Some Nonlinear Gronwall-Bellman-Gamidov Integral Inequalities and Their Weakly Singular Analogues with Applications

Some Gronwall-Bellman-Gamidov type integral inequalities with power nonlinearity and their weakly singular analogues are established, which can give the explicit bound on solution of a class of nonlinear fractional integral equations. An example is presented to show the application for the qualitative study of solutions of a fractional integral equation with the Riemann-Liouville fractional operator

Some Nonlinear Gronwall-Bellman-Gamidov Integral Inequalities and Their Weakly Singular Analogues with Applications

Some Gronwall-Bellman-Gamidov type integral inequalities with power nonlinearity and their weakly singular analogues are established, which can give the explicit bound on solution of a class of nonlinear fractional integral equations. An example is presented to show the application for the qualitative study of solutions of a fractional integral equation with the Riemann-Liouville fractional operator

Development and Validation of a New Method to Diagnose Apical Hypertrophic Cardiomyopathy By Gated Single-Photon Emission Computed Tomography Myocardial Perfusion Imaging

Aim The aim of this study is to develop and validate a new method to diagnose apical hypertrophic cardiomyopathy (AHCM) by the integral quantitative analysis of myocardial perfusion and wall thickening from gated single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI). Patients and methods Twenty-two consecutive patients, who showed T wave inversion of at least 3 mm in precordial leads and sinus rhythm in ECG, were enrolled. All the patients underwent cardiac magnetic resonance (CMR), gated rest SPECT MPI and echocardiography. According to CMR diagnostic results, 13 patients were categorized as in the AHCM group and the remaining nine patients were categorized as in the non-AHCM group. Operators who were blinded to the CMR diagnosis independently performed the diagnosis by gated SPECT MPI. The regions of interest inside the apical hotspots on the perfusion polar map were drawn and the mean values of wall thickening in the drawn region of interests were calculated. Using MRI diagnosis as the gold standard, AHCM was diagnosed based on receiver operating characteristic analysis of the mean wall thickening in the apical perfusion hotspot. The area under curve, sensitivity, specificity, and accuracy of our method were 0.97, 100, 89, and 95%, respectively. Conclusion Our new method has high sensitivity, specificity, and accuracy against CMR diagnosis. It has great promise to become a clinical tool in the diagnosis of AHCM

The prognostic value of multiparametric cardiac magnetic resonance in patients with systemic light chain amyloidosis

BackgroundLate gadolinium enhancement (LGE) is a classic imaging modality derived from cardiac magnetic resonance (CMR), which is commonly used to describe cardiac tissue characterization. T1 mapping with extracellular volume (ECV) and native T1 are novel quantitative parameters. The prognostic value of multiparametric CMR in patients with light chain (AL) amyloidosis remains to be thoroughly investigated.MethodsA total of 89 subjects with AL amyloidosis were enrolled from April 2016 to January 2021, and all of them underwent CMR on a 3.0 T scanner. The clinical outcome and therapeutic effect were observed. Cox regression was used to investigate the effect of multiple CMR parameters on outcomes in this population.ResultsLGE extent, native T1 and ECV correlated well with cardiac biomarkers. During a median follow-up of 40 months, 21 patients died. ECV (hazard ratio [HR]: 2.087 for per 10% increase, 95% confidence interval [CI]: 1.379-3.157, P < 0.001) and native T1 (HR: 2.443 for per 100 ms increase, 95% CI: 1.381-4.321, P=0.002) were independently predictive of mortality. A novel prognostic staging system based on median native T1 (1344 ms) and ECV (40%) was similar to Mayo 2004 Stage, and the 5-year estimated overall survival rates in Stage I, II, and III were 95%, 80%, and 53%, respectively. In patients with ECV > 40%, receiving autologous stem cell transplantation had higher cardiac and renal response rates than conventional chemotherapy.ConclusionBoth native T1 and ECV independently predict mortality in patients with AL amyloidosis. Receiving autologous stem cell transplantation is effective and significantly improves the clinical outcomes in patients with ECV > 40%

Effects of sand burial on biomass, chlorophyll fluorescence and extracellular polysaccharides of man-made cyanobacterial crusts under experimental conditions

Soil cyanobacterial crusts occur throughout the world, especially in the semiarid and arid regions. It always encounters sand burial, which is an important feature of mobile sand dunes. A greenhouse 41 study was conducted to determine the effects of sand burial on biomass, chlorophyll fluorescence and extracellular polysaccharides of man-made cyanobacterial crusts in six periods of time (0, 5, 10, 15, 20 and 30 d after burying) and at five depths (0, 0.2, 0.5, 1 and 2cm). The results indicated that with the increase of the burial time and burial depth extracellular polysaccharides content and Fv/Fm decreased correspondingly and there were no significant differences between 20 and 30 burial days under different burial depths. The degradation of chlorophyll a content appeared only at 20 and 30 burial days and there was also no significant difference between them under different burial depths. It was also observed a simultaneous decrease of the values of the Fv/Fm and the content of extracellular polysaccharides happened in the crusted cyanobacterium Microcoleus vaginatus Gom. It may suggest that there exists a relationship between extracellular polysaccharides and recovery of the activity of photosystem II (PS II) after rehydration.Soil cyanobacterial crusts occur throughout the world, especially in the semiarid and arid regions. It always encounters sand burial, which is an important feature of mobile sand dunes. A greenhouse 41 study was conducted to determine the effects of sand burial on biomass, chlorophyll fluorescence and extracellular polysaccharides of man-made cyanobacterial crusts in six periods of time (0, 5, 10, 15, 20 and 30 d after burying) and at five depths (0, 0.2, 0.5, 1 and 2cm). The results indicated that with the increase of the burial time and burial depth extracellular polysaccharides content and Fv/Fm decreased correspondingly and there were no significant differences between 20 and 30 burial days under different burial depths. The degradation of chlorophyll a content appeared only at 20 and 30 burial days and there was also no significant difference between them under different burial depths. It was also observed a simultaneous decrease of the values of the Fv/Fm and the content of extracellular polysaccharides happened in the crusted cyanobacterium Microcoleus vaginatus Gom. It may suggest that there exists a relationship between extracellular polysaccharides and recovery of the activity of photosystem II (PS II) after rehydration

Convergence Analysis of an Inexact Three-Operator Splitting Algorithm

The three-operator splitting algorithm is a new splitting algorithm for finding monotone inclusion problems of the sum of three maximally monotone operators, where one is cocoercive. As the resolvent operator is not available in a closed form in the original three-operator splitting algorithm, in this paper, we introduce an inexact three-operator splitting algorithm to solve this type of monotone inclusion problem. The theoretical convergence properties of the proposed iterative algorithm are studied in general Hilbert spaces under mild conditions on the iterative parameters. As a corollary, we obtain general convergence results of the inexact forward-backward splitting algorithm and the inexact Douglas-Rachford splitting algorithm, which extend the existing results in the literature

Deep convolutional neural network target detection algorithm for coal mine fault detection

Fault interpretation plays an important role in the field of coal mine safety. The development of neural network gives rise to many intelligent seismic data interpretation and processing schemes based on neural network algorithm. This study ①selected the Faster R-CNN target detection algorithm more suitable for fault recognition by comparing different deep convolutional neural network target detection algorithms. ②tested AlexNet, residual network ResNet50 and ResNet101 feature extraction networks through seismic forward modeling with various geological characteristics. It is found that ResNet101 feature extraction network has better performance in fault detection. ③constructed a fault detection model based on the preferred ResNet101 feature extraction network and Faster R-CNN target detection algorithm, and detected the actual seismic data. Results show that the object detection algorithm based on deep convolutional neural network shows satisfactory generalization ability in fault detection. It could improve the fault interpretation efficiency, and has potential in application