Search results for: in vitro skin model

Authors: Sungeun Hyun, Sooin Lee, Gyewan Moon

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Work-Family Conflict has been an active research area for the past decades. Work-Family Conflict harms individuals and organizations, it is ultimately expected to bring the cost of losses to the company in the long run. WFC has mainly focused on effects of organizational effectiveness and job attitude such as Job Satisfaction, Organizational Commitment, and Turnover Intention variables. This study is different from consequence variable with previous research. For this purpose, we selected the positive job attitude 'Work Engagement' as a consequence of WFC. This research has its primary research purpose in identifying the negative effects of the Work-Family Conflict, and started out from the recognition of the problem that the research on the direct relationship on the influence of the WFC on Work Engagement is lacking. Based on the COR(Conservation of resource theory) and JD-R(Job Demand- Resource model), the empirical study model to examine the negative effects of WFC with Emotional Exhaustion as the link between WFC and Work Engagement was suggested and validated. Also, it was analyzed how much Positive Psychological Capital may buffer the negative effects arising from WFC within this relationship, and the Mediated Moderation model controlling the indirect effect influencing the Work Engagement by the Positive Psychological Capital mediated by the WFC and Emotional Exhaustion was verified. Data was collected by using questionnaires distributed to 500 employees engaged manufacturing, services, finance, IT industry, education services, and other sectors, of which 389 were used in the statistical analysis. The data are analyzed by statistical package, SPSS 21.0, SPSS macro and AMOS 21.0. The hierarchical regression analysis, SPSS PROCESS macro and Bootstrapping method for hypothesis testing were conducted. Results showed that all hypotheses are supported. First, WFC showed a negative effect on Work Engagement. Specifically, WIF appeared to be on more negative effects than FIW. Second, Emotional exhaustion found to mediate the relationship between WFC and Work Engagement. Third, Positive Psychological Capital showed to moderate the relationship between WFC and Emotional Exhaustion. Fourth, the effect of mediated moderation through the integration verification, Positive Psychological Capital demonstrated to buffer the relationship among WFC, Emotional Exhastion, and Work Engagement. Also, WIF showed a more negative effects than FIW through verification of all hypotheses. Finally, we discussed the theoretical and practical implications on research and management of the WFC, and proposed limitations and future research directions of research.

Keywords: emotional exhaustion, positive psychological capital, work engagement, work-family conflict

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Authors: Alexis Akinyemi, Laurene Houtin

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Measures of employee motivation at work are often based on the theory of self-determined motivation, which implies that human resources departments and managers seek to motivate employees in the most self-determined way possible and use strategies to achieve this goal. In practice, they often tend to assess employee motivation and then adapt management to the most important source of motivation for their employees, for example by financially rewarding an employee who is extrinsically motivated, and by rewarding an intrinsically motivated employee with congratulations and recognition. Thus, the use of motivation measures contradicts theoretical positioning: theory does not provide for the promotion of extrinsically motivated behaviour. In addition, a corpus of social psychology linked to fundamental needs makes it possible to personally address a person’s different sources of motivation (need for cognition, need for uniqueness, need for effects and need for closure). By developing a composite measure of motivation based on these needs, we provide human resources professionals, and in particular occupational psychologists, with a tool that complements the assessment of self-determined motivation, making it possible to precisely address the objective of adapting work not to the self-determination of behaviours, but to the motivational traits of employees. To develop such a model, we gathered the French versions of the cognitive needs scales (need for cognition, need for uniqueness, need for effects, need for closure) and conducted a study with 645 employees of several French companies. On the basis of the data collected, we conducted a confirmatory factor analysis to validate the model, studied the correlations between the various needs, and highlighted the different reference groups that could be used to use these needs as a basis for interviews with employees (career, recruitment, etc.). The results showed a coherent model and the expected links between the different needs. Taken together, these results make it possible to propose a valid and theoretically adjusted tool to managers who wish to adapt their management to their employees’ current motivations, whether or not these motivations are self-determined.

Keywords: motivation, personality, work commitment, cognitive needs

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Authors: Manish Kumar, Krupa Shah

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The usage of renewable energy sources is increased day by day to overcome the dependency on fossil fuels. The wind energy is considered as a prominent source of renewable energy. This paper presents an approach for utilizing wind energy obtained from moving the vehicle for cell-phone charging. The selection of wind turbine, blades, generator, etc. is done to have the most efficient system. The calculation procedure for power generated and drag force is shown to know the effectiveness of the proposal. The location of the turbine is selected such that the system remains symmetric, stable and has the maximum induced wind. The calculation of the generated power at different velocity is presented. The charging is achieved for the speed 30 km/h and the system works well till 60 km/h. The model proposed seems very useful for the people traveling long distances in the absence of mobile electricity. The model is very economical and easy to fabricate. It has very less weight and area that makes it portable and comfortable to carry along. The practical results are shown by implementing the portable wind turbine system on two-wheeler.

Keywords: cell-phone charging, on-board power generation, wind energy, vehicle

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Authors: Fadia Gafri, Kathryn Mckintosh, Louise Young, Alan Harvey, Simon Mackay, Andrew Paul, Robin Plevin

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Nuclear factor-kappa B (NF-κB) is a ubiquitous transcription factor found originally to play a key role in regulating inflammation. However considerable evidence links this pathway to the suppression of apoptosis, cellular transformation, proliferation and invasion (Aggarwal et al., 2006). Moreover, recent studies have also linked inflammation to cancer progression making NF-κB overall a promising therapeutic target for drug discovery (Dobrovolskaia & Kozlov, 2005). In this study we examined the effect of the natural product canthin-6-one (SU182) as part of a CRUK small molecule drug discovery programme for effects upon the NF-κB pathway. Initial studies demonstrated that SU182 was found to have good potency against the inhibitory kappa B kinases (IKKs) at 30M in vitro. However, at concentrations up to 30M, SU182 had no effect upon TNFα stimulated loss in cellular IκBα or p65 phosphorylation in the keratinocyte cell line NCTC2544. Nevertheless, 30M SU182 reduced TNF-α / PMA-induced NF-κB-linked luciferase reporter activity to (22.9 ± 5%) and (34.6± 3 %, P<0.001) respectively, suggesting an action downstream of IKK signalling. Indeed, SU182 neither decreased NF-κB-DNA binding as assayed by EMSA nor prevented the translocation of p65 (NF-κB) to the nucleus assessed by immunofluorescence and subcellular fractionation. In addition to the inhibition of transcriptional activity of TNFα-induced NF-κB reporter activity SU182 significantly reduced PMA-induced AP-1-linked luciferase reporter activity to about (48± 9% at 30M, P<0.001) . This mode of inhibition was not sufficient to prevent the activation of NF-κB dependent induction of other proteins such as COX-2 and iNOS, or activated MAP kinases (p38, JNK and ERK1/2) in LPS stimulated RAW 264.7 macrophages. Taken together these data indicate the potential for SU182 to interfere with the transcription factors NF-κB and AP-1 at transcriptional level. However, no potential anti-inflammatory effect was indicated, further investigation for other NF-κB dependent proteins linked to survival are also required to identify the exact mechanism of action.

Keywords: Canthin-6-one, NF-κB, AP-1, phosphorylation, Nuclear translocation, DNA-binding activity, inflammatory proteins.

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Authors: K. Noah, F.-S. Lien

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In Computational Fluid Dynamics (CFD), there are a variety of numerical methods, of which some depend on macroscopic model representatives. These models can be solved by finite-volume, finite-element or finite-difference methods on a microscopic description. However, the lattice Boltzmann method (LBM) is considered to be a mesoscopic particle method, with its scale lying between the macroscopic and microscopic scales. The LBM works well for solving incompressible flow problems, but certain limitations arise from solving compressible flows, particularly at high Mach numbers. An improved lattice Boltzmann model for compressible flow problems is presented in this research study. A higher-order Taylor series expansion of the Maxwell equilibrium distribution function is used to overcome limitations in LBM when solving high-Mach-number flows. Large eddy simulation (LES) is implemented in LBM to simulate turbulent jet flows. The results have been validated with available experimental data for turbulent compressible free jet flow at subsonic speeds.

Keywords: compressible lattice Boltzmann method, multiple relaxation times, large eddy simulation, turbulent jet flows

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Authors: S. P. Sharma, Som Nath Saha

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This paper deals with the analytical investigation of thermal and thermohydraulic performance of double flow solar air heaters with corrugated and flat plate absorber. A mathematical model of double flow solar air heater has been presented, and a computer program in C⁺⁺ language is developed to estimate the outlet temperature of air for the evaluation of thermal and thermohydraulic efficiency by solving the governing equations numerically using relevant correlations for heat transfer coefficients. The results obtained from the mathematical model is compared with the available experimental results and it is found to be reasonably good. The results show that the double flow solar air heaters have higher efficiency than conventional solar air heater, although the double flow corrugated absorber is superior to that of flat plate double flow solar air heater. It is also observed that the thermal efficiency increases with increase in mass flow rate; however, thermohydraulic efficiency increases with increase in mass flow rate up to a certain limit, attains the maximum value, then thereafter decreases sharply.

Keywords: corrugated absorber, double flow, solar air heater, thermos-hydraulic efficiency

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Authors: Bin Ji, Kai Xu, Shunyu Yao, Jingjing Liu, Ye Pan

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Human pose estimation is a popular research area in computer vision for its important application in human-machine interface. In recent years, 2D human pose estimation based on convolution neural network has got great progress and development. However, in more and more practical applications, people often need to deal with tasks based on video. It’s not far-fetched for us to consider how to combine the spatial and temporal information together to achieve a balance between computing cost and accuracy. To address this issue, this study proposes a new spatiotemporal model, namely Spatiotemporal Net (STNet) to combine both temporal and spatial information more rationally. As a result, the predicted keypoints heatmap is potentially more accurate and spatially more precise. Under the condition of ensuring the recognition accuracy, the algorithm deal with spatiotemporal series in a decoupled way, which greatly reduces the computation of the model, thus reducing the resource consumption. This study demonstrate the effectiveness of our network over the Penn Action Dataset, and the results indicate superior performance of our network over the existing methods.

Keywords: convolutional long short-term memory, deep learning, human pose estimation, spatiotemporal series

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Authors: Mostafa Kazemi, Zahra N. Farkhani

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This paper proposes an integrated Data Envelopment Analysis (DEA) and Variance Inflation Factor (VIF) model for measuring the technical efficiency of decision making units. The model is validated using a set of 69% sales representatives’ dairy products. The analysis is done in two stages, in the first stage, VIF technique is used to distinguish independent effective factors of resellers, and in the second stage we used DEA for measuring efficiency for both constant and variable return to scales status. Further DEA is used to examine the utilization of environmental factors on efficiency. Results of this paper indicated an average managerial efficiency of 83% in the whole sales representatives’ dairy products. In addition, technical and scale efficiency were counted 96% and 80% respectively. 38% of sales representative have the technical efficiency of 100% and 72% of the sales representative in terms of managerial efficiency are quite efficient.High levels of relative efficiency indicate a good condition for sales representative efficiency.

Keywords: data envelopment analysis (DEA), relative efficiency, sales representatives’ dairy products, variance inflation factor (VIF)

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Authors: Hyelim Park, Juan Martin Zorrilla

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Climate change influences very widely and in various ways ocean ecosystem functioning. The consequences of climate change on marine ecosystems are an increase in temperature and irregular behavior of some solute concentrations. These changes would affect fisheries catches in several ways. Our aim is to assess the quantitative contribution change of fishery catches along the time and express them through four environment variables: Sea Surface Temperature (SST4) and the concentrations of Chlorophyll (CHL), Particulate Inorganic Carbon (PIC) and Particulate Organic Carbon (POC) at two spatial scales: Global and the nineteen FAO Major Fishing Areas divisions. Data collection was based on the FAO FishStatJ 2014 database as well as MODIS Aqua satellite observations from 2002 to 2012. Some data had to be corrected and interpolated using some existing methods. As the results, a multivariable regression model for average Global fisheries captures contained temporal mean of SST4, standard deviation of SST4, standard deviation of CHL and standard deviation of PIC. Global vector auto-regressive (VAR) model showed that SST4 was a statistical cause of global fishery capture. To accommodate varying conditions in fishery condition and influence of climate change variables, a model was constructed for each FAO major fishing area. From the management perspective it should be recognized some limitations of the FAO marine areas division that opens to possibility to the discussion of the subdivision of the areas into smaller units. Furthermore, it should be treated that the contribution changes of fishery species and the possible environment factor for specific species at various scale levels.

Keywords: fisheries-catch, FAO FishStatJ, MODIS Aqua, sea surface temperature (SST), chlorophyll, particulate inorganic carbon (PIC), particulate organic carbon (POC), VAR, granger causality

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Authors: Hasan Farahneh

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Smart asset management along roadsides and in deserted areas is a topic of deprived attention. We find most of the work in emergency reporting services in intelligent transportation systems (ITS) and rural areas but not much in asset reporting. Currently, available asset management mechanisms are based on scheduled maintenance and do not effectively report any emergency situation in a timely manner. This paper is the continuation of our previous work, in which we proposed the usage of Foglets and VLC link between smart vehicles and road side assets. In this paper, we propose a hybrid communication system for asset management and emergency reporting architecture for smart transportation. We incorporate Foglets along with visible light communication (VLC) and radio frequency (RF) communication. We present the channel model and parameters of a hybrid model to support an intelligent transportation system (ITS) system. Simulations show high improvement in the system performance in terms of communication range and received data. We present a comparative analysis of a hybrid ITS system.

Keywords: Internet of Things, Foglets, VLC, RF, smart vehicle, roadside asset management

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Authors: Arun Dhakal, Geoff Cockfield, Tek Narayan Maraseni

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This paper attempts to fulfil the gap in measuring adoption in agroforestry studies. It explains the derivation of an index of adoption rate in a Nepalese context and examines the factors affecting adoption of agroforestry-based land management practice (AFLMP) in the Dhanusha District of Nepal. Data about the different farm practices and the factors (bio-physical, socio-economic) influencing adoption were collected during focus group discussion and from the randomly selected households using a household survey questionnaire, respectively. A multivariate regression model was used to determine the factors. The factors (variables) found to significantly affect adoption of AFLMP were: farm size, availability of irrigation water, education of household heads, agricultural labour force, frequency of visits by extension workers, expenditure on farm inputs purchase, household’s experience in agroforestry, and distance from home to government forest. The regression model explained about 75% of variation in adoption decision. The model rejected ‘erosion hazard’, ‘flood hazard’ and ‘gender’ as determinants of adoption, which in case of single agroforestry practice were major variables and played positive role. Out of eight variables, farm size played the most powerful role in explaining the variation in adoption, followed by availability of irrigation water and education of household heads. The results of this study suggest that policies to promote the provision of irrigation water, extension services and motivation to obtaining higher education would probably provide the incentive to adopt agroforestry elsewhere in the terai of Nepal.

Keywords: agroforestry, adoption index, determinants of adoption, step-wise linear regression, Nepal

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Authors: Joseph Marae Djouda, Ashraf Kasmi, François Hild

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Fused filament fabrication is one of the most widespread additive manufacturing techniques because of its low-cost implementation. Its initial development was based on part fabrication with thermoplastic materials. The influence of the manufacturing parameters such as the filament orientation through the nozzle, the deposited layer thickness, or the speed deposition on the mechanical properties of the parts has been widely experimentally investigated. It has been recorded the remarkable variations of the anisotropy in the function of the filament path during the fabrication process. However, there is a lack in the development of constitutive models describing the mechanical properties. In this study, integrated digital image correlation (I-DIC) is used for the identification of mechanical constitutive parameters of two configurations of ABS samples: +/-45° and so-called “oriented deposition.” In this last, the filament was deposited in order to follow the principal strain of the sample. The identification scheme based on the gap reduction between simulation and the experiment directly from images recorded from a single sample (single edge notched tension specimen) is developed. The macroscopic and mesoscopic analysis are conducted from images recorded in both sample surfaces during the tensile test. The elastic and elastoplastic models in isotropic and orthotropic frameworks have been established. It appears that independently of the sample configurations (filament orientation during the fabrication), the elastoplastic isotropic model gives the correct description of the behavior of samples. It is worth noting that in this model, the number of constitutive parameters is limited to the one considered in the elastoplastic orthotropic model. This leads to the fact that the anisotropy of the architectured 3D printed ABS parts can be neglected in the establishment of the macroscopic behavior description.

Keywords: elastic anisotropy, fused filament fabrication, Acrylonitrile butadiene styrene, I-DIC identification

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Authors: Simone F. Medeiros, Jessica M. Fonseca, Gizelda M. Alves, Danilo M. Santos, Sérgio P. Campana-Filho, Amilton M. Santos

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Stimuli responsive and biocompatible hydrogel nanoparticles have gained special attention as systems for potential applications in controlled release of drugs to improve their therapeutic efficacy while minimizing side effects. In this work, novel solid dispersions based on thermo- and pH-responsive poly(N-vinylcaprolactam-co-itaconic acid-co-ethylene- glycol dimethacrylate) hydrogel nanoparticles embedded in chitosan matrices were prepared via spray drying for controlled release of ketoprofen. Firstly, the hydrogel nanoparticles containing ketoprofen were prepared via precipitation polymerization and their stimuli-responsive behavior, thermal properties, chemical composition, encapsulation efficiency and morphology were characterized. Then, hydrogel nanoparticles with different particles size were embedded into chitosan matrices via spray-drying. Scanning electron microscopy (SEM) analyses were performed to investigate the particles size, dispersity and morphology. Finally, ketoprofen release profiles were studied as a function of pH and temperature. Chitosan/poly(NVCL-co-IA-co-EGDMA)-ketoprofen microparticles presented spherical shape, rough surface and pronounced agglomeration, indicating that hydrogels nanoparticles loaded with ketoprofen modified the surface of chitosan matrix. The maximum encapsulation efficiency of ketoprofen into hydrogel nanoparticles was 57.8% and the electrostatic interactions between amino groups from chitosan and carboxylic groups from hydrogel nanoparticles were able to control ketoprofen release. The hydrogel nanoparticles themselves were capable to retard the release of ketoprofen-loaded until 48h of in vitro release tests, while their incorporation into chitosan matrix achieved a maximum percentage of drug release of 45%, using a mass ratio of chitosan: poly(NVCL-co-IA-co-EGDMA equal to 10:7, and 69%, using a mass ratio of chitosan: poly(NVCL-co-IA-co-EGDMA equal to 5:2.

Keywords: hydrogel nanoparticles, poly(N-vinylcaprolactam-co-itaconic acid-co-ethylene- glycol dimethacrylate), chitosan, ketoprofen, spray-drying

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Authors: Amel Bouaziz, Seddik Khennouf, Mussa Abu Zarga, Shtayway Abdalla, Saliha Djidel, Assia Bentahar, Saliha Dahamna, Smain Amira

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The present study aimed to evaluate the hypotensive and the in vitro antioxidant activities of Crataegus azarolus L. (Rosaceae), a plant widely used as natural remedy for hypertension in folk medicine. The antioxidant potential of methanolic extract (ME)and its three fractions of Chloroform (CHE), ethyl acetate (EAE)and water (AqE) have been investigated using several assays, including the DPPH scavenging, ABTS scavenging, hydroxyl radical scavenging. Inhibition of lipid peroxidation was performed by the β-carotene bleaching assay, ferric thiocyanate method and thiobarburic acid method. Total phenolic and total flavonoid contents of the extracts were estimated using Folin-Chiocalteu reagent and AlCl3, respectively. EAE extract showed the highest polyphenolic and flavonoids contents (396,04±1.20 mg GAE/g of dry extract and 32,73 ± 0.03mg QE/g of dry extract) respectively. Similarly, this extract possessed the highest scavenging activity for DPPH radical (IC 50 = 0,006±0,0001mg /ml), ABTS radical (IC50=0.0035±0,0007 mg/ml) and hydroxyl radical(IC 50=0,283± 0.01 mg/ml). In addition, the EAE exhibited the highest antioxidant activity in the inhibition of linoleic acid/ß-carotene coupled oxidation (89,21%), lipid peroxidation in the ferric thiocyanate(FTC) method (90.13%), and thio-barbituric acid (TBA) method (74.23%). Intravenous administration of Me and EAE decreased mean arterial blood pressure, systolic and diastolic blood pressure in anesthetized rats dose-dependently, at the dose range of 0.4 to 12 mg/kg. The mean arterial blood pressure dropped by 27.58 and 39.37% for ME and EAE, respectively. In conclusion, The present study supported the significant potential to use C. azarolus by-products as a source of natural antioxidants and provides scientific justification for its traditional uses as cardio-protective and anti-hypertensive remedy.

Keywords: Crataegus azarolus, polyphenols, flavonoids, hypertension, antioxidant activity, free radicals, peroxidation

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Authors: P. Annapurna, Cecil Ross, Sudhir Krishna, Sweta Srivastava

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Irradiation plays a pivotal role in cervical cancer treatment, however some tumors exhibit resistance to therapy while some exhibit relapse, due to better repair and enhanced resistance mechanisms operational in their cells. The present study aims to understand the signaling mechanism operational in resistance phenotype and in the present study we report the role of Rho GTPase associated protein kinase (ROCK) signaling in cervical carcinoma radio-resistance. ROCK signaling has been implicated in several tumor progressions and is important for DNA repair. Irradiation of spheroid cultures of SiHa cervical carcinoma derived cell line at 6Gy resulted in generation of resistant cells in vitro which had better clonogenic abilities and formed larger and more colonies, in soft agar colony formation assay, as compared to the non-irradiated cells. These cells also exhibited an enhanced motility phenotype. Cell cycle profiling showed the cells to be blocked in G2M phase with enhanced pCDC2 levels indicating onset of possible DNA repair mechanism. Notably, 3 days post-irradiation, irradiated cells showed increased ROCK2 translocation to the nucleus with enhanced protein expression as compared to the non-irradiated cells. Radio-sensitization of the resistant cells was enhanced using Y27632, an inhibitor to ROCK signaling. The treatment of resistant cells with Y27632 resulted in increased cell death upon further irradiation. This observation has been confirmed using inhibitory antibodies to ROCK1/2. Result show that both ROCK1/2 have a functional contribution in radiation resistance of cervical cancer cells derived from cell lines. Interestingly enrichment of stem like cells (Hoechst negative cells) was also observed upon irradiation and these cells were markedly sensitive to Y27632 treatment. Our results thus suggest the role of ROCK signaling in radio-resistance in cervical carcinoma. Further studies with human biopsies, mice models and mechanistic of ROCK signaling in the context of radio-resistance will clarify the role of this molecule further and allow for therapeutics development.

Keywords: cervical carcinoma, radio-resistance, ROCK signaling, cancer treatment

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Authors: Kamyar Tolouei, Ehsan Moosavi

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

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

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Authors: Milad Keshvardoost, Amir Khanlari, Nader Khalesi

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Background: Any firm in the pharmaceutical industry requires efficient and effective management information systems (MIS) to support managerial functions. Purpose: The aim of this study is to investigate the impact of Task-Technology Fit on user effectiveness, efficiency, and creativity in Iranian pharmaceutical companies. Methodology: 345 reliable and validate questionnaires were distributed among selected samples, through the cluster method, to Information system users of eight leading Iranian pharmaceutical companies, based on the likert scale. The proposed model of the article is based on a model with Task technology fit, on user performance with the definition of efficiency, effectiveness, and creativity through mediation effects of perceived usefulness and ease of use. Results: This study confirmed that TTF with definitions of adequacy and compatibility has positive impacts on user performance Conclusion: We concluded that pharmaceutical users of IS, utilizing a system with a precise and intense observation of users' demands, may make facilitation for them to design an exclusive IS framework.

Keywords: information systems, user performance, pharmaceuticals, task technology fit

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Authors: Khaled R. Khater

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The weight of the SPT hammer is standard (0.623kN). The locally manufacturer drilling rigs use hammers, sometimes deviating off the standard weight. This affects the field measured blow counts (Nf) consequentially, affecting most of correlations previously obtained, as they were obtained based on standard hammer weight. The literature presents energy corrections factor (η2) to be applied to the SPT total input energy. This research investigates the effect of the hammer weight variation, as a single parameter, on the field measured blow counts (Nf). The outcome is a correction factor (ηk), equation, and correction chart. They are recommended to adjust back the measured misleading (Nf) to the standard one as if the standard hammer is used. This correction is very important to be done in such cases where a non-standard hammer is being used because the bore logs in any geotechnical report should contain true and representative values (Nf), let alone the long records of correlations, already in hand. The study here-in is achieved by using laboratory physical model to simulate the SPT dripping hammer mechanism. It is designed to allow different hammer weights to be used. Also, it is manufactured to avoid and eliminate the energy loss sources. This produces a transmitted efficiency up to 100%.

Keywords: correction factors, hammer weight, physical model, standard penetration test

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Authors: S. Wakim, M. Nemer, B. Zeghondy, B. Ghannam, C. Bouallou

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Designing the optimal heat exchanger is still an essential objective to be achieved. Parametrical optimization involves the evaluation of the heat exchanger dimensions to find those that best satisfy certain objectives. This method contributes to an enhanced design rather than an optimized one. On the contrary, topology optimization finds the optimal structure that satisfies the design objectives. The huge development in metal additive manufacturing allowed topology optimization to find its way into engineering applications especially in the aerospace field to optimize metal structures. Using topology optimization in 3d heat and mass transfer problems requires huge computational time, therefore coupling it with CFD simulations can reduce this it. However, existed CFD models cannot be coupled with topology optimization. The CFD model must allow creating a uniform mesh despite the initial geometry complexity and also to swap the cells from fluid to solid and vice versa. In this paper, a porous media approach compatible with topology optimization criteria is developed. It consists of modeling the fluid region of the heat exchanger as porous media having high porosity and similarly the solid region is modeled as porous media having low porosity. The switching from fluid to solid cells required by topology optimization is simply done by changing each cell porosity using a user defined function. This model is tested on a plate and fin heat exchanger and validated by comparing its results to experimental data and simulations results. Furthermore, this model is used to perform a material reallocation based on local criteria to optimize a plate and fin heat exchanger under a constant heat duty constraint. The optimized fin uses 20% fewer materials than the first while the pressure drop is reduced by about 13%.

Keywords: computational methods, finite element method, heat exchanger, porous media, topology optimization

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Authors: Sukwoong Kang

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Background: The application of light-emitting diode (LED)-dependent photobiomodulation (PBM) in promoting post-tendon injury healing has been recently reported. Despite the establishment of a theoretical basis for ligament restoration through PBM, the lack of any empirical evidence deems this therapeutic strategy contentious. Therefore, the aim of this study was to investigate the potency of LED-based PBM in facilitating tendon healing in a murine model. Methods: Migration kinetics were analyzed at two specific wavelengths: 630 and 880 nm. The Achilles tendon in the hind limbs of Balb/c mice was severed via Achilles tendon transection. Subsequently, the mice were randomized into LED non-irradiation and LED irradiation groups. Mice with intact tendons were employed as healthy controls. The wounds were LED-irradiated for 20 min daily for two days. Histological properties, tendon healing mediators, and inflammatory mediators were screened on day 14. Results: The roundness of the nuclei and fiber structure, indicating the degree of infiltrated inflammatory cells and severity of fiber fragmentation, respectively, were considerably lower in the LED irradiation group than in the LED non-irradiation group. Immunohistochemical analysis depicted an increase in tenocytes (SCX+ cells) and a recovery of wounds with reduced fibrosis (lower collagen 3 and TGF-β1) in the LED irradiation group during healing; conversely, the LED non-irradiation group exhibited tissue fibrosis. The ratio of M2 macrophages to total macrophages was higher in the LED irradiation group than in the injured group. Conclusion: LED-based PBM in the Achilles tendon rupture murine model effectuated a rapid restoration of histological and immunochemical outcomes. The aforementioned findings suggest that LED-based PBM presents remarkable potential as an adjunct therapeutic for tendon healing and warrants further research to standardize various parameters to advance and establish it as a reliable treatment regime.

Keywords: photobiomodulation, light-emitting diode, tendon, regeneration

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Authors: Ali Akbar, Seungho Shin, Sukkee Um

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The composition of catalyst layers (CLs) plays an important role in the overall performance and cost of the proton exchange membrane fuel cells (PEMFCs). Low platinum loading, high utilization, and more durable catalyst still remain as critical challenges for PEMFCs. In this study, a three-dimensional material network model is developed to visualize the nanostructure of carbon supported platinum Pt/C and Pt/VACNT catalysts in pursuance of maximizing the catalyst utilization. The quadruple-phase randomly generated CLs domain is formulated using quasi-random stochastic Monte Carlo-based method. This unique statistical approach of four-phase (i.e., pore, ionomer, carbon, and platinum) model is closely mimic of manufacturing process of CLs. Various CLs compositions are simulated to elucidate the effect of electrons, ions, and mass transport paths on the catalyst utilization factor. Based on simulation results, the effect of key factors such as porosity, ionomer contents and Pt weight percentage in Pt/C catalyst have been investigated at the represented elementary volume (REV) scale. The results show that the relationship between ionomer content and Pt utilization is in good agreement with existing experimental calculations. Furthermore, this model is implemented on the state-of-the-art Pt/VACNT CLs. The simulation results on Pt/VACNT based CLs show exceptionally high catalyst utilization as compared to Pt/C with different composition ratios. More importantly, this study reveals that the maximum catalyst utilization depends on the distance spacing between the carbon nanotubes for Pt/VACNT. The current simulation results are expected to be utilized in the optimization of nano-structural construction and composition of Pt/C and Pt/VACNT CLs.

Keywords: catalyst layer, platinum utilization, proton exchange membrane fuel cell, stochastic modeling

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Authors: Josip Visković, Josip Arnerić, Ante Rozga

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Based on the fact that volatility is time varying in high frequency data and that periods of high volatility tend to cluster, the most successful and popular models in modelling time varying volatility are GARCH type models. When financial returns exhibit sudden jumps that are due to structural breaks, standard GARCH models show high volatility persistence, i.e. integrated behaviour of the conditional variance. In such situations models in which the parameters are allowed to change over time are more appropriate. This paper compares different GARCH models in terms of their ability to describe structural changes in returns caused by financial crisis at stock markets of six selected central and east European countries. The empirical analysis demonstrates that Markov regime switching GARCH model resolves the problem of excessive persistence and outperforms uni-regime GARCH models in forecasting volatility when sudden switching occurs in response to financial crisis.

Keywords: central and east European countries, financial crisis, Markov switching GARCH model, transition probabilities

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Authors: Umamaheswari Shanmugam, Silvia Ronchi

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Software, artificial intelligence, and machine learning can improve healthcare through innovative and advanced technologies that can use the large amount and variety of data generated during healthcare services every day; one of the significant advantages of these new technologies is the ability to get experience and knowledge from real-world use and to improve their performance continuously. Healthcare systems and institutions can significantly benefit because the use of advanced technologies improves the efficiency and efficacy of healthcare. Software-defined as a medical device, is stand-alone software that is intended to be used for patients for one or more of these specific medical intended uses: - diagnosis, prevention, monitoring, prediction, prognosis, treatment or alleviation of a disease, any other health conditions, replacing or modifying any part of a physiological or pathological process–manage the received information from in vitro specimens derived from the human samples (body) and without principal main action of its principal intended use by pharmacological, immunological or metabolic definition. Software qualified as medical devices must comply with the general safety and performance requirements applicable to medical devices. These requirements are necessary to ensure high performance and quality and protect patients' safety. The evolution and the continuous improvement of software used in healthcare must consider the increase in regulatory requirements, which are becoming more complex in each market. The gap between these advanced technologies and the new regulations is the biggest challenge for medical device manufacturers. Regulatory requirements can be considered a market barrier, as they can delay or obstacle the device's approval. Still, they are necessary to ensure performance, quality, and safety. At the same time, they can be a business opportunity if the manufacturer can define the appropriate regulatory strategy in advance. The abstract will provide an overview of the current regulatory framework, the evolution of the international requirements, and the standards applicable to medical device software in the potential market all over the world.

Keywords: artificial intelligence, machine learning, SaMD, regulatory, clinical evaluation, classification, international requirements, MDR, 510k, PMA, IMDRF, cyber security, health care systems

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Authors: Liwei Liu, Shuguo Pan, Wang Gao

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In order to take full advantages of the BDS-3 penta-frequency signals in the long-baseline RTK positioning, a long-baseline RTK positioning method based on the BDS-3 penta-frequency ionospheric-reduced (IR) combinations is proposed. First, the low noise and weak ionospheric delay characteristics of the multi-frequency combined observations of BDS-3is analyzed. Second, the multi-frequency extra-wide-lane (EWL)/ wide-lane (WL) combinations with long-wavelengths are constructed. Third, the fixed IR EWL combinations are used to constrain the IR WL, then constrain narrow-lane (NL)ambiguityies and start multi-epoch filtering. There is no need to consider the influence of ionospheric parameters in the third step. Compared with the estimated ionospheric model, the proposed method reduces the number of parameters by half, so it is suitable for the use of multi-frequency and multi-system real-time RTK. The results using real data show that the stepwise fixed model of the IR EWL/WL/NL combinations can realize long-baseline instantaneous cimeter-level positioning.

Keywords: penta-frequency, ionospheric-reduced (IR), RTK positioning, long-baseline

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Authors: Hadi Allafta, Christian Opp

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Soil erosion is a major concern in the Shatt Al-Arab basin owing to the steepness of its topography as well as the remarkable altitudinal deference between the upstream and downstream parts of the basin. Such conditions resulted in soil vulnerability to erosion; huge amounts of soil are annually transported, creating enormous implications such as land degradation, structure damage, biodiversity loss, productivity decline, etc. Thus, evaluation of soil erosion risk and its spatial distribution is crucial to build adatabase for efficient control measures. The present study used revised universal soil loss equation (RUSLE) model integrated with Geographic Information System (GIS) for depicting soil erosion hazard zones in the Shatt Al-Arab basin. The RUSLE model incorporated several parameters such as rainfall-runoff erosivity, soil erodibility, slope length and steepness, land cover and management, and conservation support practice for soil erosion zonation. High to medium soil loss of 100 to 20 ton perhectare per year represents around 25% of the basin area, while the areas of low soil loss of less than 20 ton per hectare per year occupied the rest of the total area. The high soil loss rates are linked to areas of high rainfall levels, loamy soil domination, elevated terrains/plateau margins with steep side slope, and high cultivation activities. The findings of the current study can be useful for managers and policy makers in the implementation of a suitable conservation program to reduce soil erosion or to recommend soil conservation acts if development projects are to be continued at regions of high soil erosion risk.

Keywords: geographic information system, revised universal soil loss equation, shatt Al-Arab basin, soil erosion

Procedia PDF Downloads 105

Authors: Arjumand Warsy

Abstract:

The Holy Quran was revealed to Prophet Mohammad (May Peace and Blessings of Allah be upon Him) over fourteen hundred years ago, at a time when majority of the people in Arabia were illiterate and very few could read or write. Any knowledge about medicine, anatomy, biology, astronomy, physics, geology, geophysics or other sciences were almost non-existent. Many superstitious and groundless believes were prevalent and these believes were passed down through past generations. At that time, the Holy Quran was revealed and it presented several phenomenon that have been only currently unveiled, as scientists have worked endlessly to provide explanation for these physical and biological phenomenon applying scientific technologies. Many important discoveries were made during the 20th century and it is interesting to note that many of these discoveries were already present in the Holy Quran fourteen hundred years ago. The Scientific phenomenon, mentioned in the Holy Quran, cover many different fields in biological and physical sciences and have been the source of guidance for a number of scientists. A perfect description of the creation of the universe, the orbits in space, the development process, development of hearing process prior to sight, importance of the skin in sensing pain, uniqueness of fingerprints, role of males in selection of the sex of the baby, are just a few of the many facts present in the Quran that have astonished many scientists. The Quran in Chapter 20, verse 50 states: قَالَ رَبُّنَا الَّذِيۤ اَعْطٰى كُلَّ شَيْءٍ خَلْقَهٗ ثُمَّ هَدٰى ۰۰ (He said "Our Lord is He, Who has given a distinctive form to everything and then guided it aright”). Explaining this brief statement in the light of the modern day Molecular Genetics unveils the entire genetic basis of life and how guidance is stored in the genetic material (DNA) present in the nucleus. This thread like structure, made of only six molecules (sugar, phosphate, adenine, thymine, cytosine and guanine), is so brilliantly structured by the Creator that it holds all the information about each and every living thing, whether it is viruses, bacteria, fungi, plants, animals or humans or any other living being. This paper will present an update on some of the physical and biological phenomena’ presented in the Holy Quran, unveiled using advanced technologies during the last century and will discuss how the need to incorporate this information in the curricula.

Keywords: The Holy Quran, scientific facts, curriculum, Muslims

Procedia PDF Downloads 344

Authors: Aibek Kukpayev, Dhawal Shah

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Combustion of sour fuels containing high amount of sulfur leads to the formation of sulfur oxides, which adversely harm the environment and has a negative impact on human health. Considering this, several legislations have been imposed to bring down the sulfur content in fuel to less than 10 ppm. In recent years, novel deep eutectic solvents (DESs) have been developed to achieve deep desulfurization, particularly to extract thiophenic compounds from liquid fuels. These novel DESs, considered as analogous to ionic liquids are green, eco-friendly, inexpensive, and sustainable. We herein, using molecular dynamic simulation, analyze the interactions of metal-based DESs with model oil consisting of thiophenic compounds. The DES used consists of polyethylene glycol (PEG-200) as a hydrogen bond donor, choline chloride (ChCl) or tetrabutyl ammonium chloride (TBAC) as a hydrogen bond acceptor, and cobalt chloride (CoCl₂) as metal salt. In particular, the combination of ChCl: PEG-200:CoCl₂ at a ratio 1:2:1 and the combination of TBAC:PEG-200:CoCl₂ at a ratio 1:2:0.25 were simulated, separately, with model oil consisting of octane and thiophenes at 25ᵒC and 1 bar. The results of molecular dynamics simulations were analyzed in terms of interaction energies between different components. The simulations revealed a stronger interaction between DESs/thiophenes as compared with octane/thiophenes, suggestive of an efficient desulfurization process. In addition, our analysis suggests that the choice of hydrogen bond acceptor strongly influences the efficiency of the desulfurization process. Taken together, the results also show the importance of the metal ion, although present in small amount, in the process, and the role of the polymer in desulfurization of the model fuel.

Keywords: deep eutectic solvents, desulfurization, molecular dynamics simulations, thiophenes

Procedia PDF Downloads 132

Authors: Chin-Chia Jane

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In a transportation network, travel time refers to the transmission time from source node to destination node, whereas reliability refers to the probability of a successful connection from source node to destination node. With an increasing emphasis on quality of service (QoS), both performance indexes are significant in the design and analysis of transportation systems. In this work, we extend the well-known flow network model for transportation networks so that travel time and reliability are integrated into the QoS measurement simultaneously. In the extended model, in addition to the general arc capacities, each intermediate node has a time weight which is the travel time for per unit of commodity going through the node. Meanwhile, arcs and nodes are treated as binary random variables that switch between operation and failure with associated probabilities. For pre-specified travel time limitation and demand requirement, the QoS of a transportation network is the probability that source can successfully transport the demand requirement to destination while the total transmission time is under the travel time limitation. This work is pioneering, since existing literatures that evaluate travel time reliability via a single optimization path, the proposed QoS focuses the performance of the whole network system. To compute the QoS of transportation networks, we first transfer the extended network model into an equivalent min-cost max-flow network model. In the transferred network, each arc has a new travel time weight which takes value 0. Each intermediate node is replaced by two nodes u and v, and an arc directed from u to v. The newly generated nodes u and v are perfect nodes. The new direct arc has three weights: travel time, capacity, and operation probability. Then the universal set of state vectors is recursively decomposed into disjoint subsets of reliable, unreliable, and stochastic vectors until no stochastic vector is left. The decomposition is made possible by applying existing efficient min-cost max-flow algorithm. Because the reliable subsets are disjoint, QoS can be obtained directly by summing the probabilities of these reliable subsets. Computational experiments are conducted on a benchmark network which has 11 nodes and 21 arcs. Five travel time limitations and five demand requirements are set to compute the QoS value. To make a comparison, we test the exhaustive complete enumeration method. Computational results reveal the proposed algorithm is much more efficient than the complete enumeration method. In this work, a transportation network is analyzed by an extended flow network model where each arc has a fixed capacity, each intermediate node has a time weight, and both arcs and nodes are independent binary random variables. The quality of service of the transportation network is an integration of customer demands, travel time, and the probability of connection. We present a decomposition algorithm to compute the QoS efficiently. Computational experiments conducted on a prototype network show that the proposed algorithm is superior to existing complete enumeration methods.

Keywords: quality of service, reliability, transportation network, travel time

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Authors: Eyup Dogan

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This empirical aims to analyze the impacts of real income and biomass energy consumption on the level of emissions in the EKC model for the panel of biomass-consuming countries over the period 1980-2011. Because we detect the presence of cross-sectional dependence and heterogeneity across countries for the analyzed data, we use panel estimation methods robust to cross-sectional dependence and heterogeneity. The CADF and the CIPS panel unit root tests indicate that carbon emissions, real income and biomass energy consumption are stationary at the first-differences. The LM bootstrap panel cointegration test shows that the analyzed variables are cointegrated. Results from the panel group-mean DOLS and the panel group-mean FMOLS estimators show that increase in biomass energy consumption decreases CO2 emissions and the EKC hypothesis is validated. Therefore, countries are advised to boost their production and increase the use of biomass energy for lower level of emissions.

Keywords: biomass energy, CO2 emissions, EKC model, heterogeneity, cross-sectional dependence

Procedia PDF Downloads 281

Authors: Jun Yuan

Abstract:

Shipping is a major transportation mode all over the world, and it has a significant contribution to global carbon emissions. Electrification of ships is one of the main strategies to reduce shipping carbon emissions. The number of electric ships has continued to grow in recent years. However, charging infrastructure is still scarce, which severely restricts the development of electric ships. Therefore, it is very important to design ship charging stations reasonably by comprehensively considering charging demand and investment costs. This study aims to minimize the full life cycle cost of charging stations, considering the uncertainty of charging demand. A mixed integer programming model is developed for this optimization problem. Based on the characteristics of the mathematical model, a simulation based optimization method is proposed to find the optimal number and rated power of chargers. In addition, the impact of renewable energy and storage systems is analyzed. The results can provide decision support and a reference basis for the design of ship charging stations.

Keywords: shipping emission, electricity ship, charging station, optimal design

Procedia PDF Downloads 47