Search results for: voltage gradient

Authors: Belgherbi Aicha, Hadjidj Ismahen, Bessaid Abdelhafid

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The phase of segmentation is an important step in the processing and interpretation of medical images. In this paper, we focus on the segmentation of liver and spleen from the abdomen computed tomography (CT) images. The importance of our study comes from the fact that the segmentation of ROI from CT images is usually a difficult task. This difficulty is the gray’s level of which is similar to the other organ also the ROI are connected to the ribs, heart, kidneys, etc. Our proposed method is based on the anatomical information and mathematical morphology tools used in the image processing field. At first, we try to remove the surrounding and connected organs and tissues by applying morphological filters. This first step makes the extraction of interest regions easier. The second step consists of improving the quality of the image gradient. In this step, we propose a method for improving the image gradient to reduce these deficiencies by applying the spatial filters followed by the morphological filters. Thereafter we proceed to the segmentation of the liver, spleen. To validate the segmentation technique proposed, we have tested it on several images. Our segmentation approach is evaluated by comparing our results with the manual segmentation performed by an expert. The experimental results are described in the last part of this work.The system has been evaluated by computing the sensitivity and specificity between the semi-automatically segmented (liver and spleen) contour and the manually contour traced by radiological experts.

Keywords: CT images, liver and spleen segmentation, anisotropic diffusion filter, morphological filters, watershed algorithm

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Authors: Vedansh More, Lalatendu Bal, Ronak Panchal, Atharva Kulkarni

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The project aims at developing a cost-effective test bench capable of testing and validating the complete powertrain package of an electric vehicle. Emrax 228 high voltage synchronous motor was selected as the prime mover for study. A tandem type dynamometer comprising of two loading methods; inertial, using standard inertia rollers and absorptive, using a separately excited DC generator with resistive coils was developed. The absorptive loading of the prime mover was achieved by implementing a converter circuit through which duty of the input field voltage level was controlled. This control was efficacious in changing the magnetic flux and hence the generated voltage which was ultimately dropped across resistive coils assembled in a load bank with all parallel configuration. The prime mover and loading elements were connected via a chain drive with a 2:1 reduction ratio which allows flexibility in placement of components and a relaxed rating of the DC generator. The development will aid in determination of essential characteristics like torque-RPM, power-RPM, torque factor, RPM factor, heat loads of devices and battery pack state of charge efficiency but also provides a significant financial advantage over existing versions of dynamometers with its cost-effective solution.

Keywords: absorptive load, chain drive, chordal action, DC generator, dynamometer, electric vehicle, inertia rollers, load bank, powertrain, pulse width modulation, reduction ratio, road load, testbench

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Authors: Wei Zha, Jingzeng Zhang, Chen Zhao, Ran Cai, Xueyuan Nie

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Cathodic plasma electrolysis (CPE) is used to create surface textures on cast iron samples for improving the tribological properties. Micro craters with confined size distribution were successfully formed by CPE process. These craters can generate extra hydrodynamic pressure that separates two sliding surfaces, increase the oil film thickness and accelerate the transition from boundary to mixed lubrication. It was found that the optimal crater size was 1.7 μm, at which the maximum lubrication efficiency was achieved. The Taguchi method was used to optimize the process parameters (voltage and roughness) for CPE surface texturing. The orthogonal array and the signal-to-noise ratio were employed to study the effect of each process parameter on the coefficient of friction. The results showed that with higher voltage and lower roughness, the lower friction coefficient can be obtained, and thus the lubrication can be more efficiently used for friction reduction.

Keywords: cathodic plasma electrolysis, friction, lubrication, plasma surface texturing

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Authors: O. Ojeda Mena, Y. Cressault, P. Teulet, J. P. Gonnet, D. F. N. Santos, MD. Cunha, M. S. Benilov

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The assumption of plasma in local thermal equilibrium (LTE) is commonly used to perform electric arc simulations for industrial applications. This assumption allows to model the arc using a set of magneto-hydromagnetic equations that can be solved with a computational fluid dynamic code. However, the LTE description is only valid in the arc column, whereas in the regions close to the electrodes the plasma deviates from the LTE state. The importance of these near-electrode regions is non-trivial since they define the energy and current transfer between the arc and the electrodes. Therefore, any accurate modelling of the arc must include a good description of the arc-electrode phenomena. Due to the modelling complexity and computational cost of solving the near-electrode layers, a simplified description of the arc-electrode interaction was developed in a previous work to study a steady high-pressure arc discharge, where the near-electrode regions are introduced at the interface between arc and electrode as boundary conditions. The present work proposes a similar approach to simulate the arc ignition in a free-burning arc configuration following an LTE description of the plasma. To obtain the transient evolution of the arc characteristics, appropriate boundary conditions for both the near-cathode and the near-anode regions are used based on recent publications. The arc-cathode interaction is modeled using a non-linear surface heating approach considering the secondary electron emission. On the other hand, the interaction between the arc and the anode is taken into account by means of the heating voltage approach. From the numerical modelling, three main stages can be identified during the arc ignition. Initially, a glow discharge is observed, where the cold non-thermionic cathode is uniformly heated at its surface and the near-cathode voltage drop is in the order of a few hundred volts. Next, a spot with high temperature is formed at the cathode tip followed by a sudden decrease of the near-cathode voltage drop, marking the glow-to-arc discharge transition. During this stage, the LTE plasma also presents an important increase of the temperature in the region adjacent to the hot spot. Finally, the near-cathode voltage drop stabilizes at a few volts and both the electrode and plasma temperatures reach the steady solution. The results after some seconds are similar to those presented for thermionic cathodes.

Keywords: arc-electrode interaction, thermal plasmas, electric arc simulation, cold electrodes

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Authors: Andrea Pietrelli, Vincenzo Ferrara, Bruno Allard, Francois Buret, Irene Bavasso, Nicola Lovecchio, Francesca Costantini, Firas Khaled

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This paper aims to show some applications of microbial fuel cells (MFCs), an energy harvesting technique, as clean power source to supply low power device for application like wireless sensor network (WSN) for environmental monitoring. Furthermore, MFC can be used directly as biosensor to analyse parameters like pH and temperature or arranged in form of cluster devices in order to use as small power plant. An MFC is a bioreactor that converts energy stored in chemical bonds of organic matter into electrical energy, through a series of reactions catalysed by microorganisms. We have developed a lab-scale terrestrial microbial fuel cell (TMFC), based on soil that acts as source of bacteria and flow of nutrient and a lab-scale waste water microbial fuel cell (WWMFC), where waste water acts as flow of nutrient and bacteria. We performed large series of tests to exploit the capability as biosensor. The pH value has strong influence on the open circuit voltage (OCV) delivered from TMFCs. We analyzed three condition: test A and B were filled with same soil but changing pH from 6 to 6.63, test C was prepared using a different soil with a pH value of 6.3. Experimental results clearly show how with higher pH value a higher OCV was produced; indeed reactors are influenced by different values of pH which increases the voltage in case of a higher pH value until the best pH value of 7 is achieved. The influence of pH on OCV of lab-scales WWMFC was analyzed at pH value of 6.5, 7, 7.2, 7.5 and 8. WWMFCs are influenced from temperature more than TMFCs. We tested the power performance of WWMFCs considering four imposed values of ambient temperature. Results show how power performance increase proportionally with higher temperature values, doubling the output power from 20° to 40°. The best value of power produced from our lab-scale TMFC was equal to 310 μW using peaty soil, at 1KΩ, corresponding to a current of 0.5 mA. A TMFC can supply proper energy to low power devices of a WSN by means of the design of three stages scheme of an energy management system, which adapts voltage level of TMFC to those required by a WSN node, as 3.3V. Using a commercial DC/DC boost converter, that needs an input voltage of 700 mV, the current source of 0.5 mA, charges a capacitor of 6.8 mF until it will have accumulated an amount of charge equal to 700 mV in a time of 10 s. The output stage includes an output switch that close the circuit after a time of 10s + 1.5ms because the converter can boost the voltage from 0.7V to 3.3V in 1.5 ms. Furthermore, we tested in form of clusters connected in series up to 20 WWMFCs, we have obtained a high voltage value as output, around 10V, but low current value. MFC can be considered a suitable clean energy source to be used to supply low power devices as a WSN node or to be used directly as biosensor.

Keywords: energy harvesting, low power electronics, microbial fuel cell, terrestrial microbial fuel cell, waste-water microbial fuel cell, wireless sensor network

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Authors: Abdelrahman Zkria, Tsuyoshi Yoshitake

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Diamond is one of the most interesting semiconducting carbon materials owing to its unique physical and chemical properties, yet its application in electronic devices is limited due to the difficulty of realizing n-type conduction by nitrogen doping. In contrast Ultrananocrystalline diamond with diamond grains of about 3–5 nm in diameter have attracted much attention for device-oriented applications because they may enable the realization of n-type doping with nitrogen. In this study, nitrogen-doped Ultra-Nanocrystalline diamond films were prepared by coaxial arc plasma deposition (CAPD) method, the nitrogen content was estimated by X-ray photoemission spectroscopy (XPS). The electrical conductivity increased with increasing nitrogen contents. Heterojunction diodes with p-type Si were fabricated and evaluated based on current–voltage (I–V) and capacitance–voltage (C–V) characteristics measured in dark at room temperature.

Keywords: heterojunction diodes, hopping conduction mechanism, nitrogen-doping, ultra-nanocrystalline diamond

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Authors: L. Raczynski, P. Moskal, P. Kowalski, W. Wislicki, T. Bednarski, P. Bialas, E. Czerwinski, A. Gajos, L. Kaplon, A. Kochanowski, G. Korcyl, J. Kowal, T. Kozik, W. Krzemien, E. Kubicz, Sz. Niedzwiecki, M. Palka, Z. Rudy, O. Rundel, P. Salabura, N.G. Sharma, M. Silarski, A. Slomski, J. Smyrski, A. Strzelecki, A. Wieczorek, M. Zielinski, N. Zon

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The J-PET scanner, which allows for single bed imaging of the whole human body, is currently under development at the Jagiellonian University. The J-PET detector improves the TOF resolution due to the use of fast plastic scintillators. Since registration of the waveform of signals with duration times of few nanoseconds is not feasible, a novel front-end electronics allowing for sampling in a voltage domain at four thresholds was developed. To take fully advantage of these fast signals a novel scheme of recovery of the waveform of the signal, based on ideas from the Tikhonov regularization (TR) and Compressive Sensing methods, is presented. The prior distribution of sparse representation is evaluated based on the linear transformation of the training set of waveform of the signals by using the Principal Component Analysis (PCA) decomposition. Beside the advantage of including the additional information from training signals, a further benefit of the TR approach is that the problem of signal recovery has an optimal solution which can be determined explicitly. Moreover, from the Bayes theory the properties of regularized solution, especially its covariance matrix, may be easily derived. This step is crucial to introduce and prove the formula for calculations of the signal recovery error. It has been proven that an average recovery error is approximately inversely proportional to the number of samples at voltage levels. The method is tested using signals registered by means of the single detection module of the J-PET detector built out from the 30 cm long BC-420 plastic scintillator strip. It is demonstrated that the experimental and theoretical functions describing the recovery errors in the J-PET scenario are largely consistent. The specificity and limitations of the signal recovery method in this application are discussed. It is shown that the PCA basis offers high level of information compression and an accurate recovery with just eight samples, from four voltage levels, for each signal waveform. Moreover, it is demonstrated that using the recovered waveform of the signals, instead of samples at four voltage levels alone, improves the spatial resolution of the hit position reconstruction. The experiment shows that spatial resolution evaluated based on information from four voltage levels, without a recovery of the waveform of the signal, is equal to 1.05 cm. After the application of an information from four voltage levels to the recovery of the signal waveform, the spatial resolution is improved to 0.94 cm. Moreover, the obtained result is only slightly worse than the one evaluated using the original raw-signal. The spatial resolution calculated under these conditions is equal to 0.93 cm. It is very important information since, limiting the number of threshold levels in the electronic devices to four, leads to significant reduction of the overall cost of the scanner. The developed recovery scheme is general and may be incorporated in any other investigation where a prior knowledge about the signals of interest may be utilized.

Keywords: plastic scintillators, positron emission tomography, statistical analysis, tikhonov regularization

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Authors: Ajay Kumar, Neha Gupta

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This work presents the sensitivity assessment of Gallium Nitride (GaN) material-based FinFET by dielectric modulation in the nanocavity gap for label-free biosensing applications. The significant deflection is observed in the electrical characteristics such as drain current (ID), transconductance (gm), surface potential, energy band profile, electric field, sub-threshold slope (SS), and threshold voltage (Vth) in the presence of biomolecules owing to GaN material. Further, the device sensitivity is evaluated to identify the effectiveness of the proposed biosensor and its capability to detect the biomolecules with high precision or accuracy. Higher sensitivity is observed for Gelatin (k=12) in terms of on-current (SION), threshold voltage (SVth), and switching ratio (SSR) by 104.88%, 82.12%, and 119.73%, respectively. This work is performed using a powerful tool 3D Sentaurus TCAD using a well-calibrated structure. All the results pave the way for GaN-FinFET as a viable candidate for label-free dielectric modulated biosensor applications.

Keywords: biosensor, biomolecules, FinFET, sensitivity

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Authors: Lifar M. S., Tereshchenko A. A., Bulgakov A. N., Guda S. A., Guda A. A., Soldatov A. V.

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Metal nanoparticles are widely used as heterogeneous catalysts to activate adsorbed molecules and reduce the energy barrier of the reaction. Reaction product yield depends on the interplay between elementary processes - adsorption, activation, reaction, and desorption. These processes, in turn, depend on the inlet feed concentrations, temperature, and pressure. At stationary conditions, the active surface sites may be poisoned by reaction byproducts or blocked by thermodynamically adsorbed gaseous reagents. Thus, the yield of reaction products can significantly drop. On the contrary, the dynamic control accounts for the changes in the surface properties and adjusts reaction parameters accordingly. Therefore dynamic control may be more efficient than stationary control. In this work, a reinforcement learning algorithm has been applied to control the simulation of CO oxidation on a catalyst. The policy gradient algorithm is learned to maximize the CO₂ production rate based on the CO and O₂ flows at a given time step. Nonstationary solutions were found for the regime with surface deactivation. The maximal product yield was achieved for periodic variations of the gas flows, ensuring a balance between available adsorption sites and the concentration of activated intermediates. This methodology opens a perspective for the optimization of catalytic reactions under nonstationary conditions.

Keywords: artificial intelligence, catalyst, co oxidation, reinforcement learning, dynamic control

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Authors: Yifan Gao

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Owing to the high breakdown field, high saturation drift velocity, 2DEG with high density and mobility and so on, AlGaN/GaN HEMTs have been widely used in high-frequency and high-power applications. To acquire a higher power often means higher breakdown voltage and higher drain current. Surface leakage current is usually the key issue affecting the breakdown voltage and power performance. In this work, we have performed in-situ N₂/NH₃ pretreatment before the passivation to suppress the surface leakage and achieve device performance enhancement. The AlGaN/GaN HEMT used in this work was grown on a 3-in. SiC substrate, whose epitaxial structure consists of a 3.5-nm GaN cap layer, a 25-nm Al₀.₂₅GaN barrier layer, a 1-nm AlN layer, a 400-nm i-GaN layer and a buffer layer. In order to analyze the mechanism for the N-based pretreatment, the details are measured by XPS analysis. It is found that the intensity of Ga-O bonds is decreasing and the intensity of Ga-N bonds is increasing, which means with the supplement of N, the dangling bonds on the surface are indeed reduced with the forming of Ga-N bonds, reducing the surface states. The surface states have a great influence on the leakage current, and improved surface states represent a better off-state of the device. After the N-based pretreatment, the breakdown voltage of the device with Lₛ𝒹=6 μm increased from 93V to 170V, which increased by 82.8%. Moreover, for HEMTs with Lₛ𝒹 of 6-μm, we can obtain a peak output power (Pout) of 12.79W/mm, power added efficiency (PAE) of 49.84% and a linear gain of 20.2 dB at 60V under 3.6GHz. Comparing the result with the reference 6-μm device, Pout is increased by 16.5%. Meanwhile, PAE and the linear gain also have a slight increase. The experimental results indicate that using N₂/NH₃ pretreatment before passivation is an attractive approach to achieving power performance enhancement.

Keywords: AlGaN/GaN HEMT, N-based pretreatment, output power, passivation

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Authors: Bo-Bin Xiaoa, Chia-Yi Liua

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In the task of searching for anomalous radiation sources, personnel holding radiation detectors to search for radiation sources may be exposed to unnecessary radiation risk, and automated search using machines becomes a required project. The research uses various sophisticated algorithms, which are double Q learning, dueling network, and NoisyNet, of deep reinforcement learning to search for radiation sources. The simulation environment, which is a 10*10 grid and one shielding wall setting in it, improves the development of the AI model by training 1 million episodes. In each episode of training, the radiation source position, the radiation source intensity, agent position, shielding wall position, and shielding wall length are all set randomly. The three algorithms are applied to run AI model training in four environments where the training shielding wall is a full-shielding wall, a lead wall, a concrete wall, and a lead wall or a concrete wall appearing randomly. The 12 best performance AI models are selected by observing the reward value during the training period and are evaluated by comparing these AI models with the gradient search algorithm. The results show that the performance of the AI model, no matter which one algorithm, is far better than the gradient search algorithm. In addition, the simulation environment becomes more complex, the AI model which applied Double DQN combined Dueling and NosiyNet algorithm performs better.

Keywords: double Q learning, dueling network, NoisyNet, source searching

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Authors: Rahil Bahrami, Kaveh Ashenayi

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This paper presents a systematic classification and comparative analysis of non-isolated bi-directional DC-DC converters. The increasing demand for efficient energy conversion in diverse applications has spurred the development of various converter topologies. In this study, we categorize bi-directional converters into three distinct classes: Inverting, Non-Inverting, and Interleaved. Each category is characterized by its unique operational characteristics and benefits. Furthermore, a practical comparison is conducted by evaluating the results of simulation of each bi-directional converter. BDCs can be classified into isolated and non-isolated topologies. Non-isolated converters share a common ground between input and output, making them suitable for applications with minimal voltage change. They are easy to integrate, lightweight, and cost-effective but have limitations like limited voltage gain, switching losses, and no protection against high voltages. Isolated converters use transformers to separate input and output, offering safety benefits, high voltage gain, and noise reduction. They are larger and more costly but are essential for automotive designs where safety is crucial. The paper focuses on non-isolated systems.The paper discusses the classification of non-isolated bidirectional converters based on several criteria. Common factors used for classification include topology, voltage conversion, control strategy, power capacity, voltage range, and application. These factors serve as a foundation for categorizing converters, although the specific scheme might vary depending on contextual, application, or system-specific requirements. The paper presents a three-category classification for non-isolated bi-directional DC-DC converters: inverting, non-inverting, and interleaved. In the inverting category, converters produce an output voltage with reversed polarity compared to the input voltage, achieved through specific circuit configurations and control strategies. This is valuable in applications such as motor control and grid-tied solar systems. The non-inverting category consists of converters maintaining the same voltage polarity, useful in scenarios like battery equalization. Lastly, the interleaved category employs parallel converter stages to enhance power delivery and reduce current ripple. This classification framework enhances comprehension and analysis of non-isolated bi-directional DC-DC converters. The findings contribute to a deeper understanding of the trade-offs and merits associated with different converter types. As a result, this work aids researchers, practitioners, and engineers in selecting appropriate bi-directional converter solutions for specific energy conversion requirements. The proposed classification framework and experimental assessment collectively enhance the comprehension of non-isolated bi-directional DC-DC converters, fostering advancements in efficient power management and utilization.The simulation process involves the utilization of PSIM to model and simulate non-isolated bi-directional converter from both inverted and non-inverted category. The aim is to conduct a comprehensive comparative analysis of these converters, considering key performance indicators such as rise time, efficiency, ripple factor, and maximum error. This systematic evaluation provides valuable insights into the dynamic response, energy efficiency, output stability, and overall precision of the converters. The results of this comparison facilitate informed decision-making and potential optimizations, ensuring that the chosen converter configuration aligns effectively with the designated operational criteria and performance goals.

Keywords: bi-directional, DC-DC converter, non-isolated, energy conversion

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Authors: Kumlachew Zelalem Walle, Chun-Chen Yang

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Solid-state Lithium metal batteries (SSLMBs) that contain polymer and ceramic solid electrolytes have received considerable attention as an alternative to substitute liquid electrolytes in lithium metal batteries (LMBs) for highly safe, excellent energy storage performance and stability under elevated temperature situations. Here, a novel fast Li-ion conducting material, LiTa₂PO₈ (LTPO), was synthesized and electrochemical performance of as-prepared powder and LTPO-incorporated composite solid polymer electrolyte (LTPO-CPE) membrane were investigated. The as-prepared LTPO powder was homogeneously dispersed in polymer matrices, and a hybrid solid electrolyte membrane was synthesized via a simple solution-casting method. The room temperature total ionic conductivity (σt) of the LTPO pellet and LTPO-CPE membrane were 0.14 and 0.57 mS cm-1, respectively. A coin battery with NCM811 cathode is cycled under 1C between 2.8 to 4.5 V at room temperature, achieving a Coulombic efficiency of 99.3% with capacity retention of 74.1% after 300 cycles. Similarly, the LFP cathode also delivered an excellent performance at 0.5C with an average Coulombic efficiency of 100% without virtually capacity loss (the maximum specific capacity is at 27th: 138 mAh g−1 and 500th: 131.3 mAh g−1). These results demonstrates the feasibility of a high Li-ion conductor LTPO as a filler, and the developed polymer/ceramic hybrid electrolyte has potential to be a high-performance electrolyte for high-voltage cathodes, which may provide a fresh platform for developing more advanced solid-state electrolytes.

Keywords: li-ion conductor, lithium-metal batteries, composite solid electrolytes, liTa2PO8, high-voltage cathode

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Authors: Syed M. Rizvi, Yiqing Meng, Simon Iwnicki

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With an increased demand in the land cargo industry, it is predicted that the freight trade will rise to a record $1.1 trillion in revenue and volume in the following years to come. This increase is mainly driven by the e-commerce model ever so popular in the consumer market. Many innovative ideas have stemmed from this demand and change in lifestyle likes of which include e-bike cargo and drones. Rural and urban areas are facing air quality challenges to keep pollution levels in city centre to a minimum. For this purpose, this paper presents the design and implementation of a non-linear PID control system, employing a micro-controller and low cost sensing technique, for controlling an electrical motor based cargo vehicle with various loads, to follow a leading vehicle (bike). Within using this system, the cargo vehicle will have no load influence on the bike rider on different gradient conditions, such as hill climbing. The system is being integrated with a microcontroller to continuously measure several parameters such as relative displacement between bike and the cargo vehicle and gradient of the road, and process these measurements to create a portable controller capable of controlling the performance of electrical vehicle without the need of a PC. As a result, in the case of carrying 180kg of parcel weight, the cargo vehicle can maintain a reasonable spacing over a short length of sensor travel between the bike and itself.

Keywords: cargo, e-bike, microcontroller, embedded system, nonlinear pid, self-adaptive, inertial measurement unit (IMU)

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Authors: Muhtasim Shafi Kader, Fizar Ahmed, Annesha Acharjee

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Machine learning and data mining are crucial in health care, as well as medical information and detection. Machine learning approaches are now being utilized to improve awareness of a variety of critical health issues, including diabetes detection, neuron cell tumor diagnosis, COVID 19 identification, and so on. Parkinson’s disease is basically a disease for our senior citizens in Bangladesh. Parkinson's Disease indications often seem progressive and get worst with time. People got affected trouble walking and communicating with the condition advances. Patients can also have psychological and social vagaries, nap problems, hopelessness, reminiscence loss, and weariness. Parkinson's disease can happen in both men and women. Though men are affected by the illness at a proportion that is around partial of them are women. In this research, we have to get out the accurate ML algorithm to find out the disease with a predictable dataset and the model of the following machine learning classifiers. Therefore, nine ML classifiers are secondhand to portion study to use machine learning approaches like as follows, Naive Bayes, Adaptive Boosting, Bagging Classifier, Decision Tree Classifier, Random Forest classifier, XBG Classifier, K Nearest Neighbor Classifier, Support Vector Machine Classifier, and Gradient Boosting Classifier are used.

Keywords: naive bayes, adaptive boosting, bagging classifier, decision tree classifier, random forest classifier, XBG classifier, k nearest neighbor classifier, support vector classifier, gradient boosting classifier

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Authors: Morné Roman, Robert van Zyl, Nishanth Parus, Nishal Mahatho

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Leakage current monitoring for high voltage transmission line insulators is of interest as a performance indicator. Presently, to the best of our knowledge, there is no commercially available, clamp-on type, non-intrusive device for measuring leakage current on energised high voltage direct current (HVDC) transmission line insulators. The South African power utility, Eskom, is investigating the development of such a hand-held sensor for two important applications; first, for continuous real-time condition monitoring of HVDC line insulators and, second, for use by live line workers to determine if it is safe to work on energised insulators. In this paper, a DC leakage current sensor based on magnetic field sensing techniques is developed. The magnetic field sensor used in the prototype can also detect alternating current up to 5 MHz. The DC leakage current prototype detects the magnetic field associated with the current flowing on the surface of the insulator. Preliminary HVDC leakage current measurements are performed on glass insulators. The results show that the prototype can accurately measure leakage current in the specified current range of 1-200 mA. The influence of external fields from the HVDC line itself on the leakage current measurements is mitigated through a differential magnetometer sensing technique. Thus, the developed sensor can perform measurements on in-service HVDC insulators. The research contributes to the body of knowledge by providing a sensor to measure leakage current on energised HVDC insulators non-intrusively. This sensor can also be used by live line workers to inform them whether or not it is safe to perform maintenance on energized insulators.

Keywords: direct current, insulator, leakage current, live line, magnetic field, sensor, transmission lines

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Authors: Md. Aminul Islam, Adel Merabet, Rachid Beguenane, Hussein Ibrahim

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This paper presents a simulation and mathematical model of stand-alone solar-wind-diesel based hybrid energy system (HES). A power management system is designed for multiple energy resources in a stand-alone hybrid energy system. Both Solar photovoltaic and wind energy conversion system consists of maximum power point tracking (MPPT), voltage regulation, and basic power electronic interfaces. An additional diesel generator is included to support and improve the reliability of stand-alone system when renewable energy sources are not available. A power management strategy is introduced to distribute the generated power among resistive load banks. The frequency regulation is developed with conventional phase locked loop (PLL) system. The power management algorithm was applied in Matlab®/Simulink® to simulate the results.

Keywords: solar photovoltaic, wind energy, diesel engine, hybrid energy system, power management, frequency and voltage regulation

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Authors: Nkwachukwu Chukwuchekwa, Joy Ulumma Chukwuchekwa

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Magnetic characteristics of grain-oriented electrical steel (GOES) are usually measured at high flux densities suitable for its typical applications in power transformers. There are limited magnetic data at low flux densities which are relevant for the characterization of GOES for applications in metering instrument transformers and low frequency magnetic shielding in magnetic resonance imaging medical scanners. Magnetic properties such as coercivity, B-H loop, AC relative permeability and specific power loss of conventional grain oriented (CGO) and high permeability grain oriented (HGO) electrical steels were measured and compared at high and low flux densities at power magnetising frequency. 40 strips comprising 20 CGO and 20 HGO, 305 mm x 30 mm x 0.27 mm from a supplier were tested. The HGO and CGO strips had average grain sizes of 9 mm and 4 mm respectively. Each strip was singly magnetised under sinusoidal peak flux density from 8.0 mT to 1.5 T at a magnetising frequency of 50 Hz. The novel single sheet tester comprises a personal computer in which LabVIEW version 8.5 from National Instruments (NI) was installed, a NI 4461 data acquisition (DAQ) card, an impedance matching transformer, to match the 600  minimum load impedance of the DAQ card with the 5 to 20  low impedance of the magnetising circuit, and a 4.7 Ω shunt resistor. A double vertical yoke made of GOES which is 290 mm long and 32 mm wide is used. A 500-turn secondary winding, about 80 mm in length, was wound around a plastic former, 270 mm x 40 mm, housing the sample, while a 100-turn primary winding, covering the entire length of the plastic former was wound over the secondary winding. A standard Epstein strip to be tested is placed between the yokes. The magnetising voltage was generated by the LabVIEW program through a voltage output from the DAQ card. The voltage drop across the shunt resistor and the secondary voltage were acquired by the card for calculation of magnetic field strength and flux density respectively. A feedback control system implemented in LabVIEW was used to control the flux density and to make the induced secondary voltage waveforms sinusoidal to have repeatable and comparable measurements. The low noise NI4461 card with 24 bit resolution and a sampling rate of 204.8 KHz and 92 KHz bandwidth were chosen to take the measurements to minimize the influence of thermal noise. In order to reduce environmental noise, the yokes, sample and search coil carrier were placed in a noise shielding chamber. HGO was found to have better magnetic properties at both high and low magnetisation regimes. This is because of the higher grain size of HGO and higher grain-grain misorientation of CGO. HGO is better CGO in both low and high magnetic field applications.

Keywords: flux density, electrical steel, LabVIEW, magnetization

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Authors: Mohammed E. A. Brixi Nigassa, Nassima Labdelli, Ahmed Slami, Arnaud Pothier, Sofiane Soulimane

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According to the world health organization (WHO), there are almost 285 million people with visual disability, 39 million of these people are blind. Nevertheless, there is a code for these people that make their life easier and allow them to access information more easily; this code is the Braille code. There are several commercial devices allowing braille reading, unfortunately, most of these devices are not ergonomic and too expensive. Moreover, we know that 90 % of blind people in the world live in low-incomes countries. Our contribution aim is to concept an original microactuator for Braille reading, as well as being ergonomic, inexpensive and lowest possible energy consumption. Nowadays, the piezoelectric device gives the better actuation for low actuation voltage. In this study, we focus on piezoelectric (PZT) material which can bring together all these conditions. Here, we propose to use one matrix composed by six actuators to form the 63 basic combinations of the Braille code that contain letters, numbers, and special characters in compliance with the standards of the braille code. In this work, we use a finite element model with Comsol Multiphysics software for designing and modeling this type of miniature actuator in order to integrate it into a test device. To define the geometry and the design of our actuator, we used physiological limits of perception of human being. Our results demonstrate in our study that piezoelectric actuator could bring a large deflection out-of-plain. Also, we show that microactuators can exhibit non uniform compression. This deformation depends on thin film thickness and the design of membrane arm. The actuator composed of four arms gives the higher deflexion and it always gives a domed deformation at the center of the deviceas in case of the Braille system. The maximal deflection can be estimated around ten micron per Volt (~ 10µm/V). We noticed that the deflection according to the voltage is a linear function, and this deflection not depends only on the voltage the voltage, but also depends on the thickness of the film used and the design of the anchoring arm. Then, we were able to simulate the behavior of the entire matrix and thus display different characters in Braille code. We used these simulations results to achieve our demonstrator. This demonstrator is composed of a layer of PDMS on which we put our piezoelectric material, and then added another layer of PDMS to isolate our actuator. In this contribution, we compare our results to optimize the final demonstrator.

Keywords: Braille code, comsol software, microactuators, piezoelectric

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Authors: Jonathan Sohn

Abstract:

Deep neural networks (DNNs) have shown state-of-the-art performance for many applications, including computer vision, natural language processing, and speech recognition. Recently, adversarial attacks have been studied in the context of deep neural networks, which aim to alter the results of deep neural networks by modifying the inputs slightly. For example, an adversarial attack on a DNN used for object detection can cause the DNN to miss certain objects. As a result, the reliability of DNNs is undermined by their lack of robustness against adversarial attacks, raising concerns about their use in safety-critical applications such as autonomous driving. In this paper, we focus on studying the adversarial attacks and defenses on DNNs for image classification. There are two types of adversarial attacks studied which are fast gradient sign method (FGSM) attack and projected gradient descent (PGD) attack. A DNN forms decision boundaries that separate the input images into different categories. The adversarial attack slightly alters the image to move over the decision boundary, causing the DNN to misclassify the image. FGSM attack obtains the gradient with respect to the image and updates the image once based on the gradients to cross the decision boundary. PGD attack, instead of taking one big step, repeatedly modifies the input image with multiple small steps. There is also another type of attack called the target attack. This adversarial attack is designed to make the machine classify an image to a class chosen by the attacker. We can defend against adversarial attacks by incorporating adversarial examples in training. Specifically, instead of training the neural network with clean examples, we can explicitly let the neural network learn from the adversarial examples. In our experiments, the digit recognition accuracy on the MNIST dataset drops from 97.81% to 39.50% and 34.01% when the DNN is attacked by FGSM and PGD attacks, respectively. If we utilize FGSM training as a defense method, the classification accuracy greatly improves from 39.50% to 92.31% for FGSM attacks and from 34.01% to 75.63% for PGD attacks. To further improve the classification accuracy under adversarial attacks, we can also use a stronger PGD training method. PGD training improves the accuracy by 2.7% under FGSM attacks and 18.4% under PGD attacks over FGSM training. It is worth mentioning that both FGSM and PGD training do not affect the accuracy of clean images. In summary, we find that PGD attacks can greatly degrade the performance of DNNs, and PGD training is a very effective way to defend against such attacks. PGD attacks and defence are overall significantly more effective than FGSM methods.

Keywords: deep neural network, adversarial attack, adversarial defense, adversarial machine learning

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Authors: Syed Masood Hussain

Abstract:

An effective control method, including system-level control and pulse width modulation for quasi-Z-source cascade multilevel inverter (qZS-CMI) based grid-tie photovoltaic (PV) power system is proposed. The system-level control achieves the grid-tie current injection, independent maximum power point tracking (MPPT) for separate PV panels, and dc-link voltage balance for all quasi-Z-source H-bridge inverter (qZS-HBI) modules. A recent upsurge in the study of photovoltaic (PV) power generation emerges, since they directly convert the solar radiation into electric power without hampering the environment. However, the stochastic fluctuation of solar power is inconsistent with the desired stable power injected to the grid, owing to variations of solar irradiation and temperature. To fully exploit the solar energy, extracting the PV panels’ maximum power and feeding them into grids at unity power factor become the most important. The contributions have been made by the cascade multilevel inverter (CMI). Nevertheless, the H-bridge inverter (HBI) module lacks boost function so that the inverter KVA rating requirement has to be increased twice with a PV voltage range of 1:2; and the different PV panel output voltages result in imbalanced dc-link voltages. However, each HBI module is a two-stage inverter, and many extra dc–dc converters not only increase the complexity of the power circuit and control and the system cost, but also decrease the efficiency. Recently, the Z-source/quasi-Z-source cascade multilevel inverter (ZS/qZS-CMI)-based PV systems were proposed. They possess the advantages of both traditional CMI and Z-source topologies. In order to properly operate the ZS/qZS-CMI, the power injection, independent control of dc-link voltages, and the pulse width modulation (PWM) are necessary. The main contributions of this paper include: 1) a novel multilevel space vector modulation (SVM) technique for the single phase qZS-CMI is proposed, which is implemented without additional resources; 2) a grid-connected control for the qZS-CMI based PV system is proposed, where the all PV panel voltage references from their independent MPPTs are used to control the grid-tie current; the dual-loop dc-link peak voltage control.

Keywords: Quzi-Z source inverter, Photo voltaic power system, space vector modulation, cascade multilevel inverter

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Authors: T. D. Ibragimov, A. R. Imamaliyev, G. M. Bayramov

Abstract:

Influence of barium titanate particles on electro-optic properties of liquid crystal 4-cyano-4′-pentylbiphenyl (5CB) with positive dielectric anisotropy and the liquid crystalline (LC) mixture Н-37 consisting of 4-methoxybezylidene-4'–butylaniline and 4-ethoxybezylidene-4'–butylaniline with negative dielectric anisotropy was investigated. It was shown that a presence of particles inside 5СВ and H-37 decreased the clearing temperature from 35.2 °С to 32.5°С and from 61.2 oC to 60.1oC, correspondingly. The threshold voltage of the Fredericksz effect became 0.3 V for the BaTiO3-5CB colloid while the beginning of this effect of the pure 5СВ was observed at 2.1 V. Threshold voltage of the Fredericksz effect increased from 2.8 V to up 3.1 V at additive of particles into H-37. A rise time of the BaTiO3-5CB colloid improved while a decay time worsened in comparison with the pure 5CB at all applied voltages. The inverse trends were observed for the H-37 matrix, namely, a rise time worsened and a decay time improved. Among other things, the effect of fast light modulation was studied at application of the rectangular impulse with direct bias to an electro-optical cell with the BaTiO3 particles+5CB and the pure 5CB. At this case, a rise time of the composite worsened, a decay time improved in comparison with the pure 5CB. The pecularities of electrohydrodynamic instability (EHDI) formation was also investigated into the composite with the H-37 matrix. It was found that the voltage of the EHDI formation decreased, a rise time increased and a decay time decreased in comparison with the pure H-37. First of all, experimental results are explained by appearance of local electric fields near the polarized ferroelectric particles at application of external electric field and an existence of the additional obstacles (particles) for movement of ions.

Keywords: liquid crystal, ferroelectric particles, composite, electro-optics

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Authors: Orose Rugchati, Kanita Thanacharoenchanaphas, Sarawut Wattanawongpitak

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In this study, the effect of electric stimulation on the quality of hot-boned beef brisket muscles was evaluated, including the tenderness, pH, temperature change, and colorant. Muscles were obtained from steers in the local slaughter house. (3 steers for each muscle), removed from the carcasses 4-hour postmortem and variable time to treated with direct current electric 1 and 5 minutes, respectively. Six different electric intensities (direct current voltage of 50, 70 and 90 Volt, pulse with 10, 20 and 40 ms) plus a control were applied to each muscle to determine the optimum treatment conditions. Hot-boned beef brisket was found to get tender with increasing treatment direct current voltage and reduction in the shear force with pulsed with electric treatment. But in a long time to treated with electric current get fading in red color and temperature increase whereas pH quite different compared to non-treated control samples.

Keywords: electric stimulation, characteristic changes, hot-boned beef brisket, potential tenderness

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Authors: M. Suresh Kumar, K. Ramani

Abstract:

This paper proposed the harmonic elimination of Cascaded H-Bridge Multi-Level Inverter by using Selective Harmonic Elimination-Pulse Width Modulation method programmed with Particle Swarm Optimization algorithm. PSO method determine proficiently the required switching angles to eliminate low order harmonics up to the 11th order from the inverter output voltage waveform while keeping the magnitude of the fundamental harmonics at the desired value. Results demonstrate that the proposed method does efficiently eliminate a great number of specific harmonics and the output voltage is resulted in minimum Total Harmonic Distortion. The results shown that the PSO algorithm attain successfully to the global solution faster than other algorithms.

Keywords: multi-level inverter, Selective Harmonic Elimination Pulse Width Modulation (SHEPWM), Particle Swarm Optimization (PSO), Total Harmonic Distortion (THD)

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Authors: Belgherbi Aicha, Hadjidj Ismahen, Bessaid Abdelhafid

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Interpretation of medical images benefits from anatomical and physiological priors to optimize computer-aided diagnosis applications. Segmentation of liver, spleen and kidneys is regarded as a major primary step in the computer-aided diagnosis of abdominal organ diseases. In this paper, a semi-automated method for medical image data is presented for the abdominal organ segmentation data using mathematical morphology. Our proposed method is based on hierarchical segmentation and watershed algorithm. In our approach, a powerful technique has been designed to suppress over-segmentation based on mosaic image and on the computation of the watershed transform. Our algorithm is currency in two parts. In the first, we seek to improve the quality of the gradient-mosaic image. In this step, we propose a method for improving the gradient-mosaic image by applying the anisotropic diffusion filter followed by the morphological filters. Thereafter, we proceed to the hierarchical segmentation of the liver, spleen and kidney. To validate the segmentation technique proposed, we have tested it on several images. Our segmentation approach is evaluated by comparing our results with the manual segmentation performed by an expert. The experimental results are described in the last part of this work.

Keywords: anisotropic diffusion filter, CT images, morphological filter, mosaic image, simultaneous organ segmentation, the watershed algorithm

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Authors: M. Almutairi, S. Hadjiloucas

Abstract:

The harmonic distortion of voltage is important in relation to power quality due to the interaction between the large diffusion of non-linear and time-varying single-phase and three-phase loads with power supply systems. However, harmonic distortion levels can be reduced by improving the design of polluting loads or by applying arrangements and adding filters. The application of passive filters is an effective solution that can be used to achieve harmonic mitigation mainly because filters offer high efficiency, simplicity, and are economical. Additionally, possible different frequency response characteristics can work to achieve certain required harmonic filtering targets. With these ideas in mind, the objective of this paper is to determine what size single tuned passive filters work in distribution networks best, in order to economically limit violations caused at a given point of common coupling (PCC). This article suggests that a single tuned passive filter could be employed in typical industrial power systems. Furthermore, constrained optimization can be used to find the optimal sizing of the passive filter in order to reduce both harmonic voltage and harmonic currents in the power system to an acceptable level, and, thus, improve the load power factor. The optimization technique works to minimize voltage total harmonic distortions (VTHD) and current total harmonic distortions (ITHD), where maintaining a given power factor at a specified range is desired. According to the IEEE Standard 519, both indices are viewed as constraints for the optimal passive filter design problem. The performance of this technique will be discussed using numerical examples taken from previous publications.

Keywords: harmonics, passive filter, power factor, power quality

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Authors: Amir Mahdavi

Abstract:

In this paper, a circuit topology of voltage-controlled oscillators (VCO) which is suitable for ultra-low-phase noise operations is introduced. To do so, a new low phase noise cross-coupled oscillator by using the general topology of cross-coupled oscillator and adding a differential stage for tail current shaping is designed. In addition, a tail current shaping technique to improve phase noise in differential LC VCOs is presented. The tail current becomes large when the oscillator output voltage arrives at the maximum or minimum value and when the sensitivity of the output phase to the noise is the smallest. Also, the tail current becomes small when the phase noise sensitivity is large. The proposed circuit does not use extra power and extra noisy active devices. Furthermore, this topology occupies small area. Simulation results show the improvement in phase noise by 2.5dB under the same conditions and at the carrier frequency of 1 GHz for GSM applications. The power consumption of the proposed circuit is 2.44 mW and the figure of merit (FOM) with -192.2 dBc/Hz is achieved for the new oscillator.

Keywords: LC oscillator, low phase noise, current shaping, diff mode

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Authors: M. Nageswara Rao, V. S. N. K. Chaitanya, K. Amarendranath

Abstract:

This paper presents an optimal allocation and sizing of Distributed Generation (DG) in Radial Distribution Network (RDN) for total power loss minimization and enhances the voltage profile of the system. The two main important part of this study first is to find optimal allocation and second is optimum size of DG. The locations of DGs are identified by Analytical expressions and crow search algorithm has been employed to determine the optimum size of DG. In this study, the DG has been placed on single and multiple allocations.CSA is a meta-heuristic algorithm inspired by the intelligent behavior of the crows. Crows stores their excess food in different locations and memorizes those locations to retrieve it when it is needed. They follow each other to do thievery to obtain better food source. This analysis is tested on IEEE 33 bus and IEEE 69 bus under MATLAB environment and the results are compared with existing methods.

Keywords: analytical expression, distributed generation, crow search algorithm, power loss, voltage profile

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Authors: Jasvinder Singh, Manjinder Singh

Abstract:

Welding of dissimilar materials is a complicated process due to the difference in melting point of two materials. Thermal conductivity and coefficient of thermal expansion of dissimilar materials also different; therefore, residual stresses produced in the weldment and base metal are the most critical problem associated with the joining of dissimilar materials. Tensile strength and impact toughness also reduced due to the residual stresses. In the present research work, an attempt has been made to weld SS304 and MS1018 dissimilar materials by submerged arc welding (SAW). By conducting trail, runs most effective parameters welding current, Arc voltage, welding speed and nozzle to plate distance were selected to weld these materials. The fractional factorial technique was used to optimize the welding parameters. Effect on tensile strength (TS), fracture toughness (FT) and microhardness of weldment were studied. It was concluded that by optimizing welding current, voltage and welding speed the properties of weldment can be enhanced.

Keywords: SAW, Tensile Strength (TS), fracture toughness, micro hardness

Procedia PDF Downloads 535

Authors: Lina T. Al Kury, Oleg I. Voitychuk, Ramiz M. Ali, Sehamuddin Galadari, Keun-Hang Susan Yang, Frank Christopher Howarth, Yaroslav M. Shuba, Murat Oz

Abstract:

A role for anandamide (N-arachidonoyl ethanolamide; AEA), a major endocannabinoid, in the cardiovascular system in various pathological conditions has been reported in earlier studies. In the present work, we have hypothesized that the antiarrhythmic effects reported for AEA are due to its negative inotropic effect and altered action potential (AP) characteristics. Therefore, we tested the effects of AEA on contractility and electrophysiological properties of rat ventricular myocytes. Video edge detection was used to measure myocyte shortening. Intracellular Ca2+ was measured in cells loaded with the fluorescent indicator fura-2 AM. Whole-cell patch-clamp technique was employed to investigate the effect of AEA on the characteristics of APs. AEA (1 μM) caused a significant decrease in the amplitudes of electrically-evoked myocyte shortening and Ca2+ transients and significantly decreased the duration of AP. The effect of AEA on myocyte shortening and AP characteristics was not altered in the presence of pertussis toxin (PTX, 2 µg/ml for 4 h), AM251 and SR141716 (cannabinoid type 1 receptor antagonists) or AM630 and SR 144528 (cannabinoid type 2 receptor antagonists). Furthermore, AEA inhibited voltage-activated inward Na+ (INa) and Ca2+ (IL,Ca) currents; major ionic currents shaping the APs in ventricular myocytes, in a voltage and PTX-independent manner. Collectively, the results suggest that AEA depresses ventricular myocyte contractility, by decreasing the action potential duration (APD), and inhibits the function of voltage-dependent Na+ and L-type Ca2+ channels in a manner independent of cannabinoid receptors. This mechanism may be importantly involved in the antiarrhythmic effects of anandamide.

Keywords: action potential, anandamide, cannabinoid receptor, endocannabinoid, ventricular myocytes

Procedia PDF Downloads 350