Small differences in the sensitivity of stomatal conductance to light intensity on leaf surfaces may lead to large differences in total canopy transpiration (EC) with increasing canopy leaf area (L). Typically, the increase of L would more than compensate for the decrease of transpiration per unit of leaf area (EL), resulting in concurrent increase of EC. However, highly shade-intolerant species, such as Larix principis-rupprechtii Mayr., may be so sensitive to increased shading that such compensation is not complete. We hypothesized that in such a stand, windfall-induced spatial variation at a decameter scale would result in greatly reduced EL in patches of high L leading to lower EC than low competition patches of sparse canopy. We further hypothesized that quicker extraction of soil moisture in patches of lower competition will result in earlier onset of drought symptoms in these patches. Thus, patches of low L will transition from light to soil moisture as the factor dominating EL. This process should progressively homogenize EC in the stand even as the variation of soil moisture is increasing. We tested the hypotheses utilizing sap flux of nine trees, and associated environmental and stand variables. The results were consistent with only some of the expectations. Under non-limiting soil moisture, EL was very sensitive to the spatial variation of L, decreasing sharply with increasing L and associated decrease of mean light intensity on leaf surfaces. Thus, under the conditions of ample soil moisture maximum EC decreased with increasing patch-scale L. Annual EC and biomass production also decreased with L, albeit more weakly. Furthermore, variation of EC among patches decreased as average stand soil moisture declined between rain events. However, contrary to expectation, high L plots which transpired less showed a greater EL sensitivity to decreasing stand-scale soil moisture, suggesting a different mechanism than simple control by decreasing soil moisture. We offer potential explanations to the observed phenomenon. Our results demonstrate that spatial variation of L at decameter scale, even within relatively homogeneous, single-species, even-aged stands, can produce large variation of transpiration, soil moisture and biomass production and should be considered in 1-D soil-plant-atmosphere models.
Data representing driving behavior, as measured by various sensors installed in a vehicle, are collected as multi-dimensional sensor time-series data. These data often include redundant information, e.g., both the speed of wheels and the engine speed represent the velocity of the vehicle. Redundant information can be expected to complicate the data analysis, e.g., more factors need to be analyzed; even varying the levels of redundancy can influence the results of the analysis. We assume that the measured multi-dimensional sensor time-series data of driving behavior are generated from low-dimensional data shared by the many types of one-dimensional data of which multi-dimensional time-series data are composed. Meanwhile, sensor time-series data may be defective because of sensor failure. Therefore, another important function is to reduce the negative effect of defective data when extracting low-dimensional time-series data. This study proposes a defect-repairable feature extraction method based on a deep sparse autoencoder (DSAE) to extract low-dimensional time-series data. In the experiments, we show that DSAE provides high-performance latent feature extraction for driving behavior, even for defective sensor time-series data. In addition, we show that the negative effect of defects on the driving behavior segmentation task could be reduced using the latent features extracted by DSAE.
Substantial research has been conducted on the mechanisms responsible for the wellbore collapse in shale formations. For chemically active soft shale formations, pore pressure and stress change due to osmotic pressure and hydration swelling are usually recognized as the primary mechanisms, while for chemically inactive hard shale formation, wellbore instability is generally attributed to weak structural planes like bedding planes and microcracks. In this paper, experimental testing and analytical and numerical analyses are performed to reveal the dominant mechanism of the frequently encountered severe wellbore instability events in the middle-deep shale formation in the Bohai oil field of China. It is evidenced from the physical and chemical experimental testing that the middle-deep shale features both medium chemical activity and abundant bedding planes and microcracks, indicating that the middle-deep shale is in the transition process from chemically actively soft shale to the chemically inactive but laminated and fractured hard shale. Mechanical testing also shows considerable strength degradation of the middle-deep transition shale due to drilling fluid-shale interaction. Analysis through a hydro-chemo-mechanical coupling theory shows that the extent of the damage zone around the wellbore is limited if only pore pressure change and hydration swelling caused by the chemical difference between the drilling fluid and the formation fluid are considered, which cannot explain the severe wellbore collapse in the drilling process. In contrast, when pore pressure increase and strength degradation of the shale due to drilling fluid penetration along the bedding planes and microcracks are taken into account, a damage zone of 3~4 times of the wellbore diameter can be generated, implying that the dominant mechanism of the wellbore instability in the middle-deep transition shale formation should be the pore pressure change and strength degradation resulted from drilling fluid penetration along the bedding planes and microcracks.
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