Search results for: random coefficients model

Authors: Adel Bougamouza, Boualam Remini, Abd El Hadi Ammari, Feteh Sakhraoui

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The assessment of sediments being carried by a river is importance for planning and designing of various water resources projects. In this study, Artificial Neural Network Techniques are used to estimate the daily suspended sediment concentration for the corresponding daily discharge flow in the upstream of Foum El Gherza dam, Biskra, Algeria. The FFNN, GRNN, and RBNN models are established for estimating current suspended sediment values. Some statistics involving RMSE and R2 were used to evaluate the performance of applied models. The comparison of three AI models showed that the RBNN model performed better than the FFNN and GRNN models with R2 = 0.967 and RMSE= 5.313 mg/l. Therefore, the ANN model had capability to improve nonlinear relationships between discharge flow and suspended sediment with reasonable precision.

Keywords: artificial neural network, Oued Abiod watershed, feedforward network, generalized regression network, radial basis network, sediment concentration

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Authors: Gulshan Mammadova

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This paper presents the results of studying the surface microrelief in 2D and 3D models and analyzing the spectroscopy of a three-junction TlInSe₂ crystal. Analysis of the results obtained showed that with a change in the composition of the TlInSe₂ crystal, sharp changes occur in the microrelief of its surface. An X-ray optical diffraction analysis of the TlInSe₂ crystal was experimentally carried out. Based on ellipsometric data, optical functions were determined - the real and imaginary parts of the dielectric permittivity of crystals, the coefficients of optical absorption and reflection, the dependence of energy losses and electric field power on the effective density, the spectral dependences of the real (σᵣ) and imaginary (σᵢ) parts, optical electrical conductivity were experimentally studied. The fluorescence spectra of the ternary compound TlInSe₂ were isolated and analyzed when excited by light with a wavelength of 532 nm. X-ray studies of TlInSe₂ showed that this phase crystallizes into tetragonal systems. Ellipsometric measurements showed that the real (ε₁) and imaginary (ε₂) parts of the dielectric constant are components of the dielectric constant tensor of the uniaxial joints under consideration and do not depend on the angle. Analysis of the dependence of the real and imaginary parts of the refractive index of the TlInSe₂ crystal on photon energy showed that the nature of the change in the real and imaginary parts of the dielectric constant does not differ significantly. When analyzing the spectral dependences of the real (σr) and imaginary (σi) parts of the optical electrical conductivity, it was noticed that the real part of the optical electrical conductivity increases exponentially in the energy range 0.894-3.505 eV. In the energy range of 0.654-2.91 eV, the imaginary part of the optical electrical conductivity increases linearly, reaches a maximum value, and decreases at an energy of 2.91 eV. At 3.6 eV, an inversion of the imaginary part of the optical electrical conductivity of the TlInSe₂ compound is observed. From the graphs of the effective power density versus electric field energy losses, it is known that the effective power density increases significantly in the energy range of 0.805–3.52 eV. The fluorescence spectrum of the ternary compound TlInSe₂ upon excitation with light with a wavelength of 532 nm has been studied and it has been established that this phase has luminescent properties.

Keywords: optical properties, dielectric permittivity, real and imaginary dielectric permittivity, optical electrical conductivity

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Authors: Aghamolaei Teamur, Hosseini Zahra, Ghanbarnejad Amin

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Introduction: A diet rich in fruits and vegetables, especially for adolescents is of a great importance due to the need for nutrients and the rapid growth of this age group. The aim of this study was to investigate the relationship between decisional balance and self-efficacy with stages of change for fruit and vegetable consumption in high school students in Bandar Abbas, Iran. Methods: In this descriptive-analytical study, the data were collected from 345 students studying in 8 high schools of Bandar Abbas were selected through multistage sampling. To collect data, separate questionnaires were designed for evaluating each of the variables including the stages of change, perceived benefits, perceived barriers, and self-efficacy of fruit and vegetable consumption. Decisional balance was estimated by subtracting the perceived benefits and barriers. The data were analyzed using SPSS19 and one-way ANOVA. Results: The results of this study indicated that individuals’ progress along the stages of change from pre-contemplation to maintenance level was associated with a significant increase in their decisional balance and self-efficacy for fruit and vegetable consumption. (P < 0.001). The lowest level of decisional balance and self-efficacy regarding for fruit showed up in the pre-contemplation stage, and the highest level of decisional balance and self-efficacy was in the maintenance stage. The same trends were observed in the case of vegetable consumption. Conclusion: Decisional balance and self-efficacy should be considered in designing interventions to increase consumption of fruits and vegetables. There needs to be more emphasis in educational programs based on the Trans-theoretical Model (TTM) on the enhancement of perceived benefits and elimination of perceived barriers regarding consumption of fruits and vegetables.

Keywords: fruit, vegetable, decision balance, self-efficacy, trans-theoretical model

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Authors: B. Touati, A. Saad, B. Lips, A. Abdenbi, M. Mokhtari.

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The purpose of this study is an application of experiment design method for dimensioning of a solar drying system. NIMROD software was used to build up the matrix of experiments and to analyze the results. The software has the advantages of being easy to use and consists of a forced way, with some choices about the number and range of variation of the parameters, and the desired polynomial shape. The first design of experiments performed concern the drying with constant input characteristics of the hot air in the dryer and a second design of experiments in which the drying chamber is coupled with a solar collector. The first design of experiments allows us to study the influence of various parameters and get the studied answers in a polynomial form. The correspondence between the polynomial thus determined, and the model results were good. The results of the polynomials of the second design of experiments and those of the model are worse than the results in the case of drying with constant input conditions. This is due to the strong link between all the input parameters, especially, the surface of the sensor and the drying chamber, and the mass of the product.

Keywords: solar drying, experiment design method, NIMROD, mint leaves

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Authors: W. Sriwattanapongse, S. Prasitwattanaseree, S. Wongtrangan

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The transportation accidents mortality is a major problem that leads to loss of human lives, and economic. The objective was to identify patterns of statistical modeling for estimating mortality rates due to transportation accidents in Thailand by using data from 2000 to 2009. The data was taken from the death certificate, vital registration database. The number of deaths and mortality rates were computed classifying by gender, age, year and region. There were 114,790 cases of transportation accidents deaths. The highest average age-specific transport accident mortality rate is 3.11 per 100,000 per year in males, Southern region and the lowest average age-specific transport accident mortality rate is 1.79 per 100,000 per year in females, North-East region. Linear, poisson and negative binomial models were chosen for fitting statistical model. Among the models fitted, the best was chosen based on the analysis of deviance and AIC. The negative binomial model was clearly appropriate fitted.

Keywords: transportation accidents, mortality, modeling, analysis of deviance

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Authors: Ce Liu, Wei Huo

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A nonlinear trajectory tracking controller for quadrotor helicopter based on controlled Lagrangian (CL) method is proposed in this paper. A Lagrangian system with virtual angles as generated coordinates rather than Euler angles is developed. Based on the model, the matching conditions presented by nonlinear partial differential equations are simplified and explicitly solved. Smooth tracking control laws and the range of control parameters are deduced based on the controlled energy of closed-loop system. Besides, a constraint condition for reference accelerations is deduced to identify the trackable reference trajectories by the proposed controller and to ensure the stability of the closed-loop system. The proposed method in this paper does not rely on the division of the quadrotor system, and the design of the control torques does not depend on the thrust as in backstepping or hierarchical control method. Simulations for a quadrotor model demonstrate the feasibility and efficiency of the theoretical results.

Keywords: quadrotor, trajectory tracking control, controlled lagrangians, underactuated system

Procedia PDF Downloads 125

Authors: M. Ezzat, Y. Zaghloul, T. Sorour, A. Hefny, M. Eid

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Ultimate capacity of large diameter bored piles is usually determined from pile loading tests as recommended by several international codes and foundation design standards. However, loading of this type of piles till achieving apparent failure is practically seldom. In this paper, numerical analyses are carried out to simulate load test of a large diameter bored pile performed at the location of Alzey highway bridge project (Germany). Test results of pile load settlement relationship till failure as well as results of the base and shaft resistances are available. Apparent failure was indicated in this test by the significant increase of the induced settlement during the last load increment applied on the pile head. Measurements of this pile load test are used to assess the quality of the numerical models investigated. Three different material soil models are implemented in the analyses: Mohr coulomb (MC), Soft soil (SS), and Modified Mohr coulomb (MMC). Very good agreement is obtained between the field measured settlement and the calculated settlement using the MMC model. Results of analysis showed also that the MMC constitutive model is superior to MC, and SS models in predicting the ultimate base and shaft resistances of the large diameter bored pile. After calibrating the numerical model, behavior of large diameter bored piles under axial loads is discussed and the formation of the plastic zone around the pile is explored. Results obtained showed that the plastic zone below the base of the pile at failure extended laterally to about four times the pile diameter and vertically to about three times the pile diameter.

Keywords: ultimate capacity, large diameter bored piles, plastic zone, failure, pile load test

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Authors: Nadjib Melkemi, Salah Belaidi

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Quantitative Structure-Activity Relationship (QSAR) studies have been performed on nineteen molecules of 1,2-dithiole-3-thione analogues. The compounds used are the potent inducers of enzymes involved in the maintenance of reduced glutathione pools as well as phase-2 enzymes important to electrophile detoxication. A multiple linear regression (MLR) procedure was used to design the relationships between molecular descriptor and detoxication properties of the 1,2-dithiole-3-thione derivatives. The predictivity of the model was estimated by cross-validation with the leave-one-out method. Our results suggest a QSAR model based of the following descriptors: qS2, qC3, qC5, qS6, DM, Pol, log P, MV, SAG, HE and EHOMO for the specific activity of quinone reductase; qS1, qS2, qC3, qC4, qC5, qS6, DM, Pol, logP, MV, SAG, HE and EHOMO for the production of growth hormone. To confirm the predictive power of the models, an external set of molecules was used. High correlation between experimental and predicted activity values was observed, indicating the validation and the good quality of the derived QSAR models.

Keywords: QSAR, quinone reductase activity, production of growth hormone, MLR

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Authors: Alexander I. Dovgyallo, Evgeniy A. Zinoviev, Svetlana O. Nekrasova

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The most of works applied for the pulse tube converters contain the workflow description implemented through the use of mathematical models on stationary modes. However, the study of the thermoacoustic systems unsteady behavior in the start, stop, and acoustic load changes modes is in the particular interest. The aim of the present study was to develop a mathematical thermal excitation model of acoustic oscillations in pulse tube engine (PTE) as a small-scale scheme of pulse tube engine operating at atmospheric air. Unlike some previous works this standing wave configuration is a fully closed system. The improvements over previous mathematical models are the following: the model allows specifying any values of porosity for regenerator, takes into account the piston weight and the friction in the cylinder and piston unit, and determines the operating frequency. The numerical method is based on the relation equations between the pressure and volume velocity variables at the ends of each element of PTE which is recorded through the appropriate transformation matrix. A solution demonstrates that the PTE operation frequency is the complex value, and it depends on the piston mass and the dynamic friction due to its movement in the cylinder. On the basis of the determined frequency thermoacoustically induced heat transport and generation of acoustic power equations were solved for channel with temperature gradient on its ends. The results of numerical simulation demonstrate the features of the initialization process of oscillation and show that that generated acoustic power more than power on the steady mode in a factor of 3…4. But doesn`t mean the possibility of its further continuous utilizing due to its existence only in transient mode which lasts only for a 30-40 sec. The experiments were carried out on small-scale PTE. The results shows that the value of acoustic power is in the range of 0.7..1.05 W for the defined frequency range f = 13..18 Hz and pressure amplitudes 11..12 kPa. These experimental data are satisfactorily correlated with the numerical modeling results. The mathematical model can be straightforwardly applied for the thermoacoustic devices with variable temperatures of thermal reservoirs and variable transduction loads which are expected to occur in practical implementations of portable thermoacoustic engines.

Keywords: nonlinear processes, pulse tube engine, thermal excitation, standing wave

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Authors: Jun Sung Go, Jong Kang Park, Jong Tae Kim

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As semi-conductor manufacturing technology evolves; the single event transient problem becomes more significant issue. Single event transient has a critical impact on both combinational and sequential logic circuits, so it is important to evaluate the soft error tolerance of the circuits at the design stage. In this paper, we present a soft error detecting simulation using scan chain. The simulation model generates a single event transient randomly in the circuit, and detects the soft error during the execution of the test patterns. We verified this model by inserting a scan chain in an 8051 microprocessor using 65 nm CMOS technology. While the test patterns generated by ATPG program are passing through the scan chain, we insert a single event transient and detect the number of soft errors per sub-module. The experiments show that the soft error rates per cell area of the SFR module is 277% larger than other modules.

Keywords: scan chain, single event transient, soft error, 8051 processor

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Authors: Usarat Thawornchaisit, Kamalasiri Juthaisong, Kasama Parsongjeen, Phonsiri Phoengchan

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In this study, sludge samples that were collected from the wastewater treatment plant of a printed circuit board manufacturing industry in Thailand were subjected to acid extraction using sulfuric acid as the chemical extracting agent. The effects of sulfuric acid concentration (A), the ratio of a volume of acid to a quantity of sludge (B) and extraction time (C) on the efficiency of copper extraction were investigated with the aim of finding the optimal conditions for maximum removal of copper from the wastewater treatment sludge. Factorial experimental design was employed to model the copper extraction process. The results were analyzed statistically using analysis of variance to identify the process variables that were significantly affected the copper extraction efficiency. Results showed that all linear terms and an interaction term between volume of acid to quantity of sludge ratio and extraction time (BC), had statistically significant influence on the efficiency of copper extraction under tested conditions in which the most significant effect was ascribed to volume of acid to quantity of sludge ratio (B), followed by sulfuric acid concentration (A), extraction time (C) and interaction term of BC, respectively. The remaining two-way interaction terms, (AB, AC) and the three-way interaction term (ABC) is not statistically significant at the significance level of 0.05. The model equation was derived for the copper extraction process and the optimization of the process was performed using a multiple response method called desirability (D) function to optimize the extraction parameters by targeting maximum removal. The optimum extraction conditions of 99% of copper were found to be sulfuric acid concentration: 0.9 M, ratio of the volume of acid (mL) to the quantity of sludge (g) at 100:1 with an extraction time of 80 min. Experiments under the optimized conditions have been carried out to validate the accuracy of the Model.

Keywords: acid treatment, chemical extraction, sludge, waste management

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Authors: R. Nandhini, Gaurab Mudbhari

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Ranging from the field of health care to self-driving cars, machine learning and deep learning algorithms have revolutionized the field with the proper utilization of images and visual-oriented data. Segmentation, regression, classification, clustering, dimensionality reduction, etc., are some of the Machine Learning tasks that helped Machine Learning and Deep Learning models to become state-of-the-art models for the field where images are key datasets. Among these tasks, classification and clustering are essential but difficult because of the intricate and high-dimensional characteristics of image data. This finding examines and assesses advanced techniques in supervised classification and unsupervised clustering for image datasets, emphasizing the relative efficiency of Convolutional Neural Networks (CNNs), Vision Transformers (ViTs), Deep Embedded Clustering (DEC), and self-supervised learning approaches. Due to the distinctive structural attributes present in images, conventional methods often fail to effectively capture spatial patterns, resulting in the development of models that utilize more advanced architectures and attention mechanisms. In image classification, we investigated both CNNs and ViTs. One of the most promising models, which is very much known for its ability to detect spatial hierarchies, is CNN, and it serves as a core model in our study. On the other hand, ViT is another model that also serves as a core model, reflecting a modern classification method that uses a self-attention mechanism which makes them more robust as this self-attention mechanism allows them to lean global dependencies in images without relying on convolutional layers. This paper evaluates the performance of these two architectures based on accuracy, precision, recall, and F1-score across different image datasets, analyzing their appropriateness for various categories of images. In the domain of clustering, we assess DEC, Variational Autoencoders (VAEs), and conventional clustering techniques like k-means, which are used on embeddings derived from CNN models. DEC, a prominent model in the field of clustering, has gained the attention of many ML engineers because of its ability to combine feature learning and clustering into a single framework and its main goal is to improve clustering quality through better feature representation. VAEs, on the other hand, are pretty well known for using latent embeddings for grouping similar images without requiring for prior label by utilizing the probabilistic clustering method.

Keywords: machine learning, deep learning, image classification, image clustering

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Authors: Luís Marques, João Rocha, Andreia Fernandes, Maria Moura, Cláudia Caseiro, Filipa Figueiredo, João Nunes

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The implementation of circularity strategies other than recycling, such as reducing the amount of raw material, as well as reusing or sharing existing products, remains marginal. The European Commission announced that the transition towards a more circular economy could lead to the net creation of about 700,000 jobs in Europe by 2030, through additional labour demand from recycling plants, repair services and other circular activities. Efforts to create new circular business models in accordance with completely circular processes, as opposed to linear ones, have increased considerably in recent years. In order to create a societal Circular Economy transition model, it is necessary to include innovative solutions, where startups play a key role. Early-stage startups based on new business models according to circular processes often face difficulties in creating enough impact. The StartUp Zero Program designs a model and approach to increase the flow of startups in the Circular Economy field, focusing on a systemic decision analysis and multi-generational approach, considering Multi-Criteria Decision Analysis to support a decision-making tool, which is also supported by the use of a combination of an Analytical Hierarchy Process and Multi-Attribute Value Theory methods. We define principles, criteria and indicators for evaluating startup prerogatives, quantifying the evaluation process in a unique result. Additionally, this entrepreneurship program spanning 16 months involved more than 2400 young people, from ages 14 to 23, in more than 200 interaction activities.

Keywords: circular economy, entrepreneurship, startups;, multi-criteria decision analysis

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Authors: Jian Zheng, Jinfeng Yu, Xinhua Ni

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The limiting fracture stress predicting model of composite ceramics with symmetric triangle eutectic was established based on its special microscopic structure. The symmetric triangle eutectic is consisted of matrix, the strong constraint inter-phase and reinforced fiber inclusions which are 120 degrees uniform symmetrical distribution. Considering the conditions of the rupture of the cohesive bond between matrix and fibers in eutectic and the stress concentration effect at the fiber end, the intrinsic fracture stress of eutectic was obtained. Based on the biggest micro-damage strain in eutectic, defining the load function, the macro-damage fracture stress of symmetric triangle eutectic was determined by boundary conditions. Introducing the conception of critical zone, the theoretical limiting fracture stress forecasting model of composite ceramics was got, and the stress was related to the fiber size and fiber volume fraction in eutectic. The calculated results agreed with the experimental results in the literature.

Keywords: symmetric triangle eutectic, composite ceramics, limiting stress, intrinsic fracture stress

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Authors: Chia Yu Chen, Shu Fen Wu, Chen-Fuh Lam, I-Ling Tsai, Shu Jiuan Chen, Yen Ling Liu

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Aim: It remains undetermined that whether increased work stress may affect the job satisfaction and career loyalty among nursing staffs in the operating room. The long-term goal of this study is to lengthen the professional life of operating room nurses by attenuating the work stress and enhancing their contentment in work. Method: This was a cross-sectional, descriptive study performed in a metropolitan teaching hospital in the southern Taiwan between May 2017 to July 2017. A structured self-administered questionnaire, modified from the Occupational Stress Indicator-2 (OSI-2) and Maslach Burnout Inventory (MBI) manual was collected from the operating room nurses. Chi-square test was used to analyze the categorical data and Pearson correlation was used to analyze the association between two numerical datasets (SPSS version 20.0). Results: The response rate was 80% (80/100) and a total of 73 (73%) completed forms were eventually proceeded for analysis. The average scores for work stress and job satisfaction of the operating room nurses were 145.96±32.91 and 47.38±6.07, respectively. The correlation coefficients of work stress versus job satisfaction and organizational identity were (r=-0.338, p=0.003 and r=-0.354, p=0.002), respectively. There were more nurses who took rotating shift quitted works from the operating room than those who took only dayshift (2＝5.176, p<0.05). Nurses who reported of having lower job satisfaction were associated with significantly higher turnover intention (t=3.714, p< 0.01). Following multivariate regression analysis, rotating shift and low job satisfaction were identified as the two independent predictors of intention to quit from working in the operating room. Conclusion: Our study clearly demonstrates that increased work stress significantly attenuates job satisfaction and organizational identity. Rotating shift is associated with higher work stress, lower job satisfaction, and higher turnover intention, which is consistent with the previous surveys carried out in the department of medical technology. Therefore, improvement of working quality in the operating rooms is essential to increase the retain intention of the well-trained nursing staffs. Further investigation into types of work shifts and other strategies of attenuating stress in workplace is currently undertaken in order to improve the job satisfaction and to decrease turnover intention in the operating room.

Keywords: rotating shift, work stress, job satisfaction, turnover intention

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Authors: Rehab F. Abdel-Rahman, Sally A. El Awdan, Rehab R. Hegazy, Dina F. Mansour, Hanan A. Ogaly, Marwan Abdelbaset

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Disorders of the cerebral circulation are the leading cause of numerous neurological and psychiatric illnesses. The transient middle cerebral artery occlusion model (MCAO) is considered to be a reliable and reproducible rodent model of cerebral ischemia. The purpose of the current study was to examine the neuroprotective effects of Crocus sativus (saffron) in a rat model of left middle cerebral artery MCAO. Male Wistar rats were anesthetized and subjected to 1 h of MCAO followed by 48 h reperfusion or sham surgery. One group of the ischemia operated animals was kept as left brain ischemia/reperfusion (I/R). Another 2 operated groups received saffron extract (100 or 200 mg/kg, i.p) four times (60 min before the surgery, during the surgery, and on days 1 and 2 after the occlusion). During the experiment, behavioral tests were performed. After 72 h the animals were euthanized and their left brain hemispheres were used in the biochemical, histopathological, and immunohistochemical studies. Saffron administration revealed an improvement in I/R-induced alteration of locomotor balance and coordination ability of rats. Moreover, saffron decreased the brain content of malondialdehyde, nitric oxide, brain natriuretic peptide and vascular endothelial growth factor with significant increase of reduced glutathione. Immunohistochemical evaluation of caspase-3 and Bax protein expression revealed reduction in I/R-enhanced apoptosis in saffron treated rats. In conclusion, saffron treatment decreases ischemic brain injury in association with inhibition of apoptotic and oxidative cell death in a dose dependent manner.

Keywords: caspase-3, cerebral ischemia, Crocus sativus, rats, vascular endothelial growth factor

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Authors: Mahmoud Hassan, Walid Oueslati, Damien Rousseliere

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This paper explores the channels through which energy taxes may affect economic growth, using a simultaneous equations model for a balanced panel data of 31 OECD countries over the 1994–2013 period. The empirical results reveal a negative impact of energy taxes on physical investment in the short and long term. This impact is negatively sensitive to the existence and level of public debt. Additionally, the results show that energy taxes have an indirect effect on human capital through their impact on polluting emissions. The taxes on energy products are able to reduce both the flux and the stock of polluting emissions that have a negative impact on human capital skills in the short and long term. Finally, we found that energy taxes could encourage eco-innovation in the short and long term.

Keywords: energy taxes, economic growth, public debt, simultaneous equations model, multiple imputation

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Authors: Jianliang Xu, Zhenghua Dai, Zhongjie Shen, Haifeng Liu, Fuchen Wang

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In an entrained flow gasifier, the combustible components are converted into the gas phase, and the mineral content is converted into ash. Most of the ash particles or droplets are deposited on the refractory or membrane wall and form a slag layer that flows down to the quenching system. The captured particle reaction process and slag flow and phase transformation play an important role in gasifier performance and safe and stable operation. The reaction characteristic of captured char particles on the molten slag had been studied by applied a high-temperature stage microscope. The gasification process of captured chars with CO2 on the slag surface was observed and recorded, compared to the original char gasification. The particle size evolution, heat transfer process are discussed, and the gasification reaction index of the capture char particle are modeled. Molten slag layer promoted the char reactivity from the analysis of reaction index, Coupled with heat transfer analysis, shrinking particle model (SPM) was applied and modified to predict the gasification time at carbon conversion of 0.9, and results showed an agreement with the experimental data. A comprehensive model with gas-particle-slag flow and reaction models was used to model the different industry gasifier. The carbon conversion information in the spatial space and slag layer surface are investigated. The slag flow characteristic, such as slag velocity, molten slag thickness, slag temperature distribution on the membrane wall and refractory brick are discussed.

Keywords: char, slag, numerical simulation, gasification, wall reaction, membrane wall

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Authors: Stephen Coandadiputra, Chrestella Carissa

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Technology is created to simplify human’s life. One of current technology which being called as the second wave internet generation is the internet of things. Internet of things lets thousands of devices connected each other. In today's marketing world, IOT has brought customer into the next level which helping the customer to shorten every transaction they are conducting from traditional approach to sophisticated approach. However, the implementation of technology has always obstacles. The objective of this paper is to explore the determinants of customer to accepts such technology like the internet of things within their transaction. According to TAM (Technology Acceptance Model), researcher constructs the acceptance of internet of things based on perceived usefulness, perceived ease of use and trust and social factor and the two customer characteristics: perceived enjoyment and perceived behavioral control. This research uses exploratory research design which being facilitated by spreading questionnaire to 145 T-cash users in Jakarta and in its suburban region. At least, 190 samples were observed and questioned accordingly. All the collected data will be analyzed using Lisrel.

Keywords: behavioral intention to use, internet of things, near field communication, technology acceptance model

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Authors: Lorenza Fabiocchi, Marco Mariani, Andrea Lucchini Huspek, Matteo Pozzi, Massimiliano Bestetti, Serena Graziosi, Nora Lecis

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Additive manufacturing of stainless steels is rapidly developing thanks to the ability to achieve complex designs effortlessly. Stainless steel 17-4PH is valued for its high strength and corrosion resistance, however intricate geometries are challenging to obtain due to rapid tool wear when machined. Binder jetting additive manufacturing was used to produce 17–4PH samples and pulsed electron beam surface treatment was investigated to enhance surface properties of components. The aim is to improve the tribological performance compared to the as-sintered condition and the H900 aging process, which optimizes hardness and wear resistance. Printed samples were sintered in a reducing atmosphere and superficially treated with an electron beam by varying the voltage (20 - 25 - 30 kV) and pulse count (20 – 40 pulses). Then, the surface was characterized from a microstructural and mechanical standpoint. Scratch tests were performed, and a reciprocating linear pin-on-disk wear test was conducted at 2 N and 10 Hz. Results showed that the voltage affects the roughness and thickness of the treated layer, whilst the number of pulses influences the hardening of the microstructure and consequently the wear resistance. Treated samples exhibited lower coefficients of friction compared to as-printed surfaces, though the values approached those of aged samples after the abrasion of the melted layer, indicating a deeper heat-affected zone formation. Different amounts of residual stress in the heat effected zone were individuated through the scratch tests. Still, the friction remained lower than that of as-printed specimens. This study demonstrates that optimizing electron beam parameters is vital for achieving surface performance comparable to bulk aging treatments, with significant implications for long-term wear resistance.

Keywords: low energy high current pulsed electron beam, tribology, binder jetting 3D printing, 17-4PH stainless steel

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Authors: Calassandra Nwokoro

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Introduction: The nursing profession requires a lot of commitment, effort, and time to efficiently manage patients and provide them quality healthcare services, this work load may eventually cause the nurses to become burned out and experience psychological distress. This study assessed the prevalence of burnout, risk factors, and the coping strategies among nurses working in Lagos University Teaching Hospital (LUTH), Lagos state, Nigeria. Methodology: A descriptive cross-sectional study design was conducted among 308 nurses working in LUTH. Simple random sampling was used in selection of study respondents. The questionnaire comprised three parts; the sociodemographic characteristics of the respondents, the extent of burnout syndrome using the Maslach Burnout Inventory, and the coping strategies used among the respondents using the BRIEF-COPE Inventory. Results: This study revealed relatively high levels of burnout among the nurses in LUTH with a prevalence of 16.9%, 31.2% and 20.1% for high emotional exhaustion, high depersonalization and reduced professional accomplishment respectively. It also showed that burnout was significantly associated with long working hours. Religion was found to be the most commonly used coping strategy overall, while emotional support was the most frequently used coping strategy among nurses who had burnout. Conclusion: This study has revealed a relatively high prevalence of burnout among the nurses in Lagos University Teaching Hospital. In order to minimize the negative health impacts of burnout, the government should collaborate with psychologists and psychiatrists to implement regular stress management and stress inoculation programs for nurses and other health professionals in the country.

Keywords: burnout, nurses, coping strategies, healthcare

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Authors: Eugene Okyere-Kwakye

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Knowledge sharing is a practice where individuals commonly exchange both tacit and explicit knowledge to jointly create a new knowledge. Knowledge management literature vividly express that knowledge sharing is the keystone and perhaps it is the most important aspect of knowledge management. To enhance the understanding of knowledge sharing domain, this study is aimed to investigate some factors that could influence employee’s attitude and behaviour to share their knowledge. The researchers employed the social exchange theory as a theoretical foundation for this study. Three essential factors namely: Trust, mutual reciprocity and perceived enjoyment that could influence knowledge sharing behaviour has been incorporated into a research model. To empirically validate this model, data was collected from one hundred and twenty respondents. The multiple regression analysis was employed to analyse the data. The results indicate that perceived enjoyment and trust have a significant influence on knowledge sharing. Surprisingly, mutual reciprocity did not influence knowledge sharing. The paper concludes by highlight the practical implications of the findings and areas for future research to consider.

Keywords: perceived enjoyment, trust, knowledge sharing, knowledge management

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Authors: Brian J. Biroscak

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In the United States (US), “sex trafficking” is defined at the federal level in the Trafficking Victims Protection Act of 2000 as encompassing a number of processes such as recruitment, transportation, and provision of a person for the purpose of a commercial sex act. It involves the use of force, fraud, or coercion, or in which the person induced to perform such act has not attained 18 years of age. Accumulating evidence suggests that sex trafficking is exacerbated by social and environmental stressors (e.g., pandemics). Given that “provision” is a key part of the definition, “provisioning systems” may offer a useful lens through which to study sex trafficking dynamics. Provisioning systems are the social systems connecting individuals, small groups, entities, and embedded communities as they seek to satisfy their needs and wants for goods, services, experiences and ideas through value-based exchange in communities. This project presents a conceptual framework for understanding sex trafficking dynamics in the context of the COVID pandemic. The framework is developed as a system dynamics simulation model based on published evidence, social and behavioral science theory, and key informant interviews with stakeholders from the Protection, Prevention, Prosecution, and Partnership sectors in one US state. This “4 P Paradigm” has been described as fundamental to the US government’s anti-trafficking strategy. The present research question is: “How do sex trafficking systems (e.g., supply, demand and price) interact with other provisioning systems (e.g., networks of organizations that help sexually exploited persons) to influence trafficking over time vis-à-vis the COVID pandemic?” Semi-structured interviews with stakeholders (n = 19) were analyzed based on grounded theory and combined for computer simulation. The first step (Problem Definition) was completed by open coding video-recorded interviews, supplemented by a literature review. The model depicts provision of sex trafficking services for victims and survivors as declining in March 2020, coincidental with COVID, but eventually rebounding. The second modeling step (Dynamic Hypothesis Formulation) was completed by open- and axial coding of interview segments, as well as consulting peer-reviewed literature. Part of the hypothesized explanation for changes over time is that the sex trafficking system behaves somewhat like a commodities market, with each of the other subsystems exhibiting delayed responses but collectively keeping trafficking levels below what they would be otherwise. Next steps (Model Building & Testing) led to a ‘proof of concept’ model that can be used to conduct simulation experiments and test various action ideas, by taking model users outside the entire system and seeing it whole. If sex trafficking dynamics unfold as hypothesized, e.g., oscillated post-COVID, then one potential leverage point is to address the lack of information feedback loops between the actual occurrence and consequences of sex trafficking and those who seek to prevent its occurrence, prosecute the traffickers, protect the victims and survivors, and partner with the other anti-trafficking advocates. Implications for researchers, administrators, and other stakeholders are discussed.

Keywords: pandemics, provisioning systems, sex trafficking, system dynamics modeling

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Authors: Andre M. Carvalho, Pedro Sebastiao

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This article is based on a dissertation that intends to analyze and make a model, intelligently, algorithms based on stochastic processes of a gamification application applied to marketing. Gamification is used in our daily lives to engage us to perform certain actions in order to achieve goals and gain rewards. This strategy is an increasingly adopted way to encourage and retain customers through game elements. The application of gamification aims to encourage children between 6 and 10 years of age to have healthy habits and the purpose of serving as a model for use in marketing. This application was developed in unity; we implemented intelligent algorithms based on stochastic processes, web services to respond to all requests of the application, a back-office website to manage the application and the database. The behavioral analysis of the use of game elements and stochastic processes in children’s motivation was done. The application of algorithms based on stochastic processes in-game elements is very important to promote cooperation and to ensure fair and friendly competition between users which consequently stimulates the user’s interest and their involvement in the application and organization.

Keywords: engage, games, gamification, randomness, stochastic processes

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Authors: Messis A., Adjebli A., Ayeche R., Talbi M., Tighilet K., Louardiane M.

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Cancers are the second cause of death worldwide. Prevalence and incidence of cancers is getting increased by aging and population growth. This study aims to predict and modeling the evolution of breast, Colorectal, Lung, Bladder and Prostate cancers over the period of 2014-2019. In this study, data were analyzed using time series analysis with double exponential smoothing method to forecast the future pattern. To describe and fit the appropriate models, Minitab statistical software version 17 was used. Between 2014 and 2019, the overall trend in the raw number of new cancer cases registered has been increasing over time; the change in observations over time has been increasing. Our forecast model is validated since we have good prediction for the period 2020 and data not available for 2021 and 2022. Time series analysis showed that the double exponential smoothing is an efficient tool to model the future data on the raw number of new cancer cases.

Keywords: cancer, time series, prediction, double exponential smoothing

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Authors: Davoud Jafari, Paolo Di Marco, Alessandro Franco, Sauro Filippeschi

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This paper summarizes the results of an investigation into the heat pipe heat transfer for solar collector applications. The study aims to show the feasibility of a concentrating solar collector, which is coupled with a heat pipe. Particular emphasis is placed on the capillary and boiling limits in capillary porous structures, with different mesh numbers and wick thicknesses. A mathematical model of a cylindrical heat pipe is applied to study its behaviour when it is exposed to higher heat input at the evaporator. The steady state analytical model includes two-dimensional heat conduction in the HP’s wall, the liquid flow in the wick and vapor hydrodynamics. A sensitivity analysis was conducted by considering different design criteria and working conditions. Different wicks (mesh 50, 100, 150, 200, 250, and, 300), different porosities (0.5, 0.6, 0.7, 0.8, and 0.9) with different wick thicknesses (0.25, 0.5, 1, 1.5, and 2 mm) are analyzed with water as a working fluid. Results show that it is possible to improve heat transfer capability (HTC) of a HP by selecting the appropriate wick thickness, the effective pore radius, and lengths for a given HP configuration, and there exist optimal design criteria (optimal thick, evaporator adiabatic and condenser sections). It is shown that the boiling and wicking limits are connected and occurs in dependence on each other. As different parts of the HP external surface collect different fractions of the total incoming insolation, the analysis of non-uniform heat flux distribution indicates that peak heat flux is not affecting parameter. The parametric investigations are aimed to determine working limits and thermal performance of HP for medium temperature SC application.

Keywords: screened heat pipes, analytical model, boiling and capillary limits, concentrating collector

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Authors: Samuel Fernandes, Dylan Kato, Emin Burak Onat, Patrick Keyantuo, Raja Sengupta, Amine Bouzaghrane

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The COVID-19 pandemic has spread across the United States, forcing cities to impose stay-at-home and shelter-in-place orders. Building operations had to adjust as non-essential personnel worked from home. But as buildings prepare for personnel to return, they need to plan for safe operations amid new COVID-19 guidelines. In this paper we propose a methodology for capacity and flow modeling of personnel within buildings to safely operate under COVID-19 guidelines. We model personnel flow within buildings by network flows with queuing constraints. We study maximum flow, minimum cost, and minimax objectives. We compare our network flow approach with a simulation model through a case study and present the results. Our results showcase various scenarios of how buildings could be operated under new COVID-19 guidelines and provide a framework for building operators to plan and operate buildings in this new paradigm.

Keywords: network analysis, building simulation, COVID-19

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Authors: Evariste Boj, Jan Schee

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We present the temperature anisotropy of the cosmic microwave background radiation due to the inhomogeneity region constructed on a 3-brane in the framework of a Randall-Sundrum one brane immersed into a 5D bulk $AdS_5$ spacetime. We employ the Brane-World Friedmann-Lemaitre-Robertson-Walker (FLRW) cosmological model to describe the cosmic expansion on the brane. The inhomogeneity is modeled by the static, spherically symmetric spacetime that replaces the spherically symmetric part of a dust-filled universe and is connected to the FLRW spacetime through the junction conditions. As the vacuum region expands it induces an additional frequency shift to a CMBR photon passing through this inhomogeneity in comparison to the case of a photon propagating through a pure FLRW spacetime. This frequency shift is associated with the effective temperature change of the CMBR in the corresponding direction. We give an estimate of the CMBR effective temperature changes with the change of the value of the tidal charge parameter.

Keywords: CMBR, Randall-Sundrum model, Rees-Sciama effect, Braneworld

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Authors: Anthony John Walker, Glen Bright

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The challenge faced by manufactures, when producing custom products, is that each product needs exact components. This can cause work-in-process instability due to component matching constraints imposed on assembly cells. Clearing type flow control policies have been used extensively in mediating server access between multiple arrival processes. Although the stability and performance of clearing policies has been well formulated and studied in the literature, the growth in arrival to departure sequence disorder for each arriving job, across a serving resource, is still an area for further analysis. In this paper, a closed form industrial model has been formulated that characterizes arrival-to-departure sequence disorder through stable manufacturing systems under clearing type flow control policy. Specifically addressed are the effects of sequence disorder imposed on a downstream assembly cell in terms of work-in-process instability induced through component matching constraints. Results from a simulated manufacturing system show that steady state average sequence disorder in parallel upstream processing cells can be balanced in order to decrease downstream assembly system instability. Simulation results also show that the closed form model accurately describes the growth and limiting behavior of average sequence disorder between parts arriving and departing from a manufacturing system flow controlled via clearing policy.

Keywords: assembly system constraint, custom products, discrete sequence disorder, flow control

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Authors: Brandon Ko

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Whether it’s a kitchen staff or a law firm, many groups tend to have homogenous characteristics of race, gender, interests, and goals. Social groups are not typically random samples of the population and will usually have common identifiers. According to Blau, age, sex, and education all play salient roles in shaping relationships within members of society. So if there is some degree of homogeneity within groups, the question arises whether this is beneficial or harmful to a group’s effectiveness. There has been much disagreement in the scientific community as to whether the presence of homophily benefits or hinders an athletic team's cohesiveness. For this paper, a comparative study of research of soccer case studies that followed various, youth players was studied against examinations of the effects that such a culture has on athletes. The case studies were used as evidence to determine what kind of homophily existed within the soccer camps. One case study followed several European developmental clubs such as Bayern Munich and Barcelona. Another study followed eight different players, four of each gender, implementing a similar method of interviewing, observing, and questioning. The individual and team goals of each athlete were reviewed to see which teams and players were ego-oriented and which were team-oriented. Additionally, there had been little research done on the relationship between homophily and how it applies to the sport community, suggesting the need to develop this neglected problem in applied psychology. This paper argues that the benefits of an egalitarian culture and stronger relations with people of a similar socio-demographic outweigh the liabilities of cohesion like being stereotyped and a lack of network outside the group as produced by homophily in athletic competition.

Keywords: group cohesion, homophily, sports psychology, youth athletics

Procedia PDF Downloads 288