Double neutron star (DNS) merger events are promising candidates of short gamma-ray burst (sGRB) progenitors as well as high-frequency gravitational wave (GW) emitters. On August 17, 2017, such a ...coinciding event was detected by both the LIGO-Virgo gravitational wave detector network as GW170817 and Gamma-Ray Monitor on board NASA's Fermi Space Telescope as GRB 170817A. Here, we show that the fluence and spectral peak energy of this sGRB fall into the lower portion of the distributions of known sGRBs. Its peak isotropic luminosity is abnormally low. The estimated event rate density above this luminosity is at least Formula: see text Gpc
yr
, which is close to but still below the DNS merger event rate density. This event likely originates from a structured jet viewed from a large viewing angle. There are similar faint soft GRBs in the Fermi archival data, a small fraction of which might belong to this new population of nearby, low-luminosity sGRBs.
Objective
To compare pre‐eclampsia risk factors identified by clinical practice guidelines (CPGs) with risk factors from hierarchical evidence review, to guide pre‐eclampsia prevention.
Design
Our ...search strategy provided hierarchical evidence of relationships between risk factors and pre‐eclampsia using Medline (Ovid), searched from January 2010 to January 2021.
Setting
Published studies and CPGs.
Population
Pregnant women.
Methods
We evaluated the strength of association and quality of evidence (GRADE). CPGs (n = 15) were taken from a previous systematic review.
Main outcome measure
Pre‐eclampsia.
Results
Of 78 pre‐eclampsia risk factors, 13 (16.5%) arise only during pregnancy. Strength of association was usually ‘probable’ (n = 40, 51.3%) and the quality of evidence was low (n = 35, 44.9%). The ‘major’ and ‘moderate’ risk factors proposed by 8/15 CPGs were not well aligned with the evidence; of the ten ‘major’ risk factors (alone warranting aspirin prophylaxis), associations with pre‐eclampsia were definite (n = 4), probable (n = 5) or possible (n = 1), based on moderate (n = 4), low (n = 5) or very low (n = 1) quality evidence. Obesity (‘moderate’ risk factor) was definitely associated with pre‐eclampsia (high‐quality evidence). The other ten ‘moderate’ risk factors had probable (n = 8), possible (n = 1) or no (n = 1) association with pre‐eclampsia, based on evidence of moderate (n = 1), low (n = 5) or very low (n = 4) quality. Three risk factors not identified by the CPGs had probable associations (high quality): being overweight; ‘prehypertension’ at booking; and blood pressure of 130–139/80–89 mmHg in early pregnancy.
Conclusions
Pre‐eclampsia risk factors in CPGs are poorly aligned with evidence, particularly for the strongest risk factor of obesity. There is a lack of distinction between risk factors identifiable in early pregnancy and those arising later. A refresh of the strategies advocated by CPGs is needed.
Linked article: This article is commented on by Stefan C. Kane et al., pp. 63 in this issue. To view this mini commentary visit https://doi.org/10.1111/1471‐0528.17311.
The work is an initial effort on adopting a statistical approach to correlate the fracture behavior between a notched and a fracture mechanics specimen. The random nature of cleavage fracture process ...determines that both the microscopic fracture stress and the macroscopic properties including fracture load, fracture toughness, and the ductile to brittle transition temperature are all stochastic parameters. This understanding leads to the proposal of statistical assessment of cleavage induced notch brittleness of ferritic steels according to a recently proposed local approach model of cleavage fracture. The temperature independence of the 2 Weibull parameters in the new model induces a master curve to correlate the fracture load at different temperatures. A normalized stress combining the 2 Weibull parameters and the yield stress is proposed as the deterministic index to measure notch toughness. This proposed index is applied to compare the notch toughness of a ferritic steel with 2 different microstructures.
The random distribution of microcracks in terms of their size, shape, orientation and spatial location has direct impact on the cumulative probability of brittle fracture induced failure, with the ...effect of spatial distribution being rarely explored. Recently, two weakest link theory‐based formulations for the cumulative probability of brittle fracture induced failure have been proposed for the spatial distribution of microcracks obeying the Poisson postulates and the uniform distribution, respectively. This work compares these two new formulations with the currently commonly adopted one built on the Poisson postulates under both the uniform and the non‐uniform uniaxial loading conditions. It is concluded that under general loading conditions involving non‐uniform stress states, the existing formulation is equivalent to or closely approximate to neither of the two new formulations thus should be discarded, because of its inaccurate derivation. The new formulations are featured with unique symmetry or self‐similarity in their expressions. Their capability in revealing the size effect or the scaling law of failure is highlighted and validated by a set of published uniaxial and biaxial flexural strength data of brittle material.
The objective of this study is to investigate the feasibility of utilizing the signal features in vibration measurements during the milling process and the cutting parameters for predicting the ...surface roughness of S45C steel. The features of vibration signals are extracted by means of the envelope analysis, statistical computation, such as RMS (root-mean-square), kurtosis, skewness, and multi-scale entropy (MSE), as well as the frequency normalization. Through the correlation analysis, the features of higher priority are sifted out so that the prediction computation efforts can be reduced. The sifted vibration signal features are then collected as the input layer parameters of artificial neural network (ANN) for surface roughness prediction. The prediction results and accuracy through using different classes of input features are also discussed and compared. The experimental results show that the surface roughness is affected not only by the cutting parameters, but also by the vibration behavior during the milling process. Therefore, the cutting parameters combining the essential vibration features can be utilized to enhance the prediction accuracy of surface roughness during the milling process.
The random distribution of single‐fibre tensile strength has been commonly characterized by the two‐parameter Weibull statistics. However, the calibrated Weibull model from one set of strength data ...at a given gauge length cannot accurately predicts the strength variation of the fibre at different gauge lengths. Instead of presuming the two‐parameter Weibull distribution or any other specific statistical distribution for the single‐fibre strength to begin with, this work proposes an approach to incorporating the appropriate spatial flaw distribution within a fibre and synchronizing multiple sets of tensile strength data to evaluate the single‐fibre strength distribution. The approach is examined and validated by published single‐fibre strength data sets of glass, ceramic and synthetic and natural carbon fibres. It is shown that the single‐fibre strength statistics does not necessarily always follow the two‐parameter Weibull distribution.
The contribution of garbage burning (GB) emissions to chloride and PM2.5 in the Mexico City Metropolitan Area (MCMA) has been investigated for the period of 24 to 29 March during the MILAGRO-2006 ...campaign using the WRF-CHEM model. When the MCMA 2006 official emission inventory without biomass burning is used in the simulations, the WRF-CHEM model significantly underestimates the observed particulate chloride in the urban and the suburban areas. The inclusion of GB emissions substantially improves the simulations of particulate chloride; GB contributes more than 60% of the observation, indicating that it is a major source of particulate chloride in Mexico City. GB yields up to 3 pbb HCl at the ground level in the city, which is mainly caused by the burning of polyvinyl chloride (PVC) in the garbage. GB is also an important source of PM2.5 , contributing about 3-30% simulated PM2.5 mass on average. More modeling work is needed to evaluate the GB contribution to hazardous air toxics, such as dioxin, which is found to be released at high level from PVC burning in laboratory experiments.
Quantification of rill erosion processes is of great importance in both model parameter estimations for process-based rill erosion models and in model performance verification. This study presents a ...mathematical method to determine a physics-based rill erosion process derived from the feedback relationship of transport capacity and detachment capacity. Experimental data sets were used to determine transport capacities under steep slope gradients of 15°, 20°, and 25° and the detachment capacities. The estimated transport and detachment capacities were then used to determine the sediment delivery processes under different hydraulic regimes. The sediment concentrations along the rill determined with the mathematical method were compared with the experimental measurements to verify the methodology and the mathematics. Results showed that the mathematical model results agreed well with the experimental data in references. The predicted detachment capacity calculated by the new method was capable of predicting saturated, unsaturated, and thawed slope, but incapable of partially thawed soil. This study not only supports the analytical solution to the differential equation of rill erosion, but also verifies that the experimental method was fit well with the mathematical concept. The new method provides a useful and efficient way to quantify rill erosion processes.
The ordinary Weibull distribution function has been commonly accepted for empirical characterization of cleavage fracture toughness of nuclear reactor and containment pressure vessel steels. However, ...this method lacks a fundamental basis. This work adopts the standardized Weibull distribution function to analyze cleavage fracture toughness of ferritic steels measured from different sized fracture mechanics specimens at different temperatures to estimate the Weibull modulus. The toughness data of five different nuclear reactor and containment vessel steels are analyzed. The estimations obtained the Weibull modulus (m) in the range of 1.83 to 2.55 and strong temperature dependence of the threshold cleavage fracture toughness
K
min
, as opposed to the constant values of
m
K
= 4 and
K
min
= 20 MPam
1/2
given in ASTM E1921-19. The goodness of fit test by the one-sample Kolmogorov–Smirnov (K–S) test validated Weibull distribution function for describing the toughness distribution.
Two-dimensional (2D) nanostructures, bismuth telluride (Bi2Te3), as represented by one of the topological insulators (TI) materials, have attracted tremendous interests from world-wide scientists due ...to their potential applications in electronic devices. However, the growth mechanism especially chemical vapour deposition (CVD) and the optoelectronic device applications of these Bi2Te3 nanostructures have barely been investigated and reported. In this work, we present a detailed study on the controlled CVD growth of 2D Bi2Te3 nanostructures and explore their applications in high performance visible photodetectors. With increasing the precursor material temperature from 470 °C to 510 °C, it is observed that the lateral size of Bi2Te3 nanoplates first increases and then becomes saturated when the precursor material temperature over 490 °C, which is mainly due to the competition between the transportation and diffusion of precursor molecules onto the substrate surface and the reaction consumption of precursor atoms on the substrate surface. In addition, it is also observed that the lateral size of Bi2Te3 nanoplates decreases with increasing the total inner tube pressure as a result of the reduced diffusion rate of Bi2Te3 precursor molecules. 2D Bi2Te3 nanoplates with a lateral size over 10 μm can be obtained with applying proper precursor material temperature and total inner tube pressure. Furthermore, a visible photodetector is fabricated using few-layered 2D Bi2Te3 nanoplates grown in this work. This visible photodetector demonstrates a high responsivity of 23.43 AW−1 and a high detectivity of 1.54 × 1010 Jones, outperforming some visible detectors based on traditional 2D nanomaterials. Tche intensity-dependent photo-responsivity measurements show stable photoswitching behavior. This 2D Bi2Te3 nanoplate photodetector also presents high flexibility by showing no obvious performance degradation after being bent for 50 times. The results presented in this work will not only contribute to a comprehensive understanding of the CVD growth mechanism of Bi2Te3 nanostructures, but open up novel optoelectronic device applications for 2D Bi2Te3 nanostructures.
•We provide a growth model for achieving controlled growth of Bi2Te3 nanoplates.•The device shows a responsivity of 23.43 AW−1 and a detectivity of 1.54 × 1010 Jones.•The Bi2Te3 nanoplate photodetectors also show high flexibility.
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