Estimation of root zone soil moisture at point scale based on soil water measurements from cosmic-ray neutron sensing in a karst catchment

The cosmic-ray neutron sensing (CRNS) is an emerging method for continuously monitoring soil water content (SWC) at an intermediate scale. However, when multiple hydrologic units are present within its footprint, the potential application of CRNS in water resources management is restricted. Here we propose a new strategy to predict point-scale SWC in root zone established on CRNS-based soil moisture and improved relative difference method. A total of 768 days of soil moisture data were collected by CRNS at the intermediate scale and EC-TM sensors at the point scale in a karst catchment. The original and improved mean relative difference methods predicted point-scale SWCs within and without the effective measuring depth, respectively. The mean effective measuring depth was 13.16 cm, ranging from 10.13 to 19.23 cm. Both land use type and soil structure played essential roles in regulating point scale SWC in the soil profile. Point-scale SWC in root zone can be predicted accurately (P < 0.001) based on SWC data derived from the CRNS system. The prediction accuracy of point scale SWC can be improved by increasing the averaging time of the soil moisture values. Our results demonstrated that the proposed strategy was reliable for CRNS to predict SWC beyond the effective measurement depth. This study provides a good perspective for effectively managing of water resources in areas with complex hydrological processes

Research on Collaborative Order Decision-Making Method for Symmetric Participants in Complex Shipbuilding Projects

More extensive enterprise cooperation is an effective means to increase the competitiveness of shipbuilding companies in the current distributed manufacturing environment. Most cross-enterprise collaborative processes for shipbuilding projects have been widely concerned. However, the symmetry and cooperativity among the order decision-making process is rarely involved. A key issue for decision makers is to balance the interests of each symmetric participant and realize the consistent decision-making for the order. Existing order decision-making methods in the shipbuilding industry are low efficiency. The aim of this paper is to provide an assistant decision-making method to support effective order decision-making and multi-party cooperation for the multi-wining negotiation objectives. To solve this problem, a collaborative order decision-making framework based on decision support system (DSS) and multi-agent system (MAS) theory is presented, simulating the collaborative order decision-making process, and bridging the order decision-making with production scheduling. Then, a multi-stage negotiation method is provided to solve the distributed and symmetric order decision-making problem, and an illustrative example is conducted to demonstrate the effectiveness and rationality of the methods. Finally, an application case using a prototype system will be reported as a result

Effect of Deep Vertical Rotary Tillage on Soil Properties and Sugarcane Biomass in Rainfed Dry-Land Regions of Southern China

Conventional tillage (CT) is the main agricultural practice for rainfed sugarcane production in China. However, subsoil compaction formed by long-term CT is harmful to soil properties and crop yield. Deep vertical rotary tillage (DVRT) is a novel tillage practice, which can alleviate subsoil compaction and create a more favorable soil environment for crop growth. This study aims to compare the effects of DVRT and CT practices on soil properties and sugarcane characteristics. The results showed that DVRT reduced soil bulk density and increased soil porosity to some extent in the 0&ndash;40 cm soil profile. Soil water storage of DVRT was relatively higher compared with CT due to the combined effects of soil water holding capacity and vegetation water consumption. There was significantly higher final aboveground biomass, underground biomass, and plant height from DVRT compared to CT (p &lt; 0.05), but there were no differences in final root length between tillage practices. Compared with CT, DVRT with one and two growth-years significantly increased aboveground biomass by 68.90% and 50.14%, respectively. Generally, the soil properties and sugarcane characteristics were not significantly different between DVRT with different growth years. DVRT is recommended as a tillage practice for sustainable agriculture in rainfed regions

Research on Collaborative Planning and Symmetric Scheduling for Parallel Shipbuilding Projects in the Open Distributed Manufacturing Environment

In the current distributed manufacturing environment, more extensive enterprise cooperation is an effective means for shipbuilding companies to increase the competitiveness. However, considering the project scale and the uneven production capacity between the collaborative enterprises, a key issue for shipbuilding companies is to effectively combine the product-oriented project tasks and the specialized production-oriented plants. Due to information privatization, the decision-making process of project planning and scheduling is distributed and symmetric. Existing project scheduling methods and collaboration mechanisms in the shipbuilding industry are somehow inefficient. The aim of the research is to provide an assistant decision-making method to support effective task dispatching and multi-party cooperation for better utilization of the distributed resources and to help project managers control the shipbuilding process. The article initially establishes an agent-based complex shipbuilding project collaborative planning and symmetric scheduling framework, simulating the distributed collaborative decision-making process and bridging the multi-project planning with the individual project scheduling in much detail, which fills the research gap. A negotiation method based on iterative combination auction (ICA) is further proposed to solve the integration problem of project planning and task scheduling, and an illustrative example is conducted to demonstrate the effectiveness and rationality of the methods. Finally, an application case using a prototype system on shipbuilding projects collaborative planning and scheduling will be reported as a result

Dense Temperature Mapping and Heat Wave Risk Analysis Based on Multisource Remote Sensing Data

As high temperature and heat wave have become great threats to human survival, social stability, and ecological safety, it is of great significance to master the spatial and temporal dynamic changes of temperature to prevent high temperature and heat wave risks. The meteorological station can provide accurate near-ground temperature, but only within a specific space and time. In order to meet the needs of large-scale research, spatial interpolation methods were widely used to obtain spatially continuous temperature maps. However, these methods often ignore the influence of external factors on temperature, such as land cover, height, etc., and neglect to supplement temporal-wise information. To deal with these issues, a joint spatio-temporal method is proposed to obtain dense temperature mapping from multisource remote sensing data, which combining a geographically weighted regression model and a polynomial fitting model. Besides, a heat wave risk model is also built based on the dense temperature maps and population data, in order to evaluate the heat wave risk of different areas. Accuracy evaluations and experiments have verified the effectiveness of the proposed methods. Case study on the four cities of Zhejiang Province, China have demonstrated that areas with higher degree of urbanization are often accompanied by higher heat wave risks, such as the northern part of the study area. The study also found that the heat wave risks have presented a centralized distribution and spatial autocorrelation characteristics in the study area

Azithromycin Synergistically Enhances Anti-Proliferative Activity of Vincristine in Cervical and Gastric Cancer Cells

cancer

Analysis of thermal-force coupling stress field under the temperature of alternating of molecular sieve adsorption tower

The thermal stress of molecular sieve adsorption tower under transient temperature of 40-290°C is the basis for ensuring the safe operation of the adsorption tower. In this paper, based on the transient thermodynamics theory, the finite element model of the full-size adsorption tower is established. The distribution of thermal stress at the key positions of the tower body is analyzed, and the strength of the maximum equivalent stress position is evaluated. The results show that the maximum residual stress is at the corner of the inner wall of the tower opening to take over the import and export, the maximum is 313.34MPa, and the effect force is gradually diffused along the takeover; The thermal stress on the inside and outside of the skirt is greater than the thermal stress on the inside and outside of the head. The corresponding stress linearization results of each assessment path were evaluated and passed. The strength design, life prediction and maintenance of adsorption tower in complex temperature cross-change conditions provide theoretical basis