Search results for: random stimulation

Authors: Sergo Esadze

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Seismic resistance norms require calculation of cantilevers on vertical components of the base seismic acceleration. Long span cantilevers, as a rule, must be calculated as a separate construction element. According to the architectural-planning solution, functional purposes and environmental condition of a designing buildings/structures, long span cantilever construction may be of very different types: both by main bearing element (beam, truss, slab), and by material (reinforced concrete, steel). A choice from these is always linked with bearing construction system of the building. Research of vertical seismic vibration of these constructions requires individual approach for each (which is not specified in the norms) in correlation with model of seismic load. The latest may be given both as deterministic load and as a random process. Loading model as a random process is more adequate to this problem. In presented paper, two types of long span (from 6m – up to 12m) reinforcement concrete cantilever beams have been considered: a) bearing elements of cantilevers, i.e., elements in which they fixed, have cross-sections with large sizes and cantilevers are made with haunch; b) cantilever beam with load-bearing rod element. Calculation models are suggested, separately for a) and b) types. They are presented as systems with finite quantity degree (concentrated masses) of freedom. Conditions for fixing ends are corresponding with its types. Vertical acceleration and vertical component of the angular acceleration affect masses. Model is based on assumption translator-rotational motion of the building in the vertical plane, caused by vertical seismic acceleration. Seismic accelerations are considered as random processes and presented by multiplication of the deterministic envelope function on stationary random process. Problem is solved within the framework of the correlation theory of random process. Solved numerical examples are given. The method is effective for solving the specific problems.

Keywords: cantilever, random process, seismic load, vertical acceleration

Procedia PDF Downloads 159

Authors: Chung Hyun Goh, Armin Yazdanshenas, X. Neil Dong, Yong Tai Wang

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Physical rehabilitation is a necessary step in regaining lower body function after a partial paralysis caused by a spinal cord injury or a stroke. The purpose of this paper is to present the development and optimization of a training device that accurately recreates the motions in a gait cycle with the goal of rehabilitation for individuals with incomplete spinal cord injuries or who are victims of a stroke. A functional electrical stimulator was used in conjunction with the training device to stimulate muscle groups pertaining to rehabilitative walking. The feasibility and reliability of the design are presented. To validate the design functionality, motion analyses of the knee and ankle gait paths were made using motion capture systems. Key results indicate that the robotic walking training device provides a viable mode of physical rehabilitation.

Keywords: functional electrical stimulation, rehabilitative walking, robotic walking training device, spinal cord injuries

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Authors: Songul Cinaroglu

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Machine learning regression methods are recommended as an alternative to classical regression methods in the existence of variables which are difficult to model. Data for health expenditure is typically non-normal and have a heavily skewed distribution. This study aims to compare machine learning regression methods by hyperparameter tuning to predict health expenditure per capita. A multiple regression model was conducted and performance results of Lasso Regression, Random Forest Regression and Support Vector Machine Regression recorded when different hyperparameters are assigned. Lambda (λ) value for Lasso Regression, number of trees for Random Forest Regression, epsilon (ε) value for Support Vector Regression was determined as hyperparameters. Study results performed by using 'k' fold cross validation changed from 5 to 50, indicate the difference between machine learning regression results in terms of R², RMSE and MAE values that are statistically significant (p < 0.001). Study results reveal that Random Forest Regression (R² ˃ 0.7500, RMSE ≤ 0.6000 ve MAE ≤ 0.4000) outperforms other machine learning regression methods. It is highly advisable to use machine learning regression methods for modelling health expenditures.

Keywords: machine learning, lasso regression, random forest regression, support vector regression, hyperparameter tuning, health expenditure

Procedia PDF Downloads 188

Authors: Shima Mahmoudi, Setareh Mamishi, Babak Pourakbari, Majid Marjani

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In the last years, the potential role of distinct T-cell subsets as biomarkers of active tuberculosis TB and/or latent tuberculosis infection (LTBI) has been studied. The aim of this study was to investigate the potential role of interleukin-2 (IL-2) in whole blood stimulated with M. tuberculosis-specific antigens in the QuantiFERON-TB Gold In Tube (QFT-G-IT) for the discrimination of active and latent tuberculosis. After 72-h of stimulation by antigens from the QFT-G-IT assay, IL-2 secretion was quantitated in supernatants by using ELISA (Mabtech AB, Sweden). Observing the level of IL-2 released after 72-h of incubation, we found that the level of IL-2 were significantly higher in LTBI group than in patients with active TB infection or control group (P value=0.019, Kruskal–Wallis test). The discrimination performance (assessed by the area under ROC curve) between LTBI and patients with active TB was 0.816 (95%CI: 0.72-0.97). Maximum discrimination was reached at a cut-off of 13.9 pg/mL for IL-2 following stimulation with 82% sensitivity and 86% specificity. In conclusion, although cytokine analysis has greatly contributed to the understanding of TB pathogenesis, data on cytokine profiles that might distinguish progression from latency of TB infection are scarce and even controversial. Our data indicate that the concomitant evaluation of IFN- γ and IL-2 could be instrumental in discriminating of active and latent TB infection.

Keywords: interleukin-2, discrimination, active TB, latent TB

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Authors: G. C. Tikkiwal, Mukesh Upadhyay

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During the surveillance operations at war or peace time, the Radar operator gets a scatter of targets over the screen. This may be a tracked vehicle like tank vis-à-vis T72, BMP etc, or it may be a wheeled vehicle like ALS, TATRA, 2.5Tonne, Shaktiman or moving army, moving convoys etc. The Radar operator selects one of the promising targets into Single Target Tracking (STT) mode. Once the target is locked, the operator gets a typical audible signal into his headphones. With reference to the gained experience and training over the time, the operator then identifies the random target. But this process is cumbersome and is solely dependent on the skills of the operator, thus may lead to misclassification of the object. In this paper we present a technique using mathematical and statistical methods like Fast Fourier Transformation (FFT) and Principal Component Analysis (PCA) to identify the random objects. The process of classification is based on transforming the audible signature of target into music octave-notes. The whole methodology is then automated by developing suitable software. This automation increases the efficiency of identification of the random target by reducing the chances of misclassification. This whole study is based on live data.

Keywords: radar target, fft, principal component analysis, eigenvector, octave-notes, dsp

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Authors: Alhusein Almahjoub, Dongyu Qiu

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This paper deals with the random access procedure in next-generation networks and presents the solution to reduce total service time (TST) which is one of the most important performance metrics in current and future internet of things (IoT) based networks. The proposed solution focuses on the calculation of optimal transmission probability which maximizes the success probability and reduces TST. It uses the information of several idle preambles in every time slot, and based on it, it estimates the number of backlogged IoT devices using Naïve Bayes estimation which is a type of supervised learning in the machine learning domain. The estimation of backlogged devices is necessary since optimal transmission probability depends on it and the eNodeB does not have information about it. The simulations are carried out in MATLAB which verify that the proposed solution gives excellent performance.

Keywords: random access, LTE/LTE-A, 5G, machine learning, Naïve Bayes estimation

Procedia PDF Downloads 121

Authors: I-Han Hsiao, Chun-Ping Huang, Ching-Liang Hsieh, Yi-Wen Lin

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Epilepsy is chronic brain disorder that results in the sporadic occurrence of spontaneous seizures in the temporal lobe, cerebral cortex, and hippocampus. Clinical antiepileptic medicines are often ineffective or little benefits in the small amount of patients and usually initiate severe side effects. This inflammation contributes to enhanced neuronal excitability and the onset of epilepsy. Auricular electric-stimulation (AES) can increase parasympathetic activity and stimulate the solitary tract nucleus to induce the cholinergic anti-inflammatory pathway. Furthermore, it may be a therapeutic strategy for the treatment of epilepsy. In the present study, we want to investigate the effects of AES on inflammatory mediators in kainic acid (KA)-induced epileptic seizure rats. Experimental KA injection increased expression of TLR-2 pathway associated inflammatory mediators, were further reduced by either 2Hz or 15 Hz AES in the prefrontal cortex, hippocampus, and somatosensory cortex. We suggest that AES can successfully control the epileptic seizure by down-regulation of inflammation signaling pathway.

Keywords: auricular electric-stimulation, epileptic seizures, anti-inflammation

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Authors: Mohamed A. Eid, Sobhy M. Aly

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Background: About 75% of children with spastic hemiplegic cerebral palsy walk independently, but most still show abnormal gait patterns because of contractures across the joints and muscle spasticity. Objective: The purpose of this study was to investigate and compare the effects of extracorporeal shock wave therapy (ESWT) versus functional electrical stimulation (FES) on spasticity, function, and gait parameters in children with hemiplegic cerebral palsy (CP). Methods: A randomized controlled trail was conducted for 45 children with hemiplegic CP ranging in age from 6 to 9 years. They were assigned randomly using opaque envelopes into three groups. Physical Therapy (PT) group consisted of 15 children and received the conventional physical therapy program (CPTP) in addition to ankle foot orthosis (AFO). ESWT group consisted of 15 children and received the CPTP, AFO in addition to ESWT. FES group also consisted of 15 children and received the CPTP, AFO in addition to FES. All groups received the program of treatment 3 days/week for 12 weeks. Evaluation of spasticity by using the Modified Ashworth Scale (MAS), function by using the Pediatric Evaluation Disability Inventory (PEDI) and gait parameters by using the 3-D gait analysis was conducted at baseline and after 12 weeks of the treatment program. Results: Within groups, significant improvements in spasticity, function, and gait (P = 0.05) were observed in both ESWT and FES groups after treatment. While between groups, ESWT group showed significant improvements in all measured variables compared with FES and PT groups (P ˂ 0.05) after treatment. Conclusion: ESWT induced significant improvement than FES in decreasing spasticity and improving function and gait in children with hemiplegic CP. Therefore, ESWT should be included as an adjunctive therapy in the rehabilitation program of these children.

Keywords: cerebral palsy, extracorporeal shock wave therapy, functional electrical stimulation, function, gait, spasticity

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Authors: Guillaume Leduc

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In this paper, we describe a broad setting under which the error of the approximation can be quantified, controlled, and for which convergence occurs at a speed of n⁻¹ for European and American options. We describe how knowledge of the error allows for arbitrarily fast acceleration of the convergence.

Keywords: random walk approximation, European and American options, rate of convergence, option pricing

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Authors: Rodrigo Lentini, Beatrice Ionascu, Friederike A. Eyssel, Scandar Copti, Mohamad Eid

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The haptic modality has brought a new dimension to human computer interaction by engaging the human sense of touch. However, designing appropriate haptic stimuli, and in particular tactile stimuli, for various applications is still challenging. To tackle this issue, we present an intuitive system that facilitates the authoring of tactile gestures for various applications. The system transforms a hand gesture into a tactile gesture that can be rendering using a home-made haptic jacket. A case study is presented to demonstrate the ability of the system to develop tactile gestures that are recognizable by human subjects. Four tactile gestures are identified and tested to intensify the following four emotional responses: high valence – high arousal, high valence – low arousal, low valence – high arousal, and low valence – low arousal. A usability study with 20 participants demonstrated high correlation between the selected tactile gestures and the intended emotional reaction. Results from this study can be used in a wide spectrum of applications ranging from gaming to interpersonal communication and multimodal simulations.

Keywords: tactile stimulation, tactile gesture, emotion reactions, arousal, valence

Procedia PDF Downloads 342

Authors: Z. C. Dlamini, R. L. S. Langa, A. I. Okoh, O. A. Aiyegoro

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The indiscriminate usage of antibiotics in swine production have consequential outcomes; such as development of bacterial resistance to prophylactic antibiotics and possibility of antibiotic residues in animal products. The use of probiotics appears to be the most effective procedure with positive metabolic nutritional implications. The aim of this study was to investigate the efficacy of probiotic bacteria (Lactobacillus reuteri ZJ625, Lactobacillus reuteri VB4, Lactobacillus salivarius ZJ614 and Streptococcus salivarius NBRC13956) administered as direct-fed microorganisms in weaned piglets. 45 weaned piglets blocked by weight were dived into 5 treatments groups: diet with antibiotic, diet with no-antibiotic and no probiotic, and diet with probiotic and diet with combination of probiotics. Piglets performance was monitored during the trials. Faecal and Ileum samples were collected for microbial count analysis. Blood samples were collected from pigs at the end of the trial, for analysis of haematological, biochemical and IgG stimulation. The data was analysed by Split-Plot ANOVA using SAS statistically software (SAS 9.3) (2003). The difference was observed between treatments for daily weight and feed conversion ratio. No difference was observed in analysis of faecal samples in regards with bacterial counts, difference was observed in ileums samples with enteric bacteria colony forming unit being lower in P2 treatment group as compared with lactic acid and total bacteria. With exception of globulin and albumin, biochemistry blood parameters were not affected, likewise for haematology, only basophils and segmented neutrophils were differed by having higher concentration in NC treatment group as compared with other treatment groups. Moreover, in IgG stimulation analysis, difference was also observed, with P2 treatment group having high concentration of IgG in P2 treatment group as compared to other groups. The results of this study suggest that probiotics have a beneficial effect on growth performances, blood parameters and IgG stimulation of pigs, most effective when they are administered in synergy form. This means that it is most likely that these probiotics will offer a significant benefit in pig farming by reducing risk of morbidity and mortality and produce quality meat that is more affordable to poorer communities, and thereby enhance South African pig industry’s economy. In addition, these results indicate that there is still more research need to be done on probiotics in regards with, i.e. dosage, shelf life and mechanism of action.

Keywords: antibiotics, biochemistry, haematology, IgG-stimulation, microbial count, probiotics

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Authors: A. GuhaRay, C. V. S. P. Kiranmayi, S. Rudraraju

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The present study considers the effect of variation of different geotechnical random variables in the design of stone column-foundation systems for assessing the bearing capacity and consolidation settlement of highly compressible soil. The soil and stone column properties, spacing, diameter and arrangement of stone columns are considered as the random variables. Probability of failure (P_f) is computed for a target degree of consolidation and a target safe load by Monte Carlo Simulation (MCS). The study shows that the variation in coefficient of radial consolidation (c_r) and cohesion of soil (c_s) are two most important factors influencing Pf. If the coefficient of variation (COV) of c_r exceeds 20%, P_f exceeds 0.001, which is unsafe following the guidelines of US Army Corps of Engineers. The bearing capacity also exceeds its safe value for COV of c_s > 30%. It is also observed that as the spacing between the stone column increases, the probability of reaching a target degree of consolidation decreases. Accordingly, design guidelines, considering both consolidation and bearing capacity of improved ground, are proposed for different spacing and diameter of stone columns and geotechnical random variables.

Keywords: bearing capacity, consolidation, geotechnical random variables, probability of failure, stone columns

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Authors: A. Soni, D. R. Mishra, D. K. Koul

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α-Al2O3:C has been reported to have deeper traps at 600°C and 900°C respectively. These traps have been reported to accessed at relatively earlier temperatures (122 and 322 °C respectively) using thermally assisted OSL (TA-OSL). In this work, the dose response α-Al2O3:C was studied in the dose range of 10Gy to 10kGy for its application in food irradiation in low ( upto 1kGy) and medium(1 to 10kGy) dose range. The TOL (Thermo-optically stimulated luminescence) measurements were carried out on RisØ TL/OSL, TL-DA-15 system having a blue light-emitting diodes (λ=470 ±30nm) stimulation source with power level set at the 90% of the maximum stimulation intensity for the blue LEDs (40 mW/cm2). The observations were carried on commercial α-Al2O3:C phosphor. The TOL experiments were carried out with number of active channel (300) and inactive channel (1). Using these settings, the sample is subjected to linear thermal heating and constant optical stimulation. The detection filter used in all observations was a Hoya U-340 (Ip ~ 340 nm, FWHM ~ 80 nm). Irradiation of the samples was carried out using a 90Sr/90Y β-source housed in the system. A heating rate of 2 °C/s was preferred in TL measurements so as to reduce the temperature lag between the heater plate and the samples. To study the dose response of deep traps of α-Al2O3:C, samples were irradiated with various dose ranging from 10 Gy to 10 kGy. For each set of dose, three samples were irradiated. In order to record the TA-OSL, initially TL was recorded up to a temperature of 400°C, to deplete the signal due to 185°C main dosimetry TL peak in α-Al2O3:C, which is also associated with the basic OSL traps. After taking TL readout, the sample was subsequently subjected to TOL measurement. As a result, two well-defined TA-OSL peaks at 121°C and at 232°C occur in time as well as temperature domain which are different from the main dosimetric TL peak which occurs at ~ 185°C. The linearity of the integrated TOL signal has been measured as a function of absorbed dose and found to be linear upto 10kGy. Thus, it can be used for low and intermediate dose range of for its application in food irradiation. The deep energy level defects of α-Al2O3:C phosphor can be accessed using TOL section of RisØ reader system.

Keywords: α-Al2O3:C, deep traps, food irradiation, TA-OSL

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Authors: Mansour H. Alkmim, Adriano T. Fabro, Marcus V. G. De Morais

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In this paper, a global direct search optimization algorithm to reduce vibration of a tuned liquid column damper (TLCD), a class of passive structural control device, is presented. The objective is to find optimized parameters for the TLCD under stochastic load from different wind power spectral density. A verification is made considering the analytical solution of an undamped primary system under white noise excitation. Finally, a numerical example considering a simplified wind turbine model is given to illustrate the efficacy of the TLCD. Results from the random vibration analysis are shown for four types of random excitation wind model where the response PSDs obtained showed good vibration attenuation.

Keywords: generalized pattern search, parameter optimization, random vibration analysis, vibration suppression

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Authors: Mustapha Benssalah, Mustapha Djeddou, Karim Drouiche

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The random number generation (RNG) presents a significant importance for the security and the privacy of numerous applications, such as RFID technology and smart cards. Since, the quality of the generated bit sequences is paramount that a weak internal generator for example, can directly cause the entire application to be insecure, and thus it makes no sense to employ strong algorithms for the application. In this paper, we propose a new pseudo random number generator (PRNG), suitable for cryptosystems ECC-based, constructed by randomly selecting points from several elliptic curves randomly selected. The main contribution of this work is the increasing of the generator internal states by extending the set of its output realizations to several curves auto-selected. The quality and the statistical characteristics of the proposed PRNG are validated using the Chi-square goodness of fit test and the empirical Special Publication 800-22 statistical test suite issued by NIST.

Keywords: PRNG, security, cryptosystem, ECC

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Authors: Ali Nourollah, Mohsen Movahedinejad

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In this paper a new algorithm to generate random simple polygons from a given set of points in a two dimensional plane is designed. The proposed algorithm uses a genetic algorithm to generate polygons with few vertices. A new merge algorithm is presented which converts any two polygons into a simple polygon. This algorithm at first changes two polygons into a polygonal chain and then the polygonal chain is converted into a simple polygon. The process of converting a polygonal chain into a simple polygon is based on the removal of intersecting edges. The merge algorithm has the time complexity of O ((r+s) *l) where r and s are the size of merging polygons and l shows the number of intersecting edges removed from the polygonal chain. It will be shown that 1 < l < r+s. The experiments results show that the proposed algorithm has the ability to generate a great number of different simple polygons and has better performance in comparison to celebrated algorithms such as space partitioning and steady growth.

Keywords: Divide and conquer, genetic algorithm, merge polygons, Random simple polygon generation.

Procedia PDF Downloads 505

Authors: Yaping Zhao

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In the present study, the exact solutions for the steady response of quasi-linear systems under non-white wide-band random excitation are considered by means of the stochastic averaging method. The non linearity of the systems contains the power-law damping and the cross-product term of the power-law damping and displacement. The drift and diffusion coefficients of the Fokker-Planck-Kolmogorov (FPK) equation after averaging are obtained by a succinct approach. After solving the averaged FPK equation, the joint probability density function and the marginal probability density function in steady state are attained. In the process of resolving, the eigenvalue problem of ordinary differential equation is handled by integral equation method. Some new results are acquired and the novel method to deal with the problems in nonlinear random vibration is proposed.

Keywords: random vibration, stochastic averaging method, FPK equation, transition probability density

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Authors: Seon Soon Choi

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The essential purpose is to present the good fatigue crack propagation model describing a stochastic fatigue crack growth behavior in a rolled magnesium alloy, AZ31, under various load ratio conditions. Fatigue crack propagation experiments were carried out in laboratory air under four conditions of load ratio, R, using AZ31 to investigate the crack growth behavior. The stochastic fatigue crack growth behavior was analyzed using an interpolation of random variable, Z, introduced to an empirical fatigue crack propagation model. The empirical fatigue models used in this study are Paris-Erdogan model, Walker model, Forman model, and modified Forman model. It was found that the random variable is useful in describing the stochastic fatigue crack growth behaviors under various load ratio conditions. The good probabilistic model describing a stochastic fatigue crack growth behavior under various load ratio conditions was also proposed.

Keywords: magnesium alloys, fatigue crack propagation model, load ratio, interpolation of random variable

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Authors: Mohd Faridz Ahmad, Amirul Hakim Hasbullah

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Electrical Muscle Stimulation (EMS) has been introduced to the world in the 19th and 20th centuries and has globally gained increasing attention on its usefulness. EMS is known as the application of electrical current transcutaneous to muscles through electrodes to induce involuntary contractions that can lead to the increment of muscle mass and strength. This study can be used as an alternative to help people especially those living a sedentary lifestyle to improve their muscle activity without having to go through a heavy workout session. Therefore, this study intended to investigate the effectiveness of EMS training in 5 weeks interventions towards male body composition. It was a quasi-experimental design, held at the Impulse Studio Bangsar, which examined the effects of EMS training towards skeletal muscle mass among the subjects. Fifteen subjects (n = 15) were selected to assist in this study. The demographic data showed that, the average age of the subjects was 43.07 years old ± 9.90, height (173.4 cm ± 9.09) and weight was (85.79 kg ± 18.07). Results showed that there was a significant difference on the skeletal muscle mass (p = 0.01 < 0.05), upper body (p = 0.01 < 0.05) and lower body (p = 0.00 < 0.05). Therefore, the null hypothesis has been rejected in this study. As a conclusion, the application of EMS towards body composition can increase the muscle size and strength. This method has been proven to be able to improve athlete strength and thus, may be implemented in the sports science area of knowledge.

Keywords: body composition, EMS, skeletal muscle mass, strength

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Authors: Aid Abdelkrim

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A method of fatigue damage accumulation based upon application of energy parameters of the fatigue process is proposed in the paper. Using this model is simple, it has no parameter to be determined, it requires only the knowledge of the curve W–N (W: strain energy density N: number of cycles at failure) determined from the experimental Wöhler curve. To examine the performance of nonlinear models proposed in the estimation of fatigue damage and fatigue life of components under random loading, a batch of specimens made of 6082 T 6 aluminium alloy has been studied and some of the results are reported in the present paper. The paper describes an algorithm and suggests a fatigue cumulative damage model, especially when random loading is considered. This work contains the results of uni-axial random load fatigue tests with different mean and amplitude values performed on 6082T6 aluminium alloy specimens. The proposed model has been formulated to take into account the damage evolution at different load levels and it allows the effect of the loading sequence to be included by means of a recurrence formula derived for multilevel loading, considering complex load sequences. It is concluded that a ‘damaged stress interaction damage rule’ proposed here allows a better fatigue damage prediction than the widely used Palmgren–Miner rule, and a formula derived in random fatigue could be used to predict the fatigue damage and fatigue lifetime very easily. The results obtained by the model are compared with the experimental results and those calculated by the most fatigue damage model used in fatigue (Miner’s model). The comparison shows that the proposed model, presents a good estimation of the experimental results. Moreover, the error is minimized in comparison to the Miner’s model.

Keywords: damage accumulation, energy model, damage indicator, variable loading, random loading

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Authors: Tarana Siddika, Ilka U. Heinemann, Patrick O’Donoghue

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Protein kinase B (AKT1) is a serine/threonine kinase and central transducer of cell survival pathways. Typical approaches to study AKT1 biology in cells rely on growth factor or insulin stimulation that activates AKT1 via phosphorylation at two key regulatory sites (Threonine308, Serine473), yet cell stimulation also activates many other kinases and fails to differentiate the effect of the two main activating sites of AKT1 on downstream substrate phosphorylation and cell growth. While both AKT1 activating sites are associated with disease and used as clinical markers, in some cancers, high levels of Threonine308 phosphorylation are associated with poor prognosis while in others poor survival correlates with high Serine473 levels. To produce cells with specific AKT1 activity, a system was developed to deliver active AKT1 to human cells. AKT1 phospho-variants were produced from Escherichia coli with programmed phosphorylation by genetic code expansion. Tagging of AKT1 with an N-terminal cell penetrating peptide tag derived from the human immunodeficiency virus trans-activator of transcription (TAT) helped to enter AKT1 proteins in mammalian cells. The TAT-tag did not alter AKT1 kinase activity and was necessary and sufficient to rapidly deliver AKT1 protein variants that persisted in human cells for 24 h without the need to use transfection reagents. TAT-pAKT1T308, TAT-pAKT1S473 and TAT-pAKT1T308S473 proteins induced selective phosphorylation of the known AKT1 substrate GSK-3αβ, and downstream stimulation of the AKT1 pathway as evidenced by phosphorylation of ribosomal protein S6 at Serine240/244 in transfected cells. Increase in cell growth and proliferation was observed due to the transfection of different phosphorylated AKT1 protein variants compared to cells with TAT-AKT1 protein. The data demonstrate efficient delivery of AKT1 with programmed phosphorylation to human cells, thus establishing a cell-based model system to investigate signaling that is dependent on specific AKT1 activity and phosphorylation.

Keywords: cell penetrating peptide, cell signaling, protein kinase b (AKT1), phosphorylation

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Authors: Elizabeth Stojanovski

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Associations between life events and various forms of cancers have been identified. The purpose of a recent random-effects meta-analysis was to identify studies that examined the association between adverse events associated with changes to financial status including decreased income and breast cancer risk. The same association was studied in four separate studies which displayed traits that were not consistent between studies such as the study design, location and time frame. It was of interest to pool information from various studies to help identify characteristics that differentiated study results. Two random-effects Bayesian meta-analysis models are proposed to combine the reported estimates of the described studies. The proposed models allow major sources of variation to be taken into account, including study level characteristics, between study variance, and within study variance and illustrate the ease with which uncertainty can be incorporated using a hierarchical Bayesian modelling approach.

Keywords: random-effects, meta-analysis, Bayesian, variation

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Authors: R. Sudhesh Solomon, P. Y. K. L. Srinivas, Abhay Narayan, Amitava Das

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Users in social networks either unicast or broadcast their messages. At mention is the popular way of unicasting for Twitter whereas general tweeting could be considered as broadcasting method. Understanding the information flow and dynamics within a Social Network and modeling the same is a promising and an open research area called Information Diffusion. This paper seeks an answer to a fundamental question - understanding if the at-mention network or the unicasting pattern in social media is purely random in nature or is there any user specific selectional preference? To answer the question we present an empirical analysis to understand the sociological aspects of Twitter mentions network within a social network community. To understand the sociological behavior we analyze the values (Schwartz model: Achievement, Benevolence, Conformity, Hedonism, Power, Security, Self-Direction, Stimulation, Traditional and Universalism) of all the users. Empirical results suggest that values traits are indeed salient cue to understand how the mention-based communication network functions. For example, we notice that individuals possessing similar values unicast among themselves more often than with other value type people. We also observe that traditional and self-directed people do not maintain very close relationship in the network with the people of different values traits.

Keywords: information diffusion, personality and values, social network analysis, twitter mentions network

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Authors: Dua Hişam, Serhat İkizoğlu

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Identifying the problem behind balance disorder is one of the most interesting topics in the medical literature. This study has considerably enhanced the development of artificial intelligence (AI) algorithms applying multiple machine learning (ML) models to sensory data on gait collected from humans to classify between normal people and those suffering from Vestibular System (VS) problems. Although AI is widely utilized as a diagnostic tool in medicine, AI models have not been used to perform feature extraction and identify VS disorders through training on raw data. In this study, three machine learning (ML) models, the Random Forest Classifier (RF), Extreme Gradient Boosting (XGB), and K-Nearest Neighbor (KNN), have been trained to detect VS disorder, and the performance comparison of the algorithms has been made using accuracy, recall, precision, and f1-score. With an accuracy of 95.28 %, Random Forest Classifier (RF) was the most accurate model.

Keywords: vestibular disorder, machine learning, random forest classifier, k-nearest neighbor, extreme gradient boosting

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Authors: Lara Ann Türeli, Özlem Bozkurt

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There is a biochemical component to listening to music. The type of music listened to can lead to different levels of neurotransmitter and biochemical activity within the brain, resulting in brain stimulation and different moods. Therefore, music plays an important role in neuromarketing and consumer behavior. The quality of a commercial can be measured by the effect the music has on its audience. Thus, understanding how music can affect the brain can provide better marketing strategies for all businesses. The type of music used plays an important role in how a person responds to certain experiences. In the context of marketing and consumer behavior, music can determine whether a person will be intrigued to buy something. Depending on the type of music listened to by an individual; the music may trigger the release of pleasurable neurotransmitters such as dopamine. Dopamine is a neurotransmitter that plays an important role in reward pathways in the brain. When an individual experiences a pleasurable activity, increased levels of dopamine are produced, eventually leading to the formation of new reward pathways. Consequently, the increased dopamine activity within the brain triggered by music can result in new reward pathways along the dopamine pathways in the brain. Selecting pleasurable music for commercials can result in long-term brain stimulation, increasing consumerism. The effect of music on consumerism should be considered not only in commercials but also in the atmosphere it creates within stores. The type of music played in a store can affect consumer behavior and intention. Specifically, the rhythm, pitch, and pace of music can contribute to the mood of the song. The background music in a store can determine the consumer’s emotional presence and consequently affect their intentions. In conclusion, understanding the physiological, psychological, and neurochemical basis of the effect of music on brain stimulation is essential to understand consumer behavior. The role of dopamine in the formation of reward pathways as a result of music directly contributes to consumer behavior and the tendency of a commercial or store to leave a long-term effect on the consumer. The careful consideration of the pitch, pace, and rhythm of a song in the selection of music can not only help companies predict the behavior of a consumer but also determine the behavior of a consumer.

Keywords: sensory processing, neuropsychology, dopamine, neuromarketing

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Authors: Carlos Gonzales, Zaida Quiroz, Marcos Prates

Abstract:

Several spatial variables collected at the same location that share a common spatial distribution can be modeled simultaneously through a multivariate geostatistical model that takes into account the correlation between these variables and the spatial autocorrelation. The main goal of this model is to perform spatial prediction of these variables in the region of study. Here we focus on a geostatistical multivariate formulation that relies on sharing common spatial random effect terms. In particular, the first response variable can be modeled by a mean that incorporates a shared random spatial effect, while the other response variables depend on this shared spatial term, in addition to specific random spatial effects. Each spatial random effect is defined through a Gaussian process with a valid covariance function, but in order to improve the computational efficiency when the data are large, each Gaussian process is approximated to a Gaussian random Markov field (GRMF), specifically to the block nearest neighbor Gaussian process (Block-NNGP). This approach involves dividing the spatial domain into several dependent blocks under certain constraints, where the cross blocks allow capturing the spatial dependence on a large scale, while each individual block captures the spatial dependence on a smaller scale. The multivariate geostatistical model belongs to the class of Latent Gaussian Models; thus, to achieve fast Bayesian inference, it is used the integrated nested Laplace approximation (INLA) method. The good performance of the proposed model is shown through simulations and applications for massive data.

Keywords: Block-NNGP, geostatistics, gaussian process, GRMF, INLA, multivariate models.

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Authors: Reni M. Sagayaraj, Anand Gnana S. Selvam, Reynald R. Susainathan

Abstract:

In this paper, we consider stochastic queueing models for Steady-state behavior of a multi-phase M/M/1 queue in random evolution subject to catastrophe failure. The arrival flow of customers is described by a marked Markovian arrival process. The service times of different type customers have a phase-type distribution with different parameters. To facilitate the investigation of the system we use a generalized phase-type service time distribution. This model contains a repair state, when a catastrophe occurs the system is transferred to the failure state. The paper focuses on the steady-state equation, and observes that, the steady-state behavior of the underlying queueing model along with the average queue size is analyzed.

Keywords: M/G/1 queuing system, multi-phase, random evolution, steady-state equation, catastrophe failure

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Authors: Yung-Shan Lu, Chia-Fone Lee, Shang-Hsuan Li, Chien-Hao Liu

Abstract:

Recently, various bioelectronic devices have been developed for neurologic disease treatments via electro-stimulations such as cochlear implants and retinal prosthesis. Since the electric signal needs electrodes to be transmitted to an organism, electrodes play an important role of stimulations. The materials of stimulation electrodes affect the efficiency of the delivered currents. The higher the efficiency of the electrodes, the lower the threshold current can be used to stimulate the organism which minimizes the potential damages to the adjacent tissues. In this study, we proposed a biocompatible composite electrode composed of high-charge-capacity iridium oxide (IrOₓ) film for a bone-guide extra-cochlear implant. IrOₓ was exploited to decrease the threshold current due to its high capacitance and low impedance. The IrOₓ electrode was fabricated via microelectromechanical systems (MEMS) photolithography and examined with in-vivo tests with guinea pigs. Based on the measured responses of brain waves to sound, the results demonstrated that IrOₓ electrodes have a lower threshold current compared with the Platinum (Pt) electrodes. The research results are expected to be beneficial for implantable and biocompatible electrodes for electrical stimulations.

Keywords: cochlear implants, electrode, electrical stimulation, iridium oxide

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Authors: Bayan Almofty, Yuto Yamaki, Tadamasa Terai, Sadahito Uto

Abstract:

Myopathy (muscles disease) treatment are expected in the field of regenerative medicine and applied research of cultured muscle to bio actuator is performed in Biomedical Engineering as applied research of cultured muscle. This study is about cultured myoblast C2C12 from mouse skeletal muscle and a mechanism of cultured muscle contraction by electric stimulation is investigated. Grayanotoxins (GTXs) belong to neurotoxins known to enhance the permeability of cell membrane for Na ions. Grayanotoxins are extracted from a famous Pieris japonica and Ericaceae as a phytotoxin. We investigated the functional role of GTXs on muscle cells (C2C12) contraction and membrane potential. A change in membrane potential is measured using a micro glass tube electrode contraction of myotubes is induced by applying an external electrical stimulation. The contraction and membrane potential change induced by injection of current using the micro glass electrode are also measured. From the result, contraction and membrane potential of muscle cells was affected by GTXs treatment, suggesting that the diverse chemical structures of GTXs are responsible for contraction and membrane potential of muscle cells.

Keywords: skeletal muscle, C2C12, myoblast, myotubes, contraction, Grayanotoxins, membrane potential, neurotoxins, phytotoxin

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Authors: Anthony Cogrove, Shagun Saikia, Pradeep Deshpande

Abstract:

Introduction: Management of anxiety in rehabilitation setting often is a challenge and is usually done by using medication. The role of psychology and the creation of a quite environment in order to reduce stimulation helps in the process. We have a hypothesis that feedback from a calm visual imagery with soothing music help in reducing anxiety in these setting Aim-To explore the possibility of using virtual reality in the management of anxiety in a setting of neuro-rehabilitation unit. Method: Six patients in an inpatient rehabilitation unit with acquired brain injury subjected to a low stimulation calming visual motion picture with calm music. Six sessions were conducted over 6 weeks. All sessions were performed in a separate purpose built room in the unit. . A cohort of 6 people with various neurological conditions were involved in 6 sessions of 30 minutes during their inpatient rehabilitation. They reported benefit from using the virtual reality environment in reducing their anxiety. Results: All reported improvement in their anxiety levels. They felt there was a calming effect of the session. There was a sense of feeling of self empowerment on direct questioning. Conclusion: Virtual reality environment can aid the traditional rehabilitation techniques used to manage the levels of anxiety experienced by people with acquired brain injury undergoing inpatient rehabilitation.

Keywords: neurological rehabilitation, virtual reality, anxiety, calming environment

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