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.     

Older Adults at Increased Risk as Pedestrians in Victoria,Australia: An Examination of Crash Characteristics and Injury Outcomes

Objectives: Engaging in active transport modes (especially walking) is a healthy and environmentally friendly alternative to driving and may be particularly beneficial for older adults. However, older adults are a vulnerable group: they are at higher risk of injury compared with younger adults, mainly due to frailty and may be at increased risk of collision due to the effects of age on sensory, cognitive, and motor abilities. Moreover, our population is aging, and there is a trend for the current cohort of older adults to maintain mobility later in life compared with previous cohorts. Though these trends have serious implications for transport policy and safety, little is known about the contributing factors and injury outcomes of pedestrian collision. Further, previous research generally considers the older population as a homogeneous group and rarely considers the increased risks associated with continued ageing.

Method: Collision characteristics and injury outcomes for 2 subgroups of older pedestrians (65–74 years and 75+ years) were examined by extracting data from the state police–reported crash dataset and hospital admission/emergency department presentation data over the 10-year period between 2003 and 2012. Variables identified for analysis included pedestrian characteristics (age, gender, activity, etc.), crash location and type, injury characteristics and severity, and duration of hospital stay. A spatial analysis of crash locations was also undertaken to identify collision clusters and the contribution of environmental features on collision and injury risk.

Results: Adults over 65 years were involved in 21% of all pedestrian collisions. A high fatality rate was found among older adults, particularly for those aged 75 years and older: this group had 3.2 deaths per 100,000 population, compared to a rate of 1.3 for 65- to 74-year-olds and 0.7 for adults below 65 years of age. Older pedestrian injuries were most likely to occur while crossing the carriageway; they were also more likely to be injured in parking lots, at driveway intersections, and on sidewalks compared to younger cohorts. Spatial analyses revealed older pedestrian crash clusters on arterial roads in urban shopping precincts. Significantly higher rates of hospital admissions were found for pedestrians over the age of 75 years and for abdominal, head, and neck injuries; conversely, older adults were underrepresented in emergency department presentations (mainly lower and upper extremity injuries), suggesting an increased severity associated with older pedestrian injuries. Average length of hospital stay also increased with increasing age.

Conclusion: This analysis revealed age differences in collision risk and injury outcomes among older adults and that aggregate analysis of older pedestrians can distort the significance of risk factors associated with older pedestrian injuries. These findings have implications that extend to the development of engineering, behavioral, and enforcement countermeasures to address the problems faced by the oldest pedestrians and reduce collision risk and improve injury outcomes.     

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.     

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.