A full scale water modeling experiment has been conducted to address the relationship between the instability of fluid flow and level fluctuation in the continuous thin slab casting mould with the particle image visualization. The results show that the internal fluid flow and level fluctuation are unsteady and periodical. The probabilities of fluctuated meniscus and moving circumfluence center position seem Possion distributions with the highest frequency near the average position. The circumfluence and meniscus profile are asymmetrical, and the phase difference of wave height and circumfluence center in the two sides of mould centerline is half period. The average meniscus profile, the highest and lowest meniscus positions are generally symmetry about the mould centerline, and the circumfluence center swings with a similar trace. The wave height mainly depends on the circumfluence center position along the mould height. The wave height has an inverse relation with the circumfluence center depth, and the wave height decreases with descending circumfluence.
A water modelling experiment was conducted to study the meniscus instability in a continuous thin slab casting mould using particle image visualisation. The results show that the level fluctuation, circulation centre position and jet impinging depth are unsteady and periodic with a similar period. The probability distributions of the fluctuating meniscus and wave height have been obtained with the highest frequency near the average position. The flow pattern and meniscus profile may be momentarily asymmetrical, and the phase difference of level fluctuation in the two sides of mould centreline is a half period. The average meniscus profile, the highest and lowest meniscus positions are generally symmetrical about the mould centreline. The wave height mainly depends on the jet impinging depth and circulation centre position. The wave height increases as the jet impinging position rises and the circulation centre approaches to the submerged entry nozzle.
The development of novel inhibitors against metallo-β-lactamase is essential to remedy metallo-β-lactamase mediated bacterial resistance. A recently emerged metallo-β-lactamase, VIM-2, has demonstrated resistance to existing β-lactamase inhibitors in the clinic. In this study, a hybrid virtual screening protocol that combines pharmacophore modeling, molecular docking, and calculation of binding free energy was employed to screen an internal tripeptide database for novel inhibitors against VIM-2. This resulted in four tripeptides (WWC, WCW, MCW, YCW) as potential inhibitors, and their effects on VIM-2 metallo-β-lactamase were subsequently tested in vitro. Significantly, two peptides (MCW, YCW) exhibited potent inhibitory activities with IC50 values of 18.15 µM and 52.9 µM, respectively. To our knowledge, this is the first study that employed the hybrid virtual screening of combinational peptide database and discovered potent peptide inhibitors of VIM-2 metallo-β-lactamase.
Flow instability in continuous thin slab casting moulds has been studied using a full scale water model with particle image visualization. The results show that jet impinging depth, circumfluence centre position and wave height are unsteady and periodical. The probabilities of jet impinging depth and circumfluence centre position seem to be Poisson distributions with the highest frequency near the average position. The flow pattern is asymmetrical for a short time and the phase difference of jet impinging depth, circumfluence centre position and wave height on the two sides of the mould centreline is half a period. The average jet impinging depth, average circumfluence centre position, average meniscus wave profile and the highest and lowest meniscus positions are generally symmetrical to the mould centreline.
In order to solve the problem of high dimensionality and low recognition rate caused by complex calculation in face recognition, the author proposes a face recognition algorithm based on weighted DWT and DCT based on particle swarm neural network applied to new energy vehicles. The algorithm first decomposes the face image with wavelet transform, removes the influence of the diagonal component, the weighted low-frequency and high-frequency discrete cosine transform coefficients are extracted as feature vectors, and finally, the particle swarm optimization BP neural network is used for classification and identification. Experimental results show that when the wavelet weights take a 0 = 0.9 , a 1 = 0.05 , and a 2 = 0.05 , the recognition rate reaches the highest. Regardless of whether the low-frequency component continues to increase or decrease, and the high-frequency component continues to decrease or increase, the recognition rate will decrease. When the eigenvector dimension is around 60, the recognition rate difference between the weighted wavelet algorithm and the general low-frequency wavelet algorithm reaches the maximum. The recognition rate of the proposed algorithm is much higher than the other two traditional algorithms. Conclusion. The effectiveness and feasibility of the algorithm are verified on the ORL face database.
The microstructure evolution of hypoeutectoid steel during casting and heat treatment processes was simulated by using cellular automaton method. In the simulation, the peritectic solidification, α phase precipitation and pearlite transformation during casting process were considered, and the austenite formation, grain coarsening and decomposition during heat treatment were simulated. The final microstructure, including the average grain size and fraction of α phase as well as the average interlamellar spacing of pearlite, was obtained. The use of through-process simulation as well as a comparison with experiments was demonstrated using a hollow shaft casting as an example. By using the model, the microstructure evolution at different locations in the hollow shaft was simulated, in which the thermal history data obtained by simulating the casting and heat treatment processes were adopted. Metallographic samples taken from the test bar were examined and corresponding mechanical properties tests were conducted. The simulated results were compared with the experimental results to validate the model.
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