Search results for: component damage function

Authors: Iwan Setiawan, Bobby Eka Gunara, Katshuhiro Nakamura

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The theory to accelerate system on quantum dynamics has been constructed to get the desired wave function on shorter time. This theory is developed on adiabatic quantum dynamics which any regulation is done on wave function that satisfies Schrödinger equation. We show accelerated manipulation of WFs with the use of a parameter-dependent in asymmetric double-well potential and also when it’s influenced by electromagnetic fields.

Keywords: driving potential, Adiabatic Quantum Dynamics, regulation, electromagnetic field

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Authors: Menan M. Elsayed, Hussein A. Heshmat

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The aim of the study is to determine the effect of 100 mg/d Pregnenolone on biological variables after plyometric training for volleyball players. Methods: 15 male volleyball players participated in this study. Serum levels of testosterone, creatine phosphokinase (CPK), lactate, and glucose were measured before and post-exercise. Results: Testosterone was not altered, while creatine phosphokinase (CPK), lactate, and glucose levels significantly decreased. It is recommended to use Pregnenolone administration to decreased muscle damage and delayed fatigue for volleyball players after plyometric training. In conclusion, this study demonstrated that oral Pregnenolone administration of 100 mg/d might decrease muscle damage and delayed fatigue which may affect positively the volleyball players after a plyometric training bout.

Keywords: biological variables, plyometric exercise program, pregnenolone, volleyball player

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Authors: Fariba Dortaj, Reza Asadinejad, Akram Dortaj, Atena Baziyar

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The aim of this study was to determine the effect of distance education (based on MOOC) on the components of academic engagement of Kerman PNU. The research was quasi-experimental method that cluster sampling with an appropriate volume was used in this study (one class in experimental group and one class in controlling group). Sampling method is single-stage cluster sampling. The statistical society is students of Kerman Payam Noor University, which) were selected 40 of them as sample (20 students in the control group and 20 students in experimental group). To test the hypothesis, it was used the analysis of univariate and Co-covariance to offset the initial difference (difference of control) in the experimental group and the control group. The instrument used in this study is academic engagement questionnaire of Zerang (2012) that contains component of cognitive, behavioral and motivational engagement. The results showed that there is no significant difference between mean scores of academic components of academic engagement in experimental group and the control group on the post-test, after elimination of the pre-test. The adjusted mean scores of components of academic engagement in the experimental group were higher than the adjusted average of scores after the test in the control group. The use of technology-based education in distance education has been effective in increasing cognitive engagement, motivational engagement and behavioral engagement among students. Experimental variable with the effect size 0.26, predicted 26% of cognitive engagement component variance. Experimental variable with the effect size 0.47, predicted 47% of the motivational engagement component variance. Experimental variable with the effect size 0.40, predicted 40% of behavioral engagement component variance. So teaching with technology (MOOC) has a positive impact on increasing academic engagement and academic performance of students in educational technology. The results suggest that technology (MOOC) is used to enrich the teaching of other lessons of PNU.

Keywords: educational technology, distance education, components of academic engagement, mooc technology

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Authors: Bijan Nahavandi, Navid Jafarinejad, Somayeh Mehrafzad

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Strategy maps represent the way of value creation in in each organization. Nowadays, implementation of strategy is the main concern for all organizations. Strategy map establishment is the start-up point of strategy implementation and this shows the critical importance of this concept. After some years past since emergence of strategy map, there are some shortcomings in its methodology that frequently quoted by many of researchers. One of these shortcomings is the shortage of a mechanism for refinement of objectives candidate for entrance to map. Organizations in practice have obsession and avidity to determine more number of objectives in strategy map. This study wants to represent a step by step approach to help obviate this problem using quality function deployment (QFD) as a helpful tool and fuzzy screening method. Finally, represented approach applies in a practical case and conclusions have been explained.

Keywords: balanced scorecard, fuzzy screening, house of strategic objectives (HoSO), quality function deployment, strategy map

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Authors: Elia Favarelli, Enrico Testi, Andrea Giorgetti

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Autonomous structural health monitoring (SHM) of many structures and bridges became a topic of paramount importance for maintenance purposes and safety reasons. This paper proposes a set of machine learning (ML) tools to perform automatic feature selection and detection of anomalies in a bridge from vibrational data and compare different feature extraction schemes to increase the accuracy and reduce the amount of data collected. As a case study, the Z-24 bridge is considered because of the extensive database of accelerometric data in both standard and damaged conditions. The proposed framework starts from the first four fundamental frequencies extracted through operational modal analysis (OMA) and clustering, followed by density-based time-domain filtering (tracking). The fundamental frequencies extracted are then fed to a dimensionality reduction block implemented through two different approaches: feature selection (intelligent multiplexer) that tries to estimate the most reliable frequencies based on the evaluation of some statistical features (i.e., mean value, variance, kurtosis), and feature extraction (auto-associative neural network (ANN)) that combine the fundamental frequencies to extract new damage sensitive features in a low dimensional feature space. Finally, one class classifier (OCC) algorithms perform anomaly detection, trained with standard condition points, and tested with normal and anomaly ones. In particular, a new anomaly detector strategy is proposed, namely one class classifier neural network two (OCCNN2), which exploit the classification capability of standard classifiers in an anomaly detection problem, finding the standard class (the boundary of the features space in normal operating conditions) through a two-step approach: coarse and fine boundary estimation. The coarse estimation uses classics OCC techniques, while the fine estimation is performed through a feedforward neural network (NN) trained that exploits the boundaries estimated in the coarse step. The detection algorithms vare then compared with known methods based on principal component analysis (PCA), kernel principal component analysis (KPCA), and auto-associative neural network (ANN). In many cases, the proposed solution increases the performance with respect to the standard OCC algorithms in terms of F1 score and accuracy. In particular, by evaluating the correct features, the anomaly can be detected with accuracy and an F1 score greater than 96% with the proposed method.

Keywords: anomaly detection, frequencies selection, modal analysis, neural network, sensor network, structural health monitoring, vibration measurement

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Authors: Razieh Rezaeekalantari

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Objective: The purpose of this study was to investigate the prediction of parenting orientations in terms of the components of couples' sexual review. Methods: This was a descriptive correlational research method. The population consisted of 500 couples referring to Sari Health Center. Two hundred and fifteen (215) people were selected randomly by using Krejcie-Morgan-sample-size-table. For data collection, the childbearing orientations scale and the Multidimensional Sexual Self-Concept Questionnaire were used. Result: For data analysis, the mean and standard deviation were used and to analyze the research hypothesis regression correlation and inferential statistics were used. Conclusion: The findings indicate that there is not a significant relationship between the tendency to childbearing and the predictive value of sexual review (r = 0.84) with significant level (sig = 219.19) (P < 0.05). So, with 95% confidence, we conclude that there is not a meaningful relationship between sexual orientation and tendency to child-rearing.

Keywords: couples referring, health center, sexual review component, parenting orientations

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Authors: Helena Dvořáčková, Mikajlo Irina, Záhora Jaroslav, Elbl Jakub

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Biochar can be produced from the waste matter and its application has been associated with returning of carbon in large amounts into the soil. The impacts of this material on physical and chemical properties of soil have been described. The biggest part of the research work is dedicated to the hypothesis of this material’s toxic effects on the soil life regarding its effect on the soil biological component. At present, it has been worked on methods which could eliminate these undesirable properties of biochar. One of the possibilities is to mix biochar with organic material, such as compost, or focusing on the natural processes acceleration in the soil. In the experiment has been used as the addition of compost as well as the elimination of toxic substances by promoting microbial activity in aerated water environment. Biochar was aerated for 7 days in a container with a volume of 20 l. This way modified biochar had six times higher biomass production and reduce mineral nitrogen leaching. Better results have been achieved by mixing biochar with compost.

Keywords: leaching of nitrogen, soil, biochar, compost

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Authors: Selim M. Khan

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Indoor air quality is strongly influenced by the presence of radioactive radon (222Rn) gas. Indeed, exposure to high 222Rn concentrations is unequivocally linked to DNA damage and lung cancer and is a worsening issue in North American and European built environments, having increased over time within newer housing stocks as a function of as yet unclear variables. Indoor air radon concentration can be influenced by a wide range of environmental, structural, and behavioral factors. As some of these factors are quantitative while others are qualitative, no single statistical model can determine indoor radon level precisely while simultaneously considering all these variables across a complex and highly diverse dataset. The ability of AI- machine (deep) learning to simultaneously analyze multiple quantitative and qualitative features makes it suitable to predict radon with a high degree of precision. Using Canadian and Swedish long-term indoor air radon exposure data, we are using artificial deep neural network models with random weights and polynomial statistical models in MATLAB to assess and predict radon health risk to human as a function of geospatial, human behavioral, and built environmental metrics. Our initial artificial neural network with random weights model run by sigmoid activation tested different combinations of variables and showed the highest prediction accuracy (>96%) within the reasonable iterations. Here, we present details of these emerging methods and discuss strengths and weaknesses compared to the traditional artificial neural network and statistical methods commonly used to predict indoor air quality in different countries. We propose an artificial deep neural network with random weights as a highly effective method for assessing and predicting indoor radon.

Keywords: radon, radiation protection, lung cancer, aI-machine deep learnng, risk assessment, risk prediction, Europe, North America

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Authors: Ryo Shikimoto, Hidehito Niimura, Hisashi Kida, Kota Suzuki, Yukiko Miyasaka, Masaru Mimura

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Introduction: In Japan, the most aged country in the world, it is important to explore predictive factors of cognitive function among the elderly. Coping behavior relieves chronic stress and improves lifestyle, and consequently may reduce the risk of cognitive impairment. One of the most widely investigated frameworks evaluated in previous studies is approach-oriented and avoidance-oriented coping strategies. The purpose of this study is to investigate the relationship between cognitive function and coping strategies among elderly residents in urban areas of Japan. Method: This is a part of the cross-sectional Arakawa geriatric cohort study for 1,099 residents (aged 65 to 86 years; mean [SD] = 72.9 [5.2]). Participants were assessed for cognitive function using the Mini-Mental State Examination (MMSE) and diagnosed by psychiatrists in face-to-face interviews. They were then investigated for their each coping behaviors and coping strategies (approach- and avoidance-oriented coping) using stress and coping inventory. A multiple regression analysis was used to investigate the relationship between MMSE score and each coping strategy. Results: Of the 1,099 patients, the mean MMSE score of the study participants was 27.2 (SD = 2.7), and the numbers of the diagnosis of normal, mild cognitive impairment (MCI), and dementia were 815 (74.2%), 248 (22.6%), and 14 (1.3%), respectively. Approach-oriented coping score was significantly associated with MMSE score (B [partial regression coefficient] = 0.12, 95% confidence interval = 0.05 to 0.19) after adjusting for confounding factors including age, sex, and education. Avoidance-oriented coping did not show a significant association with MMSE score (B [partial regression coefficient] = -0.02, 95% confidence interval = -0.09 to 0.06). Conclusion: Approach-oriented coping was clearly associated with neurocognitive function in the Japanese population. A future longitudinal trial is warranted to investigate the protective effects of coping behavior on cognitive function.

Keywords: approach-oriented coping, cognitive impairment, coping behavior, dementia

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Authors: Abhilash Sahu, Amit Priyadarshi

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In this paper, we will discuss the existence of weak solutions of the Kirchhoff type boundary value problem on the Sierpinski gasket. Where S denotes the Sierpinski gasket in R² and S₀ is the intrinsic boundary of the Sierpinski gasket. M: R → R is a positive function and h: S × R → R is a suitable function which is a part of our main equation. ∆p denotes the p-Laplacian, where p > 1. First of all, we will define a weak solution for our problem and then we will show the existence of at least two solutions for the above problem under suitable conditions. There is no well-known concept of a generalized derivative of a function on a fractal domain. Recently, the notion of differential operators such as the Laplacian and the p-Laplacian on fractal domains has been defined. We recall the result first then we will address the above problem. In view of literature, Laplacian and p-Laplacian equations are studied extensively on regular domains (open connected domains) in contrast to fractal domains. In fractal domains, people have studied Laplacian equations more than p-Laplacian probably because in that case, the corresponding function space is reflexive and many minimax theorems which work for regular domains is applicable there which is not the case for the p-Laplacian. This motivates us to study equations involving p-Laplacian on the Sierpinski gasket. Problems on fractal domains lead to nonlinear models such as reaction-diffusion equations on fractals, problems on elastic fractal media and fluid flow through fractal regions etc. We have studied the above p-Laplacian equations on the Sierpinski gasket using fibering map technique on the Nehari manifold. Many authors have studied the Laplacian and p-Laplacian equations on regular domains using this Nehari manifold technique. In general Euler functional associated with such a problem is Frechet or Gateaux differentiable. So, a critical point becomes a solution to the problem. Also, the function space they consider is reflexive and hence we can extract a weakly convergent subsequence from a bounded sequence. But in our case neither the Euler functional is differentiable nor the function space is known to be reflexive. Overcoming these issues we are still able to prove the existence of at least two solutions of the given equation.

Keywords: Euler functional, p-Laplacian, p-energy, Sierpinski gasket, weak solution

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Authors: Shabnam Najafi, Metin Turkay

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Network design problem (NDP) is used to determine the set of optimal values for certain pre-specified decision variables such as capacity expansion of nodes and links by optimizing various system performance measures including safety, congestion, and accessibility. The designed transportation network should improve objective functions defined for the system by considering the route choice behaviors of network users at the same time. The NDP studies mostly investigated the random demand and route selection constraints separately due to computational challenges. In this work, we consider both random demand and route selection constraints simultaneously. This work presents a nonlinear stochastic model for land use and road network design problem to address the development of different functional zones in urban areas by considering both cost function and air pollution. This model minimizes cost function and air pollution simultaneously with random demand and stochastic route selection constraint that aims to optimize network performance via road capacity expansion. The Bureau of Public Roads (BPR) link impedance function is used to determine the travel time function in each link. We consider a city with origin and destination nodes which can be residential or employment or both. There are set of existing paths between origin-destination (O-D) pairs. Case of increasing employed population is analyzed to determine amount of roads and origin zones simultaneously. Minimizing travel and expansion cost of routes and origin zones in one side and minimizing CO emission in the other side is considered in this analysis at the same time. In this work demand between O-D pairs is random and also the network flow pattern is subject to stochastic user equilibrium, specifically logit route choice model. Considering both demand and route choice, random is more applicable to design urban network programs. Epsilon-constraint is one of the methods to solve both linear and nonlinear multi-objective problems. In this work epsilon-constraint method is used to solve the problem. The problem was solved by keeping first objective (cost function) as the objective function of the problem and second objective as a constraint that should be less than an epsilon, where epsilon is an upper bound of the emission function. The value of epsilon should change from the worst to the best value of the emission function to generate the family of solutions representing Pareto set. A numerical example with 2 origin zones and 2 destination zones and 7 links is solved by GAMS and the set of Pareto points is obtained. There are 15 efficient solutions. According to these solutions as cost function value increases, emission function value decreases and vice versa.

Keywords: epsilon-constraint, multi-objective, network design, stochastic

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Authors: Ieva Bruzauskaite, Jovile Raudoniute, Karina Poliakovaite, Danguole Zabulyte, Daiva Bironaite, Ruta Aldonyte

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Introduction: Air pollution is a growing global problem which has been shown to be responsible for various adverse health outcomes. Immunotoxicity, such as dysregulated inflammation, has been proposed as one of the main mechanisms in air pollution-associated diseases. Chronic obstructive pulmonary disease (COPD) is among major morbidity and mortality causes worldwide and is characterized by persistent airflow limitation caused by the small airways disease (obstructive bronchiolitis) and irreversible parenchymal destruction (emphysema). Exact pathways explaining the air pollution induced and mediated disease states are still not clear. However, modern societies understand dangers of polluted air, seek to mitigate such effects and are in need for reliable biomarkers of air pollution. We hypothesise that post-translational modifications of structural proteins, e.g. citrullination, might be a good candidate biomarker. Thus, we have designed this study, where mice were exposed to diesel exhaust and the ongoing protein modifications and inflammation in lungs and other tissues were assessed. Materials And Methods: To assess the effects of diesel exhaust a in vivo study was designed. Mice (n=10) were subjected to everyday 2-hour exposure to diesel exhaust for 14 days. Control mice were treated the same way without diesel exhaust. The effects within lung and other tissues were assessed by immunohistochemistry of formalin-fixed and paraffin-embedded tissues. Levels of inflammation and citrullination related markers were investigated. Levels of parenchymal damage were also measured. Results: In vivo study corroborates our own data from in vitro and reveals diesel exhaust initiated inflammatory shift and modulation of lung peptidyl arginine deiminase 4 (PAD4), citrullination associated enzyme, levels. In addition, high levels of citrulline were observed in exposed lung tissue sections co-localising with increased parenchymal destruction. Conclusions: Subacute exposure to diesel exhaust renders mice lungs inflammatory and modifies certain structural proteins. Such structural changes of proteins may pave a pathways to lost/gain function of affected molecules and also propagate autoimmune processes within the lung and systemically.

Keywords: air pollution, citrullination, in vivo, lungs

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Authors: Seyedehsomayeh Hosseini

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Much attention has been paid over centuries to understanding and solving the problem of minimization of functions. Compared to linear programming and nonlinear unconstrained optimization problems, nonlinear constrained optimization problems are much more difficult. Since the procedure of finding an optimizer is a search based on the local information of the constraints and the objective function, it is very important to develop techniques using geometric properties of the constraints and the objective function. In fact, differential geometry provides a powerful tool to characterize and analyze these geometric properties. Thus, there is clearly a link between the techniques of optimization on manifolds and standard constrained optimization approaches. Furthermore, there are manifolds that are not defined as constrained sets in R^n an important example is the Grassmann manifolds. Hence, to solve optimization problems on these spaces, intrinsic methods are used. In a nondifferentiable problem, the gradient information of the objective function generally cannot be used to determine the direction in which the function is decreasing. Therefore, techniques of nonsmooth analysis are needed to deal with such a problem. As a manifold, in general, does not have a linear structure, the usual techniques, which are often used in nonsmooth analysis on linear spaces, cannot be applied and new techniques need to be developed. This paper presents necessary and sufficient conditions for a strict local minimum of extended real-valued, nonsmooth functions defined on Riemannian manifolds.

Keywords: Riemannian manifolds, nonsmooth optimization, lower semicontinuous functions, subdifferential

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Authors: Yuri Boiko, Iluju Kiringa, Tet Yeap

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Current drainage attack suggested previously is further studied in regular settings of closed-loop controlled Brushless DC (BLDC) motor with Kalman filter in the feedback loop. Modeling and simulation experiments are conducted in a Matlab environment, implementing the closed-loop control model of BLDC motor operation in position sensorless mode under Kalman filter drive. The current increase in the motor windings is caused by the controller (p-controller in our case) affected by false data injection of substitution of the angular velocity estimates with distorted values. Operation of multiplication to distortion coefficient, values of which are taken from the distortion function synchronized in its periodicity with the rotor’s position change. A saw function with a triangular tooth shape is studied herewith for the purpose of carrying out the bias injection with current drainage consequences. The specific focus here is on how the asymmetry of the tooth in the saw function affects the flow of current drainage. The purpose is two-fold: (i) to produce and collect the signature of an asymmetric saw in the attack for further pattern recognition process, and (ii) to determine conditions of improving stealthiness of such attack via regulating asymmetry in saw function used. It is found that modification of the symmetry in the saw tooth affects the periodicity of current drainage modulation. Specifically, the modulation frequency of the drained current for a fully asymmetric tooth shape coincides with the saw function modulation frequency itself. Increasing the symmetry parameter for the triangle tooth shape leads to an increase in the modulation frequency for the drained current. Moreover, such frequency reaches the switching frequency of the motor windings for fully symmetric triangular shapes, thus becoming undetectable and improving the stealthiness of the attack. Therefore, the collected signatures of the attack can serve for attack parameter identification via the pattern recognition route.

Keywords: bias injection attack, Kalman filter, BLDC motor, control system, closed loop, P-controller, PID-controller, current drainage, saw-function, asymmetry

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Authors: Guermache Ahmed Chafik, Khelfellah Ismail, Ait-Ali Takfarines

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The Savonius vertical axis wind turbine is characterized by sufficient starting torque at low wind speeds, simple design and does not require orientation to the wind direction; however, the developed power is lower than other types of wind turbines such as Darrieus. To increase these performances several studies and researches have been developed, such as optimizing blades shape, using passive controls and also minimizing power losses sources like the resisting torque due to friction. This work aims to estimate the performance of a Savonius wind turbine introducing a User Defined Function to the CFD model analyzing resisting torque. This User Defined Function is developed to simulate the action of the wind speed on the rotor; it receives the moment coefficient as an input to compute the rotational velocity that should be imposed on computational domain rotating regions. The rotational velocity depends on the aerodynamic moment applied on the turbine and the resisting torque, which is considered a linear function. Linking the implemented User Defined Function with the CFD solver allows simulating the real functioning of the Savonius turbine exposed to wind. It is noticed that the wind turbine takes a while to reach the stationary regime where the rotational velocity becomes invariable; at that moment, the tip speed ratio, the moment and power coefficients are computed. To validate this approach, the power coefficient versus tip speed ratio curve is compared with the experimental one. The obtained results are in agreement with the available experimental results.

Keywords: resistant torque modeling, Savonius wind turbine, user-defined function, vertical axis wind turbine performances

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Authors: Iván Rivet, Narges Dialami, Miguel Cervera, Michele Chiumenti

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Process parameters in Additive Manufacturing (AM) play a critical role in the mechanical performance of the final component. In order to find the input configuration that guarantees the optimal performance of the printed part, the process-performance relationship must be found. Fused Filament Fabrication (FFF) is the selected demonstrative AM technology due to its great popularity in the industrial manufacturing world. A material model that considers the different printing patterns present in a FFF part is used. A voxelized mesh is built from the manufacturing toolpaths described in the G-Code file. An Adaptive Mesh Refinement (AMR) based on the octree strategy is used in order to reduce the complexity of the mesh while maintaining its accuracy. High-fidelity and cost-efficient Finite Element (FE) simulations are performed and the influence of key process parameters in the mechanical performance of the component is analyzed. A robust optimization process based on appropriate failure criteria is developed to find the printing direction that leads to the optimal mechanical performance of the component. The Tsai-Wu failure criterion is implemented due to the orthotropy and heterogeneity constitutive nature of FFF components and because of the differences between the strengths in tension and compression. The optimization loop implements a modified version of an Anomaly Detection (AD) algorithm and uses the computed metrics to obtain the optimal printing direction. The developed methodology is verified with a case study on an industrial demonstrator.

Keywords: additive manufacturing, optimization, printing direction, mechanical performance, voxelization

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Authors: C. Bay, A. Mahr, H. Groneberg, F. Döpper

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Additive Manufacturing processes are becoming increasingly established in the industry for the economic production of complex prototypes and functional components. Laser beam melting (LBM), the most frequently used Additive Manufacturing technology for metal parts, has been gaining in industrial importance for several years. The LBM process chain – from material storage to machine set-up and component post-processing – requires many manual operations. These steps often depend on the manufactured component and are therefore not standardized. These operations are often not performed in a standardized manner, but depend on the experience of the machine operator, e.g., levelling of the build plate and adjusting the first powder layer in the LBM machine. This lack of standardization limits the reproducibility of the component quality. When processing metal powders with inhalable and alveolar particle fractions, the machine operator is at high risk due to the high reactivity and the toxic (e.g., carcinogenic) effect of the various metal powders. Faulty execution of the operation or unintentional omission of safety-relevant steps can impair the health of the machine operator. In this paper, all the steps of the LBM process chain are first analysed in terms of their influence on the two aforementioned challenges: reproducibility and work safety. Standardization to avoid errors increases the reproducibility of component quality as well as the adherence to and correct execution of safety-relevant operations. The corresponding lean method 5S will therefore be applied, in order to develop approaches in the form of recommended actions that standardize the work processes. These approaches will then be evaluated in terms of ease of implementation and their potential for improving reproducibility and work safety. The analysis and evaluation showed that sorting tools and spare parts as well as standardizing the workflow are likely to increase reproducibility. Organizing the operational steps and production environment decreases the hazards of material handling and consequently improves work safety.

Keywords: additive manufacturing, lean production, reproducibility, work safety

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Authors: R. K. Chaurasiya, N. D. Londhe, S. Ghosh

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The study of the electrical signals produced by neural activities of human brain is called Electroencephalography. In this paper, we propose an automatic and efficient EEG signal classification approach. The proposed approach is used to classify the EEG signal into two classes: epileptic seizure or not. In the proposed approach, we start with extracting the features by applying Discrete Wavelet Transform (DWT) in order to decompose the EEG signals into sub-bands. These features, extracted from details and approximation coefficients of DWT sub-bands, are used as input to Principal Component Analysis (PCA). The classification is based on reducing the feature dimension using PCA and deriving the support-vectors using Support Vector Machine (SVM). The experimental are performed on real and standard dataset. A very high level of classification accuracy is obtained in the result of classification.

Keywords: discrete wavelet transform, electroencephalogram, pattern recognition, principal component analysis, support vector machine

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Authors: Sayyed-javad Ziaolhagh, Ali-Reza Saadatifar

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Introduction: Athletes frequently perform anabolic steroid resistance exercise, but the effects of medical doses and abuse along with resistance exercise on structural damage to the Pancreases and also jujube extract are unknown. The aim of this study was to investigate the effects of resistance training on body weight and hip fractures induced by boldenone injection in male rats. Materials and methods: In this experimental study, 30 male Wistar rats aged 8-12 weeks (weight 202±9.34 g) were randomly divided into five groups: control, boldenone, extract of iujuba+boldenone, boldenone+resistance training and boldenone+resistance training +extract of jujuba. The resistance training program included climbing the ladder for 8 weeks, 3 days a week, 1 session training in a day and each session consisted of the 3 sets and 5 repetitions. Injection was conducted in depth in the hamstring once a week on an appointed day. After anesthesia, autopsy was performed, and the cardiac tissue was isolated. Results: Results showed that boldenone caused tissue damage, congestion, and nuclei unclear and diffuse. In the group "resistance + Boldenone," The Pancreases tissue showed a high degree of hyperemia, and the muscle cells were somewhat abnormal. In boldenone + jujube, the appearance of the tissue was normal, and the rejuvenating effect was visible. Conclusion: Boldenone appears to cause structural damage to the Pancreases tissue. Strength training with Jujube Extract can reduce part of the pancreatic system disorders (necrosis and inflammation) caused by anabolic steroid use.

Keywords: boldenone, Jujube extract, pancreases tissue, resistance training

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Authors: Dimitris Varsamis, Christos Talagkozis, Alkiviadis Tsimpiris, Paris Mastorocostas

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The aim of this work is the parallel implementation of k-means in MATLAB, in order to reduce the execution time. Specifically, a new function in MATLAB for serial k-means algorithm is developed, which meets all the requirements for the conversion to a function in MATLAB with parallel computations. Additionally, two different variants for the definition of initial values are presented. In the sequel, the parallel approach is presented. Finally, the performance tests for the computation times respect to the numbers of features and classes are illustrated.

Keywords: K-means algorithm, clustering, parallel computations, Matlab

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Authors: P. Venu, Joeju M. Issac

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Quality Function Deployment (QFD) is a systematic technique that creates a platform where the customer responses can be positively converted to design attributes. The accuracy of a QFD process heavily depends on the data that it is handling which is captured from customers or QFD team members. Customized computer programs that perform Quality Function Deployment within a stipulated time have been used by various companies across the globe. These programs heavily rely on storage and retrieval of the data on a common database. This database must act as a perfect source with minimum missing values or error values in order perform actual prioritization. This paper introduces a missing/error data handler module which uses Genetic Algorithm and Fuzzy numbers. The prioritization of customer requirements of sesame oil is illustrated and a comparison is made between proposed data handler module-based deployment and manual deployment.

Keywords: hybrid data handler, QFD, prioritization, module-based deployment

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Authors: Tella Toluwani, Adegbegi Ademuyiwa, Musei Chiedu, Adekunle Odola, Ayangbenro Ayansina, Adaramoye Oluwatosin

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Dithiocarbamates are very useful biological agents with antioxidant properties. Diclofenac (DIC) is a non-steroidal analgesic, anti-inflammatory, and antipyretic agent. The use of diclofenac has been linked with reproductive toxicity/damage. The purpose of this study is (i) To investigate the therapeutic potential of diisopropyldithiocarbamate sodium salt (Na(i-Pr₂dtc)) and vitamin E (VIT E) against diclofenac induced toxicity in the testes of male Wistar rats. (ii) To investigate the effect of (Na(i-Pr₂dtc)) and vitamin E on ameliorating damage done to the testes through histological analysis of the testes. Thirty-six (36) male Wistar rats were used for the experiment, they were divided into six (6) groups, the animals in group 1 served as control, animals in groups 2, 3, 4, 5 and 6 received DIC only, DIC and (Na(i-Pr₂dtc)), DIC and VIT E, (Na(i-Pr₂dtc) only and VIT E only respectively. A single dose of 100 mg/kg body weight of DIC was administered to male Wistar rats, while 30 mg/kg body weight of (Na(i-Pr₂dtc)) was used to treat both normal and DIC treated animals, control animals were treated with the vehicle, after 24 hrs of treatment the animals were euthanized and the testes were removed for analysis. The treatment of rats with Na(i-Pr₂dtc) significantly restored catalase (CAT) activity depressed by diclofenac. (Na(i-Pr₂dtc)) also restored glutathione levels reduced by DIC treatment and this was also accompanied by reduced lipid peroxidation (LPO) level. VIT E significantly restored superoxide dismutase (SOD) activity when compared with DIC only treated animals. Photomicrographs of testes from (Na(i-Pr₂dtc)) treated rats showed seminiferous epithelium with no lesions. We conclude that (Na(i-Pr₂dtc)) has an antioxidant effect, which might be related to the dose and duration of administration.

Keywords: diisopropyldithiocarbamate sodium salt, diclofenac, vitamin E, testes

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Authors: Mikel Alonso López, María Francisca Blasco López, Víctor Molero Ayala

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The present study explains the somatic marker theory of Antonio Damasio, which indicates that when making a decision, the stored or possible future scenarios (future memory) images allow people to feel for a moment what would happen when they make a choice, and how this is emotionally marked. This process can be conscious or unconscious. The development of new Neuromarketing techniques such as functional magnetic resonance imaging (fMRI), carries a greater understanding of how the brain functions and consumer behavior. In the results observed in different studies using fMRI, the evidence suggests that the somatic marker and future memories influence the decision-making process, adding a positive or negative emotional component to the options. This would mean that all decisions would involve a present emotional component, with a rational cost-benefit analysis that can be performed later.

Keywords: emotions, decision making, somatic marker, consumer´s brain

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Authors: Omer Altaf, Liam Wotherspoon, Rolando Orense

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The Wairau Plains are located in the north-east of the South Island of New Zealand in the region of Marlborough. The region is cut by many active crustal faults such as the Wairau, Awatere, and Clarence faults, which give rise to frequent seismic events. This paper presents the preliminary results of the overall project in which liquefaction-induced ground damage maps are developed in the Wairau Plains based on the Ministry of Business, Innovation and Employment NZ guidance. A suite of maps has been developed in relation to the level of details that was available to inform the liquefaction hazard mapping. Maps at the coarsest level of detail make use of regional geologic information, applying semi-quantitative criteria based on geological age, design peak ground accelerations and depth to the water table. The next level of detail incorporates higher resolution surface geomorphologic characteristics to better delineate potentially liquefiable and non-liquefiable deposits across the region. The most detailed assessment utilised CPT sounding data to develop ground damage response curves for areas across the region and provide a finer level of categorisation of liquefaction vulnerability. Linking these with design level earthquakes defined through NZGS guidelines will enable detailed classification to be carried out at CPT investigation locations, from very low through to high liquefaction vulnerability. To update classifications to these detailed levels, CPT investigations in geomorphic regions are grouped together to provide an indication of the representative performance of the soils in these areas making use of the geomorphic mapping outlined above.

Keywords: hazard, liquefaction, mapping, seismicity

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Authors: Carlos H. Cuadra, Nobuhiro Shimoi

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Application of piezoelectric sensors to detect structural damage due to seismic action on building structures is investigated. Plate-type piezoelectric sensor was developed and proposed for this task. A film-type piezoelectric sheet was attached on a steel plate and covered by a layer of glass. A special glue is used to fix the glass. This glue is a silicone that requires the application of ultraviolet rays for its hardening. Then, the steel plate was set up at a steel column-beam joint of a test specimen that was subjected to bending moment when test specimen is subjected to monotonic load and cyclic load. The structural behavior of test specimen during cyclic loading was verified using a finite element model, and it was found good agreement between both results on load-displacement characteristics. The cross section of steel elements (beam and column) is a box section of 100 mm×100 mm with a thin of 6 mm. This steel section is specified by the Japanese Industrial Standards as carbon steel square tube for general structure (STKR400). The column and beam elements are jointed perpendicularly using a fillet welding. The resulting test specimen has a T shape. When large deformation occurs the glass plate of the sensor device cracks and at that instant, the piezoelectric material emits a voltage signal which would be the indicator of a certain level of deformation or damage. Applicability of this piezoelectric sensor to detect structural damages was verified; however, additional analysis and experimental tests are required to establish standard parameters of the sensor system.

Keywords: piezoelectric sensor, static cyclic test, steel structure, seismic damages

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Authors: Amberkar Mohanbabu Vittalrao, Avin, Meena Kumari Kamalkishore, Padmanabha Udupa, Vinaykumar Bavimane, Honnegouda

Abstract:

Objective: To evaluate the hepato-protective activity of Tinospora cordiofolia (Tc) against paracetamol induced hepatic damage in rats. Methods: The plant stem (test drug) was procured locally, shade dried, powdered and extracted with water. Silymarin was used as standard hepatoprotective drugs and 2% gum acacia as a control (vehicle) against paracetamol (PCT) induced hepatotoxicity. Results and Discussion: The hepato-protective activity of aqueous stem extract was assessed by paracetamol induced hepatotoxicity preventive model in rats. Alteration in the levels of biochemical markers of hepatic damage like AST, ALT, ALP and lipid peroxides were tested in both paracetamol treated and untreated groups. Paracetamol (3g/kg) had enhanced the AST, ALT, ALP and the lipid peroxides in the serum. Treatment of silymarin and aqueous stem extract of Tc (200 and 400mg/kg) extract showed significant hepatoprotective activity by altering biochemical marker levels to the near normal. Preliminary phytochemical tests were done. Aqueous Tc extract showed presence of phenolic compound and flavonoids. Our findings suggested that Tc extract possessed hepatoprotective activity in a dose dependent manner. Conclusions: Tc was found to possess significant hepatoprotective property when treated with PCT. This was evident by decreasing the liver enzymes significantly when treated with PCT as compared to PCT only treated group (P < 0.05). Hence Tinospora cardiofolia could be a good, promising, preventive agent against PCT induced hepatotoxicity.

Keywords: Tinospora cardiofolia, hepatoprotection, paracetamol, silymarin

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Authors: James Britton, Vijaya Krishna, Manus Biggs, Abhay Pandit

Abstract:

Regeneration of the spinal cord after injury remains a great challenge due to the complexity of this organ. Inflammation and gliosis at the injury site hinder the outgrowth of axons and hence prevent synaptic reconnection and reinnervation. Hyaluronic acid (HA) is the main component of the spinal cord extracellular matrix and plays a vital role in cell proliferation and axonal guidance. In this study, we have synthesized and characterized a photo-cross-linkable HA-tyramine (tyr) hydrogel from a chemical, mechanical, electrical, biological and structural perspective. From our experimentation, we have found that HA-tyr can be synthesized with controllable degrees of tyramine substitution using click chemistry. The complex modulus (G*) of HA-tyr can be tuned to mimic the mechanical properties of the native spinal cord via optimization of the photo-initiator concentration and UV exposure. We have examined the degree of tyramine-tyramine covalent bonding (polymerization) as a function of UV exposure and photo-initiator use via Photo and Nuclear magnetic resonance spectroscopy. Both swelling and enzymatic degradation assays were conducted to examine the resilience of our 3D printed hydrogel constructs in-vitro. Using a femtosecond 780nm laser, the two-photon polymerization of HA-tyr hydrogel in the presence of riboflavin photoinitiator was optimized. A laser power of 50mW and scan speed of 30,000 μm/s produced high-resolution spatial patterning within the hydrogel with sustained mechanical integrity. Using dorsal root ganglion explants, the cytocompatibility of photo-crosslinked HA-tyr was assessed. Using potentiometry, the electrical conductivity of photo-crosslinked HA-tyr was assessed and compared to that of native spinal cord tissue as a function of frequency. In conclusion, we have developed a biocompatible hydrogel that can be used for photolithographic 3D printing to fabricate tissue engineered constructs for neural tissue regeneration applications.

Keywords: 3D printing, hyaluronic acid, photolithography, spinal cord injury

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Authors: Samaneh Rahimirshnani, Hossein Jafari

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In this paper, we consider fluid queueing processes fed by an isonormal Gaussian process. We study the correlation structure of the queueing process and the rate of convergence of the running supremum in the queueing process. The Malliavin calculus techniques are applied to obtain relations that show the workload process inherits the dependence properties of the input process. As examples, we consider two isonormal Gaussian processes, the sub-fractional Brownian motion (SFBM) and the fractional Brownian motion (FBM). For these examples, we obtain upper bounds for the covariance function of the queueing process and its rate of convergence to zero. We also discover that the rate of convergence of the queueing process is related to the structure of the covariance function of the input process.

Keywords: queue length process, Malliavin calculus, covariance function, fractional Brownian motion, sub-fractional Brownian motion

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Authors: Z. Sakka, I. Assakkaf, T. Al-Yaqoub, J. Parol

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A reliability-based methodology for the analysis assessment and evaluation of reinforced concrete structural elements of concrete structures is presented herein. The results of the reliability analysis and assessment for structural elements are verified by the results obtained from the deterministic methods. The analysis outcomes of reliability-based analysis are compared against the safety limits of the required reliability index β according to international standards and codes. The methodology is based on probabilistic analysis using reliability concepts and statistics of the main random variables that are relevant to the subject matter, and for which they are to be used in the performance-function equation(s) related to the structural elements under study. These methodology techniques can result in reliability index β, which is commonly known as the reliability index or reliability measure value that can be utilized to assess and evaluate the safety, human risk, and functionality of the structural component. Also, these methods can result in revised partial safety factor values for certain target reliability indices that can be used for the purpose of redesigning the reinforced concrete elements of the building and in which they could assist in considering some other remedial actions to improve the safety and functionality of the member.

Keywords: structural reliability, concrete structures, FORM, Monte Carlo simulation

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Authors: Landry Tchambou Tchouongsi, Appolinaire Derbetini Vondou

Abstract:

This study describes the local Hadley circulation (HC) during the December-February (DJF) and June-August (JJA) seasons, respectively, in Central Africa (CA) from the divergent component of the mean meridional wind and also from a new method called the variation of the ψ vector. Historical data from the ERA5 reanalysis for the period 1983 to 2013 were used. The results show that the maximum of the upward branch of the local Hadley circulation in the DJF and JJA seasons is located under the Congo Basin (CB). However, seasonal and horizontal variations in the mean temperature gradient and thermodynamic properties are largely associated with the distribution of convection and large-scale upward motion. Thus, temperatures beneath the CB show a slight variation between the DJF and JJA seasons. Moreover, energy transport of the moist static energy (MSE) adequately captures the mean flow component of the HC over the tropics. By the way, the divergence under the CB is enhanced by the presence of the low pressure of western Cameroon and the contribution of the warm and dry air currents coming from the Sahara.

Keywords: Circulation, reanalysis, thermodynamic, local Hadley.

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