Search results for: activation function

Authors: Zilin Zhang

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Agent-based simulation has become a popular method of exploring the behavior of all kinds of urban systems. The city clearly is viewed as such a system. Many urban evolution processes, such as the development or the transaction of a piece of land, can be modeled with a set of rules. Such modeling approaches can be used to gain insight into urban-development and land market transactions in the real world. Our work contributes to such type of research by modeling the transactions of lands in a city and its surrounding suburbs. By replicating the demand and supply needs in the land market, we are able to demonstrate the different transaction patterns in three types of residential areas - downtown, city-suburban, and further suburban areas. In addition, we are also able to compare the vital roles of different activation conditions play in generating the various transaction patterns of the land market at the macro level. We use this simulation to loosely test our hypotheses about the nature of activation regimes by the replication of the Zi traders’ model. In the end, we hope our analytical results can be useful for city planners and policymakers to develop rational city plans and policies for shaping sustainable urban development.

Keywords: simulation, agent-based modeling, housing market, city

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Authors: Soheil Zorofchian Moghadamtousi, Habsah Abdul Kadir, Mohammadjavad Paydar, Elham Rouhollahi, Hamed Karimian

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The present study was designed to evaluate the molecular mechanisms of Annona muricata leaves ethyl acetate extract (AMEAE) against lung cancer A549 cells. Cell viability analysis revealed the selective cytotoxic effect of AMEAE towards A549 cells. Treatment of A549 cells with AMEAE significantly elevated the reactive oxygen species formation, followed by attenuation of mitochondrial membrane potential via upregulation of Bax and downregulation of Bcl-2, accompanied by cytochrome c release to the cytosol. The released cytochrome c triggered the activation of caspase-9 followed by caspase-3. In addition, AMEAE-induced apoptosis was accompanied by cell cycle arrest at G1 phase. Our data showed for the first time that AMEAE inhibited the proliferation of A549 cells, leading to cell cycle arrest and programmed cell death through activation of the mitochondrial-mediated signaling pathway.

Keywords: Annona muricata, lung cancer, apoptosis, mitochondria

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Authors: A. N. Gornostaeva, P. I. Bobyleva, E. R. Andreeva, L. B. Buravkova

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Multipotent mesenchymal stromal cells (MSCs) possess immunomodulatory properties. The effect of MSCs on the crucial cellular immunity compartment – T-cells is of a special interest. It is known that MSC tissue niche and expected milieu of their interaction with T- cells are characterized by low oxygen concentration, whereas the in vitro experiments usually are carried out at a much higher ambient oxygen (20%). We firstly evaluated immunomodulatory effects of MSCs on T-cells at tissue-related oxygen (5%) after interaction implied cell-to-cell contacts and paracrine factors only. It turned out that MSCs under reduced oxygen can effectively suppress the activation and proliferation of PHA-stimulated T-cells and can provoke decrease in the production of proinflammatory and increase in anti-inflammatory cytokines. In hypoxia some effects were amplified (inhibition of proliferation, anti-inflammatory cytokine profile shift). This impact was more evident after direct cell-to-cell interaction; lack of intercellular contacts could revoke the potentiating effect of hypoxia.

Keywords: MSCs, T-cells, activation, low oxygen, cell-to-cell interaction, immunosuppression

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Authors: Helan Satish, M. Ramasubba Reddy

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The simulation of an endocardial cell for gene mutation in the cardiac sodium ion channel NaV1.5, encoded by SCN5A gene, is discussed. The characterization of Brugada Syndrome by loss of function effect on SCN5A mutation due to L812Q mutant present in the DII-S4 transmembrane region of the NaV1.5 channel protein and its effect in an endocardial cell is studied. Ten Tusscher model of human ventricular action potential is modified to incorporate the changes contributed by L812Q mutant in the endocardial cells. Results show that BrS-associated SCN5A mutation causes reduction in the inward sodium current by modifications in the channel gating dynamics such as delayed activation, enhanced inactivation, and slowed recovery from inactivation in the endocardial cell. A decrease in the inward sodium current was also observed, which affects depolarization phase (Phase 0) that leads to reduction in the spike amplitude of the cardiac action potential.

Keywords: SCN5A gene mutation, sodium channel, Brugada syndrome, cardiac arrhythmia, action potential

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Authors: S. B. Provost, Hossein Zareamoghaddam

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A univariate density approximation technique whereby the derivative of the logarithm of a density function is assumed to be expressible as a rational function is introduced. This approach which extends Pearson’s curve system is solely based on the moments of a distribution up to a determinable order. Upon solving a system of linear equations, the coefficients of the polynomial ratio can readily be identified. An explicit solution to the integral representation of the resulting density approximant is then obtained. It will be explained that when utilised in conjunction with sample moments, this methodology lends itself to the modelling of ‘big data’. Applications to sets of univariate and bivariate observations will be presented.

Keywords: density estimation, log-density, moments, Pearson's curve system

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Authors: Miroslava Hujová, Patricia Rabello Monich, Jozef Kraxner, Dusan Galusek, Enrico Bernardo

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Inorganic waste upcycling offers a solution how to avoid landfilling and how to save raw materials at the same time. However, its practical implementations in Slovakia and elsewhere in Europe, are rather limited despite the potential smaller countries like Slovakia have their advantage in closely-knitted inorganic materials industry. One part of discussion should include an overview of wastes that can be possibly used for upcycling, i.e. fly ashes, red mud, glass cullets, vitrified bottom ashes etc. These wastes can be processed by a variety of strategies, the one of our choice, alkali activation, opens the possibility for the formation of novel materials at almost negligible energetic expense. In the research, these materials are characterized by comprehensive means (X-Ray Fluorescece, Diffraction methods, Thermal Analysis, Scanning Electron Microscopy, Mechanical tests and Chemical stability), which time and time again demonstrate their competitive properties against traditional materials available at the market. It is just a question for discussion why these materials do not receive more significant attention from industry and there is pressing interest for the solution of standing situation.

Keywords: upcycling, inorganic wastes, glass ceramics, alkali-activation

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Authors: M. Abd elfattah, M. Ossman, Nahla A. Taha

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The present work explored the use of Egyptian rice straw, an agricultural waste that leads to global warming problem through brown cloud, as a potential feedstock for the preparation of activated carbon by physical and chemical activation. The results of this study showed that it is feasible to prepare activated carbons with relatively high surface areas and pore volumes from the Egyptian rice straw by direct chemical and physical activation. The produced activated carbon from the two methods (AC1 and AC2) could be used as potential adsorbent for the removal of Fe(III) from aqueous solution contains heavy metals and polluted water. The adsorption of Fe(III) was depended on the pH of the solution. The optimal Fe(III) removal efficiency occurs at pH 5. Based on the results, the optimum contact time is 60 minutes and adsorbent dosage is 3 g/L. The adsorption breakthrough curves obtained at different bed depths indicated increase of breakthrough time with increase in bed depths. A rise in inlet Fe(III) concentration reduces the throughput volume before the packed bed gets saturated. AC1 showed higher affinity for Fe(III) as compared to Raw rice husk.

Keywords: rice straw, activated carbon, Fe(III), fixed bed column, pyrolysis

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Authors: Miroslava Zelinkova, Marcela Ondova

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Fly ash (FA) thanks to the significant presence of SiO2 and Al2O3 as the main components is a potential raw material for geopolymers production. Mechanical activation is a method for improving FA reactivity and also the porosity of final mixture; those parameters can be analysed through sorption properties. They have direct impact on the durability of fly ash based geopolymer mortars. In the paper, effect of FA fineness on sorption properties of geopolymers based on sodium silicate, as well as relationship between fly ash fineness and apparent density, compressive and flexural strength of geopolymers are presented. The best results in the evaluated area reached the sample H1, which contents the highest portion of particle under 20μm (100% of GFA). The interdependence of individual tested properties was confirmed for geopolymer mixtures corresponding to those in the cement based mixtures: higher is portion of fine particles < 20μm, higher is strength, density and lower are sorption properties. The compressive strength as well as sorption parameters of the geopolymer can be reasonably controlled by grinding process and also ensured by the higher share of fine particle (to 20μm) in total mass of the material.

Keywords: alkali activation, geopolymers, fly ash, particle fineness

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Authors: Mizam Doğan

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In service life; structures can be damaged if they are subjected to dead and live loads which are greater than design values. For preventing this case; possible loads must be correctly calculated, structure must be designed according to determined loads, and structure must not be used out of its function. If loading case of the structure changes when its function changes; it must be reinforced for continuing it is new function. Reinforcement is a process that is made by increasing the existing strengths of structural system elements of the structure as reinforced concrete walls, beams, and slabs. Reinforcement can be done by casting reinforced concrete, placing steel and fiber structural elements. In this paper, reinforcing of columns and slabs of a structure of which function is changed is studied step by step. This reinforcement is made for increasing vertical and lateral load carrying capacity of the building. Not for repairing damaged structural system.

Keywords: strengthening, RC slabs, seismic load, steel beam, structural irregularity

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Authors: C. H. Shashikanth, M. J. Davidson, V. Suresh Babu

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The formability of metals depends on a number of variables such as strain, strain rate, and temperature. Though most of the metals are formable at room temperature, few are not. To evaluate the workability of such metals at elevated temperatures, thermomechanical experiments should be carried out to find out the forming temperatures and strain rates. Though a number of constitutive relations are available to correlate the material parameters and the corresponding formability at elevated temperatures, the constitutive rule proposed by Arrhenius has been used in this work. Thus, in the present work, the material constants such as A (constant), α (stress multiplier), β (constant), and n (stress exponent) of AA 2017 has been found by conducting a series of hot compression tests at different temperatures such as 400°C, 450°C, 500°C, and 550°C and at different strain rates such as 0.16, 0.18, and 0.2. True stress (σt), true strains (εt) deformation activation energy (Q), and the Zener-Hollomon parameter (Z value) were also calculated. The results indicate that the value of ln (Z) decreases as the temperature increases and it increases as the strain rate increases.

Keywords: hot compression test, aluminium alloy, flow stress, activation energy

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Authors: Iliyasu Musa Omoyine, Musa Sunday Abraham, Oladele Sunday Blessing, Iliya Ibrahim Abdullahi, Ibegbu Augustine Oseloka, Nuhu Nana-Hawau, Animoku Abdulrazaq Amoto, Yusuf Abdullateef Onoruoiza, Sambo Sohnap James, Akpulu Steven Peter, Ajayi Abayomi

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The neuroprotective role of inflammation from detrimental intrinsic and extrinsic factors has been reported. However, the overactivation of astrocytes and microglia due to lead toxicity produce excessive pro-inflammatory cytokines, mediating neurodegenerative diseases. The present study investigated the mitigatory effects of quercetin on neuroinflammation, correlating with memory function in lead-exposed rats. In this study, Wistar rats were administered orally with Quercetin (Q: 60 mg/kg) and Succimer as a standard drug (S: 10 mg/kg) for 21 days after lead exposure (Pb: 125 mg/kg) of 21 days or in combination with Pb, once daily for 42 days. Working and reference memory was assessed using an Eight-arm radial water maze (8-ARWM). The changes in brain lead level, the neuronal nitric oxide synthase (nNOS) activity, and the level of neuroinflammatory markers such as tumour necrosis factor-alpha (TNF-α) and Interleukin 1 Beta (IL-1β) were determined. Immunohistochemically, astrocyte expression was evaluated. The results showed that the brain level of lead was increased significantly in lead-exposed rats. The expression of astrocytes increased in the CA3 and CA1 regions of the hippocampus, and the levels of brain TNF-α and IL-1β increased in lead-exposed rats. Lead impaired reference and working memory by increasing reference memory errors and working memory incorrect errors in lead-exposed rats. However, quercetin treatment effectively improved memory and inhibited neuroinflammation by reducing astrocytes’ expression and the levels of TNF-α and IL-1β. The expression of astrocytes and the levels of TNF-α and IL-1β correlated with memory function. The possible explanation for quercetin’s anti-neuroinflammatory effect is that it modulates the activity of cellular proteins involved in the inflammatory response; inhibits the transcription factor of nuclear factor-kappa B (NF-κB), which regulates the expression of proinflammatory molecules; inhibits kinases required for the synthesis of Glial fibrillary acidic protein (GFAP) and modifies the phosphorylation of some proteins, which affect the structure and function of intermediate filament proteins; and, lastly, induces Cyclic-AMP Response Element Binding (CREB) activation and neurogenesis as a compensatory mechanism for memory deficits and neuronal cell death. In conclusion, the levels of neuroinflammatory markers negatively correlated with memory function. Thus, quercetin may be a promising therapy in neuroinflammation and memory dysfunction in populations prone to lead exposure.

Keywords: lead, quercetin, neuroinflammation, memory

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Authors: Jade Edey, Andrew Bennett, Gareth Hathway

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Nuclear receptor-related 1 protein (also known as Nurr1 or NR4A2) is an orphan nuclear receptor which plays a vital role in the development, survival and maintenance of dopaminergic (DA) neurons particularly in the substantia nigra (SN). Increasing research has investigated Nurr1’s additional role within microglia and astrocytes where it has been suggested to act as a negative regulator of inflammation; potentially offering neuroprotection. Considering both DA neurodegeneration and neuroinflammation are commonly accepted constituents of Parkinson’s Disease (PD), understanding the mechanisms by which Nurr1 regulates inflammatory processes could provide an attractive therapeutic target. Nurr1 regulates inflammation via a transrepressive mechanism possibly dependent upon SUMOylation. In addition, Nurr1 can transactivate numerous genes involved in DA synthesis, such as Tyrosine Hydroxylase (TH). A C-terminal splice variant of Nurr1, Nurr-1a, has been reported in both neuronal and glial cells. However, research into its transcriptional activity is minimal. We employed in vitro methods such as SUMO-Pulldown experiments alongside Luciferase reporter assays to investigate the SUMOylation status and transactivation capabilities of Nurr1 and Nurr-1a respectively. The SUMO-Pulldown assay demonstrated Nurr-1a undergoes significantly more SUMO modification than its full-length variant. Consequently, despite having less transcriptional activation than Nurr1, Nurr1a may play a more prominent role in repression of microglial inflammation. Contrary to published literature we also identified that SUMOylation enhances transcriptional activation by Nurr1 and Nurr1a. SUMOylation-dependent increases in Nurr1 and Nurr1a transcriptional activation were only evident in neuronal SHSY5Y cells but not in HEK293 cells. This research provides novel insight into the regulation of Nurr-1a and indicates differential effects of SUMOylation dependent regulation in neuronal and inflammatory cells.

Keywords: nuclear receptors, Parkinson’s disease, inflammation, transcriptional regulation

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Authors: Neeta Kumari, Gopal Pathak

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Artificial neural network has been proved to be an efficient tool for non-parametric modeling of data in various applications where output is non-linearly associated with input. It is a preferred tool for many predictive data mining applications because of its power , flexibility, and ease of use. A standard feed forward networks (FFN) is used to predict the groundwater fluoride content. The ANN model is trained using back propagated algorithm, Tansig and Logsig activation function having varying number of neurons. The models are evaluated on the basis of statistical performance criteria like Root Mean Squarred Error (RMSE) and Regression coefficient (R2), bias (mean error), Coefficient of variation (CV), Nash-Sutcliffe efficiency (NSE), and the index of agreement (IOA). The results of the study indicate that Artificial neural network (ANN) can be used for groundwater fluoride prediction in the limited data situation in the hard rock region like western parts of Jharkhand with sufficiently good accuracy.

Keywords: Artificial neural network (ANN), FFN (Feed-forward network), backpropagation algorithm, Levenberg-Marquardt algorithm, groundwater fluoride contamination

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Authors: Manh-Dung Ho, Van-Giap Pham, Van-Doanh Ho, Quang-Thien Tran, Tuan-Anh Tran

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The k0-factors and related nuclear data, i.e. the Q0-factors and effective resonance energies (Ēr) of the selected radionuclides which are used in the k0-based neutron activation analysis (k0-NAA), were critically reviewed to be integrated in the “k0-DALAT” software. The k0- and Q0-factors of some short-lived radionuclides: 46mSc, 110Ag, 116m2In, 165mDy, and 183mW, were experimentally determined at the Dalat research reactor. The other radionuclides selected are: 20F, 36S, 49Ca, 60mCo, 60Co, 75Se, 77mSe, 86mRb, 115Cd, 115mIn, 131Ba, 134mCs, 134Cs, 153Gd, 153Sm, 159Gd, 170Tm, 177mYb, 192Ir, 197mHg, 239U and 239Np. The reviewed data as compared with the literature data were biased within 5.6-7.3% in which the experimental re-determined factors were within 6.1 and 7.3%. The NIST standard reference materials: Oyster Tissue (1566b), Montana II Soil (2711a) and Coal Fly Ash (1633b) were used to validate the new reviewed data showing that the new data gave an improved k0-NAA using the “k0-DALAT” software with a factor of 4.5-6.8% for the investigated radionuclides.

Keywords: neutron activation analysis, k0-based method, k0 factor, Q0 factor, effective resonance energy

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Authors: Arya Prakash Padhi, Anupam Chakrabarti, Rajib Chowdhury

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Topology or layout optimization often gives better performing economic structures and is very helpful in the conceptual design phase. But traditionally it is being done in finite element-based optimization schemes which, although gives a good result, is very time-consuming especially in 3D structures. Among other alternatives machine learning, especially deep learning-based methods, have a very good potential in resolving this computational issue. Here convolutional neural network (3D-CNN) based variational auto encoder (VAE) is trained using a dataset generated from commercially available topology optimization code ABAQUS Tosca using solid isotropic material with penalization (SIMP) method for compliance minimization. The encoded data in latent space is then fed to a 3D generative adversarial network (3D-GAN) to generate the outcome in 64x64x64 size. Here the network consists of 3D volumetric CNN with rectified linear unit (ReLU) activation in between and sigmoid activation in the end. The proposed network is seen to provide almost optimal results with significantly reduced computational time, as there is no iteration involved.

Keywords: 3D generative adversarial network, deep learning, structural topology optimization, variational auto encoder

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Authors: Can Yao, Chang Dong Sheng

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The heat released by wood pellets during storage will cause self-heating and even self-ignition. In this work, the heat release rates of pine, fir wood and mahogany pellets at 30–70℃ were measured by TAM air isothermal calorimeter, and the kinetic analysis was performed by iso-conversion ratio and non-steady-state methods to evaluate its self-heating potential. The results show that the reaction temperature can significantly affect the heat release rate. The higher the temperature, the greater the heat release rate. The heat release rates of different kinds of wood pellets are obviously different, and the order of the heat release rates for the three pellets at 70℃ is pine > fir wood > mahogany. The kinetic analysis of the iso-conversion ratio method indicates that the distribution of activation energy for pine, fir wood and mahogany pellets under the release of 0.1–1.0 J/g specific heat are 58–102 kJ/mol, 59–108 kJ/mol and 59–112 kJ/mol, respectively. Their activation energies obtained from the non-steady-state kinetic analysis are 13.43 kJ/mol, 19.19 kJ/mol and 21.09 kJ/mol, respectively. Both kinetic analyses show that the magnitude of self-heating risk for the three pellet fuels is pine pellets > fir wood pellets > mahogany pellets.

Keywords: isothermal calorimeter, kinetics, self-heating, wood pellets

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Authors: Aisulu Tileukulova, Zhexebay Dauren

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Radar plays an important role because it is widely used in civil and military fields. Target detection is one of the most important radar applications. The accuracy of detecting inconspicuous aerial objects in radar facilities is lower against the background of noise. Convolutional neural networks can be used to improve the recognition of this type of aerial object. The purpose of this work is to develop an algorithm for recognizing aerial objects using convolutional neural networks, as well as training a neural network. In this paper, the structure of a convolutional neural network (CNN) consists of different types of layers: 8 convolutional layers and 3 layers of a fully connected perceptron. ReLU is used as an activation function in convolutional layers, while the last layer uses softmax. It is necessary to form a data set for training a neural network in order to detect a target. We built a Confusion Matrix of the CNN model to measure the effectiveness of our model. The results showed that the accuracy when testing the model was 95.7%. Classification of echo signals using CNN shows high accuracy and significantly speeds up the process of predicting the target.

Keywords: radar, neural network, convolutional neural network, echo signals

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Authors: Parker Townes, Prabdeep Panesar, Chunlin Liu, Soo Youn Lee, Dan Devoe, Paul D. Arnold, Jennifer Crosbie, Russell Schachar

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Attention-deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) are impairing childhood neurodevelopmental disorders with problems in executive functions. Executive functions are higher-level mental processes essential for daily functioning and goal attainment. There is genetic and neural overlap between ADHD and ASD. The aim of this meta-analysis was to evaluate if pediatric ASD and ADHD have distinct executive function profiles. This review was completed following Cochrane guidelines. Fifty-eight articles were identified through database searching, followed by a blinded screening in duplicate. A meta-analysis was performed for all task performance metrics evaluated by at least two articles. Forty-five metrics from 24 individual tasks underwent analysis. No differences were found between youth with ASD and ADHD in any domain under direct comparison. However, individuals with ASD and ADHD exhibited deficient attention, flexibility, visuospatial abilities, working memory, processing speed, and response inhibition compared to controls. No deficits in planning were noted in either disorder. Only 11 studies included a group with comorbid ASD+ADHD, making it difficult to determine whether common executive function deficits are a function of comorbidity. Further research is needed to determine if comorbidity accounts for the apparent commonality in executive function between ASD and ADHD.

Keywords: autism spectrum disorder, ADHD, neurocognition, executive function, youth

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Authors: Meng Wu

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Unmanned aerial vehicle (UAV) landing technology is a common task that is required to be fulfilled by fly robots. In this paper, the crazyflie2.0 is located by ultra-wideband (UWB) localization system that contains 4 UWB anchors. Another UWB anchor is introduced and installed on a stationary platform. One cost function is designed to find the minimum distance between crazyflie2.0 and the anchor installed on the stationary platform. The coordinates of the anchor are unknown in advance, and the goal of the cost function is to define the location of the anchor, which can be considered as an optimal landing point. When the cost function reaches the minimum value, the corresponding coordinates of the UWB anchor fixed on the stationary platform can be calculated and defined as the landing point. The simulation shows the effectiveness of the method in this paper.

Keywords: UAV landing, UWB localization system, UWB anchor, cost function, stationary platform

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Authors: Moh'd Alodat

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In this paper, we discuss the power function distribution and derive the maximum likelihood estimator of its parameter as well as the reliability parameter. We derive the large sample properties of the estimators based on the selective order statistic scheme. We conduct simulation studies to investigate the significance of the selective order statistic scheme in our setup and to compare the efficiency of the new proposed estimators.

Keywords: fisher information, maximum likelihood estimator, power function distribution, ranked set sampling, selective order statistics sampling

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Authors: Myung-Gon Yoon, Jung-Ho Moon, Tae Kwon Ha

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This paper considers a robust stabilization problem of a single agent in a multi-agent consensus system composed of identical agents, when the network topology of the system is completely unknown. It is shown that the transfer function of an agent in a consensus system can be described as a multiplicative perturbation of the isolated agent transfer function in frequency domain. Applying known robust stabilization results, we present sufficient conditions for a robust stabilization of an agent against unknown network topology.

Keywords: single agent control, multi-agent system, transfer function, graph angle

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Authors: Noriko Hanakawa, Masaki Obana

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A simulation tool has been proposed for big-scale projection mapping events. The tool has four main functions based on Mapbox and Unity utilities. The first function is building a 3D model of real cities by MapBox. The second function is a movie projection to some buildings in real cities by Unity. The third function is a movie sending function from a PC to a virtual projector. The fourth function is mapping movies with fitting buildings. The simulation tool was adapted to a real projection mapping event that was held in 2019. The event has been finished. The event had a serious problem in the movie projection to the target building. The extra tents were set in front of the target building. The tents became the obstacles to the movie projection. The simulation tool can be reappeared the problems of the event. Therefore, if the simulation tool was developed before the 2019 projection mapping event, the problem of the tents’ obstacles could be avoided with the simulation tool. In addition, we confirmed that the simulation tool is useful to make a plan of future projection mapping events in order to avoid obstacles of various extra equipment such as utility poles, planting trees, monument towers.

Keywords: projection mapping, projector position, real 3D map, avoiding obstacles

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Authors: Artem A. Krylov

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Instrumental seismological researches in water areas are complicated and expensive, that leads to the lack of strong motion records in most offshore regions. In the same time the number of offshore industrial infrastructure objects, such as oil rigs, subsea pipelines, is constantly increasing. The empirical Green’s function technique proved to be very effective for accelerograms synthesis under the conditions of poorly described seismic wave propagation medium. But the selection of suitable small earthquake record in offshore regions as an empirical Green’s function is a problem because of short seafloor instrumental seismological investigation results usually with weak micro-earthquakes recordings. An approach based on moving average smoothing in the frequency domain is presented for preliminary processing of weak micro-earthquake records before using it as empirical Green’s function. The method results in significant waveform correction for modeled event. The case study for 2009 L’Aquila earthquake was used to demonstrate the suitability of the method. This work was supported by the Russian Foundation of Basic Research (project № 18-35-00474 mol_a).

Keywords: accelerogram synthesis, empirical Green's function, marine seismology, microearthquakes

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Authors: Fernando Maass, Pablo Martin, Jorge Olivares

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The Bessel function J₀(x) is very important in Electrodynamics and Physics, as well as its zeros. In this work, a method to obtain high accuracy approximation is presented through an application to that function. In most of the applications of this function, the values of the zeros are very important. In this work, analytic approximations for this function have been obtained valid for all positive values of the variable x, which have high accuracy for the function as well as for the zeros. The approximation is determined by the simultaneous used of the power series and asymptotic expansion. The structure of the approximation is a combination of two rational functions with elementary functions as trigonometric and fractional powers. Here us in Pade method, rational functions are used, but now there combined with elementary functions us fractional powers hyperbolic or trigonometric functions, and others. The reason of this is that now power series of the exact function are used, but together with the asymptotic expansion, which usually includes fractional powers trigonometric functions and other type of elementary functions. The approximation must be a bridge between both expansions, and this can not be accomplished using only with rational functions. In the simplest approximation using 4 parameters the maximum absolute error is less than 0.006 at x ∼ 4.9. In this case also the maximum relative error for the zeros is less than 0.003 which is for the second zero, but that value decreases rapidly for the other zeros. The same kind of behaviour happens for the relative error of the maximum and minimum of the functions. Approximations with higher accuracy and more parameters will be also shown. All the approximations are valid for any positive value of x, and they can be calculated easily.

Keywords: analytic approximations, asymptotic approximations, Bessel functions, quasirational approximations

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Authors: Javier Comes Fayos, Isabel Rodríguez Moreno, Sara Bressanutti, Marisol Lila, Angel Romero Martínez, Luis Moya Albiol

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Empathy is a cognitive-affective capacity whose deterioration is associated with aggressive behaviour. Deficient affective processing is one of the predominant risk factors in men convicted of intimate partner violence (IPV perpetrators), since it makes their capacity to empathize very difficult. The objective of this study is to compare the response of electrodermal activity (EDA), as an indicator of emotionality, to an empathic induction task, between IPV perpetrators and men without a history of violence. The sample was composed of 51 men who attended the CONTEXTO program, with penalties for gender violence under two years, and 47 men with no history of violence. Empathic induction was achieved through the visualization of 4 negative emotional-eliciting videos taken from an emotional induction battery of videos validated for the Spanish population. The participants were asked to actively empathize with the video characters (previously pointed out). The psychophysiological recording of the EDA was accomplished by the "Vrije Universiteit Ambulatory Monitoring System (VU-AMS)." An analysis of repeated measurements was carried out with 10 intra-subject measurements (time) and "group" (IPV perpetrators and non-violent perpetrators) as the inter-subject factor. First, there were no significant differences between groups in the baseline AED levels. Yet, a significant interaction between the “time” and “group” was found with IPV perpetrators exhibiting lower EDA response than controls after the empathic induction task. These findings provide evidence of a subdued EDA response after an empathic induction task in IPV perpetrators with respect to men without a history of violence. Therefore, the lower psychophysiological activation would be indicative of difficulties in the emotional processing and response, functions that are necessary for the empathic function. Consequently, the importance of addressing possible empathic difficulties in IPV perpetrator psycho-educational programs is reinforced, putting special emphasis on the affective dimension that could hinder the empathic function.

Keywords: electrodermal activity, emotional induction, empathy, intimate partner violence

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Authors: Li Ni, Pen ManMan, Li KenLi

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Clustering is an intensive research for some years because of its multifaceted applications, such as biology, information retrieval, medicine, business and so on. The expectation maximization (EM) is a kind of algorithm framework in clustering methods, one of the ten algorithms of machine learning. Traditionally, optimization of objective function has been the standard approach in EM. Hence, research has investigated the utility of evolutionary computing and related techniques in the regard. Chemical Reaction Optimization (CRO) is a recently established method. So the property embedded in CRO is used to solve optimization problems. This paper presents an algorithm framework (EM-CRO) with modified CRO operators based on EM cluster problems. The hybrid algorithm is mainly to solve the problem of initial value sensitivity of the objective function optimization clustering algorithm. Our experiments mainly take the EM classic algorithm:k-means and fuzzy k-means as an example, through the CRO algorithm to optimize its initial value, get K-means-CRO and FKM-CRO algorithm. The experimental results of them show that there is improved efficiency for solving objective function optimization clustering problems.

Keywords: chemical reaction optimization, expection maimization, initia, objective function clustering

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Authors: Nurul Aini Abdul Wahab, Nor Syamim Halidin, Sayidatina Aisah Masnan, Nur Izzati Romli

Abstract:

There are many applications of principle component method for reducing the large set of variables in various fields. Fisher’s Discriminant function is also a popular tool for classification. In this research, the researcher focuses on studying the performance of Principle Component-Fisher’s Discriminant function in helping to classify rice kernels to their defined classes. The data were collected on the smells or odour of the rice kernel using odour-detection sensor, Cyranose. 32 variables were captured by this electronic nose (e-nose). The objective of this research is to measure how well a combination model, between principle component and linear discriminant, to be as a classification model. Principle component method was used to reduce all 32 variables to a smaller and manageable set of components. Then, the reduced components were used to develop the Fisher’s Discriminant function. In this research, there are 4 defined classes of rice kernel which are Aromatic, Brown, Ordinary and Others. Based on the output from principle component method, the 32 variables were reduced to only 2 components. Based on the output of classification table from the discriminant analysis, 40.76% from the total observations were correctly classified into their classes by the PC-Discriminant function. Indirectly, it gives an idea that the classification model developed has committed to more than 50% of misclassifying the observations. As a conclusion, the Fisher’s Discriminant function that was built on a 2-component from PCA (2-PC-D) is not satisfying to classify the rice kernels into its defined classes.

Keywords: classification model, discriminant function, principle component analysis, variable reduction

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Authors: Strahinja Kovačević, Jelena Vladić, Senka Vidović, Zoran Zeković, Lidija Jevrić, Sanja Podunavac Kuzmanović

Abstract:

Supercritical extracts of highly valuated medicinal plant Satureja montana were prepared by application of supercritical carbon dioxide extraction in the carbon dioxide pressure range from 125 to 350 bar and temperature range from 40 to 60°C. Using GC/MS method of analysis chemical profiles (aromatic constituents) of S. montana extracts were obtained. Self-training artificial neural networks were applied to predict the retention time of the analyzed terpenes in GC/MS system. The best ANN model obtained was multilayer perceptron (MLP 11-11-1). Hidden activation was tanh and output activation was identity with Broyden–Fletcher–Goldfarb–Shanno training algorithm. Correlation measures of the obtained network were the following: R(training) = 0.9975, R(test) = 0.9971 and R(validation) = 0.9999. The comparison of the experimental and predicted retention times of the analyzed compounds showed very high correlation (R = 0.9913) and significant predictive power of the established neural network.

Keywords: ANN regression, GC/MS, Satureja montana, terpenes

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Authors: A. Selmi, A. Bisharat

Abstract:

Using Fourier transform and based on the Mindlin's 2^nd gradient model that involves two length scale parameters, the Green's function, the Eshelby tensor, and the Eshelby-like tensor for a spherical inclusion are derived. It is proved that the Eshelby tensor consists of two parts; the classical Eshelby tensor and a gradient part including the length scale parameters which enable the interpretation of the size effect. When the strain gradient is not taken into account, the obtained Green's function and Eshelby tensor reduce to its analogue based on the classical elasticity. The Eshelby tensor in and outside the inclusion, the volume average of the gradient part and the Eshelby-like tensor are explicitly obtained. Unlike the classical Eshelby tensor, the results show that the components of the new Eshelby tensor vary with the position and the inclusion dimensions. It is demonstrated that the contribution of the gradient part should not be neglected.

Keywords: Eshelby tensor, Eshelby-like tensor, Green’s function, Mindlin’s 2nd gradient model, spherical inclusion

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Authors: Milu T. Cherian, Sergio C. Chai, Morgan A. Casal, Taosheng Chen

Abstract:

This study aims to use CINPA1, a recently discovered small-molecule inhibitor of the xenobiotic receptor CAR (constitutive androstane receptor) for understanding the binding modes of CAR and to guide CAR-mediated gene expression profiling studies in human primary hepatocytes. CAR and PXR are xenobiotic sensors that respond to drugs and endobiotics by modulating the expression of metabolic genes that enhance detoxification and elimination. Elevated levels of drug metabolizing enzymes and efflux transporters resulting from CAR activation promote the elimination of chemotherapeutic agents leading to reduced therapeutic effectiveness. Multidrug resistance in tumors after chemotherapy could be associated with errant CAR activity, as shown in the case of neuroblastoma. CAR inhibitors used in combination with existing chemotherapeutics could be utilized to attenuate multidrug resistance and resensitize chemo-resistant cancer cells. CAR and PXR have many overlapping modulating ligands as well as many overlapping target genes which confounded attempts to understand and regulate receptor-specific activity. Through a directed screening approach we previously identified a new CAR inhibitor, CINPA1, which is novel in its ability to inhibit CAR function without activating PXR. The cellular mechanisms by which CINPA1 inhibits CAR function were also extensively examined along with its pharmacokinetic properties. CINPA1 binding was shown to change CAR-coregulator interactions as well as modify CAR recruitment at DNA response elements of regulated genes. CINPA1 was shown to be broken down in the liver to form two, mostly inactive, metabolites. The structure-activity differences of CINPA1 and its metabolites were used to guide computational modeling using the CAR-LBD structure. To rationalize how ligand binding may lead to different CAR pharmacology, an analysis of the docked poses of human CAR bound to CITCO (a CAR activator) vs. CINPA1 or the metabolites was conducted. From our modeling, strong hydrogen bonding of CINPA1 with N165 and H203 in the CAR-LBD was predicted. These residues were validated to be important for CINPA1 binding using single amino-acid CAR mutants in a CAR-mediated functional reporter assay. Also predicted were residues making key hydrophobic interactions with CINPA1 but not the inactive metabolites. Some of these hydrophobic amino acids were also identified and additionally, the differential coregulator interactions of these mutants were determined in mammalian two-hybrid systems. CINPA1 represents an excellent starting point for future optimization into highly relevant probe molecules to study the function of the CAR receptor in normal- and pathophysiology, and possible development of therapeutics (for e.g. use for resensitizing chemoresistant neuroblastoma cells).

Keywords: antagonist, chemoresistance, constitutive androstane receptor (CAR), multi-drug resistance, structure activity relationship (SAR), xenobiotic resistance

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