Search results for: computational biomechanics

Authors: Pamita Awasthi, Kirna, Shilpa Dogra, Manu Vatsal, Ritu Barthwal

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Doxorubicin, also known as adriamycin, is an anthracycline class of drug used in cancer chemotherapy. It is used in the treatment of non-Hodgkin’s lymphoma, multiple myeloma, acute leukemias, breast cancer, lung cancer, endometrium cancer and ovary cancers. It functions via intercalating DNA and ultimately killing cancer cells. The major side effects of doxorubicin are hair loss, myelosuppression, nausea & vomiting, oesophagitis, diarrhoea, heart damage and liver dysfunction. The minor modifications in the structure of compound exhibit large variation in the biological activity, has prompted us to carry out the synthesis of sulfonamide derivatives. Sulfonamide is an important feature with broad spectrum of biological activity such as antiviral, antifungal, diuretics, anti-inflammatory, antibacterial and anticancer activities. Structure of the synthesized compound N-(1-methyl-2-oxo-2-N-methyl anilino-ethyl)benzene sulfonamide confirmed by proton nuclear magnetic resonance (1H NMR),13C NMR, Mass and FTIR spectroscopic tools to assure the position of all protons and hence stereochemistry of the molecule. Further we have reported the binding potential of synthesized sulfonamide analogues in comparison to doxorubicin drug using Auto Dock 4.2 software. Computational binding energy (B.E.) and inhibitory constant (Ki) has been evaluated for the synthesized compound in comparison of doxorubicin against Poly (dA-dT).Poly (dA-dT) and Poly (dG-dC).Poly (dG-dC) sequences. The in vitro cytotoxic study against human breast cancer cell lines confirms the better anticancer activity of the synthesized compound over currently in use anticancer drug doxorubicin. The IC50 value of the synthesized compound is 7.12 µM where as for doxorubicin is 7.2 µ.

Keywords: Doxorubicin, auto dock, in silco, in vitro

Procedia PDF Downloads 393

Authors: Muhammad Mehran Arshad Khan, Chengliang Wang, Zou Minhui, Danyal Badar Soomro

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Security of the smart home in terms of behavior activity pattern recognition is a totally dissimilar and unique issue as compared to the security issues of other scenarios. Sensor devices (low capacity and high capacity) interact and negotiate each other by detecting the daily behavior activity of individuals to execute common tasks. Once a device (e.g., surveillance camera, smart phone and light detection sensor etc.) is compromised, an adversary can then get access to a specific device and can damage daily behavior activity by altering the data and commands. In this scenario, a group of common instruction processes may get involved to generate deadlock. Therefore, an effective suitable security solution is required for smart home architecture. This paper proposes seamless distributed Scheme which fortifies low computational wireless devices for secure communication. Proposed scheme is based on lightweight key-session process to upheld cryptic-link for trajectory by recognizing of individual’s behavior activities pattern. Every device and service provider unit (low capacity sensors (LCS) and high capacity sensors (HCS)) uses an authentication token and originates a secure trajectory connection in network. Analysis of experiments is revealed that proposed scheme strengthens the devices against device seizure attack by recognizing daily behavior activities, minimum utilization memory space of LCS and avoids network from deadlock. Additionally, the results of a comparison with other schemes indicate that scheme manages efficiency in term of computation and communication.

Keywords: authentication, key-session, security, wireless sensors

Procedia PDF Downloads 295

Authors: Sumera, Sanila Amber, Fatima Javed Mirza, Amjad Ali, Saadia Zahid

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Glioblastoma multiforme (GBM) is a widely spread and fatal primary brain tumor with an increased risk of relapse in spite of aggressive treatment. The current procedures for GBM diagnosis include invasive procedures i.e. resection or biopsy, to acquire tumor mass. Implementation of negligibly invasive tests as a potential diagnostic technique and biofluid-based monitoring of GBM stresses on discovering biomarkers in CSF and blood. Therefore, we performed a comprehensive in silico analysis to identify potential circulating biomarkers for GBM. Initially, six gene and protein databases were utilized to mine brain-specific proteins. The resulting proteins were filtered using a channel of five tools to predict the secretory proteins. Subsequently, the expression profile of the secreted proteins was verified in the brain and blood using two databases. Additional verification of the resulting proteins was done using Plasma Proteome Database (PPD) to confirm their presence in blood. The final set of proteins was searched in literature for their relationship with GBM, keeping a special emphasis on secretome proteome. 2145 proteins were firstly mined as brain-specific, out of which 69 proteins were identified as secretory in nature. Verification of expression profile in brain and blood eliminated 58 proteins from the 69 proteins, providing a final list of 11 proteins. Further verification of these 11 proteins further eliminated 2 proteins, giving a final set of nine secretory proteins i.e. OPCML, NPTX1, LGI1, CNTN2, LY6H, SLIT1, CREG2, GDF1 and SERPINI1. Out of these 9 proteins, 7 were found to be linked to GBM, whereas 2 proteins are not investigated in GBM so far. We propose that these secretory proteins can serve as potential circulating biomarker signatures of GBM and will facilitate the development of minimally invasive diagnostic methods and novel therapeutic interventions for GBM.

Keywords: glioblastoma multiforme, secretory proteins, brain secretome, biomarkers

Procedia PDF Downloads 120

Authors: Syed Asif Hassan, Syed Atif Hassan

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Multidrug-resistant Tuberculosis (MDR-TB) is an infection caused by the resistant strains of Mycobacterium tuberculosis that do not respond either to isoniazid or rifampicin, which are the most important anti-TB drugs. The increase in the occurrence of a drug-resistance strain of MTB calls for an intensive search of novel target-based therapeutics. In this context LprG (Rv1411c) a lipoprotein from MTB plays a pivotal role in the immune evasion of Mtb leading to survival and propagation of the bacterium within the host cell. Therefore, a machine learning method will be developed for generating a computational model that could predict for a potential anti LprG activity of the novel antituberculosis compound. The present study will utilize dataset from PubChem database maintained by National Center for Biotechnology Information (NCBI). The dataset involves compounds screened against MTB were categorized as active and inactive based upon PubChem activity score. PowerMV, a molecular descriptor generator, and visualization tool will be used to generate the 2D molecular descriptors for the actives and inactive compounds present in the dataset. The 2D molecular descriptors generated from PowerMV will be used as features. We feed these features into three different classifiers, namely, random forest, a deep neural network, and a recurring neural network, to build separate predictive models and choosing the best performing model based on the accuracy of predicting novel antituberculosis compound with an anti LprG activity. Additionally, the efficacy of predicted active compounds will be screened using SMARTS filter to choose molecule with drug-like features.

Keywords: antituberculosis drug, classifier, machine learning, molecular descriptors, prediction

Procedia PDF Downloads 355

Authors: João F. A. Martos, Felipe J. Costa, Sergio N. P. Laiton, Bruno C. Lima, Israel S. Rêgo, Paulo P. G. Toro

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Nowadays, the scramjet is a topic that has attracted the attention of several scientific communities (USA, Australia, Germany, France, Japan, India, China, Russia), that are investing in this in this type of propulsion system due its interest to facilitate access to space and reach hypersonic speed, who have invested in this type of propulsion due to the interest in facilitating access to space. The Brazilian hypersonic scramjet aerospace vehicle 14-X B is a technological demonstrator of a hypersonic airbreathing propulsion system based on the supersonic combustion (scramjet) intended to be tested in flight into the Earth's atmosphere at 30 km altitude and Mach number 7. The 14-X B has been designed at the Prof. Henry T. Nagamatsu Laboratory of Aerothermodynamics and Hypersonics of the Institute for Advanced Studies (IEAv) in Brazil. The IEAv Hypersonic Shock Tunnel, named T3, is a ground-test facility able to reproduce the flight conditions as the Mach number as well as pressure and temperature in the test section close to those encountered during the test flight of the vehicle 14-X B into design conditions. A 1-m long stainless steel 14-X B model was experimentally investigated at T3 Hypersonic Shock Tunnel, for freestream Mach number 7. Static pressure measurements along the lower surface of the 14-X B model, along with high-speed schlieren photographs taken from the 5.5° leading edge and the 14.5° deflection compression ramp, provided experimental data that were compared to the analytical-theoretical solutions and the computational fluid dynamics (CFD) simulations. The results show a good qualitative agreement, and in consequence demonstrating the importance of these methods in the project of the 14-X B hypersonic aerospace vehicle.

Keywords: 14-X, CFD, hypersonic, hypersonic shock tunnel, scramjet

Procedia PDF Downloads 331

Authors: Rafael Muñoz, Juan Melchor, Alicia Valera, Laura Peralta, Guillermo Rus

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A torsional piezoelectric ultrasonic transducer design is proposed to measure shear moduli in soft tissue with direct access availability, using shear wave elastography technique. The measurement of shear moduli of tissues is a challenging problem, mainly derived from a) the difficulty of isolating a pure shear wave, given the interference of multiple waves of different types (P, S, even guided) emitted by the transducers and reflected in geometric boundaries, and b) the highly attenuating nature of soft tissular materials. An immediate application, overcoming these drawbacks, is the measurement of changes in cervix stiffness to estimate the gestational age at delivery. The design has been optimized using a finite element model (FEM) and a semi-analytical estimator of the probability of detection (POD) to determine a suitable geometry, materials and generated waves. The technique is based on the time of flight measurement between emitter and receiver, to infer shear wave velocity. Current research is centered in prototype testing and validation. The geometric optimization of the transducer was able to annihilate the compressional wave emission, generating a quite pure shear torsional wave. Currently, mechanical and electromagnetic coupling between emitter and receiver signals are being the research focus. Conclusions: the design overcomes the main described problems. The almost pure shear torsional wave along with the short time of flight avoids the possibility of multiple wave interference. This short propagation distance reduce the effect of attenuation, and allow the emission of very low energies assuring a good biological security for human use.

Keywords: cervix ripening, preterm birth, shear modulus, shear wave elastography, soft tissue, torsional wave

Procedia PDF Downloads 327

Authors: Mohammed Islam, Jungyong Wang, Dong Cheol Seo

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The Smoothed Particle Hydrodynamics (SPH) method is a novel, meshless, and Lagrangian technique based numerical method that has shown promises to accurately predict the hydrodynamics of water and structure interactions in violent flow conditions. The main goal of this study is to build confidence on the versatility of the Smoothed Particle Hydrodynamics (SPH) based tool, to use it as a complementary tool to the physical model testing capabilities and support research need for the performance evaluation of ships and offshore platforms exposed to an extreme and harsh environment. In the current endeavor, an open-sourced SPH-based tool was used and validated for modeling and predictions of the hydrodynamic interactions of a 6-DOF ship and bergy bits. The study involved the modeling of a modern generic drillship and simplified bergy bits in floating and towing scenarios and in regular and irregular wave conditions. The predictions were validated using the model-scale measurements on a moored ship towed at multiple oblique angles approaching a floating bergy bit in waves. Overall, this study results in a thorough comparison between the model scale measurements and the prediction outcomes from the SPH tool for performance and accuracy. The SPH predicted ship motions and forces were primarily within ±5% of the measurements. The velocity and pressure distribution and wave characteristics over the free surface depicts realistic interactions of the wave, ship, and the bergy bit. This work identifies and presents several challenges in preparing the input file, particularly while defining the mass properties of complex geometry, the computational requirements, and the post-processing of the outcomes.

Keywords: SPH, ship and bergy bit, hydrodynamic interactions, model validation, physical model testing

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Authors: Naila Nasreen, Dianchen Lu

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This paper explores the dynamical behavior of the (2+1)-dimensional Boussinesq equation, which is a nonlinear water wave equation and is used to model wave packets in dispersive media with weak nonlinearity. This equation depicts how long wave made in shallow water propagates due to the influence of gravity. The (2+1)- dimensional Boussinesq equation combines the two-way propagation of the classical Boussinesq equation with the dependence on a second spatial variable, as that occurs in the two-dimensional Kadomstev- Petviashvili equation. This equation provides a description of head- on collision of oblique waves and it possesses some interesting properties. The governing model is discussed by the assistance of Ricatti equation mapping method, a relatively integration tool. The solutions have been extracted in different forms the solitary wave solutions as well as hyperbolic and periodic solutions. Moreover, the sensitivity analysis is demonstrated for the designed dynamical structural system’s wave profiles, where the soliton wave velocity and wave number parameters regulate the water wave singularity. In addition to being helpful for elucidating nonlinear partial differential equations, the method in use gives previously extracted solutions and extracts fresh exact solutions. Assuming the right values for the parameters, various graph in different shapes are sketched to provide information about the visual format of the earned results. This paper’s findings support the efficacy of the approach taken in enhancing nonlinear dynamical behavior. We believe this research will be of interest to a wide variety of engineers that work with engineering models. Findings show the effectiveness simplicity, and generalizability of the chosen computational approach, even when applied to complicated systems in a variety of fields, especially in ocean engineering.

Keywords: (2+1)-dimensional Boussinesq equation, solitary wave solutions, Ricatti equation mapping approach, nonlinear phenomena

Procedia PDF Downloads 50

Authors: Pranab Kumar Das

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Vulnerability assessment of buildings with irregularity in the vertical direction has been carried out in this study. The constructions of vertically irregular buildings are increasing in the context of fast urbanization in the developing countries including India. During two reconnaissance based survey performed after Nepal earthquake 2015 and Imphal (India) earthquake 2016, it has been observed that so many structures are damaged due to the vertically irregular configuration. These irregular buildings are necessary to perform safely during seismic excitation. Therefore, it is very urgent demand to point out the actual vulnerability of the irregular structure. So that remedial measures can be taken for protecting those structures during natural hazard as like earthquake. This assessment will be very helpful for India and as well as for the other developing countries. A sufficient number of research has been contributed to the vulnerability of plan asymmetric buildings. In the field of vertically irregular buildings, the effort has not been forwarded much to find out their vulnerability during an earthquake. Irregularity in vertical direction may be caused due to irregular distribution of mass, stiffness and geometrically irregular configuration. Detailed analysis of such structures, particularly non-linear/ push over analysis for performance based design seems to be challenging one. The present paper considered a number of models of irregular structures. Building models made of both reinforced concrete and brick masonry are considered for the sake of generality. The analyses are performed with both help of finite element method and computational method.The study, as a whole, may help to arrive at a reasonably good estimate, insight for fundamental and other natural periods of such vertically irregular structures. The ductility demand, storey drift, and seismic response study help to identify the location of critical stress concentration. Summarily, this paper is a humble step for understanding the vulnerability and framing up the guidelines for vertically irregular structures.

Keywords: ductility, stress concentration, vertically irregular structure, vulnerability

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Authors: Hammam Aljabri, Hong G. Im

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Hydrogen is a promising future fuel to support the transition of the energy sector toward carbon neutrality. The direct utilization of H2 in Internal Combustion Engines (ICEs) is possible, and this technology faces mainly two challenges; high NOx emissions and severe knocking at mid to high loads. In this study, we numerically investigated the potential of H2 combustion in a truck-size engine operated in SI mode. To mitigate the knocking nature of H2 combustion, we have focused on studying the effects of three primary parameters; the compression ratio (CR), the air-fuel ratio, and the spark time. The baseline case was set using a CR of 16.5 and an equivalence ratio of 0.35. In simulations, the auto-ignition tendency was evaluated based on the maximum pressure rise rate and the local pressure fluctuations at the monitoring points set along the wall of the combustion chamber. To mitigate the auto-ignition tendency while enabling a wider range of engine operation, the effect of lowering the compression ratio was assessed. The results indicate that by lowering the compression ratio from 16.5:1 to 12.5:1, an indicated thermal efficiency of 47.5% can be achieved. Aiming to restrain the auto-ignition while maintaining good efficiency, a reduction in the equivalence ratio was examined under different compression ratios. The result indicates that higher compression ratios will require lower equivalence ratios, and due to practical limitations, a lower equivalence ratio of 0.25 was set as the limit. Using a compression ratio of 13.5 combined with an equivalence ratio of 0.3 resulted in an indicated thermal efficiency of 48.6%, that is, at a fixed spark time. It is found that under such lean conditions, the incomplete combustion losses and exhaust losses were high. Thus, advancing the spark time was assessed as a possible solution. The results demonstrated the advantages of advancing the spark time, where an indicated thermal efficiency exceeding 50% was achieved using a compression ratio of 14.5:1 and an equivalence ratio of 0.25.

Keywords: hydrogen, combustion, engine knock, SI engine

Procedia PDF Downloads 104

Authors: Deepshikha Shukla, C. H. Solanki, Mayank Desai

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In the last few years, it has been observed that earthquake is proving a threat to the scientist across the world. With a large number of earthquakes occurring in day to day life, the threat to life and property has increased manifolds which call for an urgent attention of all the researchers globally to carry out the research in the field of Earthquake Engineering. Any hazard related to the earthquake and seismicity is considered to be seismic hazards. The common forms of seismic hazards are Ground Shaking, Structure Damage, Structural Hazards, Liquefaction, Landslides, Tsunami to name a few. Among all the natural hazards, the most devastating and damaging is the earthquake as all other hazards are triggered only after the occurrence of an earthquake. In order to quantify and estimate the seismicity and seismic hazards, many methods and approaches have been proposed in the past few years. Such approaches are Mathematical, Conventional and Computational. Convex Set Theory, Empirical Green’s Function are some of the Mathematical Approaches whereas the Deterministic and Probabilistic Approaches are the Conventional Approach for the estimation of the seismic Hazards. Ground response and Ground Shaking of a particular area or region plays an important role in the damage caused due to the earthquake. In this paper, seismic study using Deterministic Approach and 1 D Ground Response Analysis has been carried out for Madhya Pradesh Tourism Office in Indore Region in Madhya Pradesh in Central India. Indore lies in the seismic zone III (IS: 1893, 2002) in the Seismic Zoning map of India. There are various faults and lineament in this area and Narmada Some Fault and Gavilgadh fault are the active sources of earthquake in the study area. Deepsoil v6.1.7 has been used to perform the 1 D Linear Ground Response Analysis for the study area. The Peak Ground Acceleration (PGA) of the city ranges from 0.1g to 0.56g.

Keywords: seismicity, seismic hazards, deterministic, probabilistic methods, ground response analysis

Procedia PDF Downloads 135

Authors: Masahiro Suzuki, Nobuyuki Okura

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The crosswind effect on ground transportations has been extensively investigated for decades. The effect of tornado, however, has been hardly studied in spite of the fact that even heavy ground vehicles, namely, trains were overturned by tornadoes with casualties in the past. Therefore, aerodynamic effects of the tornado on the train were studied by several approaches in this study. First, an experimental facility was developed to clarify aerodynamic forces acting on a vehicle running through a tornado. Our experimental set-up consists of two apparatus. One is a tornado simulator, and the other is a moving model rig. PIV measurements showed that the tornado simulator can generate a swirling-flow field similar to those of the natural tornadoes. The flow field has the maximum tangential velocity of 7.4 m/s and the vortex core radius of 96 mm. The moving model rig makes a 1/40 scale model train of single-car/three-car unit run thorough the swirling flow with the maximum speed of 4.3 m/s. The model car has 72 pressure ports on its surface to estimate the aerodynamic forces. The experimental results show that the aerodynamic forces vary its magnitude and direction depends on the location of the vehicle in the flow field. Second, the aerodynamic forces on the train were estimated by using Rankin vortex model. The Rankin vortex model is a simple tornado model which widely used in the field of civil engineering. The estimated aerodynamic forces on the middle car were fairly good agreement with the experimental results. Effects of the vortex core radius and the path of the train on the aerodynamic forces were investigated using the Rankin vortex model. The results shows that the side and lift forces increases as the vortex core radius increases, while the yawing moment is maximum when the core radius is 0.3875 times of the car length. Third, a computational simulation was conducted to clarify the flow field around the train. The simulated results qualitatively agreed with the experimental ones.

Keywords: aerodynamic force, experimental method, tornado, train

Procedia PDF Downloads 206

Authors: Tuğçe Kiper Elibol, İbrahim Uslan, Mehmet Ali Guler, Murat Buyuk, Uğur Yolum

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According to the FAA report, 142603 bird strikes were reported for a period of 24 years, between 1990 – 2013. Bird strike with aerospace structures not only threaten the flight security but also cause financial loss and puts life in danger. The statistics show that most of the bird strikes are happening with the nose and the leading edge of the wings. Also, a substantial amount of bird strikes is absorbed by the jet engines and causes damage on blades and engine body. Crash proof designs are required to overcome the possibility of catastrophic failure of the airplane. Using computational methods for bird strike analysis during the product development phase has considerable importance in terms of cost saving. Clearly, using simulation techniques to reduce the number of reference tests can dramatically affect the total cost of an aircraft, where for bird strike often full-scale tests are considered. Therefore, development of validated numerical models is required that can replace preliminary tests and accelerate the design cycle. In this study, to verify the simulation parameters for a bird strike analysis, several different numerical options are studied for an impact case against a primitive structure. Then, a representative bird mode is generated with the verified parameters and collided against the leading edge of a training aircraft wing, where each structural member of the wing was explicitly modeled. A nonlinear explicit dynamics finite element code, LS-DYNA was used for the bird impact simulations. SPH methodology was used to model the behavior of the bird. Dynamic behavior of the wing superstructure was observed and will be used for further design optimization purposes.

Keywords: bird impact, bird strike, finite element modeling, smoothed particle hydrodynamics

Procedia PDF Downloads 296

Authors: Martins Y. Otache, John J. Musa, Abayomi I. Kuti, Mustapha Mohammed

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The performance of an artificial neural network (ANN) is contingent on a host of factors, for instance, the network optimisation scheme. In view of this, the study examined the general implications of the ANN training optimisation algorithm on its forecast performance. To this end, the Bayesian regularisation (Br), Levenberg-Marquardt (LM), and the adaptive learning gradient descent: GDM (with momentum) algorithms were employed under different ANN structural configurations: (1) single-hidden layer, and (2) double-hidden layer feedforward back propagation network. Results obtained revealed generally that the gradient descent with momentum (GDM) optimisation algorithm, with its adaptive learning capability, used a relatively shorter time in both training and validation phases as compared to the Levenberg- Marquardt (LM) and Bayesian Regularisation (Br) algorithms though learning may not be consummated; i.e., in all instances considering also the prediction of extreme flow conditions for 1-day and 5-day ahead, respectively especially using the ANN model. In specific statistical terms on the average, model performance efficiency using the coefficient of efficiency (CE) statistic were Br: 98%, 94%; LM: 98 %, 95 %, and GDM: 96 %, 96% respectively for training and validation phases. However, on the basis of relative error distribution statistics (MAE, MAPE, and MSRE), GDM performed better than the others overall. Based on the findings, it is imperative to state that the adoption of ANN for real-time forecasting should employ training algorithms that do not have computational overhead like the case of LM that requires the computation of the Hessian matrix, protracted time, and sensitivity to initial conditions; to this end, Br and other forms of the gradient descent with momentum should be adopted considering overall time expenditure and quality of the forecast as well as mitigation of network overfitting. On the whole, it is recommended that evaluation should consider implications of (i) data quality and quantity and (ii) transfer functions on the overall network forecast performance.

Keywords: streamflow, neural network, optimisation, algorithm

Procedia PDF Downloads 116

Authors: Ali Elshabrawy

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Cloud computing is expected to be important for e Government in near future. Governments need it for solving some of its e Government, financial, infrastructure, legacy systems and integration problems. It reduces information technology (IT) infrastructure needs and support costs, and offers on-demand infrastructure and computational power, improved collaboration capabilities, which are important for e Government projects start up and sustainability. Budget pressures will continue to drive more and more government IT to hybrid and even public clouds, and more cooperation between cloud service providers and governmental agencies are expected, Or developing governmental private, community clouds. Motivation to convince governments to use cloud computing services, will create a pressure on cloud service providers to cope with government's requirements for interoperability, security standards, open data and integration between their cloud systems There will be significant legal action arising out of governmental uses of cloud computing, and legislation addressing both IT and business needs and consumer fears and protections. Cloud computing is a considered a revolution for IT and E business in general and e commerce, e Government in particular. As governments faces increasing challenges regarding IT infrastructure required for e Government projects implementation. As a result of Lack of required financial resources allocated for e Government projects in developed and developing countries. Cloud computing can play a major role to solve some of e Government projects challenges such as, lack of financial resources, IT infrastructure, Human resources trained to manage e Government applications, interoperability, cost efficiency challenges. If we could solve some security issues related to cloud computing usage which considered critical for e Government projects. Pretty sure it’s Just a matter of time before cloud service providers will find out solutions to attract governments as major customers for their business.

Keywords: cloud computing, e-government, adoption, supply side barriers, e-government requirements, challenges

Procedia PDF Downloads 329

Authors: Hamed Reza Heshmat Mohajer, Lan Ding, Mattheos Santamouris

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One of the worst environmental dangers for people who live in cities is the Urban Heat Island (UHI) impact which is anticipated to become stronger in the coming years as a result of climate change. Accordingly, the key aim of this paper is to study the interaction between the urban configuration and mitigation strategies including increasing albedo of the urban environment (reflective material), implementation of Urban Green Infrastructure (UGI) and/or a combination thereof. To analyse the microclimate models of different urban categories in the metropolis of Sydney, this study will assess meteorological parameters using a 3D model simulation tool of computational fluid dynamics (CFD) named ENVI-met. In this study, four main parameters are taken into consideration while assessing the effectiveness of UHI mitigation strategies: ambient air temperature, wind speed/direction, and outdoor thermal comfort. Layouts with present condition simulation studies from the basic model (scenario one) are taken as the benchmark. A base model is used to calculate the relative percentage variations between each scenario. The findings showed that maximum cooling potential across different urban layouts can be decreased by 2.15 °C degrees by combining high-albedo material with flora; besides layouts with open arrangements(OT1) present a highly remarkable improvement in ambient air temperature and outdoor thermal comfort when mitigation technologies applied compare to compact counterparts. Besides all layouts present a higher intensity on the maximum ambient air temperature reduction rather than the minimum ambient air temperature. On the other hand, Scenarios associated with an increase in greeneries are anticipated to have a slight cooling effect, especially on high-rise layouts.

Keywords: sustainable urban development, urban green infrastructure, high-albedo materials, heat island effect

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Authors: Ebru Dural, M. Zulfu Asık

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Laminated glass is a kind of safety glass, which is made by 'sandwiching' two glass sheets and a polyvinyl butyral (PVB) interlayer in between them. When the glass is broken, the interlayer in between the glass sheets can stick them together. Because of this property, the hazards of sharp projectiles during natural and man-made disasters reduces. They can be widely applied in building, architecture, automotive, transport industries. Laminated glass can easily undergo large displacements even under their own weight. In order to explain their true behavior, they should be analyzed by using large deflection theory to represent nonlinear behavior. In this study, a nonlinear mathematical model is developed for the analysis of laminated glass cylindrical shell which is free in radial directions and restrained in axial directions. The results will be verified by using the results of the experiment, carried out on laminated glass cylindrical shells. The behavior of laminated composite cylindrical shell can be represented by five partial differential equations. Four of the five equations are used to represent axial displacements and radial displacements and the fifth one for the transverse deflection of the unit. Governing partial differential equations are derived by employing variational principles and minimum potential energy concept. Finite difference method is employed to solve the coupled differential equations. First, they are converted into a system of matrix equations and then iterative procedure is employed. Iterative procedure is necessary since equations are coupled. Problems occurred in getting convergent sequence generated by the employed procedure are overcome by employing variable underrelaxation factor. The procedure developed to solve the differential equations provides not only less storage but also less calculation time, which is a substantial advantage in computational mechanics problems.

Keywords: laminated glass, mathematical model, nonlinear behavior, PVB

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Authors: Ashish Bhattarai, Bishnu Bhatta, Hem Raj Joshi, Nabin Neupane, Pankaj Yadav

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This report concerns the design, development, and analysis of the combined Darrieus and Savonius wind turbine. Vertical Axis Wind Turbines (VAWT's) are of two type's viz. Darrieus (lift type) and Savonius (drag type). The problem associated with Darrieus is the lack of self-starting while Savonius has low efficiency. There are 3 straight Darrieus blades having the cross-section of NACA(National Advisory Committee of Aeronautics) 0018 placed circumferentially and a helically twisted Savonius blade to get even torque distribution. This unique design allows the use of Savonius as a method of self-starting the wind turbine, which the Darrieus cannot achieve on its own. All the parts of the wind turbine are designed in CAD software, and simulation data were obtained via CFD(Computational Fluid Dynamics) approach. Also, the design was imported to FlashForge Finder to 3D print the wind turbine profile and finally, testing was carried out. The plastic material used for Savonius was ABS(Acrylonitrile Butadiene Styrene) and that for Darrieus was PLA(Polylactic Acid). From the data obtained experimentally, the hybrid VAWT so fabricated has been found to operate at the low cut-in speed of 3 m/s and maximum power output has been found to be 7.5537 watts at the wind speed of 6 m/s. The maximum rpm of the rotor blade is recorded to be 431 rpm(rotation per minute) at the wind velocity of 6 m/s, signifying its potentiality of wind power production. Besides, the data so obtained from both the process when analyzed through graph plots has shown the similar nature slope wise. Also, the difference between the experimental and theoretical data obtained has shown mechanical losses. The objective is to eliminate the need for external motors for self-starting purposes and study the performance of the model. The testing of the model was carried out for different wind velocities.

Keywords: VAWT, Darrieus, Savonius, helical blades, CFD, flash forge finder, ABS, PLA

Procedia PDF Downloads 173

Authors: A. Clementking, C. Jothi Venkateswaran

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Mathematical and computational functionalities such as descriptive mining, optimization, and predictions are espoused to resolve natural resource planning. The water quality prediction and its attributes influence determinations are adopted optimization techniques. The water properties are tainted while merging water resource one with another. This work aimed to predict influencing water resource distribution connectivity in accordance to water quality and sediment using an innovative proposed master-slave neural network back-propagation model. The experiment results are arrived through collecting water quality attributes, computation of water quality index, design and development of neural network model to determine water quality and sediment, master–slave back propagation neural network back-propagation model to determine variations on water quality and sediment attributes between the water resources and the recommendation for connectivity. The homogeneous and parallel biochemical reactions are influences water quality and sediment while distributing water from one location to another. Therefore, an innovative master-slave neural network model [M (9:9:2)::S(9:9:2)] designed and developed to predict the attribute variations. The result of training dataset given as an input to master model and its maximum weights are assigned as an input to the slave model to predict the water quality. The developed master-slave model is predicted physicochemical attributes weight variations for 85 % to 90% of water quality as a target values.The sediment level variations also predicated from 0.01 to 0.05% of each water quality percentage. The model produced the significant variations on physiochemical attribute weights. According to the predicated experimental weight variation on training data set, effective recommendations are made to connect different resources.

Keywords: master-slave back propagation neural network model(MSBPNNM), water quality analysis, multivariate analysis, environmental mining

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Authors: Jamerson Felipe Pereira Lima, Jeane Cecília Bezerra de Melo

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The difficulty and cost related to obtaining of protein tertiary structure information through experimental methods, such as X-ray crystallography or NMR spectroscopy, helped raising the development of computational methods to do so. An approach used in these last is prediction of tridimensional structure based in the residue chain, however, this has been proved an NP-hard problem, due to the complexity of this process, explained by the Levinthal paradox. An alternative solution is the prediction of intermediary structures, such as the secondary structure of the protein. Artificial Intelligence methods, such as Bayesian statistics, artificial neural networks (ANN), support vector machines (SVM), among others, were used to predict protein secondary structure. Due to its good results, artificial neural networks have been used as a standard method to predict protein secondary structure. Recent published methods that use this technique, in general, achieved a Q3 accuracy between 75% and 83%, whereas the theoretical accuracy limit for protein prediction is 88%. Alternatively, to achieve better results, support vector machines prediction methods have been developed. The statistical evaluation of methods that use different AI techniques, such as ANNs and SVMs, for example, is not a trivial problem, since different training sets, validation techniques, as well as other variables can influence the behavior of a prediction method. In this study, we propose a prediction method based on artificial neural networks, which is then compared with a selected SVM method. The chosen SVM protein secondary structure prediction method is the one proposed by Huang in his work Extracting Physico chemical Features to Predict Protein Secondary Structure (2013). The developed ANN method has the same training and testing process that was used by Huang to validate his method, which comprises the use of the CB513 protein data set and three-fold cross-validation, so that the comparative analysis of the results can be made comparing directly the statistical results of each method.

Keywords: artificial neural networks, protein secondary structure, protein structure prediction, support vector machines

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Authors: Arunkumar Balamurugan, G. Soundharya Lakshmi, V. Thenmozhi, M. Jegannath, V. R. Sanal Kumar

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Aerodynamics of insects is of topical interest in aeronautical industries due to its wide applications on various types of Micro Air Vehicles (MAVs). Note that the MAVs are having smaller geometric dimensions operate at significantly lower speeds on the order of 10 m/s and their Reynolds numbers range is approximately 1,50,000 or lower. In this paper, numerical study has been carried out to capture the flow physics of a biological inspired Swallowtail Butterfly with fixed wing having twin tail at a flight speed of 10 m/s. Comprehensive numerical simulations have been carried out on swallow butterfly with twin tail flying at a speed of 10 m/s with uniform upper and lower angles of attack in both lateral and longitudinal position for identifying the best wing orientation with better aerodynamic efficiency. Grid system in the computational domain is selected after a detailed grid refinement exercises. Parametric analytical studies have been carried out with different lateral and longitudinal angles of attack for finding the better aerodynamic efficiency at the same flight speed. The results reveal that lift coefficient significantly increases with marginal changes in the longitudinal angle and vice versa. But in the case of drag coefficient the conventional changes have been noticed, viz., drag increases at high longitudinal angles. We observed that the change of twin tail section has a significant impact on the formation of vortices and aerodynamic efficiency of the MAV’s. We concluded that for every lateral angle there is an exact longitudinal orientation for the existence of an aerodynamically efficient flying condition of any MAV. This numerical study is a pointer towards for the design optimization of Twin tail MAVs with flapping wings.

Keywords: aerodynamics of insects, MAV, swallowtail butterfly, twin tail MAV design

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Authors: Ruqaiya Khalil, Saman Usmani, Zaheer Ul-Haq

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The accurate characterization of ligand binding affinity is indispensable for designing molecules with optimized binding affinity. Computational tools help in many directions to predict quantitative correlations between protein-ligand structure and their binding affinities. Molecular dynamics (MD) simulation is a modern state-of-the-art technique to evaluate the underlying basis of ligand-protein interactions by characterizing dynamic and energetic properties during the event. Autoimmune diseases arise from an abnormal immune response of the body against own tissues. The current regimen for the described condition is limited to immune-modulators having compromised pharmacodynamics and pharmacokinetics profiles. One of the key player mediating immunity and tolerance, thus invoking autoimmunity is Interleukin-2; a cytokine influencing the growth of T cells. Molecular dynamics simulation techniques are applied to seek insight into the inhibitory mechanisms of newly synthesized compounds that manifested immunosuppressant potentials during in silico pipeline. In addition to estimation of free energies associated with ligand binding, MD simulation yielded us a great deal of information about ligand-macromolecule interactions to evaluate the pattern of interactions and the molecular basis of inhibition. The present study is a continuum of our efforts to identify interleukin-2 inhibitors of both natural and synthetic origin. Herein, we report molecular dynamics simulation studies of Interluekin-2 complexed with different antagonists previously reported by our group. The study of protein-ligand dynamics enabled us to gain a better understanding of the contribution of different active site residues in ligand binding. The results of the study will be used as the guide to rationalize the fragment based synthesis of drug-like interleukin-2 inhibitors as immune-modulators.

Keywords: immuno-modulators, MD simulation, protein-ligand interaction, structure-based drug design

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Authors: Min Wang, Sergey Utev

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The lessons from the 2007-09 global financial crisis have driven scientific research, which considers the design of new methodologies and financial models in the global market. The quantum mechanics approach was introduced in the unpredictable stock market modeling. One famous quantum tool is Feynman path integral method, which was used to model insurance risk by Tamturk and Utev and adapted to formalize the path-dependent option pricing by Hao and Utev. The research is based on the path-dependent calculation method, which is motivated by the Feynman path integral method. The path calculation can be studied in two ways, one way is to label, and the other is computational. Labeling is a part of the representation of objects, and generating functions can provide many different ways of representing share price paths. In this paper, the recent works on graphical theoretical construction of individual share price path via matroid is presented. Firstly, a study is done on the knowledge of matroid, relationship between lattice path matroid and Tutte polynomials and ways to connect points in the lattice path matroid and Tutte polynomials is suggested. Secondly, It is found that a general binary tree can be validly constructed from a connected lattice path matroid rather than general lattice path matroid. Lastly, it is suggested that there is a way to represent share price paths via a general binary tree, and an algorithm is developed to construct share price paths from general binary trees. A relationship is also provided between lattice integer points and Tutte polynomials of a transversal matroid. Use this way of connection together with the algorithm, a share price path can be constructed from a given connected lattice path matroid.

Keywords: combinatorial construction, graphical representation, matroid, path calculation, share price, Tutte polynomial

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Authors: Manju Kanu, Subrata Sinha, Surabhi Johari

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Viral proteins of Ebola viruses belong to one of the best studied viruses; however no effective prevention against EBOV has been developed. Epitope-based vaccines provide a new strategy for prophylactic and therapeutic application of pathogen-specific immunity. A critical requirement of this strategy is the identification and selection of T-cell epitopes that act as vaccine targets. This study describes current methodologies for the selection process, with Ebola virus as a model system. Hence great challenge in the field of ebola virus research is to design universal vaccine. A combination of publicly available bioinformatics algorithms and computational tools are used to screen and select antigen sequences as potential T-cell epitopes of supertypes Human Leukocyte Antigen (HLA) alleles. MUSCLE and MOTIF tools were used to find out most conserved peptide sequences of viral proteins. Immunoinformatics tools were used for prediction of immunogenic peptides of viral proteins in zaire strains of Ebola virus. Putative epitopes for viral proteins (VP) were predicted from conserved peptide sequences of VP. Three tools NetCTL 1.2, BIMAS and Syfpeithi were used to predict the Class I putative epitopes while three tools, ProPred, IEDB-SMM-align and NetMHCII 2.2 were used to predict the Class II putative epitopes. B cell epitopes were predicted by BCPREDS 1.0. Immunogenic peptides were identified and selected manually by putative epitopes predicted from online tools individually for both MHC classes. Finally sequences of predicted peptides for both MHC classes were looked for common region which was selected as common immunogenic peptide. The immunogenic peptides were found for viral proteins of Ebola virus: epitopes FLESGAVKY, SSLAKHGEY. These predicted peptides could be promising candidates to be used as target for vaccine design.

Keywords: epitope, b cell, immunogenicity, ebola

Procedia PDF Downloads 284

Authors: Shyaka Eugene

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The efficient and safe demolition of structures is a critical challenge in civil engineering and construction. This study focuses on the development of optimal demolition strategies by investigating the crack propagation behavior in beams induced by soundless cracking agents. It is commonly used in controlled demolition and has gained prominence due to its non-explosive and environmentally friendly nature. This research employs a comprehensive experimental and computational approach to analyze the crack initiation, propagation, and eventual failure in beams subjected to soundless cracking agents. Experimental testing involves the application of various cracking agents under controlled conditions to understand their effects on the structural integrity of beams. High-resolution imaging and strain measurements are used to capture the crack propagation process. In parallel, numerical simulations are conducted using advanced finite element analysis (FEA) techniques to model crack propagation in beams, considering various parameters such as cracking agent composition, loading conditions, and beam properties. The FEA models are validated against experimental results, ensuring their accuracy in predicting crack propagation patterns. The findings of this study provide valuable insights into optimizing demolition strategies, allowing engineers and demolition experts to make informed decisions regarding the selection of cracking agents, their application techniques, and structural reinforcement methods. Ultimately, this research contributes to enhancing the safety, efficiency, and sustainability of demolition practices in the construction industry, reducing environmental impact and ensuring the protection of adjacent structures and the surrounding environment.

Keywords: expansion pressure, energy release rate, soundless chemical demolition agent, crack propagation

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Authors: Reza E. Sedgh, Rajesh P. Dhakal

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Shear walls have been used extensively as the main lateral force resisting systems in multi-storey buildings. The recent development in performance based design urges practicing engineers to conduct nonlinear static or dynamic analysis to evaluate seismic performance of multi-storey shear wall buildings by employing distinct analytical models suggested in the literature. For practical purpose, application of macroscopic models to simulate the global and local nonlinear behavior of structural walls outweighs the microscopic models. The skill level, computational time and limited access to RC specialized finite element packages prevents the general application of this method in performance based design or assessment of multi-storey shear wall buildings in design offices. Hence, this paper organized to verify capability of nonlinear shell element in commercially available package (Sap2000) in simulating results of some specimens under monotonic and cyclic loads with very oversimplified available cyclic material laws in the analytical tool. The selection of constitutive models, the determination of related parameters of the constituent material and appropriate nonlinear shear model are presented in detail. Adoption of proposed simple model demonstrated that the predicted results follow the overall trend of experimental force-displacement curve. Although, prediction of ultimate strength and the overall shape of hysteresis model agreed to some extent with experiment, the ultimate displacement(significant strength degradation point) prediction remains challenging in some cases.

Keywords: analytical model, nonlinear shell element, structural wall, shear behavior

Procedia PDF Downloads 371

Authors: Ali Javaid, Rizwan Latif, Syed Adnan Qasim, Imran Shafi

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To control combustion inside a direct injection diesel engine, fuel atomization is the best tool. Controlling combustion helps in reducing emissions and improves efficiency. Cavitation is one of the most important factors that significantly affect the nature of spray before it injects into combustion chamber. Typical fuel injector nozzles are small and operate at a very high pressure, which limits the study of internal nozzle behavior especially in case of diesel engine. Simulating cavitation in a fuel injector will help in understanding the phenomenon and will assist in further development. There is a parametric variation between high speed and high torque low speed diesel engines. The objective of this study is to simulate internal spray characteristics for a low speed high torque diesel engine. In-nozzle cavitation has strong effects on the parameters e.g. mass flow rate, fuel velocity, and momentum flux of fuel that is to be injected into the combustion chamber. The external spray dynamics and subsequently the air – fuel mixing depends on a lot of the parameters of fuel injecting the nozzle. The approach used to model turbulence induced in – nozzle cavitation for high-torque low-speed diesel engine, is homogeneous equilibrium model. The governing equations were modeled using Matlab. Complete Model in question was extensively evaluated by performing 3-D time-dependent simulations on Open FOAM, which is an open source flow solver and implemented in CFD (Computational Fluid Dynamics). Results thus obtained will be analyzed for better evaporation in the near-nozzle region. The proposed analyses will further help in better engine efficiency, low emission, and improved fuel economy.

Keywords: cavitation, HEM model, nozzle flow, open foam, turbulence

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Authors: José Alberto García Fernández, Zhimin Du, Xinqiao Jin

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Nowadays, data center industry faces strong challenges for increasing the speed and data processing capacities while at the same time is trying to keep their devices a suitable working temperature without penalizing that capacity. Consequently, the cooling systems of this kind of facilities use a large amount of energy to dissipate the heat generated inside the servers, and developing new cooling techniques or perfecting those already existing would be a great advance in this type of industry. The installation of a temperature sensor matrix distributed in the structure of each server would provide the necessary information for collecting the required data for obtaining a temperature profile instantly inside them. However, the number of temperature probes required to obtain the temperature profiles with sufficient accuracy is very high and expensive. Therefore, other less intrusive techniques are employed where each point that characterizes the server temperature profile is obtained by solving differential equations through simulation methods, simplifying data collection techniques but increasing the time to obtain results. In order to reduce these calculation times, complicated and slow computational fluid dynamics simulations are replaced by simpler and faster finite element method simulations which solve the Burgers‘ equations by backward, forward and central discretization techniques after simplifying the energy and enthalpy conservation differential equations. The discretization methods employed for solving the first and second order derivatives of the obtained Burgers‘ equation after these simplifications are the key for obtaining results with greater or lesser accuracy regardless of the characteristic truncation error.

Keywords: Burgers' equations, CFD simulation, data center, discretization methods, FEM simulation, temperature profile

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Authors: Juan Antonio Mondragon Sanchez, Ruben Santamaria

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The DNA G-quadruplex is a four-stranded DNA structure formed by stacked planes of four base paired guanines (G-quartet). Guanine rich DNA sequences appear in many sites of genomic DNA and can potential form G-quadruplexes, such as those occurring at 3'-terminus of the human telomeric DNA. The formation and stabilization of a G-quadruplex by small ligands at the telomeric region can inhibit the telomerase activity. In turn, the ligands can be used to down regulate oncogene expression making G-quadruplex an attractive target for anticancer therapy. Many G-quadruplex ligands have been proposed with a planar core to facilitate the pi–pi stacking and electrostatic interactions with the G-quartets. However, many drug candidates are impossibilitated to discriminate a G-quadruplex from a double helix DNA structure. In this context, it is important to investigate the site topology for the interaction of a G-quadruplex with a ligand. In this work, we determine the free energy surface of a G-quadruplex-ligand to study the binding modes of the G-quadruplex (TG4T) with the daunomycin (DM) drug. The complex TG4T-DM is studied using classical molecular dynamics in combination with metadynamics simulations. The metadynamics simulations permit an enhanced sampling of the conformational space with a modest computational cost and obtain free energy surfaces in terms of the collective variables (CV). The free energy surfaces of TG4T-DM exhibit other local minima, indicating the presence of additional binding modes of daunomycin that are not observed in short MD simulations without the metadynamics approach. The results are compared with similar calculations on a different structure (the mutated mu-G4T-DM where the 5' thymines on TG4T-DM have been deleted). The results should be of help to design new G-quadruplex drugs, and understand the differences in the recognition topology sites of the duplex and quadruplex DNA structures in their interaction with ligands.

Keywords: g-quadruplex, cancer, molecular dynamics, metadynamics

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Authors: Y. Trantafyllou, C. Alexandraki

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Music interpretation accounts to the way musicians shape their performance by deliberately deviating from composers’ intentions, which are commonly communicated via some form of music transcription, such as a music score. For transcribed and non-improvised music, music expression is manifested by introducing subtle deviations in tempo, dynamics and articulation during the evolution of performance. This paper presents an application, named FlameCens, which, given two recordings of the same piece of music, presumably performed by different musicians, allow visualising deviations in tempo and dynamics during playback. The application may also compare a certain performance to the music score of that piece (i.e. MIDI file), which may be thought of as an expression-neutral representation of that piece, hence depicting the expressive queues employed by certain performers. FlameCens uses the Dynamic Time Warping algorithm to compare two audio sequences, based on CENS (Chroma Energy distribution Normalized Statistics) audio features. Expressive deviations are illustrated in a moving flame, which is generated by an animation of particles. The length of the flame is mapped to deviations in dynamics, while the slope of the flame is mapped to tempo deviations so that faster tempo changes the slope to the right and slower tempo changes the slope to the left. Constant slope signifies no tempo deviation. The detected deviations in tempo and dynamics can be additionally recorded in a text file, which allows for offline investigation. Moreover, in the case of monophonic music, the color of particles is used to convey the pitch of the notes during performance. FlameCens has been implemented in Python and it is openly available via GitHub. The application has been experimentally validated for different music genres including classical, contemporary, jazz and popular music. These experiments revealed that FlameCens can be a valuable tool for music specialists (i.e. musicians or musicologists) to investigate the expressive performance strategies employed by different musicians, as well as for music audience to enhance their listening experience.

Keywords: audio synchronization, computational music analysis, expressive music performance, information visualization

Procedia PDF Downloads 104