Search results for: biological molecular networks

Authors: Chanyuan Gu, Shouming Zhong

Abstract:

Synchronization is a fundamental phenomenon that enables coherent behavior in networks as a result of interactions. The purpose of this research had been to investigate the problem of anti-phase synchronization for complex delayed dynamical networks with output coupling. The coupling configuration is general, with the coupling matrix not assumed to be symmetric or irreducible. The amount of the coupling variables between two connected nodes is flexible, the nodes in the drive and response systems need not to be identical and there is not any extra constraint on the coupling matrix. Some pinning controllers are designed to make the drive-response system achieve the anti-phase synchronization. For the convenience of description, we applied the matrix Kronecker product. Some new criteria are proposed based on the Lyapunov stability theory, linear matrix inequalities (LMI) and Schur complement. Lastly, some simulation examples are provided to illustrate the effectiveness of our proposed conditions.

Keywords: anti-phase synchronization, complex networks, output coupling, pinning control

Procedia PDF Downloads 382

Authors: Seyyed Feisal Asbaghian Namin, Reza Pilafkan, Mahmood Kaffash Irzarahimi

Abstract:

TThis paper considers vibration of single-layered graphene sheets using molecular dynamics (MD) and nonlocal elasticity theory. Based on the MD simulations, Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS), an open source software, is used to obtain fundamental frequencies. On the other hand, governing equations are derived using nonlocal elasticity and first order shear deformation theory (FSDT) and solved using generalized differential quadrature method (GDQ). The small-scale effect is applied in governing equations of motion by nonlocal parameter. The effect of different side lengths, boundary conditions and nonlocal parameter are inspected for aforementioned methods. Results are obtained from MD simulations is compared with those of the nonlocal elasticity theory to calculate appropriate values for the nonlocal parameter. The nonlocal parameter value is suggested for graphene sheets with various boundary conditions. Furthermore, it is shown that the nonlocal elasticity approach using classical plate theory (CLPT) assumptions overestimates the natural frequencies.

Keywords: graphene sheets, molecular dynamics simulations, fundamental frequencies, nonlocal elasticity theory, nonlocal parameter

Procedia PDF Downloads 502

Authors: M. Rahimnejad, B. Vahidi, B. Ebrahimi Hoseinzadeh, F. Yazdian, P. Motamed Fath, R. Jamjah

Abstract:

In this study, we developed and simulated nano-drug delivery systems efficacy in compare to free drug prescription. Computational models can be utilized to accelerate experimental steps and control the experiments high cost. Molecular dynamics simulation (MDS), in particular NAMD was utilized to better understand the anti-cancer drug interaction with cell membrane model. Paclitaxel (PTX) and dipalmitoylphosphatidylcholine (DPPC) were selected for the drug molecule and as a natural phospholipid nanocarrier, respectively. This work focused on two important interaction parameters between molecules in terms of center of mass (COM) and van der Waals interaction energy. Furthermore, we compared the simulation results of the PTX interaction with the cell membrane and the interaction of DPPC as a nanocarrier loaded by the drug with the cell membrane. The molecular dynamic analysis resulted in low energy between the nanocarrier and the cell membrane as well as significant decrease of COM amount in the nanocarrier and the cell membrane system during the interaction. Thus, the drug vehicle showed notably better interaction with the cell membrane in compared to free drug interaction with the cell membrane.

Keywords: anti-cancer drug, center of mass, interaction energy, molecular dynamics simulation, nanocarrier

Procedia PDF Downloads 329

Authors: Shiva Kumar, G. S. Vijay, Srinivas Pai P., Shrinivasa Rao B. R.

Abstract:

In the present study RBF neural networks were used for predicting the performance and emission parameters of a biodiesel engine. Engine experiments were carried out in a 4 stroke diesel engine using blends of diesel and Honge methyl ester as the fuel. Performance parameters like BTE, BSEC, Tech and emissions from the engine were measured. These experimental results were used for ANN modeling. RBF center initialization was done by random selection and by using Clustered techniques. Network was trained by using fixed and varying widths for the RBF units. It was observed that RBF results were having a good agreement with the experimental results. Networks trained by using clustering technique gave better results than using random selection of centers in terms of reduced MRE and increased prediction accuracy. The average MRE for the performance parameters was 3.25% with the prediction accuracy of 98% and for emissions it was 10.4% with a prediction accuracy of 80%.

Keywords: radial basis function networks, emissions, performance parameters, fuzzy c means

Procedia PDF Downloads 545

Authors: Sungkyung Kim, Jee-Hyeon Na, Dong-Seung Kwon

Abstract:

Future mobile networks following 5th generation will be characterized by one thousand times higher gains in capacity; connections for at least one hundred billion devices; user experience capable of extremely low latency and response times. To be close to the capacity requirements and higher reliability, advanced technologies have been studied, such as multiple connectivity, small cell enhancement, heterogeneous networking, and advanced interference and mobility management. This paper is focused on the multiple connectivity in heterogeneous cellular networks. We investigate the performance of coverage and user throughput in several deployment scenarios. Using the stochastic geometry approach, the SINR distributions and the coverage probabilities are derived in case of dual connection. Also, to compare the user throughput enhancement among the deployment scenarios, we calculate the spectral efficiency and discuss our results.

Keywords: heterogeneous networks, multiple connectivity, small cell enhancement, stochastic geometry

Procedia PDF Downloads 316

Authors: Joo-Hyung Oh

Abstract:

The number of service users of 4G VoLTE (voice over LTE) using LTE data networks is rapidly growing. VoLTE based on all-IP network enables clearer and higher-quality voice calls than 3G. It does, however, pose new challenges; a voice call through IP networks makes it vulnerable to security threats such as wiretapping and forged or falsified information. And in particular, stealing other users’ phone numbers and forging or falsifying call request messages from outgoing voice calls within VoLTE result in considerable losses that include user billing and voice phishing to acquaintances. This paper focuses on the threats of caller phone number spoofing in the VoLTE and countermeasure technology as safety measures for mobile communication networks.

Keywords: LTE, 4G, VoLTE, phone number spoofing

Procedia PDF Downloads 421

Authors: Lu Zhao, Nadir Farhi, Yeltsin Valero, Zoi Christoforou, Nadia Haddadou

Abstract:

In this paper, a long short-term memory (LSTM) neural network model is proposed to replicate simultaneously car-following and lane-changing behaviors in road networks. By combining two kinds of LSTM layers and three input designs of the neural network, six variants of the LSTM model have been created. These models were trained and tested on the NGSIM 101 dataset, and the results were evaluated in terms of longitudinal speed and lateral position, respectively. Then, we compared the LSTM model with a classical car-following model (the intelligent driving model (IDM)) in the part of speed decision. In addition, the LSTM model is compared with a model using classical neural networks. After the comparison, the LSTM model demonstrates higher accuracy than the physical model IDM in terms of car-following behavior and displays better performance with regard to both car-following and lane-changing behavior compared to the classical neural network model.

Keywords: traffic modeling, neural networks, LSTM, car-following, lane-change

Procedia PDF Downloads 236

Authors: Konstantinos Perifanos, Eirini Florou, Dionysis Goutsos

Abstract:

This paper presents and benchmarks a number of end-to-end Deep Learning based models for metaphor detection in Greek. We combine Convolutional Neural Networks and Recurrent Neural Networks with representation learning to bear on the metaphor detection problem for the Greek language. The models presented achieve exceptional accuracy scores, significantly improving the previous state-of-the-art results, which had already achieved accuracy 0.82. Furthermore, no special preprocessing, feature engineering or linguistic knowledge is used in this work. The methods presented achieve accuracy of 0.92 and F-score 0.92 with Convolutional Neural Networks (CNNs) and bidirectional Long Short Term Memory networks (LSTMs). Comparable results of 0.91 accuracy and 0.91 F-score are also achieved with bidirectional Gated Recurrent Units (GRUs) and Convolutional Recurrent Neural Nets (CRNNs). The models are trained and evaluated only on the basis of training tuples, the related sentences and their labels. The outcome is a state-of-the-art collection of metaphor detection models, trained on limited labelled resources, which can be extended to other languages and similar tasks.

Keywords: metaphor detection, deep learning, representation learning, embeddings

Procedia PDF Downloads 137

Authors: Bojan Najdenov, Danco Davcev

Abstract:

Reduction of traffic congestions and the effects of pollution and waste of resources that come with them has been a big challenge in the past decades. Having reliable systems to facilitate the process of modeling and prediction of traffic conditions would not only reduce the environmental pollution, but will also save people time and money. Social networks play big role of people’s lives nowadays providing them means of communicating and sharing thoughts and ideas, that way generating huge knowledge bases by crowdsourcing. In addition to that, crowdsourcing as a concept provides mechanisms for fast and relatively reliable data generation and also many services are being used on regular basis because they are mainly powered by the public as main content providers. In this paper we present the Social-NETS-Traffic-Control System (SNTCS) that should serve as a facilitator in the process of modeling and prediction of traffic congestions. The main contribution of our system is to integrate data from social networks as Twitter and also implements a custom created crowdsourcing subsystem with which users report traffic conditions using an android application. Our first experience of the usage of the system confirms that the integrated approach allows easy extension of the system with other social networks and represents a very useful tool for traffic control.

Keywords: traffic, congestion reduction, crowdsource, social networks, twitter, android

Procedia PDF Downloads 467

Authors: A. Melka, N. Slater, A. Mualem, Y. Louzoun

Abstract:

Networks are often presented as containing a “core” and a “periphery.” The existence of a core suggests that some vertices are central and form the skeleton of the network, to which all other vertices are connected. An alternative view of graphs is through communities. Multiple measures have been proposed for dense communities in graphs, the most classical being k-cliques, k-cores, and k-plexes, all presenting groups of tightly connected vertices. We here show that the edge number thresholds for such communities to emerge and for their percolation into a single dense connectivity component are very close, in all networks studied. These percolating cliques produce a natural core and periphery structure. This result is generic and is tested in configuration models and in real-world networks. This is also true for k-cores and k-plexes. Thus, the emergence of this connectedness among communities leading to a core is not dependent on some specific mechanism but a direct result of the natural percolation of dense communities.

Keywords: cliques, core structure, percolation, phase transition

Procedia PDF Downloads 158

Authors: Mahdi Jalili

Abstract:

Functional connectivity in the human brain can be represented as a network using electroencephalography (EEG) signals. Network representation of EEG time series can be an efficient vehicle to understand the underlying mechanisms of brain function. Brain functional networks – whose nodes are brain regions and edges correspond to functional links between them – are characterized by neurobiologically meaningful graph theory metrics. This study investigates the degree to which graph theory metrics are sex dependent. To this end, EEGs from 24 healthy female subjects and 21 healthy male subjects were recorded in eyes-closed resting state conditions. The connectivity matrices were extracted using correlation analysis and were further binarized to obtain binary functional networks. Global and local efficiency measures – as graph theory metrics– were computed for the extracted networks. We found that male brains have a significantly greater global efficiency (i.e., global communicability of the network) across all frequency bands for a wide range of cost values in both hemispheres. Furthermore, for a range of cost values, female brains showed significantly greater right-hemispheric local efficiency (i.e., local connectivity) than male brains.

Keywords: EEG, brain, functional networks, network science, graph theory

Procedia PDF Downloads 430

Authors: R. Byler

Abstract:

Innovation, particularly in technology development, is a crucial aspect of nanotechnology R&D and, although several approaches to effective innovation management exist, organizational structures that promote knowledge exchange have been found to be most effect in supporting new and emerging technologies. This paper discusses Integrated Knowledge Networks (IKNs) and evaluates its use within nanotechnology R&D to increase technology innovation. Specifically, this paper reviews the role of IKNs in bolstering national and international nanotechnology development and in enhancing nanotechnology innovation. Both physical and virtual IKNs, particularly IT-based network platforms for community-based innovation, offer strategies for enhanced technology innovation, interdisciplinary cooperation, and enterprise development. Effectively creating and managing technology R&D networks can facilitate successful knowledge exchange, enhanced innovation, commercialization, and technology transfer. As such, IKNs are crucial to technology development processes and, thus, in increasing the quality and access to new, innovative nanoscience and technologies worldwide.

Keywords: community-based innovation, integrated knowledge networks, nanotechnology, technology innovation

Procedia PDF Downloads 395

Authors: Nazmul Shahadat, Anthony S. Maida

Abstract:

In recent years, hypercomplex inspired neural networks improved deep CNN architectures due to their ability to share weights across input channels and thus improve cohesiveness of representations within the layers. The work described herein studies the effect of replacing existing layers in an Axial Attention ResNet with their quaternion variants that use cross-channel weight sharing to assess the effect on image classification. We expect the quaternion enhancements to produce improved feature maps with more interlinked representations. We experiment with the stem of the network, the bottleneck layer, and the fully connected backend by replacing them with quaternion versions. These modifications lead to novel architectures which yield improved accuracy performance on the ImageNet300k classification dataset. Our baseline networks for comparison were the original real-valued ResNet, the original quaternion-valued ResNet, and the Axial Attention ResNet. Since improvement was observed regardless of which part of the network was modified, there is a promise that this technique may be generally useful in improving classification accuracy for a large class of networks.

Keywords: axial attention, representational networks, weight sharing, cross-channel correlations, quaternion-enhanced axial attention, deep networks

Procedia PDF Downloads 67

Authors: Muhammet Baldan, Emel Timuçin

Abstract:

Generally, absorption and bioavailability increase if solubility increases; therefore, it is crucial to predict them in drug discovery applications. Molecular descriptors and Molecular properties are traditionally used for the prediction of water solubility. There are various key descriptors that are used for this purpose, namely Drogan Descriptors, Morgan Descriptors, Maccs keys, etc., and each has different prediction capabilities with differentiating successes between different data sets. Another source for the prediction of solubility is structural features; they are commonly used for the prediction of solubility. However, there are little to no studies that combine three or more properties or descriptors for prediction to produce a more powerful prediction model. Unlike available models, we used a combination of those features in a random forest machine learning model for improved solubility prediction to better predict and, therefore, contribute to drug discovery systems.

Keywords: solubility, random forest, molecular descriptors, maccs keys

Procedia PDF Downloads 27

Authors: Ncoza Dlova, Tivani Mashamba-Thompson

Abstract:

Garcinia livingstonei (Clusiaceae) extracts, morelloflavone- 7″- sulphate and sargaol were shown to be effective against hyper-pigmentation through inhibition of tyrosinase enzyme, in vitro . The aim of this study is to elucidate the structural mechanism through which morelloflavone- 7″- sulphate and sargaol binds human tyrosinase. Implementing a homology model to construct a tyrosinase model using the crystal structure of a functional unit from Octopus hemocyanin (PDB: 1JS8) as a reference template enabled us to create a human tyrosinase model. Molecular dynamics and binding free energy calculations were optimized to enable molecular dynamics simulation of the copper dependent inhibitors. Results show the importance of the hydrogen bond formation morelloflavone- 7″- sulphate and sargaol between compound and active site residues. Both complexes demonstrated the metallic coordination between compound and arginine residue as well as copper ions within the active site. The comprehensive molecular insight gained from this study should be vital in understanding the binding mechanism morelloflavone- 7″- sulphate and sargaol. Moreover, these results will assist in the design of novel of metal ion dependent enzyme inhibitors as potential anti-hyper-pigmentation disorder therapies.

Keywords: hyper-pigmentation disorders, dyschromia African skin, morelloflavone- 7″- sulphate, sagoal

Procedia PDF Downloads 393

Authors: Raya Hamed Hial Al Maamari

Abstract:

The gulf societies have been undergoing radical changes because of the technology transfer. It altered the humanities attitudes. Especially, youth habits so they become a fond of using social networking. This study aimed to find out the ratio of social networking in Directing youth to participate with government institutions in decision-making and improving their societies. The study considered a descriptive study, social survey method was used on a sample of 100 young men from different gulf countries, using an electronic questionnaire, with some interviews with famous leaders of youth groups. Finally, the researchers suggested many effective views to activate youth efforts using social networks as an effective manner to plan for the development policy and Implemented accurately in the community. The findings illustrated that social networks play a vital role in encouraging youth to participate Enthusiastically in providing the service. As it notices these networks contain large numbers of youth. Therefore, the influences become widely and feasible. Moreover, the study indicated the fact that most of youth teamwork started in these social networks. Then, it has been growing to the real society.

Keywords: social work, volunteering, youth, community

Procedia PDF Downloads 328

Authors: Min Kyung An, Hyuk Cho

Abstract:

In this paper, we study the Minimum Latency Broadcast Scheduling (MLBS) problem in wireless sensor networks (WSNs). The main issue of the MLBS problem is to compute schedules with the minimum number of timeslots such that a base station can broadcast data to all other sensor nodes with no collisions. Unlike existing works that utilize the traditional omni-directional WSNs, we target the directional WSNs where nodes can collaboratively determine and orientate their antenna directions. We first develop a 7-approximation algorithm, adopting directional WSNs. Our ratio is currently the best, to the best of our knowledge. We then validate the performance of the proposed algorithm through simulation.

Keywords: broadcast, collision-free, directional antenna, approximation, wireless sensor networks

Procedia PDF Downloads 332

Authors: Amrita Anil Agashe, Sumant Tapas, Ajay Verma Yogesh Sonavane, Sourabh Yeravar

Abstract:

Due to advancement in MEMS technology today wireless sensors network has gained a lot of importance. The wide range of its applications includes environmental and habitat monitoring, object localization, target tracking, security surveillance etc. Wireless sensor networks consist of tiny sensor devices called as motes. The constrained computation power, battery power, storage capacity and communication bandwidth of the tiny motes pose challenging problems in the design and deployment of such systems. In this paper, we propose a ubiquitous framework for Real-Time Tracking, Sensing and Management System using IITH motes. Also, we explain the algorithm that we have developed for location management in wireless sensor networks with the aspect of mobility. Our developed framework and algorithm can be used to detect emergency events and safety threats and provides warning signals to handle the emergency.

Keywords: mobility management, motes, multihop, wireless sensor networks

Procedia PDF Downloads 406

Authors: Ewelina Nowak, Anna Wisla-Swider, Krzysztof Danel

Abstract:

Aqueous suspensions of DNA were illuminated with linearly polarized visible light and ultraviolet for 5, 15, 20 and 40 h. In order to check the nature of modification, DNA interactions were characterized by FTIR spectroscopy. For each illuminated sample, weight average molecular weight and hydrodynamic radius were measured by high pressure size exclusion chromatography. Resulting optical changes for illuminated DNA were investigated using UV-Vis spectra and photoluminescent. Optical properties show potential application in sensors based on modified DNA. Then selected DNA-surfactant complexes were illuminated with electromagnetic radiation for 5h. Molecular structure, optical characteristic were examinated for obtained complexes. Illumination led to changes of complexes physicochemical properties as compared with native DNA. Observed changes were induced by rearrangement of the molecular structure of DNA chains.

Keywords: biopolymers, deoxyribonucleic acid, ionic liquids, linearly polarized visible light, ultraviolet

Procedia PDF Downloads 199

Authors: F. S. Irwansyah, I. Farida, Y. Maulana

Abstract:

Studying chemistry requires the ability to understand three levels of understanding in the form of macroscopic, submicroscopic and symbolic, but the lack of emphasis on the submicroscopic level leads to the understanding of chemical concepts becoming incomplete, due to the limitations of the tools capable of providing visualization of submicroscopic concepts. The purpose of this study describes the stages of making augmented reality learning media on the concept of molecular geometry and analyze the feasibility test result of augmented reality learning media on the concept of molecular geometry. This research uses Research and Development (R & D) method which produces a product of AR learning media on molecular geometry concept and test the effectiveness of the product. Research stages include concept analysis and learning indicators, design development, validation, feasibility, and limited testing. The stages of validation and limited trial are aimed to get feedback in the form of assessment, suggestion and improvement on learning aspect, material substance aspect, visual communication aspect and software engineering aspects and media feasibility in terms of media creation purpose to be used in learning. The results of the overall feasibility test obtained r-calculation 0,7-0,9 with the interpretation of high feasibility value, whereas the result of limited trial got the percentage of eligibility with the average value equal to 70,83-92,5%. This percentage indicates that AR's learning media product on the concept of molecular geometry, deserves to be used as a learning resource.

Keywords: android, augmented reality, chemical learning, geometry

Procedia PDF Downloads 199

Authors: M. S. Mrudula, M. R. Gopinathan Nair

Abstract:

In order to utilize the natural rubber for developing new green polymeric materials for specialty applications, we have prepared natural rubber and polyethylene oxide based polymeric networks by two shot method. The polymeric networks thus formed have been used as chelating exchanger for metal ion binding. Chelating exchangers are, in general, coordinating copolymers containing one or more electron donor atoms such as N, S, O, and P that can form coordinate bonds with metals. Hydrogels are water- swollen network of hydrophilic homopolymer or copolymers. They acquire a great interest due to the facility of the incorporation of different chelating groups into the polymeric networks. Such polymeric hydrogels are promising materials in the field of hydrometallurgical applications and water purification due to their chemical stability. The current study discusses the swelling response of the polymeric networks as a function of time, temperature, pH and [NaCl] and sorption studies. Equilibrium swelling has been observed to depend on both structural aspects of the polymers and environmental factors. Metal ion sorption shows that these polymeric networks can be used for removal, separation, and enrichment of metal ions from aqueous solutions and can play an important role for environmental remediation of municipal and industrial wastewater.

Keywords: block copolymer, adsorption, chelating exchanger, swelling study, polymer, metal complexes

Procedia PDF Downloads 330

Authors: Abdul Majid, Alia Jabeen, Nimra Zulifqar

Abstract:

The inorganic molecular crystal (IMCs) due to their unusual structure has grabbed a lot of attention due to anisotropy in crystal structure. The IMCs consist of the molecular structures joined together via weak forces. Therefore, a difference between the bonding between the inter-cage and intra-cage interactions exists. To look closely at the bonding and interactions, we investigated interactions between two cages of Sb2O3 structure. The interactions were characterized via Extended Transition State-Natural Orbital for Chemical Valence-method (ETS-NOCV), Natural Bond Orbitals (NBO) and Quantum Theory of Atoms in Molecules (QTAIM). The results revealed strong intra-cage covalent bonding while weak van der Waals (vdWs) interactions along inter-cages exits. This structure cannot be termed as layered material although they have anisotropy in bonding and presence of weak vdWs interactions but its bulk is termed as inorganic layered clusters. This is due to the fact that the free standing sheet/films with these materials are not possible. This type of structures may be the most feasible to be used for the system to deal with high pressures and stress bearing materials.

Keywords: inorganic molecular crystals, density functional theory, cages, interactions

Procedia PDF Downloads 76

Authors: Fayez Mostafa Alhamoui, Adnan Hadi Mahdi Al- Helali

Abstract:

The main issue in designing a wireless sensor network (WSN) is the finding of a proper routing protocol that complies with the several requirements of high reliability, short latency, scalability, low power consumption, and many others. This paper proposes a novel routing algorithm that complies with these design requirements. The new routing protocol divides the WSN into several sub-networks and each sub-network is divided into several clusters. This division is designed to reduce the number of radio transmission and hence decreases the power consumption. The network division may be changed dynamically to adapt with the network changes and allows the realization of the design requirements.

Keywords: wireless sensor networks, routing protocols, AD HOC topology, cluster, sub-network, WSN design requirements

Procedia PDF Downloads 525

Authors: Ekaterina A. Savchenko, Elena N. Velichko, Evgenii T. Aksenov

Abstract:

The development of pathological processes, such as cardiovascular and oncological diseases, are accompanied by changes in molecular parameters in cells, tissues, and serum. The study of the behavior of protein molecules in solutions is of primarily importance for diagnosis of such diseases. Various physical and chemical methods are used to study molecular systems. With the advent of the laser and advances in electronics, optical methods, such as scanning electron microscopy, sedimentation analysis, nephelometry, static and dynamic light scattering, have become the most universal, informative and accurate tools for estimating the parameters of nanoscale objects. The electrophoretic light scattering is the most effective technique. It has a high potential in the study of biological solutions and their properties. This technique allows one to investigate the processes of aggregation and dissociation of different macromolecules and obtain information on their shapes, sizes and molecular weights. Electrophoretic light scattering is an analytical method for registration of the motion of microscopic particles under the influence of an electric field by means of quasi-elastic light scattering in a homogeneous solution with a subsequent registration of the spectral or correlation characteristics of the light scattered from a moving object. We modified the technique by using the regime of total internal reflection with the aim of increasing its sensitivity and reducing the volume of the sample to be investigated, which opens the prospects of automating simultaneous multiparameter measurements. In addition, the method of total internal reflection allows one to study biological fluids on the level of single molecules, which also makes it possible to increase the sensitivity and the informativeness of the results because the data obtained from an individual molecule is not averaged over an ensemble, which is important in the study of bimolecular fluids. To our best knowledge the study of electrophoretic light scattering in the regime of total internal reflection is proposed for the first time, latex microspheres 1 μm in size were used as test objects. In this study, the total internal reflection regime was realized on a quartz prism where the free electrophoresis regime was set. A semiconductor laser with a wavelength of 655 nm was used as a radiation source, and the light scattering signal was registered by a pin-diode. Then the signal from a photodetector was transmitted to a digital oscilloscope and to a computer. The autocorrelation functions and the fast Fourier transform in the regime of Brownian motion and under the action of the field were calculated to obtain the parameters of the object investigated. The main result of the study was the dependence of the autocorrelation function on the concentration of microspheres and the applied field magnitude. The effect of heating became more pronounced with increasing sample concentrations and electric field. The results obtained in our study demonstrated the applicability of the method for the examination of liquid solutions, including biological fluids.

Keywords: light scattering, electrophoretic light scattering, electrophoresis, total internal reflection

Procedia PDF Downloads 202

Authors: K. Kalaiarasan, B. Pandeeswari, A. Arockia John Francis

Abstract:

Wireless, Multi-hop networks consist of one or more intermediate nodes along the path that receive and forward packets via wireless links. The backpressure algorithm provides throughput optimal routing and scheduling decisions for multi-hop networks with dynamic traffic. Xpress, a cross-layer backpressure architecture was designed to reach the capacity of wireless multi-hop networks and it provides well coordination between layers of network by turning a mesh network into a wireless switch. Transmission over the network is scheduled using a throughput-optimal backpressure algorithm. But this architecture operates much below their capacity due to out-of-order packet delivery and variable packet size. In this paper, we present Xpress-T, a throughput optimal backpressure architecture with TCP support designed to reach maximum throughput of wireless multi-hop networks. Xpress-T operates at the IP layer, and therefore any transport protocol, including TCP, can run on top of Xpress-T. The proposed design not only avoids bottlenecks but also handles out-of-order packet delivery and variable packet size, optimally load-balances traffic across them when needed, improving fairness among competing flows. Our simulation results shows that Xpress-T gives 65% more throughput than Xpress.

Keywords: backpressure scheduling and routing, TCP, congestion control, wireless multihop network

Procedia PDF Downloads 509

Authors: Ayesha Waqar Khan, Mariam Altaf, Jamil Ahmad, Shaheen Shahzad

Abstract:

Kidney fibrosis is an anticipated outcome of possibly all types of progressive chronic kidney disease (CKD). Epithelial-mesenchymal transition (EMT) signaling pathway is responsible for production of matrix-producing fibroblasts and myofibroblasts in diseased kidney. In this study, a discrete model of TGF-beta (transforming growth factor) and CTGF (connective tissue growth factor) was constructed using Rene Thomas formalism to investigate renal fibrosis turn over. The kinetic logic proposed by Rene Thomas is a renowned approach for modeling of Biological Regulatory Networks (BRNs). This modeling approach uses a set of constraints which represents the dynamics of the BRN thus analyzing the pathway and predicting critical trajectories that lead to a normal or diseased state. The molecular connection between TGF-beta, Smad 2/3 (transcription factor) phosphorylation and CTGF is modeled using GenoTech. The order of BRN is CTGF, TGF-B, and SMAD3 respectively. The predicted cycle depicts activation of TGF-B (TGF-β) via cleavage of its own pro-domain (0,1,0) and presentation to TGFR-II receptor phosphorylating SMAD3 (Smad2/3) in the state (0,1,1). Later TGF-B is turned off (0,0,1) thereby activating SMAD3 that further stimulates the expression of CTGF in the state (1,0,1) and itself turns off in (1,0,0). Elevated CTGF expression reactivates TGF-B (1,1,0) and the cycle continues. The predicted model has generated one cycle and two steady states. Cyclic behavior in this study represents the diseased state in which all three proteins contribute to renal fibrosis. The proposed model is in accordance with the experimental findings of the existing diseased state. Extended cycle results in enhanced CTGF expression through Smad2/3 and Smad4 translocation in the nucleus. The results suggest that the system converges towards organ fibrogenesis if CTGF remains constructively active along with Smad2/3 and Smad 4 that plays an important role in kidney fibrosis. Therefore, modeling regulatory pathways of kidney fibrosis will escort to the progress of therapeutic tools and real-world useful applications such as predictive and preventive medicine.

Keywords: CTGF, renal fibrosis signaling pathway, system biology, qualitative modeling

Procedia PDF Downloads 168

Authors: Jungkyun Im

Abstract:

Nonsteroidal anti-inflammatory drugs (NSAIDs) are effective for relieving pain and reducing inflammation. They are nonselective inhibitors of two isoforms of COX, cyclooxygenase-1 (COX-1) and cyclooxygenase-2 (COX-2), and thereby inhibiting the production of hormone-like lipid compounds such as, prostaglandins and thromboxanes which cause inflammation, pain, fever, platelet aggregation, etc. In addition, recently there are many research articles reporting the neuroprotective effect of NSAIDs in neurodegenerative diseases, such as Alzheimer’s disease (AD) and Parkinson’s disease (PD). However, the clinical use of NSAIDs in these diseases is limited by low brain distribution. Therefore, in order to assist the in-depth investigation on the pharmaceutical mechanism of flurbiprofen in neuroprotection and to make flurbiprofen a more potent drug to prevent or alleviate neurodegenerative diseases, delivery of flurbiprofen to brain should be effective and sufficient amount of flurbiprofen must penetrate the BBB thus gaining access into the patient’s brain. We have recently developed several types of guanidine-rich molecular carriers with high molecular weights and good water solubility that readily cross the blood-brain barrier (BBB) and display efficient distributions in the mouse brain. The G8 (having eight guanidine groups) molecular carrier based on D-sorbitol was found to be very effective in delivering anticancer drugs to a mouse brain. In the present study, employing the same molecular carrier, we prepared the flurbiprofen conjugate and studied its BBB permeation by mouse tissue distribution study. Flurbiprofen was attached to a molecular carrier with a fluorescein probe and multiple terminal guanidiniums. The conjugate was found to internalize into live cells and readily cross the BBB to enter the mouse brain. Our novel synthetic flurbiprofen conjugate will hopefully delivery NSAIDs into brain, and is therefore applicable to the neurodegenerative diseases treatment or prevention.

Keywords: flurbiprofen, drug delivery, molecular carrier, organic synthesis

Procedia PDF Downloads 225

Authors: Rade M. Ciric

Abstract:

The paper shows the development and implementation of the syllabus of the subject 'Distribution and Industrial Networks', attended by the vocational specialist Year 4 students of the Electric Power Engineering study programme at the Higher Education Technical School of Vocational Studies in Novi Sad. The aim of the subject is to equip students with the knowledge necessary for planning, exploitation and management of distributive and industrial electric power networks in an open electricity market environment. The results of the evaluation of educational outcomes on the subject are presented and discussed.

Keywords: engineering education, power distribution network, syllabus implementation, outcome evaluation

Procedia PDF Downloads 387

Authors: Amandeep Singh Dhaliwal

Abstract:

Networking solutions, particularly wireless local area networks have revolutionized the technological advancement. Wireless Local Area Networks (WLANs) have gained a lot of popularity as they provide location-independent network access between computing devices. There are a number of access methods used in Wireless Networks among which DCF and PCF are the fundamental access methods. This paper emphasizes on the impact of DCF and PCF access mechanisms on the performance of the IEEE 802.11a, 802.11b and 802.11g standards. On the basis of various parameters viz. throughput, delay, load etc performance is evaluated between these three standards using above mentioned access mechanisms. Analysis revealed a superior throughput performance with low delays for 802.11g standard as compared to 802.11 a/b standard using both DCF and PCF access methods.

Keywords: DCF, IEEE, PCF, WLAN

Procedia PDF Downloads 411

Authors: Sipu Guo, Silin Huang

Abstract:

Background: Most studies investigate the link between executive function and allostatic load (AL) among adults aged 18 years and older. Studies differed regarding the specific biological indicators studied and executive functions accounted for. Specific executive functions may be differentially related to allostatic load. We investigated the comorbidities of executive functions and allostatic load via network analysis. Methods: We included 603 adolescents (49.84% girls; Mean age = 12.38, SD age = 1.79) from junior high school in rural China. Eight biological markers at T1 and four executive function tasks at T2 were used to evaluate networks. Network analysis was used to determine the network structure, core symptoms, and bridge symptoms in the AL-executive function network among rural adolescents. Results: The executive functions were related to 6 AL biological markers, not to cortisol and epinephrine. The most influential symptoms were inhibition control, cognitive flexibility, processing speed, and systolic blood pressure (SBP). SBP, dehydroepiandrosterone, and processing speed were the bridges through which AL was related to executive functions. dehydroepiandrosterone strongly predicted processing speed. The SBP was the biggest influencer in the entire network. Conclusions: We found evidence for differential relations between markers and executive functions. SBP was a driver in the network; dehydroepiandrosterone showed strong relations with executive function.

Keywords: allostatic load, executive function, network analysis, rural adolescent

Procedia PDF Downloads 39