scholarly journals Galactic potential constraints from clustering in action space of combined stellar stream data

2021 ◽  
Vol 502 (3) ◽  
pp. 4170-4193
Author(s):  
Stella Reino ◽  
Elena M Rossi ◽  
Robyn E Sanderson ◽  
Elena Sellentin ◽  
Amina Helmi ◽  
...  

ABSTRACT Stream stars removed by tides from their progenitor satellite galaxy or globular cluster act as a group of test particles on neighbouring orbits, probing the gravitational field of the Milky Way. While constraints from individual streams have been shown to be susceptible to biases, combining several streams from orbits with various distances reduces these biases. We fit a common gravitational potential to multiple stellar streams simultaneously by maximizing the clustering of the stream stars in action space. We apply this technique to members of the GD-1, Palomar 5 (Pal 5), Orphan, and Helmi streams, exploiting both the individual and combined data sets. We describe the Galactic potential with a Stäckel model, and vary up to five parameters simultaneously. We find that we can only constrain the enclosed mass, and that the strongest constraints come from the GD-1, Pal 5, and Orphan streams whose combined data set yields $M(\lt 20\, \mathrm{kpc}) = 2.96^{+0.25}_{-0.26} \times 10^{11} \, \mathrm{ M}_{\odot}$. When including the Helmi stream in the data set, the mass uncertainty increases to $M(\lt 20\, \mathrm{kpc}) = 3.12^{+3.21}_{-0.46} \times 10^{11} \, \mathrm{M}_{\odot}$.

2019 ◽  
Vol 622 ◽  
pp. A172 ◽  
Author(s):  
F. Murgas ◽  
G. Chen ◽  
E. Pallé ◽  
L. Nortmann ◽  
G. Nowak

Context. Rayleigh scattering in a hydrogen-dominated exoplanet atmosphere can be detected using ground- or space-based telescopes. However, stellar activity in the form of spots can mimic Rayleigh scattering in the observed transmission spectrum. Quantifying this phenomena is key to our correct interpretation of exoplanet atmospheric properties. Aims. We use the ten-meter Gran Telescopio Canarias (GTC) telescope to carry out a ground-based transmission spectra survey of extrasolar planets to characterize their atmospheres. In this paper we investigate the exoplanet HAT-P-11b, a Neptune-sized planet orbiting an active K-type star. Methods. We obtained long-slit optical spectroscopy of two transits of HAT-P-11b with the Optical System for Imaging and low-Intermediate-Resolution Integrated Spectroscopy (OSIRIS) on August 30, 2016 and September 25, 2017. We integrated the spectrum of HAT-P-11 and one reference star in several spectroscopic channels across the λ ~ 400–785 nm region, creating numerous light curves of the transits. We fit analytic transit curves to the data taking into account the systematic effects and red noise present in the time series in an effort to measure the change of the planet-to-star radius ratio (Rp∕Rs) across wavelength. Results. By fitting both transits together, we find a slope in the transmission spectrum showing an increase of the planetary radius towards blue wavelengths. Closer inspection of the transmission spectrum of the individual data sets reveals that the first transit presents this slope while the transmission spectrum of the second data set is flat. Additionally, we detect hints of Na absorption on the first night, but not on the second. We conclude that the transmission spectrum slope and Na absorption excess found in the first transit observation are caused by unocculted stellar spots. Modeling the contribution of unocculted spots to reproduce the results of the first night we find a spot filling factor of δ = 0.62−0.17+0.20 and a spot-to-photosphere temperature difference of ΔT = 429−299+184 K.


2014 ◽  
Vol 31 (8) ◽  
pp. 1778-1789
Author(s):  
Hongkang Lin

Purpose – The clustering/classification method proposed in this study, designated as the PFV-index method, provides the means to solve the following problems for a data set characterized by imprecision and uncertainty: first, discretizing the continuous values of all the individual attributes within a data set; second, evaluating the optimality of the discretization results; third, determining the optimal number of clusters per attribute; and fourth, improving the classification accuracy (CA) of data sets characterized by uncertainty. The paper aims to discuss these issues. Design/methodology/approach – The proposed method for the solution of the clustering/classifying problem, designated as PFV-index method, combines a particle swarm optimization algorithm, fuzzy C-means method, variable precision rough sets theory, and a new cluster validity index function. Findings – This method could cluster the values of the individual attributes within the data set and achieves both the optimal number of clusters and the optimal CA. Originality/value – The validity of the proposed approach is investigated by comparing the classification results obtained for UCI data sets with those obtained by supervised classification BPNN, decision-tree methods.


2019 ◽  
Vol 16 (2) ◽  
pp. 445-452
Author(s):  
Kishore S. Verma ◽  
A. Rajesh ◽  
Adeline J. S. Johnsana

K anonymization is one of the worldwide used approaches to protect the individual records from the privacy leakage attack of Privacy Preserving Data Mining (PPDM) arena. Typically anonymized dataset will impact the effectiveness of data mining results. Anyhow, currently researchers of PPDM progress in driving their efforts in finding out the optimum trade-off between privacy and utility. This work tends in bringing out the optimum classifier from a set of best classifiers of data mining approaches that are capable enough in generating value-added classifying results on utility aware k-anonymized data set. We performed the analytical approach on the data set that are anonymized in sense of accompanying the anonymity utility factors like null values count and transformation pattern loss. The experimentation is done with three widely used classifiers HNB, PART and J48 and these classifiers are analysed with Accuracy, F-measure, and ROC-AUC which are literately proved to be the perfect measures of classification. Our experimental analysis reveals the best classifiers on the utility aware anonymized data sets of Cell oriented Anonymization (CoA), Attribute oriented Anonymization (AoA) and Record oriented Anonymization (RoA).


2016 ◽  
Vol 72 (2) ◽  
pp. 182-191
Author(s):  
Jason Nicholas Busby ◽  
J. Shaun Lott ◽  
Santosh Panjikar

The B and C proteins from the ABC toxin complex ofYersinia entomophagaform a large heterodimer that cleaves and encapsulates the C-terminal toxin domain of the C protein. Determining the structure of the complex formed by B and the N-terminal region of C was challenging owing to its large size, the non-isomorphism of different crystals and their sensitivity to radiation damage. A native data set was collected to 2.5 Å resolution and a non-isomorphous Ta6Br12-derivative data set was collected that showed strong anomalous signal at low resolution. The tantalum-cluster sites could be found, but the anomalous signal did not extend to a high enough resolution to allow model building. Selenomethionine (SeMet)-derivatized protein crystals were produced, but the high number (60) of SeMet sites and the sensitivity of the crystals to radiation damage made phasing using the SAD or MAD methods difficult. Multiple SeMet data sets were combined to provide 30-fold multiplicity, and the low-resolution phase information from the Ta6Br12data set was transferred to this combined data set by cross-crystal averaging. This allowed the Se atoms to be located in an anomalous difference Fourier map; they were then used inAuto-Rickshawfor multiple rounds of autobuilding and MRSAD.


2021 ◽  
Vol 12 ◽  
Author(s):  
Haoyang Li ◽  
Juexiao Zhou ◽  
Yi Zhou ◽  
Qiang Chen ◽  
Yangyang She ◽  
...  

Periodontitis is a prevalent and irreversible chronic inflammatory disease both in developed and developing countries, and affects about 20–50% of the global population. The tool for automatically diagnosing periodontitis is highly demanded to screen at-risk people for periodontitis and its early detection could prevent the onset of tooth loss, especially in local communities and health care settings with limited dental professionals. In the medical field, doctors need to understand and trust the decisions made by computational models and developing interpretable models is crucial for disease diagnosis. Based on these considerations, we propose an interpretable method called Deetal-Perio to predict the severity degree of periodontitis in dental panoramic radiographs. In our method, alveolar bone loss (ABL), the clinical hallmark for periodontitis diagnosis, could be interpreted as the key feature. To calculate ABL, we also propose a method for teeth numbering and segmentation. First, Deetal-Perio segments and indexes the individual tooth via Mask R-CNN combined with a novel calibration method. Next, Deetal-Perio segments the contour of the alveolar bone and calculates a ratio for individual tooth to represent ABL. Finally, Deetal-Perio predicts the severity degree of periodontitis given the ratios of all the teeth. The Macro F1-score and accuracy of the periodontitis prediction task in our method reach 0.894 and 0.896, respectively, on Suzhou data set, and 0.820 and 0.824, respectively on Zhongshan data set. The entire architecture could not only outperform state-of-the-art methods and show robustness on two data sets in both periodontitis prediction, and teeth numbering and segmentation tasks, but also be interpretable for doctors to understand the reason why Deetal-Perio works so well.


2001 ◽  
Vol 75 (3) ◽  
pp. 607-643 ◽  
Author(s):  
Jay A. Schneider ◽  
Joseph G. Carter

The shell microstructure of Carboniferous and Triassic permophorids; Triassic and Recent carditids; Devonian, Carboniferous, and Triassic crassatelloideans; and Jurassic through Recent cardioideans is examined in a phylogenetic context, using separate microstructural and morphologic data sets, as well as a combined data set. The microstructural and morphologic data sets are significantly incongruent, but the combined data set suggests that modiomorphoideans (modiomorphids and permophorids) are basal to crassatelloideans; crassatelloideans are basal to carditids (includingSeptocardia), and carditids are basal to cardiids. On the other hand, the possibility of direct permophorid ancestry for the carditid-cardiid clade cannot be excluded, as suggested by the retention of permophorid-like matted (transitional nacreous-porcelaneous) structure in some early carditids and cardiids. In the absence of stratigraphic data and other evidence for phylogenetic relationships, shell microstructure offers limited potential for assessing subfamily-level phylogenetic relationships within the Cardioidea. This is because of microstructural convergences reflecting biomechanical adaptations for fracture control and abrasion resistance, and possibly also selection for metabolic economy of secretion in tropical, oligotrophic habitats. General evolutionary trends in cardiid shell microstructure are nevertheless apparent: Cretaceous cardiids completely replaced an ancestral laminar, matted structure in their inner shell layer with non-laminar porcelaneous structures; evolved better defined CL structure, stronger reflection of the shell margins, and increased thickness or secondary loss of the ancestral prismatic outer shell layer; and, inProtocardia(Pachycardium)stantoni, added inductural deposition. Some Cenozoic cardiids then evolved wider first-order crossed lamellae, non-denticular composite prisms, composite fibrous prisms, ontogenetic submergence of a juvenile non-denticular composite prismatic outer shell layer into the CL middle shell layer, or ontogenetic submergence of the inner part of a juvenile fibrous prismatic outer shell layer into the CL middle shell layer.The shell microstructure ofHemidonax donaciformisis unusual for a cardioidean, and suggests closer affinities with the superfamily Tellinoidea than with the superfamily Cardioidea.Extensive inductural deposits inProtocardia(Pachycardium)stantoniraise the possibility that photosymbiosis evolved among some Mesozoic members of the Protocardiinae, thereby increasing the likelihood that this feature has evolved several times independently in the Cardiidae.Cemented, calcareous periostracal granules or spines are known to occur in modiolopsoideans, mytiloideans, modiomorphids, permophorids, trigonioids, astartids, cardiids, myoids, pholadomyoids, and septibranchoids. Consequently, the presence of these structures is not necessarily indicative of close anomalodesmatan affinities.


2021 ◽  
Author(s):  
Gah-Yi Ban ◽  
N. Bora Keskin

We consider a seller who can dynamically adjust the price of a product at the individual customer level, by utilizing information about customers’ characteristics encoded as a d-dimensional feature vector. We assume a personalized demand model, parameters of which depend on s out of the d features. The seller initially does not know the relationship between the customer features and the product demand but learns this through sales observations over a selling horizon of T periods. We prove that the seller’s expected regret, that is, the revenue loss against a clairvoyant who knows the underlying demand relationship, is at least of order [Formula: see text] under any admissible policy. We then design a near-optimal pricing policy for a semiclairvoyant seller (who knows which s of the d features are in the demand model) who achieves an expected regret of order [Formula: see text]. We extend this policy to a more realistic setting, where the seller does not know the true demand predictors, and show that this policy has an expected regret of order [Formula: see text], which is also near-optimal. Finally, we test our theory on simulated data and on a data set from an online auto loan company in the United States. On both data sets, our experimentation-based pricing policy is superior to intuitive and/or widely-practiced customized pricing methods, such as myopic pricing and segment-then-optimize policies. Furthermore, our policy improves upon the loan company’s historical pricing decisions by 47% in expected revenue over a six-month period. This paper was accepted by Noah Gans, stochastic models and simulation.


Geophysics ◽  
2006 ◽  
Vol 71 (3) ◽  
pp. H33-H44 ◽  
Author(s):  
Hendrik Paasche ◽  
Jens Tronicke ◽  
Klaus Holliger ◽  
Alan G. Green ◽  
Hansruedi Maurer

Inversions of an individual geophysical data set can be highly nonunique, and it is generally difficult to determine petrophysical parameters from geophysical data. We show that both issues can be addressed by adopting a statistical multiparameter approach that requires the acquisition, processing, and separate inversion of two or more types of geophysical data. To combine information contained in the physical-property models that result from inverting the individual data sets and to estimate the spatial distribution of petrophysical parameters in regions where they are known at only a few locations, we demonstrate the potential of the fuzzy [Formula: see text]-means (FCM) clustering technique. After testing this new approach on synthetic data, we apply it to limited crosshole georadar, crosshole seismic, gamma-log, and slug-test data acquired within a shallow alluvial aquifer. The derived multiparameter model effectively outlines the major sedimentary units observed in numerous boreholes and provides plausible estimates for the spatial distributions of gamma-ray emitters and hydraulic conductivity.


1999 ◽  
Vol 47 (5) ◽  
pp. 499 ◽  
Author(s):  
S. Brown ◽  
G. Rouse ◽  
P. Hutchings ◽  
D. Colgan

DNA sequence data from for histone H3 (34 species), U2 snRNA (34 species) and two segments (D1 and D9–10 expansion regions) of 28S rDNA (28 and 26 species, respectively) have been collected to investigate the relationships of polychaetes. Representatives of all of the major morphologically identified clades were used, as well as members of the Sipuncula, Echiura, Turbellaria, Clitellata and Siboglinidae (formerly the phyla Pogonophora and Vestimentifera). Maximum parsimony analyses of the separate data sets gave conflicting results and none conformed closely to previous results based on morphology. Instead each data set provided corroboration of a few of the morphological groupings, usually pairing, though inconsistently, members of the same family. Higher groupings proposed on morphological grounds were rarely recovered. Maximum parsimony analysis of the combined data, excluding areas of uncertain alignment, recovered some morphological groupings such as Cirratulidae, Terebellidae, scale worms and eunicimorphs, and did not significantly contradict others. However, some expected groupings were not recovered. Surprisingly, the fanworms (Sabellidae and Serpulidae) were not shown as sister taxa, and monophyly of Phyllodocida, a morphologically well corroborated clade, required four more steps than most parsimonious trees. Aciculata was not seen in our analyses, although it was the most strongly supported large clade in Rouse and Fauchald (1997, Cladistics and polychaetes. Zoologica Scripta 26, 138–204). Trees constrained to show Aciculata as monophyletic were 18 steps longer than the most parsimonious trees. If trees are rooted on sipunculans rather than the nematode, Aciculata is nearly recovered, being rendered paraphyletic by the inclusion of the sister-pair of Oweniidae and Chaetopteridae. As suggested by some recent morphological and molecular analyses, Siboglinidae and Clitellata may well have sister groups among polychaetes. The morphologically aberrant Sternaspidae are closest to members of Terebellida in the present analyses, supporting the placement of Rouse and Fauchald. Interesting results deserving further assessment concern the placement of Chaetopteridae, Oweniidae and Sipuncula.


Author(s):  
Gavin B. M. Vaughan ◽  
Soeren Schmidt ◽  
Henning F. Poulsen

AbstractWe present a method in which the contributions from the individual crystallites in a polycrystalline sample are separated and treated as essentially single crystal data sets. The process involves the simultaneous determination of the orientation matrices of the individual crystallites in the sample, the subsequent integration of the individual peaks, and filtering and summing of the subsequent integrated intensities, in order to arrive at a single-crystal like data set which may be treated normally. In order to demonstrate the method, we consider as a test case a small molecule structure, cupric acetate monohyrade. We show that it is possible to obtain a single-crystal quality structure solution and refinement, in which accurate anisotropic thermal parameters and hydrogen atom positions are obtained.


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