Dynamic Crack Propagating Mechanism of Rock Materials Based on Different Weighted Functions

The singularity at the crack tip can be smoothed by the non-local theory based on different types of weighted functions. In the paper, the characteristics of different types of the weighted functions and their effects on non-local model are analyzed. The effects of the stress intensity factor KI and KII on the all components of stress-strain field in the neighborhood of the crack tip are analyzed by different types of the weighted functions. It is shown that the larger intrinsic characteristic length scale is, the more significant the reduction of non-local strain with respect to the local strain predicted conventionally will be. The size of non-local strain field with the bell-shaped weighted functions is larger than that obtained by either Green's or Gaussian weighted functions. The non-local normal stress-strain components depends on the stress intensity factor KI and KII, the circumferential stress is related to the stress intensity factor KI. The effect of stress intensity factor KI on non-local radial stress is positive while the effect of KII is negative. The non-local circumferential stress is related only to the stress intensity factor KII while the non-local shear stress is related only to the stress intensity factor KI. The larger the intrinsic characteristic scale is, the more significant the reduction of non-local strain with respect to the local strain predicted conventionally will be

OsHAC1;1 and OsHAC1;2 function as arsenate reductases and regulate arsenic accumulation

Rice is a major dietary source of the toxic metalloid arsenic (As). Reducing its accumulation in rice (Oryza sativa) grain is of critical importance to food safety. Rice roots take up arsenate and arsenite depending on the prevailing soil conditions. The first step of arsenate detoxification is its reduction to arsenite, but the enzyme(s) catalyzing this reaction in rice remains unknown. Here, we identify OsHAC1;1 and OsHAC1;2 as arsenate reductases in rice. OsHAC1;1 and OsHAC1;2 are able to complement an Escherichia coli mutant lacking the endogenous arsenate reductase and to reduce arsenate to arsenite. OsHAC1:1 and OsHAC1;2 are predominantly expressed in roots, with OsHAC1;1 being abundant in the epidermis, root hairs, and pericycle cells while OsHAC1;2 is abundant in the epidermis, outer layers of cortex, and endodermis cells. Expression of the two genes was induced by arsenate exposure. Knocking out OsHAC1;1 or OsHAC1;2 decreased the reduction of arsenate to arsenite in roots, reducing arsenite efflux to the external medium. Loss of arsenite efflux was also associated with increased As accumulation in shoots. Greater effects were observed in a double mutant of the two genes. In contrast, overexpression of either OsHAC1;1 or OsHAC1;2 increased arsenite efflux, reduced As accumulation, and enhanced arsenate tolerance. When grown under aerobic soil conditions, overexpression of either OsHAC1;1 or OsHAC1;2 also decreased As accumulation in rice grain, whereas grain As increased in the knockout mutants. We conclude that OsHAC1;1 and OsHAC1;2 are arsenate reductases that play an important role in restricting As accumulation in rice shoots and grain

Selective Detection of Formaldehyde Gas Using a Cd-Doped TiO2-SnO2 Sensor

We report the microstructure and gas-sensing properties of a nonequilibrium TiO2-SnO2 solid solution prepared by the sol-gel method. In particular, we focus on the effect of Cd doping on the sensing behavior of the TiO2-SnO2 sensor. Of all volatile organic compound gases examined, the sensor with Cd doping exhibits exclusive selectivity as well as high sensitivity to formaldehyde, a main harmful indoor gas. The key gas-sensing quantities, maximum sensitivity, optimal working temperature, and response and recovery time, are found to meet the basic industrial needs. This makes the Cd-doped TiO2-SnO2 composite a promising sensor material for detecting the formaldehyde gas

LARGE ROOT ANGLE1, encoding OsPIN2, is involved in root system architecture in rice

Root system architecture is very important for plant growth and crop yield. It is essential for nutrient and water uptake, anchoring, and mechanical support. Root growth angle (RGA) is a vital constituent of root system architecture and is used as a parameter for variety evaluation in plant breeding. However, little is known about the underlying molecular mechanisms that determine root growth angle in rice (Oryza sativa). In this study, a rice mutant large root angle1 (lra1) was isolated and shown to exhibit a large RGA and reduced sensitivity to gravity. Genome resequencing and complementation assays identified OsPIN2 as the gene responsible for the mutant phenotypes. OsPIN2 was mainly expressed in roots and the base of shoots, and showed polar localization in the plasma membrane of root epidermal and cortex cells. OsPIN2 was shown to play an important role in mediating root gravitropic responses in rice and was essential for plants to produce normal RGAs. Taken together, our findings suggest that OsPIN2 plays an important role in root gravitropic responses and determining the root system architecture in rice by affecting polar auxin transport in the root tip

THE RESEARCH OF THE VARIATION LAWS OF SETTLEMENT AND INTERNAL FORCE OF PILE GROUPS OF RAI LWAY BRIDGE CAUSED BY PUMPING BRINE

Taking Yingzigou Bridge of Dezhou-Dajiawa railway as the engineering background, the three-dimensional fluid-solid coupling models of pile group caps were established on the basis of five-stage field monitoring data of the settlement and groundwater level drop by using FLAC3D software. On the basis of the field monitoring data checking, the variation of axial force and skin friction of piles at different positions under the condition of water level drop was simulated. The results show that with the underground water level dropped, the axial force of pile along the shaft increased first and then decreased. The cross section of maximum axial force moved down constantly. In the same ground water levels drop, the distance between the maximum axial force and neutral point of each pile and the top of the pile was corner pile > side pile> near borehole center pile > center pile. The size of the pile axial force and negative skin friction resistance was corner pile > side pile> near borehole center pile > center pile. The upper part of the pile was subjected to negative skin friction resistance. The skin friction resistance of each pile along the shaft increased first and then decreased. The lower part of the pile was subjected to positive skin friction resistance. The skin friction resistance of each pile along the shaft increased. The location of the maximum negative friction resistance was about 10m distance from the top of the pile. The maximum negative friction resistance of corner pile was -36.5kPa. The distance of neutral point of center pile from the top was 35.2m. The neutral point of each pile was in accordance with the position of the maximum axial force of the pile. A reliable basis was provided for high-speed railway survey and design and the prevention and control of land subsidence along the railway

OsPTF1, a Novel Transcription Factor Involved in Tolerance to Phosphate Starvation in Rice

We report here on a novel transcription factor with a basic helix-loop-helix domain for tolerance to inorganic phosphate (Pi) starvation in rice (Oryza sativa). The gene is designated OsPTF1. The expression of OsPTF1 is Pi starvation induced in roots while constitutively expressed in shoots, as shown by northern-blot analysis. Overexpression of OsPTF1 enhanced tolerance to Pi starvation in transgenic rice. Tillering ability, root and shoot biomass, and phosphorus content of transgenic rice plants were about 30% higher than those of the wild-type plants in Pi-deficient conditions in hydroponic experiments. In soil pot and field experiments, more than 20% increase in tiller number, panicle weight, and phosphorus content was observed in transgenic plants compared to wild-type plants at low-Pi levels. In Pi-deficient conditions, transgenic rice plants showed significantly higher total root length and root surface area, which results in a higher instantaneous Pi uptake rate over their wild-type counterparts. Microarray analysis for transgenic plants overexpressing OsPTF1 has been performed to investigate the downstream regulation of OsPTF1

A deep relearning method based on the recurrent neural network for land cover classification

Recent developments in deep learning (DL) techniques have provided a series of new methods for land cover classification. However, most DL-based methods do not consider the rich spatial association of land cover classes embedded in remote sensing images. In this research, a deep relearning method based on the recurrent neural network (DRRNN) is proposed for land cover classification. The relearning approach has great potential to improve classification, which has never been used in DL-based land cover classification. To utilize the spatial association of the pixels’ information classes, a class correlated feature (CCF) is first extracted in a local window from an initial classification result. This feature can reflect both the spatial autocorrelation and spatial arrangement of land cover classes. Since the recurrent neural network (RNN) is designed to process sequential data, the CCF is formed as a feature sequence, allowing RNN to model the dependency between class labels. The relearning process is then applied to iteratively classify remote sensing images based on the CCF and spectral-spatial feature. At each relearning iteration, the CCF is learned from the previous classification result until a stopping condition is satisfied. This method was tested on five remote sensing images with different sensors and diverse environments. It was observed that noise in the classification result can be filtered by considering spatial autocorrelation, and misclassified areas can be corrected by incorporating spatial arrangement in the relearning process. The classification results indicate that compared to other state-of-the-art DL methods, the proposed method consistently achieves the highest accuracy

Numerical Investigation on Effects of Assigned EGR Stratification on a Heavy Duty Diesel Engine with Two-Stage Fuel Injection

External exhaust gas recirculation (EGR) stratification in diesel engines contributes to reduction of toxic emissions. Weak EGR stratification lies in that strong turbulence and mixing between EGR and intake air by current introduction strategies of EGR. For understanding of ideal EGR stratification combustion, EGR was assigned radically at −30 °CA after top dead center (ATDC) to organize strong EGR stratification using computational fluid dynamics (CFD). The effects of assigned EGR stratification on diesel performance and emissions are discussed in this paper. Although nitric oxides (NOx) and soot emissions are both reduced by means of EGR stratification compared to uniform EGR, the trade-off between NOx and soot still exists under the condition of arranged EGR stratification with different fuel injection strategies. A deterioration of soot emissions was observed when the interval between main and post fuel injection increased, while NO emissions increased first then reduced. The case with a 4 °CA interval between main and post fuel injection is suitable for acceptable NO and soot emissions. Starting the main fuel injection too early and too late is not acceptable, which results in high NO emissions and high soot emissions respectively. The start of the main fuel injection −10 °CA ATDC is suitable