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Planting vegetation is an environmentally friendly method for reducing landslides. Current vegetated slope analysis fails to consider the influence of different root architectures, and the accuracy and effectiveness of the numerical simulations need to be improved. In this study, an explicit smoothed particle finite element method (eSPFEM) was used to evaluate slope stability under the influence of vegetation roots. The Mohr–Coulomb constitutive model was extended by incorporating apparent root cohesion into the shear strength of the soil. The slope factors of safety (FOS) of four root architectures (uniform, triangular, parabolic, and exponential) for various planting distances, root depths, slope angles, and planting locations were calculated using the shear strength reduction technique with a kinetic energy-based criterion. The results indicated that the higher the planting density, the stronger the reinforcement effect of the roots on the slope. With increasing root depth, the FOS value first decreased and then increased. The FOS value decreased with an increase in slope angle. Planting on the entire ground surface had the best improvement effect on the slope stability, followed by planting vegetation with a uniform root architecture in the upper slope region or planting vegetation with triangular or exponential root architecture on the slope’s toe. Our findings are expected to deepen our understanding of the contributions of different root architectures to vegetated slope protection and guide the selection of vegetation species and planting locations.

With the acceleration of urban modernization, the improvement of productivity, and the advancement of science and technology, people have higher and higher requirements for the quality of life, and the production of ancient methods has been updated and iterated, and folk architectural heritage has not been paid attention to. After the 1990s, the ceramic industry was gradually replaced by tourism, and the mass production of factories replaced earth kiln workshops. The development of urbanization made modern buildings replace traditional architectural features, although the contradiction between "modern" and "traditional" was prominent. The 2020 Boshan Ceramics and Glass Art Biennale officially opened in Boshan Ancient Kiln Village, which was renovated on the basis of old street buildings. Taking Boshan Ancient Kiln Village as an example, in order to make the folk architectural heritage valued, this paper discusses the application of the steamed bread kiln in the urban development process from the historical development of the main kilns in Boshan, the structural characteristics of the building itself, the combination with the surrounding buildings and the sustainable development.

With the acceleration of urban modernization in China, many historical and cultural relics are facing new challenges. The protection of ancient architecture and culture has become a very important issue in the current urban construction process. The symposium on the research project of the Grand Canal Cultural Heritage Protection Regulations in 2022 was held in Liaocheng. As an important part of the canal culture, the Shanshan Guild Hall is an indispensable key link in the inheritance of the Grand Canal culture. The artistic style, many carving techniques and cultural connotations expressed by it have important historical, cultural and artistic research valued for us. Taking the traditional carving of the Shanshan Guild Hall as the starting point, this paper digs deep into the rich connotation brought by the culture of the Grand Canal from the aspects of carving type, decorative style and theme content, discusses the characteristics of traditional architectural decorative art, and inherits and develops it.

With the continuous advancement of industrialization and urbanization, the relationship between mankind and the ecological environment has become increasingly tense, and the ecological environment assessment has become a research hotspot in recent years. The article summarizes the research content and development process of ecological environment assessment, lists various mainstream assessment methods and introduces their application characteristics, and then divides the weight determination methods into subjective weighting, objective weighting and subjective and objective combination, and analyses their advantages and disadvantages; Meanwhile, the application of remote sensing technology in ecological environment assessment research is analyzed. Finally, the main problems of ecological environment assessment work are summarized and its future development direction is pointed out.

Efforts will be made to improve the innovative design capabilities of advanced manufacturing industries and strategic emerging industries. Major breakthroughs will be made in key technologies and system integration innovation capabilities in the fields of electronic information, high-end equipment, new energy, new materials, aerospace, rail transportation, energy conservation and environmental protection.

With the impact of global climate change on extreme weather and the rapid expansion of human activity range, the cryogenic freezing rain and snow disaster is becoming more frequent, bringing quite adverse effects on transportation, electric power and other industries, thus seriously affecting social and economic development and people’s daily life. Implementation of risk early warning is one of the most effective means to prevent the cryogenic freezing rain and snow disaster. This paper, taking Guizhou Province as an example, studies the early warning technology and method for the cryogenic freezing rain and snow disaster based on the demand for prevention of the cryogenic freezing rain and snow disaster, and considering meteorological factors, topography, social economy, power transportation and other factors. On this basis, the weight of risk factors is determined by subjective weighting method, the risk early warning model for the cryogenic freezing rain and snow disaster based on AHP is constructed, and the four-level risk early warning indexes are determined. Trial application is realized in Guizhou Province.

Buffers of critical chain method have been used in multi-tier supplier collaborative project for a time. But there is still no good way to connect these buffers with current task execution information to better balance the resource using with time using. A new project deviation identification method called buffered state front line (Buffered-SFL) synthesized both the advantage state front line and the critical chain buffer. Buffered-SFL method synthesized both the advantage state front line and the critical chain buffer. By adapting the state front line, resource using and buffer corrosion can be observed on a single graph. The situations of buffer using, scenario descriptions in Buffered-SFL applications and complete effecting scope analysis for project planning delay and rescheduling are discussed in detail. This method helps to reduce the negative effects in general deviation correcting methods and make better decisions according to the deviation analysis.

In the paper, based on the technology of remote sensing and geographic information system, and according to the Landsat TM images obtained the land use database and land surface temperature of Yancheng city in the year of 2000 and 2009. Five land use types were identified, namely: farmland, building site, forest and grassland, water, and beach wetland. And then analysis of the urban expansion model based on the Defense Meteorological satellite data. The results show that: (1) In the five kinds of land use types, the largest rate of land use change is beach wetland, which is -8.23, followed by water as -5.17, forest and grassland is 3.27, building site is 2.24, farmland is 0.69. (2) During the 2000-2009, the towns of Yancheng city continuous outward expansion. In the old town, the expansion model is similar to the concentric circles spread to the periphery, but in the new district, which mainly concentrated in the northeast and southeast, the expansion model is re-planning, development and construction. (3) The land use structure change, especially the changes of beach wetland have a largest influence on the land surface temperature of Yancheng city. Among them, the average land surface temperature has increased over 8 degrees. However, the farmland change due to the overall land surface temperature decreased. And the increase of building site, making the urban heat island effect has been enhanced, while the town where the land surface temperature increases in value added in 0 to 5 degrees. At the same time, the water changes, this due to the land surface temperature increases and the added value in the range of 5 to 8 degrees.

Manufacturing industries adapt ESI (Early Supplier Involvement) to provide new products in shorter time. High-levels collaboration between members of virtual enterprise has become essential for the most advanced competiveness. However, benefits of ESI do not offset difficulties inherent in managing project across organization. To address this need, a framework of Supplier involved Collaborative Project Management (SiCPM) for project lifecycle collaboration is proposed in this study. The details of scenario and models, system architecture for project lifecycle collaboration with supplier are also depicted. It's hoped that the proposed models and approaches will lay a frontier basis for further research and development of collaborative project management within virtual enterprise.

We propose a decentralized learning algorithm over a general social network. The algorithm leaves the training data distributed on the mobile devices while utilizing a peer to peer model aggregation method. The proposed algorithm allows agents with local data to learn a shared model explaining the global training data in a decentralized fashion. The proposed algorithm can be viewed as a Bayesian and peer-to-peer variant of federated learning in which each agent keeps a "posterior probability distribution" over a global model parameters. The agent update its "posterior" based on 1) the local training data and 2) the asynchronous communication and model aggregation with their 1-hop neighbors. This Bayesian formulation allows for a systematic treatment of model aggregation over any arbitrary connected graph. Furthermore, it provides strong analytic guarantees on converge in the realizable case as well as a closed form characterization of the rate of convergence. We also show that our methodology can be combined with efficient Bayesian inference techniques to train Bayesian neural networks in a decentralized manner. By empirical studies we show that our theoretical analysis can guide the design of network/social interactions and data partitioning to achieve convergence.