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Forest as a vital natural resource in China plays an irreplaceable important role in safeguarding ecological security and human survival and development. Due to the vast territory, huge population and widespread forest landscape of China, forest management is a complex system involving massive data and various management activities. To effectively implement sustainable forest management, the big data technology has been utilized to analyze China’s forestry resources. Thus, the purpose of this paper is to clarify the role of big data technology in China’s forest management.

In this paper, the authors revisited the roles of big data in forest ecosystem monitoring, forestry management system development, and forest policy implementation.

It demonstrates that big data technology has a great potential in forest ecosystem protection and management, as well as the government’s determination for forest ecosystem protection. However, to deepen the application of big data in forest management, several challenges still need to be tackled.

Thus, enhancing modern science and technology to improve big data, cloud computing, and information technologies and their combinations will contribute to tackle the challenges and achieve wisdom of forest management.

Vision, audition, olfactory, tactile and taste are five important senses that human uses to interact with the real world. As facing more and more complex environments, a sensing system is essential for intelligent robots with various types of sensors. To mimic human-like abilities, sensors similar to human perception capabilities are indispensable. However, most research only concentrated on analyzing literature on single-modal sensors and their robotics application.

This study presents a systematic review of five bioinspired senses, especially considering a brief introduction of multimodal sensing applications and predicting current trends and future directions of this field, which may have continuous enlightenments.

This review shows that bioinspired sensors can enable robots to better understand the environment, and multiple sensor combinations can support the robot’s ability to behave intelligently.

The review starts with a brief survey of the biological sensing mechanisms of the five senses, which are followed by their bioinspired electronic counterparts. Their applications in the robots are then reviewed as another emphasis, covering the main application scopes of localization and navigation, objection identification, dexterous manipulation, compliant interaction and so on. Finally, the trends, difficulties and challenges of this research were discussed to help guide future research on intelligent robot sensors.

The calculation of the shear capacity of inclined section for prestressed reinforced concrete beams is an important topic in the design of concrete members. The purpose of this paper, based on the truss-arch model, is to analyze the shear mechanism in prestressed reinforced concrete beams and establish the calculation formula for shear capacity.

Considering the effect of the prestressed reinforcement axial force on the angle of the diagonal struts and regression coefficient of softening cocalculation of shear capacity is established. According to the shape of the cracks of prestressed reinforced concrete beams under shear compression failure, the tie-arch model for the calculation of shear capacity is established. Shear-failure-test beam results are collected to verify the established formula for shear bearing capacity.

Through theoretical analysis and experimental beam verification, it is confirmed in this study that the truss-arch model can be used to analyze the shear mechanism of prestressed reinforced concrete members accurately. The calculation formula for the angle of the diagonal struts chosen by considering the effect of prestress is accurate. The relationship between the softening coefficient of concrete and strength of concrete that is established is correct. Considering the effect of the destruction of beam shear plasticity of the concrete on the surface crack shape, the tie-arch model, which is established where the arch axis is parabolic, is applicable.

The formula for shear capacity of prestressed reinforced concrete beams based on this theoretical model can guarantee the effectiveness of the calculation results when the structural properties vary significantly. Engineers can calculate the parameters of prestressed reinforced concrete beams by using the shear capacity calculation formula proposed in this paper.

During service period, the bridge structures will be affected by the environment and load, so the carrying capacity will decline. The purpose of this paper is to research on the bearing capacity of bridge structures with time.

Destructive test and non-linear finite element analysis are carried out by utilizing two pretensioning prestressed concrete hollow slabs in service for 20 years; using the structural test deflection value to simulate the stiffness degradation of the service bridge and the finite element calculation results verify the accuracy of the calculation.

The flexural rigidity of the main beam when the test beam is destructed is degraded to approximately 20 percent of that before the test, which agrees well with the result of finite element analysis and indicates that the method of deducing the flexural rigidity of the structure according to the measured deflection value can effectively simulate the rigidity degradation law of the bridge in service. The crack resistance property of the test beam degrades obviously and the ultimate bearing capacity of the bending resistance does not degrade obviously.

The research results truly reflect the destruction process, destructive form, bearing capacity and rigidity degradation law of the old beam of the concrete bridge in service for 20 years and can provide technical basis for optimization design of newly built bridges of the same type and maintenance and reinforcement design of existing old bridges.