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Detection and separation of the subtle post-seismic deformation signals associated with moderate magnitude earthquakes from interferometric synthetic aperture radar (InSAR) time-series is often challenging. Singular spectrum analysis (SSA) is a statistical non‐parametric technique used to decompose and reconstruct signals from complex time-series data. We show that the SSA analysis effectively distinguished the post-seismic signal associated with the 2019 M w 6 Mirpur earthquake from periodic and noise components. The SSA-derived post-seismic deformation signal is smoother and fits better to an exponential model with a decay time of 34 d. The post-seismic deformation is confined to the southeast of the rupture area and lasted for ∼90 d following the main shock. Inversion of the post-seismic deformation suggests an afterslip mechanism with a maximum slip of ∼0.07 m on the shallow, updip portions of the Main Himalayan Thrust. The 2019 Mirpur earthquake and afterslip together released less than 12 per cent of the accumulated strain energy since the 1555 Kashmir earthquake and implies continued seismic hazard in the future. [ABSTRACT FROM AUTHOR]

The massive binary HDE 228766 is composed of an O type primary and an evolved secondary. However, previous qualitative analyses of the composite spectrum have led to a wide discussion about whether the secondary is an Of or a Wolf–Rayet star. We use new observations and our novel QER20 package to disentangle for the first time the spectra of the two stellar components and obtain artefact |$-$| free reconstructed spectra, yielding the more accurate and reliable spectral classifications of O7.5 V((f))z for the primary and O6 Iaf for the secondary. The emission features of the P |$-$| Cygni profiles of the H  |$\beta$| and He i 5876 Å lines, present in the reconstructed spectrum of the secondary, show that this star is at an initial phase of its transition to the WN evolutionary stage. A previously unobserved variable emission, composed of at least four independent features, is seen since 2014 superposed to the H  |$\gamma$| absorption line. Our analysis reveals that these emission features originate from a physically extended region. This could be explained by an episode of enhanced mass-loss in the scenario of a non |$-$| conservative evolution of the binary. [ABSTRACT FROM AUTHOR]

Future surveys could obtain tighter constraints on the cosmological parameters with the galaxy power spectrum than with the cosmic microwave background. However, the inclusion of multiple overlapping tracers, redshift bins, and more non-linear scales means that generating the necessary ensemble of simulations for model-fitting presents a computational burden. In this work, we combine full-shape fitting of galaxy power spectra, analytical covariance matrix estimates, the massively optimized parameter estimation and data compression (MOPED) method, and the Taylor expansion interpolation of the power spectrum for the first time to constrain the cosmological parameters directly from a state-of-the-art set of galaxy clustering measurements. We find it takes less than a day to compute the analytical covariance while it takes several months to calculate the simulated ones. Combining MOPED with the Taylor expansion interpolation of the power spectrum, we can constrain the cosmological parameters in just a few hours instead of a few days. We also find that even without a priori knowledge of the best-fitting cosmological or galaxy bias parameters, the analytical covariance matrix with the MOPED compression still gives consistent cosmological constraints to within 0.1σ after two iterations. Therefore, the pipeline we have developed here can significantly speed up the analysis for future surveys. [ABSTRACT FROM AUTHOR]

We evaluate the effectiveness of early dark energy (EDE) in addressing the Hubble tension using the luminous red galaxy (LRG), quasar (QSO), and emission line galaxy (ELG) samples from the completed eBOSS survey. We perform cosmological parameter measurements based on full shape analysis of the power spectrum employing the effective field theory of large-scale structure (EFTofLSS). EDE is known to strongly suffer from volume projection effects, complicating cosmological constraints' interpretation. To quantify the volume projection effects within an EDE full shape analysis, we explore the impact of different prior choices on the nuisance parameters of EFTofLSS through an extensive mock study. We compare classical Gaussian priors to the non-informative Jeffreys prior, known to mitigate volume projection effects in ΛCDM. Our full shape analysis combines eBOSS and BOSS data with Planck , external Baryon Acoustic Oscillation (BAO), PantheonPlus, and SH0ES supernova data. EDE reduces the tension from 5.2σ to 3σ compared to ΛCDM, yielding |$H_0=71.73_{-0.86}^{+0.82}$| km s−1 Mpc−1 with |$f_\mathrm{EDE} = 0.1179_{-0.022}^{+0.025}$| (Gaussian priors) and |$H_0=72.03_{-0.87}^{+0.82}$| km s−1 Mpc−1 with |$f_\mathrm{EDE} = 0.1399_{-0.022}^{+0.023}$| (Jeffreys prior). Although the Hubble tension is mitigated compared to ΛCDM, the inclusion of eBOSS data amplifies the tension within EDE from 2σ to 3σ, in contrast to the full shape analysis of BOSS data with Planck , external BAO, PantheonPlus, and SH0ES. This highlights the significance of incorporating additional large-scale structure data in discussions concerning models aiming to resolve the Hubble tension. [ABSTRACT FROM AUTHOR]

Motivation Zooarchaeology by Mass Spectrometry (ZooMS) is a palaeoproteomics method for the taxonomic determination of collagen, which traditionally involves challenging manual spectra analysis with limitations in quantitative results. As the ZooMS reference database expands, a faster and reproducible identification tool is necessary. Here we present SpecieScan, an open-access algorithm for automating taxa identification from raw MALDI-ToF mass spectrometry (MS) data. Results SpecieScan was developed using R (pre-processing) and Python (automation). The algorithm's output includes identified peptide markers, closest matching taxonomic group (taxon, family, order), correlation scores with the reference databases, and contaminant peaks present in the spectra. Testing on original MS data from bones discovered at Palaeothic archaeological sites, including Denisova Cave in Russia, as well as using publicly-available, externally produced data, we achieved >90% accuracy at the genus-level and ∼92% accuracy at the family-level for mammalian bone collagen previously analysed manually. Availability and implementation The SpecieScan algorithm, along with the raw data used in testing, results, reference database, and common contaminants lists are freely available on Github (https://github.com/mesve/SpecieScan). [ABSTRACT FROM AUTHOR]

Background Efficient infection control during carbapenem-resistant Enterobacterales outbreaks demands rapid and simple techniques for outbreak investigations. WGS, the current gold standard for outbreak identification, is expensive, time-consuming and requires a high level of expertise. Fourier-transform infrared (FTIR) spectroscopy (IR Biotyper) is a rapid typing method based on infrared radiation applied to samples, which provides a highly specific absorption spectrum. Objectives To investigate an outbreak of OXA-48-producing Escherichia coli in real-time using FTIR and subsequently compare the results with WGS. Methods Twenty-one isolates were collected during a nosocomial outbreak, and identification and antibiotic susceptibilities were confirmed by VITEK®2. FTIR was conducted for all isolates, and nine representative isolates were sequenced. Results FTIR was able to correctly determine the clonal relatedness of the isolates and to identify the outbreak cluster, as confirmed by WGS. By WGS, isolates in the main FTIR cluster belonged to the same MLST type and core-genome MLST type, and they harboured similar plasmids and resistance genes, whereas the singletons external to the FTIR cluster had different genetic content. Conclusions FTIR can operate as a rapid, efficient and reliable first-line tool for outbreak investigations during a real-time ongoing E. coli outbreak, which can contribute to limiting the spread of pathogens. [ABSTRACT FROM AUTHOR]

Objectives To differentiate high-grade from low-grade clear cell renal cell carcinoma (ccRCC) using diffusion-relaxation correlation spectroscopic imaging (DR-CSI) spectra in an equal separating analysis. Methods Eighty patients with 86 pathologically confirmed ccRCCs who underwent DR-CSI were enrolled. Two radiologists delineated the region of interest. The spectrum was derived based on DR-CSI and was further segmented into multiple equal subregions from 2*2 to 9*9. The agreement between the 2 radiologists was assessed by the intraclass correlation coefficient (ICC). Logistic regression was used to establish the regression model for differentiation, and 5-fold cross-validation was used to evaluate its accuracy. McNemar's test was used to compare the diagnostic performance between equipartition models and the traditional parameters, including the apparent diffusion coefficient (ADC) and T2 value. Results The inter-reader agreement decreased as the divisions in the equipartition model increased (overall ICC ranged from 0.859 to 0.920). The accuracy increased from the 2*2 to 9*9 equipartition model (0.68 for 2*2, 0.69 for 3*3 and 4*4, 0.70 for 5*5, 0.71 for 6*6, 0.78 for 7*7, and 0.75 for 8*8 and 9*9). The equipartition models with divisions >7*7 were significantly better than ADC and T2 (vs ADC: P  = .002-.008; vs T2: P  = .001-.004). Conclusions The equipartition method has the potential to analyse the DR-CSI spectrum and discriminate between low-grade and high-grade ccRCC. Advances in knowledge The evaluation of DR-CSI relies on prior knowledge, and how to assess the spectrum derived from DR-CSI without prior knowledge has not been well studied. [ABSTRACT FROM AUTHOR]

Field-level inference is emerging as a promising technique for optimally extracting information from cosmological data sets. Previous analyses have shown field-based inference produces tighter parameter constraints than power spectrum analyses. However, estimates of the detailed quantitative gain in constraining power differ. Here, we demonstrate the gain in constraining power depends on the parameter space being constrained. As a specific example, we find that lognormal field-based analysis of an LSST Y1-like mock data set only marginally improves constraints relative to a 2-point function analysis in Lambda cold dark matter (ΛCDM), yet it more than doubles the constraining power of the data in the context of w CDM models. This effect reconciles some, but not all, of the discrepant results found in the literature. Our results suggest the importance of using a full systematics model when quantifying the information gain for realistic field-level analyses of future data sets. [ABSTRACT FROM AUTHOR]

Accepted by: Konstantinos Nikolopoulos One of the challenges of emergency ambulance demand (EAD) time series prediction lies in their non-stationary nature. We study this important problem and propose two hybrid forecasting models, which combine the singular spectrum analysis (SSA) time-series technique with autoregressive integrated moving average (ARIMA) parameterized multivariate forecasting. Both daily and hourly time series are studied. The non-stationary time series are decomposed into three eigentriples by SSA: trends, periodic components and residuals. Selection of the group boundary point of the periodic component is a key issue in the SSA method. We use spectrum analysis to compute a threshold for maximum information content of periodic components. ARIMA mean value prediction models are employed to forecast the trends, periodic components and residuals sub-series. Our research compares ARIMA and SSA-based hybrid models by considering the emergency dispatching departure records of six core districts in Guangzhou city from 1 January 2021 to 31 December 2021. Results show that the integrated SSA-ARIMA model performs best. SSA is a very effective pre-processing method for non-stationary time series prediction. The predictive accuracy of using a hybrid model for hourly EAD time series is higher than that for daily ones. Our discussion should be useful for improving EAD prediction in contexts others than that considered in our research. [ABSTRACT FROM AUTHOR]

Spherical stellar systems have weakly damped response modes. The dipole modes are seiche modes. The quadrupole are zero pattern-speed prolate modes, the stable precursors to the radial orbit instability (ROI). We demonstrate that small wiggles in the distribution function (DF) can destabilize the dipole modes and describe the newly identified instabilities in NFW-like dark-matter (DM) haloes and other power-law spherical systems. The modes were identified in N -body simulations using multivariate singular spectrum analysis and corroborated using linear-response theory. The new mode peaks inside the half-mass radius but has a pattern speed typical of an outer-halo orbit. As it grows, the radial angle of the eccentric orbits that make up the mode correlates and loses angular momentum by a resonant couple to outer-halo orbits. This leads to an unsteady pattern with a density enhancement that swings from one side of the halo to another along a diameter, like the orbits that comprise the instability. In this way, the dipole mode is similar to the ROI. Since the DF found in Nature is unlikely to be smooth and isotropic with d f (E)/d E < 0 necessary for Antonov stability, these modes may be ubiquitous albeit slowly growing. Haloes that are less extended than NFW, such as the Hernquist model, tend to be stable to this dipole instability. We present the critical stability exponents for one- and two-power models. These different critical outer power-law exponents illustrate that the gravitational coupling between the inner and outer DM halo depends on the global shape of density profile. [ABSTRACT FROM AUTHOR]

The precise estimation of the mass changes in Madagascar is a challenge by using the Gravity Recovery and Climate Experiment (GRACE) mission Level-2 products since they are contaminated by noise. Although this issue can be alleviated by the empirical destriping method or spatial filtering, they result in potential signal distortion or signal leakage. To improve this, we propose a reconstructive filter, whose parameters are optimized by the signal-to-noise ratio. Subsequently, our optimal filter corresponding to the best signal-to-noise ratio (5.63) is used to estimate the mass changes (2002–2017) in Madagascar. Eventually, our results are compared with two reliable GRACE mascon products and other independent observations. Correspondingly, here are our major conclusions: (1) Compared with groundwater storage from the mascon products, our estimates have the highest Pearson correlation (0.5) with in situ observation and can detect the rapid increase of groundwater storage during the rainy season. (2) The Fourier spectrum analysis detects a ∼3.8-yr periodic signal in the terrestrial water storage changes in Madagascar, which is contributed from the interannual precipitation driven by climate factor (Indian Ocean Dipole) and the aliasing error for imperfect GRACE pre-process. Our work introduces an effective filter for processing GRACE Level-2 data and presents novel insights into mass changes in Madagascar. [ABSTRACT FROM AUTHOR]

The next generation of weak lensing surveys will measure the matter distribution of the local universe with unprecedented precision, allowing the resolution of non-Gaussian features of the convergence field. This encourages the use of higher-order mass-map statistics for cosmological parameter inference. We extend the forward-modelling based methodology introduced in a previous forecast paper to match these new requirements. We provide multiple forecasts for the |$w$| CDM parameter constraints that can be expected from stage 3 and 4 weak lensing surveys. We consider different survey setups, summary statistics and mass map filters including wavelets. We take into account the shear bias, photometric redshift uncertainties, and intrinsic alignment. The impact of baryons is investigated and the necessary scale cuts are applied. We compare the angular power spectrum analysis to peak and minima counts as well as Minkowski functionals of the mass maps. We find a preference for Starlet over Gaussian filters. Our results suggest that using a survey setup with 10 instead of 5 tomographic redshift bins is beneficial. Adding cross-tomographic information improves the constraints on cosmology and especially on galaxy intrinsic alignment for all statistics. In terms of constraining power, we find the angular power spectrum and the peak counts to be equally matched for stage 4 surveys, followed by minima counts and the Minkowski functionals. Combining different summary statistics significantly improves the constraints and compensates the stringent scale cuts. We identify the most 'cost-effective' combination to be the angular power spectrum, peak counts and Minkowski functionals following Starlet filtering. [ABSTRACT FROM AUTHOR]

We explore the timing and spectral properties of GRS 1915+105 based on X-ray observations of NICER and Insight -HXMT during the long outburst from 2017 to 2021. We find a new class of variability in the rising stage of the outburst that differs from the formerly reported patterns of light curves. This new variability pattern, which we name class ψ, is characterized by several periodic mini pulses superposed on another longer periodic pulse. The periods are ∼130 and ∼10 s for the main pulses and mini pulses, respectively, based on the analysis of power spectrum density and step-wise filter correlation (SFC), where the SFC method has an advantage in finding the superimposed periodic components. The mini pulses become weak or disappear when the luminosity increases and the light curves change into the classical class κ. The class ψ shows a softer spectrum with lower count rates compared to the class κ during the main pulse. The new class ψ shows peculiar timing and spectral properties compared to those of classic class κ, which can help us to explore the class transition mechanism in GRS 1915+105. [ABSTRACT FROM AUTHOR]

We present early-stage analyses of low-resolution (R = 1000) optical spectra and near-infrared light curves of the bright Type II supernova (SN II) 2023ixf in the notable nearby face-on spiral galaxy M 101, which were obtained from t = 1.7 to 8.0 d. Our first spectrum showed remarkable emission features of the Balmer series, He  ii , N  iii , C  iv , and N  iv with a strong blue continuum. Compared with the SNe II which show flash-ionized features, we suggest that this SN could be categorized as a high-luminosity SN II with a nitrogen/helium-rich circumstellar material (CSM), e.g., SNe 2014G, 2017ahn, and 2020pni. The Hα emission line can be tentatively explained by a narrower component with a velocity of <300 km s−1 and a broader one with ∼2200 km s−1. The near-infrared light curves were well consistent with those of the another luminous SN 2017ahn, and its absolute magnitudes are located at the bright end of the luminosity distribution of SNe II. These observational facts support that SN 2023ixf is well consistent with high-luminosity SNe II showing evidence of a dense nitrogen/helium-rich CSM. [ABSTRACT FROM AUTHOR]

We report the analysis of high-precision space-based photometric and high-resolution spectroscopic observations of HD 180347. The high-quality light curves from the Transiting Exoplanet Survey Satellite (TESS) under sectors 14, 15, and 26 were used. By visual inspection of the light curves and the Fourier transforms, only low-frequency signals (less than 1 d−1) were detected. After using wavelet, autocorrelation, and composite spectrum analyses, HD 180347 is classified as a rotational variable with a period of about 4.1 ± 0.2 d. In reference to the observation limit of TESS , no pulsations were detected. For the spectroscopic analysis, we used data collected with the High Efficiency and Resolution Mercator Échelle Spectrograph (HERMES). We determined the spectral type of this star and obtained atmospheric parameters such as the effective temperature, the surface gravity, and the projected rotational, microturbulent, and radial velocities. We performed a detailed chemical abundance analysis. The LTE abundances were derived for 25 chemical elements. For 13 of them, including Ca, Sc, Sr, Zr, and Ba, which are important for the characterization of chemical peculiarities, we also present the non-local thermodynamic equilibrium (NLTE) abundances. NLTE improves the accuracy of the derived abundances and confirms that Ca and Sc are depleted in HD 180347 relative to their solar abundances, while the heavy elements beyond Sr are enhanced, by more than 0.7 dex. Based on the spectral class and the element abundance pattern, we classify this star as Am (kA1hA8mA8). [ABSTRACT FROM AUTHOR]

We provide in this paper new Stark broadening parameters for the four ions Ga IV, Ga V, Ge IV, and Ge V. The calculations have been performed using our quantum mechanical method. To the best of our knowledge, the only available Stark broadening results are those of the Ge IV ion, where the semiclassical perturbation and the modified semi-empirical methods have been used. For the three other ions, no data have been found. In 2020 and for the first time, about five hundred lines of trans-iron elements including gallium (Ga) and germanium (Ge) have been identified in the ultraviolet (UV) spectrum of a DAO-type white dwarf BD-22°3467. Other precedent observations showed the existence of Ga IV–V lines in two white dwarfs (G191-B2B and RE 0503-289), and those of Ge IV and Ge V in the UV spectrum of RE 0503-289. Theoretical evaluations and measurements of atomic and Stark broadening data are a pre-requisite for stellar-atmosphere modelling, which is a tool for the determination of the photospheric Ga and Ge abundance in white dwarfs. Since there is no Stark broadening data for the three ions Ga IV, Ga V, and Ge V, our calculations come to fill this gap, and the obtained results can be used for the abundance determination of elements, the calculation of stellar opacity, the interpretation and modelling of stellar spectra, and the estimation of the relative transfer through stellar plasmas. They will be also implemented into the data base of Stark broadening parameters, STARK-B. [ABSTRACT FROM AUTHOR]

Diffractions are seismic waves generated by small-scale heterogeneities in the subsurface. These are often superimposed by strong reflections so that they are not visible on the image, leading to misinterpretation and incorrect localization of the scatterers. Therefore, the separation of diffracted and reflected waves is a crucial step in identifying these small-scale diffractors. To realize the separation of diffraction and imaging, a least-squares reverse time migration method of plane waves (PLSRTM) optimized with short-time singular spectrum analysis (STSSA) was developed in this work. The proposed STSSA algorithm exploits the properties of singular spectral analysis (SSA) to separate linear signals. By establishing the Hanning window and the energy compensation function, it also compensates for the shortcomings of SSA in local dip processing and convergence of linear signals. As there is no clear boundary between reflected and diffracted waves, the energy loss during separation leads to a slow convergence rate of the diffraction wave imaging technique. We use STSSA as a constraint for PLSRTM, which greatly improves the imaging quality for diffraction waves. The tests with the Sigsbee2A model and noisy seismic data have shown that our method can effectively improve the resolution of diffraction wave imaging and that the constraint of STSSA increases the robustness to noisy data. [ABSTRACT FROM AUTHOR]

Studying coupling between different galactic components is a challenging problem in galactic dynamics. Using basis function expansions (BFEs) and multichannel singular spectrum analysis (mSSA) as a means of dynamical data mining, we discover evidence for two multicomponent disc–halo dipole modes in a Milky-Way-like simulated galaxy. One of the modes grows throughout the simulation, while the other decays throughout the simulation. The multicomponent disc–halo modes are driven primarily by the halo, and have implications for the structural evolution of galaxies, including observations of lopsidedness and other non-axisymmetric structure. In our simulation, the modes create surface density features up to 10 per cent relative to the equilibrium model stellar disc. While the simulated galaxy was constructed to be in equilibrium, BFE + mSSA also uncovered evidence of persistent periodic signals incited by aphysical initial conditions disequilibrium, including rings and weak two-armed spirals, both at the 1 per cent level. The method is sensitive to distinct evolutionary features at and even below the 1 per cent level of surface density variation. The use of mSSA produced clean signals for both modes and disequilibrium, efficiently removing variance owing to estimator noise from the input BFE time series. The discovery of multicomponent halo–disc modes is strong motivation for application of BFE + mSSA to the rich zoo of dynamics of multicomponent interacting galaxies. [ABSTRACT FROM AUTHOR]

Primary aromatic amines (PAAs) are a class of hazardous substances where many compounds are classified as carcinogen, mutagen, and reproduction toxin (CMR). PAAs can be taken up by dermal exposure. In the polyurethane industry, a valid and trustworthy method for the quantification of PAAs in the presence of isocyanates that could interfere is of great interest, especially on workplaces where a regular contact to PAAs cannot be excluded. The aim of this work is the development, validation, and verification of a novel sampling device to quantify selectively the PAA load on work surfaces. We describe the synthesis of Cell-ßALA-PEMSA analytical papers and their characterization by infrared spectroscopy and thermogravimetric analysis. The recovery of TDA and MDA spiked on these filters is satisfactory. An excellent selectivity of Cell-ßALA-PEMSA papers towards PAAs in the presence of isocyanates of almost 100% was found by wipe tests of amine/isocyanate contaminated surfaces. First positive field tests were achieved at certain areas in a Polyurethane Technical Application Department where surface contamination with PAAs was expected, and the Cell-ßALA-PEMSA analytical papers were superior to an established method of surface sampling. However, recovery of these amines from surfaces shows a large variability, and more work is required to address influencing surface properties. [ABSTRACT FROM AUTHOR]

Understanding the temporal characteristics of data from low-frequency radio telescopes is of importance in devising suitable calibration strategies. Application of time-series analysis techniques to data from radio telescopes can reveal a wealth of information that can aid in calibration. In this paper, we investigate singular spectrum analysis (SSA) as an analysis tool for radio data. We show the intimate connection between SSA and Fourier techniques. We develop the relevant mathematics starting with an idealized periodic dataset and proceeding to include various non-ideal behaviours. We propose a novel technique to obtain long-term gain changes in data, leveraging the periodicity arising from sky drift through the antenna beams. We also simulate several plausible scenarios and apply the techniques to a 30-day time series data collected during 2021 June from SITARA – a short-spacing two element interferometer for global 21-cm detection. Applying the techniques to real data, we find that the first reconstructed component – the trend – has a strong anti-correlation with the local temperature suggesting temperature fluctuations as the most likely origin for the observed variations in the data. We also study the limitations of the calibration in the presence of diurnal gain variations and find that such variations are the likely impediment to calibrating SITARA data with SSA. [ABSTRACT FROM AUTHOR]

Interacting dark energy models have been suggested as alternatives to the standard cosmological model, ΛCDM. We focus on a phenomenologically interesting class of dark scattering models that is characterized by pure momentum exchange between dark energy and dark matter. This model extends the parameter space with respect to ΛCDM by two parameters, w and A , which define the dark energy equation of state and the strength of the coupling between dark energy and dark matter, respectively. In order to test non-standard cosmologies with Stage-IV galaxy clustering surveys, it is crucial to model mildly non-linear scales and perform precision versus accuracy tests. We use the Effective Field Theory of Large-Scale Structure; and we perform validation tests by means of an MCMC analysis using a large set of N -body simulations. We find that adding the bispectrum monopole to the power spectrum multipoles improves the constraints on the dark energy parameters by |$\sim 30 {{\ \rm per\ cent}}$| for |$k_{\mathrm{max}, B}^{l=0} = 0.11$|   h  Mpc−1, without introducing biases in the parameter estimation. We also find that the same improvement can be achieved with more moderate scale cuts and the use of bias relations, or with the addition of the bispectrum quadrupole. Finally, we study degeneracies between the dark energy parameters and the scalar amplitude A s and discuss the corresponding projection effects, as well as degeneracies with other cosmological parameters. [ABSTRACT FROM AUTHOR]

Background There is scarce evidence on the fourth dose of severe acute respiratory syndrome coronavirus 2 vaccines in chronic kidney disease (CKD) patients. We evaluated the humoral response and effectivity of the fourth dose in the CKD spectrum: non-dialysis CKD (ND-CKD), haemodialysis (HD), peritoneal dialysis (PD) and kidney transplant (KT) recipients. Methods This is a prespecified analysis of the prospective, observational, multicentric SENCOVAC study. In patients with CKD who had received a complete initial vaccination and one or two boosters and had anti-Spike antibody determinations 6 and 12 months after the initial vaccination, we analysed factors associated with persistent negative humoral response and higher anti-Spike antibody titres as well as the efficacy of vaccination on coronavirus disease 2019 (COVID-19) severity. Results Of 2186 patients (18% KT, 8% PD, 69% HD and 5% ND-CKD), 30% had received a fourth dose. The fourth dose increased anti-Spike antibody titres in HD (P  = .001) and ND-CKD (P  = .014) patients and seroconverted 72% of previously negative patients. Higher anti-Spike antibody titres at 12 months were independently associated with repeated exposure to antigen (fourth dose, previous breakthrough infections), previous anti-Spike antibody titres and not being a KT recipient. Breakthrough COVID-19 was registered in 137 (6%) patients, 5% of whom required admission. Admitted patients had prior titres <620 UI/ml and median values were lower (P  = .020) than in non-admitted patients. Conclusions A fourth vaccine dose increased anti-Spike antibody titres or seroconverted many CKD patients, but those with the highest need for a vaccine booster (i.e. those with lower pre-booster antibody titres or KT recipients) derived the least benefit in terms of antibody titres. Admission for breakthrough COVID-19 was associated with low anti-Spike antibody titres. [ABSTRACT FROM AUTHOR]

The time‐varying frequency characteristics of many biomedical time series contain important scientific information. However, the high‐dimensional nature of the time‐varying power spectrum as a surface in time and frequency limits its direct use by applied researchers and clinicians for elucidating complex mechanisms. In this article, we introduce a new approach to time–frequency analysis that decomposes the time‐varying power spectrum in to orthogonal rank‐one layers in time and frequency to provide a parsimonious representation that illustrates relationships between power at different times and frequencies. The approach can be used in fully nonparametric analyses or in semiparametric analyses that account for exogenous information and time‐varying covariates. An estimation procedure is formulated within a penalized reduced‐rank regression framework that provides estimates of layers that are interpretable as power localized within time blocks and frequency bands. Empirical properties of the procedure are illustrated in simulation studies and its practical use is demonstrated through an analysis of heart rate variability during sleep. [ABSTRACT FROM AUTHOR]

Thermomagnetic instability is a crucial issue for the application of superconductors. Effects of edge cracks on the thermomagnetic instability of superconducting thin films are systematically investigated in this work. Dendritic flux avalanches in thin films are well reproduced through electrodynamics simulations, and relevant physical mechanisms are revealed from dissipative vortex dynamics simulations. It is found that edge cracks sharply decrease the threshold field for the thermomagnetic instability of superconducting films. Spectrum analysis shows that the time series of magnetization jumping displays scale-invariance and follows a power law with an exponent around 1.9. In a cracked film, flux jumps more frequently with lower amplitudes compared with its crack-less counterpart. As the crack extends, the threshold field decreases, the jumping frequency gets lower, while its magnitude gets larger. When the crack has extended long enough, the threshold field increases to even larger than that of the crack-less film. This counterintuitive result originates from the transition of the thermomagnetic instability triggered at the crack tip to the one triggered at the center of the crack edges, which is validated by the multifractal spectrum of magnetization jumping sequences. In addition, with the variation of crack lengths, three different modes of vortex motion are found, which explains the different flux patterns formed in the avalanche process. [ABSTRACT FROM AUTHOR]

The central part of the Galaxy hosts a multitude of stellar populations, including the spheroidal bulge stars, stars moved to the bulge through secular evolution of the bar, inner halo, inner thick disc, inner thin disc, as well as debris from past accretion events. We identified a sample of 58 candidate stars belonging to the stellar population of the spheroidal bulge, and analyse their abundances. The present calculations of Mg, Ca, and Si lines are in agreement with the ASPCAP abundances, whereas abundances of C, N, O, and Ce are re-examined. We find normal α-element enhancements in oxygen, similar to magnesium, Si, and Ca abundances, which are typical of other bulge stars surveyed in the optical in Baade's Window. The enhancement of [O/Fe] in these stars suggests that they do not belong to accreted debris. No spread in N abundances is found, and none of the sample stars is N-rich, indicating that these stars are not second generation stars originated in globular clusters. Ce instead is enhanced in the sample stars, which points to an s-process origin such as due to enrichment from early generations of massive fast rotating stars, the so-called spinstars. [ABSTRACT FROM AUTHOR]

Here, we investigate the kinematics of the part of the broad-line region (BLR) in active galactic nuclei (AGNs) emitting H β and H α emission lines. We explore the widths and asymmetries of the broad H β and H α emission lines in a sample of high-quality (i.e. high signal-to-noise ratio) spectra of type-1 AGN taken from the Data Release 16 of the Sloan Digital Sky Survey in order to explore possible deviation from the gravitationally bound motion. To find only the broad component of H β and H α, we use the fantasy (Fully Automated pythoN Tool for AGN Spectra analYsis) code for the multicomponent modelling of the AGN spectra and for careful extraction of the broad emission-line parameters. We show that based on the broad-line profiles widths and asymmetries, the BLR gas emitting H β and H α lines follows similar kinematics, and seems to be virialized in our sample of type-1 AGN. [ABSTRACT FROM AUTHOR]

We analyse medium resolution optical spectra of 14 narrow-line Seyfert 1 galaxies with average to strong iron emission. The targets were observed several times over a 2-yr period to probe the nature of spectral variations. Parameters determined from fitting the line profiles include relative strength, width, and asymmetry. We explore the applicability of various profile combinations to H β. We achieve satisfactory fits using three components: the narrow and broad components characteristic of all Seyfert 1 galaxies and that are reasonably represented by Gaussian profiles, and an intermediate component with width similar to that of the Fe  ii lines. This intermediate component accounted for the largest fraction of the H β flux in most of our sample, especially when fitted with a Lorentzian instead of a Gaussian profile. This Lorentzian component improves the overall H β fits in most cases. In contrast to many other types of active galactic nucleus, no dramatic spectral changes were detected in our sample over the 2-yr period spanning this study, even though some of our targets are known for large and rapid X-ray variability. In particular, we find the variability of the Fe  ii lines relative to the H β intermediate component to be minimal. For the [O  iii ] lines, we identified asymmetries in almost all our targets well represented by two Gaussians: a primary central and a second blueshifted component. These may signify different gas dynamics connected with nuclear outflow. As in several previous studies, we identify a clear correlation between [O  iii ] asymmetry and its core component width. [ABSTRACT FROM AUTHOR]

To evaluate biological effects triggered by low levels of radiation, we established a uniquely sensitive experimental system to detect somatic mutations. By using the system, we found that mutant frequencies induced by X-rays were statistically significant at doses over 0.15 Gy, and a linear dose relationship with the mutant frequency was observed at doses over 0.15 Gy. The mutation spectra analysis revealed that mutation events generated by X-ray doses below 0.1 Gy were similar to those observed in unirradiated controls. In addition, a significant inflection point for both, the mutant frequency and the mutation spectra, was found at dose-rates around 11 mGy/day when cells were cultured in medium containing tritiated water. Because induced radiation-type events presented a clear dose/dose-rate dependency above the critical dose or the inflection point, these observations suggest that mutation events generated by radiation could change at a threshold dose-rate or a critical dose. [ABSTRACT FROM AUTHOR]

We perform a cosmic shear analysis of Hyper Suprime-Cam Subaru Strategic Program first-year data (HSC-Y1) using complete orthogonal sets of E/B-integrals (COSEBIs) to derive cosmological constraints. We compute E/B-mode COSEBIs from cosmic shear two-point correlation functions measured on an angular range of 4′ < θ < 180′. We perform a standard Bayesian likelihood analysis for cosmological inference from the measured E-mode COSEBIs, including contributions from intrinsic alignments of galaxies as well as systematic effects from point spread function model errors, shear calibration uncertainties, and source redshift distribution errors. We adopt a covariance matrix derived from realistic mock catalogs constructed from full-sky gravitational lensing simulations that fully take account of the survey geometry and measurement noise. For a flat Λ cold dark matter model, we find |$S\,_8 \equiv \sigma _8\sqrt{\Omega _{\rm m}/0.3}=0.809_{-0.026}^{+0.036}$|⁠. We carefully check the robustness of the cosmological results against astrophysical modeling uncertainties and systematic uncertainties in measurements, and find that none of them has a significant impact on the cosmological constraints. We also find that the measured B-mode COSEBIs are consistent with zero. We examine, using mock HSC-Y1 data, the consistency of our S 8 constraints with those derived from the other cosmic shear two-point statistics, the power spectrum analysis by Hikage et al. (2019, PASJ, 71, 43) and the two-point correlation function analysis by Hamana et al. (2020, PASJ, 72, 16), which adopt the same HSC-Y1 shape catalog, and find that all the S 8 constraints are consistent with each other, although the expected correlations between derived S 8 constraints are weak. [ABSTRACT FROM AUTHOR]

We report results on the joint-fit of the NuSTAR and HXMT data for the black hole X-ray binary candidate MAXI J1535-571. The observations were obtained in 2017 when the source evolved through the hard, hard-intermediate, and soft-intermediate states over the rising phase of the outburst. After subtracting continuum components, X-ray reflection signatures are clearly showed in those observations. By modelling the relativistic reflection in detail, we find that the inner radius R in is relatively stable with R in ≲ 1.55 R g during the three states, which implies that the inner radius likely extends to the innermost stable circular orbit even in the bright hard state. When adopting R in = R ISCO, the spin parameter is constrained to be |$0.985_{-0.004}^{+0.002}$| at 90 per cent confidence (statistical only). The best-fitting results reveal that the inclination of the inner accretion disc is ∼70–74 deg, which notably conflicts with the apparent orientation of the ballistic jet (≤45 deg). In addition, both the photon index and the electron temperature increase during the transition from hard to soft state. It seems that the corona evolves from dense low-temperature in the low/hard state to tenuous high-temperature after the state transition, which indicates that the state transition is accompanied by the evolution of the coronal properties. [ABSTRACT FROM AUTHOR]

In this work, we aim to investigate the presence of absorption bands around 3.4 μm in the infrared spectra of primitive asteroids. We collected the published reflectance spectra of low-albedo asteroids from the literature and analysed the 2.4–3.8 μm region using the same techniques. From the initial data set of 92 asteroids, we restricted our analysis to 42 spectra of low-albedo asteroids with a good signal-to-noise (S/N) ratio, and we found the absorption feature around 3.4 μm in the spectra of 16 objects. For objects that are classified by the 3 μm band into the 'rounded', Ceres-like, and Europa-like groups, the depth of the 3.4 μm feature is strongly correlated with that of the 3 μm band. The majority of objects in our data set not showing the 3.4 μm absorption band have lower S/N spectra and belong to Ch or Chg classes, while asteroids with a detected 3.4 μm bands mostly belong to C, B, and also P types. Additionally, asteroids with a detected 3.4 μm band tend to have a lower albedo, redder J-K colours, and more neutral U-V colours. We observe that the analysed objects larger than ∼300 km in diameter show features due to carbon-bearing materials, which could be explained by their higher S/N ratio in our data set. Finally, we found that the distributions of asteroids showing the 3.4 μm feature appear to be shifted towards larger distances from the Sun compared to those not showing this band. [ABSTRACT FROM AUTHOR]

A comparison of the analysis of respirable crystalline silica direct-on-filter methods using X-ray diffraction (XRD) and Fourier transform infrared (FT-IR) spectroscopy was undertaken using 253 real workplace air samples from road construction and tunnelling, coal mining, and kitchen benchtop manufacturing in Australia. Using pure α-quartz standards, XRD and FT-IR direct-on-filter analyses produced identical test results, however, the real workplace samples showed a clear discrepancy between FT-IR and XRD results with on average a 9% positive bias of the FT-IR results. The cause of the positive bias was due to matrix interferences which was confirmed by using synthetic mixture air samples. Approximately a third of the data by direct-on-filter method using FT-IR was assessed to be invalid based on the peak height ratio criterion due to excessive interferences and weight overload limitations. The XRD method showed better results due to less interference from the common matrices. XRD could handle up to twice the sample loading and at higher loadings up to 7 mg when a correction was applied. It was also able to achieve a lower limit of detection of 2 µg filter−1 when a slower scan condition was utilized. [ABSTRACT FROM AUTHOR]

In this investigation, oscillation periods in Mg  ii k-line intensity, brightness temperature, and Doppler velocity obtained above magnetic bright points (MBPs) are investigated. For this purpose, data from the Interface Region Imaging Spectrometer (IRIS) observing the higher chromosphere and transition region (TR) were analysed, together with imaging and magnetogram data obtained by the Solar Dynamics Observatory (SDO). The MBPs were identified by combining Si  iv 1403-Å slit-jaw images with magnetogram information from the Heliospheric and Magnetic Imager (HMI). A time-slice analysis followed by a wavelet inspection were carried out on the Mg  ii k (2796-Å and 10 000 K) resonance lines for the detection of the oscillation period. Finally, a power spectrum analysis was performed to characterize the oscillations. It was found that the network points feature a typical intensity, temperature, and velocity oscillation period of about 300 s. The internetwork points have a mean intensity oscillation period of about 180 s, a mean temperature oscillation period of about 202 s, and a mean velocity oscillation period of about 202 s. In addition, one BP that was analysed in detail demonstrates intensity oscillation periods with a value of 500 s, which are obviously not related to the common 3- or 5-min oscillations typically found elsewhere in chromospheric/photospheric structures. [ABSTRACT FROM AUTHOR]

Empirical estimates of the band power covariance matrix are commonly used in cosmic microwave background (CMB) power spectrum analyses. While this approach easily captures correlations in the data, noise in the resulting covariance estimate can systematically bias the parameter fitting. Conditioning the estimated covariance matrix, by applying prior information on the shape of the eigenvectors, can reduce these biases and ensure the recovery of robust parameter constraints. In this work, we use simulations to benchmark the performance of four different conditioning schemes, motivated by contemporary CMB analyses. The simulated surveys measure the TT ,  TE , and EE power spectra over the angular multipole range 300 ≤ ℓ ≤ 3500 in Δℓ = 50 wide bins, for temperature map-noise levels of 10, 6.4, and |$2\, \mu$| K arcmin. We divide the survey data into N real = 30, 50, or 100 uniform subsets. We show the results of different conditioning schemes on the errors in the covariance estimate, and how these uncertainties on the covariance matrix propagate to the best-fitting parameters and parameter uncertainties. The most significant effect we find is an additional scatter in the best-fitting point, beyond what is expected from the data likelihood. For a minimal conditioning strategy, N real = 30, and a temperature map-noise level of 10 |$\, \mu$| K arcmin, we find the uncertainty on the recovered best-fitting parameter to be ×1.3 larger than the apparent posterior width from the likelihood (×1.2 larger than the uncertainty when the true covariance is used). Stronger priors on the covariance matrix reduce the misestimation of parameter uncertainties to |$\lt 1{{\ \rm per\ cent}}$|⁠. As expected, empirical estimates perform better with higher N real, ameliorating the adverse effects on parameter constraints. [ABSTRACT FROM AUTHOR]

Summary We present NMRtist, an online platform that combines deep learning, large-scale optimization and cloud computing to automate protein NMR spectra analysis. Our website provides virtual storage for NMR spectra deposition together with a set of applications designed for automated peak picking, chemical shift assignment and protein structure determination. The system can be used by non-experts and allows protein assignments and structures to be determined within hours after the measurements, strictly without any human intervention. Availability and implementation NMRtist is freely available to non-commercial users at https://nmrtist.org. Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

Oscillating eclipsing Algols (oEAs) are remarkable systems that allow us to determine accurate fundamental stellar parameters (mass, radius) and probe the stellar interiors through pulsations. TZ Dra is an oEA system containing a δ Scuti component. To examine particular characteristics of such close systems including pulsations and mass transfer, we present a detailed photometric and spectroscopic study of TZ Dra. With the analysis of high-resolution spectra, the orbital parameters were determined by the radial velocity analysis and the atmospheric parameters were derived for the primary component. The binary modelling and the pulsational frequency analysis was carried out using the Transiting Exoplanet Survey Satellite data set. The H α line profiles show the signature of mass transfer from the cool to the hot binary component. The conclusion of mass transfer/mass-loss in the system was supported by the analysis of the orbital period changes. As a result, it was found that there is |$3.52 \times 10^{-9}\, {\rm M}_\odot$|  yr−1 mass-loss from the system most probably through the hotspot and stellar winds. Additionally, most pulsation frequencies originating from the primary component were found to be spaced by harmonics of the orbital frequencies in particular, 12 doublets spaced by 2 f orb were detected from which we infer that this star is a tidally tilted pulsator. A mean p-mode frequency spacing of ≈7.2 d−1 was found as well. [ABSTRACT FROM AUTHOR]

NMR spectroscopy permits real-time monitoring of reactions that involve changes in the spectra of reactants. MICCS (MIcro Channelled Cell for Synthesis monitoring) is a microfluidic chip for such purposes, which is used to rapidly activate reactions by mixing the reactant solutions in the chip inserted into the typical NMR tube. Although it allows monitoring of chemical reactions of small compounds, its simple mixing system dependent on diffusion in the microchannel was not suitable for macromolecules such as proteins with low diffusion rates. Here, we developed a new microfluidic chip based on MICCS by incorporating a mixer of split-and-recombination type within the microchannel. We applied it to monitoring of the protein-folding reaction in a stopped-flow mode. A solution of denaturant-unfolded RNase A was injected from a syringe pump into the microchip set inside the NMR magnet and mixed with a buffer for dilution to reach the folding condition. Immediately after dilution, the reaction was initiated and detected by a series of NMR measurements that were synchronized with activation and inactivation of the pump. The process was repeated for accumulation of the data. By analysing the change of the spectra by factor analysis, a kinetic constant of 0.57 min−1 was obtained. [ABSTRACT FROM AUTHOR]

The ensemble of chemical element abundance measurements for stars, along with precision distances and orbit properties, provides high-dimensional data to study the evolution of the Milky Way. With this third data release of the Galactic Archaeology with HERMES (GALAH) survey, we publish 678 423 spectra for 588 571 mostly nearby stars (81.2 per cent of stars are within <2 kpc), observed with the HERMES spectrograph at the Anglo-Australian Telescope. This release (hereafter GALAH+ DR3) includes all observations from GALAH Phase 1 (bright, main, and faint survey, 70 per cent), K2-HERMES (17 per cent), TESS-HERMES (5 per cent), and a subset of ancillary observations (8 per cent) including the bulge and >75 stellar clusters. We derive stellar parameters T eff, log  g , [Fe/H], v mic, v broad, and v rad using our modified version of the spectrum synthesis code Spectroscopy Made Easy (sme) and 1D marcs model atmospheres. We break spectroscopic degeneracies in our spectrum analysis with astrometry from Gaia  DR2 and photometry from 2MASS. We report abundance ratios [X/Fe] for 30 different elements (11 of which are based on non-LTE computations) covering five nucleosynthetic pathways. We describe validations for accuracy and precision, flagging of peculiar stars/measurements and recommendations for using our results. Our catalogue comprises 65 per cent dwarfs, 34 per cent giants, and 1 per cent other/unclassified stars. Based on unflagged chemical composition and age, we find 62 per cent young low- |$\alpha$|⁠ , 9 per cent young high- |$\alpha$|⁠ , 27 per cent old high- |$\alpha$|⁠ , and 2 per cent stars with [Fe/H] ≤ −1. Based on kinematics, 4 per cent are halo stars. Several Value-Added-Catalogues, including stellar ages and dynamics, updated after Gaia eDR3, accompany this release and allow chrono-chemodynamic analyses, as we showcase. [ABSTRACT FROM AUTHOR]

Gravity Recovery and Climate Experiment (GRACE) Spherical Harmonics (SH) solutions are usually provided together with the corresponding formal errors, however, all multichannel singular spectrum analysis (MSSA) approaches neglect the formal errors of SH coefficients in processing the GRACE time-series. In this contribution, we propose a weighted MSSA to directly process the incomplete time-series of GRACE monthly gravity models by taking the formal errors into account. A 14-yr time-series of Release 06 (RL06) monthly gravity field models from the Center for Space Research (CSR) truncated to degree and order 60 for the period April 2002 to August 2016 is analysed by weighted MSSA, the results are compared with those from the improved MSSA that directly processes the incomplete time-series without considering the formal errors. The first 10 principal components derived by using the weighted MSSA can capture the variance in total up to 82.05 per cent, higher than 80.19 per cent by the improved MSSA. All the fitting errors of GRACE SH coefficients by the weighted MSSA are smaller than those by the improved MSSA, which indicates that weighted MSSA can extract more geophysical signals than the improved MSSA approach. To evaluate the efficiency of the weighted MSSA to eliminate noise, the ratios of the latitude weighted RMS of signals over lands and oceans are computed. Based on all the available months of GRACE solutions, the mean RMS ratio of signals over lands relative to oceans derived by the weighted MSSA is 5.04, higher than 4.96 by the improved MSSA. Therefore, we can conclude that the proposed weighted MSSA can suppress noise more efficiently and extract more geophysical signals from the GRACE time-series, which highlights the necessity of considering formal errors and the effectiveness of the weighted MSSA in post-processing the GRACE monthly gravity field models. [ABSTRACT FROM AUTHOR]

We perform for the first time a 3D hydrodynamics simulation of the evolution of the last minutes pre-collapse of the oxygen shell of a fast-rotating massive star. This star has an initial mass of 38 M⊙, a metallicity of ∼1/50 Z⊙, an initial rotational velocity of 600 km s−1, and experiences chemically homogeneous evolution. It has a silicon- and oxygen-rich (Si/O) convective layer at (4.7–17) × 108 cm, where oxygen-shell burning takes place. The power spectrum analysis of the turbulent velocity indicates the dominance of the large-scale mode (ℓ ∼ 3), which has also been seen in non-rotating stars that have a wide Si/O layer. Spiral arm structures of density and silicon-enriched material produced by oxygen-shell burning appear in the equatorial plane of the Si/O shell. Non-axisymmetric, large-scale (m ≤ 3) modes are dominant in these structures. The spiral arm structures have not been identified in previous non-rotating 3D pre-supernova models. Governed by such a convection pattern, the angle-averaged specific angular momentum becomes constant in the Si/O convective layer, which is not considered in spherically symmetrical stellar evolution models. Such spiral arms and constant specific angular momentum might affect the ensuing explosion or implosion of the star. [ABSTRACT FROM AUTHOR]

The noise attenuation is a fundamental step in seismic data processing, especially when ground-roll suppression remains a challenge. Rank-reduction methods have become quite popular in recent decades, as they promote significant improvements in the quality of data, highlighting reflections in seismograms. We present a methodology for ground-roll filtering, which combines the application of a recursive-iterative singular spectrum analysis method, in the time domain, as a particular way to decompose seismic data, with the computation of the average instantaneous frequency of the signal components. This combination allows for a precise estimation and filtering of the ground-roll noise. The frequency values are used for determining, in each component, the low-frequency parts associated with the ground roll. For every single component, the ground roll is attenuated by zeroing, and stacking the data components, where the average instantaneous frequency values match the ground-roll bandwidth of frequency. Also, in order to enhance the lateral coherence of the reflectors, we present an extension of the recursive-iterative algorithm for a multichannel case. The multichannel algorithm is applicable on a shot, or common mid-point family of seismic traces, after the normal moveout correction. The numerical results using real data show the effectiveness of the proposed methodology for ground-roll attenuation and for improving the velocity analysis. [ABSTRACT FROM AUTHOR]

We recompute the 26-yr weekly Geocentre Motion (GCM) time-series from 1994 to 2020 through the network shift approach using Satellite Laser Ranging (SLR) observations to LAGEOS1/2. Then the Singular Spectrum Analysis (SSA) is applied for the first time to separate and investigate the geophysical signals from the GCM time-series. The Principal Components (PCs) of the embedded covariance matrix of SSA from the GCM time-series are determined based on the w-correlation criterion and two PCs with large w-correlation are regarded as one periodic signal pair. The results indicate that the annual signal in all three coordinate components and semi-annual signal in both X and Z components are detected. The annual signal from this study agrees well in both amplitude and phase with those derived by the Astronomical Institute of the University of Bern and the Center for Space Research, especially for the Y and Z components. Besides, the other periodic signals with the periods of (1043.6, 85, 28), (570, 280, 222.7) and (14.1, 15.3) days are also quantitatively explored for the first time from the GCM time-series by using SSA, interpreting the corresponding geophysical and astrodynamic sources of aliasing effects of K1/O1, T2 and Mm tides, draconitic effects, and overlapping effects of the ground-track repeatability of LAGEOS1/2. [ABSTRACT FROM AUTHOR]

We investigate whether a Gaussian likelihood is sufficient to obtain accurate parameter constraints from a Euclid -like combined tomographic power spectrum analysis of weak lensing, galaxy clustering, and their cross-correlation. Testing its performance on the full sky against the Wishart distribution, which is the exact likelihood under the assumption of Gaussian fields, we find that the Gaussian likelihood returns accurate parameter constraints. This accuracy is robust to the choices made in the likelihood analysis, including the choice of fiducial cosmology, the range of scales included, and the random noise level. We extend our results to the cut sky by evaluating the additional non-Gaussianity of the joint cut-sky likelihood in both its marginal distributions and dependence structure. We find that the cut-sky likelihood is more non-Gaussian than the full-sky likelihood, but at a level insufficient to introduce significant inaccuracy into parameter constraints obtained using the Gaussian likelihood. Our results should not be affected by the assumption of Gaussian fields, as this approximation only becomes inaccurate on small scales, which in turn corresponds to the limit in which any non-Gaussianity of the likelihood becomes negligible. We nevertheless compare against N-body weak lensing simulations and find no evidence of significant additional non-Gaussianity in the likelihood. Our results indicate that a Gaussian likelihood will be sufficient for robust parameter constraints with power spectra from stage IV weak lensing surveys. [ABSTRACT FROM AUTHOR]

We investigate the prospects for using the weak lensing bispectrum alongside the power spectrum to control systematic uncertainties in a Euclid -like survey. Three systematic effects are considered: the intrinsic alignment of galaxies, uncertainties in the means of tomographic redshift distributions, and multiplicative bias in the measurement of the shear signal. We find that the bispectrum is very effective in mitigating these systematic errors. Varying all three systematics simultaneously, a joint power spectrum and bispectrum analysis reduces the area of credible regions for the cosmological parameters Ωm and σ8 by a factor of 90 and for the two parameters of a time-varying dark energy equation of state by a factor of almost 20, compared with the baseline approach of using the power spectrum alone and of imposing priors consistent with the accuracy requirements specified for Euclid. We also demonstrate that including the bispectrum self-calibrates all three systematic effects to the stringent levels required by the forthcoming generation of weak lensing surveys, thereby reducing the need for external calibration data. [ABSTRACT FROM AUTHOR]

The receiver function (RF) method is fundamental in assessing mantle seismic discontinuity depths and reflectivities. Most of the current approaches rely on phase equalization, though in many applications, high levels of incoherent noise, incomplete and irregular sampling customarily interfere with the analysis of weak secondary phases. In recent years, advancements in the field of multidimensional seismic data processing have triggered a shift in interest towards its application to RFs, specifically to single station gathers that depend on a single spatial dimension. Our work generalizes the application of singular spectrum analysis to RFs that rely on two and four spatial dimensions recorded by dense seismic arrays. We adopt a multidimensional signal processing approach known as multichannel singular spectrum analysis. We develop a strategy to assemble and enhance 3-D and 5-D seismic volumes via matrix rank reduction and a reinsertion algorithm to simultaneously suppress random noise, retrieve absent observations and boost identifiability of secondary conversions. We provide informative synthetic examples to gain insight into the effectiveness and limitations of our approach. In the real data example, we improve weak conversions from the mantle transition zone (MTZ) recorded by the USArray in the Yellowstone area. The reconstruction algorithm accurately recovers the timing and polarity of conversions associated with the 410-, 520- and 660-km seismic discontinuities. Our investigation shows that the simultaneous processing of several spatial variables expedites signal restoration, particularly in directions where large recording gaps exist due to a lack of earthquakes, which aids the mapping and identification of the MTZ interfaces. This study presents a theoretical/practical framework for the reconstruction of multidimensional RF data, and its full potential can be exploited with dense acquisition available from the emerging seismic nodal arrays to improve passive seismic imaging. [ABSTRACT FROM AUTHOR]

High-redshift 21-cm observations will provide crucial insights into the physical processes of the Epoch of Reionization. Next-generation interferometers such as the Square Kilometer Array will have enough sensitivity to directly image the 21-cm fluctuations and trace the evolution of the ionizing fronts. In this work, we develop an inferential approach to recover the sources and IGM properties of the process of reionization using the number and, in particular, the morphological pattern spectra of the ionized regions extracted from realistic mock observations. To do so, we extend the Markov Chain Monte Carlo analysis tool 21cmmc by including these 21-cm tomographic statistics and compare this method to only using the power spectrum. We demonstrate that the evolution of the number-count and morphology of the ionized regions as a function of redshift provides independent information to disentangle multiple reionization scenarios because it probes the average ionizing budget per baryon. Although less precise, we find that constraints inferred using 21-cm tomographic statistics are more robust to the presence of contaminants such as foreground residuals. This work highlights that combining power spectrum and tomographic analyses more accurately recovers the astrophysics of reionization. [ABSTRACT FROM AUTHOR]

Respirable crystalline silica (RCS) overexposure can lead to the development of silicosis which is a chronic, irreversible, potentially fatal respiratory disease. The most significant prerequisite for any silica exposure control plan is an accurate occupational exposure assessment. The results of crystalline silica analysis are often affected by other mineral interferences and are influenced by an analyst's knowledge of mineralogy to accurately interpret infrared spectra and correct matrix interferences. Partial least squares (PLS) and artificial neural networks (ANNs) are two multivariate calibration methods to overcome the problem of spectral interferences without the need for an analyst intervention. The performance of these two methods in quantitative analysis of quartz in the presence of mineral interferences was evaluated and compared in this study. Fifty mixtures with different crystalline silica content ratios were prepared by mixing quartz with four common mineral interferences including kaolinite, albite, muscovite, and amorphous silica. Fourier-transform infrared spectra of the mixtures were split into training and test datasets. The optimal architecture of the ANN model was achieved using a two-level full factorial design experiment and data were modeled using ANN and PLS regression analysis. Root mean squared error of prediction values of 1.69 and 6.12 µg quartz for ANN and PLS models, respectively, revealed the fact that the both models performed very well in quantitative analysis of quartz in the presence of mineral interferences, with a better relative performance of the ANN model which can be related to the inherent nonlinear predictive ability of ANNs. Given the excellent predictive ability of the ANN model which can deal with a completely overlapped peak without any need of user's intervention, it is recommended that the ANN model be optimized in future studies and utilized for reliable and rapid on-field assessment of RCS exposure. [ABSTRACT FROM AUTHOR]

We report the results from spectroscopic observations of the multiple images of the strongly lensed Type Ia supernova (SN Ia), iPTF16geu, obtained with ground-based telescopes and the Hubble Space Telescope (HST). From a single epoch of slitless spectroscopy with HST , we resolve spectra of individual lensed supernova images for the first time. This allows us to perform an independent measurement of the time-delay between the two brightest images, Δ t = 1.4 ± 5.0 d, which is consistent with the time-delay measured from the light curves. We also present measurements of narrow emission and absorption lines characterizing the interstellar medium in the SN Ia host galaxy at z = 0.4087, as well as in the foreground lensing galaxy at z = 0.2163. We detect strong Na  id absorption in the host galaxy, indicating that iPTF16geu belongs to a subclass of SNe Ia displaying 'anomalously' large Na  id column densities compared to dust extinction derived from light curves. For the lens galaxy, we refine the measurement of the velocity dispersion, σ = 129 ± 4 km s−1, which significantly constrains the lens model. We use ground-based spectroscopy, boosted by a factor ∼70 from lensing magnification, to study the properties of a high- z SN Ia with unprecedented signal-to-noise ratio. The spectral properties of the supernova, such as pseudo-Equivalent widths of several absorption features and velocities of the Si  ii -line, indicate that iPTF16geu is a normal SN Ia. We do not detect any significant deviations of the SN spectral energy distribution from microlensing of the SN photosphere by stars and compact objects in the lensing galaxy. [ABSTRACT FROM AUTHOR]

Objectives The aim of this study was to show the usefulness of a mid-infrared fibre evanescent wave spectroscopy point of care device in the identification of septic arthritis patients in a multicentre cohort, and to apply this technology to clinical practice among physicians. Methods SF samples from 402 patients enrolled in a multicentre cohort were frozen for analysis by mid-infrared fibre evanescent wave spectroscopy. The calibration cohort was divided into two groups of patients (septic arthritis and non-septic arthritis) and relevant spectral variables were used for logistic regression model. Model performances were tested on an independent set of 86 freshly obtained SF samples from patients enrolled in a single-centre acute arthritis cohort and spectroscopic analyses performed at the patient's bedside. Results The model set-up, using frozen–thawed SFs, provided good performances, with area under the curve 0.95, sensitivity 0.90, specificity 0.90, positive predictive value 0.41 and negative predictive value 0.99. Performances obtained in the validation cohort were area under the curve 0.90, sensitivity 0.92, specificity 0.81, positive predictive value 0.46 and negative predictive value 0.98. The septic arthritis probability has been translated into a risk score from 0 to 4 according to septic risk. For a risk score of 0, the probability of identifying a septic patient is very low (negative predictive value of 1), whereas a risk score of 4 indicates very high risk of septic arthritis (positive predictive value of 1). Conclusion Mid-infrared fibre evanescent wave spectroscopy could distinguish septic from non-septic synovial arthritis fluids with good performances, and showed particular usefulness in ruling out septic arthritis. Our data supports the possibility of technology transfer. Trial registration ClinicalTrials.gov, http://clinicaltrials.gov , NCT02860871. [ABSTRACT FROM AUTHOR]

Spectroscopic observations of AH Herculis during a deep quiescent state are put forward. We found the object in a rare long minima, allowing us to derive accurately the semi-amplitudes: |$K_1 =121 \pm \, 4$|  km s−1 and K 2 = 152 ± 2 km s−1 and its mass functions MW sin 3 i  = 0.30 ± 0.01 M⊙ and MR sin 3 i  = 0.24 ± 0.02 M⊙, while its binary separation is given by a sin  i  = 1.39 ± 0.02 R⊙. The orbital period P orb =  0.25812 ± 0.00032 d was found from a power spectrum analysis of the radial velocities of the secondary star. These values are consistent with those determined by Horne, Wade & Szkody. Our observations indicate that K5 is the most likely spectral type of the secondary. We discuss why we favour the assumption that the donor in AH Her is a slightly evolved star, in which case we find that the best solution for the inclination yields i  = 48° ± 2°. None the less, should the donor be a ZAMS star, we obtain that the inclination is between i  = 43° and i  = 44°. We also present Doppler tomography of H α and H β, and found that the emission in both lines is concentrated in a large asymmetric region at low velocities, but at an opposite position to the secondary star, outside the tidal radius and therefore at an unstable position. We also analyse the H α and H β line profiles, which show a single broad peak and compare it with the previous quiescent state study that shows a double-peaked profile, providing evidence for its transient nature. [ABSTRACT FROM AUTHOR]