Statistical modeling of ground motion relations for seismic hazard analysis

We introduce a new approach for ground motion relations (GMR) in the probabilistic seismic hazard analysis (PSHA), being influenced by the extreme value theory of mathematical statistics. Therein, we understand a GMR as a random function. We derive mathematically the principle of area-equivalence; wherein two alternative GMRs have an equivalent influence on the hazard if these GMRs have equivalent area functions. This includes local biases. An interpretation of the difference between these GMRs (an actual and a modeled one) as a random component leads to a general overestimation of residual variance and hazard. Beside this, we discuss important aspects of classical approaches and discover discrepancies with the state of the art of stochastics and statistics (model selection and significance, test of distribution assumptions, extreme value statistics). We criticize especially the assumption of logarithmic normally distributed residuals of maxima like the peak ground acceleration (PGA). The natural distribution of its individual random component (equivalent to exp(epsilon_0) of Joyner and Boore 1993) is the generalized extreme value. We show by numerical researches that the actual distribution can be hidden and a wrong distribution assumption can influence the PSHA negatively as the negligence of area equivalence does. Finally, we suggest an estimation concept for GMRs of PSHA with a regression-free variance estimation of the individual random component. We demonstrate the advantages of event-specific GMRs by analyzing data sets from the PEER strong motion database and estimate event-specific GMRs. Therein, the majority of the best models base on an anisotropic point source approach. The residual variance of logarithmized PGA is significantly smaller than in previous models. We validate the estimations for the event with the largest sample by empirical area functions. etc

Genome of the Avirulent Human-Infective Trypanosome—Trypanosoma rangeli

Background: Trypanosoma rangeli is a hemoflagellate protozoan parasite infecting humans and other wild and domestic mammals across Central and South America. It does not cause human disease, but it can be mistaken for the etiologic agent of Chagas disease, Trypanosoma cruzi. We have sequenced the T. rangeli genome to provide new tools for elucidating the distinct and intriguing biology of this species and the key pathways related to interaction with its arthropod and mammalian hosts.  Methodology/Principal Findings: The T. rangeli haploid genome is ,24 Mb in length, and is the smallest and least repetitive trypanosomatid genome sequenced thus far. This parasite genome has shorter subtelomeric sequences compared to those of T. cruzi and T. brucei; displays intraspecific karyotype variability and lacks minichromosomes. Of the predicted 7,613 protein coding sequences, functional annotations could be determined for 2,415, while 5,043 are hypothetical proteins, some with evidence of protein expression. 7,101 genes (93%) are shared with other trypanosomatids that infect humans. An ortholog of the dcl2 gene involved in the T. brucei RNAi pathway was found in T. rangeli, but the RNAi machinery is non-functional since the other genes in this pathway are pseudogenized. T. rangeli is highly susceptible to oxidative stress, a phenotype that may be explained by a smaller number of anti-oxidant defense enzymes and heatshock proteins.  Conclusions/Significance: Phylogenetic comparison of nuclear and mitochondrial genes indicates that T. rangeli and T. cruzi are equidistant from T. brucei. In addition to revealing new aspects of trypanosome co-evolution within the vertebrate and invertebrate hosts, comparative genomic analysis with pathogenic trypanosomatids provides valuable new information that can be further explored with the aim of developing better diagnostic tools and/or therapeutic targets

Stochastic signalling rewires the interaction map of a multiple feedback network during yeast evolution

During evolution, genetic networks are rewired through strengthening or weakening their interactions to develop new regulatory schemes. In the galactose network, the GAL1/GAL3 paralogues and the GAL2 gene enhance their own expression mediated by the Gal4p transcriptional activator. The wiring strength in these feedback loops is set by the number of Gal4p binding sites. Here we show using synthetic circuits that multiplying the binding sites increases the expression of a gene under the direct control of an activator, but this enhancement is not fed back in the circuit. The feedback loops are rather activated by genes that have frequent stochastic bursts and fast RNA decay rates. In this way, rapid adaptation to galactose can be triggered even by weakly expressed genes. Our results indicate that nonlinear stochastic transcriptional responses enable feedback loops to function autonomously, or contrary to what is dictated by the strength of interactions enclosing the circuit

Effective Rheology of Bubbles Moving in a Capillary Tube

We calculate the average volumetric flux versus pressure drop of bubbles moving in a single capillary tube with varying diameter, finding a square-root relation from mapping the flow equations onto that of a driven overdamped pendulum. The calculation is based on a derivation of the equation of motion of a bubble train from considering the capillary forces and the entropy production associated with the viscous flow. We also calculate the configurational probability of the positions of the bubbles.Comment: 4 pages, 1 figur

Functional gene expression profile underlying methotrexate-induced senescence in human colon cancer cells

Cellular functions accompanying establishment of premature senescence in methotrexate-treated human colon cancer C85 cells are deciphered in the present study from validated competitive expression microarray data, analyzed with the use of Ingenuity Pathways Analysis (IPA) software. The nitrosative/oxidative stress, inferred from upregulated expression of inducible nitric oxide synthase (iNOS) and mitochondrial dysfunction-associated genes, including monoamine oxidases MAOA and MAOB, β-amyloid precursor protein (APP) and presenilin 1 (PSEN1), is identified as the main determinant of signaling pathways operating during senescence establishment. Activation of p53-signaling pathway is found associated with both apoptotic and autophagic components contributing to this process. Activation of nuclear factor κB (NF-κB), resulting from interferon γ (IFNγ), integrin, interleukin 1β (IL-1β), IL-4, IL-13, IL-22, Toll-like receptors (TLRs) 1, 2 and 3, growth factors and tumor necrosis factor (TNF) superfamily members signaling, is found to underpin inflammatory properties of senescent C85 cells. Upregulation of p21-activated kinases (PAK2 and PAK6), several Rho molecules and myosin regulatory light chains MYL12A and MYL12B, indicates acquisition of motility by those cells. Mitogen-activated protein kinase p38 MAPK β, extracellular signal-regulated kinases ERK2 and ERK5, protein kinase B AKT1, as well as calcium, are identified as factors coordinating signaling pathways in senescent C85 cells

Shear wave velocity prediction using seismic attributes and well log data

Formation’s properties can be estimated indirectly using joint analysis of compressional and shear wave velocities. Shear wave data isnot usually acquired during well logging, which is most likely for costsaving purposes. Even if shear data is available, the logging programs provide only sparsely sampled one-dimensional measurements: this informationis inadequate to estimate reservoir rock properties. Thus, if the shear wave data can be obtained using seismic methods, the results can be used across the field to estimate reservoir properties. The aim of this paper is to use seismic attributes for prediction of shear wave velocity in a field located in southern part of Iran. Independent component analysis(ICA) was used to select the most relevant attributes to shear velocity data. Considering the nonlinear relationship between seismic attributes and shear wave velocity, multi-layer feed forward neural network was used for prediction of shear wave velocity and promising results were presented

Toi-1235 b: A keystone super-earth for testing radius valley emergence models around early m dwarfs

Small planets on close-in orbits tend to exhibit envelope mass fractions of either effectively zero or up to a few percent depending on their size and orbital period. Models of thermally-driven atmospheric mass loss and of terrestrial planet formation in a gas-poor environment make distinct predictions regarding the location of this rocky/non-rocky transition in period-radius space. Here we present the confirmation of TOI-1235 b ($P=3.44$ days, $r_p=1.738^{+0.087}_{-0.076}$ R$_{\oplus}$), a planet whose size and period are intermediate between the competing model predictions, thus making the system an important test case for emergence models of the rocky/non-rocky transition around early M dwarfs ($R_s=0.630\pm 0.015$ R$_{\odot}$, $M_s=0.640\pm 0.016$ M$_{\odot}$). We confirm the TESS planet discovery using reconnaissance spectroscopy, ground-based photometry, high-resolution imaging, and a set of 38 precise radial-velocities from HARPS-N and HIRES. We measure a planet mass of $6.91^{+0.75}_{-0.85}$ M$_{\oplus}$ which implies an iron core mass fraction of $20^{+15}_{-12}$% in the absence of a gaseous envelope. The bulk composition of TOI-1235 b is therefore consistent with being Earth-like and we constrain a H/He envelope mass fraction to be $<0.5$% at 90% confidence. Our results are consistent with model predictions from thermally-driven atmospheric mass loss but not with gas-poor formation, which suggests that the former class of processes remain efficient at sculpting close-in planets around early M dwarfs. Our RV analysis also reveals a strong periodicity close to the first harmonic of the photometrically-determined stellar rotation period that we treat as stellar activity, despite other lines of evidence favoring a planetary origin ($P=21.8^{+0.9}_{-0.8}$ days, $m_p\sin{i}=13.0^{+3.8}_{-5.3}$ M$_{\oplus}$) that cannot be firmly ruled out by our data

The TOP-SCOPE Survey of Planck Galactic Cold Clumps: Survey Overview and Results of an Exemplar Source, PGCC G26.53+0.17

This is the final version. Available from American Astronomical Society via the DOI in this record.The low dust temperatures (<14 K) of Planck Galactic cold clumps (PGCCs) make them ideal targets to probe the initial conditions and very early phase of star formation. "TOP-SCOPE" is a joint survey program targeting ∼2000 PGCCs in J = 1-0 transitions of CO isotopologues and ∼1000 PGCCs in 850 μm continuum emission. The objective of the "TOP-SCOPE" survey and the joint surveys (SMT 10 m, KVN 21 m, and NRO 45 m) is to statistically study the initial conditions occurring during star formation and the evolution of molecular clouds, across a wide range of environments. The observations, data analysis, and example science cases for these surveys are introduced with an exemplar source, PGCC G26.53+0.17 (G26), which is a filamentary infrared dark cloud (IRDC). The total mass, length, and mean line mass (M/L) of the G26 filament are ∼6200 M, ∼12 pc, and ∼500 Mpc-1, respectively. Ten massive clumps, including eight starless ones, are found along the filament. The most massive clump as a whole may still be in global collapse, while its denser part seems to be undergoing expansion owing to outflow feedback. The fragmentation in the G26 filament from cloud scale to clump scale is in agreement with gravitational fragmentation of an isothermal, nonmagnetized, and turbulent supported cylinder. A bimodal behavior in dust emissivity spectral index (β) distribution is found in G26, suggesting grain growth along the filament. The G26 filament may be formed owing to large-scale compression flows evidenced by the temperature and velocity gradients across its natal cloud.German Research FoundationJoint Research Fund in AstronomyTop Talents Program of Yunnan ProvinceAcademy of FinlandMinistry of Education, Science, and TechnologyNational Research Foundation of KoreaChinese Academy of SciencesMinistry of Science and Technology of TaiwanEuropean Research Counci

Predictors of disease worsening defined by progression of organ damage in diffuse systemic sclerosis: a European Scleroderma Trials and Research (EUSTAR) analysis.

Objectives Mortality and worsening of organ function are desirable endpoints for clinical trials in systemic sclerosis (SSc). The aim of this study was to identify factors that allow enrichment of patients with these endpoints, in a population of patients from the European Scleroderma Trials and Research group database. Methods Inclusion criteria were diagnosis of diffuse SSc and follow-up over 12\ub13 months. Disease worsening/organ progression was fulfilled if any of the following events occurred: new renal crisis; decrease of lung or heart function; new echocardiography-suspected pulmonary hypertension or death. In total, 42 clinical parameters were chosen as predictors for the analysis by using (1) imputation of missing data on the basis of multivariate imputation and (2) least absolute shrinkage and selection operator regression. Results Of 1451 patients meeting the inclusion criteria, 706 had complete data on outcome parameters and were included in the analysis. Of the 42 outcome predictors, eight remained in the final regression model. There was substantial evidence for a strong association between disease progression and age, active digital ulcer (DU), lung fibrosis, muscle weakness and elevated C-reactive protein (CRP) level. Active DU, CRP elevation, lung fibrosis and muscle weakness were also associated with a significantly shorter time to disease progression. A bootstrap validation step with 10 000 repetitions successfully validated the model. Conclusions The use of the predictive factors presented here could enable cohort enrichment with patients at risk for overall disease worsening in SSc clinical trial

Particle identification in ALICE: a Bayesian approach

We present a Bayesian approach to particle identification (PID) within the ALICE experiment. The aim is to more effectively combine the particle identification capabilities of its various detectors. After a brief explanation of the adopted methodology and formalism, the performance of the Bayesian PID approach for charged pions, kaons and protons in the central barrel of ALICE is studied. PID is performed via measurements of specific energy loss ($\mathrm{d}E/\mathrm{d}x$) and time-of-flight. PID efficiencies and misidentification probabilities are extracted and compared with Monte Carlo simulations using high-purity samples of identified particles in the decay channels ${\rm K}^0_S \rightarrow \pi^-\pi^+$, $\phi \rightarrow {\rm K}^-{\rm K}^+$, and $\Lambda \rightarrow {\rm p}\pi^-$ in p-Pb collisions at $\sqrt{s_{\rm NN}}=5.02$ TeV. In order to thoroughly assess the validity of the Bayesian approach, this methodology was used to obtain corrected $p_{\rm T}$ spectra of pions, kaons, protons, and D$^0$ mesons in pp collisions at $\sqrt{s}=7$ TeV. In all cases, the results using Bayesian PID were found to be consistent with previous measurements performed by ALICE using a standard PID approach. For the measurement of D$^0 \rightarrow {\rm K}^-\pi^+$, it was found that a Bayesian PID approach gave a higher signal-to-background ratio and a similar or larger statistical significance when compared with standard PID selections, despite a reduced identification efficiency. Finally, we present an exploratory study of the measurement of $\Lambda_{\rm c}^{+}\rightarrow {\rm p} {\rm K}^-\pi^+$ in pp collisions at $\sqrt{s}=7$ TeV, using the Bayesian approach for the identification of its decay products