Synchro-Squeezed Adaptive Wavelet Transform and its Application to Impact Echo Signals for Pavement Defect Detection

In this study, the recently-proposed adaptive wavelet transform (AWT) and synchro-squeezed adaptive wavelet transform (SSAWT) are introduced with their optimum transformation parameters automatically searched to derive at a desirable time-frequency representation of any dynamic response. The AWT enables the selectivity of time and frequency resolution in a domain of interest and the synchro-squeezing algorithm reduces the dispersion of a scalogram of the AWT, facilitating an accurate extraction of frequency features over time. The effectiveness of AWT is first demonstrated with an illustrative signal of four time segments covering various frequency distribution cases. In comparison with conventional wavelet transform, the AWT can clearly separate time-varying frequency features from the signal. Accordingly, the SSAWT is at least 5 times more accurate with a 1.1% error than conventional synchro-squeezed wavelet transform. The AWT is then applied to the impact echo (IE) responses experimentally recorded from a 60 ×36 ×7.25 concrete slab for potential pavement applications. The time-frequency resolution and corresponding frequency spectra led to the successful detections of deep pavement defect, shallow pavement defect or no pavement defect from 40 sets of experimental data. The SSAWT results in a 1.5% estimation error in the identification of deep pavement defect depth and a 5% estimation error in slab thickness, both being twice more accurate than the AWT in terms of estimation error. The selection process of time-varying central frequencies, scaling factors, and window lengths proves robust

Integrability for Solutions of Anisotropic Obstacle Problems

This paper deals with anisotropic obstacle problem for the -harmonic equation ∑i=1nDi(ai(x,Du(x)))=0. An integrability result is given under suitable assumptions, which show higher integrability of the boundary datum, and the obstacle force solutions u have higher integrability as well

Transcriptomic and metabolomic analysis reveals the influence of carbohydrates on lignin degradation mediated by Bacillus amyloliquefaciens

IntroductionLigninolytic bacteria can secrete extracellular enzymes to depolymerize lignin into small-molecular aromatics that are subsequently metabolized and funneled into the TCA cycle. Carbohydrates, which are the preferred carbon sources of bacteria, influence the metabolism of lignin-derived aromatics through bacteria.MethodsIn this study, untargeted metabolomics and transcriptomics analyses were performed to investigate the effect of carbohydrates on lignin degradation mediated by Bacillus amyloliquefaciens MN-13, a strain with lignin-degrading activity that was isolated in our previous work.ResultsThe results demonstrated that the cell growth of the MN-13 strain and lignin removal were promoted when carbohydrates such as glucose and sodium carboxymethyl cellulose were added to an alkaline lignin-minimal salt medium (AL-MSM) culture. Metabolomics analysis showed that lignin depolymerization took place outside the cells, and the addition of glucose regulated the uptake and metabolism of lignin-derived monomers and activated the downstream metabolism process in cells. In the transcriptomics analysis, 299 DEGs were screened after 24 h of inoculation in AL-MSM with free glucose and 2 g/L glucose, respectively, accounting for 8.3% of the total amount of annotated genes. These DEGs were primarily assigned to 30 subcategories, including flagellar assembly, the PTS system, RNA degradation, glycolysis/gluconeogenesis, the TCA cycle, pyruvate metabolism, and tryptophan metabolism. These subcategories were closely associated with the cell structure, generation of cellular energy, and precursors for biosynthetic pathways, based on a − log 10 (P adjust) value in the KEGG pathway analysis.ConclusionIn summary, the addition of glucose increased lignin degradation mediated by the MN-13 strain through regulating glycolysis, TCA cycle, and central carbon metabolism

Applications of Fixed Point Theorems to Generalized Saddle Points of Bifunctions on Chain-Complete Posets

We apply the extensions of the Abian-Brown fixed point theorem for set-valued mappings on chain-complete posets to examine the existence of generalized and extended saddle points of bifunctions defined on posets. We also study the generalized and extended equilibrium problems and the solvability of ordered variational inequalities on posets, which are equipped with a partial order relation and have neither an algebraic structure nor a topological structure

Wind Effects on Dome Structures and Evaluation of CFD Simulations through Wind Tunnel Testing

In the Study, a Series of Wind Tunnel Tests Were Conducted to Investigate Wind Effects Acting on Dome Structures (1/60 Scale) Induced by Straight-Line Winds at a Reynolds Number in the Order of 106. Computational Fluid Dynamics (CFD) Simulations Were Performed as Well, Including a Large Eddy Simulation (LES) and Reynolds-Averaged Navier–Stokes (RANS) Simulation, and their Performances Were Validated by a Comparison with the Wind Tunnel Testing Data. It is Concluded that Wind Loads Generally Increase with Upstream Wind Velocities, and They Are Reduced over Suburban Terrain Due to Ground Friction. the Maximum Positive Pressure Normally Occurs Near the Base of the Dome on the Windward Side Caused by the Stagnation Area and Divergence of Streamlines. the Minimum Suction Pressure Occurs at the Apex of the Dome Because of the Blockage of the Dome and Convergence of Streamlines. Suction Force is the Most Significant among All Wind Loads, and Special Attention Should Be Paid to the Roof Design for Proper Wind Resistance. Numerical Simulations Also Indicate that LES Results Match Better with the Wind Tunnel Testing in Terms of the Distribution Pattern of the Mean Pressure Coefficient on the Dome Surface and Total Suction Force. the Mean and Root-Mean-Square Errors of the Meridian Pressure Coefficient Associated with the LES Are About 60% Less Than Those Associated with RANS Results, and the Error of Suction Force is About 40–70% Less. Moreover, the LES is More Accurate in Predicting the Location of Boundary Layer Separation and Reproducing the Complex Flow Field Behind the Dome, and is Superior in Simulating Vortex Structures Around the Dome to Further Understand the Unsteadiness and Dynamics in the Flow Field

Immune-inflammatory biomarkers for the occurrence of MACE in patients with myocardial infarction with non-obstructive coronary arteries

BackgroundNeutrophil-to-high-density lipoprotein cholesterol ratio (NHR), monocyte-to-high-density lipoprotein cholesterol ratio (MHR), lymphocyte-to-high-density lipoprotein cholesterol ratio (LHR), platelet-to-high-density lipoprotein cholesterol ratio (PHR), systemic immune-inflammation index (SII), systemic inflammation response index (SIRI), and aggregate index of systemic inflammation (AISI) have been identified as immune-inflammatory biomarkers associated with the prognosis of cardiovascular diseases. However, the relationship of these biomarkers with the prognosis of myocardial infarction with non-obstructive coronary arteries (MINOCA) remains unclear.MethodPatients with MINOCA who underwent coronary angiography at the 920th Hospital of Joint Logistics Support Force were included in our study. Clinical baseline characteristics and laboratory testing data were collected from the hospital record system. The patients were divided into two groups on the basis of major adverse cardiovascular events (MACE) occurrence. Multiple logistic regression analysis was conducted to assess the relationship between NHR, MHR, LHR, PHR, SII, SIRI, AISI, and MACE. Receiver operating characteristic (ROC) curves were generated to evaluate the predictive value of NHR, MHR, LHR, PHR, SII, SIRI, and AISI for MACE in patients with MINOCA. The accuracy of the prediction was indicated by the area under the curve (AUC) value.ResultsThe study included 335 patients with MINOCA. (81 in the MACE group and 254 in the No-MACE group). The MACE group had higher levels of NHR, MHR, LHR, PHR, SII, SIRI, and AISI than the No-MACE group. Multiple logistic regression analysis adjusted for confounding factors indicated that the higher levels of NHR, MHR, PHR, SII, SIRI, and AISI were associated with the occurrence of MACE in patients with MINOCA (P < 0.001). The AUC values for NHR, MHR, PHR, SII, SIRI, and AISI were 0.695, 0.747, 0.674, 0.673, 0.688, and 0.676, respectively. The combination of NHR, MHR, PHR, SII, SIRI, and AISI improved the accuracy of predicting MACE in patients with MINOCA (AUC = 0.804).ConclusionHigher levels of NHR, MHR, PHR, SII, SIRI, and AISI were associated with the occurrence of MACE, and the combination of NHR, MHR, PHR, SII, SIRI, and AISI improved the accuracy for predicting the incidence of MACE events in patients with MINOCA

Statefinder Parameters for Five-Dimensional Cosmology

We study the statefinder parameter in the five-dimensional big bounce model, and apply it to differentiate the attractor solutions of quintessence and phantom field. It is found that the evolving trajectories of these two attractor solutions in the statefinder parameters plane are quite different, and that are different from the statefinder trajectories of other dark energy models.Comment: 8 pages, 12 figures. accepted by MPL