4-(3-Nitro­phen­yl)-3-(phenyl­sulfon­yl)but-3-en-2-one

The C=C double bond in the title mol­ecule, C16H13NO5S, has an E configuration. The crystal structure is stabilized by C—H⋯O hydrogen bonds. There is also a weak C—H⋯π-ring inter­action in the structure

Identification of Technical Journals by Image Processing Techniques

The emphasis of this study is put on developing an automatic approach to identifying a given unknown technical journal from its cover page. Since journal cover pages contain a great deal of information, determining the title of an unknown journal using optical character recognition techniques seems difficult. Comparing the layout structures of text blocks on the journal cover pages is an effective method for distinguishing one journal from the other. In order to achieve efficient layout-structure comparison, a left-to-right hidden Markov model (HMM) is used to represent the layout structure of text blocks for each kind of journal. Accordingly, title determination of an input unknown journal can be effectively achieved by comparing the layout structure of the unknown journal to each HMM in the database. Besides, from the layout structure of the best matched HMM, we can locate the text block of the issue date, which will be recognized by OCR techniques for accomplishing an automatic journal registration system. Experimental results show the feasibility of the proposed approach

Numerical computation for vibration characteristics of long-span bridges with considering vehicle-wind coupling excitations based on finite element and neural network models

CA (Cellular Automaton) model was applied to the simulation of random traffic flow to develop a model considering the randomness of traffic flow and apply it to wind-vehicle-bridge coupling vibration. Finite element and neural network models were adopted respectively to numerically compute the vibration characteristics of bridges under wind and vehicle loads, verify the correctness of model. Subspace iteration method was used for the modal analysis of bridges. Natural frequencies of the top 8 orders were 0.21 Hz, 0.27 Hz, 0.36 Hz, 0.45 Hz, 0.56 Hz, 0.66 Hz, 0.87 Hz and 1.02 Hz respectively. The vibration frequency of the long-span bridge was consistent with the vibration characteristics of large-scale complex structures. Natural modes mainly reflected the torsion and bending of main beam and the swinging vibration of side and main towers. Fluctuation wind time-history presented periodic characteristics. The maximum and minimum values of fluctuation wind were about 20 m/s and –20 m/s respectively. The target and simulation values of power spectral density of wind speed were basically the same in change trend, which indicated that the fluctuation wind time-history computed in this paper was reliable. The model of dense traffic flow based on CA more truly described the running status like accelerating, decelerating and changing lanes of vehicles on the bridge, also contained the density information of vehicles and more truly reflected traffic characteristics. Vibration accelerations of the long-span bridge were symmetrically distributed. Vibration acceleration of central position in the left main span was the largest and near 50 cm/s2; vibration acceleration on the main tower was the smallest. The curve of vibration displacement with considering wind loads presented some fluctuations, while the vibration displacement of bridges without considering wind loads was very smooth. In addition, the amplitude of vibration displacement without considering wind loads moved laterally towards the left compared with that with considering wind loads. Therefore, wind loads must be considered when the vibration characteristics of the long-span bridge were computed. Otherwise, the accuracy of computational results would be reduced. It only took 0.5 hours to use neural network to predict the vibration acceleration of the long-span bridge. In the case of the same computer performance, it took 5 hours to use finite element model to predict the vibration acceleration of the long-span bridge. The advantage of neural network model in predicting the performance of large-scale complex structures like a long-span bridge could be obviously found. In the future, we will consider using neural network model to systematically study and optimize the long-span bridge

Research on the computational method of vibration impact coefficient for the long-span bridge and its application in engineering

To compute vibration impact coefficient at each part of the long-span bridge more accurately, this paper proposed a computational method based on vehicle-bridge coupling vibration. Firstly, the general equations of vehicle-bridge coupling vibration were derived based on the standard fatigue vehicle and multi-scale model of bridges. Secondly, the corresponding program of vehicle-bridge coupling vibration was designed. Thirdly, the computational method of vibration impact coefficient for the long-span bridge was introduced and obtained. The proposed computation method of vibration impact coefficient based on vehicle-bridge coupling vibration was finally verified by the corresponding experiment. They were consistent with each other, and the computational method was reliable and can be used to analyze the bridge. Based on the verified method, a lot of influence factors on vibration impact coefficient were analyzed. As a result, we can obtain a bridge with the smallest vibration impact coefficient. Finally, the remaining life of bridges was computed and evaluated based on the smallest vibration impact coefficient

The UV Excesses of Supernovae and the Implications for Studying Supernovae and Other Optical Transients

Supernovae (SNe), kilonovae (KNe), tidal disruption events (TDEs), optical afterglows of gamma ray bursts (GRBs), and many other optical transients are important phenomena in time-domain astronomy. Fitting the multi-band light curves (LCs) or the synthesized (pseudo-)bolometric LCs can be used to constrain the physical properties of optical transients. The (UV absorbed) blackbody module is one of the most important modules used to fit the multi-band LCs of optical transients having (UV absorbed) blackbody spectral energy distributions (SEDs). We find, however, that the SEDs of some SNe show UV excesses, which cannot be fitted by the model including a (UV absorbed) blackbody module. We construct the bolometric LCs and employ the (cooling plus) \Ni model to fit the constructed bolometric LCs, obtaining decent fits. Our results demonstrate that the optical transients showing UV excesses cannot be fitted by the multi-band models that include (UV-absorbed) blackbody module, but can be well modeled by constructing and fitting their bolometric LCs.Comment: 9 pages, 4 figures, 1 table, submitted to Ap