Search results for: genome scale model
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 21762

Search results for: genome scale model

20352 Therapeutic Hypothermia Post Cardiac Arrest

Authors: Tahsien Mohamed Okasha

Abstract:

We hypothesized that Post cardiac arrest patients with Glasgow coma scale (GCS) score of less than (8) and who will be exposed to therapeutic hypothermia protocol will exhibit improvement in their neurological performance. Purposive sample of 17 patients who were fulfilling the inclusion criteria during one year collected. The study carried out using Quasi-experimental research design. Four Tools used for data collection of this study: Demographic and medical data sheet, Post cardiac arrest health assessment sheet, Bedside Shivering Assessment Scale (BSAS), and Glasgow Pittsburgh cerebral performance category scale (CPC). Result: the mean age was X̅ ± SD = 53 ± 8.122 years, 47.1% were arrested because of cardiac etiology. 35.3% with initial arrest rhythm ventricular tachycardia (VT), 23.5% with ventricular fibrillation (VF), and 29.4% with A-Systole. Favorable neurological outcome was seen among 70.6%. There was significant statistical difference in WBC, Platelets, blood gases value, random blood sugar. Also Initial arrest rhythm, etiology of cardiac arrest, and shivering status were significantly correlated with cerebral performance categories score. therapeutic hypothermia has positive effects on neurological performance among post cardiac arrest patients with GCS score of less than (8). replication of the study on larger probability sample, with randomized control trial design. Further study for suggesting nursing protocol for patients undergoing therapeutic hypothermia.

Keywords: therapeutic hypothermia, neurological performance, after resuscitation from cardiac arrest., resuscitation

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20351 RAPDAC: Role Centric Attribute Based Policy Driven Access Control Model

Authors: Jamil Ahmed

Abstract:

Access control models aim to decide whether a user should be denied or granted access to the user‟s requested activity. Various access control models have been established and proposed. The most prominent of these models include role-based, attribute-based, policy based access control models as well as role-centric attribute based access control model. In this paper, a novel access control model is presented called “Role centric Attribute based Policy Driven Access Control (RAPDAC) model”. RAPDAC incorporates the concept of “policy” in the “role centric attribute based access control model”. It leverages the concept of "policy‟ by precisely combining the evaluation of conditions, attributes, permissions and roles in order to allow authorization access. This approach allows capturing the "access control policy‟ of a real time application in a well defined manner. RAPDAC model allows making access decision at much finer granularity as illustrated by the case study of a real time library information system.

Keywords: authorization, access control model, role based access control, attribute based access control

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20350 Enhancing Wheat Productivity for Small-Scale Farmers in the Northern State of Sudan through Developing a Local Made Seed Cleaner and Different Seeding Methods

Authors: Yasir Hassan Satti Mohammed

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The wheat cleaner was designed, manufactured, and tested in the workshop of the department of agricultural engineering, faculty of agricultural sciences, university of Dongola, the northern state of Sudan, for the purpose of enhancing productivity for small-scale-farmers who used to plant their saved wheat seeds every season with all risk of weed infestation and low viability. A one-season field experiment was then conducted according to the Randomized Complete Block Design (RCBD) experimental design in the demonstration farm of Dongola research station using clean seeds and unclean seeds of a local wheat variety (Imam); two different planting methods were also adopted in the experiment. One is the traditional seed drilling within the recommended seed rate (50 kg.feddan⁻¹), whereas the other was the precision seeding method using half of the recommended seed rate (25 kg.feddan⁻¹). The effect of seed type and planting method on field parameters were investigated, and the data was then analyzed using a computer application SAS system version 9.3. The results revealed significant (P ≥ 0.05) and highly significant (P ≥ 0.01) differences between treatments. The precision seeding method with clean seeds increased the number of kernels per spike (KS), tillers per plant (TPP), one thousand kernels mass (TKM), the biomass of wheat (BWT), and total yield (TOY), whereas weeds per area (WSM), the biomass of weeds (BWD) and weight of weed seeds were apparently decreased compared to seed drilling with unclean seed. Wheat seed cleaner could be of great benefit for small-scale wheat farmers in Sudan who cannot afford the cleaned seeds commercially provided by the local government.

Keywords: wheat cleaner, precision seeding, seed drilling method, small-scale farmers

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20349 Efficient Bargaining versus Right to Manage in the Era of Liberalization

Authors: Panagiota Koliousi, Natasha Miaouli

Abstract:

We compare product and labour market liberalization under the two trade union bargaining models: the Right-to-Manage (RTM) model and the Efficient Bargaining (EB) model. The vehicle is a dynamic general equilibrium (DGE) model that incorporates two types of agents (capitalists and workers), imperfectly competitive product and labour markets. The model is solved numerically employing common parameter values and data from the euro area. A key message is that product market deregulation is favourable under any labour market structure while opting for labour market deregulation one should provide special attention to the structure of the labour market such as the bargaining system of unions. If the prevailing way of bargaining is the RTM model then restructuring both markets is beneficial for all agents.

Keywords: market structure, structural reforms, trade unions, unemployment

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20348 Non-Autonomous Seasonal Variation Model for Vector-Borne Disease Transferral in Kampala of Uganda

Authors: Benjamin Aina Peter, Amos Wale Ogunsola

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In this paper, a mathematical model of malaria transmission was presented with the effect of seasonal shift, due to global fluctuation in temperature, on the increase of conveyor of the infectious disease, which probably alters the region transmission potential of malaria. A deterministic compartmental model was proposed and analyzed qualitatively. Both qualitative and quantitative approaches of the model were considered. The next-generation matrix is employed to determine the basic reproduction number of the model. Equilibrium points of the model were determined and analyzed. The numerical simulation is carried out using Excel Micro Software to validate and support the qualitative results. From the analysis of the result, the optimal temperature for the transmission of malaria is between and . The result also shows that an increase in temperature due to seasonal shift gives rise to the development of parasites which consequently leads to an increase in the widespread of malaria transmission in Kampala. It is also seen from the results that an increase in temperature leads to an increase in the number of infectious human hosts and mosquitoes.

Keywords: seasonal variation, indoor residual spray, efficacy of spray, temperature-dependent model

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20347 Correlation Between Cytokine Levels and Lung Injury in the Syrian Hamster (Mesocricetus Auratus) Covid-19 Model

Authors: Gleb Fomin, Kairat Tabynov, Nurkeldy Turebekov, Dinara Turegeldiyeva, Rinat Islamov

Abstract:

The level of major cytokines in the blood of patients with COVID-19 varies greatly depending on age, gender, duration and severity of infection, and comorbidity. There are two clinically significant cytokines, IL-6 and TNF-α, which increase in levels in patients with severe COVID-19. However, in a model of COVID-19 in hamsters, TNF-α levels are unchanged or reduced, while the expression of other cytokines reflects the profile of cytokines found in patients’ plasma. The aim of our study was to evaluate the relationship between the level of cytokines in the blood, lungs, and lung damage in the model of the Syrian hamster (Mesocricetus auratus) infected with the SARS-CoV-2 strain. The study used outbred female and male Syrian hamsters (n=36, 4 groups) weighing 80-110 g and 5 months old (protocol IACUC, #4, 09/22/2020). Animals were infected intranasally with the hCoV-19/Kazakhstan/KazNAU-NSCEDI-481/2020 strain and euthanized at 3 d.p.i. The level of cytokines IL-6, TNF-α, IFN-α, and IFN-γ was determined by ELISA MyBioSourse (USA) for hamsters. Lung samples were subjected to histological processing. The presence of pathological changes in histological preparations was assessed on a 3-point scale. The work was carried out in the ABSL-3 laboratory. The data were analyzed in GraphPad Prism 6.00 (GraphPad Software, La Jolla, California, USA). The work was supported by the MES RK grant (AP09259865). In the blood, the level of TNF-α increased in males (p=0.0012) and IFN-γ in males and females (p=0.0001). On the contrary, IFN-α production decreased (p=0.0006). Only TNF-α level increased in lung tissues (p=0.0011). Correlation analysis showed a negative relationship between the level of IL-6 in the blood and lung damage in males (r -0.71, p=0.0001) and females (r-0.57, p=0.025). On the contrary, in males, the level of IL-6 in the lungs and score is positively correlated (r 0.80, p=0.01). The level of IFN-γ in the blood (r -0.64, p=0.035) and lungs (r-0.72, p=0.017) in males has a negative correlation with lung damage. No links were found for TNF-α and IFN-α. The study showed a positive association between lung injury and tissue levels of IL-6 in male hamsters. It is known that in humans, high concentrations of IL-6 in the lungs are associated with suppression of cellular immunity and, as a result, with an increase in the severity of COVID-19. TNF-α and IFN-γ play a key role in the pathogenesis of COVID-19 in hamsters. However, the mechanisms of their activity require more detailed study. IFN-α plays a lesser role in direct lung injury in a Syrian hamster model. We have shown the significance of tissue IL-6 and IFN-γ as predictors of the severity of lung damage in COVID-19 in the Syrian hamster model. Changes in the level of cytokines in the blood may not always reflect pathological processes in the lungs with COVID-19.

Keywords: syrian hamster, COVID-19, cytokines, biological model

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20346 A Two Stage Stochastic Mathematical Model for the Tramp Ship Routing with Time Windows Problem

Authors: Amin Jamili

Abstract:

Nowadays, the majority of international trade in goods is carried by sea, and especially by ships deployed in the industrial and tramp segments. This paper addresses routing the tramp ships and determining the schedules including the arrival times to the ports, berthing times at the ports, and the departure times in an operational planning level. In the operational planning level, the weather can be almost exactly forecasted, however in some routes some uncertainties may remain. In this paper, the voyaging times between some of the ports are considered to be uncertain. To that end, a two-stage stochastic mathematical model is proposed. Moreover, a case study is tested with the presented model. The computational results show that this mathematical model is promising and can represent acceptable solutions.

Keywords: routing, scheduling, tram ships, two stage stochastic model, uncertainty

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20345 The Relationship between Working Models and Psychological Safety

Authors: Rosyellen Rabelo Szvarça, Pedro Fialho, Auristela Duarte de Lima Moser

Abstract:

Background: New ways of working, such as teleworking or hybrid working, have changed and have impacted both employees and organizations. To understand the individuals' perceptions among different working models, this study aimed to investigate levels of psychological safety among employees working in person, hybrid, and remote environments and the correlation of demographic or professional characteristics. Methods: A cross-sectional survey was distributed electronically. A self-administered questionnaire was composed of sociodemographic data, academic status, professional contexts, working models, and the seven-item instrument of psychological safety. The psychological safety instrument was computed to determine its reliability, showing a Cronbach’s 0.75, considering a good scale when compared to the original, analyzed with 51 teams from a North American company, with a Cronbach's alpha coefficient of 0.82. Results: The survey was completed by 328 individuals, 60% of whom were in-person, 29.3% hybrid, and 10.7% remote. The Chi-Square test with the Bonferroni post-test for qualitative variables associated with the working models indicates a significant association (p 0.001) for academic qualifications. In-person models present 29.4% of individuals with secondary education and 38.1% undergraduate; hybrid present 51% postgraduate and 35.4% undergraduate. This was similar to remote workers, with 48.6% postgraduate and 34.3% undergraduate. There were no significant differences in gender composition between work models (p = 0.738), with most respondents being female in all three work groups. Remote workers predominated in areas such as commerce, marketing, and services; education and the public sector were common in the in-person group, while technology and the financial sector were predominant among hybrid workers (p < 0.001). As for leadership roles, there was no significant association with working models (p = 0.126). The decision on the working model was predominantly made by the organization for in-person and hybrid workers (p < 0.001). Preference for the working model was in line with the workers' scenario at that time (p < 0.001). Kruskal-Wallis test with Bonferroni's post hoc test compared the psychological safety scores between working groups, reveling statistically higher scores in hybrid group x̃ = 5.64 compared to in-person group x̃ = 5, with remote workers showing scores similar to other groups x̃ = 5.43 (p = 0.004). Age demonstrated no significant difference between the working groups (p = 0.052). On the other hand, organization tenure and job tenure were higher in in-person groups compared to the hybrid and remote groups (p < 0.001). The hybrid model illustrates a balance between in-person and remote models. The results highlight that higher levels of psychological safety can be correlated with the flexibility of hybrid work, as well as physical interaction, spontaneity, and informal relationships, which are considered determinants of high levels of psychological safety. Conclusions: Psychological safety at the group level using the seven-item scale is widely employed in comparison to other commonly employed measures. Despite psychological safety having been around for decades, primarily studied in in-person work contexts, the current findings contribute to expanding research with hybrid or remote settings. Ultimately, this investigation has demonstrated the significance of work models in assessing psychological safety levels.

Keywords: hybrid work, new ways of working, psychological safety, workplace, working models

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20344 Automatic Fluid-Structure Interaction Modeling and Analysis of Butterfly Valve Using Python Script

Authors: N. Guru Prasath, Sangjin Ma, Chang-Wan Kim

Abstract:

A butterfly valve is a quarter turn valve which is used to control the flow of a fluid through a section of pipe. Generally, butterfly valve is used in wide range of applications such as water distribution, sewage, oil and gas plants. In particular, butterfly valve with larger diameter finds its immense applications in hydro power plants to control the fluid flow. In-lieu with the constraints in cost and size to run laboratory setup, analysis of large diameter values will be mostly studied by computational method which is the best and inexpensive solution. For fluid and structural analysis, CFD and FEM software is used to perform large scale valve analyses, respectively. In order to perform above analysis in butterfly valve, the CAD model has to recreate and perform mesh in conventional software’s for various dimensions of valve. Therefore, its limitation is time consuming process. In-order to overcome that issue, python code was created to outcome complete pre-processing setup automatically in Salome software. Applying dimensions of the model clearly in the python code makes the running time comparatively lower and easier way to perform analysis of the valve. Hence, in this paper, an attempt was made to study the fluid-structure interaction (FSI) of butterfly valves by varying the valve angles and dimensions using python code in pre-processing software, and results are produced.

Keywords: butterfly valve, flow coefficient, automatic CFD analysis, FSI analysis

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20343 The Association between Attachment Styles, Satisfaction of Life, Alexithymia, and Psychological Resilience: The Mediational Role of Self-Esteem

Authors: Zahide Tepeli Temiz, Itir Tari Comert

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Attachment patterns based on early emotional interactions between infant and primary caregiver continue to be influential in adult life, in terms of mental health and behaviors of individuals. Several studies reveal that infant-caregiver relationships have impressed the affect regulation, coping with stressful and negative situations, general satisfaction of life, and self image in adulthood, besides the attachment styles. The present study aims to examine the relationships between university students’ attachment style and their self-esteem, alexithymic features, satisfaction of life, and level of resilience. In line with this aim, the hypothesis of the prediction of attachment styles (anxious and avoidant) over life satisfaction, self-esteem, alexithymia, and psychological resilience was tested. Additionally, in this study Structural Equational Modeling was conducted to investigate the mediational role of self-esteem in the relationship between attachment styles and alexithymia, life satisfaction, and resilience. This model was examined with path analysis. The sample of the research consists of 425 university students who take education from several region of Turkey. The participants who sign the informed consent completed the Demographic Information Form, Experiences in Close Relationships-Revised, Rosenberg Self-Esteem Scale, The Satisfaction with Life Scale, Toronto Alexithymia Scale, and Resilience Scale for Adults. According to results, anxious, and avoidant dimensions of insecure attachment predicted the self-esteem score and alexithymia in positive direction. On the other hand, these dimensions of attachment predicted life satisfaction in negative direction. The results of linear regression analysis indicated that anxious and avoidant attachment styles didn’t predict the resilience. This result doesn’t support the theory and research indicating the relationship between attachment style and psychological resilience. The results of path analysis revealed the mediational role self esteem in the relation between anxious, and avoidant attachment styles and life satisfaction. In addition, SEM analysis indicated the indirect effect of attachment styles over alexithymia and resilience besides their direct effect. These findings support the hypothesis of this research relation to mediating role of self-esteem. Attachment theorists suggest that early attachment experiences, including supportive and responsive family interactions, have an effect on resilience to harmful situations in adult life, ability to identify, describe, and regulate emotions and also general satisfaction with life. Several studies examining the relationship between attachment styles and life satisfaction, alexithymia, and psychological resilience draw attention to mediational role of self-esteem. Results of this study support the theory of attachment patterns with the mediation of self-image influence the emotional, cognitive, and behavioral regulation of person throughout the adulthood. Therefore, it is thought that any intervention intended for recovery in attachment relationship will increase the self-esteem, life satisfaction, and resilience level, on the one side, decrease the alexithymic features, on the other side.

Keywords: alexithymia, anxious attachment, avoidant attachment, life satisfaction, path analysis, resilience, self-esteem, structural equation

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20342 Conduction Model Compatible for Multi-Physical Domain Dynamic Investigations: Bond Graph Approach

Authors: A. Zanj, F. He

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In the current paper, a domain independent conduction model compatible for multi-physical system dynamic investigations is suggested. By means of a port-based approach, a classical nonlinear conduction model containing physical states is first represented. A compatible discrete configuration of the thermal domain in line with the elastic domain is then generated through the enhancement of the configuration of the conventional thermal element. The presented simulation results of a sample structure indicate that the suggested conductive model can cover a wide range of dynamic behavior of the thermal domain.

Keywords: multi-physical domain, conduction model, port based modeling, dynamic interaction, physical modeling

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20341 Enhancement of Indexing Model for Heterogeneous Multimedia Documents: User Profile Based Approach

Authors: Aicha Aggoune, Abdelkrim Bouramoul, Mohamed Khiereddine Kholladi

Abstract:

Recent research shows that user profile as important element can improve heterogeneous information retrieval with its content. In this context, we present our indexing model for heterogeneous multimedia documents. This model is based on the combination of user profile to the indexing process. The general idea of our proposal is to operate the common concepts between the representation of a document and the definition of a user through his profile. These two elements will be added as additional indexing entities to enrich the heterogeneous corpus documents indexes. We have developed IRONTO domain ontology allowing annotation of documents. We will present also the developed tool validating the proposed model.

Keywords: indexing model, user profile, multimedia document, heterogeneous of sources, ontology

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20340 An Improved C-Means Model for MRI Segmentation

Authors: Ying Shen, Weihua Zhu

Abstract:

Medical images are important to help identifying different diseases, for example, Magnetic resonance imaging (MRI) can be used to investigate the brain, spinal cord, bones, joints, breasts, blood vessels, and heart. Image segmentation, in medical image analysis, is usually the first step to find out some characteristics with similar color, intensity or texture so that the diagnosis could be further carried out based on these features. This paper introduces an improved C-means model to segment the MRI images. The model is based on information entropy to evaluate the segmentation results by achieving global optimization. Several contributions are significant. Firstly, Genetic Algorithm (GA) is used for achieving global optimization in this model where fuzzy C-means clustering algorithm (FCMA) is not capable of doing that. Secondly, the information entropy after segmentation is used for measuring the effectiveness of MRI image processing. Experimental results show the outperformance of the proposed model by comparing with traditional approaches.

Keywords: magnetic resonance image (MRI), c-means model, image segmentation, information entropy

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20339 Securing Land Rights for Food Security in Africa: An Appraisal of Links Between Smallholders’ Land Rights and the Right to Adequate Food in Ethiopia

Authors: Husen Ahmed Tura

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There are strong links between secure land rights and food security in Africa. However, as land is owned by governments, land users do not have adequate legislative protection. This article explores normative and implementation gaps in relation to small-scale farmers’ land rights under the Ethiopia’s law. It finds that the law facilitates eviction of small-scale farmers and indigenous peoples from their land without adequate alternative means of livelihood. It argues that as access to land and other natural resources is strongly linked to the right to adequate food, Ethiopia should reform its land laws in the light of its legal obligations under international human rights law to respect, protect and fulfill the right to adequate food and ensure freedom from hunger.

Keywords: smallholder, secure land rights , food security, right to food, land grabbing, forced evictions

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20338 Ground Surface Temperature History Prediction Using Long-Short Term Memory Neural Network Architecture

Authors: Venkat S. Somayajula

Abstract:

Ground surface temperature history prediction model plays a vital role in determining standards for international nuclear waste management. International standards for borehole based nuclear waste disposal require paleoclimate cycle predictions on scale of a million forward years for the place of waste disposal. This research focuses on developing a paleoclimate cycle prediction model using Bayesian long-short term memory (LSTM) neural architecture operated on accumulated borehole temperature history data. Bayesian models have been previously used for paleoclimate cycle prediction based on Monte-Carlo weight method, but due to limitations pertaining model coupling with certain other prediction networks, Bayesian models in past couldn’t accommodate prediction cycle’s over 1000 years. LSTM has provided frontier to couple developed models with other prediction networks with ease. Paleoclimate cycle developed using this process will be trained on existing borehole data and then will be coupled to surface temperature history prediction networks which give endpoints for backpropagation of LSTM network and optimize the cycle of prediction for larger prediction time scales. Trained LSTM will be tested on past data for validation and then propagated for forward prediction of temperatures at borehole locations. This research will be beneficial for study pertaining to nuclear waste management, anthropological cycle predictions and geophysical features

Keywords: Bayesian long-short term memory neural network, borehole temperature, ground surface temperature history, paleoclimate cycle

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20337 CFD Simulation of Spacer Effect on Turbulent Mixing Phenomena in Sub Channels of Boiling Nuclear Assemblies

Authors: Shashi Kant Verma, S. L. Sinha, D. K. Chandraker

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Numerical simulations of selected subchannel tracer (Potassium Nitrate) based experiments have been performed to study the capabilities of state-of-the-art of Computational Fluid Dynamics (CFD) codes. The Computational Fluid Dynamics (CFD) methodology can be useful for investigating the spacer effect on turbulent mixing to predict turbulent flow behavior such as Dimensionless mixing scalar distributions, radial velocity and vortices in the nuclear fuel assembly. A Gibson and Launder (GL) Reynolds stress model (RSM) has been selected as the primary turbulence model to be applied for the simulation case as it has been previously found reasonably accurate to predict flows inside rod bundles. As a comparison, the case is also simulated using a standard k-ε turbulence model that is widely used in industry. Despite being an isotropic turbulence model, it has also been used in the modeling of flow in rod bundles and to produce lateral velocities after thorough mixing of coolant fairly. Both these models have been solved numerically to find out fully developed isothermal turbulent flow in a 30º segment of a 54-rod bundle. Numerical simulation has been carried out for the study of natural mixing of a Tracer (Passive scalar) to characterize the growth of turbulent diffusion in an injected sub-channel and, afterwards on, cross-mixing between adjacent sub-channels. The mixing with water has been numerically studied by means of steady state CFD simulations with the commercial code STAR-CCM+. Flow enters into the computational domain through the mass inflow at the three subchannel faces. Turbulence intensity and hydraulic diameter of 1% and 5.9 mm respectively were used for the inlet. A passive scalar (Potassium nitrate) is injected through the mass fraction of 5.536 PPM at subchannel 2 (Upstream of the mixing section). Flow exited the domain through the pressure outlet boundary (0 Pa), and the reference pressure was 1 atm. Simulation results have been extracted at different locations of the mixing zone and downstream zone. The local mass fraction shows uniform mixing. The effect of the applied turbulence model is nearly negligible just before the outlet plane because the distributions look like almost identical and the flow is fully developed. On the other hand, quantitatively the dimensionless mixing scalar distributions change noticeably, which is visible in the different scale of the colour bars.

Keywords: single-phase flow, turbulent mixing, tracer, sub channel analysis

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20336 Extraction of Phycocyanin from Spirulina platensis by Isoelectric Point Precipitation and Salting Out for Scale Up Processes

Authors: Velasco-Rendón María Del Carmen, Cuéllar-Bermúdez Sara Paulina, Parra-Saldívar Roberto

Abstract:

Phycocyanin is a blue pigment protein with fluorescent activity produced by cyanobacteria. It has been recently studied to determine its anticancer, antioxidant and antiinflamatory potential. Since 2014 it was approved as a Generally Recognized As Safe (GRAS) proteic pigment for the food industry. Therefore, phycocyanin shows potential for the food, nutraceutical, pharmaceutical and diagnostics industry. Conventional phycocyanin extraction includes buffer solutions and ammonium sulphate followed by chromatography or ATPS for protein separation. Therefore, further purification steps are time-requiring, energy intensive and not suitable for scale-up processing. This work presents an alternative to conventional methods that also allows large scale application with commercially available equipment. The extraction was performed by exposing the dry biomass to mechanical cavitation and salting out with NaCl to use an edible reagent. Also, isoelectric point precipitation was used by addition of HCl and neutralization with NaOH. The results were measured and compared in phycocyanin concentration, purity and extraction yield. Results showed that the best extraction condition was the extraction by salting out with 0.20 M NaCl after 30 minutes cavitation, with a concentration in the supernatant of 2.22 mg/ml, a purity of 3.28 and recovery from crude extract of 81.27%. Mechanical cavitation presumably increased the solvent-biomass contact, making the crude extract visibly dark blue after centrifugation. Compared to other systems, our process has less purification steps, similar concentrations in the phycocyanin-rich fraction and higher purity. The contaminants present in our process edible NaCl or low pHs that can be neutralized. It also can be adapted to a semi-continuous process with commercially available equipment. This characteristics make this process an appealing alternative for phycocyanin extraction as a pigment for the food industry.

Keywords: extraction, phycocyanin, precipitation, scale-up

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20335 How to Change Things When Change is Hard: Beyond Teaching Facts, How Can English Language Teachers Train Students to Use the 21st Century Skills

Authors: Hameda Suwaed

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In today's world, knowledge and information are increasing in a way that no one can learn everything about every subject and the jobs that students will get after graduation may not yet exist. Therefore, teaching them just facts without teaching them how to use the facts in real life, how to work in a team and how to think critically is no longer enough. In Libya, a country characterized by using traditional methods of teaching, how can English language teachers train students to use such skills? And what type of activities and adaptations to classroom teaching methods will be necessary to do this? Using action research and classroom research gathered data, this study adjusts Heath's (2010) model of change that includes giving students clear directions, sufficient motivation and supportive environment. These steps were applied by encouraging students to participate actively in the classroom by using group work and variety of activities to train them how to find, interpret and use information. The findings of the study showed that following the suggested model can broaden students' perspectives on studying in their environment starting with their classroom and ending with their country. In conclusion, although this was a small scale study, the students' participation in the classroom shows that they gained self confidence in using practices such as group work, critical thinking, time management, creativity and how to present their ideas and accepting different opinions. What was remarkable is that most students were aware that is what we need in Libya nowadays.

Keywords: change, classroom practice, skills, Libya, group work

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20334 A Model for Solid Transportation Problem with Three Hierarchical Objectives under Uncertain Environment

Authors: Wajahat Ali, Shakeel Javaid

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In this study, we have developed a mathematical programming model for a solid transportation problem with three objective functions arranged in hierarchical order. The mathematical programming models with more than one objective function to be solved in hierarchical order is termed as a multi-level programming model. Our study explores a Multi-Level Solid Transportation Problem with Uncertain Parameters (MLSTPWU). The proposed MLSTPWU model consists of three objective functions, viz. minimization of transportation cost, minimization of total transportation time, and minimization of deterioration during transportation. These three objective functions are supposed to be solved by decision-makers at three consecutive levels. Three constraint functions are added to the model, restricting the total availability, total demand, and capacity of modes of transportation. All the parameters involved in the model are assumed to be uncertain in nature. A solution method based on fuzzy logic is also discussed to obtain the compromise solution for the proposed model. Further, a simulated numerical example is discussed to establish the efficiency and applicability of the proposed model.

Keywords: solid transportation problem, multi-level programming, uncertain variable, uncertain environment

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20333 Experimental and Numerical Analyses of Tehran Research Reactor

Authors: A. Lashkari, H. Khalafi, H. Khazeminejad, S. Khakshourniya

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In this paper, a numerical model is presented. The model is used to analyze a steady state thermo-hydraulic and reactivity insertion transient in TRR reference cores respectively. The model predictions are compared with the experiments and PARET code results. The model uses the piecewise constant and lumped parameter methods for the coupled point kinetics and thermal-hydraulics modules respectively. The advantages of the piecewise constant method are simplicity, efficiency and accuracy. A main criterion on the applicability range of this model is that the exit coolant temperature remains below the saturation temperature, i.e. no bulk boiling occurs in the core. The calculation values of power and coolant temperature, in steady state and positive reactivity insertion scenario, are in good agreement with the experiment values. However, the model is a useful tool for the transient analysis of most research reactor encountered in practice. The main objective of this work is using simple calculation methods and benchmarking them with experimental data. This model can be used for training proposes.

Keywords: thermal-hydraulic, research reactor, reactivity insertion, numerical modeling

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20332 Improved K-Means Clustering Algorithm Using RHadoop with Combiner

Authors: Ji Eun Shin, Dong Hoon Lim

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Data clustering is a common technique used in data analysis and is used in many applications, such as artificial intelligence, pattern recognition, economics, ecology, psychiatry and marketing. K-means clustering is a well-known clustering algorithm aiming to cluster a set of data points to a predefined number of clusters. In this paper, we implement K-means algorithm based on MapReduce framework with RHadoop to make the clustering method applicable to large scale data. RHadoop is a collection of R packages that allow users to manage and analyze data with Hadoop. The main idea is to introduce a combiner as a function of our map output to decrease the amount of data needed to be processed by reducers. The experimental results demonstrated that K-means algorithm using RHadoop can scale well and efficiently process large data sets on commodity hardware. We also showed that our K-means algorithm using RHadoop with combiner was faster than regular algorithm without combiner as the size of data set increases.

Keywords: big data, combiner, K-means clustering, RHadoop

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20331 Effect of Horizontal Joint Reinforcement on Shear Behaviour of RC Knee Connections

Authors: N. Zhang, J. S. Kuang, S. Mogili

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To investigate seismic performance of beam-column knee joints, four full-scale reinforced concrete beam-column knee joints, which were fabricated to simulate those in as-built RC frame buildings designed to ACI 318-14 and ACI-ASCE 352R-02, were tested under reversed cyclic loading. In the experimental programme, particular emphasis was given to the effect of horizontal reinforcement (in format of inverted U-shape bars) on the shear strength and ductility capacity of knee joints. Test results are compared with those predicted by four seismic design codes, including ACI 318-14, EC8, NZS3101 and GB50010. It is seen that the current design codes of practice cannot accurately predict the shear strength of seismically designed knee joints.

Keywords: large-scale tests, RC beam-column knee joints, seismic performance, shear strength

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20330 Using Scale Invariant Feature Transform Features to Recognize Characters in Natural Scene Images

Authors: Belaynesh Chekol, Numan Çelebi

Abstract:

The main purpose of this work is to recognize individual characters extracted from natural scene images using scale invariant feature transform (SIFT) features as an input to K-nearest neighbor (KNN); a classification learner algorithm. For this task, 1,068 and 78 images of English alphabet characters taken from Chars74k data set is used to train and test the classifier respectively. For each character image, We have generated describing features by using SIFT algorithm. This set of features is fed to the learner so that it can recognize and label new images of English characters. Two types of KNN (fine KNN and weighted KNN) were trained and the resulted classification accuracy is 56.9% and 56.5% respectively. The training time taken was the same for both fine and weighted KNN.

Keywords: character recognition, KNN, natural scene image, SIFT

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20329 Sliding Mode Control of a Bus Suspension System

Authors: Mujde Turkkan, Nurkan Yagiz

Abstract:

The vibrations, caused by the irregularities of the road surface, are to be suppressed via suspension systems. In this paper, sliding mode control for a half bus model with air suspension system is presented. The bus is modelled as five degrees of freedom (DoF) system. The mathematical model of the half bus is developed using Lagrange Equations. For time domain analysis, the bus model is assumed to travel at certain speed over the bump road. The numerical results of the analysis indicate that the sliding mode controllers can be effectively used to suppress the vibrations and to improve the ride comfort of the busses.

Keywords: active suspension system, air suspension, bus model, sliding mode control

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20328 A Novel Approach of NPSO on Flexible Logistic (S-Shaped) Model for Software Reliability Prediction

Authors: Pooja Rani, G. S. Mahapatra, S. K. Pandey

Abstract:

In this paper, we propose a novel approach of Neural Network and Particle Swarm Optimization methods for software reliability prediction. We first explain how to apply compound function in neural network so that we can derive a Flexible Logistic (S-shaped) Growth Curve (FLGC) model. This model mathematically represents software failure as a random process and can be used to evaluate software development status during testing. To avoid trapping in local minima, we have applied Particle Swarm Optimization method to train proposed model using failure test data sets. We drive our proposed model using computational based intelligence modeling. Thus, proposed model becomes Neuro-Particle Swarm Optimization (NPSO) model. We do test result with different inertia weight to update particle and update velocity. We obtain result based on best inertia weight compare along with Personal based oriented PSO (pPSO) help to choose local best in network neighborhood. The applicability of proposed model is demonstrated through real time test data failure set. The results obtained from experiments show that the proposed model has a fairly accurate prediction capability in software reliability.

Keywords: software reliability, flexible logistic growth curve model, software cumulative failure prediction, neural network, particle swarm optimization

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20327 Thermodynamic Modeling of Cryogenic Fuel Tanks with a Model-Based Inverse Method

Authors: Pedro A. Marques, Francisco Monteiro, Alessandra Zumbo, Alessia Simonini, Miguel A. Mendez

Abstract:

Cryogenic fuels such as Liquid Hydrogen (LH₂) must be transported and stored at extremely low temperatures. Without expensive active cooling solutions, preventing fuel boil-off over time is impossible. Hence, one must resort to venting systems at the cost of significant energy and fuel mass loss. These losses increase significantly in propellant tanks installed on vehicles, as the presence of external accelerations induces sloshing. Sloshing increases heat and mass transfer rates and leads to significant pressure oscillations, which might further trigger propellant venting. To make LH₂ economically viable, it is essential to minimize these factors by using advanced control techniques. However, these require accurate modelling and a full understanding of the tank's thermodynamics. The present research aims to implement a simple thermodynamic model capable of predicting the state of a cryogenic fuel tank under different operating conditions (i.e., filling, pressurization, fuel extraction, long-term storage, and sloshing). Since this model relies on a set of closure parameters to drive the system's transient response, it must be calibrated using experimental or numerical data. This work focuses on the former approach, wherein the model is calibrated through an experimental campaign carried out on a reduced-scale model of a cryogenic tank. The thermodynamic model of the system is composed of three control volumes: the ullage, the liquid, and the insulating walls. Under this lumped formulation, the governing equations are derived from energy and mass balances in each region, with mass-averaged properties assigned to each of them. The gas-liquid interface is treated as an infinitesimally thin region across which both phases can exchange mass and heat. This results in a coupled system of ordinary differential equations, which must be closed with heat and mass transfer coefficients between each control volume. These parameters are linked to the system evolution via empirical relations derived from different operating regimes of the tank. The derivation of these relations is carried out using an inverse method to find the optimal relations that allow the model to reproduce the available data. This approach extends classic system identification methods beyond linear dynamical systems via a nonlinear optimization step. Thanks to the data-driven assimilation of the closure problem, the resulting model accurately predicts the evolution of the tank's thermodynamics at a negligible computational cost. The lumped model can thus be easily integrated with other submodels to perform complete system simulations in real time. Moreover, by setting the model in a dimensionless form, a scaling analysis allowed us to relate the tested configurations to a representative full-size tank for naval applications. It was thus possible to compare the relative importance of different transport phenomena between the laboratory model and the full-size prototype among the different operating regimes.

Keywords: destratification, hydrogen, modeling, pressure-drop, pressurization, sloshing, thermodynamics

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20326 How to Applicate Knowledge Management in Security Environment within the Scope of Optimum Balance Model

Authors: Hakan Erol, Altan Elibol, Ömer Eryılmaz, Mehmet Şimşek

Abstract:

Organizations aim to manage information in a most possible effective way for sustainment and development. In doing so, they apply various procedures and methods. The very same situation is valid for each service of Armed Forces. During long-lasting endeavors such as shaping and maintaining security environment, supporting and securing peace, knowledge management is a crucial asset. Optimum Balance Model aims to promote the system from a decisive point to a higher decisive point. In this context, this paper analyses the application of optimum balance model to knowledge management in Armed Forces and tries to find answer to the question how Optimum Balance Model is integrated in knowledge management.

Keywords: optimum balance model, knowledge management, security environment, supporting peace

Procedia PDF Downloads 398
20325 Effects of Cold Treatments on Methylation Profiles and Reproduction Mode of Diploid and Tetraploid Plants of Ranunculus kuepferi (Ranunculaceae)

Authors: E. Syngelaki, C. C. F. Schinkel, S. Klatt, E. Hörandl

Abstract:

Environmental influence can alter the conditions for plant development and can trigger changes in epigenetic variation. Thus, the exposure to abiotic environmental stress can lead to different DNA methylation profiles and may have evolutionary consequences for adaptation. Epigenetic control mechanisms may further influence mode of reproduction. The alpine species R. kuepferi has diploid and tetraploid cytotypes, that are mostly sexual and facultative apomicts, respectively. Hence, it is a suitable model system for studying the correlations of mode of reproduction, ploidy, and environmental stress. Diploid and tetraploid individuals were placed in two climate chambers and treated with low (+7°C day/+2°C night, -1°C cold shocks for three nights per week) and warm (control) temperatures (+15°C day/+10°C night). Subsequently, methylation sensitive-Amplified Fragment-Length Polymorphism (AFPL) markers were used to screen genome-wide methylation alterations triggered by stress treatments. The dataset was analyzed for four groups regarding treatment (cold/warm) and ploidy level (diploid/tetraploid), and also separately for full methylated, hemi-methylated and unmethylated sites. Patterns of epigenetic variation suggested that diploids differed significantly in their profiles from tetraploids independent from treatment, while treatments did not differ significantly within cytotypes. Furthermore, diploids are more differentiated than the tetraploids in overall methylation profiles of both treatments. This observation is in accordance with the increased frequency of apomictic seed formation in diploids and maintenance of facultative apomixis in tetraploids during the experiment. Global analysis of molecular variance showed higher epigenetic variation within groups than among them, while locus-by-locus analysis of molecular variance showed a high number (54.7%) of significantly differentiated un-methylated loci. To summarise, epigenetic variation seems to depend on ploidy level, and in diploids may be correlated to changes in mode of reproduction. However, further studies are needed to elucidate the mechanism and possible functional significance of these correlations.

Keywords: apomixis, cold stress, DNA methylation, Ranunculus kuepferi

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20324 Small Scale Batch Anaerobic Digestion of Rice Straw

Authors: V. H. Nguyen, A. Castalone, C. Jamieson, M. Gummert

Abstract:

Rice straw is an abundant biomass resource in Asian countries that can be used for bioenergy. In continuously flooded rice fields, it can be removed without reducing the levels of soil organic matter. One suitable bioenergy technology is anaerobic digestion (AD), but it needs to be further verified using rice straw as a feedstock. For this study, a batch AD system was developed using rice straw and cow dung. It is low cost, farm scale, with the batch capacity ranging from 5 kg to 200 kg of straw mixed with 10% of cow dung. The net energy balance obtained was from 3000 to 4000 MJ per ton of straw input at 15-18% moisture content. Net output energy obtained from biogas and digestate ranged from 4000 to 5000 MJ per ton of straw. This indicates AD as a potential solution for converting rice straw from a waste to a clean fuel, reducing the environmental footprint caused by current disposal practices.

Keywords: rice straw, anaerobic digestion, biogas, bioenergy

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20323 A Sustainable Design Model by Integrated Evaluation of Closed-loop Design and Supply Chain Using a Mathematical Model

Authors: Yuan-Jye Tseng, Yi-Shiuan Chen

Abstract:

The paper presented a sustainable design model for integrated evaluation of the design and supply chain of a product for the sustainable objectives. To design a product, there can be alternative ways to assign the detailed specifications to fulfill the same design objectives. In the design alternative cases, different material and manufacturing processes with various supply chain activities may be required for the production. Therefore, it is required to evaluate the different design cases based on the sustainable objectives. In this research, a closed-loop design model is developed by integrating the forward design model and reverse design model. From the supply chain point of view, the decisions in the forward design model are connected with the forward supply chain. The decisions in the reverse design model are connected with the reverse supply chain considering the sustainable objectives. The purpose of this research is to develop a mathematical model for analyzing the design cases by integrated evaluating the criteria in the closed-loop design and the closed-loop supply chain. The decision variables are built to represent the design cases of the forward design and reverse design. The cost parameters in a forward design include the costs of material and manufacturing processes. The cost parameters in a reverse design include the costs of recycling, disassembly, reusing, remanufacturing, and disposing. The mathematical model is formulated to minimize the total cost under the design constraints. In practical applications, the decisions of the mathematical model can be used for selecting a design case for the purpose of sustainable design of a product. An example product is demonstrated in the paper. The test result shows that the sustainable design model is useful for integrated evaluation of the design and the supply chain to achieve the sustainable objectives.

Keywords: closed-loop design, closed-loop supply chain, design evaluation, supply chain management, sustainable design model

Procedia PDF Downloads 426