Abstract
We present structural parameters from a wide-field homogeneous imaging survey of Milky Way satellites carried out with the MegaCam imagers on the 3.6 m Canada–France–Hawaii Telescope and 6.5 ...m Magellan-Clay telescope. Our survey targets an unbiased sample of “outer halo” satellites (i.e., substructures having galactocentric distances greater than 25 kpc) and includes classical dSph galaxies, ultra-faint dwarfs, and remote globular clusters. We combine deep, panoramic
gr
imaging for 44 satellites and archival
gr
imaging for 14 additional objects (primarily obtained with the DECam instrument as part of the Dark Energy Survey) to measure photometric and structural parameters for 58 outer halo satellites. This is the largest and most uniform analysis of Milky Way satellites undertaken to date and represents roughly three-quarters (58/81 ≃ 72%) of all known outer halo satellites. We use a maximum-likelihood method to fit four density laws to each object in our survey: exponential, Plummer, King, and Sérsic models. We systematically examine the isodensity contour maps and color–magnitude diagrams for each of our program objects, present a comparison with previous results, and tabulate our best-fit photometric and structural parameters, including ellipticities, position angles, effective radii, Sérsic indices, absolute magnitudes, and surface brightness measurements. We investigate the distribution of outer halo satellites in the size–magnitude diagram and show that the current sample of outer halo substructures spans a wide range in effective radius, luminosity, and surface brightness, with little evidence for a clean separation into star cluster and galaxy populations at the faintest luminosities and surface brightnesses.
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•Ball-milled and < 2 mm soils showed similar accuracy in MIR and NIR spectral models.•Grinding soils did not improve the accuracy in both MIR and NIR models.•MIR/NIR spectroscopy can ...distinguish first horizon from subsurface horizon soils.•Chemical information is the same in ball-milled and < 2 mm spectra models.•MIR/NIR spectroscopy can be used to determine a range of soil attributes.
This study evaluated the influence on predicted physical and chemical parameters of soil particle sizes commonly used in the infrared spectra acquisition, < 0.100 mm (ball-milled) and < 2 mm for MIR and NIR ranges, respectively. The influences were evaluated through the accuracy (RMSEP and RPIQ) results and the chemical information extracted by multivariate classification and regression models. For this a national population of soils containing 888 samples from 225 modal soil profiles, each with the reference values of sand, silt, clay, pH(CaCl2), pH(Water), total carbon, organic carbon (OC), cation exchange capacity, nitrogen, aluminium and bulk density, was used. Spectra were collected in MIR and NIR ranges using samples with both particle sizes. For each soil attribute, 29 random calibration and validation sets were generated and SVM, PLS and Cubist regression models were built. This same strategy was used to classify the soil samples according to their respective horizons (1 or 2-7) using SVM, PLS-DA and random forest algorithms. Results obtained by the randomised calibration and validation set did not present positive or negative bias on the RMSEP and RPIQ values based on soil particle sizes. In general, random variations of the RMSEP and RPIQ values were observed for all soil attributes. In addition, ball-milled and < 2 mm spectral models did not present large differences in both accuracy parameters simultaneously. The median Matthews correlation coefficient values calculated by the classification models showed minor variations of 2.61% and 0.65% for samples from both particle sizes in MIR and NIR ranges, respectively. The ‘Variable Importance in Projection’ or VIP scores, calculated by PLS and PLS-DA models, did not show any large variation in the chemical information extracted from MIR and NIR spectra for models built using samples from both particle sizes. The results from this study show that scanning ball-milled or < 2 mm sieved soil samples will result in spectra models in MIR and NIR ranges with the same accuracy and same chemical information. This suggests there is a big potential to eliminate the ball-milling sample step in soil laboratories that use MIR and NIR vibrational spectroscopy techniques to predict soil attributes, thereby reducing the time and costs associated with soil analysis.
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•MIR predicts soil phosphorus (P) sorption maximum sorption capacity (Smax) with high accuracy.•The benchtop instrument demonstrated high efficiency and accuracy in predicting soil ...Smax without the need for sample ball-milling.•The handheld instrument can robustly predict soil Smax from ball-milled samples only.•The handheld spectrometer can be used to classify soil P sorption using 2 mm sieved samples.
Traditional soil phosphorus (P) sorption capacity is examined from a Langmuir isotherm batch technique, which is time-consuming, labour intensive and generates chemical waste. In this work, we provide an efficient and convenient technique with MIR spectroscopy to predict the Langmuir parameter of soil P sorption maximum capacity (Smax, mg·kg−1).
Four spectral libraries from benchtop (Bruker) and handheld (Agilent) MIR spectrometers were built with samples in two particle size ranges, <0.100 mm (ball-milled) and <2 mm. respectively. Using an archive of samples with a database of sorption parameters, soils were classified into ‘low’ and ‘high’ sorption capacities. Chemometric regression models of partial least squares (PLS), Cubist, support vector machine (SVM) regression and random forest (RF) were evaluated for Smax prediction. Bruker spectral libraries with both soil particle sizes yielded ‘excellent models’, with SVM predicting Smax values with high accuracy (RPIQV = 4.50 and 4.25 for the spectral libraries of the ball-milled and <2 mm samples, respectively). In comparison, the Agilent handheld spectral libraries contained more noise and less resolution. For Agilent MIR spectroscopy, more homogeneous samples after ball milling resulted in a higher accurate Smax prediction. For Agilent libraries of ball-milled samples, an ‘approximate quantitative model’ (RPIQV = 2.74) was obtained from the raw spectra using the Cubist algorithm. However, for Agilent spectroscopy of <2 mm samples, the best performing Cubist algorithm can only achieve a ‘fair model’ (RPIQV=2.23) with the potential to discriminate between ‘low’ and ‘high’ Smax values.
The results suggest that the benchtop spectrometer can predict the Langmuir Smax value with high accuracy without the need to ball mill samples. However, the handheld spectrometer can only make approximate quantitative predictions of Smax for ball-milled samples. For <2 mm samples, Agilent can only be used to classify ‘low’ and ‘high’ sorption capacity soils.
The Hercules stream as seen by APOGEE-2 South Hunt, Jason A. S; Bovy, Jo; Pérez-Villegas, Angeles ...
Monthly Notices of the Royal Astronomical Society,
02/2018, Volume:
474, Issue:
1
Journal Article
Peer reviewed
Open access
Abstract
The Hercules stream is a group of comoving stars in the solar neighbourhood, which can potentially be explained as a signature of either the outer Lindblad resonance (OLR) of a fast Galactic ...bar or the corotation resonance (CR) of a slower bar. In either case, the feature should be present over a large area of the disc. With the recent commissioning of the APOGEE-2 Southern spectrograph we can search for the Hercules stream at (l, b) = (270°, 0), a direction in which the Hercules stream, if caused by the bar's OLR, would be strong enough to be detected using only the line-of-sight velocities. We clearly detect a narrow, Hercules-like feature in the data that can be traced from the solar neighbourhood to a distance of about 4 kpc. The detected feature matches well the line-of-sight velocity distribution from the fast-bar (OLR) model. Confronting the data with a model where the Hercules stream is caused by the CR of a slower bar leads to a poorer match, as the corotation model does not predict clearly separated modes, possibly because the slow-bar model is too hot.
Abstract
The Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2) is a dual-hemisphere, near-infrared (NIR), spectroscopic survey with the goal of producing a chemodynamical mapping of ...the Milky Way. The targeting for APOGEE-2 is complex and has evolved with time. In this paper, we present the updates and additions to the initial targeting strategy for APOGEE-2N presented in Zasowski et al. (2017). These modifications come in two implementation modes: (i) “Ancillary Science Programs” competitively awarded to Sloan Digital Sky Survey IV PIs through proposal calls in 2015 and 2017 for the pursuit of new scientific avenues outside the main survey, and (ii) an effective 1.5 yr expansion of the survey, known as the Bright Time Extension (BTX), made possible through accrued efficiency gains over the first years of the APOGEE-2N project. For the 23 distinct ancillary programs, we provide descriptions of the scientific aims, target selection, and how to identify these targets within the APOGEE-2 sample. The BTX permitted changes to the main survey strategy, the inclusion of new programs in response to scientific discoveries or to exploit major new data sets not available at the outset of the survey design, and expansions of existing programs to enhance their scientific success and reach. After describing the motivations, implementation, and assessment of these programs, we also leave a summary of lessons learned from nearly a decade of APOGEE-1 and APOGEE-2 survey operations. A companion paper, F. Santana et al. (submitted; AAS29036), provides a complementary presentation of targeting modifications relevant to APOGEE-2 operations in the Southern Hemisphere.
Precision agriculture requires faster and automatic responses for fertility parameters, especially regarding soil organic matter (SOM). In Brazil, the standard methodology for SOM determination is a ...wet procedure based on the oxidation of the sample by an excess of potassium dichromate based on Walkley–Black method. This methodology has serious drawbacks, since, at a national level, generates approximately 600,000 L/year of toxic acid waste containing Cr3+ and possibly Cr6+, besides time consuming and expensive. Herein, we present a faster green methodology that can eliminate the generation of these hazardous wastes and reduces the costs of analysis by approximately 80%, democratizing the soil fertility information and increasing the productivity. The methodology is based on the use of a national near infrared spectral library with approximately 43,000 samples and learning machine data analysis based on a random forest algorithm. The methodology was validated by submitting the prediction results of 12 blind soil samples to a proficiency assay used for fertility soil laboratories qualification, receiving the maximum quality excellence index, indicating that it is suitable for use in routine analysis.
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•Soil organic matter content based on Vis-NIR spectroscopy and leaning machine•National soil spectral library with approximately 43,000 samples•Methodology was validated via national proficiency assay for fertility laboratories.•The methodology can reduce 600,000 L per year of acid wastes containing Cr3+/Cr+6.•The methodology is capable to analyze 2000 soil samples per day.
•Quality of chocolates was analyzed by portable NIR.•Multivariate analysis allowed prediction of chocolates stored at 35 °C and 40 °C.•Data mining was effective in classifying chocolates in three ...storage temperatures.•Temperature abuse affects the polymorphic form of cocoa butter.
Cocoa butter provides desirable sensory properties to chocolates; however, the exposure of chocolate to temperature variations during transportation and/or storage can lead to changes in the polymorphic form of butter, with the appearance of a dull-white film on the chocolate surface, known as fat bloom. This study investigated the use of a portable NIR spectrometer combined with chemometric tools to discriminate milk chocolate, white chocolate, 40% cocoa chocolate, and 70% cocoa chocolate samples, which were subjected to temperature abuse for 6 hours. The PCA allowed separating the samples into three classes: control at 20 °C, chocolate subjected to 35 °C, and chocolate subjected to 40 °C, for each type of chocolate studied. The PLS-DA models provided sensibility, specificity, and accuracy values in the range of 80 to 100%, and allowed identifying the wavelengths associated with the different chocolates that most impacted the construction of the models.
We analyzed the interaction between offensive (i.e. space creation dynamics--SCDs) and defensive (i.e. space protection dynamics--SPDs) actions in six play outcomes (free shot, contested shot, new ...SCD, reset, foul, and turnover) in Spanish professional basketball games.
Data consisted of 1548 SCD-SPD-outcome triples obtained from six play-off games. We used Bayesian methods to compute marginal probabilities of six outcomes following five different SCDs. We also computed probabilities of the six outcomes following the 16 most frequent SCD-SPD combinations.
The pick action (e.g. pick and roll, pop and pop) was the most prevalent SCD (33%). However, this SCD did not produce the highest probability of a free shot (0.235). The highest probability of a free shot followed the SCD without ball (0.409). The pick was performed not only to attempt scoring but also to initiate offenses, as it produced the highest probability leading to a new SCD (0.403). Additionally, the SPD performed influenced the outcome of the SCD. This reinforces the notion that the opposition (offensive-defensive interaction) should be considered. To the best of our knowledge, in team sports, this is the first study to successfully model the tactical features involved in offense-defense interactions. Our analyses revealed that the high frequency of occurrence of some SCDs may be justified not only by an associated high probability of free shots but also by the possibility of progressively create more space in the defense (i.e. a new SCD as outcome). In the second case, it evidences offensive strategic features of progressive disruption of the defensive system through the concatenation of subsequent offensive actions.
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