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The design and implementation of virtual museums have evolved over decades, broadening the scope of traditional museum exhibitions and serving as an effective complement to physical museums. However, virtual visual effects have consistently fallen short of replicating the authentic exhibition experience and cannot substitute for physical museums. In this paper, we report a dual-mode mixed visualization system combining computational photography and binocular stereo vision techniques, and introduce an innovative virtual museum for Sanxingdui bronzes. This approach enables visitors to engage with the artifacts in a multifaceted manner-allowing for navigation, interaction, auditory guidance, and the examination of textural details as if handling the artifacts directly. Further analysis of participant responses in terms of visual cognition and aesthetic appreciation across different settings demonstrates that this dual-mode mixed visualization delivers not only a spatiotemporal experience consistent with the real world but also surreal visual effects. This immersive experience allows audiences to experience Sanxingdui art intimately, offering both high-resolution visuals and cost-effectiveness. [ABSTRACT FROM AUTHOR]

Although the government highly focuses on old residential building energy-saving renovation (ORBESR), many hinders still exist and the efficiency of it is still low. This paper proposes a four-party evolutionary game model to study the impact of relative stakeholders' choices, involving developers, residents, neighborhood councils, and governments. Using this model, this paper studies what influences the conflicts between developers and residents take on the efficiency of ORBESR. In addition, what influence the residents, neighborhood councils, and developers' strategies will take on the ORBESR under the condition of evolutionary stability strategy. This paper finally concludes that governments could propose high penalties first to accelerate the stability of the system, then suitable subsidies to relieve the financial burden and to achieve high efficiency. The governments could provide a suitable plan for residents' investment to promote residents' participation. The neighborhood councils arouse the ways and facilities to help residents understand and participate in the ORBESR and try to solve the conflicts between developers and residents can improve the residents' participation and the developers' willingness to implement the ORBESR. [ABSTRACT FROM AUTHOR]

Exhaust gas recirculation control (EGRC), an inlet air heating technology, can be utilized in combination with inlet/variable guide vane control (IGV/VGVC) and fuel flow control (FFC) to regulate the load, thereby effectively improving the part-load (i.e., off-design) performance of the gas turbine combined cycle (GTCC). In this study, the E-, F-, and H-Class EGR-GTCC design and off-design system models were established and validated to perform a comparative analysis of the part-load performance under the EGR-IGV-FFC and conventional IGV-FFC strategies in the E/F/H-Class GTCC. Results show that EGR-IGV-FFC has considerable potential for the part-load performance enhancement and can show a higher combined cycle efficiency than IGV-FFC in the E-, F-, and H-Class GTCCs. However, the part-load performance improvement in the corresponding GTCC was weakened for the higher class of the gas turbine because of the narrower load range of EGR action and the deterioration of the gas turbine performance. Furthermore, EGR-IGV-FFC was inferior to IGV-FFC in improving the performance at loads below 50% for the H-Class GTCC. The results obtained in this paper could help guide the application of EGR-IGV-FFC to enhance the part-load performance of various classes of GTCC systems. [ABSTRACT FROM AUTHOR]

The solvent has an important impact on liquefaction conversion from biomass to efficiently obtain fuels and chemicals. In this paper, the catalytic liquefaction of woody biomass was studied using fir sawdust as raw material and concentrated sulfuric acid as catalyst in GVL/1-octanol mixed solvent with mechanical stirring and oil bath heating. The influence of GVL on liquefaction yield was discussed, and the liquefaction productions were characterized by some analysis methods to analyze the liquefaction mechanism. The results show that adding GVL benefits to improving liquefaction yield and generating high value-added monophenol because of the enhancement of the surface wettability of biomass and the inhibition of polymerization of mononuclear aromatics with other degradation products. The maximum liquefaction yield of 76.07% was obtained under the suitable conditions of fir sawdust 10 g, temperature 150 ℃, reaction time 60 min, mass ratio of sawdust/solvent 1:6, catalyst concentration 0.6 mol·L−1, and mass ratio of GVL/1-octanol 4:6. The mechanism study reveals that aromatics originated by lignin degradation as well as small molecule ketones from cellulose and hemicellulose degradation. GVL/1-octanol as an eco-friendly solvent system exhibits a promising prospect of application in woody biomass conversion. [ABSTRACT FROM AUTHOR]

In tunnel construction, hazardous water structures pose significant risks. The transient electromagnetic method (TEM) is widely used for advanced geological prediction due to its sensitivity to conductive targets. Currently, loop sources are generally used to detect these structures, but the space in the tunnel limits the magnetic moment and detection distance. This article proposes using an electric wire source TEM configuration on the tunnel sidewall for lateral exploration. The feasibility of this configuration is preliminarily analyzed using 3D numerical simulations based on tensor grids. The simulations include the six electromagnetic components under the axial electric source and the effects of offset, tunnel spatial conductivity, and tunnel size on the response. The results show that the inline electric field component and the vertical-induced electromotive force component are more sensitive to the target body in this configuration. We also found that when there is a small difference in resistivity between the target body and the surrounding rock, the sensitivity of the induced electromotive force z-component to the abnormal body will be reduced. When the distance between the source and the receiver is large, the broadside-induced electromotive force component can also be used to identify anomalous body electrical properties. Moreover, the conductivity and size of the tunnel have a certain impact on the detection results. In the next research, it is necessary to select more suitable model parameters for numerical simulations based on the actual conditions. [ABSTRACT FROM AUTHOR]

This paper presents the energy and exergy analysis of the gas turbine combined cycle during part-load operation under the exhaust gas recirculation - inlet/variable guide vane control (EGR-IGVC) strategy. The exergy destruction across each component and the energy and exergy efficiency of the topping, bottoming, and combined cycle are determined. Results show that EGR-IGVC and IGVC both effectively enhance the part-load efficiency of the combined cycle compared to fuel flow control (FFC) because higher turbine exhaust temperature allows more exergy to enter the bottoming cycle and increases bottoming cycle power output. However, EGR-IGVC decreases the bottoming cycle energy and exergy efficiency compared with IGVC. Even so, EGR-IGVC increases the topping cycle energy and exergy efficiency and can obtain a higher bottoming cycle power output. The combined cycle efficiency is enhanced by 0.97–1.21 percentage points over IGVC at 40 %–90 % loads. Exergy analysis has important guiding significance for further improving the part-load performance of the combined cycle. [ABSTRACT FROM AUTHOR]

With the orderly advancement of China Energy Development Strategic Action Plan, clean energy has become a major trend in the energy market. As a major industry of clean energy, natural gas industry plans to consume at least 10% of the total primary energy by 2020. The energy structure will be improved in an orderly manner to achieve the goal of energy conservation, consumption reduction, and emission reduction. To achieve energy saving and emission reduction, and using clean energy effectively, accurate prediction of natural gas consumption is of great importance. Because of the many influencing factors affecting natural gas demand, this paper first utilizes STRIPAT to analyze the factors affecting natural gas consumption and then uses a deep learning ensemble approach to analyze and predict China's natural gas consumption. One is an advanced deep neural network model named gated recurrent unit model which is used to model the nonlinear and complex relationships of natural gas consumption with its factors. The other is a powerful ensemble method named bootstrap aggregation which generates multiple data sets for training a set of base models. Our approach combines the advantages of these two technologies to forecast the demand for China's natural gas market. In empirical research, our method has been tested by some competitive methods and has shown superiority. [ABSTRACT FROM AUTHOR]

Depth completion aims to generate dense depth maps from sparse depth maps and corresponding RGB images. In this task, the locality based on the convolutional layer poses challenges for the network in obtaining global information. While the Transformer-based architecture performs well in capturing global information, it may lead to the loss of local detail features. Consequently, improving the simultaneous attention to global and local information is crucial for achieving effective depth completion. This paper proposes a novel and effective dual-encoder–three-decoder network, consisting of local and global branches. Specifically, the local branch uses a convolutional network, and the global branch utilizes a Transformer network to extract rich features. Meanwhile, the local branch is dominated by color image and the global branch is dominated by depth map to thoroughly integrate and utilize multimodal information. In addition, a gate fusion mechanism is used in the decoder stage to fuse local and global information, to achieving high-performance depth completion. This hybrid architecture is conducive to the effective fusion of local detail information and contextual information. Experimental results demonstrated the superiority of our method over other advanced methods on KITTI Depth Completion and NYU v2 datasets. [ABSTRACT FROM AUTHOR]