Table1_New 2D roughness parameters with geometric and physical meanings for rock joints and their correlation with joint roughness coefficient.DOCX

Determining the joint roughness accurately will better serve the peak shear strength estimation models of rock joints used for stability assessment of rock masses. Considering the defects of the existing quantitative characterization parameters for two-dimensional (2D) joint roughness, especially the lack of explicit geometric and physical meaning, we proposed two new 2D roughness parameters, θ2D and h2D. The former, θ2D, represents the average inclination angle of all potential contact asperities over the entire joint profile, while the latter, h2D, characterizes their average undulation height. Both parameters are closely related to the shear strength of rock joints. Then, the roughness parameters θ2D and h2D of 102 rock joint profiles digitized at 0.5 mm sampling interval were calculated, and a new nonlinear regression equation for the determination of the 2D joint roughness coefficient (JRC) was established by combining the calculated results of the two roughness parameters. It was verified that the proposed equation could give accurate JRC estimation values of the 10 standard profiles of rock joints. Through the comparative analysis of the experimental data collected from earlier studies for the peak shear strength of 73 rock joint samples and corresponding estimated values, the equation was further verified to be applicable and accurate for estimating the JRC values of rock joints. Furthermore, we discussed the effects of shear direction and sampling interval on roughness and further provided another equation that could be applied to estimate the JRC values of joint profiles at the sampling interval of 1.0 mm.</p

Correlation coefficient of broadleaf tree volume and RS factors.

<p>Correlation coefficient of broadleaf tree volume and RS factors.</p

Cumulative probability distribution map.

<p>Cumulative probability distribution map.</p

Mimic diagram of three-dimensional laser scanning method for measuring the crown volume.

<p>Mimic diagram of three-dimensional laser scanning method for measuring the crown volume.</p

3D point cloud data.

<p>3D point cloud data.</p

Testing Results of Precision Ratio of TGB Based-on SPOT5 Image.

<p>Testing Results of Precision Ratio of TGB Based-on SPOT5 Image.</p

A Metal–Organic Tetrahedron as a Redox Vehicle to Encapsulate Organic Dyes for Photocatalytic Proton Reduction

The design of artificial systems that mimic highly evolved and finely tuned natural photosynthetic systems is a subject of intensive research. We report herein a new approach to constructing supramolecular systems for the photocatalytic generation of hydrogen from water by encapsulating an organic dye molecule into the pocket of a redox-active metal–organic polyhedron. The assembled neutral Co₄L₄ tetrahedron consists of four ligands and four cobalt ions that connect together in alternating fashion. The cobalt ions are coordinated by three thiosemicarbazone NS chelators and exhibit a redox potential suitable for electrochemical proton reduction. The close proximity between the redox site and the photosensitizer encapsulated in the pocket enables photoinduced electron transfer from the excited state of the photosensitizer to the cobalt-based catalytic sites via a powerful pseudo-intramolecular pathway. The modified supramolecular system exhibits TON values comparable to the highest values reported for related cobalt/fluorescein systems. Control experiments based on a smaller tetrahedral analogue of the vehicle with a filled pocket and a mononuclear compound resembling the cobalt corner of the tetrahedron suggest an enzymatic dynamics behavior. The new, well-elucidated reaction pathways and the increased molarity of the reaction within the confined space render these supramolecular systems superior to other relevant systems

Correlation coefficient of conifer volume and RS factors.

<p>Correlation coefficient of conifer volume and RS factors.</p

Factors loading rotation matrix of varimax.

<p>Note: B1, B2 are visible bands, where B1 can detect absorption and reflectance of plant green hormone, and B2 belongs to the red light zone capable of distinguishing the color of different types of vegetation from the color difference; Where B3 is near-infrared bands, which can reflect the sensitivity of plants to chlorophyll by the correlation between some acquired strong information and factors like leaf area index and biomass; SWIR (short-wave (length) infrared (band)); NDVI (Normalized Difference Vegetation Index); SAVI (Soil-Adjusted Vegetation Index); MSAVI (Modified Soil-Adjusted Vegetation Index).</p

Mimic diagram of measuring crown cross-sectional area.

<p>Mimic diagram of measuring crown cross-sectional area.</p