Search results for: Carlo Stephen O. Moneva

Authors: Weirong Wang, Shenghong Huang, Xisheng Luo, Zhenyu Li

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Material mixing process and related dynamic issues at extreme compressing conditions have gained more and more concerns in last ten years because of the engineering appealings in inertial confinement fusion (ICF) and hypervelocity aircraft developments. However, there lacks models and methods that can handle fully coupled turbulent material mixing and complex fluid evolution under conditions of high energy density regime up to now. In aspects of macro hydrodynamics, three numerical methods such as direct numerical simulation (DNS), large eddy simulation (LES) and Reynolds-averaged Navier–Stokes equations (RANS) has obtained relative acceptable consensus under the conditions of low energy density regime. However, under the conditions of high energy density regime, they can not be applied directly due to occurrence of dissociation, ionization, dramatic change of equation of state, thermodynamic properties etc., which may make the governing equations invalid in some coupled situations. However, in view of micro/meso scale regime, the methods based on Molecular Dynamics (MD) as well as Monte Carlo (MC) model are proved to be promising and effective ways to investigate such issues. In this study, both classical MD and first-principle based electron force field MD (eFF-MD) methods are applied to investigate Richtmyer-Meshkov Instability of metal Lithium and gas Hydrogen (Li-H2) interface mixing at different shock loading speed ranging from 3 km/s to 30 km/s. It is found that: 1) Classical MD method based on predefined potential functions has some limits in application to extreme conditions, since it cannot simulate the ionization process and its potential functions are not suitable to all conditions, while the eFF-MD method can correctly simulate the ionization process due to its ‘ab initio’ feature; 2) Due to computational cost, the eFF-MD results are also influenced by simulation domain dimensions, boundary conditions and relaxation time choices, etc., in computations. Series of tests have been conducted to determine the optimized parameters. 3) Ionization induced by strong shock compression has important effects on Li-H2 interface evolutions of RMI, indicating a new micromechanism of RMI under conditions of high energy density regime.

Keywords: first-principle, ionization, molecular dynamics, material mixture, Richtmyer-Meshkov instability

Procedia PDF Downloads 219

Authors: Albert Mufundirwa, Satoru Yoshioka, K. Ogi, Takeharu Sugiyama, George F. Harrington, Bretislav Smid, Benjamin Cunning, Kazunari Sasaki, Akari Hayashi, Stephen M. Lyth

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Polymer electrolyte membrane fuel cells (PEMFCs) are electrochemical energy conversion devices used for portable, residential and vehicular applications due to their low emissions, high efficiency, and quick start-up characteristics. However, PEMFCs generally use expensive, Pt-based electrocatalysts as electrode catalysts. Due to the high cost and limited availability of platinum, research and development to either drastically reduce platinum loading, or replace platinum with alternative catalysts is of paramount importance. A combination of high surface area supports and nano-structured active sites is essential for effective operation of catalysts. We synthesize carbon foam supports by thermal decomposition of sodium ethoxide, using a template-free, gram scale, cheap, and scalable pyrolysis method. This carbon foam has a high surface area, highly porous, three-dimensional framework which is ideal for electrochemical applications. These carbon foams can have surface area larger than 2500 m²/g, and electron microscopy reveals that they have micron-scale cells, separated by few-layer graphene-like carbon walls. We applied this carbon foam as a platinum catalyst support, resulting in the improved electrochemical surface area and mass activity for the oxygen reduction reaction (ORR), compared to carbon black. Similarly, silver-decorated carbon foams showed higher activity and efficiency for electrochemical carbon dioxide conversion than silver-decorated carbon black. A promising alternative to Pt-catalysts for the ORR is iron-impregnated nitrogen-doped carbon catalysts (Fe-N-C). Doping carbon with nitrogen alters the chemical structure and modulates the electronic properties, allowing a degree of control over the catalytic properties. We have adapted our synthesis method to produce nitrogen-doped carbon foams with large surface area, using triethanolamine as a nitrogen feedstock, in a novel bottom-up protocol. These foams are then infiltrated with iron acetate (FeAc) and pyrolysed to form Fe-N-C foams. The resulting Fe-N-C foam catalysts have high initial activity (half-wave potential of 0.68 VRHE), comparable to that of commercially available Pt-free catalysts (e.g., NPC-2000, Pajarito Powder) in acid solution. In alkaline solution, the Fe-N-C carbon foam catalysts have a half-wave potential of 0.89 VRHE, which is higher than that of NPC-2000 by almost 10 mVRHE, and far out-performing platinum. However, the durability is still a problem at present. The lessons learned from X-ray absorption spectroscopy (XAS), transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS), and electrochemical measurements will be used to carefully design Fe-N-C catalysts for higher performance PEMFCs.

Keywords: carbon-foam, polymer electrolyte membrane fuel cells, platinum, Pt-free, Fe-N-C, ORR

Procedia PDF Downloads 163

Authors: Huseyin Guler, Cigdem Kosar

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The aim of this study is to propose Bridge estimator for seasonal unit root tests. Seasonality is an important factor for many economic time series. Some variables may contain seasonal patterns and forecasts that ignore important seasonal patterns have a high variance. Therefore, it is very important to eliminate seasonality for seasonal macroeconomic data. There are some methods to eliminate the impacts of seasonality in time series. One of them is filtering the data. However, this method leads to undesired consequences in unit root tests, especially if the data is generated by a stochastic seasonal process. Another method to eliminate seasonality is using seasonal dummy variables. Some seasonal patterns may result from stationary seasonal processes, which are modelled using seasonal dummies but if there is a varying and changing seasonal pattern over time, so the seasonal process is non-stationary, deterministic seasonal dummies are inadequate to capture the seasonal process. It is not suitable to use seasonal dummies for modeling such seasonally nonstationary series. Instead of that, it is necessary to take seasonal difference if there are seasonal unit roots in the series. Different alternative methods are proposed in the literature to test seasonal unit roots, such as Dickey, Hazsa, Fuller (DHF) and Hylleberg, Engle, Granger, Yoo (HEGY) tests. HEGY test can be also used to test the seasonal unit root in different frequencies (monthly, quarterly, and semiannual). Another issue in unit root tests is the lag selection. Lagged dependent variables are added to the model in seasonal unit root tests as in the unit root tests to overcome the autocorrelation problem. In this case, it is necessary to choose the lag length and determine any deterministic components (i.e., a constant and trend) first, and then use the proper model to test for seasonal unit roots. However, this two-step procedure might lead size distortions and lack of power in seasonal unit root tests. Recent studies show that Bridge estimators are good in selecting optimal lag length while differentiating nonstationary versus stationary models for nonseasonal data. The advantage of this estimator is the elimination of the two-step nature of conventional unit root tests and this leads a gain in size and power. In this paper, the Bridge estimator is proposed to test seasonal unit roots in a HEGY model. A Monte-Carlo experiment is done to determine the efficiency of this approach and compare the size and power of this method with HEGY test. Since Bridge estimator performs well in model selection, our approach may lead to some gain in terms of size and power over HEGY test.

Keywords: bridge estimators, HEGY test, model selection, seasonal unit root

Procedia PDF Downloads 323

Authors: Moustafa Osman Mohammed

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The modeling of a spatial-economic database is crucial in recitation economic network structure to social development. Sustainability within the spatial-economic model gives attention to green businesses to comply with Earth’s Systems. The natural exchange patterns of ecosystems have consistent and periodic cycles to preserve energy and materials flow in systems ecology. When network topology influences formal and informal communication to function in systems ecology, ecosystems are postulated to valence the basic level of spatial sustainable outcome (i.e., project compatibility success). These referred instrumentalities impact various aspects of the second level of spatial sustainable outcomes (i.e., participant social security satisfaction). The sustainability outcomes are modeling composite structure based on a network analysis model to calculate the prosperity of panel databases for efficiency value, from 2005 to 2025. The database is modeling spatial structure to represent state-of-the-art value-orientation impact and corresponding complexity of sustainability issues (e.g., build a consistent database necessary to approach spatial structure; construct the spatial-economic-ecological model; develop a set of sustainability indicators associated with the model; allow quantification of social, economic and environmental impact; use the value-orientation as a set of important sustainability policy measures), and demonstrate spatial structure reliability. The structure of spatial-ecological model is established for management schemes from the perspective pollutants of multiple sources through the input–output criteria. These criteria evaluate the spillover effect to conduct Monte Carlo simulations and sensitivity analysis in a unique spatial structure. The balance within “equilibrium patterns,” such as collective biosphere features, has a composite index of many distributed feedback flows. The following have a dynamic structure related to physical and chemical properties for gradual prolong to incremental patterns. While these spatial structures argue from ecological modeling of resource savings, static loads are not decisive from an artistic/architectural perspective. The model attempts to unify analytic and analogical spatial structure for the development of urban environments in a relational database setting, using optimization software to integrate spatial structure where the process is based on the engineering topology of systems ecology.

Keywords: ecological modeling, spatial structure, orientation impact, composite index, industrial ecology

Procedia PDF Downloads 45

Authors: Sabyasachi Mukhopadhyay, Joseph Ogutu, Gundula Bartzke, Hans-Peter Piepho

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Rainfall is a critical component of climate governing vegetation growth and production, forage availability and quality for herbivores. However, reliable rainfall measurements are not always available, making it necessary to predict rainfall values for particular locations through time. Predicting rainfall in space and time can be a complex and challenging task, especially where the rain gauge network is sparse and measurements are not recorded consistently for all rain gauges, leading to many missing values. Here, we develop a flexible Bayesian model for predicting rainfall in space and time and apply it to Narok County, situated in southwestern Kenya, using data collected at 23 rain gauges from 1965 to 2015. Narok County encompasses the Maasai Mara ecosystem, the northern-most section of the Mara-Serengeti ecosystem, famous for its diverse and abundant large mammal populations and spectacular migration of enormous herds of wildebeest, zebra and Thomson's gazelle. The model incorporates geographical and meteorological predictor variables, including elevation, distance to Lake Victoria and minimum temperature. We assess the efficiency of the model by comparing it empirically with the established Gaussian process, Kriging, simple linear and Bayesian linear models. We use the model to predict total monthly rainfall and its standard error for all 5 * 5 km grid cells in Narok County. Using the Monte Carlo integration method, we estimate seasonal and annual rainfall and their standard errors for 29 sub-regions in Narok. Finally, we use the predicted rainfall to predict large herbivore biomass in the Maasai Mara ecosystem on a 5 * 5 km grid for both the wet and dry seasons. We show that herbivore biomass increases with rainfall in both seasons. The model can handle data from a sparse network of observations with many missing values and performs at least as well as or better than four established and widely used models, on the Narok data set. The model produces rainfall predictions consistent with expectation and in good agreement with the blended station and satellite rainfall values. The predictions are precise enough for most practical purposes. The model is very general and applicable to other variables besides rainfall.

Keywords: non-stationary covariance function, gaussian process, ungulate biomass, MCMC, maasai mara ecosystem

Procedia PDF Downloads 282

Authors: Khulud Alhussain, Anna Gavine, Stephen Macgillivray, Sushila Chowdhry

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Background: Estimates show that by the year 2030, mental illness will account for more than half of the global economic burden, second to non-communicable diseases. Often, the perinatal period is characterised by psychological ambivalence and a mixed anxiety-depressive condition. Maternal mental disorder is associated with perinatal anxiety and depression and affects breastfeeding behaviors. Studies also indicate that maternal mental health can considerably influence a baby's health in numerous aspects and impact the newborn health due to lack of adequate breastfeeding. However, studies reporting factors associated with breastfeeding behaviors are predominantly quantitative. Therefore, it is not clear what literature is available to understand the factors affecting breastfeeding and perinatal women’s perspectives and experiences. Aim: This review aimed to explore the perceptions and experiences of women with perinatal anxiety and depression, as well as how these experiences influence their breastfeeding behaviours. Methods: A systematic literature review of qualitative studies in line with the Enhancing Transparency in Reporting the Synthesis of Qualitative Research (ENTREQ). Four electronic databases (CINAHL, PsycINFO, Embase, and Google Scholar) were explored for relevant studies using a search strategy. The search was restricted to studies published in the English language between 2000 and 2022. Findings from the literature were screened using a pre-defined screening criterion and the quality of eligible studies was appraised using the Walsh and Downe (2006) checklist. Findings were extracted and synthesised based on Braun and Clark. The review protocol was registered on PROSPERO (Ref: CRD42022319609). Result: A total of 4947 studies were identified from the four databases. Following duplicate removal and screening 16 studies met the inclusion criteria. The studies included 87 pregnant and 302 post-partum women from 12 countries. The participants were from a variety of economic, regional, and religious backgrounds, mainly from the age of 18 to 45 years old. Three main themes were identified: Barriers to breastfeeding, breastfeeding facilitators, emotional disturbance, and breastfeeding. Seven subthemes emerged from the data: expectation versus reality, uncertainly about maternal competencies, body image and breastfeeding, lack of sufficient breastfeeding support for family and caregivers’ support, influences positive breastfeeding practices, breastfeeding education, and causes of mental strain among breastfeeding women. Breastfeeding duration is affected in women with mental health disorders, irrespective of their desire to breastfeed. Conclusion: There is significant empirical evidence that breastfeeding behaviour and perinatal mental disturbance are linked. However, there is a lack of evidence to apply the findings to Saudi women due to lack of empirical qualitative information. To improve the psychological well-being of mothers, it is crucial to explore and recognise any concerns with their mental, physical, and emotional well-being. Therefore, robust research is needed so that breastfeeding intervention researchers and policymakers can focus on specifically what needs to be done to help mentally distressed perinatal women and their new-born.

Keywords: pregnancy, perinatal period, anxiety, depression, emotional disturbance, breastfeeding

Procedia PDF Downloads 72

Authors: Desmond Appiah, Fan Zhang, Shouqi Yuan, Wei Xueyuan, Stephen N. Asomani

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The side channel pump has distinctive hydraulic performance characteristics over other vane pumps because of its generation of high pressure heads in only one impeller revolution. Hence, there is soaring utilization and application in the fields of petrochemical, food processing fields, automotive and aerospace fuel pumping where high heads are required at low flows. The side channel pump is characterized by unstable flow because after fluid flows into the impeller passage, it moves into the side channel and comes back to the impeller again and then moves to the next circulation. Consequently, the flow leaves the side channel pump following a helical path. However, the pressure fluctuation exhibited in the flow greatly contributes to the unwanted noise and vibration which is associated with the flow. In this paper, a side channel pump prototype was examined thoroughly through numerical calculations based on SST k-ω turbulence model to ascertain the pressure fluctuation behavior. The pressure fluctuation intensity of the 3D unstable flow dynamics were carefully investigated under different working conditions 0.8QBEP, 1.0 QBEP and 1.2QBEP. The results showed that the pressure fluctuation distribution around the pressure side of the blade is greater than the suction side at the impeller and side channel interface (z=0) for all three operating conditions. Part-load condition 0.8QBEP recorded the highest pressure fluctuation distribution because of the high circulation velocity thus causing an intense exchanged flow between the impeller and side channel. Time and frequency domains spectra of the pressure fluctuation patterns in the impeller and the side channel were also analyzed under the best efficiency point value, QBEP using the solution from the numerical calculations. It was observed from the time-domain analysis that the pressure fluctuation characteristics in the impeller flow passage increased steadily until the flow reached the interrupter which separates low-pressure at the inflow from high pressure at the outflow. The pressure fluctuation amplitudes in the frequency domain spectrum at the different monitoring points depicted a gentle decreasing trend of the pressure amplitudes which was common among the operating conditions. The frequency domain also revealed that the main excitation frequencies occurred at 600Hz, 1200Hz, and 1800Hz and continued in the integers of the rotating shaft frequency. Also, the mass flow exchange plots indicated that the side channel pump is characterized with many vortex flows. Operating conditions 0.8QBEP, 1.0 QBEP depicted less and similar vortex flow while 1.2Q recorded many vortex flows around the inflow, middle and outflow regions. The results of the numerical calculations were finally verified experimentally. The performance characteristics curves from the simulated results showed that 0.8QBEP working condition recorded a head increase of 43.03% and efficiency decrease of 6.73% compared to 1.0QBEP. It can be concluded that for industrial applications where the high heads are mostly required, the side channel pump can be designed to operate at part-load conditions. This paper can serve as a source of information in order to optimize a reliable performance and widen the applications of the side channel pumps.

Keywords: exchanged flow, pressure fluctuation, numerical simulation, side channel pump

Procedia PDF Downloads 124

Authors: Trevor Stephen, Joshua D. Aceves, David Guyer, Jona Jacobson

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As a profession, social work has much to offer individuals, groups, and organizations. A multidisciplinary approach to understanding and solving complex challenges and a commitment to developing and training ethical practitioners outlines characteristics of a profession embedded with leadership skills. This presentation will take an overview of the historical context of social work leadership, examine social work as a unique leadership model composed of its qualities and theories that inform effective leadership capability as it relates to our code of ethics. Reflect critically on leadership theories and their foundational comparison. Finally, a look at recommendations and implementation to social work education and practice. Similar to defining leadership, there is no universally accepted definition of social work leadership. However, some distinct traits and characteristics are essential. Recent studies help set the stage for this research proposal because they measure views on effective social work leadership among social work and non-social leaders and followers. However, this research is interested in working backward from that approach and examining social workers' leadership preparedness perspectives based solely on social work training, competencies, values, and ethics. Social workers understand how to change complex structures and challenge resistance to change to improve the well-being of organizations and those they serve. Furthermore, previous studies align with the idea of practitioners assessing their skill and capacity to engage in leadership but not to lead. In addition, this research is significant because it explores aspiring social work leaders' competence to translate social work practice into direct leadership skills. The research question seeks to answer whether social work training and competencies are sufficient to determine whether social workers believe they possess the capacity and skill to engage in leadership practice. Aim 1: Assess whether social workers have the capacity and skills to assume leadership roles. Aim 2: Evaluate how the development of social workers is sufficient in defining leadership. This research intends to reframe the misconception that social workers do not possess the capacity and skills to be effective leaders. On the contrary, social work encompasses a framework dedicated to lifelong development and growth. Social workers must be skilled, competent, ethical, supportive, and empathic. These are all qualities and traits of effective leadership, whereas leaders are in relation with others and embody partnership and collaboration with followers and stakeholders. The proposed study is a cross-sectional quasi-experimental survey design that will include the distribution of a multi-level social work leadership model and assessment tool. The assessment tool aims to help define leadership in social work using a Likert scale model. A cross-sectional research design is appropriate for answering the research questions because the measurement survey will help gather data using a structured tool. Other than the proposed social work leadership measurement tool, there is no other mechanism based on social work theory and designed to measure the capacity and skill of social work leadership.

Keywords: leadership competencies, leadership education, multi-level social work leadership model, social work core values, social work leadership, social work leadership education, social work leadership measurement tool

Procedia PDF Downloads 159

Authors: Mustafa Alhamdi

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Industrial application to classify gamma rays and neutron events is investigated in this study using deep machine learning. The identification using a convolutional neural network and recursive neural network showed a significant improvement in predication accuracy in a variety of applications. The ability to identify the isotope type and activity from spectral information depends on feature extraction methods, followed by classification. The features extracted from the spectrum profiles try to find patterns and relationships to present the actual spectrum energy in low dimensional space. Increasing the level of separation between classes in feature space improves the possibility to enhance classification accuracy. The nonlinear nature to extract features by neural network contains a variety of transformation and mathematical optimization, while principal component analysis depends on linear transformations to extract features and subsequently improve the classification accuracy. In this paper, the isotope spectrum information has been preprocessed by finding the frequencies components relative to time and using them as a training dataset. Fourier transform implementation to extract frequencies component has been optimized by a suitable windowing function. Training and validation samples of different isotope profiles interacted with CdTe crystal have been simulated using Geant4. The readout electronic noise has been simulated by optimizing the mean and variance of normal distribution. Ensemble learning by combing voting of many models managed to improve the classification accuracy of neural networks. The ability to discriminate gamma and neutron events in a single predication approach using deep machine learning has shown high accuracy using deep learning. The paper findings show the ability to improve the classification accuracy by applying the spectrogram preprocessing stage to the gamma and neutron spectrums of different isotopes. Tuning deep machine learning models by hyperparameter optimization of neural network models enhanced the separation in the latent space and provided the ability to extend the number of detected isotopes in the training database. Ensemble learning contributed significantly to improve the final prediction.

Keywords: machine learning, nuclear physics, Monte Carlo simulation, noise estimation, feature extraction, classification

Procedia PDF Downloads 137

Authors: Ece Cigdem Mutlu, Burak Alakent

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Maintaining the quality of manufactured products at a desired level depends on the stability of process dispersion and location parameters and detection of perturbations in these parameters as promptly as possible. Shewhart control chart is the most widely used technique in statistical process monitoring to monitor the quality of products and control process mean and variability. In the application of Xbar control charts, sample standard deviation and sample mean are known to be the most efficient conventional estimators in determining process dispersion and location parameters, respectively, based on the assumption of independent and normally distributed datasets. On the other hand, there is no guarantee that the real-world data would be normally distributed. In the cases of estimated process parameters from Phase I data clouded with outliers, efficiency of traditional estimators is significantly reduced, and performance of Xbar charts are undesirably low, e.g. occasional outliers in the rational subgroups in Phase I data set may considerably affect the sample mean and standard deviation, resulting a serious delay in detection of inferior products in Phase II. For more efficient application of control charts, it is required to use robust estimators against contaminations, which may exist in Phase I. In the current study, we present a simple approach to construct robust Xbar control charts using average distance to the median, Qn-estimator of scale, M-estimator of scale with logistic psi-function in the estimation of process dispersion parameter, and Harrell-Davis qth quantile estimator, Hodge-Lehmann estimator and M-estimator of location with Huber psi-function and logistic psi-function in the estimation of process location parameter. Phase I efficiency of proposed estimators and Phase II performance of Xbar charts constructed from these estimators are compared with the conventional mean and standard deviation statistics both under normality and against diffuse-localized and symmetric-asymmetric contaminations using 50,000 Monte Carlo simulations on MATLAB. Consequently, it is found that robust estimators yield parameter estimates with higher efficiency against all types of contaminations, and Xbar charts constructed using robust estimators have higher power in detecting disturbances, compared to conventional methods. Additionally, utilizing individuals charts to screen outlier subgroups and employing different combination of dispersion and location estimators on subgroups and individual observations are found to improve the performance of Xbar charts.

Keywords: average run length, M-estimators, quality control, robust estimators

Procedia PDF Downloads 178

Authors: Bruno Cossu, Elio Carlo

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The invention (patent pending) relates to the field of devices aimed to harness wave energy (WEC) especially for artificial upwelling, forced downwelling, production of compressed air. In its basic form, the pump consists of a hydro-pneumatic machine, driven by wave energy, characterised by the fact that it has no moving mechanical parts, and is made up of only two structural components: an hollow body, which is open at the bottom to the sea and partially immersed in sea water, and a tube, both joined together to form a single body. The shape of the hollow body is like a mushroom whose cap and stem are hollow; the stem is open at both ends and the lower part of its surface is crossed by holes; the tube is external and coaxial to the stem and is joined to it so as to form a single body. This shape of the hollow body and the type of connection to the tube allows the pump to operate simultaneously as an air compressor (OWC) on the cap side, and as an airlift on the stem side. The pump can be implemented in four versions, each of which provides different variants and methods of implementation: 1) firstly, for the artificial upwelling of cold, deep ocean water; 2) secondly, for the lifting and transfer of these waters to the place of use (above all, fish farming plants), even if kilometres away; 3) thirdly, for the forced downwelling of surface sea water; 4) fourthly, for the forced downwelling of surface water, its oxygenation, and the simultaneous production of compressed air. The transfer of the deep water or the downwelling of the raised surface water (as for pump versions indicated in points 2 and 3 above), is obtained by making the water raised by the airlift flow into the upper inlet of another pipe, internal or adjoined to the airlift; the downwelling of raised surface water, oxygenation, and the simultaneous production of compressed air (as for the pump version indicated in point 4), is obtained by installing a venturi tube on the upper end of the pipe, whose restricted section is connected to the external atmosphere, so that it also operates like a hydraulic air compressor (trompe). Furthermore, by combining one or more pumps for the upwelling of cold, deep water, with one or more pumps for the downwelling of the warm surface water, the system can be used in an Ocean Thermal Energy Conversion plant to supply the cold and the warm water required for the operation of the same, thus allowing to use, without increased costs, in addition to the mechanical energy of the waves, for the purposes indicated in points 1 to 4, the thermal one of the marine water treated in the process.

Keywords: air lifted upwelling, fish farming plant, hydraulic air compressor, wave energy converter

Procedia PDF Downloads 136

Authors: Hoda Manafian, Stephen Holland

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Problem statement: Rural areas in Iran are one of the most popular tourism destinations. Abyaneh Village is one of them with a long history behind it (more than 1500 years) which is a national heritage site and also is nominated as a world heritage site in UNESCO tentative list from 2007. There is a considerable foundation of religious-cultural heritage and also agricultural history and activities. However, this heritage site suffers from mass tourism which is beyond its social and physical carrying capacity, since the annual number of tourists exceed 500,000. While there are four adjacent villages around Abyaneh which can benefit from advantages of tourism. Local managers also can at the same time prorate the tourists’ flux of Abyaneh on those other villages especially in high-season. The other villages have some cultural and natural tourism attractions as well. Goal: The main goal of this study is to identify a feasible development strategy according to the current strengths, weaknesses, opportunities and threats of rural tourism in this area (Abyaneh Village and four adjacent villages). This development strategy can lead to sustainable management of these destinations. Method: To this end, we used SWOT analysis as a well-established tool for conducting a situational analysis to define a sustainable development strategy. The procedures included following steps: 1) Extracting variables of SWOT chart based on interviewing tourism experts (n=13), local elites (n=17) and personal observations of researcher. 2) Ranking the extracted variables from 1-5 by 13 tourism experts in Isfahan Cultural Heritage, Handcrafts and Tourism Organization (ICHTO). 3) Assigning weights to the ranked variables using Expert Choice Software and the method of Analytical Hierarchical Process (AHP). 4) Defining the Total Weighted Score (TWS) for each part of SWOT chart. 5) Identifying the strategic position according to the TWS 6) Selecting the best development strategy based on the defined position using the Strategic Position and Action Evaluation (SPACE) matrix. 7) Assessing the Probability of Strategic Success (PSS) for the preferred strategy using relevant formulas. 8) Defining two feasible alternatives for sustainable development. Results and recommendations: Cultural heritage attractions were first-ranked variable in strength chart and also lack of sufficient amenities for one-day tourists (catering, restrooms, parking, and accommodation) was firs-ranked weakness. The strategic position was in ST (Strength-Threat) quadrant which is a maxi-mini position. According this position we would suggest ‘Competitive Strategy’ as a development strategy which means relying on strengths in order to neutralization threats. The result of Probability of Strategic Success assessment which was 0.6 shows that this strategy could be successful. The preferred approach for competitive strategy could be rebranding the market of tourism in this area. Rebranding the market can be achieved by two main alternatives which are based on the current strengths and threats: 1) Defining a ‘Heritage Corridor’ from first adjacent village to Abyaneh as a final destination. 2) Focus on ‘educational tourism’ versus mass tourism and also green tourism by developing agritourism in that corridor.

Keywords: Abyaneh village, rural tourism, SWOT analysis, sustainable strategies

Procedia PDF Downloads 366

Authors: Hesam Gholami

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Elevated suspended sediment loads in riverine systems resulting from accelerated erosion due to human activities are a serious threat to the sustainable management of watersheds and ecosystem services therein worldwide. Therefore, mitigation of deleterious sediment effects as a distributed or non-point pollution source in the catchments requires reliable provenance information. Sediment tracing or sediment fingerprinting, as a combined process consisting of sampling, laboratory measurements, different statistical tests, and the application of mixing or unmixing models, is a useful technique for discriminating the sources of sediments. From 1996 to the present, different aspects of this technique, such as grouping the sources (spatial and individual sources), discriminating the potential sources by different statistical techniques, and modification of mixing and unmixing models, have been introduced and modified by many researchers worldwide, and have been applied to identify the provenance of fine materials in agricultural, rural, mountainous, and coastal catchments, and in large catchments with numerous lakes and reservoirs. In the last two decades, efforts exploring the uncertainties associated with sediment fingerprinting results have attracted increasing attention. The frameworks used to quantify the uncertainty associated with fingerprinting estimates can be divided into three groups comprising Monte Carlo simulation, Bayesian approaches and generalized likelihood uncertainty estimation (GLUE). Given the above background, the primary goal of this study was to apply geochemical fingerprinting within the GLUE framework in the estimation of sub-basin spatial sediment source contributions in the arid Mehran River catchment in southern Iran, which drains into the Persian Gulf. The accuracy of GLUE predictions generated using four different sets of statistical tests for discriminating three sub-basin spatial sources was evaluated using 10 virtual sediments (VS) samples with known source contributions using the root mean square error (RMSE) and mean absolute error (MAE). Based on the results, the contributions modeled by GLUE for the western, central and eastern sub-basins are 1-42% (overall mean 20%), 0.5-30% (overall mean 12%) and 55-84% (overall mean 68%), respectively. According to the mean absolute fit (MAF; ≥ 95% for all target sediment samples) and goodness-of-fit (GOF; ≥ 99% for all samples), our suggested modeling approach is an accurate technique to quantify the source of sediments in the catchments. Overall, the estimated source proportions can help watershed engineers plan the targeting of conservation programs for soil and water resources.

Keywords: sediment source tracing, generalized likelihood uncertainty estimation, virtual sediment mixtures, Iran

Procedia PDF Downloads 64

Authors: M. Acin-Albiac, P. Filannino, R. Coda, Carlo G. Rizzello, M. Gobbetti, R. Di Cagno

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Demand for smart management of large amounts of agro-food by-products has become an area of major environmental and economic importance worldwide. Brewers' spent grain (BSG), the most abundant by-product generated in the beer-brewing process, represents an example of valuable raw material and source of health-promoting compounds. To the date, the valorization of BSG as a food ingredient has been limited due to poor technological and sensory properties. Tailored bioprocessing through lactic acid bacteria (LAB) fermentation is a versatile and sustainable means for the exploitation of food industry by-products. Indigestible carbohydrates (e.g., hemicelluloses and celluloses), high phenolic content, and mostly lignin make of BSG a hostile environment for microbial survival. Hence, the selection of tailored starters is required for successful fermentation. Our study investigated the metabolic strategies of Leuconostoc pseudomesenteroides and Lactobacillus plantarum strains to exploit BSG as a food ingredient. Two distinctive BSG samples from different breweries (Italian IT- and Finish FL-BSG) were microbially and chemically characterized. Growth kinetics, organic acid profiles, and the evolution of phenolic profiles during the fermentation in two BSG model media were determined. The results were further complemented with gene expression targeting genes involved in the degradation cellulose, hemicelluloses building blocks, and the metabolism of anti-nutritional factors. Overall, the results were LAB genus dependent showing distinctive metabolic capabilities. Leuc. pseudomesenteroides DSM 20193 may degrade BSG xylans while sucrose metabolism could be furtherly exploited for extracellular polymeric substances (EPS) production to enhance BSG pro-technological properties. Although L. plantarum strains may follow the same metabolic strategies during BSG fermentation, the mode of action to pursue such strategies was strain-dependent. L. plantarum PU1 showed a great preference for β-galactans compared to strain WCFS1, while the preference for arabinose occurred at different metabolic phases. Phenolic compounds profiling highlighted a novel metabolic route for lignin metabolism. These findings will allow an improvement of understanding of how lactic acid bacteria transform BSG into economically valuable food ingredients.

Keywords: brewery by-product valorization, metabolism of plant phenolics, metabolism of lactic acid bacteria, gene expression

Procedia PDF Downloads 117

Authors: Nancy A. Delich, Stephen D. Roberts

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This case study explores using self-efficacy theory in counseling deaf and hard of hearing students in one California school district. Self-efficacy is described as the confidence a student has for performing a set of skills required to succeed at a specific task. When students need to learn a skill, self-efficacy can be a major factor in influencing behavioral change. Self-efficacy is domain specific, meaning that students can have high confidence in their abilities to accomplish a task in one domain, while at the same time having low confidence in their abilities to accomplish another task in a different domain. The communication isolation experienced by deaf and hard of hearing children and adolescents can negatively impact their belief about their ability to navigate life challenges. There is a need to address issues that impact deaf and hard of hearing students’ social-emotional development. Failure to address these needs may result in depression, suicidal ideation, and anxiety among other mental health concerns. Self-efficacy training can be used to address these socio-emotional developmental issues with this population. Four sources of experiences are applied during an intervention: (a) enactive mastery experience, (b) vicarious experience, (c) verbal persuasion, and (d) physiological and affective states. This case study describes the use of self-efficacy training with a coed group of 12 deaf and hard of hearing high school students who experienced bullying at school. Beginning with enactive mastery experience, the counselor introduced the topic of bullying to the group. The counselor educated the students about the different types of bullying while teaching them the terminology, signs and their meanings. The most effective way to increase self-efficacy is through extensive practice. To better understand these concepts, the students practiced through role-playing with the goal of developing self-advocacy skills. Vicarious experience is the perception that students have about their capabilities. Viewing other students advocating for themselves, cognitively rehearsing what actions they will and will not take, and teaching each other how to stand up against bullying can strengthen their belief in successfully overcoming bullying. The third source of self-efficacy beliefs is verbal persuasion. It occurs when others express belief in the capabilities of the student. Didactic training and pedagogic materials on bullying were employed as part of the group counseling sessions. The fourth source of self-efficacy appraisals is physiological and affective states. Students expect positive emotions to be associated with successful skilled performance. When students practice new skills, the counselor can apply several strategies to enhance self-efficacy while reducing and controlling emotional and physical states. The intervention plan incorporated all four sources of self-efficacy training during several interactive group sessions regarding bullying. There was an increased understanding around the issues of bullying, resulting in the students’ belief of their ability to perform protective behaviors and deter future occurrences. The outcome of the intervention plan resulted in a reduction of reported bullying incidents. In conclusion, self-efficacy training can be an effective counseling and teaching strategy in addressing and enhancing the social-emotional functioning with deaf and hard of hearing adolescents.

Keywords: counseling, self-efficacy, bullying, social-emotional development, mental health, deaf and hard of hearing students

Procedia PDF Downloads 339

Authors: G. Battistoni, F. Collamati, E. De Lucia, R. Faccini, C. Mancini-Terracciano, M. Marafini, I. Mattei, S. Muraro, V. Patera, A. Sarti, A. Sciubba, E. Solfaroli Camillocci, M. Toppi, G. Traini, S. M. Valle, C. Voena

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Accelerated charged particles, mainly protons and carbon ions, are presently used in Particle Therapy (PT) to treat solid tumors. The precision of PT exploiting the charged particle high localized dose deposition in tissues and biological effectiveness in killing cancer cells demands for an online dose monitoring technique, crucial to improve the quality assurance of treatments: possible patient mis-positionings and biological changes with respect to the CT scan could negatively affect the therapy outcome. In PT the beam range confined in the irradiated target can be monitored thanks to the secondary radiation produced by the interaction of the projectiles with the patient tissue. The Dose Profiler (DP) is a novel device designed to track charged secondary particles and reconstruct their longitudinal emission distribution, correlated to the Bragg peak position. The feasibility of this approach has been demonstrated by dedicated experimental measurements. The DP has been developed in the framework of the INSIDE project, MIUR, INFN and Centro Fermi, Museo Storico della Fisica e Centro Studi e Ricerche 'E. Fermi', Roma, Italy and will be tested at the Proton Therapy center of Trento (Italy) within the end of 2017. The DP combines a tracker, made of six layers of two-view scintillating fibers with square cross section (0.5 x 0.5 mm2) with two layers of two-view scintillating bars (section 12.0 x 0.6 mm2). The electronic readout is performed by silicon photomultipliers. The sensitive area of the tracking planes is 20 x 20 cm2. To optimize the detector layout, a Monte Carlo (MC) simulation based on the FLUKA code has been developed. The complete DP geometry and the track reconstruction code have been fully implemented in the MC. In this contribution, the DP hardware will be described. The expected detector performance computed using a dedicated simulation of a 220 MeV/u carbon ion beam impinging on a PMMA target will be presented, and the result will be discussed in the standard clinical application framework. A possible procedure for real-time beam range monitoring is proposed, following the expectations in actual clinical operation.

Keywords: online range monitoring, particle therapy, quality assurance, tracking detector

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Authors: Yi H. Wong, Li L. Chan, Chee O. Leong, Stephen Ambu, Joon W. Mak, Priyadashi S. Sahu

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Background: Acanthamoeba is a free-living opportunistic protist which is ubiquitously distributed in the environment. Virulent Acanthamoeba can cause fatal encephalitis in immunocompromised patients and potential blinding keratitis in immunocompetent contact lens wearers. Approximately 24 species have been identified but only the A. castellanii, A. polyphaga and A. culbertsoni are commonly associated with human infections. Until to date, the precise molecular basis for Acanthamoeba pathogenesis remains unclear. Previous studies reported that Acanthamoeba virulence can be diminished through prolonged axenic culture but revived through serial mouse passages. As no clear explanation on this reversible pathogenesis is established, hereby, we postulate that the epigenetic regulators, DNA-methyltransferases (DNMT) and histone-deacetylases (HDAC), could possibly be involved in granting the virulence plasticity of Acanthamoeba spp. Methods: Four rounds of mouse passages were conducted to revive the virulence potential of the virulence-attenuated Acanthamoeba castellanii strain (ATCC 50492). Briefly, each mouse (n=6/group) was inoculated intraperitoneally with Acanthamoebae cells (2x 105 trophozoites/mouse) and incubated for 2 months. Acanthamoebae cells were isolated from infected mouse organs by culture method and subjected to subsequent mouse passage. In vitro cytopathic, encystment and gelatinolytic assays were conducted to evaluate the virulence characteristics of Acanthamoebae isolates for each passage. PCR primers which targeted on the 2 members (DNMT1 and DNMT2) and 5 members (HDAC1 to 5) of the DNMT and HDAC gene families respectively were custom designed. Quantitative real-time PCR (qPCR) was performed to detect and quantify the relative expression of the two gene families in each Acanthamoeba isolates. Beta-tubulin of A. castellanii (Genbank accession no: XP_004353728) was included as housekeeping gene for data normalisation. PCR mixtures were also analyzed by electrophoresis for amplicons detection. All statistical analyses were performed using the paired one-tailed Student’s t test. Results: Our pathogenicity tests showed that the virulence-reactivated Acanthamoeba had a higher degree of cytopathic effect on vero cells, a better resistance to encystment challenge and a higher gelatinolytic activity which was catalysed by serine protease. qPCR assay showed that DNMT1 expression was significantly higher in the virulence-reactivated compared to the virulence-attenuated Acanthamoeba strain (p ≤ 0.01). The specificity of primers which targeted on DNMT1 was confirmed by sequence analysis of PCR amplicons, which showed a 97% similarity to the published DNA-methyltransferase gene of A. castellanii (GenBank accession no: XM_004332804.1). Out of the five primer pairs which targeted on the HDAC family genes, only HDAC4 expression was significantly difference between the two variant strains. In contrast to DNMT1, HDAC4 expression was much higher in the virulence-attenuated Acanthamoeba strain. Conclusion: Our mouse passages had successfully restored the virulence of the attenuated strain. Our findings suggested that DNA-methyltransferase (DNMT1) and histone deacetylase (HDAC4) expressions are associated with virulence potential of Acanthamoeba spp.

Keywords: acanthamoeba, DNA-methyltransferase, histone deacetylase, virulence-associated proteins

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Authors: Kristina Pflug, Markus Busch

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Being able to predict polymer properties and processing behavior based on the applied operating reaction conditions in one of the key challenges in modern polymer reaction engineering. Especially, for cost-intensive processes such as the high-pressure polymerization of low-density polyethylene (LDPE) with high safety-requirements, the need for simulation-based process optimization and product design is high. A multi-scale modelling approach was set-up and validated via a series of high-pressure mini-plant autoclave reactor experiments. The approach starts with the numerical modelling of the complex reaction network of the LDPE polymerization taking into consideration the actual reaction conditions. While this gives average product properties, the complex polymeric microstructure including random short- and long-chain branching is calculated via a hybrid Monte Carlo-approach. Finally, the processing behavior of LDPE -its melt flow behavior- is determined in dependence of the previously determined polymeric microstructure using the branch on branch algorithm for randomly branched polymer systems. All three steps of the multi-scale modelling approach can be independently validated against analytical data. A triple-detector GPC containing an IR, viscosimetry and multi-angle light scattering detector is applied. It serves to determine molecular weight distributions as well as chain-length dependent short- and long-chain branching frequencies. 13C-NMR measurements give average branching frequencies, and rheological measurements in shear and extension serve to characterize the polymeric flow behavior. The accordance of experimental and modelled results was found to be extraordinary, especially taking into consideration that the applied multi-scale modelling approach does not contain parameter fitting of the data. This validates the suggested approach and proves its universality at the same time. In the next step, the modelling approach can be applied to other reactor types, such as tubular reactors or industrial scale. Moreover, sensitivity analysis for systematically varying process conditions is easily feasible. The developed multi-scale modelling approach finally gives the opportunity to predict and design LDPE processing behavior simply based on process conditions such as feed streams and inlet temperatures and pressures.

Keywords: low-density polyethylene, multi-scale modelling, polymer properties, reaction engineering, rheology

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Authors: Leonie Bradfield, Stephen Fityus, John Simmons

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The shearing behavior of current and planned coal mine spoil dumps up to 400m in height is studied using large-sample-high-stress direct shear tests performed on a range of spoils common to the coalfields of Eastern Australia. The motivation for the study is to address industry concerns that some constructed spoil dump heights ( > 350m) are exceeding the scale ( ≤ 120m) for which reliable design information exists, and because modern geotechnical laboratories are not equipped to test representative spoil specimens at field-scale stresses. For more than two decades, shear strength estimation for spoil dumps has been based on either infrequent, very small-scale tests where oversize particles are scalped to comply with device specimen size capacity such that the influence of prototype-sized particles on shear strength is not captured; or on published guidelines that provide linear shear strength envelopes derived from small-scale test data and verified in practice by slope performance of dumps up to 120m in height. To date, these published guidelines appear to have been reliable. However, in the field of rockfill dam design there is a broad acceptance of a curvilinear shear strength envelope, and if this is applicable to coal mine spoils, then these industry-accepted guidelines may overestimate the strength and stability of dumps at higher stress levels. The pressing need to rationally define the shearing behavior of more representative spoil specimens at field-scale stresses led to the successful design, construction and operation of a large direct shear machine (LDSM) and its subsequent application to provide reliable design information for current and planned very-high dumps. The LDSM can test at a much larger scale, in terms of combined specimen size (720mm x 720mm x 600mm) and stress (σn up to 4.6MPa), than has ever previously been achieved using a direct shear machine for geotechnical testing of rockfill. The results of an extensive LDSM testing program on a wide range of coal-mine spoils are compared to a published framework that widely accepted by the Australian coal mining industry as the standard for shear strength characterization of mine spoil. A critical outcome is that the LDSM data highlights several non-compliant spoils, and stress-dependent shearing behavior, for which the correct application of the published framework will not provide reliable shear strength parameters for design. Shear strength envelopes developed from the LDSM data are also compared with dam engineering knowledge, where failure envelopes of rockfills are curved in a concave-down manner. The LDSM data indicates that shear strength envelopes for coal-mine spoils abundant with rock fragments are not in fact curved and that the shape of the failure envelope is ultimately determined by the strength of rock fragments. Curvilinear failure envelopes were found to be appropriate for soil-like spoils containing minor or no rock fragments, or hard-soil aggregates.

Keywords: coal mine, direct shear test, high dump, large scale, mine spoil, shear strength, spoil dump

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Authors: Danish Laidin, Peter Gostomski, Aaron Marshall, Carlo Carere

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Groundwater contamination of nitrate (NO3-) is becoming more prevalent in regions of intensive and extensive agricultural activities. Household nitrate removal involves using ion exchange membranes and reverse osmosis (RO) systems, whereas industrial nitrate removal may use organic carbon substrates (e.g. methanol) for heterotrophic microbial denitrification. However, these approaches both require high capital investment and operating costs. In this study, denitrification was demonstrated using bio-electrochemical systems (BESs) inoculated from sediments and microbial enrichment cultures. The BES reactors were operated continuously as microbial electrolytic cells (MECs) with a poised potential of -0.7V and -1.1V vs Ag/AgCl. Three parallel MECs were inoculated using hydrogen-driven denitrifying enrichments, stream sediments, and biofilm harvested from a denitrifying biotrickling filter, respectively. These reactors were continuously operated for over a year as various operating conditions were investigated to determine the optimal conditions for electroactive denitrification. The mass loading rate of nitrate was varied between 10 – 70 mg NO3-/d, and the maximum observed nitrate removal rate was 22 mg NO3- /(cm2∙d) with a current of 2.1 mA. For volumetric load experiments, the dilution rate of 1 mM NO3- feed was varied between 0.01 – 0.1 hr-1 to achieve a nitrate loading rate similar to the mass loading rate experiments. Under these conditions, the maximum rate of denitrification observed was 15.8 mg NO3- /(cm2∙d) with a current of 1.7mA. Hydrogen (H2) was supplied intermittently to investigate the hydrogenotrophic potential of the denitrifying biofilm electrodes. H2 supplementation at 0.1 mL/min resulted in an increase of nitrate removal from 0.3 mg NO3- /(cm2∙d) to 3.4 mg NO3- /(cm2∙d) in the hydrogenotrophically subcultured reactor but had no impact on the reactors which exhibited direct electron transfer properties. Results from this study depict the denitrification performance of the immobilized biofilm electrodes, either by direct electron transfer or hydrogen-driven denitrification, and the contribution of the planktonic cells present in the growth medium. Other results will include the microbial community analysis via 16s rDNA amplicon sequencing, varying the effect of poising cathodic potential from 0.7V to 1.3V vs Ag/AgCl, investigating the potential of using in-situ electrochemically produced hydrogen for autotrophic denitrification and adjusting the conductivity of the feed solution to mimic groundwater conditions. These findings highlight the overall performance of sediment inoculated MECs in removing nitrate and will be used for the future development of sustainable solutions for the treatment of nitrate polluted groundwater.

Keywords: bio-electrochemical systems, groundwater, electroactive denitrification, microbial electrolytic cell

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Authors: Stephen Tullis, M. David DiDonato, Hong Sung Park

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Rowing boats (shells) are often steered by a small rudder operated by one of the backward-facing rowers; the attention required of that athlete then slightly decreases the power that that athlete can provide. Reducing the steering distraction would then increase the overall boat speed. Races are straight 2000 m courses with each boat in a 13.5 m wide lane marked by small (~15 cm) widely-spaced (~10 m) buoys, and the boat trajectory is affected by both cross-currents and winds. An optical buoy recognition and tracking system has been developed that provides the boat’s location and orientation with respect to the lane edges. This information is provided to the steering athlete as either: a simple overlay on a video display, or fed to a simplified autopilot system giving steering directions to the athlete or directly controlling the rudder. The system is then effectively a “lane-assist” device but with small, widely-spaced lane markers viewed from a very shallow angle due to constraints on camera height. The image is captured with a lightweight 1080p webcam, and most of the image analysis is done in OpenCV. The colour RGB-image is converted to a grayscale using the difference of the red and blue channels, which provides good contrast between the red/yellow buoys and the water, sky, land background and white reflections and noise. Buoy detection is done with thresholding within a tight mask applied to the image. Robust linear regression using Tukey’s biweight estimator of the previously detected buoy locations is used to develop the mask; this avoids the false detection of noise such as waves (reflections) and, in particular, buoys in other lanes. The robust regression also provides the current lane edges in the camera frame that are used to calculate the displacement of the boat from the lane centre (lane location), and its yaw angle. The interception of the detected lane edges provides a lane vanishing point, and yaw angle can be calculated simply based on the displacement of this vanishing point from the camera axis and the image plane distance. Lane location is simply based on the lateral displacement of the vanishing point from any horizontal cut through the lane edges. The boat lane position and yaw are currently fed what is essentially a stripped down marine auto-pilot system. Currently, only the lane location is used in a PID controller of a rudder actuator with integrator anti-windup to deal with saturation of the rudder angle. Low Kp and Kd values decrease unnecessarily fast return to lane centrelines and response to noise, and limiters can be used to avoid lane departure and disqualification. Yaw is not used as a control input, as cross-winds and currents can cause a straight course with considerable yaw or crab angle. Mapping of the controller with rudder angle “overall effectiveness” has not been finalized - very large rudder angles stall and have decreased turning moments, but at less extreme angles the increased rudder drag slows the boat and upsets boat balance. The full system has many features similar to automotive lane-assist systems, but with the added constraints of the lane markers, camera positioning, control response and noise increasing the challenge.

Keywords: auto-pilot, lane-assist, marine, optical, rowing

Procedia PDF Downloads 118

Authors: Yi-Hao Wong, Li-Li Chan, Chee-Onn Leong, Stephen Ambu, Joon-Wah Mak, Priyasashi Sahu

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Background: Acanthamoeba is a genus of amoebae which lives as a free-living in nature or as a human pathogen that causes severe brain and eye infections. Virulence potential of Acanthamoeba is not constant and can change with growth conditions. DNA methylation, an epigenetic process which adds methyl groups to DNA, is used by eukaryotic cells, including several human parasites to control their gene expression. We used qPCR, siRNA gene silencing, and RNA sequencing (RNA-Seq) to study DNA-methyltransferase gene family (DNMT) in order to indicate the possibility of its involvement in programming Acanthamoeba virulence potential. Methods: A virulence-attenuated Acanthamoeba isolate (designation: ATCC; original isolate: ATCC 50492) was subjected to mouse passages to restore its pathogenicity; a virulence-reactivated isolate (designation: AC/5) was generated. Several established factors associated with Acanthamoeba virulence phenotype were examined to confirm the succession of reactivation process. Differential gene expression of DNMT between ATCC and AC/5 isolates was performed by qPCR. Silencing on DNMT gene expression in AC/5 isolate was achieved by siRNA duplex. Total RNAs extracted from ATCC, AC/5, and siRNA-treated (designation: si-146) were subjected to RNA-Seq for comparative transcriptomic analysis in order to identify the genome-wide effect of DNMT in regulating Acanthamoeba gene expression. qPCR was performed to validate the RNA-Seq results. Results: Physiological and cytophatic assays demonstrated an increased in virulence potential of AC/5 isolate after mouse passages. DNMT gene expression was significantly higher in AC/5 compared to ATCC isolate (p ≤ 0.01) by qPCR. si-146 duplex reduced DNMT gene expression in AC/5 isolate by 30%. Comparative transcriptome analysis identified the differentially expressed genes, with 3768 genes in AC/5 vs ATCC isolate; 2102 genes in si-146 vs AC/5 isolate and 3422 genes in si-146 vs ATCC isolate, respectively (fold-change of ≥ 2 or ≤ 0.5, p-value adjusted (padj) < 0.05). Of these, 840 and 1262 genes were upregulated and downregulated, respectively, in si-146 vs AC/5 isolate. Eukaryotic orthologous group (KOG) assignments revealed a higher percentage of downregulated gene expression in si-146 compared to AC/5 isolate, were related to posttranslational modification, signal transduction and energy production. Gene Ontology (GO) terms for those downregulated genes shown were associated with transport activity, oxidation-reduction process, and metabolic process. Among these downregulated genes were putative genes encoded for heat shock proteins, transporters, ubiquitin-related proteins, proteins for vesicular trafficking (small GTPases), and oxidoreductases. Functional analysis of similar predicted proteins had been described in other parasitic protozoa for their survival and pathogenicity. Decreased expression of these genes in si146-treated isolate may account in part for Acanthamoeba reduced pathogenicity. qPCR on 6 selected genes upregulated in AC/5 compared to ATCC isolate corroborated the RNA sequencing findings, indicating a good concordance between these two analyses. Conclusion: To the best of our knowledge, this study represents the first genome-wide analysis of DNA methylation and its effects on gene expression in Acanthamoeba spp. The present data indicate that DNA methylation has substantial effect on global gene expression, allowing further dissection of the genome-wide effects of DNA-methyltransferase gene in regulating Acanthamoeba pathogenicity.

Keywords: Acanthamoeba, DNA methylation, RNA sequencing, virulence

Procedia PDF Downloads 184

Authors: Majed Al Otaibi, Melissa Lessard-Beaudoin, Amel Loudghi, Raphael Chouinard-Watkins, Melanie Plourde, Frederic Calon, C. Alexandre Castellano, Stephen Cunnane, Helene Payette, Pierrette Gaudreau, Denis Gris, Rona K. Graham

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Introduction: Alzheimer disease (AD) is a chronic disorder that affects millions of individuals worldwide. Symptoms include memory dysfunction, and also alterations in attention, planning, language and overall cognitive function. Olfactory dysfunction is a common symptom of several neurological disorders including AD. Studying the mechanisms underlying the olfactory dysfunction may therefore lead to the discovery of potential biomarkers and/or treatments for neurodegenerative diseases. Objectives: To determine if olfactory dysfunction predicts future cognitive impairment in the aging population and to characterize the olfactory system in a murine model expressing a genetic factor of AD. Method: For the human study, quantitative olfactory tests (UPSIT and OMT) have been done on 93 subjects (aged 80 to 94 years) from the Quebec Longitudinal Study on Nutrition and Successful Aging (NuAge) cohort accepting to participate in the ORCA secondary study. The telephone Modified Mini Mental State examination (t-MMSE) was used to assess cognition levels, and an olfactory self-report was also collected. In a separate cohort, olfactory cortical volume was calculated using MRI results from healthy old adults (n=25) and patients with AD (n=18) using the AAL single-subject atlas and performed with the PNEURO tool (PMOD 3.7). For the murine study, we are using Western blotting, RT-PCR and immunohistochemistry. Result: Human Study: Based on the self-report, 81% of the participants claimed to not suffer from any problem with olfaction. However, based on the UPSIT, 94% of those subjects showed a poor olfactory performance and different forms of microsmia. Moreover, the results confirm that olfactory function declines with age. We also detected a significant decrease in olfactory cortical volume in AD individuals compared to controls. Murine study: Preliminary data demonstrate there is a significant decrease in expression levels of the proform of caspase-3 and the caspase substrate STK3, in the olfactory bulb of mice expressing human APOE4 compared with controls. In addition, there is a significant decrease in the expression level of the caspase-9 proform and caspase-8 active fragment. Analysis of the mature neuron marker, NeuN, shows decreased expression levels of both isoforms. The data also suggest that Iba-1 immunostaining is increased in the olfactory bulb of APOE4 mice compared to wild type mice. Conclusions: The activation of caspase-3 may be the cause of the decreased levels of STK3 through caspase cleavage and may play role in the inflammation observed. In the clinical study, our results suggest that seniors are unaware of their olfactory function status and therefore it is not sufficient to measure olfaction using the self-report in the elderly. Studying olfactory function and cognitive performance in the aging population will help to discover biomarkers in the early stage of the AD.

Keywords: Alzheimer's disease, APOE4, cognition, caspase, brain atrophy, neurodegenerative, olfactory dysfunction

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Authors: Jayden R. Hunter, Brett A. Gordon, Stephen R. Bird, Amanda C. Benson

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The World Health Organisation recognises the workplace as an important setting for exercise promotion, with potential benefits including improved employee health and fitness, and reduced worker absenteeism and presenteeism. Despite these potential benefits to both employee and employer, there is a lack of evidence supporting the long-term effectiveness of workplace exercise programs. There is, therefore, a need for better-informed programs that cater to employee exercise preferences. Specifically, workplace exercise programs should address any time, motivation, internal and external barriers to participation reported by sub-groups of employees. This study sought to compare exercise participation to perceived barriers and facilitators to workplace exercise engagement of university employees. This information is needed to design and implement wider-reaching programs aiming to maximise long-term employee exercise adherence and subsequent health, fitness and productivity benefits. An online survey was advertised at an Australian university with the potential to reach 3,104 full-time employees. Along with exercise participation (International physical activity questionnaire) and behaviour (stage of behaviour change in relation to physical activity questionnaire), perceived barriers (corporate exercise barriers scale) and facilitators to workplace exercise participation were identified. The survey response rate was 8.1% (252 full-time employees; 95% white-collar; 60% female; 79.4% aged 30–59 years; 57% professional and 38% academic). Most employees reported meeting (43.7%) or exceeding (42.9%) exercise guidelines over the previous week (i.e. ⩾30 min of moderate-intensity exercise on most days or ⩾ 25 min of vigorous-intensity exercise on at least three days per week). Reported exercise behaviour over the previous six months showed that 64.7% of employees were in maintenance, 8.3% were in action, 10.9% were in preparation, 12.4% were in contemplation, and 3.8% were in the pre-contemplation stage of change. Perceived barriers towards workplace exercise participation were significantly higher in employees not attaining weekly exercise guidelines compared to employees meeting or exceeding guidelines, including a lack of time or reduced motivation (p < 0.001; partial eta squared = 0.24 (large effect)), exercise attitude (p < 0.05; partial eta squared = 0.04 (small effect)), internal (p < 0.01; partial eta squared = 0.10 (moderate effect)) and external (p < 0.01; partial eta squared = 0.06 (moderate effect)) barriers. The most frequently reported exercise facilitators were personal training (particularly for insufficiently active employees; 33%) and group exercise classes (20%). The most frequently cited preferred modes of exercise were walking (70%), swimming (50%), gym (48%), and cycling (45%). In conclusion, providing additional means of support such as individualised gym, swimming and cycling programs with personal supervision and guidance may be particularly useful for employees not meeting recommended moderate-vigorous volumes of exercise, to help overcome reported exercise barriers in order to improve participation, health, and fitness. While individual biopsychosocial factors should be considered when making recommendations for interventions, the specific barriers and facilitators to workplace exercise participation identified by this study can inform the development of workplace exercise programs aiming to broaden employee engagement and promote greater ongoing exercise adherence. This is especially important for the uptake of less active employees who perceive greater barriers to workplace exercise participation than their more active colleagues.

Keywords: exercise barriers, exercise facilitators, physical activity, workplace health

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Authors: Richard McGregor, Carmen Reaiche, Stephen Boyle

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Cyber threats are a relatively recent phenomenon and offer cyber insurers a dynamic and intelligent peril. As individuals en mass become increasingly digitally dependent, Personal Cyber Insurance (PCI) offers an attractive option to mitigate cyber risk at a personal level. This abstract proposes a literature review that conceptualises a framework for siting Personal Cyber Insurance (PCI) within the context of cyberspace. The lack of empirical research within this domain demonstrates an immediate need to define the scope of PCI to allow cyber insurers to understand personal cyber risk threats and vectors, customer awareness, capabilities, and their associated needs. Additionally, this will allow cyber insurers to conceptualise appropriate frameworks allowing effective management and distribution of PCI products and services within a landscape often in-congruent with risk attributes commonly associated with traditional personal line insurance products. Cyberspace has provided significant improvement to the quality of social connectivity and productivity during past decades and allowed enormous capability uplift of information sharing and communication between people and communities. Conversely, personal digital dependency furnish ample opportunities for adverse cyber events such as data breaches and cyber-attacksthus introducing a continuous and insidious threat of omnipresent cyber risk–particularly since the advent of the COVID-19 pandemic and wide-spread adoption of ‘work-from-home’ practices. Recognition of escalating inter-dependencies, vulnerabilities and inadequate personal cyber behaviours have prompted efforts by businesses and individuals alike to investigate strategies and tactics to mitigate cyber risk – of which cyber insurance is a viable, cost-effective option. It is argued that, ceteris parabus, the nature of cyberspace intrinsically provides characteristic peculiarities that pose significant and bespoke challenges to cyber insurers, often in-congruent with risk attributes commonly associated with traditional personal line insurance products. These challenges include (inter alia) a paucity of historical claim/loss data for underwriting and pricing purposes, interdependencies of cyber architecture promoting high correlation of cyber risk, difficulties in evaluating cyber risk, intangibility of risk assets (such as data, reputation), lack of standardisation across the industry, high and undetermined tail risks, and moral hazard among others. This study proposes a thematic overview of the literature deemed necessary to conceptualise the challenges to issuing personal cyber coverage. There is an evident absence of empirical research appertaining to PCI and the design of operational business models for this business domain, especially qualitative initiatives that (1) attempt to define the scope of the peril, (2) secure an understanding of the needs of both cyber insurer and customer, and (3) to identify elements pivotal to effective management and profitable distribution of PCI - leading to an argument proposed by the author that postulates that the traditional general insurance customer journey and business model are ill-suited for the lineaments of cyberspace. The findings of the review confirm significant gaps in contemporary research within the domain of personal cyber insurance.

Keywords: cyberspace, personal cyber risk, personal cyber insurance, customer journey, business model

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Authors: Michael Kenomore, Mohamed Hassan, Amjad Shah, Hom Dhakal

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Shale gas reservoirs have been of greater importance compared to shale oil reservoirs since 2009 and with the current nature of the oil market, understanding the technical and economic performance of shale gas reservoirs is of importance. Using the Barnett shale as a case study, an economic model was developed to quantify the effect of finding and development costs and gas prices on the basins in the Barnett shale using net present value as an evaluation parameter. A rate of return of 20% and a payback period of 60 months or less was used as the investment hurdle in the model. The Barnett was split into four basins (Strawn Basin, Ouachita Folded Belt, Forth-worth Syncline and Bend-arch Basin) with analysis conducted on each of the basin to provide a holistic outlook. The dataset consisted of only horizontal wells that started production from 2008 to at most 2015 with 1835 wells coming from the strawn basin, 137 wells from the Ouachita folded belt, 55 wells from the bend-arch basin and 724 wells from the forth-worth syncline. The data was analyzed initially on Microsoft Excel to determine the estimated ultimate recoverable (EUR). The range of EUR from each basin were loaded in the Palisade Risk software and a log normal distribution typical of Barnett shale wells was fitted to the dataset. Monte Carlo simulation was then carried out over a 1000 iterations to obtain a cumulative distribution plot showing the probabilistic distribution of EUR for each basin. From the cumulative distribution plot, the P10, P50 and P90 EUR values for each basin were used in the economic model. Gas production from an individual well with a EUR similar to the calculated EUR was chosen and rescaled to fit the calculated EUR values for each basin at the respective percentiles i.e. P10, P50 and P90. The rescaled production was entered into the economic model to determine the effect of the finding and development cost and gas price on the net present value (10% discount rate/year) as well as also determine the scenario that satisfied the proposed investment hurdle. The finding and development costs used in this paper (assumed to consist only of the drilling and completion costs) were £1 million, £2 million and £4 million while the gas price was varied from $2/MCF-$13/MCF based on Henry Hub spot prices from 2008-2015. One of the major findings in this study was that wells in the bend-arch basin were least economic, higher gas prices are needed in basins containing non-core counties and 90% of the Barnet shale wells were not economic at all finding and development costs irrespective of the gas price in all the basins. This study helps to determine the percentage of wells that are economic at different range of costs and gas prices, determine the basins that are most economic and the wells that satisfy the investment hurdle.

Keywords: shale gas, Barnett shale, unconventional gas, estimated ultimate recoverable

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Authors: Anastasia Constantinou, Stephen Morris

Abstract:

Background: The adoption of synchronous and asynchronous telemedicine modalities for primary care consultations has exponentially increased since the COVID-19 pandemic. However, there is limited understanding of how virtual consultations influence healthcare resource utilization and other quality measures including safety, timeliness, efficiency, patient and provider satisfaction, cost-effectiveness and environmental impact. Aim: Quantify the rate of follow-up visits, emergency department visits, hospitalizations, request for investigations and prescriptions and comment on the effect on different quality measures associated with different telemedicine modalities used for primary care services and primary care referrals to secondary care Design and setting: Systematic review in primary care Methods: A systematic search was carried out across three databases (Medline, PubMed and Scopus) between August and November 2023, using terms related to telemedicine, general practice, electronic referrals, follow-up, use and efficiency and supported by citation searching. This was followed by screening according to pre-defined criteria, data extraction and critical appraisal. Narrative synthesis and metanalysis of quantitative data was used to summarize findings. Results: The search identified 2230 studies; 50 studies are included in this review. There was a prevalence of asynchronous modalities in both primary care services (68%) and referrals from primary care to secondary care (83%), and most of the study participants were females (63.3%), with mean age of 48.2. The average follow-up for virtual consultations in primary care was 28.4% (eVisits: 36.8%, secure messages 18.7%, videoconference 23.5%) with no significant difference between them or F2F consultations. There was an average annual reduction of primary care visits by 0.09/patient, an increase in telephone visits by 0.20/patient, an increase in ED encounters by 0.011/patient, an increase in hospitalizations by 0.02/patient and an increase in out of hours visits by 0.019/patient. Laboratory testing was requested on average for 10.9% of telemedicine patients, imaging or procedures for 5.6% and prescriptions for 58.7% of patients. When looking at referrals to secondary care, on average 36.7% of virtual referrals required follow-up visit, with the average rate of follow-up for electronic referrals being higher than for videoconferencing (39.2% vs 23%, p=0.167). Technical failures were reported on average for 1.4% of virtual consultations to primary care. When using carbon footprint estimates, we calculate that the use of telemedicine in primary care services can potentially provide a net decrease in carbon footprint by 0.592kgCO2/patient/year. When follow-up rates are taken into account, we estimate that virtual consultations reduce carbon footprint for primary care services by 2.3 times, and for secondary care referrals by 2.2 times. No major concerns regarding quality of care, or patient satisfaction were identified. 5/7 studies that addressed cost-effectiveness, reported increased savings. Conclusions: Telemedicine provides quality, cost-effective, and environmentally sustainable care for patients in primary care with inconclusive evidence regarding the rates of subsequent healthcare utilization. The evidence is limited by heterogeneous, small-scale studies and lack of prospective comparative studies. Further research to identify the most appropriate telemedicine modality for different patient populations, clinical presentations, service provision (e.g. used to follow-up patients instead of initial diagnosis) as well as further education for patients and providers alike on how to make best use of this service is expected to improve outcomes and influence practice.

Keywords: telemedicine, healthcare utilisation, digital interventions, environmental impact, sustainable healthcare

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Authors: M. Bahari Mehrabani, Hua-Peng Chen

Abstract:

Management and maintenance of coastal defence structures during the expected life cycle have become a real challenge for decision makers and engineers. Accurate evaluation of the current condition and future performance of flood defence structures is essential for effective practical maintenance strategies on the basis of available field inspection data. Moreover, as coastal defence structures age, it becomes more challenging to implement maintenance and management plans to avoid structural failure. Therefore, condition inspection data are essential for assessing damage and forecasting deterioration of ageing flood defence structures in order to keep the structures in an acceptable condition. The inspection data for flood defence structures are often collected using discrete visual condition rating schemes. In order to evaluate future condition of the structure, a probabilistic deterioration model needs to be utilised. However, existing deterioration models may not provide a reliable prediction of performance deterioration for a long period due to uncertainties. To tackle the limitation, a time-dependent condition-based model associated with a transition probability needs to be developed on the basis of condition grade scheme for flood defences. This paper presents a probabilistic method for predicting future performance deterioration of coastal flood defence structures based on condition grading inspection data and deterioration curves estimated by expert judgement. In condition-based deterioration modelling, the main task is to estimate transition probability matrices. The deterioration process of the structure related to the transition states is modelled according to Markov chain process, and a reliability-based approach is used to estimate the probability of structural failure. Visual inspection data according to the United Kingdom Condition Assessment Manual are used to obtain the initial condition grade curve of the coastal flood defences. The initial curves then modified in order to develop transition probabilities through non-linear regression based optimisation algorithms. The Monte Carlo simulations are then used to evaluate the future performance of the structure on the basis of the estimated transition probabilities. Finally, a case study is given to demonstrate the applicability of the proposed method under no-maintenance and medium-maintenance scenarios. Results show that the proposed method can provide an effective predictive model for various situations in terms of available condition grading data. The proposed model also provides useful information on time-dependent probability of failure in coastal flood defences.

Keywords: condition grading, flood defense, performance assessment, stochastic deterioration modelling

Procedia PDF Downloads 223

Authors: Mohammed El Raey, Moustafa Osman Mohammed

Abstract:

The spatial-ecological modeling is relating sustainable dispersions with social development. Sustainability with spatial-ecological model gives attention to urban environments in the design review management to comply with Earth’s System. Naturally exchange patterns of ecosystems have consistent and periodic cycles to preserve energy flows and materials in Earth’s System. The probabilistic risk assessment (PRA) technique is utilized to assess the safety of industrial complex. The other analytical approach is the Failure-Safe Mode and Effect Analysis (FMEA) for critical components. The plant safety parameters are identified for engineering topology as employed in assessment safety of industrial ecology. In particular, the most severe accidental release of hazardous gaseous is postulated, analyzed and assessment in industrial region. The IAEA- safety assessment procedure is used to account the duration and rate of discharge of liquid chlorine. The ecological model of plume dispersion width and concentration of chlorine gas in the downwind direction is determined using Gaussian Plume Model in urban and ruler areas and presented with SURFER®. The prediction of accident consequences is traced in risk contour concentration lines. The local greenhouse effect is predicted with relevant conclusions. The spatial-ecological model is also predicted the distribution schemes from the perspective of pollutants that considered multiple factors of multi-criteria analysis. The data extends input–output analysis to evaluate the spillover effect, and conducted Monte Carlo simulations and sensitivity analysis. Their unique structure is balanced within “equilibrium patterns”, such as the biosphere and collective a composite index of many distributed feedback flows. These dynamic structures are related to have their physical and chemical properties and enable a gradual and prolonged incremental pattern. While this spatial model structure argues from ecology, resource savings, static load design, financial and other pragmatic reasons, the outcomes are not decisive in artistic/ architectural perspective. The hypothesis is an attempt to unify analytic and analogical spatial structure for development urban environments using optimization software and applied as an example of integrated industrial structure where the process is based on engineering topology as optimization approach of systems ecology.

Keywords: spatial-ecological modeling, spatial structure orientation impact, composite structure, industrial ecology

Procedia PDF Downloads 66

Authors: Nejoud Alostad, Anup Bora, Prashant Dhote

Abstract:

Kuwait Oil Company (KOC) has been producing from its major reservoirs that are well defined and highly productive and of superior reservoir quality. These reservoirs are maturing and priority is shifting towards difficult reservoir to meet future production requirements. This paper discusses the results of the detailed integrated study for one of the satellite complex field discovered in the early 1960s. Following acquisition of new 3D seismic data in 1998 and re-processing work in the year 2006, an integrated G&G study was undertaken to review Lower Cretaceous prospectivity of this reservoir. Nine wells have been drilled in the area, till date with only three wells showing hydrocarbons in two formations. The average oil density is around 300API (American Petroleum Institute), and average porosity and water saturation of the reservoir is about 23% and 26%, respectively. The area is dissected by a number of NW-SE trending faults. Structurally, the area consists of horsts and grabens bounded by these faults and hence compartmentalized. The Wara/Burgan formation consists of discrete, dirty sands with clean channel sand complexes. There is a dramatic change in Upper Wara distributary channel facies, and reservoir quality of Wara and Burgan section varies with change of facies over the area. So predicting reservoir facies and its quality out of sparse well data is a major challenge for delineating the prospective area. To characterize the reservoir of Wara/Burgan formation, an integrated workflow involving seismic, well, petro-physical, reservoir and production engineering data has been used. Porosity and water saturation models are prepared and analyzed to predict reservoir quality of Wara and Burgan 3rd sand upper reservoirs. Subsequently, boundary conditions are defined for reservoir and non-reservoir facies by integrating facies, porosity and water saturation. Based on the detailed analyses of volumetric parameters, potential volumes of stock-tank oil initially in place (STOIIP) and gas initially in place (GIIP) were documented after running several probablistic sensitivity analysis using Montecalro simulation method. Sensitivity analysis on probabilistic models of reservoir horizons, petro-physical properties, and oil-water contacts and their effect on reserve clearly shows some alteration in the reservoir geometry. All these parameters have significant effect on the oil in place. This study has helped to identify uncertainty and risks of this prospect particularly and company is planning to develop this area with drilling of new wells.

Keywords: original oil-in-place, sensitivity, uncertainty, sandstone, reservoir modeling, Monte-Carlo simulation

Procedia PDF Downloads 185