Deformation limit states for corroded reinforced concrete beams and columns

Since deformation quantities have become principal design consideration in performance-based seismic design (PBSD), it is necessary to evaluate the deformation behavior of corroded RC structures for life-cycle oriented PBSD philosophy. Firstly, the material strain-based criteria to classify the performance limit states of RC beams and columns were proposed. Numerical analysis of corroded RC beams and columns in a wide range of design parameters was performed with the aid of ABAQUS finite element analytical program to evaluate the deformation behavior of corroded RC members. It is found that the corrosion ratio of reinforced bars has little effect on the deformation capacity of corroded RC members with low corrosion ratio. RC beams and columns with high corrosion ratio could fail due to the deterioration of bond between the concrete and longitudinal reinforcement, which induces significant degradation of deformation capacity of the structural member. The statistical characteristic values of deformation indexes corresponding to individual performance limit state of corroded RC beams and columns were obtained based on numerical analysis results. The research results can be utilized for life-cycle oriented seismic performance evaluation and design of RC structures

Top-quark FCNC Productions at LHC in Topcolor-assisted Technicolor Model

We evaluate the top-quark FCNC productions induced by the topcolor assisted technicolor (TC2) model at the LHC. These productions proceed respectively through the parton-level processes g g -> t c_bar, c g->t, c g -> t g, c g -> t Z and c g -> t \gamma. We show the dependence of the production rates on the relevant TC2 parameters and compare the results with the predictions in the minimal supersymmetric model. We find that for each channel the TC2 model predicts a much larger production rate than the supersymmetric model. All these rare productions in the TC2 model can be enhanced above the 3-sigma sensitivity of the LHC. Since in the minimal supersymmetric model only c g -> t is slightly larger than the corresponding LHC sensitivity, the observation of these processes will favor the TC2 model over the supersymmetric model. In case of unobservation, the LHC can set meaningful constraints on the TC2 parameters.Comment: 5 pages, 4 fig

Maximizing the relationship of yield to site-specific management zones with object-oriented segmentation of hyperspectral images

Quick and low cost delineation of site-specific management zones (SSMZ) would improve applications of precision agriculture. In this study, a new method for delineating SSMZ using object-oriented segmentation of airborne imagery was demonstrated. Three remote sensing domains—spectral, spatial, and temporal- are exploited to improve the SSMZ relationship to yield. Common vegetation indices (VI), and first and second derivatives ([Formula: see text], [Formula: see text]) from twelve airborne hyperspectral images of a cotton field for one season [Formula: see text] were used as input layers for object-oriented segmentation. The optimal combination of VI, SSMZ size and crop phenological stage were used as input variables for SSMZ delineation, determined by maximizing the correlation to segmented yield monitor maps. Combining narrow band vegetation indices and object-oriented segmentation provided higher correlation between VI and yield at SSMZ scale than that at pixel scale by reducing multi-resource data noise. VI performance varied during the cotton growing season, providing better SSMZ delineation at the beginning and middle of the season (days after planting (DAP) 66–143).The optimal scale determined for SSMZ delineation was approximately 240 polygons for the study field, but the method also provided flexibility enabling the setting of practical scales for a given field. For a defined scale, the optimal single phenological stage for the study field was near July 11 (DAP 87) early in the growing season. SSMZs determined from multispectral VIs at a single stage were also satisfactory; compared to hyperspectral indices, temporal resolution of multi-spectral data seems more important for SSMZ delineation

Staphylococcus cohnii infection diagnosed by metagenomic next generation sequencing in a patient on hemodialysis with cirrhotic ascites: a case report

BackgroundPatients with spontaneous bacterial peritonitis (SBP) often just receive empirical antibiotic therapy, as pathogens can be identified in only few patients using the techniques of conventional culture. Metagenomic next generation sequencing (mNGS) is a useful tool for diagnosis of infectious diseases. However, clinical application of mNGS in diagnosis of infected ascites of cirrhotic patients is rarely reported.Case presentationA 53-year-old male with cirrhosis on regular hemodialysis presented with continuous abdominal pain. After treatment with empiric antibiotics, his inflammatory parameters decreased without significant relief of abdominal pain. Finally, based on ascites mNGS detection, he was diagnosed as infection of Staphylococcus cohnii (S.cohnii), a gram-positive opportunistic pathogen. With targeted antibiotic treatment, the bacterial peritonitis was greatly improved and the patient’s abdominal pain was significantly alleviated.ConclusionsWhen conventional laboratory diagnostic methods and empirical antibiotic therapy fail, proper application of mNGS can help identify pathogens and significantly improve prognosis and patients’ symptoms

Adaptive Optimizers with Sparse Group Lasso for Neural Networks in CTR Prediction

We develop a novel framework that adds the regularizers of the sparse group lasso to a family of adaptive optimizers in deep learning, such as Momentum, Adagrad, Adam, AMSGrad, AdaHessian, and create a new class of optimizers, which are named Group Momentum, Group Adagrad, Group Adam, Group AMSGrad and Group AdaHessian, etc., accordingly. We establish theoretically proven convergence guarantees in the stochastic convex settings, based on primal-dual methods. We evaluate the regularized effect of our new optimizers on three large-scale real-world ad click datasets with state-of-the-art deep learning models. The experimental results reveal that compared with the original optimizers with the post-processing procedure which uses the magnitude pruning method, the performance of the models can be significantly improved on the same sparsity level. Furthermore, in comparison to the cases without magnitude pruning, our methods can achieve extremely high sparsity with significantly better or highly competitive performance. The code is available at https://github.com/intelligent-machine-learning/dlrover/blob/master/tfplus.Comment: 24 pages. Published as a conference paper at ECML PKDD 2021. This version includes Appendix which was not included in the published version because of page limi

Sol-Gel Deposition of TiO2 Nanocoatings on Wood Surfaces with Enhanced Hydrophobicity and Photostability

To enhance the resistance of wood against weathering, Chinese fir (Cunninghamia lanceolata) wood was modified via a two-step process by first growing titanium dioxide (TiO2) nanocoatings on the wood substrate using a sol-gel process followed by low-surface free-energy treatment with hydrolyzed hexadecyltrimethoxysilane (HDTMS). The morphology and chemical composition of the formed coatings were examined by field-emission scanning electron microscopy, energy dispersive X-ray analysis, and Fourier transform IR spectroscopy. Water contact angle (WCA) was used to characterize hydrophobicity. UV-Vis spectroscopy and accelerated weathering were used to evaluate the UV-shielding properties of the nanocoatings and the photostability of the treated wood, respectively. The results showed that the introduction of TiO2 nanoparticles facilitated the generation of a dual-size roughness on the wood substrate, and the long-chain alkyl groups of HDTMS were covalently linked to the surface of the particles. The WCA of the treated wood was improved remarkably up to ≈138° displaying high hydrophobicity. The TiO2 coatings also exhibited strong absorption of UV radiation and imparted the underlying wood substrate with enhanced photostability, which was highly dependent on the TiO2 loadings in the coatings