Term-Community-Based Topic Detection with Variable Resolution

Network-based procedures for topic detection in huge text collections offer an intuitive alternative to probabilistic topic models. We present in detail a method that is especially designed with the requirements of domain experts in mind. Like similar methods, it employs community detection in term co-occurrence graphs, but it is enhanced by including a resolution parameter that can be used for changing the targeted topic granularity. We also establish a term ranking and use semantic word-embedding for presenting term communities in a way that facilitates their interpretation. We demonstrate the application of our method with a widely used corpus of general news articles and show the results of detailed social-sciences expert evaluations of detected topics at various resolutions. A comparison with topics detected by Latent Dirichlet Allocation is also included. Finally, we discuss factors that influence topic interpretation.

Exponential Satisficing

We propose the exponential satisficing model of boundedly rational decision-making, a general-purpose tool designed for use in typical microeconomic applications. The model posits that the preferences perceived and acted upon by the agent are a stochastic coarsening of his or her true, welfare-significant preferences. The decision-maker’s perceptual capabilities are controlled by a preference resolution parameter, which smoothly varies the impact of cognitive constraints on choice. To demonstrate the implementation of the model, it is applied to duopolistic price competition with satisficing consumers and to normal-form games with satisficing players. (JEL D01, D80, D90)

Cell Layers: Uncovering clustering structure and knowledge in unsupervised single-cell transcriptomic analysis

MotivationUnsupervised clustering of single-cell transcriptomics is a powerful method for identifying cell populations. Static visualization techniques for single-cell clustering only display results for a single resolution parameter. Analysts will often evaluate more than one resolution parameter, but then only report one.ResultsWe developed Cell Layers, an interactive Sankey tool for the quantitative investigation of gene expression, coexpression, biological processes, and cluster integrity across clustering resolutions. Cell Layers enhances the interpretability of single-cell clustering by linking molecular data and cluster evaluation metrics, to provide novel insight into cell populations.Availability and implementationUpon request

Method Transfer Evaluation for Digital Derivative Spectrophotometry Through its Resolution Parameter Comparison of Different Computer Programs

The application assessment of different programs was performed with equivalence tests for method transfer pro second-order derivative spectrophotometry. The digital second-order derivative spectra were calculated on different instruments; GBC Scientific Equipment Cintra 20 (Cintral v.2.6 and Spectral v.1.70 software programs) and Thermo Scientific Evolution 300 (VISIONPro software) were analyzed using the amplitude A/B ratio (A = 2D265,263; B = 2D263,261). Amplitude A/B ratio is the resolution parameter for derivative spectrophotometry prescribed in European Pharmacopoeia. The obtained values for A/B ratio were either very similar or significantly different among programs: 0.669 (Cintral v.2.6), 0.549 (Spectral v.1.70), 0.556 (medium indirect VISIONPro), 0.557 (one-step Savitzky–Golay 7 VISIONPro), 0.689 (two-step Savitzky–Golay 7 VISIONPro). Method transfer was possible between Spectral v.1.70 and VISIONPro (medium indirect and one-step Savitzky–Golay 7), but the values obtained in Cintral v.2.6 were not comparable to the other programs. The absorbance data exported from both instruments were additionally calculated in OriginPro8 which provided almost the same mean A/B values (0.627 Cintral v.2.6; 0.624 VISIONPro), confirming that the two instruments recorded the same zero-order spectra. The calculation of resolution parameter could be used for verification of program comparison, which would enable transfer between sender and receiver laboratory. The accordance between program algorithms was confirmed when acceptable differences for values of resolution parameter (A/B ratios) were achieved.

Granularity of algorithmically constructed publication-level classifications of research publications: Identification of specialties

In this work, we build on and use the outcome of an earlier study on topic identification in an algorithmically constructed publication-level classification (ACPLC), and address the issue of how to algorithmically obtain a classification of topics (containing articles), where the classes of the classification correspond to specialties. The methodology we propose, which is similar to that used in the earlier study, uses journals and their articles to construct a baseline classification. The underlying assumption of our approach is that journals of a particular size and focus have a scope that corresponds to specialties. By measuring the similarity between (1) the baseline classification and (2) multiple classifications obtained by topic clustering and using different values of a resolution parameter, we have identified a best performing ACPLC. In two case studies, we could identify the subject foci of the specialties involved, and the subject foci of specialties were relatively easy to distinguish. Further, the class size variation regarding the best performing ACPLC is moderate, and only a small proportion of the articles belong to very small classes. For these reasons, we conclude that the proposed methodology is suitable for determining the specialty granularity level of an ACPLC.

Overview of jet physics results from ALICE

Recent results from jet shower-shape and substructure analyses done by the ALICE collaboration in central Pb–Pb collisions at √sNN = 2.76 TeV and in pp collisions at √s = 7 TeV are reviewed. The presented jet shower- shape observables are angularity g and transverse momentum dispersion pTD, which were studied for a small resolution parameter R = 0.2, track-based jets with a minimum constituent transverse momentum (pT) cut-off of 0.15 GeV/c. Jet substructure is explored for track-based anti-kT jets with R = 0.4 by means of iterative declustering and grooming techniques, which were used to measure the absolutely-normalized leading subjet momentum fraction zg and the number of hard splittings in the reclustered jet shower, nSD. These observables provide complementary information on the jet fragmentation and help to discriminate between different scenarios for medium-induced modifications of the parton shower in heavy-ion collisions due to jet quenching.

Study of Jet Shape Observables in Au+Au Collisions at s N N = 200 GeV with JEWEL

Nuclear–nuclear collisions at energies attainable at the large accelerators RHIC and the LHC are an ideal environment to study nuclear matter under extreme conditions of high temperature and energy density. One of the most important probes of such nuclear matter is the study of production of jets. In this article, several jet shape observables in Au+Au collisions at the center of mass energy per nucleon–nucleon pair of s N N = 200 GeV simulated in the Monte Carlo generator JEWEL are presented. Jets were reconstructed using the anti- k T algorithm and their shapes were studied as a function of the jet-resolution parameter R, transverse momentum p T and collision centrality.

Organization in complex brain networks: energy distributions and phase shift

The Hamiltonian function of a network, derived from the intrinsic distributions of nodes and edges, magnified by resolution parameter has information on the distribution of energy in the network. In brain networks, the Hamiltonian function follows hierarchical features reflecting a power-law behavior which can be a signature of self-organization. Further, the transition of three distinct phases driven by resolution parameter is observed which could correspond to various important brain states. This resolution parameter could thus reflect a key parameter that controls and balances the energy distribution in the brain network.