Improved Performance of Compartments in Detecting the Activity of Axial Spondyloarthritis Based on IVIM DWI with Optimized Threshold b Value

Purpose. To explore the diagnostic performance of the optimized threshold b values on IVIM to detect the activity in axial spondyloarthritis (axSpA) patients. Method. 40 axSpA patients in the active group, 144 axSpA patients in the inactive group, and 20 healthy volunteers were used to evaluate the tissue diffusion coefficient ( D slow ), perfusion fraction ( f ), and pseudodiffusion coefficient ( D fast ) with b thresholds of 10, 20, and 30 s/mm2. The Kruskal-Wallis test and one way ANOVA test was used to compare the different activity among the three groups in axSpA patients, and receiver operating characteristic (ROC) curve analysis was applied to evaluate the performance for D slow , f , and D fast to detect the activity in axSpA patients, respectively. Results. D slow demonstrated a statistical difference between two groups ( P < 0.05 ) with all threshold b values. With the threshold b value of 30 s/mm2, f could discriminate the active from control groups ( P < 0.05 ). D slow had similar performance between the active and the inactive groups with threshold b values of 10, 20, and 30 s/mm2 (AUC: 0.877, 0.882, and 0.881, respectively, all P < 0.017 ). Using the optimized threshold b value of 30 s/mm2, f showed the best performance to separate the active from the inactive and the control groups with AUC of 0.613 and 0.738 (both P < 0.017 ) among all threshold b values. Conclusion. D slow and f exhibited increased diagnostic performance using the optimized threshold b value of 30 s/mm2 compared with 10 and 20 s/mm2, whereas D fast did not.

b-value of what? Complex behavior of the magnitude distribution during and within the 2016–2017 central Italy sequence

The Magnitude–Frequency-Distribution (MFD) of earthquakes is typically modeled with the (tapered) Gutenberg–Richter relation. The main parameter of this relation, the b-value, controls the relative rate of small and large earthquakes. Resolving spatiotemporal variations of the b-value is critical to understanding the earthquake occurrence process and improving earthquake forecasting. However, this variation is not well understood. Here we present unexpected MFD variability using a high-resolution earthquake catalog of the 2016–2017 central Italy sequence. Isolation of seismicity clusters reveals that the MFD differs in nearby clusters, varies or remains constant in time depending on the cluster, and features an unexpected b-value increase in the cluster where the largest event will occur. These findings suggest a strong influence of the heterogeneity and complexity of tectonic structures on the MFD. Our findings raise the question of the appropriate spatiotemporal scale for resolving the b-value, which poses a serious obstacle to interpreting and using the MFD in earthquake forecasting.

Influence of Partial Replacements of NaCl by KCl on Quality Characteristics and the Heterocyclic Aromatic Amine Contents of Bacon

The influence of partial replacements of NaCl by KCl (0, 10, 20, and 30%) on the heterocyclic aromatic amine (HAAs) contents and quality characteristics of bacon were investigated. The Na+ content, moisture, aw, pH, L* value, and sensory saltiness decreased and K+ content, a* value, and sensory bitterness increased significantly with increased substituting rates of NaCl by KCl (p < 0.05). There were no significant differences between the control and KCl substitution samples for the b* value, redness, and sensory off-odor (p > 0.05). The creatine content was not affected by the different KCl-substituting rates during the marinating process (p > 0.05), but it diminished in the smoking and frying processes (p < 0.05). The increase in the KCl-substituting rates increased the total heterocyclic aromatic amine (HAA) contents in fried bacon (p < 0.05). Moreover, the nonpolar HAA content in bacon was higher than the polar HAA content (p < 0.05). In summary, the partial replacement of NaCl by KCl increased the total HAA content and led to changes in bacon quality.

Resolution and b value dependent Structural Connectome in ex vivo Mouse Brain

Diffusion magnetic resonance imaging has been widely used in both clinical and preclinical studies to characterize tissue microstructure and structural connectivity. The diffusion MRI protocol for the Human Connectome Project (HCP) has been developed and optimized to obtain high-quality, high-resolution diffusion MRI (dMRI) datasets. However, such efforts have not been fully explored in preclinical studies, especially for rodents. In this study, high quality dMRI datasets of mouse brains were acquired at 9.4T system from two vendors. In particular, we acquired a high-spatial resolution dMRI dataset (25 um isotropic with 126 diffusion encoding directions), which we believe to be the highest spatial resolution yet obtained; and a high-angular resolution dMRI dataset (50 um isotropic with 384 diffusion encoding directions), which we believe to be the highest angular resolution compared to the dMRI datasets at the microscopic resolution. We systematically investigated the effects of three important parameters that affect the final outcome of the connectome: b value (1000 s/mm2 to 8000 s/mm2), angular resolution (10 to 126), and spatial resolution (25 um to 200 um). The stability of tractography and connectome increase with the angular resolution, where more than 50 angles are necessary to achieve consistent results. The connectome and quantitative parameters derived from graph theory exhibit a linear relationship to the b value (R2 > 0.99); a single-shell acquisition with b value of 3000 s/mm2 shows comparable results to the multi-shell high angular resolution dataset. The dice coefficient decreases and both false positive rate and false negative rate gradually increase with coarser spatial resolution. Our study provides guidelines and foundations for exploration of tradeoffs among acquisition parameters for the structural connectome in ex vivo mouse brain.

Reply to “Comment on ‘High-Definition Mapping of the Gutenberg–Richter b-Value and Its Relevance: A Case Study in Italy’ by M. Taroni, J. Zhuang, and W. Marzocchi” by Laura Gulia, Paolo Gasperini, and Stefan Wiemer

Taroni et al. (2021; hereafter TZM21) proposed a method to perform a spatial b-value mapping based on the weighted-likelihood estimation and applied this method to the Italian region as a tutorial example. In the accompanying comment, Gulia et al. (2021; hereafter GGW21) did not challenge the TZM21’s method, but they argued that the catalog used by TZM21 is contaminated by quarry blasts, introducing a bias that may impact any seismotectonic or hazard interpretations. Although in TZM21 the application to the Italian territory was only a tutorial example and we purposely did not make any thorough discussion on the meaning of the results in terms of seismotectonic or seismic hazards (that would have required many more analyses), we acknowledge the potential role of the quarry blasts, and we add some further analysis here. We thank GGW21 for giving us this opportunity. Here, removing the part of the catalog contaminated by quarry blasts and applying the same analysis as in TZM21, we obtain results that are very similar to the ones reported in TZM21; specifically, only one region that is characterized by low natural seismicity rate shows a marked effect of the quarry blasts on the b-value.

A precise method of color space conversion in the digital printing process based on PSO-DBN

Neural networks have been widely used in color space conversion in the digital printing process. The shallow neural network easily obtains the local optimal solution when establishing multi-dimensional nonlinear mapping. In this paper, an improved high-precision deep belief network (DBN) algorithm is proposed to achieve the color space conversion from CMYK to L*a*b*. First, the PANTONE TCX color card is used as sample data, in which the CMYK value of the color block is used as input and the L*a*b* value is used as output; then, the conversion model from CMYK to L*a*b* color space is established by using DBN. To obtain better weight and threshold, DBN is optimized by a particle swarm optimization algorithm. Experimental results show that the proposed method has the highest conversion accuracy compared with Back Propagation Neural Network, Generalized Regression Neural Network, and traditional DBN color space conversion methods. It can also adapt to the actual production demand of color management in digital printing.

A study of aftershocks of 20 October 1991 Uttarkashi earthquake

The Uttarkashi earthquake of 20 October 1991, which caused widespread damage in the Galhwal Himalayan region, was followed by a prominent aftershock. activity extending over a period of about two months. The aftershock activity was monitored using temporary networks established after the mainshock and the permanent stations in operation in the region. About 142 aftershocks could be located accurately using the data of these stations. The b-value of the Gutenberg-Richter's relationship for the aftershock sequence works out to be 0.6. The temporal distribution of the aftershocks suggests a hyperbolic decay with a decay constant (p) of 1.17. Macroseismic observations derived from field surveys show good agreement with the instrumentally determined source parameters.