Search results for: population balance modeling

Authors: Dimas Tri Anantyo, Zsa-Zsa Ayu Laksmi, Adhie Nur Radityo, Arsita Eka Rini, Gatot Irawan Sarosa

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A six-point-two-magnitude earthquake rocked Mamuju District, West Sulawesi Province, Indonesia, on 15 January 2021, causing significant health issues for the affected community, particularly among vulnerable populations such as neonates and children. The aim of this study is to examine and describe the diseases diagnosed in the pediatric population in Mamuju 14 days after the earthquake. This study uses a prospective observational study of the pediatric population presenting at West Sulawesi Regional Hospital, Mamuju Regional Public Hospital, and Bhayangkara Hospital for the period of 14 days after the earthquake. Demographic and clinical information were recorded. One hundred and fifty-three children were admitted to the health center. Children younger than six years old were the highest proportion (78%). Out of 153 children, 82 of them were male (54%). The most frequently diagnosed disease during the first and second weeks after the earthquake was respiratory problems, followed by gastrointestinal problems that showed an increase in incidence in the second week. This study found that age has a correlation with frequent disease in children after an earthquake. Respiratory and gastrointestinal problems were found to be the most common diseases among the pediatric population in Mamuju after the earthquake.

Keywords: health outcomes, pediatric population, earthquake, Mamuju

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Authors: Marianna Maiaru, Gregory M. Odegard

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During the processing of high-performance thermoset polymer matrix composites, chemical reactions occur during elevated pressure and temperature cycles, causing the constituent monomers to crosslink and form a molecular network that gradually can sustain stress. As the crosslinking process progresses, the material naturally experiences a gradual shrinkage due to the increase in covalent bonds in the network. Once the cured composite completes the cure cycle and is brought to room temperature, the thermal expansion mismatch of the fibers and matrix cause additional residual stresses to form. These compounded residual stresses can compromise the reliability of the composite material and affect the composite strength. Composite process modeling is greatly complicated by the multiscale nature of the composite architecture. At the molecular level, the degree of cure controls the local shrinkage and thermal-mechanical properties of the thermoset. At the microscopic level, the local fiber architecture and packing affect the magnitudes and locations of residual stress concentrations. At the macroscopic level, the layup sequence controls the nature of crack initiation and propagation due to residual stresses. The goal of this research is use molecular dynamics (MD) and finite element analysis (FEA) to predict the residual stresses in composite laminates and the corresponding effect on composite failure. MD is used to predict the polymer shrinkage and thermomechanical properties as a function of degree of cure. This information is used as input into FEA to predict the residual stresses on the microscopic level resulting from the complete cure process. Virtual testing is subsequently conducted to predict strength allowables. Experimental characterization is used to validate the modeling.

Keywords: molecular dynamics, finite element analysis, processing modeling, multiscale modeling

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Authors: J.Zambrano Nájera, M.Gómez Valentín

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Increases in urbanization during XX century, have brought as one major problem the increased of sediment production. Hydraulic erosion is one of the major causes of increasing of sediments in small urban catchments. Such increments in sediment yielding in header urban catchments can caused obstruction of drainage systems, making impossible to capture urban runoff, increasing runoff volumes and thus exacerbating problems of urban flooding. For these reasons, it is more and more important to study of sediment production in urban watershed for properly analyze and solve problems associated to sediments. The study of sediments production has improved with the use of mathematical modeling. For that reason, it is proposed a new physically based model applicable to small header urban watersheds that includes the advantages of distributed physically base models, but with more realistic data requirements. Additionally, in this paper the model proposed is compared with a lumped model, reviewing the results, the advantages and disadvantages between the both of them.

Keywords: erosion, hydrologic modeling, urban runoff, sediment modeling, sediment yielding, urban planning

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Authors: Nikolaos Papadimas, Joanna Bennett, Amir Sakhaei, Timothy Dodwell

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Composite modeling of consolidation processes is playing an important role in the process and part design by indicating the formation of possible unwanted prior to expensive experimental iterative trial and development programs. Composite materials in their uncured state display complex constitutive behavior, which has received much academic interest, and this with different models proposed. Errors from modeling and statistical which arise from this fitting will propagate through any simulation in which the material model is used. A general hyperelastic polynomial representation was proposed, which can be readily implemented in various nonlinear finite element packages. In our case, FEniCS was chosen. The coefficients are assumed uncertain, and therefore the distribution of parameters learned using Markov Chain Monte Carlo (MCMC) methods. In engineering, the approach often followed is to select a single set of model parameters, which on average, best fits a set of experiments. There are good statistical reasons why this is not a rigorous approach to take. To overcome these challenges, A hierarchical Bayesian framework was proposed in which population distribution of model parameters is inferred from an ensemble of experiments tests. The resulting sampled distribution of hyperparameters is approximated using Maximum Entropy methods so that the distribution of samples can be readily sampled when embedded within a stochastic finite element simulation. The methodology is validated and demonstrated on a set of consolidation experiments of AS4/8852 with various stacking sequences. The resulting distributions are then applied to stochastic finite element simulations of the consolidation of curved parts, leading to a distribution of possible model outputs. With this, the paper, as far as the authors are aware, represents the first stochastic finite element implementation in composite process modelling.

Keywords: data-driven , material consolidation, stochastic finite elements, surrogate models

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Authors: Irvan Adhin Cholilie, Susinggih Wijana, Yusron Sugiarto

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The aim of this research is to compare the results of black grass jelly produced using laboratory scale and double scale. In this research, the production from the laboratory scale is using ingredients of 1 kg black grass jelly added with 5 liters of water, while the double scale is using 5 kg black grass jelly and 75 liters of water. The results of organoleptic tests performed by 30 panelists (general) to the sample gels of grass black powder produced from both of laboratory and double scale are not different significantly in color, odor, flavor, and texture. Proximate test results conducted in both of grass black jelly powder produced in laboratory scale and double scale also have no significant differences in all parameters. Grass black jelly powder from double scale contains water, carbohydrate, crude fiber, and yield in the amount of 12,25 %; 43,7 %; 5,89 %; and 16,28 % respectively. The results of the energy efficiency analysis by boiling, draining, evaporation, drying, and milling processes are 85,11 %; 76,97 %; 99,64 %; 99,99% and 99,39% respectively. The utility needs including water needs for each batch amounted 0.1 m3 and cost Rp 220,5 per batch, the electricity needs for each batch is 20.01 kWh and cost Rp 18569.28 per batch, and LPG needs for each batch is 30 kg costed Rp 234,000.00 so that the total cost spent for the process is Rp 252,789.78 .

Keywords: black grass jelly, powder, mass balance, energy balance, cost

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Authors: Mohammad Javad Mollakazemi, Farhad Asadi, Aref Ghafouri

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Performance of different filtering approaches depends on modeling of dynamical system and algorithm structure. For modeling and smoothing the data the evaluation of posterior distribution in different filtering approach should be chosen carefully. In this paper different filtering approaches like filter KALMAN, EKF, UKF, EKS and smoother RTS is simulated in some trajectory tracking of path and accuracy and limitation of these approaches are explained. Then probability of model with different filters is compered and finally the effect of the noise variance to estimation is described with simulations results.

Keywords: Gaussian approximation, Kalman smoother, parameter estimation, noise variance

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Authors: Rushva Parihar, Anushka Barua

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The negative repercussions of a warming planet are already visible, with biodiversity loss, water scarcity, and extreme weather events becoming ever so frequent. The agriculture sector is perhaps the most impacted, and modern agriculture has failed to defend farmers from the effects of climate change. This, coupled with the added pressure of higher demands for food production caused due to population growth, has only compounded the impact. Traditional agricultural practices that are routed in indigenous knowledge have long safeguarded the delicate balance of the ecosystem through sustainable production techniques. This paper uses secondary data to explore these traditional processes (like Beejamrita, Jeevamrita, sheep penning, earthen bunding, and others) from around the world that have been developed over centuries and focuses on how they can be used to tackle contemporary issues arising from climate change (such as nutrient and water loss, soil degradation, increased incidences of pests). Finally, the resulting framework has been applied to the context of Indian agriculture as a means to combat climate change and improve food security, all while encouraging documentation and transfer of local knowledge as a shared resource among farmers.

Keywords: sustainable food systems, traditional agricultural practices, climate smart agriculture, climate change, indigenous knowledge

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Authors: Enerit Saçdanaku, Idriz Haxhiu

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In this study was monitored the population of the European Pond Turtle, Emys orbicularis (Linnaeus, 1758) in the area of Narta Lagoon, Vlora Bay (Albania), from August to October 2014. A total of 54 individuals of E. orbicularis were studied using different methodologies. Curved Carapace Length (CCL), Plastron Length (PL) and Curved Carapace Width (CCW) were measured for each individual of E. orbicularis and were statistically analyzed. All captured turtles were separated in seven different size–classes based on their carapace length (CCL). Each individual of E. orbicularis was marked by notching the carapace (marginal scutes). Form all individuals captured resulted that 37 were females (68.5%), 14 males (25.9%), 3 juveniles (5.5%), while 18 individuals of E. orbicularis were recaptured for the first and some for the second time.

Keywords: Emys orbicularis, female, juvenile, male, population, size–classes

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Authors: Rokas Arlauskas, Donatas Austys, Rimantas Stukas

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Background. The World Health Organization recommends to reduce an intake of added sugar. High consumption of sugar and sweets increases the risk of obesity and overweight. The analysis of the body mass index (BMI) data of the adult population of Lithuania shows that only less than half (45.7%) of the total population has a normal body weight (18.5-24.9 BMI), overweight (25.0-29, 9 BMI) more than a third (36.6 percent), obese (>=30.0 BMI) is 15.4 percent population and underweight (<18.5 BMI) has 2.1 percent population. More men than women are obese (16.5% and 14.9%, respectively). In order to achieve this, alternative sweetening methods by using sweeteners might be employed. However, studies show that attitudes and beliefs might act as a barrier for sugar replacement with sweeteners. In Lithuania, there is a lack of studies on consumption of sugar and sweeteners, including attitudes of Lithuanian residents towards them. Therefore the objective of this study was to assess the attitude of Lithuanian adults towards replacement of added sugar with sweeteners. Methods. A representative sample of Lithuanian population of adults aged 18 to 75 years was formed. A total number of 1008 residents participated. Data was collected using a questionnaire. With respect to social and demografic characteristics, distribution of respondents by answering to one question was analysed. Respondents were asked to indicate their likely behaviour in terms of added sugar if they knew that there a healthier than sugar sweetener exists.Results. Every fifth participant (20.7%) indicated no added sugar consumption and no likely use of the healthier sweetener. Every second respondent among added sugar consumers (40.0% of whole sample) indicated that if they knew about existence of a healthier sweetener than sugar, they would try it and, if liked it, would use it instead of sugar. Approximately 35.0% of whole sample would ignore the fact that healthier than sugar sweetener exists and continue to consume sugar regardless of its effects on health. Younger, urban and higher educated respondents were more likely to opt for a healthier sweetener instead of added sugar (respectively, 45.7% vs. 34.4%, 43.3% vs. 31.2%, 47.6% vs. 37.3% of whole sample, p < 0.05). Conclusions. Half of Lithuanian adult consumers of added sugar would try to replace added sugar with healthier sweetener. Such a reasonable attitude was more prevalent among younger, urban and higher educated respondents.

Keywords: added sugar, lithuanian adult population, sweeteners., food

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Authors: Keshav Dubey, Swajeeth Panchangam, Arun Rajendran, Swarnim Gupta

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In the semiconductor capital equipment industry, effective modeling of repairable system reliability is crucial for optimizing maintenance strategies and ensuring operational efficiency. However, repairable system reliability modeling using a renewal process is not as popular in the semiconductor equipment industry as it is in the locomotive and automotive industries. Utilization of this approach will help optimize maintenance practices. This paper presents a structured framework that leverages both parametric and non-parametric approaches to model the reliability of repairable subsystems based on operational data, maintenance schedules, and system-specific conditions. Data is organized at the equipment ID level, facilitating trend testing to uncover failure patterns and system degradation over time. For non-parametric modeling, the Mean Cumulative Function (Mean Cumulative Function) approach is applied, offering a flexible method to estimate the cumulative number of failures over time without assuming an underlying statistical distribution. This allows for empirical insights into subsystem failure behavior based on historical data. On the parametric side, virtual age modeling, along with Homogeneous and Non-Homogeneous Poisson Process (Homogeneous Poisson Process and Non-Homogeneous Poisson Process) models, is employed to quantify the effect of repairs and the aging process on subsystem reliability. These models allow for a more structured analysis by characterizing repair effectiveness and system wear-out trends over time. A comparison of various Generalized Renewal Process (GRP) approaches highlights their utility in modeling different repair effectiveness scenarios. These approaches provide a robust framework for assessing the impact of maintenance actions on system performance and reliability. By integrating both parametric and non-parametric methods, this framework offers a comprehensive toolset for reliability engineers to better understand equipment behavior, assess the effectiveness of maintenance activities, and make data-driven decisions that enhance system availability and operational performance in semiconductor fabrication facilities.

Keywords: reliability, maintainability, homegenous poission process, repairable system

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Authors: K. Soldatova, Y. Galerkin

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A loading factor performance is necessary for the modeling of centrifugal compressor gas dynamic performance curve. Measured loading factors are linear function of a flow coefficient at an impeller exit. The performance does not depend on the compressibility criterion. To simulate loading factor performances, the authors present two parameters: a loading factor at zero flow rate and an angle between an ordinate and performance line. The calculated loading factor performances of non-viscous are linear too and close to experimental performances. Loading factor performances of several dozens of impellers with different blade exit angles, blade thickness and number, ratio of blade exit/inlet height, and two different type of blade mean line configuration. There are some trends of influence, which are evident – comparatively small blade thickness influence, and influence of geometry parameters is more for impellers with bigger blade exit angles, etc. Approximating equations for both parameters are suggested. The next phase of work will be simulating of experimental performances with the suggested approximation equations as a base.

Keywords: loading factor performance, centrifugal compressor, impeller, modeling

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Authors: Kristina Thorell

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Food security has been one of the most important policy issues on the global arena after the Second World War. The overall aim of this presentation is to describe preconditions for a sustainable food supply from a spatial perspective. Special attention is paid to the differences between advanced and less advanced economies around the world. The theoretical framework is based upon models which are explaining complex systems of factors that affect the preconditions for agricultural productions. In additions to this, theories about how population and environmental pollution change through different stages of societal development are explained. The results are based upon data of agricultural practices, population growth, hunger and nutrition levels from different countries around the world. The analysis shows that factors which affect preconditions for agricultural production are dynamic. Factors which support the food security in the near future are a decreasing population growth, technological development and innovation but the environmental crisis is associated to high risks. It is, therefore, important to develop environmental policies and improved methods for organic farming. A final conclusion is that the spatial pattern is clear; the food supply is sufficient within advanced economies but rather complicated in development countries.

Keywords: food security, agricultural geography, demography, advanced economies, population growth, agricultural practices

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Authors: Michael Ricardo Lang, AdriéLle Costa, Ivana Iesbik, Karine Haag, Leonardo Trindade Buffara, Oscar Reimann Junior, Chelin Auswaldt Steclan

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Stroke affects not only the individual, but has significant impacts on the social and family context. Therefore, it is necessary to know the peculiarities of each region, in order to contribute to regional public health policies effectively. Thus, the present study discusses biomarkers in a post-stroke population, admitted to a stroke unit (U-stroke) of reference in the southern region of Brazil. Biomarkers were analyzed, such as age, length of stay, mortality rate, survival time, risk factors and family history of stroke in patients after ischemic stroke. In this studied population, comparing men and women, it was identified that men were more affected than women, and the average age of women affected was higher, as they also had the highest mortality rate and the shortest hospital stay. The risk factors identified here were according to the global scenario; with SAH being the most frequent and those associated with sedentary lifestyle in women the most frequent (dyspilipidemia, heart disease and obesity). In view of this, the importance of studies that characterize populations regionally is evident, strengthening the strategic planning of policies in favor of health care.

Keywords: biomarkers, sex, stroke, stroke unit, population

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Authors: A. Sebti Bouzid, S. Igoud, L. Aoudjit, H. Lebik

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Mathematical modeling and numerical simulation have emerged over the past two decades as one of the key tools for design and optimize performances of physical and chemical processes intended to water disinfection. Water photolysis is an efficient and economical technique to reduce bacterial contamination. It exploits the germicidal effect of solar ultraviolet irradiation to inactivate pathogenic microorganisms. The design of photo-reactor operating in continuous disinfection system, required tacking in account the hydrodynamic behavior of water in the reactor. Since the kinetic of disinfection depends on irradiation intensity distribution, coupling the hydrodynamic and solar radiation distribution is of crucial importance. In this work we propose a numerical simulation study for hydrodynamic and solar irradiation distribution in a tubular photo-reactor. We have used the Computational Fluid Dynamic code Fluent under the assumption of three-dimensional incompressible flow in unsteady turbulent regimes. The results of simulation concerned radiation, temperature and velocity fields are discussed and the effect of inclination angle of reactor relative to the horizontal is investigated.

Keywords: solar water disinfection, hydrodynamic modeling, solar irradiation modeling, CFD Fluent

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Authors: Tosin Deborah Akanbi

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The Building Information Modeling Execution Plan (BEP) is a document that manifests the specifications for the adoption and execution of building information modeling in the construction sector in an organized manner so as to attain the listed goals. In this regard, the study examined the barriers to the adoption of building information modeling, evaluated the effect of building information modeling adoption characteristics on the key elements of a building information modeling execution plan and developed a strategic framework for a BEP in the Lagos State construction industry. Data were gathered through a questionnaire survey with 332 construction professionals in the study area. Three online structured interviews were conducted to support and validate the findings of the quantitative analysis. The results showed the significant relationships and connections between the variables in the framework: BIM usage and model quality control (aBIMskill -> dMQ, Beta = 0.121, T statistics = 1.829), BIM adoption characteristics and information exchange (bBIM_CH -> dIE, Beta = 0.128, T statistics = 1.727), BIM adoption characteristics and process design (bBIM_CH -> dPD, Beta = 0.170, T statistics = 2.754), BIM adoption characteristics and roles and responsibilities (bBIM_CH -> dRR, Beta = 0.131, T statistics = 2.181), interest BIM barriers and BIM adoption characteristics (cBBIM_INT -> bBIM_CH, Beta = 0.137, T statistics = 2.309), legal BIM barriers and BIM adoption characteristics (cBBIM_LEG -> bBIM_CH, Beta = 0.168, T statistics = 2.818), professional BIM barriers and BIM adoption characteristics (cBBIM_PRO -> bBIM_CH, Beta = 0.152, T statistics = 2.645). The results also revealed that seven final themes were generated, namely: model structure and process design, BIM information exchange and collaboration procedures, project goals and deliverables, project model quality control, roles and responsibilities, reflect Lagos state construction industry and validity of the BEP framework. Thus, there is a need for the policy makers to direct interventions to promote, encourage and support the understanding and adoption of BIM by emphasizing the various benefits of using the technology in the Lagos state construction industry.

Keywords: building information modelling execution plan, BIM adoption characteristics, BEP framework, construction industry

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Authors: F. S. Alavi, D. Mowla, F. Esmaeilzadeh

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In this paper, the core of Sarkhoon Gas Condensate Reservoir located in the south of Iran was thermodynamically modeled in order to study the natural depletion process and methane injection phenomena for enhanced gas-condensate recovery using the Eclipse 300 compositional simulator. Modeling was performed for three different core lengths with different production and injection flow rates in both vertical and horizontal cases. According to the results, the final condensate in place value in the natural depletion process is approximately independent of the production rate for a given pressure drop. The final condensate in place value is lower in vertical cases compared to horizontal cases. An increase in the injection flow rate leads to a decrease in the percentage of gascondensate recovery. In cores of equal length, gas condensate recovery percent is higher in vertical cases in comparison to horizontal cases. For a constant injection rate, decreasing the core length leads to a decrease in gas condensate recovery.

Keywords: reservoir simulation, methane injection, enhanced condensate recovery, reservoir core, modeling

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Authors: Sanjay Kumar, Lillie Dewan

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The study of complex dynamic systems has advanced through various scientific approaches with the help of computer modeling. The common design trends in aerospace system design can be applied to quadcopter design. A quadcopter is a nonlinear, under-actuated system with complex aerodynamics parameters and creates challenges that demand new, robust, and effective control approaches. The flight control stability can be improved by planning and tracking the trajectory and reducing the effect of sensors and the operational environment. This paper presents a modern design Simmechanics visual modeling approach for a mechanical model of a quadcopter with three degrees of freedom. The Simmechanics model, considering inertia, mass, and geometric properties of a dynamic system, produces multiple translation and rotation maneuvers. The proportional, integral, and derivative (PID) controller is integrated with the Simmechanics model to follow a predefined quadcopter rotational trajectory for a fixed time interval. The results presented are satisfying. The simulation of the quadcopter control performed operations successfully.

Keywords: nonlinear system, quadcopter model, simscape modelling, proportional-integral-derivative controller

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Authors: Naso Isaiah Thanavisuth, Patompong Satapornpong

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Introduction: Covid-19 has been a global pandemic for some time now, causing severe symptoms to patients that received the virus. However, there has been no report on this gene in the Thai population. Objective: Our aim in this study is to explore and compare the frequency of HLA-C allele that is associated with severe COVID-19 symptoms in Thais and other populations. Method: 200 general Thai population were enrolled in this study. The genotyping of HLA -C alleles were determined by the polymerase chain reaction with sequence-specific oligonucleotide probes (PCR-SSOP) and Luminex®IS 100 system (Luminex Corporation, Austin, Texas, USA). Results: We found that the frequency of alleles HLA-C* 01:02 (16.00%), HLA-C* 08:01(10.50%), HLA-C* 03:04 (10.25%),HLA-C* 07:02 (10.00%), HLA-C* 03:02 (9.25%), HLA-C* 07:01 (6.75%), HLA-C* 04:01 (5.00%), HLA-C* 06:02 (4.00%), HLA-C* 04:03 (4.00%), and HLA-C* 07:04 (3.75%) were more common in the Thai population. HLA-C* 01:02 (16.00%) allele was the highest frequency in the North, Center, and North East groups in Thailand, but there was the South region that was not significantly different when compared with the other groups of the region. Additionally, HLA-C∗14:02 allele was similarly distributed in Thais (3.00%), African Americans (1.98%), Caucasians (2.08%), Hispanics (1.71%), North American Natives (1.34%) and Asians (5.01%) by p-value = 0.6506, 0.6506, 0.6506, 0.6135 and 0.7182, respectively. Conclusion: Genetic variation database is important to identify HLA can be a risk factor for severe COVID-19 in many populations. In this study, we will support the research of the HLA markers for screening severe COVID-19 in many populations.

Keywords: HLA-C * 14:02, COVID-19, allele frequency, Thailand

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Authors: Farhad Asadi, Mohammad Javad Mollakazemi, Aref Ghafouri

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Recent research in neural networks science and neuroscience for modeling complex time series data and statistical learning has focused mostly on learning from high input space and signals. Local linear models are a strong choice for modeling local nonlinearity in data series. Locally weighted projection regression is a flexible and powerful algorithm for nonlinear approximation in high dimensional signal spaces. In this paper, different learning scenario of one and two dimensional data series with different distributions are investigated for simulation and further noise is inputted to data distribution for making different disordered distribution in time series data and for evaluation of algorithm in locality prediction of nonlinearity. Then, the performance of this algorithm is simulated and also when the distribution of data is high or when the number of data is less the sensitivity of this approach to data distribution and influence of important parameter of local validity in this algorithm with different data distribution is explained.

Keywords: local nonlinear estimation, LWPR algorithm, online training method, locally weighted projection regression method

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Authors: Abdelghani Qadem, Zohair Qadem, Mohamed Lasri

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At the level of the Moroccan Sais Plateau, groundwater constitutes strategic natural resources for agricultural, industrial, and domestic use. Today, due to climate change and population growth, the pressure on groundwater has increased considerably. This contribution aims to delineate and map potential areas for groundwater storage in the area in question using GIS and remote sensing. The methodology adopted is based on the identification of the thematic layers used to assess the potential recharge of the aquifer. The mapping of potential areas for groundwater storage is developed through the method of modeling and weighted overlay using the spatial analysis tool on the Geographic Information System. The results obtained can be used for the planning of future artificial recharge projects in the study area in order to ensure the good sustainable use of this underground gift.

Keywords: Morocco, climate change, groundwater, mapping, recharge

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Authors: Bo Yan, Amy Y. M. Chow

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Bereavement is recognized as a universal challenging experience. It is important to gather research evidence on protective factors in bereavement. Hope is considered as one of the protective factors in previous coping studies. The present study aims to add knowledge by investigating hope at the first month after death to predict psychological symptoms altogether including complicated grief (CG), anxiety, and depressive symptoms at the seventh month. The data were collected via one-on-one interview survey in a longitudinal project with Hong Kong hospice users (sample size 105). Most participants were at their middle age (49-year-old on average), female (72%), with no religious affiliation (58%). Bayesian Structural Equation Modeling (BSEM) analysis was conducted on the longitudinal dataset. The BSEM findings show that hope at the first month of bereavement negatively predicts both CG and anxiety symptoms at the seventh month but not for depressive symptoms. Age and gender are controlled in the model. The overall model fit is good. The current study findings suggest assessing hope at the first month of bereavement. Hope at the first month after the loss is identified as an excellent predictor for complicated grief and anxiety symptoms at the seventh month. The result from this sample is clear, so it encourages cross-cultural research on replicated modeling and development of further clinical application. Particularly, practical consideration for early intervention to increase the level of hope has the potential to reduce the psychological symptoms and thus to improve the bereaved persons’ wellbeing in the long run.

Keywords: anxiety, complicated grief, depressive symptoms, hope, structural equational modeling

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Authors: Hamed Nazeri, Pierre Mertiny, Yongsheng Ma, Kajsa Duke

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The background of the present study is the use of environment-friendly biopolymer and biocomposite materials. Among the recently introduced biopolymers, poly (propylene carbonate) (PPC) has been gaining attention. This study focuses on the size of representative volume elements (RVE) in order to simulate PPC composites reinforced by cellulose nanocrystals (CNCs) as a bio-nanocomposite. Before manufacturing nanocomposites, numerical modeling should be implemented to explore and predict mechanical properties, which may be accomplished by creating and studying a suitable RVE. In other studies, modeling of composites with rod shaped fillers has been reported assuming that fillers are unidirectionally aligned. But, modeling of non-aligned filler dispersions is considerably more difficult. This study investigates the minimum RVE size to enable subsequent FEA modeling. The matrix and nano-fillers were modeled using the finite element software ABAQUS, assuming randomly dispersed fillers with a filler mass fraction of 1.5%. To simulate filler dispersion, a Monte Carlo technique was employed. The numerical simulation was implemented to find composite elastic moduli. After commencing the simulation with a single filler particle, the number of particles was increased to assess the minimum number of filler particles that satisfies the requirements for an RVE, providing the composite elastic modulus in a reliable fashion.

Keywords: biocomposite, Monte Carlo method, nanocomposite, representative volume element

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Authors: Shweda Mohan, J. L. Nandagopal, S. Amritha

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This paper focuses on the dynamic modelling of unicycle robot. Two main concepts used for balancing unicycle robot are: reaction wheel pendulum and inverted pendulum. The pitch axis is modelled as inverted pendulum and roll axis is modelled as reaction wheel pendulum. The unicycle yaw dynamics is not considered which makes the derivation of dynamics relatively simple. For the roll controller, sliding-mode controller has been adopted and optimal methods are used to minimize switching-function chattering. For pitch controller, an LQR controller has been implemented to drive the unicycle robot to follow the desired velocity trajectory. The pitching and rolling balance could be achieved by two DC motors. Unicycle robot is a non-holonomic, non-linear, static unbalance system that has the minimal number of point contact to the ground, therefore, it is a perfect platform for researchers to study motion and balance control. These real-time solutions will be a viable solution for advanced robotic systems and controls.

Keywords: decoupled dynamics, linear quadratic regulator (LQR) control, Lyapunov function sliding mode control, unicycle robot, velocity and trajectory control

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Authors: Ahmed M. Ashteyat

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Artificial Neural Network (ANN) models have been widely used in material modeling, inter-correlations, as well as behavior and trend predictions when the nonlinear relationship between system parameters cannot be quantified explicitly and mathematically. In this paper, ANN was used to predict the residual modulus of elasticity (RME) of self compacted concrete (SCC) damaged by heat. The ANN model was built, trained, tested and validated using a total of 112 experimental data sets, gathered from available literature. The data used in model development included temperature, relative humidity conditions, mix proportions, filler types, and fiber type. The result of ANN training, testing, and validation indicated that the RME of SCC, exposed to different temperature and relative humidity levels, could be predicted accurately with ANN techniques. The reliability between the predicated outputs and the actual experimental data was 99%. This show that ANN has strong potential as a feasible tool for predicting residual elastic modulus of SCC damaged by heat within the range of input parameter. The ANN model could be used to estimate the RME of SCC, as a rapid inexpensive substitute for the much more complicated and time consuming direct measurement of the RME of SCC.

Keywords: residual modulus of elasticity, artificial neural networks, self compacted-concrete, material modeling

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Authors: Alexander de Tomás, Miquel Sierra, Stefan Pfenninger, Francesco Lombardi, Ines Campos, Cristina Madrid

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Environmental parameters are key in the definition of sustainable energy systems yet excluded from most energy system optimization models. Still, decision-making may be misleading without considering them. Environmental analyses of the energy transition are a key part of industrial ecology but often are performed without any input from the users of the information. This work assesses the systemic impacts of energy transition pathways in Portugal. Using the Calliope energy modeling framework, 250+ optimized energy system pathways are generated. A Delphi study helps to identify the relevant criteria for the stakeholders as regards the environmental assessment, which is performed with ENBIOS, a python package that integrates life cycle assessment (LCA) with a metabolic analysis based on complex relations. Furthermore, this study focuses on how the uncertainty propagates through the model’s consortium. With the aim of doing so, a soft link between the Calliope/ENBIOS cascade and Brightway’s data capabilities is built to perform Monte Carlo simulations. These findings highlight the relevance of including uncertainty analysis as a range of values rather than informing energy transition results with a single value.

Keywords: energy transition, energy modeling, uncertainty, sustainability

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Authors: G. Levacic, A. Zupan

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Application of new technological solutions and installation of new elements into the network requires special attention when investigating its interaction with the existing power system. Special attention needs to be devoted to the occurrence of harmonic resonance. Sources of increasing harmonic penetration could be wind power plants, Flexible Alternating Current Transmission System (FACTS) devices, underground and submarine cable installations etc. Calculation in frequency domain with various software, for example, the software for power systems transients EMTP-RV presents one of the most common ways to obtain the harmonic impedance of the system. Along calculations in frequency domain, such software allows performing of different type of calculations as well as steady-state domain. This paper describes a power system modeling with software EMTP-RV based on data from SCADA/EMS system. The power flow results on 220 kV and 400 kV voltage levels retrieved from EMTP-RV are verified by comparing with power flow results from power transmissions system planning software PSS/E. The determination of the harmonic impedance for the case of remote power plant connection with cable up to 2500 Hz is presented as an example of calculations in frequency domain.

Keywords: power system modeling, frequency domain, steady state, EMTP-RV, PSS/E

Procedia PDF Downloads 322

Authors: Kaoutar Chbihi, Aziza Menouni, Imane Berni, Tarik Abchouch, Samir El Jaafari

Abstract:

The unpredictability and ambiguity of a pandemic, combined with the economic impact, sedentary lifestyle, and increased living cost, have the potential to seriously raise the risk of mental health issues among the population. Therefore, this study had the aim to assess the magnitude of mental health outcomes and risk factors among the general population in Morocco in times of the Covid-19 pandemic. This study consisted of a cross-sectional design and was survey-based and region-stratified by collecting demographic data and mental health measurements from 523 participants. The degree of depression, anxiety, and insomnia symptoms were assessed by using the 9-item Patient Health Questionnaire and the 7-items Generalized Anxiety Disorder. The survey was completed by 523 individuals. Results showed that 67.9% were women, and 58.6% were aged 18-30 years. 49% of participants reported depression issues, while 39.8% experienced anxiety. Being a married woman with children was associated with severe symptoms of depression and anxiety. Finally, our findings reported a significant mental health burden among the general population of Morocco, which needs to be tackled by specific co-created interventions and adapted strategies in order to prevent impacts on public health.

Keywords: anxiety, COVID-19, depression, mental health, Morocco, pandemic

Procedia PDF Downloads 79

Authors: Ruzanna Muradyan

Abstract:

Medical data mining is a crucial field in contemporary healthcare that offers cutting-edge tactics with enormous potential to transform patient care. This abstract examines how sophisticated data mining techniques could transform the healthcare industry, with a special focus on how they might improve patient outcomes. Healthcare data repositories have dynamically evolved, producing a rich tapestry of different, multi-dimensional information that includes genetic profiles, lifestyle markers, electronic health records, and more. By utilizing data mining techniques inside this vast library, a variety of prospects for precision medicine, predictive analytics, and insight production become visible. Predictive modeling for illness prediction, risk stratification, and therapy efficacy evaluations are important points of focus. Healthcare providers may use this abundance of data to tailor treatment plans, identify high-risk patient populations, and forecast disease trajectories by applying machine learning algorithms and predictive analytics. Better patient outcomes, more efficient use of resources, and early treatments are made possible by this proactive strategy. Furthermore, data mining techniques act as catalysts to reveal complex relationships between apparently unrelated data pieces, providing enhanced insights into the cause of disease, genetic susceptibilities, and environmental factors. Healthcare practitioners can get practical insights that guide disease prevention, customized patient counseling, and focused therapies by analyzing these associations. The abstract explores the problems and ethical issues that come with using data mining techniques in the healthcare industry. In order to properly use these approaches, it is essential to find a balance between data privacy, security issues, and the interpretability of complex models. Finally, this abstract demonstrates the revolutionary power of modern data mining methodologies in transforming the healthcare sector. Healthcare practitioners and researchers can uncover unique insights, enhance clinical decision-making, and ultimately elevate patient care to unprecedented levels of precision and efficacy by employing cutting-edge methodologies.

Keywords: data mining, healthcare, patient care, predictive analytics, precision medicine, electronic health records, machine learning, predictive modeling, disease prognosis, risk stratification, treatment efficacy, genetic profiles, precision health

Procedia PDF Downloads 63

Authors: Azadeh Rezafar, Sevkiye Sence Turk

Abstract:

Rapid population growth in urban areas and extinction danger of natural resources in order to meet the food needs of these population, has revealed the need for sustainability. It did not last long that city planners realized the importance of an equal access to natural resources with protecting and managing them in cities, in accordance with the concept of sustainable development. Like in other countries The Turkish Government is aware of the importance of the sustainable development in their cities. The government issued new laws for protection of environmental assets and so that the preservation of natural ecology. The main objective of this article is to emphasis the importance of the sustainable development in the context of the developing world by giving special information about the method of the Turkish Government for protecting nature with approval of difference laws in this area.

Keywords: population growth, sustainable development, Turkey, Turkish Urban Environmental Laws

Procedia PDF Downloads 345

Authors: Swati Tomar, Sunil Kumar Gupta

Abstract:

Anammox is a novel and promising technology that has changed the traditional concept of biological nitrogen removal. The process facilitates direct oxidation of ammonical nitrogen under anaerobic conditions with nitrite as an electron acceptor without the addition of external carbon sources. The present study investigated the feasibility of anammox hybrid reactor (AHR) combining the dual advantages of suspended and attached growth media for biodegradation of ammonical nitrogen in wastewater. The experimental unit consisted of 4 nos. of 5L capacity AHR inoculated with mixed seed culture containing anoxic and activated sludge (1:1). The process was established by feeding the reactors with synthetic wastewater containing NH4-H and NO2-N in the ratio 1:1 at HRT (hydraulic retention time) of 1 day. The reactors were gradually acclimated to higher ammonium concentration till it attained pseudo steady state removal at a total nitrogen concentration of 1200 mg/l. During this period, the performance of the AHR was monitored at twelve different HRTs varying from 0.25-3.0 d with increasing NLR from 0.4 to 4.8 kg N/m3d. AHR demonstrated significantly higher nitrogen removal (95.1%) at optimal HRT of 1 day. Filter media in AHR contributed an additional 27.2% ammonium removal in addition to 72% reduction in the sludge washout rate. This may be attributed to the functional mechanism of filter media which acts as a mechanical sieve and reduces the sludge washout rate many folds. This enhances the biomass retention capacity of the reactor by 25%, which is the key parameter for successful operation of high rate bioreactors. The effluent nitrate concentration, which is one of the bottlenecks of anammox process was also minimised significantly (42.3-52.3 mg/L). Process kinetics was evaluated using first order and Grau-second order models. The first-order substrate removal rate constant was found as 13.0 d-1. Model validation revealed that Grau second order model was more precise and predicted effluent nitrogen concentration with least error (1.84±10%). A new mathematical model based on mass balance was developed to predict N2 gas in AHR. The mass balance model derived from total nitrogen dictated significantly higher correlation (R2=0.986) and predicted N2 gas with least error of precision (0.12±8.49%). SEM study of biomass indicated the presence of the heterogeneous population of cocci and rod shaped bacteria of average diameter varying from 1.2-1.5 mm. Owing to enhanced NRE coupled with meagre production of effluent nitrate and its ability to retain high biomass, AHR proved to be the most competitive reactor configuration for dealing with nitrogen laden wastewater.

Keywords: anammox, filter media, kinetics, nitrogen removal

Procedia PDF Downloads 382