Bird’s eye view of molecular clouds in the Milky Way

Context. Describing how the properties of the interstellar medium are combined across various size scales is crucial for understanding star formation scaling laws and connecting Galactic and extragalactic data of molecular clouds. Aims. We describe how the statistical structure of the clouds and its connection to star formation changes from sub-parsec to kiloparsec scales in a complete region within the Milky Way disk. Methods. We built a census of molecular clouds within 2 kpc from the Sun using data from the literature. We examined the dust-based column density probability distributions (N-PDFs) of the clouds and their relation to star formation as traced by young stellar objects (YSOs). We then examined our survey region from the outside, within apertures of varying sizes, and describe how the N-PDFs and their relation to star formation changes with the size scale. Results. We present a census of the molecular clouds within 2 kpc distance, including 72 clouds and YSO counts for 44 of them. The N-PDFs of the clouds are not well described by any single simple model; use of any single model may bias the interpretation of the N-PDFs. The top-heaviness of the N-PDFs correlates with star formation activity, and the correlation changes with Galactic environment (spiral- and inter-arm regions). We find that the density contrast of clouds may be more intimately linked to star formation than the dense gas mass fraction. The aperture-averaged N-PDFs vary with the size scale and are more top-heavy for larger apertures. The top-heaviness of the aperture N-PDFs correlates with star formation activity up to roughly 0.5 kpc, depending on the environment. Our results suggest that the relations between cloud structure and star formation are environment specific and best captured by relative quantities (e.g. the density contrast). Finally, we show that the density structures of individual clouds give rise to a kiloparsec-scale Kennicutt-Schmidt relation as a combination of sampling effects and blending of different galactic environments.

Assessment of Athletic Development in Youth Players – Goal Setting with Normative Data from Basketball

INTRODUCTION The nationwide implementation of physical performance test batteries for youth squad players can be valuable for compiling individual physical performance profiles based on age- and gender-specific norm values. This approach is frequently used for optimizing training prescription and thus athletic development. The aim of this study was to introduce a distribution-based approach to derive an effect size scale for assessing athletic development from normative testing data in youth players, which can then be translated to setting performance goals for athletic development.METHODS Secondary analysis of norm values (mixed longitudinal and cross-sectional data [1]). In the age-groups under 12 to under 17, a maximum number of 1,172 and 846 tests were available for male and female basketball squad players, respectively. Biannual testing was conducted as part of a federal research project (20-m sprint, 20-m change of direction sprints with/without basketball, jump & reach, standing long jump, chest pass, mid-range jump shot, multistage fitness test). An effect size scale was derived from norm values which were available as quintile scores (five categories). Trivial changes were defined as the age-related mean annual performance development which was estimated as the average age-group-to-age-group change for the quintiles. Threshold values for small, medium, and large changes were calculated as average changes that were required to increase performance classification by one, two or three categories, respectively. These thresholds were additionally compared to the default effect size scale commonly used for interpreting standardized mean differences (between-player standard deviation: small 0.2, medium 0.6, large 1.2 [2]).RESULTS For example, the age-related mean annual development in the jump & reach for male players was 4 cm (trivial change). To reach one, two or three higher performance categories, jump height must improve by 8, 12 and 15 cm, respectively (i.e., small, medium, large). Compared with the default standardized effect size scale, these quintile-based thresholds were larger.CONCLUSION The quintile-based analysis presents a simple and practical approach to derive effect size thresholds based on norm values created from regular physical performance testing. These effect size scales can be easily visualized and communicated to players and coaches, as they are typically familiar with percentile-based performance classification of testing data. A limitation of this study was that only norm values in the form of quintile scores were used for analysis. Future research should attempt to model longitudinal datasets while accountingfor within- and between-player effects. Furthermore, the choice of appropriate and realistic percentilebased thresholds clearly remains up for debate and requires adequate analysis of original longitudinal data.REFERENCES 1. Stadtmann (2012) PhD thesis, Ruhr University Bochum. 2. Hopkins et al. (2009) MSSE,41,3-12.

Possibilities of Siderite and Barite Concentrates Preparation from Tailings of Settling Pit Nearby Markušovce Village (Eastern Slovakia)

The contribution deals with recovery of useful minerals such as siderite and barite from tailings collected in settling pit nearbyMarkušovce village (East Slovakia). The material form the pit was subjected to gravity pre-concentration and magnetic separationunder laboratory conditions with the aim to verify a possibility of siderite and barite concentrates preparation. A fraction of +0.2–1mm forming a 40.56 wt% of total grain size scale of the material from the pit and containing 35.71% SiO2, 22.55% Fe2O3, 7,12%Al2O3, 5.48% Ba, and 3.89% SO42– was tested in upgrading process. Thus, 78.18% of SiO2, and 60.41% of Al2O3 at loss 21.70%Fe2O3 and 2.09% of Ba were removed in gravity pre-concentration. The iron concentrate with the content of 44.33% Fe2O3 at Ferecovery of 77.29% in magnetic product was obtained. Barite pre-concentrate with the Ba content of 46.21% at Ba recovery of91.95% in non-magnetic product was won.

Hierarchical pyramidal subsampling in deep convolutional networks for visual pattern recognition

The main problem of known deep convolutional neural networks (CNN) is that they require a fixed-size input image. This requirement is “artificial” and can reduce recognition accuracy for images or its parts of arbitrary size/scale. The paper proposes a strategy of combining “hierarchical pyramidal subselection” to eliminate the above restriction. The structure of the neural network using the proposed combining strategy allows the generation of prediction regardless of the size/scale of the original image, and also improves the accuracy of recognition. Features of application of CNN for identification and recognition of defects of conducting pattern of printed circuit board blanks have been considered. Features of defects of conductive pattern of printed circuit board blanks have been briefly discussed. The invention proposes the use of artificial CNN, which have advantages in speed and accuracy in solving problems of object recognition on images relative to existing methods. The focus is on the architecture of CNN using hierarchical pyramidal subselection. Capabilities of application of CNN for recognition of defects of conducting pattern of printed circuit board blanks have been shown. Proposed method of hierarchical pyramidal subselection in deep convolutional networks has been implemented in software complex, which allows processing digital data of photographs of conducting pattern of printed circuit boards, in particular during their flaw detection, and can be used for localization of existing defects of conducting pattern. The conclusion draws the possibilities of using methods and means of image processing in flaw detection of radio-electronic equipment and instruments