cygnus-X region, is presented here. Near-infrared K-band data is used to revisit the cluster / stellar group identified in previous studies. The radio continuum observations, at 610 and 1280 MHz show the presence of a HII region possibly powered by a star of spectral type B0 - B0.5. The cometary morphology of the ionized region is explained by invoking the bow-shock model where the likely association with a nearby supernova remnant is also explored. A compact radio knot with non-thermal spectral index is detected towards the centre of the cloud. Mid-infrared data from the Spitzer Legacy Survey of the Cygnus-X region show the presence of six Class I YSOs inside the cloud. Thermal dust emission in this complex is modelled using Herschel far-infrared data to generate dust temperature and column density maps. Herschel images also show the presence of two clumps in this region, the masses of which are estimated to be {\sim} 175 M{\sun} and 30 M{\sun}. The mass-radius relation and the surface density of the clumps do not qualify them as massive star forming sites. An overall picture of a runaway star ionizing the cloud and a triggered population of intermediate-mass, Class I sources located toward the cloud centre emerges from this multiwavelength study. Variation in the dust emissivity spectral index is shown to exist in this region and is seen to have an inverse relation with the dust temperature.