Mutation of Directed Graphs -- Corresponding Regular Expressions and Complexity of Their Generation

Directed graphs (DG), interpreted as state transition diagrams, are traditionally used to represent finite-state automata (FSA). In the context of formal languages, both FSA and regular expressions (RE) are equivalent in that they accept and generate, respectively, type-3 (regular) languages. Based on our previous work, this paper analyzes effects of graph manipulations on corresponding RE. In this present, starting stage we assume that the DG under consideration contains no cycles. Graph manipulation is performed by deleting or inserting of nodes or arcs. Combined and/or multiple application of these basic operators enable a great variety of transformations of DG (and corresponding RE) that can be seen as mutants of the original DG (and corresponding RE). DG are popular for modeling complex systems; however they easily become intractable if the system under consideration is complex and/or large. In such situations, we propose to switch to corresponding RE in order to benefit from their compact format for modeling and algebraic operations for analysis. The results of the study are of great potential interest to mutation testing

A Comparative Study between Two Regression Methods on LiDAR Data: A Case Study

Airborne LiDAR (Light Detection and Ranging) has become an excellent tool for accurately assessing vegetation characteristics in forest environments. Previous studies showed empirical relationships between LiDAR and field-measured biophysical variables. Multiple linear regression (MLR) with stepwise feature selection is the most common method for building estimation models. Although this technique has provided very interesting results, many other data mining techniques may be applied. The overall goal of this study is to compare different methodologies for assessing biomass fractions at stand level using airborne Li- DAR data in forest settings. In order to choose the best methodology, a comparison between two different feature selection techniques (stepwise selection vs. genetic-based selection) is presented. In addition, classical MLR is also compared with regression trees (M5P). The results when each methodology is applied to estimate stand biomass fractions from an area of northern Spain show that genetically-selected M5P obtains the best results

A Comparative Study of Machine Learning Regression Methods on LiDAR Data: A Case Study

Light Detection and Ranging (LiDAR) is a remote sensor able to extract vertical information from sensed objects. LiDAR-derived information is nowadays used to develop environmental models for describing fire behaviour or quantifying biomass stocks in forest areas. A multiple linear regression (MLR) with previous stepwise feature selection is the most common method in the literature to develop LiDAR-derived models. MLR defines the relation between the set of field measurements and the statistics extracted from a LiDAR flight. Machine learning has recently been paid an increasing attention to improve classic MLR results. Unfortunately, few studies have been proposed to compare the quality of the multiple machine learning approaches. This paper presents a comparison between the classic MLR-based methodology and common regression techniques in machine learning (neural networks, regression trees, support vector machines, nearest neighbour, and ensembles such as random forests). The selected techniques are applied to real LiDAR data from two areas in the province of Lugo (Galizia, Spain). The results show that support vector regression statistically outperforms the rest of techniques when feature selection is applied. However, its performance cannot be said statistically different from that of Random Forests when previous feature selection is skipped

Reading Between the (Spectral) Lines: Magellan/IMACS spectroscopy of the Ultra-faint Dwarf Galaxies Eridanus IV and Centaurus I

We present a spectroscopic analysis of Eridanus IV (Eri IV) and Centaurus I (Cen I), two ultra-faint dwarf galaxies of the Milky Way. Using IMACS/Magellan spectroscopy, we identify 28 member stars of Eri IV and 34 member stars of Cen I. For Eri IV, we measure a systemic velocity of $v_{sys} = -31.5^{+1.3}_{-1.2}\:\mathrm{km\:s^{-1}}$ and velocity dispersion $\sigma_{v}= 6.1^{+1.2}_{-0.9}\:\mathrm{km\:s^{-1}}$. Additionally, we measure the metallicities of 16 member stars of Eri IV. We find a metallicity of $\mathrm{[Fe/H]}=-2.87^{+0.08}_{-0.07}$ and resolve a dispersion of $\sigma_{\mathrm{[Fe/H]}} = 0.20\pm0.09$. The mean metallicity is marginally lower than all other known ultra-faint dwarf galaxies, making it one of the most metal-poor galaxies discovered thus far. Eri IV also has a somewhat unusual right-skewed metallicity distribution. For Cen I, we find a velocity $v_{sys} = 44.9\pm0.8\:\mathrm{km\:s^{-1}}$ and velocity dispersion $\sigma_{v} = 4.2^{+0.6}_{-0.5} \:\mathrm{km\:s^{-1}}$. We measure the metallicities of 27 member stars of Cen I, and find a mean metallicity $\mathrm{[Fe/H]} = -2.57\pm0.08$ and metallicity dispersion $\sigma_{\mathrm{[Fe/H]}} = 0.38^{+0.07}_{-0.05}$. We calculate the systemic proper motion, orbit, and the astrophysical J-factor for each system, the latter of which indicates that Eri IV is a good target for indirect dark matter detection. We also find no strong evidence for tidal stripping of Cen I or Eri IV. Overall, our measurements confirm that Eri IV and Cen I are dark matter-dominated galaxies with properties largely consistent with other known ultra-faint dwarf galaxies. The low metallicity, right-skewed metallicity distribution, and high J-factor make Eri IV an especially interesting candidate for further followup.Comment: 25 pages, 11 figures, submitted to AAS journal

The Faint Satellite System of NGC 253: Insights into Low-Density Environments and No Satellite Plane

We have conducted a systematic search around the Milky Way (MW) analog NGC 253 (D=3.5 Mpc), as a part of the Panoramic Imaging Survey of Centaurus and Sculptor (PISCeS) - a Magellan+Megacam survey to identify dwarfs and other substructures in resolved stellar light around MW-mass galaxies outside of the Local Group. In total, NGC 253 has five satellites identified by PISCeS within 100 kpc with an absolute V-band magnitude $M_V<-7$. We have additionally obtained deep Hubble Space Telescope imaging of four reported candidates beyond the survey footprint: Do III, Do IV, and dw0036m2828 are confirmed to be satellites of NGC 253, while SculptorSR is found to be a background galaxy. We find no convincing evidence for the presence of a plane of satellites surrounding NGC 253. We construct its satellite luminosity function, which is complete down to $M_V$$\lesssim$$-8$ out to 100 kpc and $M_V$$\lesssim$$-9$ out to 300 kpc, and compare it to those calculated for other Local Volume galaxies. Exploring trends in satellite counts and star-forming fractions among satellite systems, we find relationships with host stellar mass, environment, and morphology, pointing to a complex picture of satellite formation, and a successful model has to reproduce all of these trends.Comment: Submitted to AAS Journal. Comments are welcom

A dark siren measurement of the Hubble constant using gravitational wave events from the first three LIGO/Virgo observing runs and DELVE

The current and next observation seasons will detect hundreds of gravitational waves (GWs) from compact binary systems coalescence at cosmological distances. When combined with independent electromagnetic measurements, the source redshift will be known, and we will be able to obtain precise measurements of the Hubble constant H0 via the distance–redshift relation. However, most observed mergers are not expected to have electromagnetic counterparts, which prevents a direct redshift measurement. In this scenario, one possibility is to use the dark sirens method that statistically marginalizes over all the potential host galaxies within the GW location volume to provide a probabilistic source redshift. Here we presented H0 measurements using two new dark sirens compared to previous analyses using DECam data: GW190924 021846 and GW200202 154313. The photometric redshifts of the possible host galaxies of these two events are acquired from the DECam Local Volume Exploration Survey (DELVE) carried out on the Blanco telescope at Cerro Tololo. The combination of the H0 posterior from GW190924 021846 and GW200202 154313 together with the brightsiren GW170817 leadsto H0 = 68.84+15.51 −7.74 km s−1 Mpc−1. Including these two dark sirens improves the 68 per cent confidence interval (CI) by 7 per cent over GW170817 alone. This demonstrates that the addition of well-localized dark sirens in such analysis improves the precision of cosmological measurements. Using a sample containing 10 well-localized dark sirens observed during the third LIGO/Virgo observation run, without the inclusion of GW170817, we determine a measurement of H0 = 76.00+17.64 −13.45 km s−1 Mpc−1

Adolescent brain maturation and cortical folding: evidence for reductions in gyrification

Evidence from anatomical and functional imaging studies have highlighted major modifications of cortical circuits during adolescence. These include reductions of gray matter (GM), increases in the myelination of cortico-cortical connections and changes in the architecture of large-scale cortical networks. It is currently unclear, however, how the ongoing developmental processes impact upon the folding of the cerebral cortex and how changes in gyrification relate to maturation of GM/WM-volume, thickness and surface area. In the current study, we acquired high-resolution (3 Tesla) magnetic resonance imaging (MRI) data from 79 healthy subjects (34 males and 45 females) between the ages of 12 and 23 years and performed whole brain analysis of cortical folding patterns with the gyrification index (GI). In addition to GI-values, we obtained estimates of cortical thickness, surface area, GM and white matter (WM) volume which permitted correlations with changes in gyrification. Our data show pronounced and widespread reductions in GI-values during adolescence in several cortical regions which include precentral, temporal and frontal areas. Decreases in gyrification overlap only partially with changes in the thickness, volume and surface of GM and were characterized overall by a linear developmental trajectory. Our data suggest that the observed reductions in GI-values represent an additional, important modification of the cerebral cortex during late brain maturation which may be related to cognitive development

Particulate Matter-Induced Lung Inflammation Increases Systemic Levels of PAI-1 and Activates Coagulation Through Distinct Mechanisms

Exposure of human populations to ambient particulate matter (PM) air pollution significantly contributes to the mortality attributable to ischemic cardiovascular events. We reported that mice treated with intratracheally instilled PM develop a prothrombotic state that requires the release of IL-6 by alveolar macrophages. We sought to determine whether exposure of mice to PM increases the levels of PAI-1, a major regulator of thrombolysis, via a similar or distinct mechanism. mice but was absent in mice treated with etanercept, a TNF-α inhibitor. Treatment with etanercept did not prevent the PM-induced tendency toward thrombus formation.Mice exposed to inhaled PM exhibited a TNF-α-dependent increase in PAI-1 and an IL-6-dependent activation of coagulation. These results suggest that multiple mechanisms link PM-induced lung inflammation with the development of a prothrombotic state