Stochastic Transfer Function Model and Neural Networks to Estimate Soil Moisture1

Abstract: A practical methodology is proposed to estimate the three‐dimensional variability of soil moisture based on a stochastic transfer function model, which is an approximation of the Richard’s equation. Satellite, radar and in situ observations are the major sources of information to develop a model that represents the dynamic water content in the soil. The soil‐moisture observations were collected from 17 stations located in Puerto Rico (PR), and a sequential quadratic programming algorithm was used to estimate the parameters of the transfer function (TF) at each station. Soil texture information, terrain elevation, vegetation index, surface temperature, and accumulated rainfall for every grid cell were input into a self‐organized artificial neural network to identify similarities on terrain spatial variability and to determine the TF that best resembles the properties of a particular grid point. Soil moisture observed at 20 cm depth, soil texture, and cumulative rainfall were also used to train a feedforward artificial neural network to estimate soil moisture at 5, 10, 50, and 100 cm depth. A validation procedure was implemented to measure the horizontal and vertical estimation accuracy of soil moisture. Validation results from spatial and temporal variation of volumetric water content (vwc) showed that the proposed algorithm estimated soil moisture with a root mean squared error (RMSE) of 2.31% vwc, and the vertical profile shows a RMSE of 2.50% vwc. The algorithm estimates soil moisture in an hourly basis at 1 km spatial resolution, and up to 1 m depth, and was successfully applied under PR climate conditions.     

Stabilization/solidification of ashes in clays used in the manufacturing of ceramic bricks.

This paper presents the results of the lixiviation of metals from different mixtures of fly and bottom ashes that have been stabilized and solidified in clays used in the manufacture of bricks. The ashes used for this study were obtained from a Hoffmann-type brick furnace adapted for the incineration of municipal solid waste during the manufacturing of ceramic bricks. The ashes were stabilized in clay in different proportions of clay:ash mix (99:1, 95:5, 90:10, 80:20 and 60:40). Such mixes were used to manufacture bricks that were calcined at a temperature ranging from 50 to 1100 degrees C. The clay, ashes and manufactured bricks were characterized using X-ray diffraction, fluorescent X-ray, thermogravimetry, differential thermal analysis, atomic absorption spectroscopy and scanning electronic microscopy. In addition, toxicity characteristic leaching procedure lixiviation tests were performed according to the EPA 1311 method for the determination of heavy metals. The results showed an affinity between clay and ash, and also that the bricks manufactured with these mixtures present low lixiviation levels. The tests also showed the highest decrease in the concentration of arsenic, nickel, chromium, zinc and silver for 99:1 mixtures. The 95:5 mixture was found to be the most favourable for the stabilization (greater concentration decrease) of lead and cadmium. Selenium was the metal with the lowest concentration change whereas arsenic, nickel, chromium, zinc and cadmium showed the greatest concentration change in all mixtures, with the exception of cadmium in the mixture 99:1.     

从我国安全理念的变迁看民生关怀

从注重生产到注重安全,体现了国家对劳动者的尊重,以人为本的具体表现.也体现我们这个社会从粗放型到人文关怀的转变.     

On-Scene Injury Severity Prediction (OSISP) Algorithm for Truck Occupants

Objective: The aim of this study is to develop an on-scene injury severity prediction (OSISP) algorithm for truck occupants using only accident characteristics that are feasible to assess at the scene of the accident. The purpose of developing this algorithm is to use it as a basis for a field triage tool used in traffic accidents involving trucks. In addition, the model can be valuable for recognizing important factors for improving triage protocols used in Sweden and possibly in other countries with similar traffic environments and prehospital procedures.

Methods: The scope is adult truck occupants involved in traffic accidents on Swedish public roads registered in the Swedish Traffic Accident Data Acquisition (STRADA) database for calendar years 2003 to 2013. STRADA contains information reported by the police and medical data on injured road users treated at emergency hospitals. Using data from STRADA, 2 OSISP multivariate logistic regression models for deriving the probability of severe injury (defined here as having an Injury Severity Score [ISS] > 15) were implemented for light and heavy trucks; that is, trucks with weight up to 3,500 kg and ??16,500 kg, respectively. A 10-fold cross-validation procedure was used to estimate the performance of the OSISP algorithm in terms of the area under the receiver operating characteristic curve (AUC).

Results: The rate of belt use was low, especially for heavy truck occupants. The OSISP models developed for light and heavy trucks achieved cross-validation AUC of 0.81 and 0.74, respectively. The AUC values obtained when the models were evaluated on all data without cross-validation were 0.87 for both light and heavy trucks. The difference in the AUC values with and without use of cross-validation indicates overfitting of the model, which may be a consequence of relatively small data sets. Belt use stands out as the most valuable predictor in both types of trucks; accident type and age are important predictors for light trucks.

Conclusions: The OSISP models achieve good discriminating capability for light truck occupants and a reasonable performance for heavy truck occupants. The prediction accuracy may be increased by acquiring more data. Belt use was the strongest predictor of severe injury for both light and heavy truck occupants. There is a need for behavior-based safety programs and/or other means to encourage truck occupants to always wear a seat belt.     

三维点云基础上排土场垮塌影响范围研究

高台阶排土场下游常分布有居民区、厂房等,一旦垮塌,后果严重,因此完善的防治与应急准备工作十分关键,而排土场垮塌影响范围的预测是这些工作的重要前提依据。为提升高台阶排土场垮塌影响范围的预测准确性,需要获取准确的地形边界基础数据。通过利用三维激光扫描仪对新建排土场及其下游地形精细扫描,对获取的三维点云数据去噪、拼接、建模等处理,生成精度更高的数字高程模型与三维实体模型。在此基础上,结合新建高台阶排土场地质勘查与设计资料,建立颗粒离散元数值模型,利用PFC3D计算高台阶排土场垮塌影响范围,并与经验公式法计算结果对比分析,结果表明排土场颗粒离散元数值模型精度符合要求,可快速、准确地计算影响范围,从而为相关部门提供科学决策依据。     

Managers as drivers of CSR in state-owned enterprises

Corporate social responsibility (CSR) is increasingly required not only of private sector companies, but also of state-owned enterprises (SOEs), whose main function is to provide services to society and not principally to obtain financial reward. The important role played by managers in implementing CSR has been demonstrated by prior research. The objective of this paper is to examine how managers of SOEs perceive the concept of CSR, the reasons for their involvement and how it is integrated into everyday business practices. In addition, we examine whether managers' attitudes towards CSR policies are influenced by their personal profiles and by the sector in which the SOEs work. We find that, although these managers are aware of the importance of the CSR principles underlying their activities and understand the meaning, scope and dimensions of CSR, there remains an evident need to enhance the application of CSR policies among the strategies of SOEs. The manager profile and the sector in which the SOEs work both have a strong influence on their behaviour regarding CSR issues.     

智能电能表功耗测量系统软件设计

智能电能表功耗测量是一项重要的试验项目,介绍了电能表功耗测量仪和连接,着重分析了功耗测量系统软件的设计。该软件用于功耗测量数据采集,分析了其中的关键技术,给出了Lab VIEW设计框图。该软件实现了智能电能表功耗数据的自动化测量。     

连续型空间故障树中因素重要度分布的定义与认知

为了解工作环境条件因素对系统故障概率的影响的特征,同时丰富连续型空间故障树(CSFT)的理论框架,提出因素重要度分布的概念。因素重要度分布从经典故障树的概率重要度发展而来,目的是研究系统所处环境因素变化导致系统可靠性变化的程度。给出元件和系统的因素重要度分布概念、公式及所需基础数据,并分析因素重要度分布的正负分布特点。使用该概念研究元件X1和系统T的因素t重要度分布和因素c重要度分布。结果表明:在不同环境中,对于因素t或c变化影响元件或系统的故障概率变化程度是不同的。因素重要度分布有效地表达了t和c对元件或系统的故障概率影响特征。     

吉林省面源污染特征及防治对策

本研究主要基于吉林省第一次污染源普查工作的实际,匡算出吉林省行政区域面源污染负荷,获取全省在区域范围内面源污染负荷总量、污染物类型等关键参数,分析在区域层面上面源污染物的分布特征,最终提出面源污染的防治对策。