Search results for: Emmanuel Carlo Belara

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

Abstract:

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 294

Authors: Moustafa Osman Mohammed

Abstract:

The resilient and sustainable of construction ecology is essential to world’s socio-economic development. Environmental resilience is crucial in relating construction ecology to topology of spatial-economic model. Sustainability of spatial-economic model gives attention to green business to comply with Earth’s System for naturally exchange patterns of ecosystems. The systems ecology has consistent and periodic cycles to preserve energy and materials flow in Earth’s System. When model structure is influencing communication of internal and external features in system networks, it postulated the valence of the first-level spatial outcomes (i.e., project compatibility success). These instrumentalities are dependent on second-level outcomes (i.e., participant security satisfaction). These outcomes of model are based on measuring database efficiency, from 2015 to 2025. The model topology has state-of-the-art in value-orientation impact and correspond complexity of sustainability issues (e.g., build a consistent database necessary to approach spatial structure; construct the spatial-economic model; develop a set of sustainability indicators associated with model; allow quantification of social, economic and environmental impact; use the value-orientation as a set of important sustainability policy measures), and demonstrate environmental resilience. The model is managing and developing schemes from perspective of multiple sources pollutants through the input–output criteria. These criteria are evaluated the external insertions effects to conduct Monte Carlo simulations and analysis for using matrices in a unique spatial structure. The balance “equilibrium patterns” such as collective biosphere features, has a composite index of the distributed feedback flows. These feedback flows have a dynamic structure with physical and chemical properties for gradual prolong of incremental patterns. While these structures argue from system ecology, static loads are not decisive from an artistic/architectural perspective. The popularity of system resilience, in the systems structure related to ecology has not been achieved without the generation of confusion and vagueness. However, this topic is relevant to forecast future scenarios where industrial regions will need to keep on dealing with the impact of relative environmental deviations. The model attempts to unify analytic and analogical structure of urban environments using database software to integrate sustainability outcomes where the process based on systems topology of construction ecology.

Keywords: system ecology, construction ecology, industrial ecology, spatial-economic model, systems topology

Procedia PDF Downloads 19

Authors: Mustafa Alhamdi

Abstract:

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 150

Authors: Ece Cigdem Mutlu, Burak Alakent

Abstract:

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 190

Authors: Bruno Cossu, Elio Carlo

Abstract:

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 148

Authors: Hesam Gholami

Abstract:

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 74

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

Abstract:

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 129

Authors: Omolola Ojetayo, Emmanuel Garuba, Obinna Ajunwa, Abiodun A. Onilude

Abstract:

Introduction: Biofilm is a functional community of microorganisms that are associated with a surface or an interface. These adherent cells become embedded within an extracellular matrix composed of polymeric substances, i.e., biofilms refer to biological deposits consisting of both microbes and their extracellular products on biotic and abiotic surfaces. Despite their detrimental effects in medicine, biofilms as natural cell immobilization have found several applications in biotechnology, such as in the treatment of wastewater, bioremediation and biodegradation, desulfurization of gas, and conversion of agro-derived materials into alcohols and organic acids. The means of enhancing immobilized cells have been chemical-inductive, and this affects the medium composition and final product. Physical factors including electrical, magnetic, and electromagnetic flux have shown potential for enhancing biofilms depending on the bacterial species, nature, and intensity of emitted signals, the duration of exposure, and substratum used. However, the concept of cell immobilisation by electrical and magnetic induction is still underexplored. Methods: To assess the effects of physical factors on biofilm formation, six American typed culture collection (Acetobacter aceti ATCC15973, Pseudomonas aeruginosa ATCC9027, Serratia marcescens ATCC14756, Gluconobacter oxydans ATCC19357, Rhodobacter sphaeroides ATCC17023, and Bacillus subtilis ATCC6633) were used. Standard culture techniques for bacterial cells were adopted. Natural autoimmobilisation potentials of test bacteria were carried out by simple biofilms ring formation on tubes, while crystal violet binding assay techniques were adopted in the characterisation of biofilm quantity. Electroinduction of bacterial cells by direct current (DC) application in cell broth, static magnetic field exposure, and electromagnetic flux were carried out, and autoimmobilisation of cells in a biofilm pattern was determined on various substrata tested, including wood, glass, steel, polyvinylchloride (PVC) and polyethylene terephthalate. Biot Savart law was used in quantifying magnetic field intensity, and statistical analyses of data obtained were carried out using the analyses of variance (ANOVA) as well as other statistical tools. Results: Biofilm formation by the selected test bacteria was enhanced by the physical factors applied. Electromagnetic induction had the greatest effect on biofilm formation, with magnetic induction producing the least effect across all substrata used. Microbial cell-cell communication could be a possible means via which physical signals affected the cells in a polarisable manner. Conclusion: The enhancement of biofilm formation by bacteria using physical factors has shown that their inherent capability as a cell immobilization method can be further optimised for industrial applications. A possible relationship between the presence of voltage-dependent channels, mechanosensitive channels, and bacterial biofilms could shed more light on this phenomenon.

Keywords: bacteria, biofilm, cell immobilization, electromagnetic induction, substrata

Procedia PDF Downloads 189

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

Abstract:

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

Procedia PDF Downloads 240

Authors: Jocelyne Uwibambe, Ange Thaina Ndizeye, Dinah Ishimwe, Emmanuel Mugabo Byakagaba

Abstract:

Background: In low- and middle-income countries (LMICs), the use of modern contraceptive methods among women, including adolescents, is still low despite the desire to avoid pregnancy. In addition, countries have set a minimum age for marriage, which is 21 years for most countries, including Rwanda. The Rwandan culture, to a certain extent, and religion, to a greater extent, however, limit the freedom of young women to use contraceptive services because it is wrongly perceived as an encouragement for premarital sexual intercourse. In the end, what doesn’t change is that denying access to contraceptives to either male or female adolescents does not translate into preventing them from sexual activities, hence leading to an ever-increasing number of unwanted pregnancies, possible STIs, HIV, Human Papilloma Virus, and subsequent unsafe abortion followed by avoidable expensive complications. The purpose of this study is to evaluate the perception of healthcare providers regarding contraceptive use among adolescents. Methodology: This was a qualitative study. Interviews were done with different healthcare providers, including doctors, nurses, midwives, and pharmacists, through focused group discussions and in-depth interviews, then the audio was transcribed, translated and thematic coding was done. Results: This study explored the perceptions of healthcare workers regarding the provision of modern contraception to adolescents in Rwanda. The findings revealed that while healthcare providers had a good understanding of family planning and contraception, they were hesitant to provide contraception to adolescents. Sociocultural beliefs played a significant role in shaping their attitudes, as many healthcare workers believed that providing contraception to adolescents would encourage promiscuous behavior and go against cultural norms. Religious beliefs also influenced their reluctance, with some healthcare providers considering premarital sex and contraception as sinful. Lack of knowledge among parents and adolescents themselves was identified as a contributing factor to unwanted pregnancies, as inaccurate information from peers and social media influenced risky sexual behavior. Conditional policies, such as the requirement for parental consent, further hindered adolescents' access to contraception. The study suggested several solutions, including comprehensive sexual and reproductive health education, involving multiple stakeholders, ensuring easy access to contraception, and involving adolescents in policymaking. Overall, this research highlights the need for addressing sociocultural beliefs, improving healthcare providers' knowledge, and revisiting policies to ensure adolescents' reproductive health rights are met in Rwanda. Conclusion: The study highlights the importance of enhancing healthcare provider training, expanding access to modern contraception, implementing community-based interventions, and strengthening policy and programmatic support for adolescent contraception. Addressing these challenges is crucial for improving the provision of family planning services to adolescents in Rwanda and achieving the Sustainable Development Goals related to sexual and reproductive health. Collaborative efforts involving various stakeholders and organizations can contribute to overcoming these barriers and promoting the well-being of adolescents in Rwanda.

Keywords: adolescent, health care providers, contraception, reproductive health

Procedia PDF Downloads 50

Authors: Zahirah Dhurmeea, Iker Zudaire, Heidi Pethybridge, Emmanuel Chassot, Maria Cedras, Natacha Nikolic, Jerome Bourjea, Wendy West, Chandani Appadoo, Nathalie Bodin

Abstract:

Scientific advice on the status of fish stocks relies on indicators that are based on strong assumptions on biological parameters such as condition, maturity and fecundity. Currently, information on the biology of albacore tuna, Thunnus alalunga, in the Indian Ocean is scarce. Consequently, many parameters used in stock assessment models for Indian Ocean albacore originate largely from other studied stocks or species of tuna. Inclusion of incorrect biological data in stock assessment models would lead to inappropriate estimates of stock status used by fisheries manager’s to establish future catch allowances. The reproductive biology of albacore tuna in the western Indian Ocean was examined through analysis of the sex ratio, spawning season, length-at-maturity (L50), spawning frequency, fecundity and fish condition. In addition, the total lipid content (TL) and lipid class composition in the gonads, liver and muscle tissues of female albacore during the reproductive cycle was investigated. A total of 923 female and 867 male albacore were sampled from 2013 to 2015. A bias in sex-ratio was found in favour of females with fork length (LF) <100 cm. Using histological analyses and gonadosomatic index, spawning was found to occur between 10°S and 30°S, mainly to the east of Madagascar from October to January. Large females contributed more to reproduction through their longer spawning period compared to small individuals. The L50 (mean ± standard error) of female albacore was estimated at 85.3 ± 0.7 cm LF at the vitellogenic 3 oocyte stage maturity threshold. Albacore spawn on average every 2.2 days within the spawning region and spawning months from November to January. Batch fecundity varied between 0.26 and 2.09 million eggs and the relative batch fecundity (mean  standard deviation) was estimated at 53.4 ± 23.2 oocytes g-1 of somatic-gutted weight. Depending on the maturity stage, TL in ovaries ranged from 7.5 to 577.8 mg g-1 of wet weight (ww) with different proportions of phospholipids (PL), wax esters (WE), triacylglycerol (TAG) and sterol (ST). The highest TL were observed in immature (mostly TAG and PL) and spawning capable ovaries (mostly PL, WE and TAG). Liver TL varied from 21.1 to 294.8 mg g-1 (ww) and acted as an energy (mainly TAG and PL) storage prior to reproduction when the lowest TL was observed. Muscle TL varied from 2.0 to 71.7 g-1 (ww) in mature females without a clear pattern between maturity stages, although higher values of up to 117.3 g-1 (ww) was found in immature females. TL results suggest that albacore could be viewed predominantly as a capital breeder relying mostly on lipids stored before the onset of reproduction and with little additional energy derived from feeding. This study is the first one to provide new information on the reproductive development and classification of albacore in the western Indian Ocean. The reproductive parameters will reduce uncertainty in current stock assessment models which will eventually promote sustainability of the fishery.

Keywords: condition, size-at-maturity, spawning behaviour, temperate tuna, total lipid content

Procedia PDF Downloads 260

Authors: Kristina Pflug, Markus Busch

Abstract:

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

Procedia PDF Downloads 124

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

Abstract:

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

Procedia PDF Downloads 66

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

Abstract:

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

Procedia PDF Downloads 302

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 234

Authors: Wiseman Emmanuel Nkhomah, Chiyembekezo Kachimanga, Julia Huggins, Fabien Munyaneza

Abstract:

Background: Partners In Health – Malawi introduced one of Operational Researches called Primary Health Care (PHC) Surveys in 2020, which seeks to assess progress of delivery of care in the district. The study consists of 5 long surveys, namely; Facility assessment, General Patient, Provider, Sick Child, Antenatal Care (ANC), primarily conducted in 4 health facilities in Neno district. These facilities include Neno district hospital, Dambe health centre, Chifunga and Matope. Usually, these annual surveys are conducted from January, and the target is to present final report by June. Once data is collected and analyzed, there are a series of reviews that take place before reaching final report. In the first place, the manual process took over 9 months to present final report. Initial findings reported about 76.9% of the data that added up when cross-checked with paper-based sources. Purpose: The aim of this approach is to run away from manually pulling the data, do fresh analysis, and reporting often associated not only with delays in reporting inconsistencies but also with poor quality of data if not done carefully. This automation approach was meant to utilize features of new technologies to create visualizations, reports, and dashboards in Power BI that are directly fished from the data source – CommCare hence only require a single click of a ‘refresh’ button to have the updated information populated in visualizations, reports, and dashboards at once. Methodology: We transformed paper-based questionnaires into electronic using CommCare mobile application. We further connected CommCare Mobile App directly to Power BI using Application Program Interface (API) connection as data pipeline. This provided chance to create visualizations, reports, and dashboards in Power BI. Contrary to the process of manually collecting data in paper-based questionnaires, entering them in ordinary spreadsheets, and conducting analysis every time when preparing for reporting, the team utilized CommCare and Microsoft Power BI technologies. We utilized validations and logics in CommCare to capture data with less errors. We utilized Power BI features to host the reports online by publishing them as cloud-computing process. We switched from sharing ordinary report files to sharing the link to potential recipients hence giving them freedom to dig deep into extra findings within Power BI dashboards and also freedom to export to any formats of their choice. Results: This data automation approach reduced research timelines from the initial 9 months’ duration to 5. It also improved the quality of the data findings from the original 76.9% to 98.9%. This brought confidence to draw conclusions from the findings that help in decision-making and gave opportunities for further researches. Conclusion: These results suggest that automating the research data process has the potential of reducing overall amount of time spent and improving the quality of the data. On this basis, the concept of data automation should be taken into serious consideration when conducting operational research for efficiency and decision-making.

Keywords: reporting, decision-making, power BI, commcare, data automation, visualizations, dashboards

Procedia PDF Downloads 116

Authors: Emmanuel Maiyanga

Abstract:

Access to sufficiently good quality freshwater has been a global challenge, but more notably in low-income countries, particularly in the Sub-Saharan countries, which Nigeria is one. Urban population is soaring, especially in many low-income countries, the existing centralised water supply infrastructures are ageing and inadequate, moreover in households peoples’ lifestyles have become more water-demanding. So, people mostly device coping strategies where municipal supply is perceived to have failed. This development threatens the futures of groundwater and calls for a review of management strategy and research approach. The various issues associated with water demand management in low-income countries and Nigeria, in particular, are well documented in the literature. However, the way people use water daily in households and the reasons they do so, and how the situation is constructing demand among the middle-class population in Abuja Nigeria is poorly understood. This is what this research aims to unpack. This is achieved by using the social practices research approach (which is based on the Theory of Practices) to understand how this situation impacts on the shared groundwater resource. A qualitative method was used for data gathering. This involved audio-recorded interviews of householders and water professionals in the private and public sectors. It also involved observation, note-taking, and document study. The data were analysed thematically using NVIVO software. The research reveals the major household practices that draw on the water on a domestic scale, and they include water sourcing, body hygiene and sanitation, laundry, kitchen, and outdoor practices (car washing, domestic livestock farming, and gardening). Among all the practices, water sourcing, body hygiene, kitchen, and laundry practices, are identified to impact most on groundwater, with impact scale varying with household peculiarities. Water sourcing practices involve people sourcing mostly from personal boreholes because the municipal water supply is perceived inadequate and unreliable in terms of service delivery and water quality, and people prefer easier and unlimited access and control using boreholes. Body hygiene practices reveal that every respondent prefers bucket bathing at least once daily, and the majority bathe twice or more every day. Frequency is determined by the feeling of hotness and dirt on the skin. Thus, people bathe to cool down, stay clean, and satisfy perceived social, religious, and hygiene demand. Kitchen practice consumes water significantly as people run the tap for vegetable washing in daily food preparation and dishwashing after each meal. Laundry practice reveals that most people wash clothes most frequently (twice in a week) during hot and dusty weather, and washing with hands in basins and buckets is the most prevalent and water wasting due to soap overdose. The research also reveals poor water governance as a major cause of current inadequate municipal water delivery. The implication poor governance and widespread use of boreholes is an uncontrolled abstraction of groundwater to satisfy desired household practices, thereby putting the future of the shared aquifer at great risk of total depletion with attendant multiplying effects on the people and the environment and population continues to soar.

Keywords: boreholes, groundwater, household water practices, self-supply

Procedia PDF Downloads 123

Authors: Maurice A. Duka, Leobel Von Q. Tamayo, Niño Carlo I. Casim

Abstract:

The paucity of long-term measurements and monitoring of accurate water quality parameter profiles is evident for small and deep tropical lakes in Southeast Asia. This leads to a poor understanding of the stratification and mixing dynamics of these lakes in the region. The water quality dynamics of Sampaloc Lake, a tropical crater lake (104 ha, 27 m deep) in the Philippines, were investigated to understand how monsoon-driven conditions impact water quality and ecological health. Located in an urban area with approximately 10% of its surface area allocated to aquaculture, the lake is subject to distinct seasonal changes associated with the Northeast (NE) and Southwest (SW) monsoons. NE Monsoon typically occurs from October to April, while SW monsoon from May to September. These monsoons influence the lake’s water temperature, dissolved oxygen (DO), chlorophyll-α (chl-α), phycocyanin (PC), and turbidity, leading to significant seasonal variability. Monthly field observations of water quality parameters were made from October 2022 to September 2023 using a multi-parameter probe, YSI ProDSS, together with the collection of meteorological data during the same period. During the NE monsoon, cooler air temperatures and winds with sustained speeds caused surface water temperatures to drop from 30.9 ºC in October to 25.5 ºC in January, resulting in the weakening of stratification and eventually in lake turnover. This turnover redistributed nutrients from hypolimnetic layers to surface layers, increasing chl-α and PC levels (14-41 and 0-2 µg/L) throughout the water column. The fish kill was also observed during the lake’s turnover event as a result of the mixing of hypoxic hypolimnetic waters. Turbidity levels (0-3 NTU) were generally low but showed mid-column peaks in October, which was linked to thermocline-related effects, while low values in November followed heavy rainfall dilution and mixing effects. Conversely, the SW monsoon showed increased surface temperatures (28-30 ºC), shallow thermocline formations (3-11 m), and lower surface chl-α and PC levels (2-8 and 0-0.5 µg/L, respectively), likely due to limited nutrient mixing and more stable stratification. Turbidity was notably higher also in July (11-15 NTU) due to intense rainfall and reduced light penetration, which minimized photosynthetic activity. The SW monsoon also coincided with the typhoon season in the study area, resulting in partial upwelling of nutrients during strong storm events. These findings emphasize the need for continued monitoring of Sampaloc Lake’s seasonal water quality patterns, as monsoon-driven changes are crucial to maintaining its ecological balance and sustainability.

Keywords: seasonal water quality dynamics, Philippine tropical lake, monsoon-driven conditions, stratification and mixing

Procedia PDF Downloads 10

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 80

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 197

Authors: Aya Al Masri, Naima Oubenali, Safoin Aktaou, Thibault Julien, Malorie Martin, Fouad Maaloul

Abstract:

Introduction: The increased number of performed 'Computed Tomography (CT)' examinations raise public concerns regarding associated stochastic risk to patients. In its Publication 102, the ‘International Commission on Radiological Protection (ICRP)’ emphasized the importance of managing patient dose, particularly from repeated or multiple examinations. We developed a Dose Archiving and Communication System that gives multiple dose indexes (organ dose, effective dose, and skin-dose mapping) for patients undergoing radiological imaging exams. The aim of this study is to compare the organ dose values given by our software for patients undergoing CT exams with those of another software named "VirtualDose". Materials and methods: Our software uses Monte Carlo simulations to calculate organ doses for patients undergoing computed tomography examinations. The general calculation principle consists to simulate: (1) the scanner machine with all its technical specifications and associated irradiation cases (kVp, field collimation, mAs, pitch ...) (2) detailed geometric and compositional information of dozens of well identified organs of computational hybrid phantoms that contain the necessary anatomical data. The mass as well as the elemental composition of the tissues and organs that constitute our phantoms correspond to the recommendations of the international organizations (namely the ICRP and the ICRU). Their body dimensions correspond to reference data developed in the United States. Simulated data was verified by clinical measurement. To perform the comparison, 270 adult patients and 150 pediatric patients were used, whose data corresponds to exams carried out in France hospital centers. The comparison dataset of adult patients includes adult males and females for three different scanner machines and three different acquisition protocols (Head, Chest, and Chest-Abdomen-Pelvis). The comparison sample of pediatric patients includes the exams of thirty patients for each of the following age groups: new born, 1-2 years, 3-7 years, 8-12 years, and 13-16 years. The comparison for pediatric patients were performed on the “Head” protocol. The percentage of the dose difference were calculated for organs receiving a significant dose according to the acquisition protocol (80% of the maximal dose). Results: Adult patients: for organs that are completely covered by the scan range, the maximum percentage of dose difference between the two software is 27 %. However, there are three organs situated at the edges of the scan range that show a slightly higher dose difference. Pediatric patients: the percentage of dose difference between the two software does not exceed 30%. These dose differences may be due to the use of two different generations of hybrid phantoms by the two software. Conclusion: This study shows that our software provides a reliable dosimetric information for patients undergoing Computed Tomography exams.

Keywords: adult and pediatric patients, computed tomography, organ dose calculation, software comparison

Procedia PDF Downloads 162

Authors: Pirta Palola, Richard Bailey, Lisa Wedding

Abstract:

Societies and economies worldwide fundamentally depend on natural capital. Alarmingly, natural capital assets are quickly depreciating, posing an existential challenge for humanity. The development of robust natural capital accounting systems is essential for transitioning towards sustainable economic systems and ensuring sound management of capital assets. However, the accurate, equitable and comprehensive estimation of natural capital asset stocks and their accounting values still faces multiple challenges. In particular, the representation of socio-cultural values held by groups or communities has arguably been limited, as to date, the valuation of natural capital assets has primarily been based on monetary valuation methods and assumptions of individual rationality. People relate to and value the natural environment in multiple ways, and no single valuation method can provide a sufficiently comprehensive image of the range of values associated with the environment. Indeed, calls have been made to improve the representation of multiple types of value (instrumental, intrinsic, and relational) and diverse ontological and epistemological perspectives in environmental valuation. This study addresses this need by establishing a novel valuation framework, Environmental Value Functions (EVF), that allows for the integration of multiple types of value in natural capital accounting systems. The EVF framework is based on the estimation and application of value functions, each of which describes the relationship between the value and quantity (or quality) of an ecosystem component of interest. In this framework, values are estimated in terms of change relative to the current level instead of calculating absolute values. Furthermore, EVF was developed to also support non-marginalist conceptualizations of value: it is likely that some environmental values cannot be conceptualized in terms of marginal changes. For example, ecological resilience value may, in some cases, be best understood as a binary: it either exists (1) or is lost (0). In such cases, a logistic value function may be used as the discriminator. Uncertainty in the value function parameterization can be considered through, for example, Monte Carlo sampling analysis. The use of EVF is illustrated with two conceptual examples. For the first time, EVF offers a clear framework and concrete methodology for the representation of multiple types of value in natural capital accounting systems, simultaneously enabling 1) the complementary use and integration of multiple valuation methods (monetary and non-monetary); 2) the synthesis of information from diverse knowledge systems; 3) the recognition of value incommensurability; 4) marginalist and non-marginalist value analysis. Furthermore, with this advancement, the coupling of EVF and ecosystem modeling can offer novel insights to the study of spatial-temporal dynamics in natural capital asset values. For example, value time series can be produced, allowing for the prediction and analysis of volatility, long-term trends, and temporal trade-offs. This approach can provide essential information to help guide the transition to a sustainable economy.

Keywords: economics of biodiversity, environmental valuation, natural capital, value function

Procedia PDF Downloads 194

Authors: Adewale Tolulope Irewale, Elias Emeka Elemike, Christian O. Dimkpa, Emeka Emmanuel Oguzie

Abstract:

As the global population steadily approaches the 10billion mark, the world is currently faced with two major challenges among others – accessing sustainable and clean energy, and food security. Accessing cleaner and sustainable energy sources to drive global economy and technological advancement, and feeding the teeming human population require sustainable, innovative, and smart solutions. To solve the food production problem, producers have relied on fertilizers as a way of improving crop productivity. Commercial inorganic fertilizers, which is employed to boost agricultural food production, however, pose significant ecological sustainability and economic problems including soil and water pollution, reduced input efficiency, development of highly resistant weeds, micronutrient deficiency, soil degradation, and increased soil toxicity. These ecological and sustainability concerns have raised uncertainties about the continued effectiveness of conventional fertilizers. With the application of nanotechnology, plant biomass upcycling offers several advantages in greener energy production and sustainable agriculture through reduction of environmental pollution, increasing soil microbial activity, recycling carbon thereby reducing GHG emission, and so forth. This innovative technology has the potential for a circular economy and creating a sustainable agricultural practice. Nanomaterials have the potential to greatly enhance the quality and nutrient composition of organic biomass which in turn, allows for the conversion of biomass into nanofertilizers that are potentially more efficient. Water hyacinth plant harvested from an inland water at Warri, Delta State Nigeria were air-dried and milled into powder form. The dry biomass were used to prepare biochar at a pre-determined temperature in an oxygen deficient atmosphere. Physicochemical analysis of the resulting biochar was carried out to determine its porosity and general morphology using the Scanning Transmission Electron Microscopy (STEM). The functional groups (-COOH, -OH, -NH2, -CN, -C=O) were assessed using the Fourier Transform InfraRed Spectroscopy (FTIR) while the heavy metals (Cr, Cu, Fe, Pb, Mg, Mn) were analyzed using Inductively Coupled Plasma – Optical Emission Spectrometry (ICP-OES). Impregnation of the biochar with nanonutrients were achieved under varied conditions of pH, temperature, nanonutrient concentrations and resident time to achieve optimum adsorption. Adsorption and desorption studies were carried out on the resulting nanofertilizer to determine kinetics for the potential nutrients’ bio-availability to plants when used as green fertilizers. Water hyacinth (Eichhornia crassipes) which is an aggressively invasive aquatic plant known for its rapid growth and profusion is being examined in this research to harness its biomass as a sustainable feedstock to formulate functionalized nano-biochar fertilizers, offering various benefits including water hyacinth biomass upcycling, improved nutrient delivery to crops and aquatic ecosystem remediation. Altogether, this work aims to create output values in the three dimensions of environmental, economic, and social benefits.

Keywords: biochar-based nanofertilizers, eichhornia crassipes, greener agriculture, sustainable ecosystem, water hyacinth

Procedia PDF Downloads 65

Authors: Wiseman Emmanuel Nkhomah, Chiyembekezo Kachimanga, Moses Banda Aron, Julia Higgins, Manuel Mulwafu, Kondwani Mpinga, Mwayi Chunga, Grace Momba, Enock Ndarama, Dickson Sumphi, Atupere Phiri, Fabien Munyaneza

Abstract:

Background: Data is key to supporting health service delivery as stakeholders, including NGOs rely on it for effective service delivery, decision-making, and system strengthening. Several studies generated debate on data quality from national health management information systems (HMIS) in sub-Saharan Africa. This limits the utilization of data in resource-limited settings, which already struggle to meet standards set by the World Health Organization (WHO). We aimed to evaluate data quality improvement of Neno district HMIS over a 4-year period (2018 – 2021) following quarterly data reviews introduced in January 2020 by the district health management team and Partners In Health. Methods: Exploratory Mixed Research was used to examine report rates, followed by in-depth interviews using Key Informant Interviews (KIIs) and Focus Group Discussions (FGDs). We used the WHO module desk review to assess the quality of HMIS data in the Neno district captured from 2018 to 2021. The metrics assessed included the completeness and timeliness of 34 reports. Completeness was measured as a percentage of non-missing reports. Timeliness was measured as the span between data inputs and expected outputs meeting needs. We computed T-Test and recorded P-values, summaries, and percentage changes using R and Excel 2016. We analyzed demographics for key informant interviews in Power BI. We developed themes from 7 FGDs and 11 KIIs using Dedoose software, from which we picked perceptions of healthcare workers, interventions implemented, and improvement suggestions. The study was reviewed and approved by Malawi National Health Science Research Committee (IRB: 22/02/2866). Results: Overall, the average reporting completeness rate was 83.4% (before) and 98.1% (after), while timeliness was 68.1% and 76.4 respectively. Completeness of reports increased over time: 2018, 78.8%; 2019, 88%; 2020, 96.3% and 2021, 99.9% (p< 0.004). The trend for timeliness has been declining except in 2021, where it improved: 2018, 68.4%; 2019, 68.3%; 2020, 67.1% and 2021, 81% (p< 0.279). Comparing 2021 reporting rates to the mean of three preceding years, both completeness increased from 88% to 99% (in 2021), while timeliness increased from 68% to 81%. Sixty-five percent of reports have maintained meeting a national standard of 90%+ in completeness while only 24% in timeliness. Thirty-two percent of reports met the national standard. Only 9% improved on both completeness and timeliness, and these are; cervical cancer, nutrition care support and treatment, and youth-friendly health services reports. 50% of reports did not improve to standard in timeliness, and only one did not in completeness. On the other hand, factors associated with improvement included improved communications and reminders using internal communication, data quality assessments, checks, and reviews. Decentralizing data entry at the facility level was suggested to improve timeliness. Conclusion: Findings suggest that data quality in HMIS for the district has improved following collaborative efforts. We recommend maintaining such initiatives to identify remaining quality gaps and that results be shared publicly to support increased use of data. These results can inform Ministry of Health and its partners on some interventions and advise initiatives for improving its quality.

Keywords: data quality, data utilization, HMIS, collaboration, completeness, timeliness, decision-making

Procedia PDF Downloads 84

Authors: Idoia Landa Oregi, Itsaso Gonzalez Ochoantesana, Olatz Nicolas Buxens, Carlo Ferretti

Abstract:

The impact of citizens in urban transformations has become increasingly important in the pursuit of creating citizen-centered cities. Citizens at the forefront of the urban transformation process are key to establishing resilient, sustainable, and inclusive cities that cater to the needs of all residents. Therefore, collecting data and information directly from citizens is crucial for the sustainable development of cities. Within this context, public participation becomes a pillar for acquiring the necessary information from citizens. Public participation in urban transformation processes establishes a more responsive, equitable, and resilient urban environment. This approach cultivates a sense of shared responsibility and collective progress in building cities that truly serve the well-being of all residents. However, the implementation of public participation practices often overlooks strategies to effectively engage citizens in the processes, resulting in non-successful participatory outcomes. Therefore, this research focuses on identifying and analyzing the critical aspects of citizen engagement during the same participatory urban transformation process in different European contexts: Ermua (Spain), Elva (Estonia) and Matera (Italy). The participatory neighborhood regeneration process is divided into three main stages, to turn social districts into inclusive and smart neighborhoods: (i) the strategic level, (ii) the design level, and (iii) the implementation level. In the initial stage, the focus is on diagnosing the neighborhood and creating a shared vision with the community. The second stage centers around collaboratively designing various action plans to foster inclusivity and intelligence while pushing local economic development within the district. Finally, the third stage ensures the proper co-implementation of the designed actions in the neighborhood. To this date, the presented results critically analyze the key aspects of engagement in the first stage of the methodology, the strategic plan, in the three above-mentioned contexts. It is a multifaceted study that incorporates three case studies to shed light on the various perspectives and strategies adopted by each city. The results indicate that despite of the various cultural contexts, all cities face similar barriers when seeking to enhance engagement. Accordingly, the study identifies specific challenges within the participatory approach across the three cities such as the existence of discontented citizens, communication gaps, inconsistent participation, or administration resistance. Consequently, key learnings of the process indicate that a collaborative sphere needs to be cultivated, educating both citizens and administrations in the aspects of co-governance, giving these practices the appropriate space and their own communication channels. This study is part of the DROP project, funded by the European Union, which aims to develop a citizen-centered urban renewal methodology to transform the social districts into smart and inclusive neighborhoods.

Keywords: citizen-centred cities, engagement, public participation, urban transformation

Procedia PDF Downloads 68

Authors: S. Pradhan, V. Kumaran

Abstract:

Centrifugal gas separation processes effect separation by utilizing the difference in the mole fraction in a high speed rotating cylinder caused by the difference in molecular mass, and consequently the centrifugal force density. These have been widely used in isotope separation because chemical separation methods cannot be used to separate isotopes of the same chemical species. More recently, centrifugal separation has also been explored for the separation of gases such as carbon dioxide and methane. The efficiency of separation is critically dependent on the secondary flow generated due to temperature gradients at the cylinder wall or due to inserts, and it is important to formulate accurate models for this secondary flow. The widely used Onsager model for secondary flow is restricted to very long cylinders where the length is large compared to the diameter, the limit of high stratification parameter, where the gas is restricted to a thin layer near the wall of the cylinder, and it assumes that there is no mass difference in the two species while calculating the secondary flow. There are two objectives of the present analysis of the rarefied gas flow in a rotating cylinder. The first is to remove the restriction of high stratification parameter, and to generalize the solutions to low rotation speeds where the stratification parameter may be O (1), and to apply for dissimilar gases considering the difference in molecular mass of the two species. Secondly, we would like to compare the predictions with molecular simulations based on the direct simulation Monte Carlo (DSMC) method for rarefied gas flows, in order to quantify the errors resulting from the approximations at different aspect ratios, Reynolds number and stratification parameter. In this study, we have obtained analytical and numerical solutions for the secondary flows generated at the cylinder curved surface and at the end-caps due to linear wall temperature gradient and external gas inflow/outflow at the axis of the cylinder. The effect of sources of mass, momentum and energy within the flow domain are also analyzed. The results of the analytical solutions are compared with the results of DSMC simulations for three types of forcing, a wall temperature gradient, inflow/outflow of gas along the axis, and mass/momentum input due to inserts within the flow. The comparison reveals that the boundary conditions in the simulations and analysis have to be matched with care. The commonly used diffuse reflection boundary conditions at solid walls in DSMC simulations result in a non-zero slip velocity as well as a temperature slip (gas temperature at the wall is different from wall temperature). These have to be incorporated in the analysis in order to make quantitative predictions. In the case of mass/momentum/energy sources within the flow, it is necessary to ensure that the homogeneous boundary conditions are accurately satisfied in the simulations. When these precautions are taken, there is excellent agreement between analysis and simulations, to within 10 %, even when the stratification parameter is as low as 0.707, the Reynolds number is as low as 100 and the aspect ratio (length/diameter) of the cylinder is as low as 2, and the secondary flow velocity is as high as 0.2 times the maximum base flow velocity.

Keywords: rotating flows, generalized onsager and carrier-Maslen model, DSMC simulations, rarefied gas flow

Procedia PDF Downloads 398

Authors: Golson Mohamed, Yasmine Gamasy, Khaled EL-Khatib, Anas Al-Natour, Shady Fadel, Haytham Rashwan, Haytham Badawy, Nadia Farghaly

Abstract:

Introduction: Wilm's tumor is the most common malignant renal tumor in children. Much progress has been made in the management of patients with this malignancy over the last 3 decades. Today treatments are based on several trials and studies conducted by the International Society of Pediatric Oncology (SIOP) in Europe and National Wilm's Tumor Study Group (NWTS) in the USA. It is necessary for us to understand why do we follow either of the protocols, NWTS which follows the upfront surgery principle or the SIOP which follows the upfront chemotherapy principle in all stages of the disease. Objective: The aim of is to assess outcome in patients treated with preoperative chemotherapy and patients treated with upfront surgery to compare their effect on overall survival. Study design: to decide which protocol to follow, study was carried out on records for patients aged 1 day to 18 years old suffering from Wilm's tumor who were admitted to Alexandria University Hospital, pediatric oncology, pediatric urology and pediatric surgery departments, with a retrospective survey records from 2010 to 2015, Design and editing of the transfer sheet with a (PRISMA flow study) Preferred Reporting Items for Systematic Reviews and Meta-Analyses. Data were fed to the computer and analyzed using IBM SPSS software package version 20.0. (11) Qualitative data were described using number and percent. Quantitative data were described using Range (minimum and maximum), mean, standard deviation and median. Comparison between different groups regarding categorical variables was tested using Chi-square test. When more than 20% of the cells have expected count less than 5, correction for chi-square was conducted using Fisher’s Exact test or Monte Carlo correction. The distributions of quantitative variables were tested for normality using Kolmogorov-Smirnov test, Shapiro-Wilk test, and D'Agstino test, if it reveals normal data distribution, parametric tests were applied. If the data were abnormally distributed, non-parametric tests were used. For normally distributed data, a comparison between two independent populations was done using independent t-test. For abnormally distributed data, comparison between two independent populations was done using Mann-Whitney test. Significance of the obtained results was judged at the 5% level. Results: A significantly statistical difference was observed for survival between the two studied groups favoring the upfront chemotherapy(86.4%)as compared to the upfront surgery group (59.3%) where P=0.009. As regard complication, 20 cases (74.1%) out of 27 were complicated in the group of patients treated with upfront surgery. Meanwhile, 30 cases (68.2%) out of 44 had complications in patients treated with upfront chemotherapy. Also, the incidence of intraoperative complication (rupture) was less in upfront chemotherapy group as compared to upfront surgery group. Conclusion: Upfront chemotherapy has superiority over upfront surgery.As the patient who started with upfront chemotherapy shown, higher survival rate, less percent in complication, less percent needed for radiotherapy, and less rate in recurrence.

Keywords: Wilm's tumor, renal tumor, chemotherapy, surgery

Procedia PDF Downloads 317

Authors: Kamyar Tolouei, Ehsan Moosavi

Abstract:

In open-pit mines, the long-term production scheduling optimization problem (LTPSOP) is a complicated problem that contains constraints, large datasets, and uncertainties. Uncertainty in the output is caused by several geological, economic, or technical factors. Due to its dimensions and NP-hard nature, it is usually difficult to find an ideal solution to the LTPSOP. The optimal schedule generally restricts the ore, metal, and waste tonnages, average grades, and cash flows of each period. Past decades have witnessed important measurements of long-term production scheduling and optimal algorithms since researchers have become highly cognizant of the issue. In fact, it is not possible to consider LTPSOP as a well-solved problem. Traditional production scheduling methods in open-pit mines apply an estimated orebody model to produce optimal schedules. The smoothing result of some geostatistical estimation procedures causes most of the mine schedules and production predictions to be unrealistic and imperfect. With the expansion of simulation procedures, the risks from grade uncertainty in ore reserves can be evaluated and organized through a set of equally probable orebody realizations. In this paper, to synthesize grade uncertainty into the strategic mine schedule, a stochastic integer programming framework is presented to LTPSOP. The objective function of the model is to maximize the net present value and minimize the risk of deviation from the production targets considering grade uncertainty simultaneously while satisfying all technical constraints and operational requirements. Instead of applying one estimated orebody model as input to optimize the production schedule, a set of equally probable orebody realizations are applied to synthesize grade uncertainty in the strategic mine schedule and to produce a more profitable and risk-based production schedule. A mixture of metaheuristic procedures and mathematical methods paves the way to achieve an appropriate solution. This paper introduced a hybrid model between the augmented Lagrangian relaxation (ALR) method and the metaheuristic algorithm, the Harris Hawks optimization (HHO), to solve the LTPSOP under grade uncertainty conditions. In this study, the HHO is experienced to update Lagrange coefficients. Besides, a machine learning method called Random Forest is applied to estimate gold grade in a mineral deposit. The Monte Carlo method is used as the simulation method with 20 realizations. The results specify that the progressive versions have been considerably developed in comparison with the traditional methods. The outcomes were also compared with the ALR-genetic algorithm and ALR-sub-gradient. To indicate the applicability of the model, a case study on an open-pit gold mining operation is implemented. The framework displays the capability to minimize risk and improvement in the expected net present value and financial profitability for LTPSOP. The framework could control geological risk more effectively than the traditional procedure considering grade uncertainty in the hybrid model framework.

Keywords: grade uncertainty, metaheuristic algorithms, open-pit mine, production scheduling optimization

Procedia PDF Downloads 105

Authors: Pierobon Enrico, Missiaggia Marta, Castelluzzo Michele, Tommasino Francesco, Ricci Leonardo, Scifoni Emanuele, Vincezo Monaco, Boscardin Maurizio, La Tessa Chiara

Abstract:

Clinical outcomes collected over the past three decades have suggested that ion therapy has the potential to be a treatment modality superior to conventional radiation for several types of cancer, including recurrences, as well as for other diseases. Although the results have been encouraging, numerous treatment uncertainties remain a major obstacle to the full exploitation of particle radiotherapy. To overcome therapy uncertainties optimizing treatment outcome, the best possible radiation quality description is of paramount importance linking radiation physical dose to biological effects. Microdosimetry was developed as a tool to improve the description of radiation quality. By recording the energy deposition at the micrometric scale (the typical size of a cell nucleus), this approach takes into account the non-deterministic nature of atomic and nuclear processes and creates a direct link between the dose deposited by radiation and the biological effect induced. Microdosimeters measure the spectrum of lineal energy y, defined as the energy deposition in the detector divided by most probable track length travelled by radiation. The latter is provided by the so-called “Mean Chord Length” (MCL) approximation, and it is related to the detector geometry. To improve the characterization of the radiation field quality, we define a new quantity replacing the MCL with the actual particle track length inside the microdosimeter. In order to measure this new quantity, we propose a two-stage detector consisting of a commercial Tissue Equivalent Proportional Counter (TEPC) and 4 layers of Low Gain Avalanche Detectors (LGADs) strips. The TEPC detector records the energy deposition in a region equivalent to 2 um of tissue, while the LGADs are very suitable for particle tracking because of the thickness thinnable down to tens of micrometers and fast response to ionizing radiation. The concept of HDM has been investigated and validated with Monte Carlo simulations. Currently, a dedicated readout is under development. This two stages detector will require two different systems to join complementary information for each event: energy deposition in the TEPC and respective track length recorded by LGADs tracker. This challenge is being addressed by implementing SoC (System on Chip) technology, relying on Field Programmable Gated Arrays (FPGAs) based on the Zynq architecture. TEPC readout consists of three different signal amplification legs and is carried out thanks to 3 ADCs mounted on a FPGA board. LGADs activated strip signal is processed thanks to dedicated chips, and finally, the activated strip is stored relying again on FPGA-based solutions. In this work, we will provide a detailed description of HDM geometry and the SoC solutions that we are implementing for the readout.

Keywords: particle tracking, ion therapy, low gain avalanche diode, tissue equivalent proportional counter, microdosimetry

Procedia PDF Downloads 175

Authors: Rubens P. Costa, Marcelo A. Leigui de Oliveira

Abstract:

The comprehension of features on the energy spectra, the chemical compositions, and the origins of Ultra-High Energy Cosmic Rays (UHECRs) - mainly atomic nuclei with energies above ~1.0 EeV (exa-electron volts) - are intrinsically linked to the problem of determining the magnitude of their deflections in cosmic magnetic fields on cosmological scales. In addition, as they propagate from the source to the observer, modifications are expected in their original energy spectra, anisotropy, and the chemical compositions due to interactions with low energy photons and matter. This means that any consistent interpretation of the nature and origin of UHECRs has to include the detailed knowledge of their propagation in a three-dimensional environment, taking into account the magnetic deflections and energy losses. The parameter space range for the magnetic fields in the universe is very large because the field strength and especially their orientation have big uncertainties. Particularly, the strength and morphology of the Extragalactic Magnetic Fields (EGMFs) remain largely unknown, because of the intrinsic difficulty of observing them. Monte Carlo simulations of charged particles traveling through a simulated magnetized universe is the straightforward way to study the influence of extragalactic magnetic fields on UHECRs propagation. However, this brings two major difficulties: an accurate numerical modeling of charged particles diffusion in magnetic fields, and an accurate numerical modeling of the magnetized Universe. Since magnetic fields do not cause energy losses, it is important to impose that the particle tracking method conserve the particle’s total energy and that the energy changes are results of the interactions with background photons only. Hence, special attention should be paid to computational effects. Additionally, because of the number of particles necessary to obtain a relevant statistical sample, the particle tracking method must be computationally efficient. In this work, we present an analysis of the propagation of ultra-high energy charged particles in the intergalactic medium. The EGMFs are considered to be coherent within cells of 1 Mpc (mega parsec) diameter, wherein they have uniform intensities of 1 nG (nano Gauss). Moreover, each cell has its field orientation randomly chosen, and a border region is defined such that at distances beyond 95% of the cell radius from the cell center smooth transitions have been applied in order to avoid discontinuities. The smooth transitions are simulated by weighting the magnetic field orientation by the particle's distance to the two nearby cells. The energy losses have been treated in the continuous approximation parameterizing the mean energy loss per unit path length by the energy loss length. We have shown, for a particle with the typical energy of interest the integration method performance in the relative error of Larmor radius, without energy losses and the relative error of energy. Additionally, we plotted the distance amplification from rectilinear propagation as a function of the traveled distance, particle's magnetic rigidity, without energy losses, and particle's energy, with energy losses, to study the influence of particle's species on these calculations. The results clearly show when it is necessary to use a full three-dimensional simulation.

Keywords: cosmic rays propagation, extragalactic magnetic fields, magnetic deflections, ultra-high energy

Procedia PDF Downloads 127