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The target of image-text clustering (ITC) is to find correct clusters by integrating complementary and consistent information of multi-modalities for these heterogeneous samples. However, the majority of current studies analyse ITC on the ideal premise that the samples in every modality are complete. This presumption, however, is not always valid in real-world situations. The missing data issue degenerates the image-text feature learning performance and will finally affect the generalization abilities in ITC tasks. Although a series of methods have been proposed to address this incomplete image text clustering issue (IITC), the following problems still exist: 1) most existing methods hardly consider the distinct gap between heterogeneous feature domains. 2) For missing data, the representations generated by existing methods are rarely guaranteed to suit clustering tasks. 3) Existing methods do not tap into the latent connections both inter and intra modalities. In this paper, we propose a Clustering-Induced Generative Incomplete Image-Text Clustering(CIGIT-C) network to address the challenges above. More specifically, we first use modality-specific encoders to map original features to more distinctive subspaces. The latent connections between intra and inter-modalities are thoroughly explored by using the adversarial generating network to produce one modality conditional on the other modality. Finally, we update the corresponding modalityspecific encoders using two KL divergence losses. Experiment results on public image-text datasets demonstrated that the suggested method outperforms and is more effective in the IITC job., Comment: 13 pages,12 figures

The superstructure of passenger ship becomes more and more plump to satisfy the requirement of different functional area and comfortable space. Therefore, the research on the bending efficiency of superstructure to hull girder strength of the passenger ship is paid more attention. In the present paper, an inland passenger ship is taken into account. The interaction of main hull and superstructure is analyzed based on the two-beam theory. The bending efficiency of superstructure is investigated and discussed which can provide technical supporting to the structural design of the superstructure of passenger ship.

Using static chamber technique, fluxes of CO2, CH4 and N2O were measured in the alpine grassland area from July 2000 to July 2001, determinations of mean fluxes showed that CO2 and N2O were generally released from the soil, while the alpine grassland accounted for a weak CH4 sink. Fluxes of CO2, CH4 and N2O ranged widely. The highest CO2 emission occurred in August, whereas almost 90% of the whole year emission occurred in the growing season. But the variations of CH4 and N2O fluxes did not show any clear patterns over the one-year-experiment. During a daily variation, the maximum CO2 emission occurred at 16:00, and then decreased to the minimum emission in the early morning. Daily pattern analyses indicated that the variation in CO2 fluxes was positively related to air temperatures (R2=0.73) and soil temperatures at a depth of 5 cm (R2=0.86), whereas daily variations in CH4 and N2O fluxes were poorly explained by soil temperatures and climatic variables. CO2 emissions in this area were much lower than other grasslands in plain areas.

In this paper, the CO2 concentrations profile from 1.5 m depth in soil to 32 m height in atmosphere were measured from July 2000 to July 2001 in an alpine grassland ecosystem located in the permafrost area on the Tibetan Plateau, which revealed that CO2 concentrations varied greatly during this study period. Mean concentrations during the whole experiment in the atmosphere were absolutely lower than the CO2 concentrations in soil, which resulted in CO2 emissions from the alpine steppe soil to the atmosphere. The highest CO2 concentration was found at a depth of 1.5 m in soil while the lowest CO2 concentration occurred in the atmosphere. Mean CO2 concentrations in soil generally increased with depth. This was the compositive influence of the increasing soil moistures and decreasing soil pH, which induced the increasing biological activities with depth. Temporally, the CO2 concentrations at different layers in air remained a more steady state because of the atmospheric turbulent milking. During the seasonal variations, CO2 concentrations at surface soil interface showed symmetrical patterns, with the lowest accumulation of CO2 occurring in the late winter and the highest CO2 concentration in the growing seasons.