Mass Estimates Research Articles

Analysis of the Influence of Polarization Measurement Errors on the Parameter and Characteristics Measurement of the Fully Polarized Entomological Radar

Measuring the orientation, mass and body length of migratory insects through entomological radar is crucial for early warnings of migratory pests. The fully polarized entomological radar is an efficient device for observing migratory insects by calculating insect parameters through the scattering matrix obtained from the target. However, the measured target scattering matrix will be affected by system polarization measurement errors, leading to errors in insect parameter calculation, while the related analysis is currently relatively limited. Therefore, the scattering matrix measurement process is modeled, followed by an analysis of the effects of different errors on orientation, mass and body length estimation. The influence of polarization measurement errors on insect scattering characteristics is also analyzed. The results present that for fixed polarization measurement errors, the measurement errors of insect orientation, mass and body length will vary with insect orientation in specific patterns, and the distribution of measured insect parameters will be drastically distorted compared to the true parameter distribution. In addition, polarization measurement errors could seriously disrupt the reciprocity and bilateral symmetry of the measured insect scattering matrix. These analyses and conclusions provide a good basis for eliminating the effects of polarization measurement errors and improving the accuracy of insect parameter measurement.

Cosmological Mass of the Photon Related to Stueckelberg and Higgs Mechanisms

I consider the electro-weak (EW) masses and interactions generated by photons using vacuum expectation values of Stueckelberg and Higgs fields. I provide a prescription to relate their parametric values to a cosmological range derived from the fundamental Heisenberg uncertainty principle and the Einstein–de Sitter cosmological constant and horizon. This yields qualitative connections between microscopic ranges acquired by W± or Z0 gauge Bosons and the cosmological scale and minimal mass acquired by g-photons. I apply this procedure to an established Stueckelberg–Higgs mechanism, while I consider a similar procedure for a pair of Higgs fields that may spontaneously break all U(1) × SU(2) gauge invariances. My estimates of photon masses and their additional parity-breaking interactions with leptons and neutrinos may be detectable in suitable accelerator experiments. Their effects may also be observable astronomically through massive g-photon condensates that may contribute to dark matter and dark energy.

Attenuation proxy hidden in surface brightness – colour diagrams

Aims. Large future sky surveys, such as the Legacy Survey of Space and Time (LSST), will provide optical photometry for billions of objects. Reliable estimation of the physical properties of galaxies requires information about dust attenuation, which is usually derived from ultraviolet (UV) and infrared (IR) data. This paper aims to construct a proxy for the far-UV (FUV) attenuation (AFUVp) from the optical data alone, enabling the rapid estimation of the star formation rate (SFR) for galaxies that lack UV or IR data. This will accelerate and improve the estimation of key physical properties of billions of LSST–like observed galaxies (observed in the optical bands only). Methods. To mimic LSST observations, we used the deep panchromatic optical coverage of the Sloan Digital Sky Survey (SDSS) Photometric Catalogue, Data Release 12, complemented by the estimated physical properties for the SDSS galaxies from the GALEX-SDSS-WISE Legacy Catalog (GSWLC) and inclination information obtained from the SDSS Data Release 7. We restricted our sample to the 0.025–0.1 spectroscopic redshift range and investigated relations among surface brightness, colours, and dust attenuation in the FUV range for star-forming galaxies obtained from the spectral energy distribution (SED). Results. Dust attenuation is best correlated with colour measured between u and r bands (u − r) and the surface brightness in the u band (μu). We provide a dust attenuation proxy for galaxies on the star-forming main sequence. This relation can be used for the LSST or any other type of broadband optical survey. The mean ratio between the catalogue values of SFRs and those estimated using optical-only SDSS data with the AFUVp prior calculated as ΔSFR = log(SFRthis work/SFRGSWLC) is found to be less than 0.1 dex, while runs without priors result in an SFR overestimation larger than 0.3 dex. The presence or absence of the AFUVp has a negligible influence on the stellar mass (Mstar) estimation (with ΔMstar in the range from 0 to −0.15 dex). Conclusions. We note that AFUVp is reliable for low-redshift main sequence galaxies. Forthcoming deep optical observations of the LSST Deep Drilling Fields, which also have multi-wavelength data, will enable one to calibrate the obtained relation for higher redshift galaxies and, possibly, extend the study towards other types of galaxies, such as early-type galaxies off the main sequence.

Planets observed with CHEOPS

Context. M-dwarf stars are the most common of potential exoplanet host stars in the Galaxy. It is therefore very important to understand planetary systems orbiting such stars and to determine the physical parameters of such planets with high precision. Also with the launch of the James Webb Space Telescope (JWST) the observation of atmospheric parameters of planets orbiting these stars has begun. It is therefore required to determine properties of potential targets. Aims. Two planets around the red dwarf TOI-776 were detected by TESS. The objective of our study was to use transit observations obtained by the CHEOPS space mission to improve the current precision of the planetary radii, as well as additional radial velocity (RV) data in order to improve mass estimates of the two planets. Using these quantities, we wanted to derive the bulk densities of those planets, improving the precision in earlier results, and use this information to put them in context of other exoplanetary systems involving very low mass stars. Methods. Utilizing new transit data from the CHEOPS satellite and its photometric telescope, we obtained very high precision planetary transit measurements. Interpretation of these provides updated planetary radii, along with other system parameters. A concurrent ESO large observing program using the high precision spectrograph HARPS has doubled the available radial velocity data. Calculating the power spectrum of a number of stellar activity indices we update the previously estimated stellar rotation period to a lower value. Results. The CHEOPS data provide precise transit depths of 909 and 1177 ppm translating into radii of Rb = 1.798−0.077+0.078 R⊕ and Rc = 2.047−0.078+0.081 R⊕, respectively. Our interpretation of the radial velocities and activity indicator time series data estimates a stellar rotation period for this early M dwarf of ~21.1 days. A further multi-dimensional Gaussian process approach confirm this new estimate. By performing a Skew-Normal (SN) fit onto the Cross Correlation Functions we extracted the RV data and the activity indicators to estimate the planetary masses, obtaining Mb = 5.0−1.6+1.6 M⊕ and Mc = 6.9−2.5+2.6 M⊕. Conclusions. We improve the precision in planetary radius for TOI-776 b and c by a factor of more than two. Our data and modelling give us parameters of both bodies consistent with mini-Neptunes, albeit with a relatively high density. The stellar activity of TOI-776 is found to have increased by a factor larger than 2 since the last set of observations.

Technical note: A comparison of methods for estimating coccolith mass

Abstract. The fossil record of coccolithophores dates back approximately 225 million years, and the production of their calcite platelets (coccoliths) contributes to the global carbon cycle over short and geological timescales. Variations in coccolithophore parameters (e.g. community composition, morphology, size and coccolith mass) are a key factor for ocean biogeochemical dynamics (e.g. biological carbon pump) and have been used as a palaeoproxy to understand past oceanographic conditions. Coccolith mass has been frequently estimated with different methods with electron microscopy being the most applied. Here, we compared the electron microscopy (EM) method with the Coulter multisizer (CM) (i.e. electric field disturbance) and bidirectional circular polarization (BCP) methods to estimate coccolith masses (pg CaCO3) in controlled laboratory experiments with two ecotypes of Emiliania huxleyi. Average coccolith mass estimates were in good agreement with literature data. However, mass estimates from the CM were slightly overestimated compared to EM and BCP estimates, and a correction factor (cf=0.8) is suggested to compensate for this discrepancy. The relative change in coccolith mass triggered by morphotype-specific structures and environmental parameters (i.e. seawater carbonate chemistry) was suitably captured by each of the three techniques.

Errors in average strength estimates of sedimentary rock masses in South Yakutia based on geometric induction sounding data

The probabilistic model developed to describe the engineering and geological conditions for the operation of buildings and infrastructure in the city of Neryungri has been verified. The model is a power-function equation which correlates, by regression relationships, laboratory-determined compressive strength of saturated frozen sandstone samples with attenuation of the high-frequency harmonic field of a vertical magnetic dipole in warm permafrost composed of sandstone. The attenuation values were obtained by geometric electromagnetic induction sounding at a frequency of 1.125 MHz. The model verification was conducted at a fixed frequency on a section of the Amur-Yakutsk Railway located at a significant distance from Neryungri. The railway here is underlain by low-temperature dolomite masses. The statistical analysis indicates that the relative errors of the dolomite saturated strength estimates from the geometric EM induction data with a 73.0% probability do not exceed 20%. With this level of accuracy close to that of laboratory tests according to GOST 25100–2020, it is reasonable to suggest that the probabilistic model can be used region-wide in southern Yakutia to predict saturated strength of foundation materials composed of sandstone and dolomite. It can provide an effective solution for market-based construction and mining industries, as increasing anthropogenic and climatic impacts are anticipated to cause thawing and saturation of sedimentary rock masses.

Predicting nuclear masses with product-unit networks

Accurate estimation of nuclear masses and their prediction beyond the experimentally explored domains of the nuclear landscape are crucial to an understanding of the fundamental origin of nuclear properties and to many applications of nuclear science, most notably in quantifying the r-process of stellar nucleosynthesis. Neural networks have been applied with some success to the prediction of nuclear masses, but they are known to have shortcomings in application to extrapolation tasks. In this work, we propose and explore a novel type of neural network for mass prediction in which the usual neuron-like processing units are replaced by complex-valued product units that permit multiplicative couplings of inputs to be learned from the input data. This generalized network model is tested on both interpolation and extrapolation data sets drawn from the Atomic Mass Evaluation. Its performance is compared with that of common neural-network architectures, substantiating its suitability for nuclear-mass prediction. Additionally, a prediction-uncertainty measure for such complex-valued networks is proposed that allows identifying nuclides of expected large prediction error. Within and beyond the experimentally explored domain, model predictions are evaluated by computing deviations from the Garvey-Kelson relations.

Impact of birth weight to placental weight ratio and other perinatal risk factors on left ventricular dimensions in newborns: a prospective cohort analysis.

To investigate the association between birth weight to placental weight (BW/PW) ratio, and echocardiographic left ventricle (LV) morphology at birth, while accounting for other relevant perinatal factors. A prospective cohort study was conducted on neonates at NewYork-Presbyterian Brooklyn Methodist Hospital from 2014 to 2018, categorized by their BW/PW percentile. Missing data were imputed with principal component analysis. Chi-squared and one-way analysis of variance were used to compare BW/PW groups and the best regression model was selected using a genetic and backward stepwise algorithm. We analyzed 827 neonates in three BW/PW groups: small (n=16), normal (n=488), and large (n=323). Placental thickness and smallest diameter were positively correlated with several LV parameters, including inter-ventricular septal thickness during diastole (IVSd) (p=0.002, p<0.001) and systole (IVSs) (p=0.001, p<0.001), LV posterior wall thickness at end of diastole (LVPWd) (p=0.003, p<0.001) and systole (LVPWs) (p<0.001, p<0.001), LV mass (p=0.017, p<0.001), and LV mass/volume (p=0.011, p<0.001). The BW/PW ratio correlated with an increased shortening fraction (estimate=0.29, 95 % CI 0.03-0.55, p=0.027). PW correlated with IVSs (p=0.019), while the longest placental diameter was linked to a decrease in LV internal dimension during diastole (LVIDd) (estimate=-0.07, p=0.039), LV mass (estimate=-0.11, p=0.024), and LV mass/volume (estimate=-0.55, p=0.005). This study found that several placental factors, including the BW/PW ratio, can independently affect LV dimension and morphology, highlighting the importance of fetal growth and placental health in the physiological adaptation of the fetal heart. More research is needed to establish causation and inform newborn prevention strategies.

Retarded Gravity in Disk Galaxies

Disk galaxies have a typical dimension of a few tens of kiloparsecs. It follows from the theory of general relativity that any signal originating from the galactic center will be noticed at the outskirts of the galaxy only tens of thousands of years later. This retardation effect, however, is absent in modelling used to calculate rotation curves throughout entire galaxies and their external gas. The considerable differences between Newtonian predictions and observed velocities are currently removed either by assuming dark matter or by suggesting various modifications to the laws of gravity, MOND being a long standing alternative to Newtonian gravity. In previous papers we have shown that by applying general relativity in a rigorous fashion, without neglecting retardation, one can explain the rotational velocities of galactic matter without modifying gravity or adding dark matter. Moreover, it was shown that dark matter effects, as they appear in gravitational lensing, the Tully-Fisher relation, and mass estimations based on the virial theorem could also be explained as retarded-gravity effects. It must be noted, however, that the proposed theory relies on the existence of a mass flow (of a changing rate) into the galaxy; a requirement that was not directly observed. In the original paper on the subject only one galaxy (M33) was analysed in detail. This was later amended with a published study of eleven galaxies. Here we give a more comprehensive retardation analysis of 143 galaxies of different types from the SPARC Galaxy collection. We show that in most cases we obtain very accurate fits to the data.

Characterisation of Plasmodium vivax lactate dehydrogenase dynamics in P. vivax infections

Plasmodium vivax lactate dehydrogenase (PvLDH) is an essential enzyme in the glycolytic pathway of P. vivax. It is widely used as a diagnostic biomarker and a measure of total-body parasite biomass in vivax malaria. However, the dynamics of PvLDH remains poorly understood. Here, we developed mathematical models that capture parasite and matrix PvLDH dynamics in ex vivo culture and the human host. We estimated key biological parameters characterising in vivo PvLDH dynamics based on longitudinal data of parasitemia and PvLDH concentration collected from P. vivax-infected humans, with the estimates informed by the ex vivo data as prior knowledge in a Bayesian hierarchical framework. We found that the in vivo accumulation rate of intraerythrocytic PvLDH peaks at 10–20 h post-invasion (late ring stage) with a median estimate of intraerythrocytic PvLDH mass at the end of the life cycle to be 9.4 × 10−3ng. We also found that the median estimate of in vivo PvLDH half-life was approximately 21.9 h. Our findings provide a foundation with which to advance our quantitative understanding of P. vivax biology and will facilitate the improvement of PvLDH-based diagnostic tools.

Total and dark mass from observations of galaxy centers with machine learning

The galaxy total mass inside the effective radius is a proxy of the galaxy dark matter content and the star formation efficiency. As such, it encodes important information on the dark matter and baryonic physics. Total central masses can be inferred via galaxy dynamics or gravitational lensing, but these methods have limitations. We propose a novel approach based on machine learning to make predictions on total and dark matter content using simple observables from imaging and spectroscopic surveys. We used catalogs of multiband photometry, sizes, stellar mass, kinematic measurements (features), and dark matter (targets) of simulated galaxies from the Illustris-TNG100 hydrodynamical simulation to train a Mass Estimate machine Learning Algorithm ( Mela ) based on random forests. We separated the simulated sample into passive early-type galaxies (ETGs), both normal and dwarf, and active late-type galaxies (LTGs) and showed that the mass estimator can accurately predict the galaxy dark masses inside the effective radius in all samples. We finally tested the mass estimator against the central mass estimates of a series of low-redshift (zlsim 0.1) datasets, including SPIDER, MaNGA/DynPop, and SAMI dwarf galaxies, derived with standard dynamical methods based on the Jeans equations. We find that Mela predictions are fully consistent with the total dynamical mass of the real samples of ETGs, LTGs, and dwarf galaxies. learns from hydro-simulations how to predict the dark and total mass content of galaxies, provided that the real galaxy samples overlap with the training sample or show similar scaling relations in the feature and target parameter space. In this case, dynamical masses are reproduced within 0.30 dex ($ with a limited fraction of outliers and almost no bias. This is independent of the sophistication of the kinematical data collected (fiber vs. 3D spectroscopy) and the dynamical analysis adopted (radial vs. axisymmetric Jeans equations, virial theorem). This makes a powerful alternative to predict the mass of galaxies of massive stage IV survey datasets using basic data, such as aperture photometry, stellar masses, fiber spectroscopy, and sizes. We finally discuss how to generalize these results to account for the variance of cosmological parameters and baryon physics using a more extensive variety of simulations and the further option of reverse engineering this approach and using model-free dark matter measurements (e.g., via strong lensing), plus visual observables, to predict the cosmology and the galaxy formation model.

Kinematical small-scale fluctuations do not affect the measurement of the dynamical mass of galaxies

ABSTRACT The stellar kinematics of low-mass galaxies are usually observed to be very unsmooth with significant kinematical fluctuations in small scales, which cannot be consistent with the projected centrosymmetric stellar kinematics obtained from commonly used dynamical models. In this work, we aim to test whether the high degree of kinematical fluctuations affects the dynamical mass estimate of galaxies. We use the asymmetry parameter η obtained from the 180° rotation self-subtraction of stellar kinematics of galaxies to quantify the degree of kinematical small-scale fluctuations. We use TNG50 numerical simulation to construct a large sample of mock galaxies with known total masses, and then obtained the virial dynamical mass estimator of these mock galaxies. We find that the dynamical masses within three-dimensional Re to the mock galaxy centres are overall averagely accurate within around 0.1 dex under the symmetric assumption, while Re means the projected circularized half-stellar mass radius in this work. We study the local virial mass estimation bias for mock galaxies of different η. The maximum bias difference of two η bins is around 0.16 dex, which with other local biases may help apply the observational virial mass estimators obtained from massive galaxies to other types of galaxies. We find that the Spearman’s ρ of η with the intrinsic mass estimation deviations is near zero if the local bias is eliminated properly. The results indicate that even for low-mass galaxies, the existence of high degree of kinematical small-scale fluctuations does not affect the measurement of the dynamical mass of galaxies.

Mass-based fates of microplastics throughout wastewater treatment processes

Sewage treatment plants (STPs) are crucial in removing microplastics from wastewater but also serve as essential point sources for microplastic pollution in environments. To address this issue by improving the microplastic removal efficiency, unveiling the mass-based fates of microplastics during treatments in STPs is essential, as these treatment systems are not specially designed to target microplastics. Herein, a thermodesorption–gas chromatography–mass spectrometry (TD–GC/MS) was developed to quantify the mass of five microplastics: polyethylene (PE), polypropylene (PP), polystyrene (PS), polyvinyl chloride (PVC), and polyethyleneglycol terephthalate (PET) in the range of 0.22 μm–5.00 mm in size. Then, the approach was further applied to evaluate the mass-based fates of these microplastics throughout the whole STP treatment process. Results showed that PE was the most common polymer detected in influent (1313.11 ± 336.96 μg/L) and effluent (25.84 ± 3.75 μg/L), while PP was the least prevalent in influent (52.47 ± 11.49 μg/L) and PS in the effluent (2.74 ± 0.26 μg/L). Moreover, the proportion of the smallest particles (0.22–20 μm) was dominant in all samples. Based on mass estimations, an average of 95.82 % ± 2.02 % of microplastics were efficiently removed from the influent, with removal rates ranging from 92.55 % for PP to 98.03 % for PE. Moreover, the removal of microplastic mainly occurred in the primary treatment unit, and their removal efficiencies decreased as the microplastic concentrations decreased, regardless of their sizes and polymer types. To the best of our knowledge, this is the first report on the mass-based fates of microplastics in STP throughout wastewater treatment processes, enabling the comparison of microplastic removal efficiencies among studies to direct future improvements in the treatment process.

Mechanical and morphometric approaches to body mass estimation in rhesus macaques: A test of skeletal variables.

Estimation of body mass from skeletal metrics can reveal important insights into the paleobiology of archeological or fossil remains. The standard approach constructs predictive equations from postcrania, but studies have questioned the reliability of traditional measures. Here, we examine several skeletal features to assess their accuracy in predicting body mass. Antemortem mass measurements were compared with common skeletal dimensions from the same animals postmortem, using 115 rhesus macaques (male: n = 43; female: n = 72). Individuals were divided into training (n = 58) and test samples (n = 57) to build and assess Ordinary Least Squares or multivariate regressions by residual sum of squares (RSS) and AIC weights. A leave-one-out approach was implemented to formulate the best fit multivariate models, which were compared against a univariate and a previously published catarrhine body-mass estimation model. Femur circumference represented the best univariate model. The best model overall was composed of four variables (femur, tibia and fibula circumference and humerus length). By RSS and AICw, models built from rhesus macaque data (RSS = 26.91, AIC = -20.66) better predicted body mass than did the catarrhine model (RSS = 65.47, AIC = 20.24). Body mass in rhesus macaques is best predicted by a 4-variable equation composed of humerus length and hind limb midshaft circumferences. Comparison of models built from the macaque versus the catarrhine data highlight the importance of taxonomic specificity in predicting body mass. This paper provides a valuable dataset of combined somatic and skeletal data in a primate, which can be used to build body mass equations for fragmentary fossil evidence.

Prevalence of low calf circumference in hospitalized patients classified by raw or body mass index-adjusted values.

Adiposity can influence the estimation of muscle mass using calf circumference (CC) and underestimate the frequency of low CC. An adjustment for CC using body mass index (BMI) was proposed to reduce this effect. We aimed to compare the low CC frequency in hospitalized patients when considering raw and BMI-adjusted values and explore data by sex, age, and race (white and non-white). Secondary analysis from two cohort studies conducted with adult hospitalized patients using BMI and CC data collected in the first 72 h after hospital admission. We classified low CC by two approaches: (1) raw CC; (2) BMI-adjusted CC for patients with BMI ≥ 25. Cutoff values for low CC were ≤34 cm (men) and ≤33 cm (women). Among 1272 patients (54.1 ± 15.3 years old; 51.7% women; 82.1% White race), low CC frequency was 30.6% and low BMI-adjusted CC was 68.9%. For all elevated BMI categories, the low CC frequency was higher when considering BMI-adjusted values (P < 0.001). Low CC was more frequent (P < 0.001) in older adults (38.7% by raw; 79.1% by BMI-adjusted value) than in younger adults (27.6% by raw; 65.2% by BMI-adjusted value) and it was not associated with race. Low CC by raw values was more frequent in men than in women (35.0% versus 26.4%; P = 0.001), but did not differ between sexes when classified by BMI-adjusted values (70.7% versus 67.1%; P = 0.184). Low CC BMI adjusted was 2.2 times more frequent in comparison with raw CC values, and it was identified in >60% of patients with BMI ≥ 25.

Global patterns of tree wood density.

Wood density is a fundamental property related to tree biomechanics and hydraulic function while playing a crucial role in assessing vegetation carbon stocks by linking volumetric retrieval and a mass estimate. This study provides a high-resolution map of the global distribution of tree wood density at the 0.01° (~1 km) spatial resolution, derived from four decision trees machine learning models using a global database of 28,822 tree-level wood density measurements. An ensemble of four top-performing models combined with eight cross-validation strategies shows great consistency, providing wood density patterns with pronounced spatial heterogeneity. The global pattern shows lower wood density values in northern and northwestern Europe, Canadian forest regions and slightly higher values in Siberia forests, western United States, and southern China. In contrast, tropical regions, especially wet tropical areas, exhibit high wood density. Climatic predictors explain 49%-63% of spatial variations, followed by vegetation characteristics (25%-31%) and edaphic properties (11%-16%). Notably, leaf type (evergreen vs. deciduous) and leaf habit type (broadleaved vs. needleleaved) are the most dominant individual features among all selected predictive covariates. Wood density tends to be higher for angiosperm broadleaf trees compared to gymnosperm needleleaf trees, particularly for evergreen species. The distributions of wood density categorized by leaf types and leaf habit types have good agreement with the features observed in wood density measurements. This global map quantifying wood density distribution can help improve accurate predictions of forest carbon stocks, providing deeper insights into ecosystem functioning and carbon cycling such as forest vulnerability to hydraulic and thermal stresses in the context of future climate change.

SPT: Spectral transformer for age and mass estimations of red giant stars

The ages and masses of red giants are key to our understanding of the structure and evolution of the Milky Way. Traditional isochrone methods for these estimations are inherently limited due to overlapping isochrones in the Hertzsprung-Russell diagram, while astero-seismology, albeit more precise, requires high-precision, long-term observations. In response to these challenges, we developed a novel framework, spectral transformer (SPT), to predict the ages and masses of red giants aligned with asteroseismology from their spectra. The main component of SPT is the multi-head Hadamard self-attention mechanism, which is designed specifically for spectra and can capture complex relationships across different wavelengths. Furthermore, we introduced a Mahalanobis distance-based loss function, to address scale imbalance and interaction mode loss, and we incorporated a Monte Carlo dropout for a quantitative analysis of the prediction uncertainty. Trained and tested on 3880 red giant spectra from LAMOST, the SPT has achieved remarkable age and mass estimations, with average percentage errors of 17.64 and 6.61%, respectively. It has also provided uncertainties for each corresponding prediction. These results significantly outperform traditional machine learning algorithms, demonstrating a high level of consistency with asteroseismology methods and isochrone-fitting techniques. In the future, our work will leverage datasets from the Chinese Space Station Telescope and Large Synoptic Survey Telescope to enhance the precision of the model and broaden its applicability in the fields of astronomy and astrophysics.

Jet Mechanism and γ-Ray-emitting Region for Fermi Flat-spectrum Radio Quasars with Broad-line Emissions

Blazars are a subject of intense debate, specifically regarding their jet launch and emission mechanisms, and the origins of their γ-ray radiation. To explore these issues, we have built a comprehensive sample of flat-spectrum radio quasars (FSRQs), with well-characterized spectral energy distribution. This study aims to elucidate the dominant jet launch mechanism and the main processes behind the inverse Compton (IC) component. Additionally, we seek to pinpoint the location of the γ-ray dissipation region relative to the central black hole, denoted as R γ . Our approach involves a detailed analysis of broad-line region (BLR) emission, from which we derive robust estimates of the black hole masses using two distinct virial techniques. This enables us to constrain the jet power across a wide array of FSRQs. Our findings lead to several significant conclusions: (i) The correlation of jet power with black hole mass allows us to test the Blandford–Znajek, Blandford–Payne, and hybrid mechanisms. We find that the hybrid mechanism is most effective in explaining the jet power observed in the majority of FSRQs; (ii) The IC component of the γ-rays in FSRQs is predominantly due to the external Compton process. (iii) Through simulations, we determine the minimum and maximum values of R γ (the γ-ray dissipation region) and conclude it is located outside the BLR. This conclusion is derived from the variability timescale analysis.

Estimation of the maximum mass of graphite removed during phased work on the management of RBMK-1000 resource characteristics

Estimation of the maximum mass of graphite removed during phased work on the management of RBMK-1000 resource characteristics

The agreement of different techniques for muscle measurement in diagnosing sarcopenia: a systematic review and meta-analysis.

The measurement or estimation of muscle mass plays an important role in the diagnosis of sarcopenia. Beside dual-energy X-ray absorptiometry (DXA), several modalities, including bioelectrical impedance analysis (BIA), ultrasound (US), computed tomography (CT), and magnetic resonance imaging (MRI), have helped to provide imaging or electrical biomarkers for muscle mass. This study was aimed at summarizing the diagnostic performance of different techniques on muscle assessment for sarcopenia. Studies on the assessment of muscle mass by different techniques (compared with DXA), published from inception to 12 October, 2023 were retrieved from 4 electronic databases: the Cochrane Library, Embase, PubMed, and Web of Science. The quality assessment of included studies was conducted using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2). The sensitivity, specificity, Cohen's kappa coefficient (κ), and Pearson correlation coefficient (r) with 95% confidence intervals (CIs) were pooled and presented via forest plots. The area under the curve (AUC) with 95% CI was pooled and presented via summary receiver operating characteristic (sROC) curve. A total of 28 studies involving 4,926 participants were included. Compared with DXA, the pooled sensitivity and specificity, AUC, and Cohen's κ were 0.79 (95% CI: 0.71-0.86, P<0.001), 0.95 (95% CI: 0.82-0.99, P<0.001), and 0.88 (95% CI: 0.85-0.90), and 0.61 (95% CI: 0.51-0.72) for BIA. The pooled r value between DXA and BIA or US or MRI was 0.94 (95% CI: 0.92-0.96, P<0.001), 0.69 (95% CI: 0.54-0.80, P<0.001), and 0.96 (95% CI: 0.95-0.97, P=0.21), respectively. No qualified original study in relation to CT was included. BIA, US, and MRI would provide acceptable diagnostic accuracy for sarcopenia by evaluating muscle mass in terms of sensitivity, specificity, accuracy, and their higher correlations with DXA. Further investigation is required to elucidate the value of CT in diagnosing sarcopenia.