Search results for: instrumental variables

Authors: James Killian, Sarah Cox

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The use of stability criteria within geotechnical engineering is the way the results of analyses are conveyed, and sensitivities and risk assessments are performed. Historically, the primary stability criteria for slope design has been the Factor of Safety (FOS) coming from a limit calculation. Increasingly, the value derived from Strength Reduction Factor (SRF) analysis is being used as the criteria for stability analysis. The purpose of this work was to study in detail the relationship between SRF values produced from a numerical modeling technique and the traditional FOS values produced from Limit Equilibrium (LEM) analyses. This study utilized a model of a 3000-foot-high slope with a 45-degree slope angle, assuming a perfectly plastic mohr-coulomb constitutive model with high cohesion and friction angle values typical of a large hard rock mine slope. A number of variables affecting the values of the SRF in a numerical analysis were tested, including zone size, in-situ stress, tensile strength, and dilation angle. This paper demonstrates that in most cases, SRF values are lower than the corresponding LEM FOS values. Modeled zone size has the greatest effect on the estimated SRF value, which can vary as much as 15% to the downside compared to FOS. For consistency when using SRF as a stability criteria, the authors suggest that numerical model zone sizes should not be constructed to be smaller than about 1% of the overall problem slope height and shouldn’t be greater than 2%. Future work could include investigations of the effect of anisotropic strength assumptions or advanced constitutive models.

Keywords: FOS, SRF, LEM, comparison

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Authors: Charlene N. T. Mfangnia, Henri E. Z. Tonnang, Berge Tsanou, Jeremy Herren

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Microsporidia MB is a recently discovered symbiont capable of blocking the transmission of Plasmodium from mosquitoes to humans. The symbiont can spread both horizontally and vertically among the mosquito population. This dual transmission gives the symbiont the ability to invade the mosquito population. The replacement of the mosquito population by the population of symbiont-infected mosquitoes then appears as a promising strategy for malaria control. In this context, the present study uses differential equations to model the transmission dynamics of Microsporidia MB in the population of female Anopheles mosquitoes. Long-term propagation scenarios of the symbiont, such as extinction, persistence or total infection, are obtained through the determination of the target and basic reproduction numbers, the equilibria, and the study of their stability. The stability is illustrated numerically, and the contribution of vertical and horizontal transmission in the spread of the symbiont is assessed. Data obtained from laboratory experiments are then used to explain the low prevalence observed in nature. The study also shows that the male death rate, the mating rate and the attractiveness of MB-positive mosquitoes are the factors that most influence the transmission of the symbiont. In addition, the introduction of temperature and the study of bifurcations show the significant influence of the environmental condition in the propagation of Microsporidia MB. This finding proves the necessity of taking into account environmental variables for the potential establishment of the symbiont in a new area.

Keywords: differential equations, stability analysis, malaria, microsporidia MB, horizontal transmission, vertical transmission, numerical illustration

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Authors: Amidu Owolabi Ayeni

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Studies have shown that spatio-temporal distribution and variability of climatic variables, urban land use, and population have had substantial impact on water supply. It is based on these facts that the impacts of climate, urbanization, and population on water supply in Lagos State Nigeria remain the focus of this study. Population and water production data on Lagos State between 1963 and 2006 were collected, and used for time series and projection analyses. Multi-temporal land-sat images of 1975, 1995 and NigeriaSat-1 imagery of 2007 were used for land use change analysis. The population of Lagos State increased by about 557.1% between 1963 and 2006, correspondingly, safe water supply increased by 554%. Currently, 60% of domestic water use in urban areas of Lagos State is from groundwater while 75% of rural water is from unsafe surface water. Between 1975 and 2007, urban land use increased by about 235.9%. The 46years climatic records revealed that temperature and evaporation decreased slightly while rainfall and Relatively Humidity (RH) decreased consistently. Based on these trends, the Lagos State population and required water are expected to increase to about 19.8millions and 2418.9ML/D respectively by the year 2026. Rainfall is likely to decrease by -6.68mm while temperature will increase by 0.950C by 2026. Urban land use is expected to increase by 20% with expectation of serious congestion in the suburb areas. With these results, over 50% of the urban inhabitants will be highly water poor in future if the trends continue unabated.

Keywords: challenges, climate change, urbanization, water supply

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Authors: Benaliouche Hana, Abdessemed Djamal, Meniai Abdessalem, Lesage Geoffroy, Heran Marc

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This paper presents a dynamic mathematical model of activated sludge which is able to predict the formation and degradation kinetics of SMP (Soluble microbial products) in membrane bioreactor systems. The model is based on a calibrated version of ASM1 with the theory of production and degradation of SMP. The model was calibrated on the experimental data from MBR (Mathematical modeling Membrane bioreactor) pilot plant. Analytical expressions have been developed, describing the concentrations of the main state variables present in the sludge matrix, with the inclusion of only six additional linear differential equations. The objective is to present a new dynamic mathematical model of activated sludge capable of predicting the formation and degradation kinetics of SMP (UAP and BAP) from the submerged membrane bioreactor (BRMI), operating at low organic load (C / N = 3.5), for two sludge retention times (SRT) fixed at 40 days and 60 days, to study their impact on membrane fouling, The modeling study was carried out under the steady-state condition. Analytical expressions were then validated by comparing their results with those obtained by simulations using GPS-X-Hydromantis software. These equations made it possible, by means of modeling approaches (ASM1), to identify the operating and kinetic parameters and help to predict membrane fouling.

Keywords: Activated Sludge Model No. 1 (ASM1), mathematical modeling membrane bioreactor, soluble microbial products, UAP, BAP, Modeling SMP, MBR, heterotrophic biomass

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Authors: Vineeth Siripuram, Abhineet Nigam

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A bioreactor is an engineered system that supports a biologically active environment. Along the years, the advancements in bioreactors have been widely accepted all over the world for varied applications ranging from sewage treatment to tissue cloning. Driven by tissue and organ shortage, tissue engineering has emerged as an alternative to transplantation for the reconstruction of lost or damaged organs. In this study, Computational fluid dynamics (CFD) has been used to model porous medium flow in scaffolds (taken from the literature) with different flow patterns. A detailed analysis of different scaffold geometries and their influence on cell deposition in the perfusion system is been carried out using Computational fluid dynamics (CFD). Considering the fact that, the scaffold should mimic the organs or tissues structures in a three-dimensional manner, certain assumptions were made accordingly. The research on scaffolds has been extensively carried out in different bioreactors. However, there has been less focus on the morphology of the scaffolds and the flow patterns in which the perfusion system is laid upon. The objective of this paper is to employ a computational approach using CFD simulation to determine the optimal morphology and the anisotropic measurements of the various samples of scaffolds. Using predictive computational modelling approach, variables which exert dominant effects on the cell deposition within the scaffold were prioritised and corresponding changes in morphology of scaffold and flow patterns in the perfusion systems are made. A Eulerian approach was carried on in multiple CFD simulations, and it is observed that the morphological and topological changes in the scaffold perfusion system are of great importance in the commercial applications of scaffolds.

Keywords: cell seeding, CFD, flow patterns, modelling, perfusion systems, scaffold

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Authors: Zhu Weimin, Allegorico Carmine, Ruggiero Gionata

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During decades of Baker Hughes (BH) iCenter experience, it is demonstrated that in addition to conventional insights on equipment steady operation conditions, insights on transient conditions can add significant and exclusive value for anomaly detection, downtime saving, and predictive maintenance. Our work shows examples from the BH iCenter experience to introduce the advantages and features of using transient condition analytics: (i) Operation under critical engine conditions: e.g., high level or high change rate of temperature, pressure, flow, vibration, etc., that would not be reachable in normal operation, (ii) Management of dedicated sub-systems or components, many of which are often bottlenecks for reliability and maintenance, (iii) Indirect detection of anomalies in the absence of instrumentation, (iv) Repetitive sequences: if data is properly processed, the engineering features of transients provide not only anomaly detection but also problem characterization and prognostic indicators for predictive maintenance, (v) Engine variables accounting for fatigue analysis. iCenter has been developing and deploying a series of analytics based on transient conditions. They are contributing to exclusive value adding in the following areas: (i) Reliability improvement, (ii) Startup reliability improvement, (iii) Predictive maintenance, (iv) Repair/overhaul cost down. Illustrative examples for each of the above areas are presented in our study, focusing on challenges and adopted techniques ranging from purely statistical approaches to the implementation of machine learning algorithms. The obtained results demonstrate how the value is obtained using transient condition analytics in the BH iCenter experience.

Keywords: analytics, diagnostics, monitoring, turbomachinery

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Authors: Mustapha Kamel Mihoubi, Mohamed Essadik Kerkar

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Probabilistic risk analysis models are used to provide a better understanding of the reliability and structural failure of works, including when calculating the stability of large structures to a major risk in the event of an accident or breakdown. This work is interested in the study of the probability of failure of concrete dams through the application of reliability analysis methods including the methods used in engineering. It is in our case, the use of level 2 methods via the study limit state. Hence, the probability of product failures is estimated by analytical methods of the type first order risk method (FORM) and the second order risk method (SORM). By way of comparison, a level three method was used which generates a full analysis of the problem and involves an integration of the probability density function of random variables extended to the field of security using the Monte Carlo simulation method. Taking into account the change in stress following load combinations: normal, exceptional and extreme acting on the dam, calculation of the results obtained have provided acceptable failure probability values which largely corroborate the theory, in fact, the probability of failure tends to increase with increasing load intensities, thus causing a significant decrease in strength, shear forces then induce a shift that threatens the reliability of the structure by intolerable values of the probability of product failures. Especially, in case the increase of uplift in a hypothetical default of the drainage system.

Keywords: dam, failure, limit-state, monte-carlo, reliability, probability, simulation, sliding, taylor

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Authors: Hemalatha Ganapathyswamy, Thirukkumar Subramani

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Celiac disease is an autoimmune response to dietary wheat gluten. Gluten is the main structure forming protein in bread and hence developing gluten-free bread is a technological challenge. The study aims at using nonwheat flours like barnyard millet and lentil flour to replace wheat in bread formulations. Other characteristics of these grains, such as high protein, soluble fiber, mineral content and bioactive components make them attractive alternatives to traditional gluten-free ingredients in the production of high protein, gluten-free bread. The composite flour formulations for the development of gluten-free bread were optimized using lentil flour (50 to 70 g), barnyard millet flour (0 to 30 g) and corn flour (0 to 30 g) by means of response surface methodology with various independent variables for physical, sensorial and nutritional characteristics. The optimized composite flour which had a desirability value of 0.517, included lentil flour –62.94 g, barnyard millet flour– 24.34 g and corn flour– 12.72 g with overall acceptability score 8.00/9.00. The optimized gluten-free bread formulation had high protein (14.99g/100g) and fiber (1.95g/100g) content. The glycemic index of the gluten-free bread was 54.58 rendering it as low glycemic which enhances the functional benefit of the gluten-free bread. Since the standardised gluten-free bread from barnyard millet and lentil flour are high protein, and gluten-free with low glycemic index, the product would serve as an ideal therapeutic food in the management of both celiac disease and diabetes mellitus with better nutritional value.

Keywords: gluten free bread, lentil, low glycemic index, response surface methodology

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Authors: Parul Suraia, Harshit Sosan Lakra

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Indigenous communities represent some of the most marginalized populations globally, with India labeled as tribals, experiencing particularly pronounced marginalization and a concerning decline in their numbers. These communities often inhabit geographically challenging regions characterized by low population densities, posing significant challenges to providing essential infrastructure services. Jharkhand, a Schedule 5 state, is infamous for its low-level health status due to disparities in access to health care. The primary objective of this study is to investigate the spatial inequalities in healthcare accessibility among tribal populations within the state and pinpoint critical areas requiring immediate attention. Health indicators were selected based on the tribal perspective and association of Sustainable Goal 3 (Good Health and Wellbeing) with other SDGs. Focused group discussions in which tribal people and tribal experts were done in order to finalize the indicators. Employing Principal Component Analysis, two essential indices were constructed: the Tribal Health Index (THI) and the Tribal Health Intervention Index (THII). Index values were calculated based on the district-wise secondary data for Jharkhand. The bivariate spatial association technique, Moran’s I was used to assess the spatial pattern of the variables to determine if there is any clustering (positive spatial autocorrelation) or dispersion (negative spatial autocorrelation) of values across Jharkhand. The results helped in facilitating targeting policy interventions in deprived areas of Jharkhand.

Keywords: tribal health, health spatial disparities, health status, Jharkhand

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Authors: Reena D. Souza, Tripti Vats, Prem F. Siril

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Esterification of free fatty acid (oleic acid) and transesterification of waste cooking oil (WCO) with ethanol over graphene oxide (GO), GO-Fe2O3, sulfonated GO (GO-SO3H), and Fe2O3/GO-SO3H catalysts were examined in the present study. Iron oxide supported graphene-based acid catalyst (Fe2O3/GO-SO3H) exhibited highest catalytic activity. GO was prepared by modified Hummer’s process. The GO-Fe2O3 nanocomposites were prepared by the addition of NaOH to a solution containing GO and FeCl3. Sulfonation was done using concentrated sulfuric acid. Transmissionelectron microscopy (TEM) and atomic force microscopy (AFM) imaging revealed the presence of Fe2O3 particles having size in the range of 50-200 nm. Crystal structure was analyzed by XRD and defect states of graphene were characterized using Raman spectroscopy. The effects of the reaction variables such as catalyst loading, ethanol to acid ratio, reaction time and temperature on the conversion of fatty acids were studied. The optimum conditions for the esterification process were molar ratio of alcohol to oleic acid at 12:1 with 5 wt% of Fe2O3/GO-SO3H at 1000C with a reaction time of 4h yielding 99% of ethyl oleate. This is because metal oxide supported solid acid catalysts have advantages of having both strong Brønsted as well as Lewis acid properties. The biodiesel obtained by transesterification of WCO was characterized by 1H NMR and Gas Chromatography techniques. XRD patterns of the recycled catalyst evidenced that the catalyst structure was unchanged up to the 5th cycle, which indicated the long life of the catalyst.

Keywords: Fe₂O₃/GO-SO₃H, Graphene Oxide, GO-Fe₂O₃, GO-SO₃H, WCO

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Authors: Riyadh Jamegh, Alla Eldin Kassam, Sawsan Sabih

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In order to overcome uncertainty conditions and inability to meet customers' requests due to these conditions, organizations tend to reserve a certain safety stock level (SSL). This level must be chosen carefully in order to avoid the increase in holding cost due to excess in SSL or shortage cost due to too low SSL. This paper used soft computing fuzzy logic to identify optimal SSL; this fuzzy model uses the dynamic concept to cope with high complexity environment status. The proposed model can deal with three input variables, i.e., demand stability level, raw material availability level, and on hand inventory level by using dynamic fuzzy logic to obtain the best SSL as an output. In this model, demand stability, raw material, and on hand inventory levels are described linguistically and then treated by inference rules of the fuzzy model to extract the best level of safety stock. The aim of this research is to provide dynamic approach which is used to identify safety stock level, and it can be implanted in different industries. Numerical case study in the dairy industry with Yogurt 200 gm cup product is explained to approve the validity of the proposed model. The obtained results are compared with the current level of safety stock which is calculated by using the traditional approach. The importance of the proposed model has been demonstrated by the significant reduction in safety stock level.

Keywords: inventory optimization, soft computing, safety stock optimization, dairy industries inventory optimization

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Authors: Nina Leila Mussa

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Background: The devastating effects of the war on Syria’s educational infrastructure has been widely reported, with millions of children denied access. However, among those who resettled in Lebanon, the impact of receiving educational assistance on their abilities to pass the English entrance exam is not well described. The aim of this study was to identify predictors of success among Syrian refugees receiving English language courses in a Lebanese university. Methods: The database of Syrian refugee girls matriculated in English courses at the American University of Beirut (AUB) was reviewed. The study period was 7/2018-09/2020. Variables compared included: family size and income, welfare status, parents’ education, English proficiency, access to the internet, and need for external help with homework. Results: For the study period, there were 28 girls enrolled. The average family size was 6 (range 4-9), with eight having completed primary, 14 secondary education, and 6 graduated high school. Eighteen were single-income families. After 12 weeks of English courses, 16 passed the Test of English as Foreign Language (TOEFL) from the first attempt, and 12 failed. Out of the 12, 8 received external help, and 6 passed on the second attempt, which brings the total number of successful passing to 22. Conclusion: Despite the tragedy of war, girls receiving assistance in learning English in Lebanon are able to pass the basic language test. Investment in enhancing those educational experiences will be determinantal in achieving widespread progress among those at-risk children.

Keywords: refugee girls, TOEFL, education, success

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Authors: Ali Alattabi, Clare Harris, Rafid Alkhaddar, Ali Alzeyadi

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Petroleum refinery wastewater (PRW) can be considered as one of the most significant source of aquatic environmental pollution. It consists of oil and grease along with many other toxic organic pollutants. In recent years, a new technique was implemented using different types of membranes and sequencing batch reactors (SBRs) to treat PRW. SBR is a fill and draw type sludge system which operates in time instead of space. Many researchers have optimised SBRs’ operating conditions to obtain maximum removal of undesired wastewater pollutants. It has gained more importance mainly because of its essential flexibility in cycle time. It can handle shock loads, requires less area for operation and easy to operate. However, bulking sludge or discharging floating or settled sludge during the draw or decant phase with some SBR configurations are still one of the problems of SBR system. The main aim of this study is to develop and innovative design for the SBR optimising the process variables to result is a more robust and efficient process. Several experimental tests will be developed to determine the removal percentages of chemical oxygen demand (COD), Phenol and nitrogen compounds from synthetic PRW. Furthermore, the dissolved oxygen (DO), pH and oxidation-reduction potential (ORP) of the SBR system will be monitored online to ensure a good environment for the microorganisms to biodegrade the organic matter effectively.

Keywords: petroleum refinery wastewater, sequencing batch reactor, hydraulic retention time, Phenol, COD, mixed liquor suspended solids (MLSS)

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Authors: Abu S. M. G. Kibria, Alison M. Behie, Robert Costanza, Colin Groves, Tracy Farrell

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This study is aimed to understand the level of access and the influence of livelihood capitals in maintaining access and control of ecosystem services (ESS) in the Sundarbans, Bangladesh. Besides the villagers, we consider other stakeholders including the forest department, coast guard, police, merchants, pirates and villagers who ‘controlled’ or ‘maintained’ access to ESS (crab catching, shrimp fry, honey, shrimp, mixed fish, fuel wood) in this region. Villagers used human, physical, natural and social capitals to gain access to ESS. The highest level of access was observed in crab catching and the lowest was found in honey collection, both of which were done when balancing the costs and benefits of accessing one ESS against another. The outcomes of these ongoing access negotiations were determined by livelihood capitals of the households. In addition, it was often found that the certain variables could have a positive effect on one ESS and a negative effect on another. For instance, human, social and natural capitals (eldest daughter’s education and No. of livelihood group membership and) had significant positive effects on honey collection while two components of human and social capitals including ‘eldest son’s education’ and ‘severity of pirate problem’ had exactly the opposite impact. These complex interactions were also observed in access to other ESS. It thus seems that access to ESS is not anything which is provided, but rather it is achieved by using livelihood capitals. Protecting any ecosystem from over exploitation and improve wellbeing can be achieved by properly balancing the livelihood capital-access nexus.

Keywords: provisioning services, access level, livelihood capital, interaction, access gain

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Authors: Lubica Hikkerova, Jean-Michel Sahut

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Environmental protection remains a global challenge but, since 2012, there has been a progressive decline in corporate engagement in environmental protection issues. This study seeks to investigate the role of financial capacity and governance in improving the level of environmental engagement of companies. The regression technique is applied to data on 351 large European companies from the ASSET4-ESG database for the 2007-2015 period. Firstly, the results show that the companies in the sample are fairly engaged in environmental protection, with a strong dispersion representing nearly four times the average. This means that the companies in the sample do not share the same level of engagement in matters of environmental protection, some being more committed than others. Secondly, the results reveal that the financial capacity of the company, as assessed through its indicators, has a significant effect on its level of environmental protection engagement in the present sample. This effect is more positive the higher the profits the company makes, and more negative the more heavily indebted or, the higher the rates of dividends it pays per share. Lastly, the results also show that a better quality of governance plays an important role in the decision to undertake actions leading to environmental protection. More specifically, the degree of management implication in the running of the business, the respect of the rights of the shareholders, the effectiveness of the control exerted by the board of directors, and, to a lesser extent, the independence of the audit committee, are variables which have a positive and significant influence on the level of environmental engagement of companies.

Keywords: financial capacity, corporate governance, environmental engagement, stakeholder theory, theory of organizational legitimacy, theory of resources and capabilities

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Authors: Rakesh Kumar, Fatima Electricwala

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One of the major thrusts of the Bus Rapid Transit System is to reduce the commuter’s dependency on private vehicles and increase the shares of public transport to make urban transportation system environmentally sustainable. In this study, commuter mode choice analysis is performed that examines behavioral responses to the proposed Bus Rapid Transit System (BRTS) in Surat, with estimation of the probable shift from private mode to public mode. Further, evaluation of the BRTS scenarios, using Surat’s transportation ecological footprint was done. A multi-modal simulation model was developed in Biogeme environment to explicitly consider private users behaviors and non-linear environmental impact. The data of the different factors (variables) and its impact that might cause modal shift of private mode users to proposed BRTS were collected through home-interview survey using revealed and stated preference approach. A multi modal logit model of mode-choice was then calibrated using the collected data and validated using proposed sample. From this study, a set of perception factors, with reliable and predictable data base, to explain the variation in modal shift behaviour and their impact on Surat’s ecological environment has been identified. A case study of the proposed BRTS connecting the Surat Industrial Hub to the coastal area is provided to illustrate the approach.

Keywords: BRTS, private modes, mode choice models, ecological footprint

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Authors: Xiang Li, Jian-Qiao Sun

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As the crucial component of city traffic network, intersections have significant impacts on urban traffic performance. Despite of the rapid development in transportation systems, increasing traffic volumes result in severe congestions especially at intersections in urban areas. Effective regulation of vehicle flows at intersections has always been an important issue in the traffic control system. This study presents a multi-objective optimization method at intersections with cellular automata to achieve better traffic performance. Vehicle conflicts and pedestrian interference are considered. Three categories of the traffic performance are studied including transportation efficiency, energy consumption and road safety. The left-turn signal type, signal timing and lane assignment are optimized for different traffic flows. The multi-objective optimization problem is solved with the cell mapping method. The optimization results show the conflicting nature of different traffic performance. The influence of different traffic variables on the intersection performance is investigated. It is observed that the proposed optimization method is effective in regulating the traffic at the intersection to meet multiple objectives. Transportation efficiency can be usually improved by the permissive left-turn signal, which sacrifices safety. Right-turn traffic suffers significantly when the right-turn lanes are shared with the through vehicles. The effect of vehicle flow on the intersection performance is significant. The display pattern of the optimization results can be changed remarkably by the traffic volume variation. Pedestrians have strong interference with the traffic system.

Keywords: cellular automata, intersection, multi-objective optimization, traffic system

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Authors: Kyu Jin Kim, Byung Kwan Oh, Hyo Seon Park

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The seismic responses-based structural health monitoring system has been performed to prevent seismic damage. Structural seismic damage of building is caused by the instantaneous stress concentration which is related with dynamic characteristic of earthquake. Meanwhile, seismic response analysis to estimate the dynamic responses of building demands significantly high computational cost. To prevent the failure of structural members from the characteristic of the earthquake and the significantly high computational cost for seismic response analysis, this paper presents an artificial neural network (ANN) based prediction model for dynamic responses of building considering specific time length. Through the measured dynamic responses, input and output node of the ANN are formed by the length of specific time, and adopted for the training. In the model, evolutionary radial basis function neural network (ERBFNN), that radial basis function network (RBFN) is integrated with evolutionary optimization algorithm to find variables in RBF, is implemented. The effectiveness of the proposed model is verified through an analytical study applying responses from dynamic analysis for multi-degree of freedom system to training data in ERBFNN.

Keywords: structural health monitoring, dynamic response, artificial neural network, radial basis function network, genetic algorithm

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Authors: Chhordaneath Hen, Ty Sok, Ilan Ich, Ratboren Chan, Chantha Oeurng

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The damages caused by hydrological extremes such as flooding have been severe globally, and several research studies indicated extreme precipitations play a crucial role. Cambodia is one of the most vulnerable countries exposed to floods and drought as consequences of climate impact. Prek Thnot River Basin in the southwest part of Cambodia, which is in the plate and plateau region and a part of the Mekong Delta, was selected to investigate the changes in extreme precipitation and hydrological extreme. Furthermore, to develop a statistical relationship between these phenomena in this basin from 1995 to 2020 using Multiple Linear Regression. The precipitation and hydrological extreme were assessed via the attributes and trends of rainfall patterns during the study periods. The extreme flow was defined as a dependent variable, while the independent variables are various extreme precipitation indices. The study showed that all extreme precipitations indices (R10, R20, R35, CWD, R95p, R99p, and PRCPTOT) had increasing decency. However, the number of rain days per year had a decreasing tendency, which can conclude that extreme rainfall was more intense in a shorter period of the year. The study showed a similar relationship between extreme precipitation and hydrological extreme and land use change association with hydrological extreme. The direct combination of land use and precipitation equals 37% of the flood causes in this river. This study provided information on these two causes of flood events and an understanding of expectations of climate change consequences for flood and water resources management.

Keywords: extreme precipitation, hydrological extreme, land use, land cover, Prek Thnot river basin

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Authors: Kawsar Ahmed, Hong Wang

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The study's goal was to estimate the causal mediation impact of tobacco tax before and after price hikes among low-income male smokers, with a particular emphasis on the effect estimating pathways framework for continuous and dichotomous variables. From July to December 2021, a cross-sectional investigation of observational data (n=739) was collected from Bangladeshi low-wage smokers. The Quasi-Bayesian technique, binomial probit model, and sensitivity analysis using a simulation of the computational tools R mediation package had been used to estimate the effect. After a price rise for tobacco products, the average number of cigarettes or bidis sticks taken decreased from 6.7 to 4.56. Tobacco product rising prices have a direct effect on low-income people's decisions to quit or lessen their daily smoking habits of Average Causal Mediation Effect (ACME) [effect=2.31, 95 % confidence interval (C.I.) = (4.71-0.00), p<0.01], Average Direct Effect (ADE) [effect=8.6, 95 percent (C.I.) = (6.8-0.11), p<0.001], and overall significant effects (p<0.001). Tobacco smoking choice is described by the mediated proportion of income effect, which is 26.1% less of following price rise. The curve of ACME and ADE is based on observational figures of the coefficients of determination that asses the model of hypothesis as the substantial consequence after price rises in the sensitivity analysis. To reduce smoking product behaviors, price increases through taxation have a positive causal mediation with income that affects the decision to limit tobacco use and promote low-income men's healthcare policy.

Keywords: causal mediation analysis, directed acyclic graphs, tobacco price policy, sensitivity analysis, pathway estimation

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Authors: Elizabeth O'Brien, Raegan Murphy

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Research suggests that high levels of empathy in individuals with partners with mental health difficulties can lead to improved outcomes for their partner while compromising their own mental health. Specifically, it is proposed that the affective dimension of empathy diminishes resilience to the distress of a partner, whereas cognitive empathy (CE) enhances it. The relationship between different empathy dimensions and psychological resilience measures has not been investigated in partners of people with depression. Psychological inflexibility (PI) is a construct that can be understood as distress intolerance and is suggested to be an important feature of psychological resilience. The current study, therefore, aimed to investigate the differential role of dispositional empathy dimensions in PI for people living with a partner with depression. A cross-sectional design was employed in which 148 participants living with a partner with depression and 45 participants for a comparison sample were recruited using online platforms. Participants completed online surveys with measures relating to demographics, empathy, and PI. Scores were compared between the study and comparison samples. The study sample scored significantly lower for CE and affective empathy (AE) and significantly higher for PI than the comparison sample. Exploratory and regression analyses were run to examine associations between variables within the study sample. Analyses revealed that CE predicted the resilience outcome whilst AE did not. These results suggest that interventions for partners of people with depression that bolster the CE dimension alone may improve mental health outcomes for both members of the couple relationship.

Keywords: affective empathy, cognitive empathy, depression, partners, psychological inflexibility

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Authors: Adriana Martínez-Arias, John Josephraj Selvaraj, Luis Octavio González-Salcedo

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In the Colombian Pacific, Dorado fish (Coryphaena hippurus L.) fisheries is of great commercial interest. However, its habitat and fisheries may be affected by climatic change especially by the actual increase in sea surface temperature. Hence, it is of interest to study the dynamics of these species fishing zones. In this study, we developed Artificial Neural Networks (ANN) models to predict Catch per Unit Effort (CPUE) as an indicator of species abundance. The model was based on four oceanographic variables (Chlorophyll a, Sea Surface Temperature, Sea Level Anomaly and Bathymetry) derived from satellite data. CPUE datasets for model training and cross-validation were obtained from logbooks of commercial fishing vessel. Sea surface Temperature for Colombian Pacific were projected under Representative Concentration Pathway (RCP) scenarios 4.5 and 8.5 using Coupled Model Intercomparison Project Phase 5 (CMIP5) and CPUE maps were created. Our results indicated that an increase in sea surface temperature reduces the potential fishing zones of this species in the Colombian Pacific. We conclude that ANN is a reliable tool for simulation of climate change effects on the potential fishing zones. This research opens a future agenda for other species that have been affected by climate change.

Keywords: climatic change, artificial neural networks, dorado fish, CPUE

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Authors: Siwei Chang, Heng Li, Haitao Wu, Xin Fang

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Construction robots are receiving more and more attention as a promising solution to the manpower shortage issue in the construction industry. The development of intelligent control techniques that assist in controlling the robots to avoid transparency and reflected building obstacles is crucial for guaranteeing the adaptability and flexibility of mobile construction robots in complex construction environments. With the boom of computer vision techniques, a number of studies have proposed vision-based methods for transparent obstacle avoidance to improve operation accuracy. However, vision-based methods are also associated with disadvantages such as high computational costs. To provide better perception and value evaluation, this study aims to analyze the performance of vision-based techniques for avoiding transparent building obstacles. To achieve this, commonly used sensors, including a lidar, an ultrasonic sensor, and a USB camera, are equipped on the robotic platform to detect obstacles. A Raspberry Pi 3 computer board is employed to compute data collecting and control algorithms. The turtlebot3 burger is employed to test the programs. On-site experiments are carried out to observe the performance in terms of success rate and detection distance. Control variables include obstacle shapes and environmental conditions. The findings contribute to demonstrating how effectively vision-based obstacle avoidance strategies for transparent building obstacle avoidance and provide insights and informed knowledge when introducing computer vision techniques in the aforementioned domain.

Keywords: construction robot, obstacle avoidance, computer vision, transparent obstacle

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Authors: Xiyang Li, Qi Yu, Lun Zhang

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In the face of natural disasters and other emergency situations, determining the optimal location of rescue centers is crucial for improving rescue efficiency and minimizing impact on affected populations. This paper proposes a method that integrates genetic algorithms (GA) and backpropagation neural networks (BPNN) to address the site selection optimization problem for emergency rescue centers. We utilize BPNN to accurately estimate the cost of delivering supplies from rescue centers to each temporary camp. Moreover, a genetic algorithm with a special partially matched crossover (PMX) strategy is employed to ensure that the number of temporary camps assigned to each rescue center adheres to predetermined limits. Using the population distribution data during the 2022 epidemic in Jiading District, Shanghai, as an experimental case, this paper verifies the effectiveness of the proposed method. The experimental results demonstrate that the BPNN-GA method proposed in this study outperforms existing algorithms in terms of computational efficiency and optimization performance. Especially considering the requirements for computational resources and response time in emergency situations, the proposed method shows its ability to achieve rapid convergence and optimal performance in the early and mid-stages. Future research could explore incorporating more real-world conditions and variables into the model to further improve its accuracy and applicability.

Keywords: emergency rescue centers, genetic algorithms, back-propagation neural networks, site selection optimization

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Authors: Divya Vats, Sanjay Mahajani

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The clarification of sugarcane juice plays a pivotal role in the production of non-centrifugal sugar (NCS), profoundly influencing the quality of the final NCS product. In this study, we have investigated the kinetics and mathematical modeling of the batch clarification process. The turbidity of the clarified cane juice (NTU) emerges as the determinant of the end product’s color. Moreover, this parameter underscores the significance of considering other variables as performance indicators for accessing the efficacy of the clarification process. Temperature-controlled experiments were meticulously conducted in a laboratory-scale batch mode. The primary objective was to discern the essential and optimized parameters crucial for augmenting the clarity of cane juice. Additionally, we explored the impact of pH and flocculant loading on the kinetics. Particle Image Velocimetry (PIV) is employed to comprehend the particle-particle and fluid-particle interaction. This technique facilitated a comprehensive understanding, paving the way for the subsequent multiphase computational fluid dynamics (CFD) simulations using the Eulerian-Lagrangian approach in the Ansys fluent. Impressively, these simulations accurately replicated comparable velocity profiles. The final mechanism of this study helps to make a mathematical model and presents a valuable framework for transitioning from the traditional batch process to a continuous process. The ultimate aim is to attain heightened productivity and unwavering consistency in product quality.

Keywords: non-centrifugal sugar, particle image velocimetry, computational fluid dynamics, mathematical modeling, turbidity

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Authors: Olufemi Samuel Shola, Oladapo Adenike Adesola

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Inadequate dietary intake has increased the susceptibility of under five children to malnutrition and infections. This study, therefore, assessed the feeding practices of children of 0-23 months of age among mothers in urban areas of Akure, Ondo State, Nigeria. Simple random sampling technique was used to select four hundred (400) mothers out of 710 mothers from 7 primary health care centres in Akure metropolis for the study. Data were collected using modified WHO 2003 Questionnaire on child feeding practices. Data were analyzed using descriptive statistics, while chi-square was used to determine the association between variables. Results showed that 52.0% of the children were males, with 47.5% in the 6-8 months age group. More than half (57.0%) of the mothers were between the ages of 20-29 years, and 45.0% had secondary education. Majority (94.3%) of the mothers breastfed their children in the last 24 hours preceding the survey. The feeding practices history of mothers showed that 28.0% and 53.7% of the mothers initiated breastfeeding less than 30 minutes and between 30 minutes to 1 hour after delivery, respectively. Also, 52.0% of mothers practiced exclusive breastfeeding for six months, while 26.2% breastfed from 6 months up to 2 years of age. Dietary diversity of the children age 6-23 months revealed that 68.7% of the children attained the minimum dietary diversity by consuming 4 or more food groups in the last 24 hours. There was a significant association (P < 0.05) between mothers’ education (n=180), occupation(n=41) and dietary diversity (n= 150) and meal frequency (n=209). Therefore, the study concluded that the duration of breastfeeding and time of introduction of complementary food did not meet WHO recommended guidelines. There is urgent need to launching more programmes.

Keywords: breastfeeding, mothers, child feeding, urban areas, ondo state, nigeria

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Authors: Ahmed Ali Torad

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Background: Breast feeding maintains the maternal fetal immunological link, favours the transmission of immune-competence from the mother to her infant and is considered an important contributory factor to the neo natal immune defense system. Purpose: This study was conducted to investigate the effect of relaxation techniques on immunological properties of breast milk. Subjects and Methods: Thirty breast feeding mothers with a single, mature infant without any complications participated in the study. Subjects will be recruited from outpatient clinic of obstetric department of El Kasr El-Aini university hospital in Cairo. Mothers were randomly divided into two equal groups using coin toss method: Group (A) (relaxation training group) (experimental group): It will be composed of 15 women who received relaxation training program in addition to breast feeding and nutritional advices and Group (B) (control group): It will be composed of 15 women who received breast feeding and nutritional advices only. Results: The results showed that mean mother’s age was 28.4 ± 3.68 and 28.07 ± 4.09 for group A and B respectively, there were statistically significant differences between pre and post values regarding cortisol level, IgA level, leucocyte count and infant’s weight and height and there is only statistically significant differences between both groups regarding post values of all immunological variables (cortisol – IgA – leucocyte count). Conclusion: We could conclude that there is a statistically significant effect of relaxation techniques on immunological properties of breast milk.

Keywords: relaxation, breast, milk, immunology, lactation

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Authors: Pilar Gamarra Gamarra, Michele Girotto

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In the expanding field of leaders’ ethical behavior research, little attention has been paid to the association between finance leaders’ ethical traits (beyond personality) and ethical leadership, and more importantly, how these ethical characteristics can be predictors of ethical behavior at the leadership level in the financial sector. In this study, we tested a theoretical model based on uponsocial cognitive theory (Bandura, 1986) and the cognitive-developmental model (Piaget, 1932) to examine leaders’ moral identity and moral attentiveness as antecedents of ethical leadership. After the 2008 economic crisis, the marketplace has awakened to the potential dangers of unethical behavior. The unethical behavior of the leaders of the financial sector was identified as guilty of this economic catastrophe. For that reason, it seems increasingly prudent for organizations to have leaders who are cognitively inclined toward ethical behavior. This evidence suggests that moral attentiveness and moral identity is perhaps one way of identifying those kinds of leaders. For leaders who are morally attentive and have a high moral identity, themes of ethics interventions are consistent with their way of seeing the word. As a result, these leaders could become critical components of change in organizations and could provide the energy and skills necessary for these efforts to be successful. Ethical behavior of leader from the financial sector and marketing sectors must be joined to manage the change. In this study, a leader’s moral identity, leader’s moral attentiveness, and self-importance of Ethical Leadership are measured for financial and marketing leaders to be compared to determine the relationship between the three variables in each sector. Other conclusion related to gender, educational level or generation are obtained.

Keywords: ethical leadership, moral identity, moral attentiveness, financial leaders, marketing leaders, ethical behavior

Procedia PDF Downloads 139

Authors: David Guillermo Piedrahita Marquez, Hector Suarez Mahecha, Jairo Humberto Lopez

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There is a need to preserve aquaculture matrices due to their high nutritional value, and its broad consumption, one of those species is the white cachama (Piaractus brachypomus), this fish is located in the rivers of eastern Colombia, and the previously mentioned species needs more study. Therefore, in a paper the effects of an alternative method of preservation of shell life were investigated, the method used is the application of an edible coating made from chitosan and ethanolic extract of propolis (EEP) encapsulated in maltodextrin. The coating was applied by immersion, and after that, we investigated the post mortem quality changes of the fish performing physicochemical and microbiological analysis. pH, volatile bases, test thiobarbituric acid and peroxide value were tested; finally, we studied the effect of the coating on mesophilic strains, coliforms and other microorganisms such as Staphylococcus, and Salmonella. Finally, we concluded that the coating prolongs the shelf life because it acts as a barrier to oxygen and moisture, the bioactive compounds trap free radicals and the coatings changes the metabolism and cause the cell lysis of the microorganisms. It was determined that the concentration of malonaldehyde, the volatile basic nitrogen content and pH are the variables that distinguish more clearly between the samples with the treatment and the control samples.

Keywords: antimicrobial activity, lipid oxidation, texture profile analysis (TPA), sensorial analysis, peroxide value, thiobarbituric acid assay (TBA), total volatile basic nitrogen (TVB-N)

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Authors: Franco Ceasar Agbalog, Shintaro Yukawa

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Mindfulness is increasingly being used as a method for resolving conflict. However, less is known about how its positive outcome develops. To better understand the underlying effects of mindfulness on conflict resolution strategies, this study examines the potential mediating factors between them. The researchers hypothesized that Emotional Intelligence (EI) mediates the effects of mindfulness on conflict resolution strategies due to its similar components to the benefits of mindfulness, such as awareness and control of one’s emotions, awareness and understanding of other’s emotions, and cultivation of compassion and empathy. Using a random sampling, 157 participants completed three questionnaires: Five Facet Mindfulness Questionnaire (FFMQ), Trait Emotional Intelligence Questionnaire-Short Form (TEIQue-SF), and Rahim Organizational Conflict Inventory-II (ROCI-II). Utilizing the SPSS Process, results showed a significant relationship between mindfulness and EI. However, among the five approaches to conflict resolution, only the integrating style was significantly related to EI. Following the principle of Mediation Analysis, mindfulness has an indirect effect on integrating style. Moreover, mindfulness and conflict resolution strategies were not significantly related. This is a rather surprising result because research literature has always indicated a positive relationship between the two variables. These findings imply that although integrating style is generally considered the best approach in handling conflict, each style may be appropriate depending on the situation. Mindfulness allows practitioners to have a holistic view of the conflict situation and choose the approach they think best for that specific situation. This could explain why statistically, there is no direct effect of mindfulness on conflict resolution strategies. This work provides basis for the necessity to investigate the factors of conflict instead of the conflict resolution strategies; factors that can be manipulated and may be directly influenced by mindfulness.

Keywords: conflict resolution strategies, emotional intelligence, mindfulness and conflict, ROCI-II integrating style

Procedia PDF Downloads 328