Chemical imaging techniques, based on a combination of microscopy and spectroscopy, are designed to analyse the composition and spatial distribution of heterogeneous chemical complexes within a sample. Over the last few decades, it has become an increasingly popular tool for characterizing trace elements, isotopic information and organic biomarkers (molecular biosignatures) found in fossils. Here, we introduce the analytical principle of each technique and the interpretation of the chemical signals, followed by a review of the main applications of these techniques in paleontology. We also demonstrate that each technique is associated with pros and cons, and the current limitations and obstacles associated with the use of each specific technique should be taken into account before being applied to fossil samples. Finally, we propose that, due to the rapid advances in the available technology and overall trends towards more multi-disciplinary studies in paleontology, chemical imaging techniques can be expected to have broader applications in paleontology in the near future.
Soil’s water-physical properties support essential soil water retention functions for driving water distribution and availability, which is vital for plant growth and biogeochemical cycling. However, the question concerning how tree compositions and their interactions with other abiotic factors modulate soil’s water-physical properties in disturbed forests remains poorly understood. Based on observational data from nine permanent forest sites (18,747 trees and 210 plots) in the northeast of China, where forests once undergone three different levels of anthropogenic logging disturbance, we evaluated how multiple biotic (i.e., tree diversity and functional trait composition) and abiotic (soil texture and soil organic carbon) factors influence water-physical properties (i.e., in terms of soil capillary water retention (WC) and soil saturated water retention (WS)) in temperate forests. We found that the impacts of logging disturbance on soil water-physical properties were associated with improved tree diversity, acquisitive functional traits, and SOC. These associated attributes were also positively related to WC and WS, while there was no significant effect from soil texture. Moreover, disturbance indirectly affected soil water-physical properties mainly by functional traits and SOC, as acquisitive functional traits significantly mediate the effect from disturbance on WC and SOC mediates the influence from disturbance on WS. Finally, our results emphasize the potential relationships of tree composition with SOC and soil water retention as compared with soil texture and hence suggest that plants can actively modulate their abiotic contexts after disturbance, which is meaningful for understanding forest health and resistance.
Machine tool is the basic manufacturing equipment in today's mechanical manufacturing industry. A considerable amount of energy and carbon emission are consumed in machining processes, the realization of sustainable manufacturing of machine tools have become an urgent problem to be solved in the field of industry and academia. Therefore, five types of machine tools were selected for the typical machining processes (turning, milling, planning, grinding and drilling). Then the model of the energy efficiency, carbon efficiency and green degree model were established in this paper which considers the theory and experiment with the resource, energy and emission modeling method. The head frame spindle and head frame box were selected to verify the feasibility and practicability of the proposed model, based on the orthogonal experiment case of the key machining process. In addition, the influence rules of machining parameters were explored and the energy efficiency and green degree of the machine tools were compared. Finally, the corresponding strategies for energy conservation and emission reduction were proposed.
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