Search results for: genome scale model

Authors: Funda Kul, İsmail Gür

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Pension scheme providers have to price mortality risk by accurate mortality forecasting method. There are many mortality-forecasting methods constructed and used in literature. The Lee-Carter model is the first model to consider stochastic improvement trends in life expectancy. It is still precisely used. Mortality forecasting is done by mortality index in the Lee-Carter model. It is assumed that mortality index fits ARIMA time series model. In this paper, we propose and use dynamic normal inverse gaussian distribution to modeling mortality indes in the Lee-Carter model. Using population mortality data for Italy, France, and Turkey, the model is forecasting capability is investigated, and a comparative analysis with other models is ensured by some well-known benchmarking criterions.

Keywords: mortality, forecasting, lee-carter model, normal inverse gaussian distribution

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Authors: Piotr Fiszeder, Marcin Fałdziński, Peter Molnár

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The dynamic conditional correlation model of Engle (2002) is one of the most popular multivariate volatility models. However, this model is based solely on closing prices. It has been documented in the literature that the high and low price of the day can be used in an efficient volatility estimation. We, therefore, suggest a model which incorporates high and low prices into the dynamic conditional correlation framework. Empirical evaluation of this model is conducted on three datasets: currencies, stocks, and commodity exchange-traded funds. The utilisation of realized variances and covariances as proxies for true variances and covariances allows us to reach a strong conclusion that our model outperforms not only the standard dynamic conditional correlation model but also a competing range-based dynamic conditional correlation model.

Keywords: volatility, DCC model, high and low prices, range-based models, covariance forecasting

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Authors: C. Shih, J. R. Wang, H. C. Chang, S. W. Chen, S. C. Chiang, T. Y. Yu

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After the measurement uncertainty recapture (MUR) power uprates, Kuosheng nuclear power plant (NPP) was uprated the power from 2894 MWt to 2943 MWt. For power upgrade, several codes (e.g., TRACE, RELAP5, etc.) were applied to assess the safety of Kuosheng NPP. Hence, the main work of this research is to establish a RELAP5/MOD3.3 model of Kuosheng NPP with SNAP interface. The establishment of RELAP5/SNAP model was referred to the FSAR, training documents, and TRACE model which has been developed and verified before. After completing the model establishment, the startup test scenarios would be applied to the RELAP5/SNAP model. With comparing the startup test data and TRACE analysis results, the applicability of RELAP5/SNAP model would be assessed.

Keywords: RELAP5, TRACE, SNAP, BWR

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Authors: Michael Zenker, Henrik Prinzhorn, Christian Böning, Tom Strating

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Large-scale products are often assembled according to the job-site principle, meaning that during the assembly the product is located at a fixed position, while the area requirements are constantly changing. On one hand, the product itself is growing with each assembly step, whereas varying areas for storage, machines or working areas are temporarily required. This is an important factor when arranging products to be assembled within the factory. Currently, it is common to reserve a fixed area for each product to avoid overlaps or collisions with the other assemblies. Intending to be large enough to include the product and all adjacent areas, this reserved area corresponds to the superposition of the maximum extents of all required areas of the product. In this procedure, the reserved area is usually poorly utilized over the course of the entire assembly process; instead a large part of it remains unused. If the available area is a limited resource, a systematic arrangement of the products, which complies with the dynamic area requirements, will lead to an increased area utilization and productivity. This paper presents the results of a study on the arrangement of assembly objects assuming dynamic, competing area requirements. First, the problem situation is extensively explained, and existing research on associated topics is described and evaluated on the possibility of an adaptation. Then, a newly developed mathematical optimization model is introduced. This model allows an optimal arrangement of dynamic areas, considering logical and practical constraints. Finally, in order to quantify the potential of the developed method, some test series results are presented, showing the possible increase in area utilization.

Keywords: dynamic area requirements, facility layout problem, optimization model, product assembly

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Authors: Hoda Ghavamipoor, S. Alireza Hashemi Golpayegani

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An approach to model the customer interaction with e-commerce websites is presented. Considering the service quality level as a predictive feature, we offer an improved method based on the Customer Behavior Model Graph (CBMG), a state-transition graph model. To derive the Quality of Service sensitive-CBMG (QoS-CBMG) model, process-mining techniques is applied to pre-processed website server logs which are categorized as ‘buy’ or ‘visit’. Experimental results on an e-commerce website data confirmed that the proposed method outperforms CBMG based method.

Keywords: customer behavior model, electronic commerce, quality of service, customer behavior model graph, process mining

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Authors: Aref Yazdani, Ali Tofighi

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We study a simulative model for production of stable micro black holes based on investigation on thermodynamics of LHC experiment. We show that how this production can be achieved through a thermodynamic process of stability. Indeed, this process can be done through a very small amount of powerful fuel. By applying the second law of black hole thermodynamics at the scale of quantum gravity and perturbation expansion of the given entropy function, a time-dependent potential function is obtained which is illustrated with exact numerical values in higher dimensions. Seeking for the conditions for stability of micro black holes is another purpose of this study. This is proven through an injection method of putting the exact amount of energy into the final phase of the production which is equivalent to the same energy injection into the center of collision at the LHC in order to stabilize the produced particles. Injection of energy into the center of collision at the LHC is a new pattern that it is worth a try for the first time.

Keywords: micro black holes, LHC experiment, black holes thermodynamics, extra dimensions model

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Authors: Sneha Samal, Iva Petrikova, Bohdana Marvalova

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Influence of grain size, shape and grain boundary diffusion at high temperature oxidation of pure metal is investigated as the function of microstructure evolution in this article. The oxidized scale depends on the geometrical parameter of the metal-scale system and grain shape, size, diffusion through boundary layers and influence of the contamination. The creation of the inner layer and the morphological structure develops from the internal stress generated during the growth of the scale. The oxidation rate depends on the cation and anion mobile transport of the metal in the inward and outward direction of the diffusion layer. Oxidation rate decreases with decreasing the grain size of the pure metal, whereas zinc deviates from this principle. A strong correlation between the surface roughness evolution, grain size, crystalline properties and oxidation mechanism of the oxidized metal was established.

Keywords: high temperature oxidation, pure metals, grain size, shape and grain boundary

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Authors: Ishit Sheth, Chandrasekhar Jinendran, Chinmaya Ranjan Sahu

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A fourteen degree of freedom (DOF) ride and handling control mathematical model is developed for a car using generalized boltzmann hamel equation which will create a basis for design of ride and handling controller. Mathematical model developed yield equations of motion for non-holonomic constrained systems in quasi-coordinates. The governing differential equation developed integrates ride and handling control of car. Model-based systems engineering approach is implemented for simulation using matlab/simulink, vehicle’s response in different DOF is examined and later validated using commercial software (ADAMS). This manuscript involves detailed derivation of full car vehicle model which provides response in longitudinal, lateral and yaw motion to demonstrate the advantages of the developed model over the existing dynamic model. The dynamic behaviour of the developed ride and handling model is simulated for different road conditions.

Keywords: Full Vehicle Model, MBSE, Non Holonomic Constraints, Boltzmann Hamel Equation

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Authors: Jolanta Tamošaitienė

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The article focuses on a developed comprehensive model to be used in an agile environment for the risk assessment and selection based on multi-attribute methods. The model is based on a multi-attribute evaluation of risk in construction, and the determination of their optimality criterion values are calculated using complex Multiple Criteria Decision-Making methods. The model may be further applied to risk assessment in an agile construction environment. The attributes of risk in a construction project are selected by applying the risk assessment condition to the construction sector, and the construction process efficiency in the construction industry accounts for the agile environment. The paper presents the comprehensive risk assessment model in an agile construction environment. It provides a background and a description of the proposed model and the developed analysis of the comprehensive risk assessment model in an agile construction environment with the criteria.

Keywords: assessment, environment, agile, model, risk

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Authors: Rit M., Girard R., Villot J., Thorel M.

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In a scenario of extensive residential housing renovation, stakeholders need models that support decision-making through a deep understanding of the existing building stock and accurate energy demand simulations. To address this need, we have modified an optimization model using open data that enables the study of renovation strategies at both territorial and national scales. This approach provides (1) a definition of a strategy to simplify decision trees from theoretical combinations, (2) input to decision makers on real-world renovation constraints, (3) more reliable identification of energy-saving measures (changes in technology or behaviour), and (4) discrepancies between currently planned and actually achieved strategies. The main contribution of the studies described in this document is the geographic scale: all residential buildings in the areas of interest were modeled and simulated using national data (geometries and attributes). These buildings were then renovated, when necessary, in accordance with the environmental objectives, taking into account the constraints applicable to each territory (number of renovations per year) or at the national level (renovation of thermal deficiencies (Energy Performance Certificates F&G)). This differs from traditional approaches that focus only on a few buildings or archetypes. This model can also be used to analyze the evolution of a building stock as a whole, as it can take into account both the construction of new buildings and their demolition or sale. Using specific case studies of French territories, this paper highlights a significant discrepancy between the strategies currently advocated by decision-makers and those proposed by our optimization model. This discrepancy is particularly evident in critical metrics such as the relationship between the number of renovations per year and achievable climate targets or the financial support currently available to households and the remaining costs. In addition, users are free to seek optimizations for their building stock across a range of different metrics (e.g., financial, energy, environmental, or life cycle analysis). These results are a clear call to re-evaluate existing renovation strategies and take a more nuanced and customized approach. As the climate crisis moves inexorably forward, harnessing the potential of advanced technologies and data-driven methodologies is imperative.

Keywords: residential housing renovation, MILP, energy demand simulations, data-driven methodology

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Authors: Rouzbeh Jafari, Joe Nava

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This study includes learnings from an engineering practice normally performed on large scale biohydrogen processes. If properly scale-up is done, biohydrogen can be a reliable pathway for biowaste valorization. Most of the studies on biohydrogen process development have used model feedstock to investigate process key performance indicators (KPIs). This study does not intend to compare different technologies with model feedstock. However, it reports economic drivers and technical challenges which help in developing a road map for expanding biohydrogen economy deployment in Canada. BBA is a consulting firm responsible for the design of hydrogen production projects. Through executing these projects, activity has been performed to identify, register and mitigate technical drawbacks of large-scale hydrogen production. Those learnings, in this study, have been applied to the biohydrogen process. Through data collected by a comprehensive literature review, a base case has been considered as a reference, and several case studies have been performed. Critical parameters of the process were identified and through common engineering practice (process design, simulation, cost estimate, and life cycle assessment) impact of these parameters on the commercialization risk matrix and class 5 cost estimations were reported. The process considered in this study is food waste and woody biomass dark fermentation. To propose a reliable road map to develop a sustainable biohydrogen production process impact of critical parameters was studied on the end-to-end process. These parameters were 1) feedstock composition, 2) feedstock pre-treatment, 3) unit operation selection, and 4) multi-product concept. A couple of emerging technologies also were assessed such as photo-fermentation, integrated dark fermentation, and using ultrasound and microwave to break-down feedstock`s complex matrix and increase overall hydrogen yield. To properly report the impact of each parameter KPIs were identified as 1) Hydrogen yield, 2) energy consumption, 3) secondary waste generated, 4) CO2 footprint, 5) Product profile, 6) $/kg-H2 and 5) environmental impact. The feedstock is the main parameter defining the economic viability of biohydrogen production. Through parametric studies, it was found that biohydrogen production favors feedstock with higher carbohydrates. The feedstock composition was varied, by increasing one critical element (such as carbohydrate) and monitoring KPIs evolution. Different cases were studied with diverse feedstock, such as energy crops, wastewater slug, and lignocellulosic waste. The base case process was applied to have reference KPIs values and modifications such as pretreatment and feedstock mix-and-match were implemented to investigate KPIs changes. The complexity of the feedstock is the main bottleneck in the successful commercial deployment of the biohydrogen process as a reliable pathway for waste valorization. Hydrogen yield, reaction kinetics, and performance of key unit operations highly impacted as feedstock composition fluctuates during the lifetime of the process or from one case to another. In this case, concept of multi-product becomes more reliable. In this concept, the process is not designed to produce only one target product such as biohydrogen but will have two or multiple products (biohydrogen and biomethane or biochemicals). This new approach is being investigated by the BBA team and the results will be shared in another scientific contribution.

Keywords: biohydrogen, process scale-up, economic evaluation, commercialization uncertainties, hydrogen economy

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Authors: Guowei Hou, Lixin Yu, Wei Zhuang, Hui Qin, Xue Yang

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Formal verification is proposed to ensure the correctness of the design and make functional verification more efficient. As cache plays a vital role in the design of System on Chip (SoC), and cache with Memory Management Unit (MMU) and cache memory unit makes the state space too large for simulation to verify, then a formal verification is presented for such system design. In the paper, a formal model checking verification flow is suggested and a new cache memory model which is called “exhaustive search model” is proposed. Instead of using large size ram to denote the whole cache memory, exhaustive search model employs just two cache blocks. For cache system contains data cache (Dcache) and instruction cache (Icache), Dcache memory model and Icache memory model are established separately using the same mechanism. At last, the novel model is employed to the verification of a cache which is module of a custom-built SoC system that has been applied in practical, and the result shows that the cache system is verified correctly using the exhaustive search model, and it makes the verification much more manageable and flexible.

Keywords: cache system, formal verification, novel model, system on chip (SoC)

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Authors: Sukrat Sinha, Abhay Kumar, Shanthy Sundaram

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The Leishmania homologue of activated C kinase (LACK) is known T cell epitope from soluble Leishmania antigens (SLA) that confers protection against Leishmania challenge. This antigen has been found to be highly conserved among Leishmania strains. LACK has been shown to be protective against L. donovani challenge. A comprehensive analysis of several LACK sequences was completed. The analysis shows a high level of conservation, lower variability and higher antigenicity in specific portions of the LACK protein. This information provides insights for the potential consideration of LACK as a putative candidate in the context of visceral Leishmaniasis vaccine target.

Keywords: bioinformatics, genome assembly, leishmania activated protein kinase c (lack), next-generation sequencing

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Authors: Owamah Hilary, O. C. Izinyon

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Many existing biogas kinetic models are difficult to apply to substrates they were not developed for, as they are substrate specific. Biodegradability kinetic (BIK) model and maximum biogas production potential and stability assessment (MBPPSA) model were therefore developed in this study for the anaerobic co-digestion of food waste and maize husk. Biodegradability constant (k) was estimated as 0.11d-1 using the BIK model. The results of maximum biogas production potential (A) obtained using the MBPPSA model corresponded well with the results obtained using the popular but complex modified Gompertz model for digesters B-1, B-2, B-3, B-4, and B-5. The (If) value of MBPPSA model also showed that digesters B-3, B-4, and B-5 were stable, while B-1 and B-2 were unstable. Similar stability observation was also obtained using the modified Gompertz model. The MBPPSA model can therefore be used as alternative model for anaerobic digestion feasibility studies and plant design.

Keywords: biogas, inoculum, model development, stability assessment

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Authors: Maryam Kiani, Abdul Basit Kiani

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At larger scales, the performance of cementitious materials is impacted by processes occurring at the nanometer scale. These materials boast intricate hierarchical structures with random features that span from the nanometer to millimeter scale. It is fascinating to observe how the nanoscale processes influence the overall behavior and characteristics of these materials. By delving into and manipulating these processes, scientists and engineers can unlock the potential to create more durable and sustainable infrastructure and construction materials. It's like unraveling a hidden tapestry of secrets that hold the key to building stronger and more resilient structures. The present work employs simulations as the computational modeling methodology to predict mechanical properties for carbon/silica based cementitious materials at the molecular/nano scale level. Studies focused on understanding the effect of higher mechanical properties of cementitious materials with carbon silica nanoparticles via Material Studio materials modeling.

Keywords: nanomaterials, SiO₂, carbon black, mechanical properties

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Authors: Chui Ka Shing

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This case study research attempts to examine the use of the Bar Model Method approach in learning and teaching mathematics in a primary school in Hong Kong. The objectives of the study are to find out to what extent (a) the Bar Model Method approach enhances the construction of students’ mathematics concepts, and (b) the school-based mathematics curriculum development with adopting the Bar Model Method approach. This case study illuminates the effectiveness of using the Bar Model Method to solve mathematics problems from Primary 1 to Primary 6. Some effective pedagogies and assessments were developed to strengthen the use of the Bar Model Method across year levels. Suggestions including school-based curriculum development for using Bar Model Method and further study were discussed.

Keywords: bar model method, curriculum development, mathematics education, problem solving

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Authors: José Silvestre Mendoza Figueroa, Anders Kvarnheden, Jesús Méndez Lozano, Edgar Antonio Rodríguez Negrete, Manuel Soriano García

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Agroindustrial plants such as cereals and pseudo cereals offer a substantial source of biomacromolecules, as they contain large amounts per tissue-gram of proteins, polysaccharides and lipids in comparison with other plants. In particular, Amaranthus hypochondriacus seeds have high levels of proteins in comparison with other cereal and pseudo cereal species, which makes the plant a good source of bioactive molecules such as peptides. Geminiviruses are one principal class of pathogens that causes important economic losses in crops, affecting directly the development and production of the plant. One such virus is the Tomato yellow leaf curl virus (TYLCV), which affects mainly Solanacea family plants such as tomato species. The symptoms of the disease are curling of leaves, chlorosis, dwarfing and floral abortion. The aim of this work was to get peptides derived from enzymatic hydrolysis of globulins and albumins from amaranth seeds with specific recognition of the replication origin in the TYLCV genome, and to test the antiviral activity on host plants with the idea to generate a direct control of this viral infection. Globulins and albumins from amaranth were extracted, the fraction was enzymatically digested with papain, and the aromatic peptides fraction was selected for further purification. Six peptides were tested against the replication origin (OR) using affinity assays, surface resonance plasmon and fluorescent titration, and two of these peptides showed high affinity values to the replication origin of the virus, dissociation constant values were calculated and showed specific interaction between the peptide Ampep1 and the OR. An in vitro replication test of the total TYLCV DNA was performed, in which the peptide AmPep1 was added in different concentrations to the system reaction, which resulted in a decrease of viral DNA synthesis when the peptide concentration increased. Also, we showed that the peptide can decrease the complementary DNA chain of the virus in Nicotiana benthamiana leaves, confirming that the peptide binds to the OR and that its expected mechanism of action is to decrease the replication rate of the viral genome. In an infection assay, N. benthamiana plants were agroinfected with TYLCV-Israel and TYLCV-Guasave. After confirming systemic infection, the peptide was infiltrated in new infected leaves, and the plants treated with the peptide showed a decrease of virus symptoms and viral titer. In order to confirm the antiviral activity in a commercial crop, tomato plants were infected with TYLCV. After confirming systemic infection, plants were infiltrated with peptide solution as above, and the symptom development was monitored 21 days after treatment, showing that tomato plants treated with peptides had lower symptom rates and viral titer. The peptide was also tested against other begomovirus such as Pepper huasteco yellow vein virus (PHYVV-Guasave), showing a decrease of symptoms in N. benthamiana infected plants. The model of direct biochemical control of TYLCV infection shown in this work can be extrapolated to other begomovirus infections, and the methods reported here can be used for design of antiviral agrochemicals for other plant virus infections.

Keywords: agrochemical screening, antiviral, begomovirus, geminivirus, peptides, plasmon, TYLCV

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Authors: Tri Harianto, Lawalenna Samang, St. Hijraini Nur, Arwin

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Recently, a port development is constructed in Makassar city, South Sulawesi Province, Indonesia. Makassar city is located in lowland area that dominated by soft marine clay deposit. A two kilometers causeway construction was built which is situated on the soft clay layer. In order to investigate the behavior of causeway embankment, a full-scale test was conducted of high embankment built on a soft clay deposit. The embankment with 3,5 m high was supported by two types of reinforcement such as raft and raft-aggregate column foundation. Since the ground was undergoing consolidation due to the preload, the raft and raft-aggregate column foundations were monitored in order to analyze the vertical ground movement by inducing the settlement of the foundation. In this study, two types of foundation (raft and raft-aggregate column) were tested to observe the effectiveness of raft-aggregate column compare to raft foundation in reducing the settlement. The settlement monitored during the construction stage by using the settlement plates, which is located in the center and toe of the embankment. Measurements were taken every day for each embankment construction stage (4 months). In addition, an analytical calculation was conducted in this study to compare the full-scale test result. The result shows that the raft-aggregate column foundation significantly reduces the settlement by 30% compared to the raft foundation. A raft-aggregate column foundation also reduced the time period of each loading stage. The Good agreement of analytical calculation compared to the full-scale test result also found in this study.

Keywords: full-scale, preloading, raft-aggregate column, soft clay

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Authors: Jasna Hrncic

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Poor family relations predict depression, but also to other mental health issues. Mediating effect of self-efficacy and differentiation of self and moderating effect of decreased accessibility and/or success of other adaptive and defensive mechanisms for overcoming social disadvantages could explain depression as a specific outcome of dysfunctional family relations. The present study analyzes the mediation effect of self-efficacy and differentiation of self from poor family functioning to depressive symptoms and the moderation effect of deprivation of liberty on the listed mediation effect. Deprivation of liberty has, as a general consequence, a decreased accessibility and/or success of many adaptive and defensive mechanisms. It is hypothesized that: 1) self-efficacy and differentiation of self will mediate between family functioning and depressiveness in the total sample, and 2) deprivation of liberty will moderate the stated relations. Cross-sectional study was conducted among 323 male juveniles in Serbia divided in three groups: 98 adolescents deprived of their liberty due to antisocial behavior (incarcerated antisocial group - IAG), 121 adolescents with antisocial behavior in their natural setting (antisocial control group - CAG) and 105 adolescents in general population (general control group - CGG). The CAG was included along with GCG to control the possible influence that comorbidity of antisocial behavior and depressiveness could have on results. Instruments for family relations assessment were: for a whole family of origin the emotional exchange scale and individuation scale from GRADIR by Knezevic, and for a relationship with mother PCS-YSR and CRPBI by barber, and intimacy, rejection, sacrifice, punishment, demands, control and internal control by Opacic and Kos. Differentiation of self (DOS) is measured by emotional self scale (Opacic), self-efficacy (SE) by general incompetence scale by Bezinovic, and depression by BDI (Back), CES-D (Radloff) and D6R (Momirovic). Two-path structural equation modeling based on most commonly reported fit indices, showed that the mediation model had unfavorable fit to our data for total sample [(χ2 (1, N = 324) = 13.73); RMSEA= .20 (90% CI= [.12, .30]); CFI= .98; NFI= .97; AIC=31.73]. Path model provided an adequate fit to the data only for AIG - and not to the data from ACG and GCG. SE and DOS mediated the relationship between PFF and depressiveness. Test of the indirect effects revealed that 23.85% of PFF influences on depressiveness is mediated by these two mediators (the quotient of mediated effect = .24). Test of specific indirect effects showed that SE mediates 22.17%, while DOS mediates 1.67% of PFF influence on depressiveness. Lack of expected mediation effect could be explained by missing other potential mediators (i.e., relationship with that father, social skills, self-esteem) and lower variability of both predictor and criterion variable due to their low levels on the whole sample and on control subsamples. Results suggested that inaccessibility and/or successfulness of other adaptive and defensive mechanisms for overcoming social disadvantages has a strong impact on the mediation effect of self/efficacy and differentiation of self from poor family functioning to depressive symptoms. Further researches could include other potential mediators and a sample of clinically depressed people.

Keywords: antisocial behavior, mediating effect, moderating effect, natural setting, incarceration

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Authors: Yun-Tao Zhang, Jong-Yeop Bae, Whoi-Yul Kim

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Background modeling and subtraction in video analysis has been widely proved to be an effective method for moving objects detection in many computer vision applications. Over the past years, a large number of approaches have been developed to tackle different types of challenges in this field. However, the dynamic background and illumination variations are two of the most frequently occurring issues in the practical situation. This paper presents a new two-layer model based on codebook algorithm incorporated with local binary pattern (LBP) texture measure, targeted for handling dynamic background and illumination variation problems. More specifically, the first layer is designed by block-based codebook combining with LBP histogram and mean values of RGB color channels. Because of the invariance of the LBP features with respect to monotonic gray-scale changes, this layer can produce block-wise detection results with considerable tolerance of illumination variations. The pixel-based codebook is employed to reinforce the precision from the outputs of the first layer which is to eliminate false positives further. As a result, the proposed approach can greatly promote the accuracy under the circumstances of dynamic background and illumination changes. Experimental results on several popular background subtraction datasets demonstrate a very competitive performance compared to previous models.

Keywords: background subtraction, codebook model, local binary pattern, dynamic background, illumination change

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Authors: Rajendra Singh, Krishna Mondal, Chandranath Chatterjee

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The water, energy, and food (WEF) nexus describes the interconnectedness of these three essential elements of human life. Each of these three sectors depends on the others. India's expanding population, urbanization, and industrialization make WEF nexus management difficult. Coupling and coordination degrees can be used as indicators of a complex system's level of sustainable development. Thus, coupling and coordination of WEF sectors in India are essential for achieving Sustainable Development Goals (SDGs) 2 (zero hunger), 6 (clean water and sanitation), and 7 (affordable and clean energy). This study used a newly developed WEF nexus model and the concept of coupling coordination degree model to examine the coupling and coordination degrees of the WEF nexus at India's sub-national scale (States/Union Territories (UTs)) for the years 2011 and 2021. Results indicate that the WEF nexus coupling degree was reasonably stable among the Indian States/UTs in both years, with all having a coupling degree above 0.90, indicating high-quality coupling. However, the degree of coordination varied spatially and temporally from ‘primary development’ to ‘quality development’ for the Indian States/UTs. In 2021, it went from 53% to 14% intermediate development and 44% to 83% good development compared to 2011. Most Indian States/UTs developed SDG2 more than SDG6 and SDG7. This study also suggests that most States/UTs must implement WEF-related policies and programmes effectively to achieve quality coordinated WEF nexus development. This study may help administrators and policymakers identify States/UTs that need more attention to implement existing or new policies for achieving SDGs 2, 6, and 7.

Keywords: WEF nexus model, Pardee-RAND WEF nexus, sustainable development, policy

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Authors: Nawal Alawad, Passent Ibrahim Tantawi, Mohamed Abdel Salam Ragheb

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Providing customers with quality experiences has been confirmed to be a sustainable, competitive advantage with a distinct financial impact for companies. The success of service providers now relies on their ability to provide customer-centric services. The importance of perceived service quality and customer experience is widely recognized. The focus of this research is in the area of mobile and fixed broadband services. This study is of dual importance both academically and practically. Academically, this research applies a new model investigating the impact of customer experience quality on loyalty based on modifying the multiple-item scale for measuring customers’ service experience in a new area and did not depend on the traditional models. The integrated scale embraces four dimensions: service experience, outcome focus, moments of truth and peace of mind. In addition, it gives a scientific explanation for this relationship so this research fill the gap in such relations in which no one correlate or give explanations for these relations before using such integrated model and this is the first time to apply such modified and integrated new model in telecom field. Practically, this research gives insights to marketers and practitioners to improve customer loyalty through evolving the experience quality of broadband customers which is interpreted to suggested outcomes: purchase, commitment, repeat purchase and word-of-mouth, this approach is one of the emerging topics in service marketing. Data were collected through 412 questionnaires and analyzed by using structural equation modeling.Findings revealed that both outcome focus and moments of truth have a significant impact on loyalty while both service experience and peace of mind have insignificant impact on loyalty.In addition, it was found that 72% of the variation occurring in loyalty is explained by the model. The researcher also measured the net prompters score and gave explanation for the results. Furthermore, assessed customer’s priorities of broadband services. The researcher recommends that the findings of this research will extend to be considered in the future plans of Telecom Egypt Group. In addition, to be applied in the same industry especially in the developing countries that have the same circumstances with similar service settings. This research is a positive contribution in service marketing, particularly in telecom industry for making marketing more reliable as managers can relate investments in service experience directly with the performance closest to income for instance, repurchasing behavior, positive word of mouth and, commitment. Finally, the researcher recommends that future studies should consider this model to explain significant marketing outcomes such as share of wallet and ultimately profitability.

Keywords: broadband services, customer experience quality, loyalty, net promoters score

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Authors: M. A. Ojo, O. A. Ojo, A. I. Odine, A. Ogaji

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The study examined marginal productivity analysis of small scale yam and cassava farmers in Kogi State, Nigeria. Data used for the study were obtained from primary source using a multi-stage sampling technique with structured questionnaires administered to 150 randomly selected yam and cassava farmers from three Local Government Areas of the State. Description statistics, data envelopment analysis and Cobb-Douglas production function were used to analyze the data. The DEA result on the overall technical efficiency of the farmers showed that 40% of the sampled yam and cassava farmers in the study area were operating at frontier and optimum level of production with mean technical efficiency of 1.00. This implies that 60% of the yam and cassava farmers in the study area can still improve their level of efficiency through better utilization of available resources, given the current state of technology. The results of the Cobb-Douglas analysis of factors affecting the output of yam and cassava farmers showed that labour, planting materials, fertilizer and capital inputs positively and significantly affected the output of the yam and cassava farmers in the study area. The study further revealed that yam and cassava farms in the study area operated under increasing returns to scale. This result of marginal productivity analysis further showed that relatively efficient farms were more marginally productive in resource utilization This study also shows that estimating production functions without separating the farms to efficient and inefficient farms bias the parameter values obtained from such production function. It is therefore recommended that yam and cassava farmers in the study area should form cooperative societies so as to enable them have access to productive inputs that will enable them expand. Also, since using a single equation model for production function produces a bias parameter estimates as confirmed above, farms should, therefore, be decomposed into efficient and inefficient ones before production function estimation is done.

Keywords: marginal productivity, DEA, production function, Kogi state

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Authors: Donatella Giuliani

Abstract:

In this research, we propose an unsupervised grayscale image segmentation method based on a combination of the Firefly Algorithm and the Gaussian Mixture Model. Firstly, the Firefly Algorithm has been applied in a histogram-based research of cluster means. The Firefly Algorithm is a stochastic global optimization technique, centered on the flashing characteristics of fireflies. In this context it has been performed to determine the number of clusters and the related cluster means in a histogram-based segmentation approach. Successively these means are used in the initialization step for the parameter estimation of a Gaussian Mixture Model. The parametric probability density function of a Gaussian Mixture Model is represented as a weighted sum of Gaussian component densities, whose parameters are evaluated applying the iterative Expectation-Maximization technique. The coefficients of the linear super-position of Gaussians can be thought as prior probabilities of each component. Applying the Bayes rule, the posterior probabilities of the grayscale intensities have been evaluated, therefore their maxima are used to assign each pixel to the clusters, according to their gray-level values. The proposed approach appears fairly solid and reliable when applied even to complex grayscale images. The validation has been performed by using different standard measures, more precisely: the Root Mean Square Error (RMSE), the Structural Content (SC), the Normalized Correlation Coefficient (NK) and the Davies-Bouldin (DB) index. The achieved results have strongly confirmed the robustness of this gray scale segmentation method based on a metaheuristic algorithm. Another noteworthy advantage of this methodology is due to the use of maxima of responsibilities for the pixel assignment that implies a consistent reduction of the computational costs.

Keywords: clustering images, firefly algorithm, Gaussian mixture model, meta heuristic algorithm, image segmentation

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Authors: Wang Xiaoqing, Fang Youyuan, Zheng Yanxing, Gu Tianyang, Zong Jianjian, Tong Jinrong

Abstract:

Compared with traditional distributed environment, the net-centric environment brings on more demanding challenges for information sharing with the characteristics of ultra-large scale and strong distribution, dynamic, autonomy, heterogeneity, redundancy. This paper realizes an information sharing model and a series of core services, through which provides an open, flexible and scalable information sharing platform.

Keywords: net-centric environment, information sharing, metadata registry and catalog, cross-domain data access control

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Authors: U. P. L. Wijayarathne, K. C. Wasalathilake

Abstract:

This work presents the modelling and simulation of saponification of ethyl acetate in the presence of sodium hydroxide in a plug flow reactor using Aspen Plus simulation software. Plug flow reactors are widely used in the industry due to the non-mixing property. The use of plug flow reactors becomes significant when there is a need for continuous large scale reaction or fast reaction. Plug flow reactors have a high volumetric unit conversion as the occurrence for side reactions is minimum. In this research Aspen Plus V8.0 has been successfully used to simulate the plug flow reactor. In order to simulate the process as accurately as possible HYSYS Peng-Robinson EOS package was used as the property method. The results obtained from the simulation were verified by the experiment carried out in the EDIBON plug flow reactor module. The correlation coefficient (r2) was 0.98 and it proved that simulation results satisfactorily fit for the experimental model. The developed model can be used as a guide for understanding the reaction kinetics of a plug flow reactor.

Keywords: aspen plus, modelling, plug flow reactor, simulation

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Authors: Irtaza M. Syed, Kaamran Raahemifar

Abstract:

This paper presents modeling of a Alternating Current (AC) Photovoltaic (PV) module using Matlab/Simulink. The proposed AC-PV module model is simple, realistic, and application oriented. The model is derived on module level as compared to cell level directly from the information provided by the manufacturer data sheet. DC-PV module, MPPT control, BC, VSI and LC filter, all were treated as a single unit. The model accounts for changes in variations of both irradiance and temperature. The AC-PV module proposed model is simulated and the results are compared with the datasheet projected numbers to validate model’s accuracy and effectiveness. Implementation and results demonstrate simplicity and accuracy, as well as reliability of the model.

Keywords: PV modeling, AC PV Module, datasheet, VI curves irradiance, temperature, MPPT, Matlab/Simulink

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Authors: Subhankar Karmakar, Madhan Kumar Vasudevan, Manivannan Muniyandi

Abstract:

Thermal Grill Illusion (TGI) elicits a strong and often painful sensation of burn when interlacing warm and cold stimuli that are individually non-painful, excites thermoreceptors beneath the skin. Among several theories of TGI, the “disinhibition” theory is the most widely accepted in the literature. According to this theory, TGI is the result of the disinhibition or unmasking of the pain-sensitive HPC (Heat-Pinch-Cold) nerve fibers due to the inhibition of cold-sensitive nerve fibers that are responsible for masking HPC nerve fibers. Although researchers focused on understanding TGI throughexperiments and models, none of them investigated the prediction of TGI pain intensity through a computational model. Furthermore, the comparison of psychophysically perceived TGI intensity with neurophysiological models has not yet been studied. The prediction of pain intensity through a computational model of TGI can help inoptimizing thermal displays and understanding pathological conditions related to temperature perception. The current studyfocuses on developing a computational model to predict the intensity of TGI pain and experimentally observe the perceived TGI pain. The computational model is developed based on the disinhibition theory and by utilizing the existing popular models of warm and cold receptors in the skin. The model aims to predict the neuronal activity of the HPC nerve fibers. With a temperature-controlled thermal grill setup, fifteen participants (ten males and five females) were presented with five temperature differences between warm and cold grills (each repeated three times). All the participants rated the perceived TGI pain sensation on a scale of one to ten. For the range of temperature differences, the experimentally observed perceived intensity of TGI is compared with the neuronal activity of pain-sensitive HPC nerve fibers. The simulation results show a monotonically increasing relationship between the temperature differences and the neuronal activity of the HPC nerve fibers. Moreover, a similar monotonically increasing relationship is experimentally observed between temperature differences and the perceived TGI intensity. This shows the potential comparison of TGI pain intensity observed through the experimental study with the neuronal activity predicted through the model. The proposed model intends to bridge the theoretical understanding of the TGI and the experimental results obtained through psychophysics. Further studies in pain perception are needed to develop a more accurate version of the current model.

Keywords: thermal grill Illusion, computational modelling, simulation, psychophysics, haptics

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Authors: Imran Hanif, Amanda Persdotter, Sedigheh Bigdeli, Jesper Liske, Torbjorn Jonsson

Abstract:

Renewable fuels such as biomass/waste for power production is an attractive alternative to fossil fuels in order to achieve a CO₂ -neutral power generation. However, the combustion results in the release of corrosive species. This puts high demands on the corrosion resistance of the alloys used in the boiler. Stainless steels containing nickel and/or nickel containing coatings are regarded as suitable corrosion resistance material especially in the superheater regions. However, the corrosive environment in the boiler caused by the presence of water vapour and reactive alkali very rapidly breaks down the primary protection, i.e., the Cr-rich oxide scale formed on stainless steels. The lifetime of the components, therefore, relies on the properties of the oxide scale formed after breakaway, i.e., the secondary protection. The aim of the current study is to investigate the role of varying nickel content (0–82%) on the high-temperature corrosion of model alloys with 18% Cr (Fe in balance) in the laboratory mimicking industrial conditions at 600°C. The influence of nickel is investigated on both the primary protection and especially the secondary protection, i.e., the scale formed after breakaway, during the oxidation/corrosion process in the dry O₂ (primary protection) and more aggressive environment such as H₂O, K₂CO₃ and KCl (secondary protection). All investigated alloys experience a very rapid loss of the primary protection, i.e., the Cr-rich (Cr, Fe)₂O₃, and the formation of secondary protection in the aggressive environments. The microstructural investigation showed that secondary protection of all alloys has a very similar microstructure in all more aggressive environments consisting of an outward growing iron oxide and inward growing spinel-oxide (Fe, Cr, Ni)₃O₄. The oxidation kinetics revealed that it is possible to influence the protectiveness of the scale formed after breakaway (secondary protection) through the amount of nickel in the alloy. The difference in oxidation kinetics of the secondary protection is linked to the microstructure and chemical composition of the complex spinel-oxide. The detailed microstructural investigations were carried out using the extensive analytical techniques such as electron back scattered diffraction (EBSD), energy dispersive X-rays spectroscopy (EDS) via the scanning and transmission electron microscopy techniques and results are compared with the thermodynamic calculations using the Thermo-Calc software.

Keywords: breakaway corrosion, EBSD, high-temperature oxidation, SEM, TEM

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Authors: Pham Van Nha, Le Cam Binh

Abstract:

Particle swarm optimization (PSO) is a population-based stochastic optimization algorithm. PSO was inspired by the natural behavior of birds and fish in migration and foraging for food. PSO is considered as a multidisciplinary optimization model that can be applied in various optimization problems. PSO’s ideas are simple and easy to understand but PSO is only applied in simple model problems. We think that in order to expand the applicability of PSO in complex problems, PSO should be described more explicitly in the form of a mathematical model. In this paper, we represent PSO in a mathematical model and apply in the multivariate data classification. First, PSOs general mathematical model (MPSO) is analyzed as a universal optimization model. Then, Model of Optimal Centroids (MOC) is proposed for the multivariate data classification. Experiments were conducted on some benchmark data sets to prove the effectiveness of MOC compared with several proposed schemes.

Keywords: analysis of optimization, artificial intelligence based optimization, optimization for learning and data analysis, global optimization

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