VdBH 222: a starburst cluster in the inner Milky Way

Context. It has been suggested that the compact open cluster VdBH 222 is a young massive distant object. Aims. We set out to characterise VdBH 222 using a comprehensive set of multi-wavelength observations. Methods. We obtained multi-band optical (UBVR) and near-infrared (JHKS) photometry of the cluster field, as well as multi-object and long-slit optical spectroscopy for a large sample of stars in the field. We applied classical photometric analysis, as well as more sophisticated methods using the CHORIZOS code, to determine the reddening to the cluster. We then plotted dereddened HR diagrams and determined cluster parameters via isochrone fitting. Results. We have identified a large population of luminous supergiants confirmed as cluster members via radial velocity measurements. We find nine red supergiants (plus one other candidate) and two yellow supergiants. We also identify a large population of OB stars. Ten of them are bright enough to be blue supergiants. The cluster lies behind ≈7.5 mag of extinction for the preferred value of RV = 2.9. Isochrone fitting allows for a narrow range of ages between 12 and 16 Ma. The cluster radial velocity is compatible with distances of ~6 and ~10 kpc. The shorter distance is inconsistent with the age range and Galactic structure. The longer distance implies an age ≈ 12 Ma and a location not far from the position where some Galactic models place the far end of the Galactic bar. Conclusions. VdBH 222 is a young massive cluster with a likely mass >20 000 M⊙. Its population of massive evolved stars is comparable to that of large associations, such as Per OB1. Its location in the inner Galaxy, presumably close to the end of the Galactic bar, adds to the increasing evidence for vigorous star formation in the inner regions of the Milky Way.

Open cluster Dolidze 25: Stellar parameters and the metallicity in the Galactic anticentre

Context. The young open cluster Dolidze 25, in the direction of the Galactic anticentre, has been attributed a very low metallicity, with typical abundances between −0.5 and −0.7 dex below solar. Aims. We intend to derive accurate cluster parameters and accurate stellar abundances for some of its members. Methods. We have obtained a large sample of intermediate- and high-resolution spectra for stars in and around Dolidze 25. We used the fastwind code to generate stellar atmosphere models to fit the observed spectra. We derive stellar parameters for a large number of OB stars in the area, and abundances of oxygen and silicon for a number of stars with spectral types around B0. Results. We measure low abundances in stars of Dolidze 25. For the three stars with spectral types around B0, we find 0.3 dex (Si) and 0.5 dex (O) below the values typical in the solar neighbourhood. These values, even though not as low as those given previously, confirm Dolidze 25 and the surrounding H ii region Sh2-284 as the most metal-poor star-forming environment known in the Milky Way. We derive a distance 4.5 ± 0.3 kpc to the cluster (rG ≈ 12.3 kpc). The cluster cannot be older than ~3 Myr, and likely is not much younger. One star in its immediate vicinity, sharing the same distance, has Si and O abundances at most 0.15 dex below solar. Conclusions. The low abundances measured in Dolidze 25 are compatible with currently accepted values for the slope of the Galactic metallicity gradient, if we take into account that variations of at least ±0.15 dex are observed at a given radius. The area traditionally identified as Dolidze 25 is only a small part of a much larger star-forming region that comprises the whole dust shell associated with Sh2-284 and very likely several other smaller H ii regions in its vicinity.

An adaptive algorithm for clustering cumulative probability distribution functions using the Kolmogorov–Smirnov two-sample test

This paper proposes an adaptive algorithm for clustering cumulative probability distribution functions (c.p.d.f.) of a continuous random variable, observed in different populations, into the minimum homogeneous clusters, making no parametric assumptions about the c.p.d.f.’s. The distance function for clustering c.p.d.f.’s that is proposed is based on the Kolmogorov–Smirnov two sample statistic. This test is able to detect differences in position, dispersion or shape of the c.p.d.f.’s. In our context, this statistic allows us to cluster the recorded data with a homogeneity criterion based on the whole distribution of each data set, and to decide whether it is necessary to add more clusters or not. In this sense, the proposed algorithm is adaptive as it automatically increases the number of clusters only as necessary; therefore, there is no need to fix in advance the number of clusters. The output of the algorithm are the common c.p.d.f. of all observed data in the cluster (the centroid) and, for each cluster, the Kolmogorov–Smirnov statistic between the centroid and the most distant c.p.d.f. The proposed algorithm has been used for a large data set of solar global irradiation spectra distributions. The results obtained enable to reduce all the information of more than 270,000 c.p.d.f.’s in only 6 different clusters that correspond to 6 different c.p.d.f.’s.

Diagnostic validity of clinical signs associated with a large exophoria at near

Purpose. To analyze the diagnostic validity of accommodative and binocular tests in a sample of patients with a large near exophoria with moderate to severe symptoms. Methods. Two groups of patients between 19 and 35 years were recruited from a university clinic: 33 subjects with large exophoria at near vision and moderate or high visual discomfort and 33 patients with normal heterophoria and low visual discomfort. Visual discomfort was defined using the Conlon survey. A refractive exam and an exhaustive evaluation of accommodation and vergence were assessed. Diagnostic validity by means of receiver operator characteristic (ROC) curves, sensitivity (S), specificity (Sp), and positive and negative likelihood ratios (LR+, LR−) were assessed. This analysis was also carried out considering multiple tests as serial testing strategy. Results. ROC analysis showed the best diagnostic accuracy for receded near point of convergence (NPC) recovery (area = 0.929) and binocular accommodative facility (BAF) (area = 0.886). Using the cut-offs obtained with ROC analysis, the best diagnostic validity was obtained for the combination of NPC recovery and BAF (S  =  0.77, Sp = 1, LR+ = value tending to infinity, LR− = 0.23) and the combination of NPC break and recovery with BAF (S  =  0.73, Sp = 1, LR+ = tending to infinity, LR− = 0.27). Conclusions. NPC and BAF tests were the tests with the best diagnostic accuracy for subjects with large near exophoria and moderate to severe symptoms.