Search results for: soil texture prediction
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5502

Search results for: soil texture prediction

3072 Prediction of Time to Crack Reinforced Concrete by Chloride Induced Corrosion

Authors: Anuruddha Jayasuriya, Thanakorn Pheeraphan

Abstract:

In this paper, a review of different mathematical models which can be used as prediction tools to assess the time to crack reinforced concrete (RC) due to corrosion is investigated. This investigation leads to an experimental study to validate a selected prediction model. Most of these mathematical models depend upon the mechanical behaviors, chemical behaviors, electrochemical behaviors or geometric aspects of the RC members during a corrosion process. The experimental program is designed to verify the accuracy of a well-selected mathematical model from a rigorous literature study. Fundamentally, the experimental program exemplifies both one-dimensional chloride diffusion using RC squared slab elements of 500 mm by 500 mm and two-dimensional chloride diffusion using RC squared column elements of 225 mm by 225 mm by 500 mm. Each set consists of three water-to-cement ratios (w/c); 0.4, 0.5, 0.6 and two cover depths; 25 mm and 50 mm. 12 mm bars are used for column elements and 16 mm bars are used for slab elements. All the samples are subjected to accelerated chloride corrosion in a chloride bath of 5% (w/w) sodium chloride (NaCl) solution. Based on a pre-screening of different models, it is clear that the well-selected mathematical model had included mechanical properties, chemical and electrochemical properties, nature of corrosion whether it is accelerated or natural, and the amount of porous area that rust products can accommodate before exerting expansive pressure on the surrounding concrete. The experimental results have shown that the selected model for both one-dimensional and two-dimensional chloride diffusion had ±20% and ±10% respective accuracies compared to the experimental output. The half-cell potential readings are also used to see the corrosion probability, and experimental results have shown that the mass loss is proportional to the negative half-cell potential readings that are obtained. Additionally, a statistical analysis is carried out in order to determine the most influential factor that affects the time to corrode the reinforcement in the concrete due to chloride diffusion. The factors considered for this analysis are w/c, bar diameter, and cover depth. The analysis is accomplished by using Minitab statistical software, and it showed that cover depth is the significant effect on the time to crack the concrete from chloride induced corrosion than other factors considered. Thus, the time predictions can be illustrated through the selected mathematical model as it covers a wide range of factors affecting the corrosion process, and it can be used to predetermine the durability concern of RC structures that are vulnerable to chloride exposure. And eventually, it is further concluded that cover thickness plays a vital role in durability in terms of chloride diffusion.

Keywords: accelerated corrosion, chloride diffusion, corrosion cracks, passivation layer, reinforcement corrosion

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3071 Author Profiling: Prediction of Learners’ Gender on a MOOC Platform Based on Learners’ Comments

Authors: Tahani Aljohani, Jialin Yu, Alexandra. I. Cristea

Abstract:

The more an educational system knows about a learner, the more personalised interaction it can provide, which leads to better learning. However, asking a learner directly is potentially disruptive, and often ignored by learners. Especially in the booming realm of MOOC Massive Online Learning platforms, only a very low percentage of users disclose demographic information about themselves. Thus, in this paper, we aim to predict learners’ demographic characteristics, by proposing an approach using linguistically motivated Deep Learning Architectures for Learner Profiling, particularly targeting gender prediction on a FutureLearn MOOC platform. Additionally, we tackle here the difficult problem of predicting the gender of learners based on their comments only – which are often available across MOOCs. The most common current approaches to text classification use the Long Short-Term Memory (LSTM) model, considering sentences as sequences. However, human language also has structures. In this research, rather than considering sentences as plain sequences, we hypothesise that higher semantic - and syntactic level sentence processing based on linguistics will render a richer representation. We thus evaluate, the traditional LSTM versus other bleeding edge models, which take into account syntactic structure, such as tree-structured LSTM, Stack-augmented Parser-Interpreter Neural Network (SPINN) and the Structure-Aware Tag Augmented model (SATA). Additionally, we explore using different word-level encoding functions. We have implemented these methods on Our MOOC dataset, which is the most performant one comparing with a public dataset on sentiment analysis that is further used as a cross-examining for the models' results.

Keywords: deep learning, data mining, gender predication, MOOCs

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3070 Improving the Performance of Deep Learning in Facial Emotion Recognition with Image Sharpening

Authors: Ksheeraj Sai Vepuri, Nada Attar

Abstract:

We as humans use words with accompanying visual and facial cues to communicate effectively. Classifying facial emotion using computer vision methodologies has been an active research area in the computer vision field. In this paper, we propose a simple method for facial expression recognition that enhances accuracy. We tested our method on the FER-2013 dataset that contains static images. Instead of using Histogram equalization to preprocess the dataset, we used Unsharp Mask to emphasize texture and details and sharpened the edges. We also used ImageDataGenerator from Keras library for data augmentation. Then we used Convolutional Neural Networks (CNN) model to classify the images into 7 different facial expressions, yielding an accuracy of 69.46% on the test set. Our results show that using image preprocessing such as the sharpening technique for a CNN model can improve the performance, even when the CNN model is relatively simple.

Keywords: facial expression recognittion, image preprocessing, deep learning, CNN

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3069 Stubble and Senesced Leaves Are the Primary Sites of Ice Nucleation Activity in Wheat

Authors: Amanuel Bekuma, Rebecca Swift, Sarah Jackson, Ben Biddulph

Abstract:

Economic loss to frost damage is increasing over the past years in the Western Australian Wheatbelt. Agronomic, genetic, and climatic works have still found a weak correlation between temperature and frost damage. One possibility that has not been explored within the Australian cropping system is whether ice nucleation active bacteria (INB) either present in situ on crop residue or introduced by rainfall could be responsible for the increased sensitivity of cereal plants to frost at different stages of development. This study investigated upper and lower leaf canopy, stubble, and soil as a potential site of ice nucleation activity (INA) and tracked the changes in INA during the plant development. We found that older leaves of wheat are the primary sites of ice nucleation (-4.7 to -6.3°C) followed by stubble (-5.7 to -6.7°C) which increases the risk of frost damage during heading and flowering (the most susceptible stages). However, healthy and green upper canopy leaves (flag and flag-2) and the soil have lower INA (< -11°C) during the frost-sensitive stage of wheat. We anticipate the higher INA on the stubble and older leaves to be due to the presence of biologically active ice-nucleating bacteria (INB), known to cause frost injury to sensitive plants at -5°C. Stubble retained or applied during the growing season further exacerbates additional frost risk by potentially increasing the INB load. The implications of the result for stubble and frost risk management in a frost-prone landscape will be discussed.

Keywords: frost, ice-nucleation-activity, stubble, wheat

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3068 Effect of Mercerization on Coconut Fiber Surface Condition

Authors: Sphiwe Simelane, Daniel Madyira

Abstract:

The use of natural fibers requires that they should be treated in preparation for their use in Natural Fiber-reinforced polymer composites. This paper reports on the effects of sodium hydroxide (NaOH) treatment on the surface of coconut fibers. The fibers were subjected to 5%, 10%, 15% and 20% NaOH concentrations and soaked for 4 hours and thoroughly rinsed and allowed to dry in the open air for seven days, after which time they were dried in an oven for 30 minutes. Untreated and treated coconut fibers were observed under the Scanning Electron Microscope and it was noted that the surface structure of the fibers was modified differently by the different NaOH concentrations, and the resultant colour of the treated fibers got darker as the solution concentration increased, and the texture felt rougher to the touch as a result of the erosion of the fiber surface. Further, the increase in alkali concentration striped the surface of more constituents, thus exposing “pits” and other surface components rendering the surface rough.

Keywords: coconut fiber, scanning electron microscope, sodium hydroxide, surface treatment

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3067 FT-NIR Method to Determine Moisture in Gluten Free Rice-Based Pasta during Drying

Authors: Navneet Singh Deora, Aastha Deswal, H. N. Mishra

Abstract:

Pasta is one of the most widely consumed food products around the world. Rapid determination of the moisture content in pasta will assist food processors to provide online quality control of pasta during large scale production. Rapid Fourier transform near-infrared method (FT-NIR) was developed for determining moisture content in pasta. A calibration set of 150 samples, a validation set of 30 samples and a prediction set of 25 samples of pasta were used. The diffuse reflection spectra of different types of pastas were measured by FT-NIR analyzer in the 4,000-12,000 cm-1 spectral range. Calibration and validation sets were designed for the conception and evaluation of the method adequacy in the range of moisture content 10 to 15 percent (w.b) of the pasta. The prediction models based on partial least squares (PLS) regression, were developed in the near-infrared. Conventional criteria such as the R2, the root mean square errors of cross validation (RMSECV), root mean square errors of estimation (RMSEE) as well as the number of PLS factors were considered for the selection of three pre-processing (vector normalization, minimum-maximum normalization and multiplicative scatter correction) methods. Spectra of pasta sample were treated with different mathematic pre-treatments before being used to build models between the spectral information and moisture content. The moisture content in pasta predicted by FT-NIR methods had very good correlation with their values determined via traditional methods (R2 = 0.983), which clearly indicated that FT-NIR methods could be used as an effective tool for rapid determination of moisture content in pasta. The best calibration model was developed with min-max normalization (MMN) spectral pre-processing (R2 = 0.9775). The MMN pre-processing method was found most suitable and the maximum coefficient of determination (R2) value of 0.9875 was obtained for the calibration model developed.

Keywords: FT-NIR, pasta, moisture determination, food engineering

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3066 Potential of Hyperion (EO-1) Hyperspectral Remote Sensing for Detection and Mapping Mine-Iron Oxide Pollution

Authors: Abderrazak Bannari

Abstract:

Acid Mine Drainage (AMD) from mine wastes and contaminations of soils and water with metals are considered as a major environmental problem in mining areas. It is produced by interactions of water, air, and sulphidic mine wastes. This environment problem results from a series of chemical and biochemical oxidation reactions of sulfide minerals e.g. pyrite and pyrrhotite. These reactions lead to acidity as well as the dissolution of toxic and heavy metals (Fe, Mn, Cu, etc.) from tailings waste rock piles, and open pits. Soil and aquatic ecosystems could be contaminated and, consequently, human health and wildlife will be affected. Furthermore, secondary minerals, typically formed during weathering of mine waste storage areas when the concentration of soluble constituents exceeds the corresponding solubility product, are also important. The most common secondary mineral compositions are hydrous iron oxide (goethite, etc.) and hydrated iron sulfate (jarosite, etc.). The objectives of this study focus on the detection and mapping of MIOP in the soil using Hyperion EO-1 (Earth Observing - 1) hyperspectral data and constrained linear spectral mixture analysis (CLSMA) algorithm. The abandoned Kettara mine, located approximately 35 km northwest of Marrakech city (Morocco) was chosen as study area. During 44 years (from 1938 to 1981) this mine was exploited for iron oxide and iron sulphide minerals. Previous studies have shown that Kettara surrounding soils are contaminated by heavy metals (Fe, Cu, etc.) as well as by secondary minerals. To achieve our objectives, several soil samples representing different MIOP classes have been resampled and located using accurate GPS ( ≤ ± 30 cm). Then, endmembers spectra were acquired over each sample using an Analytical Spectral Device (ASD) covering the spectral domain from 350 to 2500 nm. Considering each soil sample separately, the average of forty spectra was resampled and convolved using Gaussian response profiles to match the bandwidths and the band centers of the Hyperion sensor. Moreover, the MIOP content in each sample was estimated by geochemical analyses in the laboratory, and a ground truth map was generated using simple Kriging in GIS environment for validation purposes. The acquired and used Hyperion data were corrected for a spatial shift between the VNIR and SWIR detectors, striping, dead column, noise, and gain and offset errors. Then, atmospherically corrected using the MODTRAN 4.2 radiative transfer code, and transformed to surface reflectance, corrected for sensor smile (1-3 nm shift in VNIR and SWIR), and post-processed to remove residual errors. Finally, geometric distortions and relief displacement effects were corrected using a digital elevation model. The MIOP fraction map was extracted using CLSMA considering the entire spectral range (427-2355 nm), and validated by reference to the ground truth map generated by Kriging. The obtained results show the promising potential of the proposed methodology for the detection and mapping of mine iron oxide pollution in the soil.

Keywords: hyperion eo-1, hyperspectral, mine iron oxide pollution, environmental impact, unmixing

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3065 Finite Element Analysis of Raft Foundation on Various Soil Types under Earthquake Loading

Authors: Qassun S. Mohammed Shafiqu, Murtadha A. Abdulrasool

Abstract:

The design of shallow foundations to withstand different dynamic loads has given considerable attention in recent years. Dynamic loads may be due to the earthquakes, pile driving, blasting, water waves, and machine vibrations. But, predicting the behavior of shallow foundations during earthquakes remains a difficult task for geotechnical engineers. A database for dynamic and static parameters for different soils in seismic active zones in Iraq is prepared which has been collected from geophysical and geotechnical investigation works. Then, analysis of a typical 3-D soil-raft foundation system under earthquake loading is carried out using the database. And a parametric study has been carried out taking into consideration the influence of some parameters on the dynamic behavior of the raft foundation, such as raft stiffness, damping ratio as well as the influence of the earthquake acceleration-time records. The results of the parametric study show that the settlement caused by the earthquake can be decreased by about 72% with increasing the thickness from 0.5 m to 1.5 m. But, it has been noticed that reduction in the maximum bending moment by about 82% was predicted by decreasing the raft thickness from 1.5 m to 0.5 m in all sites model. Also, it has been observed that the maximum lateral displacement, the maximum vertical settlement and the maximum bending moment for damping ratio 0% is about 14%, 20%, and 18% higher than that for damping ratio 7.5%, respectively for all sites model.

Keywords: shallow foundation, seismic behavior, raft thickness, damping ratio

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3064 Microbial Fuel Cells: Performance and Applications

Authors: Andrea Pietrelli, Vincenzo Ferrara, Bruno Allard, Francois Buret, Irene Bavasso, Nicola Lovecchio, Francesca Costantini, Firas Khaled

Abstract:

This paper aims to show some applications of microbial fuel cells (MFCs), an energy harvesting technique, as clean power source to supply low power device for application like wireless sensor network (WSN) for environmental monitoring. Furthermore, MFC can be used directly as biosensor to analyse parameters like pH and temperature or arranged in form of cluster devices in order to use as small power plant. An MFC is a bioreactor that converts energy stored in chemical bonds of organic matter into electrical energy, through a series of reactions catalysed by microorganisms. We have developed a lab-scale terrestrial microbial fuel cell (TMFC), based on soil that acts as source of bacteria and flow of nutrient and a lab-scale waste water microbial fuel cell (WWMFC), where waste water acts as flow of nutrient and bacteria. We performed large series of tests to exploit the capability as biosensor. The pH value has strong influence on the open circuit voltage (OCV) delivered from TMFCs. We analyzed three condition: test A and B were filled with same soil but changing pH from 6 to 6.63, test C was prepared using a different soil with a pH value of 6.3. Experimental results clearly show how with higher pH value a higher OCV was produced; indeed reactors are influenced by different values of pH which increases the voltage in case of a higher pH value until the best pH value of 7 is achieved. The influence of pH on OCV of lab-scales WWMFC was analyzed at pH value of 6.5, 7, 7.2, 7.5 and 8. WWMFCs are influenced from temperature more than TMFCs. We tested the power performance of WWMFCs considering four imposed values of ambient temperature. Results show how power performance increase proportionally with higher temperature values, doubling the output power from 20° to 40°. The best value of power produced from our lab-scale TMFC was equal to 310 μW using peaty soil, at 1KΩ, corresponding to a current of 0.5 mA. A TMFC can supply proper energy to low power devices of a WSN by means of the design of three stages scheme of an energy management system, which adapts voltage level of TMFC to those required by a WSN node, as 3.3V. Using a commercial DC/DC boost converter, that needs an input voltage of 700 mV, the current source of 0.5 mA, charges a capacitor of 6.8 mF until it will have accumulated an amount of charge equal to 700 mV in a time of 10 s. The output stage includes an output switch that close the circuit after a time of 10s + 1.5ms because the converter can boost the voltage from 0.7V to 3.3V in 1.5 ms. Furthermore, we tested in form of clusters connected in series up to 20 WWMFCs, we have obtained a high voltage value as output, around 10V, but low current value. MFC can be considered a suitable clean energy source to be used to supply low power devices as a WSN node or to be used directly as biosensor.

Keywords: energy harvesting, low power electronics, microbial fuel cell, terrestrial microbial fuel cell, waste-water microbial fuel cell, wireless sensor network

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3063 Physiological Insight into an Age Old Biocontrol Practice in Banana Cultivation

Authors: Susmita Goswami, Joyeeta Mitra, Indu Gaur, Neha Bhadauria, Shilpi Shilpi, Prabir K. Paul

Abstract:

'Malbhog’, an indigenous banana variety, much prized for its flavour and delicacy suffers production losses due to Fusarium oxysporum f.sp. cubense. The pathogen enters young plants through feeder roots causing wilting of plants ultimately leading to death of plants. The pathogen spreads rapidly to other plants in the field. In eastern part of India, this variety escapes the onslaught of the pathogen when either co-cultivated or rotated with Amorphophallus campanulatus (yam). The present study provides an insight into the physiological aspect of the biocontrol by yam. In vitro application of sterile aqueous extract of yam tuber (100gm/100ml distilled water and its 1:10 and 1:100 dilutions) were mixed with PDA media which was substantially inoculated with spores of Fusarium oxysporum f.sp. cubense. The extract could significantly reduce germination of pathogen spores. Banana variety susceptible to Fusarium sp was raised in soil rite under aseptic conditions. Spores of the pathogen (106 spores/ml) were inoculated into the soil rite. The plants were spread with aqueous extract of yam. The control plants were treated with sterilized distilled water. The activity of phenylalanine ammonia lyase (PAL), polyphenol oxidase (PPO) and peroxidase (POX) were estimated in leaves and roots at interval of 24 hours for 5 days after treatment. The incidence of wilt disease was recorded after two weeks. The results demonstrated that yam extract could induce significant activity of PAL, PPO and POX along with accumulation of phenols in both roots and leaves of banana plants. However, significantly high activity of enzymes and phenol accumulation was observed in roots. The disease incidence was significantly low in yam treated plants. The results clearly demonstrated the control of the pathogen due to induction of defense mechanism in the host by the extract. The observed control of the pathogen in the field could possibly be due to induction of such defense responses in host by exudates leached into the soil from yam tubers. Yam extract could be a potential source of environment-friendly biocide against Panama wilt of banana.

Keywords: Amorphophallus campanulatus, banana, Fusarium oxysporum f.sp. cubense, phenylalanine ammonia lyase (PAL), polyphenol oxidase (PPO), peroxidase (POX)

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3062 Predicting Growth of Eucalyptus Marginata in a Mediterranean Climate Using an Individual-Based Modelling Approach

Authors: S.K. Bhandari, E. Veneklaas, L. McCaw, R. Mazanec, K. Whitford, M. Renton

Abstract:

Eucalyptus marginata, E. diversicolor and Corymbia calophylla form widespread forests in south-west Western Australia (SWWA). These forests have economic and ecological importance, and therefore, tree growth and sustainable management are of high priority. This paper aimed to analyse and model the growth of these species at both stand and individual levels, but this presentation will focus on predicting the growth of E. Marginata at the individual tree level. More specifically, the study wanted to investigate how well individual E. marginata tree growth could be predicted by considering the diameter and height of the tree at the start of the growth period, and whether this prediction could be improved by also accounting for the competition from neighbouring trees in different ways. The study also wanted to investigate how many neighbouring trees or what neighbourhood distance needed to be considered when accounting for competition. To achieve this aim, the Pearson correlation coefficient was examined among competition indices (CIs), between CIs and dbh growth, and selected the competition index that can best predict the diameter growth of individual trees of E. marginata forest managed under different thinning regimes at Inglehope in SWWA. Furthermore, individual tree growth models were developed using simple linear regression, multiple linear regression, and linear mixed effect modelling approaches. Individual tree growth models were developed for thinned and unthinned stand separately. The developed models were validated using two approaches. In the first approach, models were validated using a subset of data that was not used in model fitting. In the second approach, the model of the one growth period was validated with the data of another growth period. Tree size (diameter and height) was a significant predictor of growth. This prediction was improved when the competition was included in the model. The fit statistic (coefficient of determination) of the model ranged from 0.31 to 0.68. The model with spatial competition indices validated as being more accurate than with non-spatial indices. The model prediction can be optimized if 10 to 15 competitors (by number) or competitors within ~10 m (by distance) from the base of the subject tree are included in the model, which can reduce the time and cost of collecting the information about the competitors. As competition from neighbours was a significant predictor with a negative effect on growth, it is recommended including neighbourhood competition when predicting growth and considering thinning treatments to minimize the effect of competition on growth. These model approaches are likely to be useful tools for the conservations and sustainable management of forests of E. marginata in SWWA. As a next step in optimizing the number and distance of competitors, further studies in larger size plots and with a larger number of plots than those used in the present study are recommended.

Keywords: competition, growth, model, thinning

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3061 Studies on Irrigation and Nutrient Interactions in Sweet Orange (Citrus sinensis Osbeck)

Authors: S. M. Jogdand, D. D. Jagtap, N. R. Dalal

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Sweet orange (Citrus sinensis Osbeck) is one of the most important commercially cultivated fruit crop in India. It stands on second position amongst citrus group after mandarin. Irrigation and fertigation are vital importance of sweet orange orchard and considered to be the most critical cultural operations. The soil acts as the reservoir of water and applied nutrients, the interaction between irrigation and fertigation leads to the ultimate quality and production of fruits. The increasing cost of fertilizers and scarcity of irrigation water forced the farmers for optimum use of irrigation and nutrients. The experiment was conducted with object to find out irrigation and nutrient interaction in sweet orange to optimize the use of both the factors. The experiment was conducted in medium to deep soil. The irrigation level I3,drip irrigation at 90% ER (effective rainfall) and fertigation level F3 80% RDF (recommended dose of fertilizer) recorded significantly maximum plant height, plant spread, canopy volume, number of fruits, weight of fruit, fruit yield kg/plant and t/ha followed by F2 , fertigation with 70% RDF. The interaction effect of irrigation and fertigation on growth was also significant and the maximum plant height, E-W spread, N-S spread, canopy volume, highest number of fruits, weight of fruit and yield kg/plant and t/ha was recorded in T9 i.e. I3F3 drip irrigation at 90% ER and fertigation with 80% of RDF followed by I3F2 drip irrigation at 90% ER and fertigation with 70% of RDF.

Keywords: sweet orange, fertigation, irrigation, interactions

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3060 Real-Time Radar Tracking Based on Nonlinear Kalman Filter

Authors: Milca F. Coelho, K. Bousson, Kawser Ahmed

Abstract:

To accurately track an aerospace vehicle in a time-critical situation and in a highly nonlinear environment, is one of the strongest interests within the aerospace community. The tracking is achieved by estimating accurately the state of a moving target, which is composed of a set of variables that can provide a complete status of the system at a given time. One of the main ingredients for a good estimation performance is the use of efficient estimation algorithms. A well-known framework is the Kalman filtering methods, designed for prediction and estimation problems. The success of the Kalman Filter (KF) in engineering applications is mostly due to the Extended Kalman Filter (EKF), which is based on local linearization. Besides its popularity, the EKF presents several limitations. To address these limitations and as a possible solution to tracking problems, this paper proposes the use of the Ensemble Kalman Filter (EnKF). Although the EnKF is being extensively used in the context of weather forecasting and it is being recognized for producing accurate and computationally effective estimation on systems with a very high dimension, it is almost unknown by the tracking community. The EnKF was initially proposed as an attempt to improve the error covariance calculation, which on the classic Kalman Filter is difficult to implement. Also, in the EnKF method the prediction and analysis error covariances have ensemble representations. These ensembles have sizes which limit the number of degrees of freedom, in a way that the filter error covariance calculations are a lot more practical for modest ensemble sizes. In this paper, a realistic simulation of a radar tracking was performed, where the EnKF was applied and compared with the Extended Kalman Filter. The results suggested that the EnKF is a promising tool for tracking applications, offering more advantages in terms of performance.

Keywords: Kalman filter, nonlinear state estimation, optimal tracking, stochastic environment

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3059 Graph Neural Network-Based Classification for Disease Prediction in Health Care Heterogeneous Data Structures of Electronic Health Record

Authors: Raghavi C. Janaswamy

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In the healthcare sector, heterogenous data elements such as patients, diagnosis, symptoms, conditions, observation text from physician notes, and prescriptions form the essentials of the Electronic Health Record (EHR). The data in the form of clear text and images are stored or processed in a relational format in most systems. However, the intrinsic structure restrictions and complex joins of relational databases limit the widespread utility. In this regard, the design and development of realistic mapping and deep connections as real-time objects offer unparallel advantages. Herein, a graph neural network-based classification of EHR data has been developed. The patient conditions have been predicted as a node classification task using a graph-based open source EHR data, Synthea Database, stored in Tigergraph. The Synthea DB dataset is leveraged due to its closer representation of the real-time data and being voluminous. The graph model is built from the EHR heterogeneous data using python modules, namely, pyTigerGraph to get nodes and edges from the Tigergraph database, PyTorch to tensorize the nodes and edges, PyTorch-Geometric (PyG) to train the Graph Neural Network (GNN) and adopt the self-supervised learning techniques with the AutoEncoders to generate the node embeddings and eventually perform the node classifications using the node embeddings. The model predicts patient conditions ranging from common to rare situations. The outcome is deemed to open up opportunities for data querying toward better predictions and accuracy.

Keywords: electronic health record, graph neural network, heterogeneous data, prediction

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3058 Influencing Factors and Mechanism of Patient Engagement in Healthcare: A Survey in China

Authors: Qing Wu, Xuchun Ye, Kirsten Corazzini

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Objective: It is increasingly recognized that patients’ rational and meaningful engagement in healthcare could make important contributions to their health care and safety management. However, recent evidence indicated that patients' actual roles in healthcare didn’t match their desired roles, and many patients reported a less active role than desired, which suggested that patient engagement in healthcare may be influenced by various factors. This study aimed to analyze influencing factors on patient engagement and explore the influence mechanism, which will be expected to contribute to the strategy development of patient engagement in healthcare. Methods: On the basis of analyzing the literature and theory study, the research framework was developed. According to the research framework, a cross-sectional survey was employed using the behavior and willingness of patient engagement in healthcare questionnaire, Chinese version All Aspects of Health Literacy Scale, Facilitation of Patient Involvement Scale and Wake Forest Physician Trust Scale, and other influencing factor related scales. A convenience sample of 580 patients was recruited from 8 general hospitals in Shanghai, Jiangsu Province, and Zhejiang Province. Results: The results of the cross-sectional survey indicated that the mean score for the patient engagement behavior was (4.146 ± 0.496), and the mean score for the willingness was (4.387 ± 0.459). The level of patient engagement behavior was inferior to their willingness to be involved in healthcare (t = 14.928, P < 0.01). The influencing mechanism model of patient engagement in healthcare was constructed by the path analysis. The path analysis revealed that patient attitude toward engagement, patients’ perception of facilitation of patient engagement and health literacy played direct prediction on the patients’ willingness of engagement, and standard estimated values of path coefficient were 0.341, 0.199, 0.291, respectively. Patients’ trust in physician and the willingness of engagement played direct prediction on the patient engagement, and standard estimated values of path coefficient were 0.211, 0.641, respectively. Patient attitude toward engagement, patients’ perception of facilitation and health literacy played indirect prediction on patient engagement, and standard estimated values of path coefficient were 0.219, 0.128, 0.187, respectively. Conclusions: Patients engagement behavior did not match their willingness to be involved in healthcare. The influencing mechanism model of patient engagement in healthcare was constructed. Patient attitude toward engagement, patients’ perception of facilitation of engagement and health literacy posed indirect positive influence on patient engagement through the patients’ willingness of engagement. Patients’ trust in physician and the willingness of engagement had direct positive influence on the patient engagement. Patient attitude toward engagement, patients’ perception of physician facilitation of engagement and health literacy were the factors influencing the patients’ willingness of engagement. The results of this study provided valuable evidence on guiding the development of strategies for promoting patient rational and meaningful engagement in healthcare.

Keywords: healthcare, patient engagement, influencing factor, the mechanism

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3057 Use of Statistical Correlations for the Estimation of Shear Wave Velocity from Standard Penetration Test-N-Values: Case Study of Algiers Area

Authors: Soumia Merat, Lynda Djerbal, Ramdane Bahar, Mohammed Amin Benbouras

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Along with shear wave, many soil parameters are associated with the standard penetration test (SPT) as a dynamic in situ experiment. Both SPT-N data and geophysical data do not often exist in the same area. Statistical analysis of correlation between these parameters is an alternate method to estimate Vₛ conveniently and without additional investigations or data acquisition. Shear wave velocity is a basic engineering tool required to define dynamic properties of soils. In many instances, engineers opt for empirical correlations between shear wave velocity (Vₛ) and reliable static field test data like standard penetration test (SPT) N value, CPT (Cone Penetration Test) values, etc., to estimate shear wave velocity or dynamic soil parameters. The relation between Vs and SPT- N values of Algiers area is predicted using the collected data, and it is also compared with the previously suggested formulas of Vₛ determination by measuring Root Mean Square Error (RMSE) of each model. Algiers area is situated in high seismic zone (Zone III [RPA 2003: réglement parasismique algerien]), therefore the study is important for this region. The principal aim of this paper is to compare the field measurements of Down-hole test and the empirical models to show which one of these proposed formulas are applicable to predict and deduce shear wave velocity values.

Keywords: empirical models, RMSE, shear wave velocity, standard penetration test

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3056 Relevance of Reliability Approaches to Predict Mould Growth in Biobased Building Materials

Authors: Lucile Soudani, Hervé Illy, Rémi Bouchié

Abstract:

Mould growth in living environments has been widely reported for decades all throughout the world. A higher level of moisture in housings can lead to building degradation, chemical component emissions from construction materials as well as enhancing mould growth within the envelope elements or on the internal surfaces. Moreover, a significant number of studies have highlighted the link between mould presence and the prevalence of respiratory diseases. In recent years, the proportion of biobased materials used in construction has been increasing, as seen as an effective lever to reduce the environmental impact of the building sector. Besides, bio-based materials are also hygroscopic materials: when in contact with the wet air of a surrounding environment, their porous structures enable a better capture of water molecules, thus providing a more suitable background for mould growth. Many studies have been conducted to develop reliable models to be able to predict mould appearance, growth, and decay over many building materials and external exposures. Some of them require information about temperature and/or relative humidity, exposure times, material sensitivities, etc. Nevertheless, several studies have highlighted a large disparity between predictions and actual mould growth in experimental settings as well as in occupied buildings. The difficulty of considering the influence of all parameters appears to be the most challenging issue. As many complex phenomena take place simultaneously, a preliminary study has been carried out to evaluate the feasibility to sadopt a reliability approach rather than a deterministic approach. Both epistemic and random uncertainties were identified specifically for the prediction of mould appearance and growth. Several studies published in the literature were selected and analysed, from the agri-food or automotive sectors, as the deployed methodology appeared promising.

Keywords: bio-based materials, mould growth, numerical prediction, reliability approach

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3055 Two Lessons Learnt in Defining Intersections and Interfaces in Numerical Modeling with Plaxis

Authors: Mahdi Sadeghian, Somaye Sadeghian, Reza Dinarvand

Abstract:

This paper is going to discuss two issues encountered in using PLAXIS. Both issues were monitored during application of PLAXIS to estimate the excavation-induced displacement. Column Soil Mixing (CSM) was applied to stabilise the excavation. It was understood that the estimated excavation induced deformation at the top of the CSM blocks highly depends on the material type defining pavement material adjacent to the CSM blocks. Cohesive material for pavement will result in the unrealistic connection between pavement and CSM even by defining an interface element. To find the most realistic approach, the interface defined in three different manners (1) no interface elements were applied (2) a non-cohesive soil layer was defined between pavement and CSM block to represent the friction between these materials (3) built-in interface elements in PLAXIS was used to define the boundary between the pavement and the CSM block. The result showed that the option 2 would result in more realistic results. The second issue was in the modelling of the contact line between the CSM block and an inclined layer underneath. The analysis result showed that the excavation-induced deformation highly depends on how the PLAXIS user defines the contact area. It was understood that if the contact area had defined as a point in which CSM block had intersected the layer underneath the estimated lateral displacement of CSM block would be unrealistically lower than the model in which the contact area was defined as a line.

Keywords: PLAXIS, FEM, CSM, Excavation-Induced Deformation

Procedia PDF Downloads 148
3054 Efficacy of DAPG Producing Fluorescent Pseudomonas for Enhancing Nutrient Use Efficacy, Bio-Control of Soil-Borne Diseases and Yield of Groundnut

Authors: Basavaraj Yenagi, P. Nagaraju, C. R. Patil

Abstract:

Groundnut (Arachis hypohaea L.) is called as “King of oilseeds” and one of the most important food and cash crops in Indian subcontinent. Yield and quality of oil are negatively correlated with poor or imbalanced nutrition and constant exposure to both biotic and abiotic stress factors. Variety of diseases affect groundnut plant, most of them are caused by fungi and lead to severe yield loss. Imbalanced nutrition increases the concerns of environmental deterioration which includes soil fertility. Among different microbial antagonists, Pseudomonas is common member of the plant growth promoting rhizobacteria microflora present in the rhizosphere of groundnut. These are known to produce a beneficial effect on groundnut due to their high metabolic activity leading to the production of enzymes, exopolysaccharides, secondary metabolites, and antibiotics. The ability of pseudomonas lies on their ability to produce antibiotic metabolites such as 2, 4-diacetylphloroglucinol (DAPG). DAPG can inhibit the growth of fungal pathogens namely collar rot and stem rot and also increase the availability of plant nutrients through increased solubilization and uptake of nutrients. Hence, the present study was conducted for three consecutive years (2014 to 2016) in vertisol during the rainy season to assess the efficacy of DAPG producing fluorescent pseudomonas for enhancing nutrient use efficacy, bio-control of soil-borne diseases and yield of groundnut at University of Agricultural Sciences, Dharwad farm. The experiment was laid out in an RCBD with three replications and seven treatments. The mean of three years data revealed that the effect of DAPG-producing producing fluorescent pseudomonas enhanced groundnut yield, uptake of nitrogen and phosphorus and nutrient use efficiency and also found to be effective in bio-control of collar rot and stem rot incidence leading to increase pod yield of groundnut. Higher dry pod yield of groundnut was obtained with DAPG 2(3535 kg ha-1) closely followed by DAPG 4(3492 kg ha-1), FP 98(3443 kg ha-1), DAPG 1(3414 kg ha-1), FP 86(3361 kg ha-1) and Trichoderma spp. (3380 kg ha-1) over control(3173 kg ha-1). A similar trend was obtained with other growth and yield attributing parameters. N uptake ranged from 8.21 percent to FP 86 to 17.91 percent with DAPG 2 and P uptake ranged between 5.56 percent with FP 86 to 16.67 percent with DAPG 2 over control. The first year, there was no incidence of collar rot. During the second year, the control plot recorded 2.51 percent incidence and it ranged from 0.82 percent to 1.43 percent in different DAPG-producing fluorescent pseudomonas treatments. The similar trend was noticed in the third year with lower incidence. The stem rot incidence was recorded during all the three years. Mean data indicated that the control plot recorded 2.65 percent incidence and it ranged from 0.71 percent to 1.23 percent in different DAPG-producing fluorescent pseudomonas treatments. The increase in net monetary benefits ranged from Rs.5975 ha-1 to Rs.11407 ha 1 in different treatments. Hence, as a low-cost technology, seed treatment with available DAPG-producing fluorescent pseudomonas has a beneficial effect on groundnut for enhancing groundnut yield, nutrient use efficiency and bio-control of soil-borne diseases.

Keywords: groundnut, DAPG, fluorescent pseudomonas, nutrient use efficiency, collar rot, stem rot

Procedia PDF Downloads 167
3053 Boundary Conditions for 2D Site Response Analysis in OpenSees

Authors: M. Eskandarighadi, C. R. McGann

Abstract:

It is observed from past experiences of earthquakes that local site conditions can significantly affect the strong ground motion characteristicssuch as frequency content, amplitude, and duration of seismic waves. The most common method for investigating site response is one-dimensional seismic site response analysis. The infinite horizontal length of the model and the homogeneous characteristic of the soil are crucial assumptions of this method. One boundary condition that can be used in the sides is tying the sides horizontally for vertical 1D wave propagation. However, 1D analysis cannot account for the 2D nature of wave propagation in the condition where the soil profile is not fully horizontal or has heterogeneity within layers. Therefore, 2D seismic site response analysis can be used to take all of these limitations into account for a better understanding of local site conditions. Different types of boundary conditions can be appliedin 2D site response models, such as tied boundary condition, massive columns, and free-field boundary condition. The tied boundary condition has been used in 1D analysis, which is useful for 1D wave propagation. Employing two massive columns at the sides is another approach for capturing the 2D nature of wave propagation. Free-field boundary condition can simulate the free-field motion that would exist far from the domain of interest. The goal for free-field boundary condition is to minimize the unwanted reflection from sides. This research focuses on the comparison between these methods with examples and discusses the details and limitations of each of these boundary conditions.

Keywords: boundary condition, free-field, massive columns, opensees, site response analysis, wave propagation

Procedia PDF Downloads 154
3052 Agro-Industrial Waste as a Source of Catalyst Production

Authors: Brenda Cecilia Ledesma, Andrea Beltramone

Abstract:

This work deals with the bio-waste valorization approach for catalyst development, the use of products derived from biomass as raw material and the obtaining of biofuels. In this research, activated carbons were synthesized from the orange peel using different synthesis conditions. With the activated carbons obtained with the best structure and texture, PtIr bimetallic catalysts were prepared. Carbon activation was carried out through a chemical process with phosphoric acid as an activating agent, varying the acid concentration, the ratio substrate/activating agent and time of contact between them. The best support was obtained using a carbonization time of 1 h, the temperature of carbonization of 470oC, the phosphoric acid concentration of 50 wt.% and a BET area of 1429 m2/g. Subsequently, the metallic nanoparticles were deposited in the activated carbon to use the solid as a catalytic material for the hydrogenation of HMF to 2,5-DMF. The catalyst presented an excellent performance for biofuels generation.

Keywords: orange peel, bio-waste valorization, platinum, iridium, 5-hydroxymethylfurfural

Procedia PDF Downloads 178
3051 Parametric Study for Obtaining the Structural Response of Segmental Tunnels in Soft Soil by Using No-Linear Numerical Models

Authors: Arturo Galván, Jatziri Y. Moreno-Martínez, Israel Enrique Herrera Díaz, José Ramón Gasca Tirado

Abstract:

In recent years, one of the methods most used for the construction of tunnels in soft soil is the shield-driven tunneling. The advantage of this construction technique is that it allows excavating the tunnel while at the same time a primary lining is placed, which consists of precast segments. There are joints between segments, also called longitudinal joints, and joints between rings (called as circumferential joints). This is the reason because of this type of constructions cannot be considered as a continuous structure. The effect of these joints influences in the rigidity of the segmental lining and therefore in its structural response. A parametric study was performed to take into account the effect of different parameters in the structural response of typical segmental tunnels built in soft soil by using non-linear numerical models based on Finite Element Method by means of the software package ANSYS v. 11.0. In the first part of this study, two types of numerical models were performed. In the first one, the segments were modeled by using beam elements based on Timoshenko beam theory whilst the segment joints were modeled by using inelastic rotational springs considering the constitutive moment-rotation relation proposed by Gladwell. In this way, the mechanical behavior of longitudinal joints was simulated. On the other hand for simulating the mechanical behavior of circumferential joints elastic springs were considered. As well as, the stability given by the soil was modeled by means of elastic-linear springs. In the second type of models, the segments were modeled by means of three-dimensional solid elements and the joints with contact elements. In these models, the zone of the joints is modeled as a discontinuous (increasing the computational effort) therefore a discrete model is obtained. With these contact elements the mechanical behavior of joints is simulated considering that when the joint is closed, there is transmission of compressive and shear stresses but not of tensile stresses and when the joint is opened, there is no transmission of stresses. This type of models can detect changes in the geometry because of the relative movement of the elements that form the joints. A comparison between the numerical results with two types of models was carried out. In this way, the hypothesis considered in the simplified models were validated. In addition, the numerical models were calibrated with (Lab-based) experimental results obtained from the literature of a typical tunnel built in Europe. In the second part of this work, a parametric study was performed by using the simplified models due to less used computational effort compared to complex models. In the parametric study, the effect of material properties, the geometry of the tunnel, the arrangement of the longitudinal joints and the coupling of the rings were studied. Finally, it was concluded that the mechanical behavior of segment and ring joints and the arrangement of the segment joints affect the global behavior of the lining. As well as, the effect of the coupling between rings modifies the structural capacity of the lining.

Keywords: numerical models, parametric study, segmental tunnels, structural response

Procedia PDF Downloads 218
3050 Cadaver Free Fatty Acid Distribution Associated with Burial in Mangrove and Oil Palm Plantation Soils under Tropical Climate

Authors: Siti Sofo Ismail, Siti Noraina Wahida Mohd Alwi, Mohamad Hafiz Ameran, Masrudin M. Yusoff

Abstract:

Locating clandestine cadaver is crucially important in forensic investigations. However, it requires a lot of man power, costly and time consuming. Therefore, the development of a new method to locate the clandestine graves is urgently needed as the cases involve burial of cadaver in different types of soils under tropical climates are still not well explored. This study focused on the burial in mangrove and oil palm plantation soils, comparing the fatty acid distributions in different soil acidities. A stimulated burial experiment was conducted using domestic pig (Sus scrofa) to substitute human tissues. Approximately 20g of pig fatty flesh was allowed to decompose in mangrove and oil palm plantation soils, mimicking burial in a shallow grave. The associated soils were collected at different designated sampling points, corresponding different decomposition stages. Modified Bligh-Dyer Extraction method was applied to extract the soil free fatty acids. Then, the obtained free fatty acids were analyzed with gas chromatography-flame ionization (GC-FID). A similar fatty acid distribution was observed for both mangrove and oil palm plantations soils. Palmitic acid (C₁₆) was the most abundance of free fatty acid, followed by stearic acid (C₁₈). However, the concentration of palmitic acid (C₁₆) higher in oil palm plantation compare to mangrove soils. Conclusion, the decomposition rate of cadaver can be affected by different type of soils.

Keywords: clandestine grave, burial, soils, free fatty acid

Procedia PDF Downloads 381
3049 Performance of Rapid Impact Compaction as a Middle-Deep Ground Improvement Technique

Authors: Bashar Tarawneh, Yasser Hakam

Abstract:

Rapid Impact Compaction (RIC) is a modern dynamic compaction device mainly used to compact sandy soils, where silt and clay contents are low. The device uses the piling hammer technology to increase the bearing capacity of soils through controlled impacts. The RIC device uses "controlled impact compaction" of the ground using a 9-ton hammer dropped from the height between 0.3 m to 1.2 m onto a 1.5 m diameter steel patent foot. The delivered energy is about 26,487 to 105,948 Joules per drop. To evaluate the performance of this technique, three project sites in the United Arab Emirates were improved using RIC. In those sites, a loose to very loose fine to medium sand was encountered at a depth ranging from 1.0m to 4.0m below the ground level. To evaluate the performance of the RIC, Cone Penetration Tests (CPT) were carried out before and after improvement. Also, load tests were carried out post-RIC work to assess the settlements and bearing capacity. The soil was improved to a depth of about 5.0m below the ground level depending on the CPT friction ratio (the ratio between sleeve friction and tip resistance). CPT tip resistance was significantly increased post ground improvement work. Load tests showed enhancement in the soil bearing capacity and reduction in the potential settlements. This study demonstrates the successful application of the RIC for middle-deep improvement and compaction of the ground. Foundation design criteria were achieved in all site post-RIC work.

Keywords: compaction, RIC, ground improvement, CPT

Procedia PDF Downloads 355
3048 Phase Transition and Molecular Polarizability Studies in Liquid Crystalline Mixtures

Authors: M. Shahina, K. Fakruddin, C. M. Subhan, S. Rangappa

Abstract:

In this work, two mixtures with equal concentrations of 1) 4ꞌ-(6-(4-(pentylamino) methyl)-3-hydroxyphenoxy) hexyloxy) biphenyl-4-carbonitrile+-4-((4-(hexyloxy) benzylidene) amino) phenyl 4-butoxy benzoate and 2) 4ꞌ - (6-(4-(hexylamino) methyl)-3-hydroxyphenoxy) hexyloxy) biphenyl-4-carbonitrile+-4-((4-(octyloxy) benzylidene) amino) phenyl 4-butoxy benzoate, have been prepared. The transition temperature and optical texture are observed by using thermal microscopy. Density and birefringence studies are carried out on the above liquid crystalline mixtures. Using density and refractive indices data, the molecular polarizabilities are evaluated by using well-known Vuks and Neugebauer models. The molecular polarizability is also evaluated theoretically by Lippincott δ function model. The results reveal that the polarizability values are same in both experimental and theoretical methods.

Keywords: liquid crystals, optical textures, transition temperature, birefringence, polarizability

Procedia PDF Downloads 277
3047 Management of Fungal Diseases of Onion (Allium cepa L.) by Using Plant Extracts

Authors: Shobha U. Jadhav, R. S. Saler

Abstract:

Onion is most Important Vegetable crop grown throughout the world. Onion suffers from pest and fungal diseases but the fungicides cause pollution and disturb microbial balance of soil. Under integrated fungal disease management programme cost effective and eco- friendly component like plant extract are used to control plant pathogens. Alternaria porri, Fusarium oxysporium, Stemphylium vesicarium are soil borne pathogens of onion. Effect of three different plant extract (Datura metel, Pongamia pinnata, Ipomoea palmata) at five different concentration Viz, 10,25,50,75 and 100 percentage on these pathogens was studied by food poisoning techniquie. Detura metal gave 94.73% growth of Alternaria porri at 10% extract concentraton and 26.31% growth in 100% extract concentration. As compared to Fusarium oxysporium, and Stemphylium vesicarium, Alternaria porri give good inhibitory response. In Pongamia pinnata L. at 10% extract concentration 84.21% growth and at 100% extract concentration 36.84% growth of Stemphylium vesicarium was observed. Stemphylium vesicarium give good in inhibitory response as compared to Alternaria porri and Fusarium oxysporium. Ipomoea palmata in 10% extract concentration 92% growth and in 100% extract concentration 40% growth of Fusarium oxysporium was recorded. Fusarium oxysporium give good inhibitory response as compared to Alternaria porri and, Stemphylium vesicarium.

Keywords: pathogen, onion, plant extract, Allium cepa L.

Procedia PDF Downloads 453
3046 Strength of Soft Clay Reinforced with Polypropylene Column

Authors: Muzamir Hasan, Anas Bazirgan

Abstract:

Granular columns is a technique that has the properties of improving bearing capacity, accelerating the dissipation of excess pore water pressure and reducing settlement in a weak soft soil. This research aims to investigate the role of Polypropylene column in improving the shear strength and compressibility of soft reconstituted kaolin clay by determining the effects of area replacement ratio, height penetrating ratio and volume replacement ratio of a singular Polypropylene column on the strength characteristics. Reinforced kaolin samples were subjected to Unconfined Compression (UCT) and Unconsolidated Undrained (UU) triaxial tests. The kaolin samples were 50 mm in diameter and 100 mm in height. Using the PP column reinforcement, with an area replacement ratio of 0.8, 0.5 and 0.3, shear strength increased approximately 5.27%, 26.22% and 64.28%, and 37.14%, 42.33% and 51.17%, for area replacement ratios of 25% and 10.24%. Meanwhile, UU testing showed an increase in shear strength of 24.01%, 23.17% and 23.49% and 28.79%, 27.29 and 30.81% for the same ratios. Based on the UCT results, the undrained shear strength generally increased with the decrease in height penetration ratio. However, based on the UU test results Mohr-Coulomb failure criteria, the installation of Polypropylene columns did not show any significant difference in effective friction angle. However, there was an increase in the apparent cohesion and undrained shear strength of the kaolin clay. In conclusion, Polypropylene column greatly improved the shear strength; and could therefore be implemented in reducing the cost of soil improvement as a replacement for non-renewable materials.

Keywords: polypropylene, UCT, UU test, Kaolin S300, ground improvement

Procedia PDF Downloads 319
3045 Anisotropic Behavior of Sand Stabilized with Colloidal Silica

Authors: Eleni Maria Pavlopoulou, Vasiliki N. Georgiannou, Filippos C. Chortis

Abstract:

The response of M31 sand stabilized with colloidal silica (CS) aqueous gel is investigated in the laboratory. CS is introduced in the water regime, forming a hydrosol. The low viscosity hydrosol thickens in a controllable manner to form a stable, non-toxic gel; the gel fills the pore space, retains the pore water, and supports the grain structure. The role of colloidal silica on subsequent sand behavior is examined with the aid of direct shear, triaxial, and normal compression tests. Under the examined loading modes, while the strength of the treated sand is enhanced, its stiffness may reduce, and its compressibility increase. However, in most geotechnical problems, the loading conditions are complex, involving changes in both stress magnitude and direction. Rotation of principal stresses (σ1, σ2, σ3) in varying amounts expressed as angle α, (from α=0° to 90°) in concurrence with increasing shear stress loading is commonly encountered in soil structures such as foundations, embankments, underwater slopes. To assess the influence of anisotropy on the response of sands before and after their stabilization, hollow cylinder tests were performed. The behavior of stabilized sand is compared with the characteristic sand behavior, i.e., a reduction in peak stress ratio associated with a softer stress-strain response with the increasing angle a. The influence of the magnitude of the intermediate principal stress (σ2) on the mechanical response of treated and untreated sand is also examined.

Keywords: anisotropy, colloidal silica, laboratory tests, sands, soil stabilization

Procedia PDF Downloads 125
3044 Hydrogels Beads of Alginate/Seaweed Powder for Plants Nutrition

Authors: Brenda O. Mazzola, Adriel Larsen, Romina P. Ollier, Leandro N. Ludueña, Vera A. Alvarez, Jimena S. Gonzalez

Abstract:

Seaweed is a natural renewable resource with great potential that is not being used by the domestic industry. Here, it was used a kind of invasive algae U. Pinnatifida that causes serious ecological damage on the Argentinian coasts. Alginate is one of the most widely used materials for encapsulation, and has the advantage that is a natural polysaccharide derived from a marine plant. It can form thermally stable hydrogel in the presence of calcium cation. In addition, the hydrogel can be easily produced into particulate form by using simple and gentle method. The aim of this work was to obtain and to characterize novel compounds (alginate/seaweed powder) for the soil nutrition. Alginate water solutions were prepared by concentrations of 20, 30, 40 and 50 g/L, in those solutions 10g/L of seaweed powder was added. Then the dispersions were transferred from a beaker to the atomizer by a peristaltic pump (with 0.05 to 0.1 L/h flow). A tank was filled with 1 L of calcium chloride solution (4 g/L), and the solution was agitated with a magnetic stirrer. The beads were analyzed by means TGA, FTIR and swelling determinations. In addition, the improvements in the soil were qualitative measured. It was obtained beads with different diameters depend on the initial concentration and the flow used. A better dispersions of seaweed and optimal diameter for the plant nutrition applications were obtained for 40g/L concentration and 0.1 L/h flow. The beads show thermal stability and high swelling degree. It can be successfully obtained alginate beads with seaweed powder with a novelty application as plant nutrient.

Keywords: biodegradable, characterization, hydrogel, plant nutrition, seaweed

Procedia PDF Downloads 269
3043 Multi-Model Super Ensemble Based Advanced Approaches for Monsoon Rainfall Prediction

Authors: Swati Bhomia, C. M. Kishtawal, Neeru Jaiswal

Abstract:

Traditionally, monsoon forecasts have encountered many difficulties that stem from numerous issues such as lack of adequate upper air observations, mesoscale nature of convection, proper resolution, radiative interactions, planetary boundary layer physics, mesoscale air-sea fluxes, representation of orography, etc. Uncertainties in any of these areas lead to large systematic errors. Global circulation models (GCMs), which are developed independently at different institutes, each of which carries somewhat different representation of the above processes, can be combined to reduce the collective local biases in space, time, and for different variables from different models. This is the basic concept behind the multi-model superensemble and comprises of a training and a forecast phase. The training phase learns from the recent past performances of models and is used to determine statistical weights from a least square minimization via a simple multiple regression. These weights are then used in the forecast phase. The superensemble forecasts carry the highest skill compared to simple ensemble mean, bias corrected ensemble mean and the best model out of the participating member models. This approach is a powerful post-processing method for the estimation of weather forecast parameters reducing the direct model output errors. Although it can be applied successfully to the continuous parameters like temperature, humidity, wind speed, mean sea level pressure etc., in this paper, this approach is applied to rainfall, a parameter quite difficult to handle with standard post-processing methods, due to its high temporal and spatial variability. The present study aims at the development of advanced superensemble schemes comprising of 1-5 day daily precipitation forecasts from five state-of-the-art global circulation models (GCMs), i.e., European Centre for Medium Range Weather Forecasts (Europe), National Center for Environmental Prediction (USA), China Meteorological Administration (China), Canadian Meteorological Centre (Canada) and U.K. Meteorological Office (U.K.) obtained from THORPEX Interactive Grand Global Ensemble (TIGGE), which is one of the most complete data set available. The novel approaches include the dynamical model selection approach in which the selection of the superior models from the participating member models at each grid and for each forecast step in the training period is carried out. Multi-model superensemble based on the training using similar conditions is also discussed in the present study, which is based on the assumption that training with the similar type of conditions may provide the better forecasts in spite of the sequential training which is being used in the conventional multi-model ensemble (MME) approaches. Further, a variety of methods that incorporate a 'neighborhood' around each grid point which is available in literature to allow for spatial error or uncertainty, have also been experimented with the above mentioned approaches. The comparison of these schemes with respect to the observations verifies that the newly developed approaches provide more unified and skillful prediction of the summer monsoon (viz. June to September) rainfall compared to the conventional multi-model approach and the member models.

Keywords: multi-model superensemble, dynamical model selection, similarity criteria, neighborhood technique, rainfall prediction

Procedia PDF Downloads 128