Search results for: cellular neural networks.
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2556

Search results for: cellular neural networks.

756 The Expression of a Novel Gene Encoding an Ankyrin-Repeat Protein, DRA1, is Regulated by Drought-Responsive Alternative Splicing

Authors: H. Sakamoto, Y. Nakagawara, S. Oguri

Abstract:

Drought stress is a critical environmental factor that adversely affects crop productivity and quality. Because of their immobile nature, plants have evolved mechanisms to sense and respond to drought stress. We identified a novel locus of Arabidopsis, designated DRA1 (drought responsive ankyrin1), whose disruption leads to increased drought-stress tolerance. DRA1 encodes a transmembrane protein with an ankyrin-repeat motif that has been implicated in diverse cellular processes such as signal transduction. RT-PCR analysis revealed that there were at least two splicing variants of DRA1 transcripts in wild-type plants. In response to drought stress, the levels of DRA1 transcripts retaining second and third introns were increased, whereas these introns were removed under unstressed conditions. These results suggest that DRA1 protein may negatively regulate plant drought tolerance and that the expression of DRA1is regulated in response to drought stress by alternative splicing.

Keywords: Alternative splicing, ankyrin repeat, Arabidopsis, drought tolerance.

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755 The Expression of a Novel Gene Encoding an Ankyrin-Repeat Protein, DRA1, is Regulated by Drought-Responsive Alternative Splicing

Authors: H. Sakamoto, Y. Nakagawara, S. Oguri

Abstract:

Drought stress is a critical environmental factor that adversely affects crop productivity and quality. Because of their immobile nature, plants have evolved mechanisms to sense and respond to drought stress. We identified a novel locus of Arabidopsis, designated DRA1 (drought responsive ankyrin1), whose disruption leads to increased drought-stress tolerance. DRA1 encodes a transmembrane protein with an ankyrin-repeat motif that has been implicated in diverse cellular processes such as signal transduction. RT-PCR analysis revealed that there were at least two splicing variants of DRA1 transcripts in wild-type plants. In response to drought stress, the levels of DRA1 transcripts retaining second and third introns were increased, whereas these introns were removed under unstressed conditions. These results suggest that DRA1 protein may negatively regulate plant drought tolerance and that the expression of DRA1is regulated in response to drought stress by alternative splicing.

Keywords: Alternative splicing, ankyrin repeat, Arabidopsis, drought tolerance.

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754 Effects of Stiffness on Endothelial Cells Behavior

Authors: Forough Ataollahi, Belinda Pingguan-Murphy, Wan Abu Bakar Wan Abas, Noor Azuan Abu Osman

Abstract:

Endothelium proliferation is an important process in cardiovascular homeostasis and can be regulated by extracellular environment, as cells can actively sense mechanical environment. In this study, we evaluated endothelial cell proliferation on PDMS/alumina (Al2O3) composites and pure PDMS. The substrates were prepared from pure PDMS and its composites with 5% and 10% Al2O3 at curing temperature 50˚C for 4h and then characterized by mechanical, structural and morphological analyses. Higher stiffness was found in the composites compared to the pure PDMS substrate. Cell proliferation of the cultured bovine aortic endothelial cells on substrate materials were evaluated via Resazurin assay and 1, 1’-Dioctadecyl-1, 3, 3, 3’, 3’-Tetramethylindocarbocyanine Perchlorate-Acetylated LDL (Dil-Ac-LDL) cell staining, respectively. The results revealed that stiffer substrates promote more endothelial cells proliferation to the less stiff substrates. Therefore, this study firmly hypothesizes that the stiffness elevates endothelial cells proliferation.

Keywords: Bovine aortic endothelial cells, extra cellular matrix, proliferation, stiffness.

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753 Blood Cell Dynamics in a Simple Shear Flow using an Implicit Fluid-Structure Interaction Method Based on the ALE Approach

Authors: Choeng-Ryul Choi, Chang-Nyung Kim, Tae-Hyub Hong

Abstract:

A numerical method is developed for simulating the motion of particles with arbitrary shapes in an effectively infinite or bounded viscous flow. The particle translational and angular motions are numerically investigated using a fluid-structure interaction (FSI) method based on the Arbitrary-Lagrangian-Eulerian (ALE) approach and the dynamic mesh method (smoothing and remeshing) in FLUENT ( ANSYS Inc., USA). Also, the effects of arbitrary shapes on the dynamics are studied using the FSI method which could be applied to the motions and deformations of a single blood cell and multiple blood cells, and the primary thrombogenesis caused by platelet aggregation. It is expected that, combined with a sophisticated large-scale computational technique, the simulation method will be useful for understanding the overall properties of blood flow from blood cellular level (microscopic) to the resulting rheological properties of blood as a mass (macroscopic).

Keywords: Blood Flow, Fluid-Structure Interaction (FSI), Micro-Channels, Arbitrary Shapes, Red Blood Cells (RBCs)

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752 Self-Organization of Clusters Having Locally Distributed Patterns for Highly Synchronized Inputs

Authors: Toshio Akimitsu, Yoichi Okabe, Akira Hirose

Abstract:

Many experimental results suggest that more precise spike timing is significant in neural information processing. We construct a self-organization model using the spatiotemporal pat-terns, where Spike-Timing Dependent Plasticity (STDP) tunes the conduction delays between neurons. We show that, for highly syn-chronized inputs, the fluctuation of conduction delays causes globally continuous and locally distributed firing patterns through the self-organization.

Keywords: Self-organization, synfire-chain, Spike-Timing DependentPlasticity, distributed information representation.

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751 Self Organizing Analysis Platform for Wear Particle

Authors: Qurban A. Memon, Mohammad S. Laghari

Abstract:

Integration of system process information obtained through an image processing system with an evolving knowledge database to improve the accuracy and predictability of wear particle analysis is the main focus of the paper. The objective is to automate intelligently the analysis process of wear particle using classification via self organizing maps. This is achieved using relationship measurements among corresponding attributes of various measurements for wear particle. Finally, visualization technique is proposed that helps the viewer in understanding and utilizing these relationships that enable accurate diagnostics.

Keywords: Neural Network, Relationship Measurement, Selforganizing Clusters, Wear Particle Analysis.

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750 How Virtualization, Decentralization and Network Building Change the Manufacturing Landscape: An Industry 4.0 Perspective

Authors: Malte Brettel, Niklas Friederichsen, Michael Keller, Marius Rosenberg

Abstract:

The German manufacturing industry has to withstand an increasing global competition on product quality and production costs. As labor costs are high, several industries have suffered severely under the relocation of production facilities towards aspiring countries, which have managed to close the productivity and quality gap substantially. Established manufacturing companies have recognized that customers are not willing to pay large price premiums for incremental quality improvements. As a consequence, many companies from the German manufacturing industry adjust their production focusing on customized products and fast time to market. Leveraging the advantages of novel production strategies such as Agile Manufacturing and Mass Customization, manufacturing companies transform into integrated networks, in which companies unite their core competencies. Hereby, virtualization of the process- and supply-chain ensures smooth inter-company operations providing real-time access to relevant product and production information for all participating entities. Boundaries of companies deteriorate, as autonomous systems exchange data, gained by embedded systems throughout the entire value chain. By including Cyber-Physical-Systems, advanced communication between machines is tantamount to their dialogue with humans. The increasing utilization of information and communication technology allows digital engineering of products and production processes alike. Modular simulation and modeling techniques allow decentralized units to flexibly alter products and thereby enable rapid product innovation. The present article describes the developments of Industry 4.0 within the literature and reviews the associated research streams. Hereby, we analyze eight scientific journals with regards to the following research fields: Individualized production, end-to-end engineering in a virtual process chain and production networks. We employ cluster analysis to assign sub-topics into the respective research field. To assess the practical implications, we conducted face-to-face interviews with managers from the industry as well as from the consulting business using a structured interview guideline. The results reveal reasons for the adaption and refusal of Industry 4.0 practices from a managerial point of view. Our findings contribute to the upcoming research stream of Industry 4.0 and support decision-makers to assess their need for transformation towards Industry 4.0 practices. 

Keywords: Industry 4.0., Mass Customization, Production networks, Virtual Process-Chain.

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749 New Device for Enhancement of Liposomal Magnetofection Efficiency of Cancer Cells

Authors: M. Baryshev, D.Vainauska, S. Kozireva, A.Karpovs

Abstract:

Liposomal magnetofection is the most powerful nonviral method for the nucleic acid delivery into the cultured cancer cells and widely used for in vitro applications. Use of the static magnetic field condition may result in non-uniform distribution of aggregate complexes on the surface of cultured cells. To prevent this, we developed the new device which allows to concentrate aggregate complexes under dynamic magnetic field, assisting more contact of these complexes with cellular membrane and, possibly, stimulating endocytosis. Newly developed device for magnetofection under dynamic gradient magnetic field, “DynaFECTOR", was used to compare transfection efficiency of human liver hepatocellular carcinoma cell line HepG2 with that obtained by lipofection and magnetofection. The effect of two parameters on transfection efficiency, incubation time under dynamic magnetic field and rotation frequency of magnet, was estimated. Liposomal magnetofection under dynamic gradient magnetic field showed the highest transfection efficiency for HepG2 cells.

Keywords: Dynamic magnetic field, Lipofection, Magnetofection

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748 Effect of Plasma Therapy on Epidermal Regeneration

Authors: Magda Bădescu, Daniela Jitaru, C.Grigoraş, L.Bădescu, I. Topala, Manuela Ciocoiu

Abstract:

The purpose of our study was to compare spontaneous re-epithelisation characteristics versus assisted re-epithelisation. In order to assess re-epithelisation of the injured skin, we have imagined and designed a burn wound model on Wistar rat skin. Our aim was to create standardised, easy reproducible and quantifiable skin lesions involving entire epidermis and superficial dermis. We then have applied the above mentioned therapeutic strategies to compare regeneration of epidermis and dermis, local and systemic parameter changes in different conditions. We have enhanced the reepithelisation process under a moist atmosphere of a polyurethane wound dress modified with helium non-thermal plasma, and with the aid of direct cold-plasma treatment respectively. We have followed systemic parameters change: hematologic and biochemical parameters, and local features: oxidative stress markers and histology of skin in the above mentioned conditions. Re-epithelisation is just a part of the skin regeneration process, which recruits cellular components, with the aid of epidermal and dermal interaction via signal molecules.

Keywords: Plasma medicine, re-epithelisation and tissue regeneration

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747 Immunomodulatory Effects of Multipotent Mesenchymal Stromal Cells on T-Cell Populations at Tissue-Related Oxygen Level

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

Abstract:

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

Keywords: Cell-to-cell interaction, low oxygen, MSC immunosuppression, T-cells.

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746 Neuro-Fuzzy System for Equalization Channel Distortion

Authors: Rahib H. Abiyev

Abstract:

In this paper the application of neuro-fuzzy system for equalization of channel distortion is considered. The structure and operation algorithm of neuro-fuzzy equalizer are described. The use of neuro-fuzzy equalizer in digital signal transmission allows to decrease training time of parameters and decrease the complexity of the network. The simulation of neuro-fuzzy equalizer is performed. The obtained result satisfies the efficiency of application of neurofuzzy technology in channel equalization.

Keywords: Neuro-fuzzy system, noise equalization, neuro-fuzzy equalizer, neural system.

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745 Cooperative Cross Layer Topology for Concurrent Transmission Scheduling Scheme in Broadband Wireless Networks

Authors: Gunasekaran Raja, Ramkumar Jayaraman

Abstract:

In this paper, we consider CCL-N (Cooperative Cross Layer Network) topology based on the cross layer (both centralized and distributed) environment to form network communities. Various performance metrics related to the IEEE 802.16 networks are discussed to design CCL-N Topology. In CCL-N topology, nodes are classified as master nodes (Master Base Station [MBS]) and serving nodes (Relay Station [RS]). Nodes communities are organized based on the networking terminologies. Based on CCL-N Topology, various simulation analyses for both transparent and non-transparent relays are tabulated and throughput efficiency is calculated. Weighted load balancing problem plays a challenging role in IEEE 802.16 network. CoTS (Concurrent Transmission Scheduling) Scheme is formulated in terms of three aspects – transmission mechanism based on identical communities, different communities and identical node communities. CoTS scheme helps in identifying the weighted load balancing problem. Based on the analytical results, modularity value is inversely proportional to that of the error value. The modularity value plays a key role in solving the CoTS problem based on hop count. The transmission mechanism for identical node community has no impact since modularity value is same for all the network groups. In this paper three aspects of communities based on the modularity value which helps in solving the problem of weighted load balancing and CoTS are discussed.

Keywords: Cross layer network topology, concurrent scheduling, modularity value, network communities and weighted load balancing.

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744 A Refined Application of QFD in SCM, A New Approach

Authors: Nooshin La'l Mohamadi

Abstract:

Due to the fact that in the new century customers tend to express globally increasing demands, networks of interconnected businesses have been established in societies and the management of such networks seems to be a major key through gaining competitive advantages. Supply chain management encompasses such managerial activities. Within a supply chain, a critical role is played by quality. QFD is a widely-utilized tool which serves the purpose of not only bringing quality to the ultimate provision of products or service packages required by the end customer or the retailer, but it can also initiate us into a satisfactory relationship with our initial customer; that is the wholesaler. However, the wholesalers- cooperation is considerably based on the capabilities that are heavily dependent on their locations and existing circumstances. Therefore, it is undeniable that for all companies each wholesaler possesses a specific importance ratio which can heavily influence the figures calculated in the House of Quality in QFD. Moreover, due to the competitiveness of the marketplace today, it-s been widely recognized that consumers- expression of demands has been highly volatile in periods of production. Apparently, such instability and proneness to change has been very tangibly noticed and taking it into account during the analysis of HOQ is widely influential and doubtlessly required. For a more reliable outcome in such matters, this article demonstrates the application viability of Analytic Network Process for considering the wholesalers- reputation and simultaneously introduces a mortality coefficient for the reliability and stability of the consumers- expressed demands in course of time. Following to this, the paper provides further elaboration on the relevant contributory factors and approaches through the calculation of such coefficients. In the end, the article concludes that an empirical application is needed to achieve broader validity.

Keywords: Analytic Network Process, Quality Function Deployment, QFD flaws, Supply Chain Management

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743 Induction of Hsp70 and Antioxidant Status in Porcine Granulosa Cells in Response to Deoxynivalenol and Zearalenone Exposure in vitro

Authors: Marcela Capcarova, Adriana Kolesarova, Marina Medvedova, Peter Petruska, Alexander V. Sirotkin

Abstract:

The aim of this study was to determine the activity of superoxide dismutase (SOD), glutathione peroxidase (GPx), total antioxidant status (TAS) and accumulation of Hsp70 in porcine ovarian granulosa cells after deoxynivalenol (DON) and zearalenone (ZEA) exposure in vitro. Porcine ovarian granulosa cells were incubated with DON/ZEA administrations as follows: group A (10/10 ng/mL), group B (100/100 ng/mL), group C (1000/1000 ng/mL), and the control group without any additions for 24h. In this study mycotoxins developed stress reaction of porcine ovarian granulosa cells and increased accumulation of Hsp70 what resulted in increasing activities of SOD and GPx in groups with lower doses of mycotoxins. High dose of DON and ZEA had opposite effect on GPx activity than the lower doses. Slight increase in TAS of porcine granulosa cells was observed after mycotoxins exposure. These results contribute towards the understanding of cellular stress and its response.

Keywords: Deoxynivalenol, zearalenone, antioxidants, Hsp70, granulosa cells.

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742 Biochemical Changes in the Liver of Mice after Exposure to Different Doses of Diclofenac Sodium

Authors: Deepak Mohan, Sushma Sharma

Abstract:

Non-Steroidal Anti-Inflammatory Drugs (NSAIDs) are a group of widely used drugs for the treatment of rheumatoid diseases and to relieve pain and inflammation due to their analgesic anti-pyretic and anti-inflammatory properties. The therapeutic and many of the toxic effects of NSAIDs result from reversible inhibition of enzymes in the cyclooxygenase (COX) group. In the present investigation the effect of the drug on the concentration of lipids, and on the activity of the enzymes i.e. acid and alkaline phosphatase, GOT, GPT and lipid peroxidase were studied. There was a significant enhancement in the activities of both acid and alkaline phosphatase after 21 days of treatment. Proportionate increase in the MDA contents was observed after different days of diclofenac treatment. Cellular damage in the liver resulted in decrease in the activity of both GOT (Glutamate oxaloacetate transaminase) and GPT (Glutamate pyruvate transaminase) in both low and high dose groups. Significant decrease in the liver contents was also observed in both dose groups.

Keywords: Anti-inflammatory, cyclooxygenase, glutamate oxaloacetate transaminase, malondialdehyde.

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741 RRNS-Convolutional Concatenated Code for OFDM based Wireless Communication with Direct Analog-to-Residue Converter

Authors: Shahana T. K., Babita R. Jose, K. Poulose Jacob, Sreela Sasi

Abstract:

The modern telecommunication industry demands higher capacity networks with high data rate. Orthogonal frequency division multiplexing (OFDM) is a promising technique for high data rate wireless communications at reasonable complexity in wireless channels. OFDM has been adopted for many types of wireless systems like wireless local area networks such as IEEE 802.11a, and digital audio/video broadcasting (DAB/DVB). The proposed research focuses on a concatenated coding scheme that improve the performance of OFDM based wireless communications. It uses a Redundant Residue Number System (RRNS) code as the outer code and a convolutional code as the inner code. Here, a direct conversion of analog signal to residue domain is done to reduce the conversion complexity using sigma-delta based parallel analog-to-residue converter. The bit error rate (BER) performances of the proposed system under different channel conditions are investigated. These include the effect of additive white Gaussian noise (AWGN), multipath delay spread, peak power clipping and frame start synchronization error. The simulation results show that the proposed RRNS-Convolutional concatenated coding (RCCC) scheme provides significant improvement in the system performance by exploiting the inherent properties of RRNS.

Keywords: Analog-to-residue converter, Concatenated codes, OFDM, Redundant Residue Number System, Sigma-delta modulator, Wireless communication

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740 Network State Classification based on the Statistical properties of RTT for an Adaptive Multi-State Proactive Transport Protocol for Satellite based Networks

Authors: Mohanchur Sakar, K.K.Shukla, K.S.Dasgupta

Abstract:

This paper attempts to establish the fact that Multi State Network Classification is essential for performance enhancement of Transport protocols over Satellite based Networks. A model to classify Multi State network condition taking into consideration both congestion and channel error is evolved. In order to arrive at such a model an analysis of the impact of congestion and channel error on RTT values has been carried out using ns2. The analysis results are also reported in the paper. The inference drawn from this analysis is used to develop a novel statistical RTT based model for multi state network classification. An Adaptive Multi State Proactive Transport Protocol consisting of Proactive Slow Start, State based Error Recovery, Timeout Action and Proactive Reduction is proposed which uses the multi state network state classification model. This paper also confirms through detail simulation and analysis that a prior knowledge about the overall characteristics of the network helps in enhancing the performance of the protocol over satellite channel which is significantly affected due to channel noise and congestion. The necessary augmentation of ns2 simulator is done for simulating the multi state network classification logic. This simulation has been used in detail evaluation of the protocol under varied levels of congestion and channel noise. The performance enhancement of this protocol with reference to established protocols namely TCP SACK and Vegas has been discussed. The results as discussed in this paper clearly reveal that the proposed protocol always outperforms its peers and show a significant improvement in very high error conditions as envisaged in the design of the protocol.

Keywords: GEO, ns2, Proactive TCP, SACK, Vegas

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739 Probabilistic Life Cycle Assessment of the Nano Membrane Toilet

Authors: A. Anastasopoulou, A. Kolios, T. Somorin, A. Sowale, Y. Jiang, B. Fidalgo, A. Parker, L. Williams, M. Collins, E. J. McAdam, S. Tyrrel

Abstract:

Developing countries are nowadays confronted with great challenges related to domestic sanitation services in view of the imminent water scarcity. Contemporary sanitation technologies established in these countries are likely to pose health risks unless waste management standards are followed properly. This paper provides a solution to sustainable sanitation with the development of an innovative toilet system, called Nano Membrane Toilet (NMT), which has been developed by Cranfield University and sponsored by the Bill & Melinda Gates Foundation. The particular technology converts human faeces into energy through gasification and provides treated wastewater from urine through membrane filtration. In order to evaluate the environmental profile of the NMT system, a deterministic life cycle assessment (LCA) has been conducted in SimaPro software employing the Ecoinvent v3.3 database. The particular study has determined the most contributory factors to the environmental footprint of the NMT system. However, as sensitivity analysis has identified certain critical operating parameters for the robustness of the LCA results, adopting a stochastic approach to the Life Cycle Inventory (LCI) will comprehensively capture the input data uncertainty and enhance the credibility of the LCA outcome. For that purpose, Monte Carlo simulations, in combination with an artificial neural network (ANN) model, have been conducted for the input parameters of raw material, produced electricity, NOX emissions, amount of ash and transportation of fertilizer. The given analysis has provided the distribution and the confidence intervals of the selected impact categories and, in turn, more credible conclusions are drawn on the respective LCIA (Life Cycle Impact Assessment) profile of NMT system. Last but not least, the specific study will also yield essential insights into the methodological framework that can be adopted in the environmental impact assessment of other complex engineering systems subject to a high level of input data uncertainty.

Keywords: Sanitation systems, nano membrane toilet, LCA, stochastic uncertainty analysis, Monte Carlo Simulations, artificial neural network.

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738 Combining Gene and Chemo Therapy using Multifunctional Polymeric Micelles

Authors: Hong Yi Huang, Wei Ti Kuo, Yi You Huang

Abstract:

Non-viral gene carriers composed of biodegradable polymers or lipids have been considered as a safer alternative for gene carriers over viral vectors. We have developed multi-functional nano-micelles for both drug and gene delivery application. Polyethyleneimine (PEI) was modified by grafting stearic acid (SA) and formulated to polymeric micelles (PEI-SA) with positive surface charge for gene and drug delivery. Our results showed that PEI-SA micelles provided high siRNA binding efficiency. In addition, siRNA delivered by PEI-SA carriers also demonstrated significantly high cellular uptake even in the presence of serum proteins. The post-transcriptional gene silencing efficiency was greatly improved by the polyplex formulated by 10k PEI-SA/siRNA. The amphiphilic structure of PEI-SA micelles provided advantages for multifunctional tasks; where the hydrophilic shell modified with cationic charges can electrostatically interact with DNA or siRNA, and the hydrophobic core can serve as payloads for hydrophobic drugs, making it a promising multifunctional vehicle for both genetic and chemotherapy application.

Keywords: polyethyleneimine, gene delivery, micelles, siRNA

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737 Survey of Communication Technologies for IoT Deployments in Developing Regions

Authors: Namugenyi Ephrance Eunice, Julianne Sansa Otim, Marco Zennaro, Stephen D. Wolthusen

Abstract:

The Internet of Things (IoT) is a network of connected data processing devices, mechanical and digital machinery, items, animals, or people that may send data across a network without requiring human-to-human or human-to-computer interaction. Each component has sensors that can pick up on specific phenomena, as well as processing software and other technologies that can link to and communicate with other systems and/or devices over the Internet or other communication networks and exchange data with them. IoT is increasingly being used in fields other than consumer electronics, such as public safety, emergency response, industrial automation, autonomous vehicles, the Internet of Medical Things (IoMT), and general environmental monitoring. Consumer-based IoT applications, like smart home gadgets and wearables, are also becoming more prevalent. This paper presents the main IoT deployment areas for environmental monitoring in developing regions and the backhaul options suitable for them based on a couple of related works. The study includes an overview of existing IoT deployments, the underlying communication architectures, protocols, and technologies that support them. This overview shows that Low Power Wireless Area Networks (LPWANs) are very well suited for monitoring environment architectures designed for remote locations. LoRa technology, particularly the LoRaWAN protocol, has an advantage over other technologies due to its low power consumption, adaptability, and suitable communication range. The current challenges of various architectures are discussed in detail, with the major issue identified as obstruction of communication paths by buildings, trees, hills, etc.

Keywords: Communication technologies, environmental monitoring, Internet of Things, IoT, IoT deployment challenges.

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736 Machine Learning Techniques for Short-Term Rain Forecasting System in the Northeastern Part of Thailand

Authors: Lily Ingsrisawang, Supawadee Ingsriswang, Saisuda Somchit, Prasert Aungsuratana, Warawut Khantiyanan

Abstract:

This paper presents the methodology from machine learning approaches for short-term rain forecasting system. Decision Tree, Artificial Neural Network (ANN), and Support Vector Machine (SVM) were applied to develop classification and prediction models for rainfall forecasts. The goals of this presentation are to demonstrate (1) how feature selection can be used to identify the relationships between rainfall occurrences and other weather conditions and (2) what models can be developed and deployed for predicting the accurate rainfall estimates to support the decisions to launch the cloud seeding operations in the northeastern part of Thailand. Datasets collected during 2004-2006 from the Chalermprakiat Royal Rain Making Research Center at Hua Hin, Prachuap Khiri khan, the Chalermprakiat Royal Rain Making Research Center at Pimai, Nakhon Ratchasima and Thai Meteorological Department (TMD). A total of 179 records with 57 features was merged and matched by unique date. There are three main parts in this work. Firstly, a decision tree induction algorithm (C4.5) was used to classify the rain status into either rain or no-rain. The overall accuracy of classification tree achieves 94.41% with the five-fold cross validation. The C4.5 algorithm was also used to classify the rain amount into three classes as no-rain (0-0.1 mm.), few-rain (0.1- 10 mm.), and moderate-rain (>10 mm.) and the overall accuracy of classification tree achieves 62.57%. Secondly, an ANN was applied to predict the rainfall amount and the root mean square error (RMSE) were used to measure the training and testing errors of the ANN. It is found that the ANN yields a lower RMSE at 0.171 for daily rainfall estimates, when compared to next-day and next-2-day estimation. Thirdly, the ANN and SVM techniques were also used to classify the rain amount into three classes as no-rain, few-rain, and moderate-rain as above. The results achieved in 68.15% and 69.10% of overall accuracy of same-day prediction for the ANN and SVM models, respectively. The obtained results illustrated the comparison of the predictive power of different methods for rainfall estimation.

Keywords: Machine learning, decision tree, artificial neural network, support vector machine, root mean square error.

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735 The Effect of Laser Surface Melting on the Microstructure and Mechanical Properties of Low Carbon Steel

Authors: Suleiman M. Elhamali, K. M. Etmimi, A. Usha

Abstract:

The paper presents the results of microhardness and microstructure of low carbon steel surface melted using carbon dioxide laser with a wavelength of 10.6μm and a maximum output power of 2000W. The processing parameters such as the laser power, and the scanning rate were investigated in this study. After surface melting two distinct regions formed corresponding to the melted zone MZ, and the heat affected zone HAZ. The laser melted region displayed a cellular fine structures while the HAZ displayed martensite or bainite structure. At different processing parameters, the original microstructure of this steel (Ferrite+Pearlite) has been transformed to new phases of martensitic and bainitic structures. The fine structure and the high microhardness are evidence of the high cooling rates which follow the laser melting. The melting pool and the transformed microstructure in the laser surface melted region of carbon steel showed clear dependence on laser power and scanning rate.

Keywords: Carbon steel, laser surface melting, microstructure, microhardness.

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734 The Challenges of Cloud Computing Adoption in Nigeria

Authors: Chapman Eze Nnadozie

Abstract:

Cloud computing, a technology that is made possible through virtualization within networks represents a shift from the traditional ownership of infrastructure and other resources by distinct organization to a more scalable pattern in which computer resources are rented online to organizations on either as a pay-as-you-use basis or by subscription. In other words, cloud computing entails the renting of computing resources (such as storage space, memory, servers, applications, networks, etc.) by a third party to its clients on a pay-as-go basis. It is a new innovative technology that is globally embraced because of its renowned benefits, profound of which is its cost effectiveness on the part of organizations engaged with its services. In Nigeria, the services are provided either directly to companies mostly by the key IT players such as Microsoft, IBM, and Google; or in partnership with some other players such as Infoware, Descasio, and Sunnet. This action enables organizations to rent IT resources on a pay-as-you-go basis thereby salvaging them from wastages accruable on acquisition and maintenance of IT resources such as ownership of a separate data centre. This paper intends to appraise the challenges of cloud computing adoption in Nigeria, bearing in mind the country’s peculiarities’ in terms of infrastructural development. The methodologies used in this paper include the use of research questionnaires, formulated hypothesis, and the testing of the formulated hypothesis. The major findings of this paper include the fact that there are some addressable challenges to the adoption of cloud computing in Nigeria. Furthermore, the country will gain significantly if the challenges especially in the area of infrastructural development are well addressed. This is because the research established the fact that there are significant gains derivable by the adoption of cloud computing by organizations in Nigeria. However, these challenges can be overturned by concerted efforts in the part of government and other stakeholders.

Keywords: Cloud computing, data centre, infrastructure, IT resources, network, servers, virtualization.

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733 An Analysis of Blackouts for Electric Power Transmission Systems

Authors: Karamitsos Ioannis, Orfanidis Konstantinos

Abstract:

In this paper an analysis of blackouts in electric power transmission systems is implemented using a model and studied in simple networks with a regular topology. The proposed model describes load demand and network improvements evolving on a slow timescale as well as the fast dynamics of cascading overloads and outages.

Keywords: Blackout, Generator, Load, Power Load.

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732 RF Power Consumption Emulation Optimized with Interval Valued Homotopies

Authors: Deogratius Musiige, François Anton, Vital Yatskevich, Laulagnet Vincent, Darka Mioc, Nguyen Pierre

Abstract:

This paper presents a methodology towards the emulation of the electrical power consumption of the RF device during the cellular phone/handset transmission mode using the LTE technology. The emulation methodology takes the physical environmental variables and the logical interface between the baseband and the RF system as inputs to compute the emulated power dissipation of the RF device. The emulated power, in between the measured points corresponding to the discrete values of the logical interface parameters is computed as a polynomial interpolation using polynomial basis functions. The evaluation of polynomial and spline curve fitting models showed a respective divergence (test error) of 8% and 0.02% from the physically measured power consumption. The precisions of the instruments used for the physical measurements have been modeled as intervals. We have been able to model the power consumption of the RF device operating at 5MHz using homotopy between 2 continuous power consumptions of the RF device operating at the bandwidths 3MHz and 10MHz.

Keywords: Radio frequency, high power amplifier, baseband, LTE, power, emulation, homotopy, interval analysis, Tx power, register-transfer level.

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731 Loading and Unloading Scheduling Problem in a Multiple-Multiple Logistics Network: Modeling and Solving

Authors: Yasin Tadayonrad, Alassane Ballé Ndiaye

Abstract:

Most of the supply chain networks have many nodes starting from the suppliers’ side up to the customers’ side that each node sends/receives the raw materials/products from/to the other nodes. One of the major concerns in this kind of supply chain network is finding the best schedule for loading/unloading the shipments through the whole network by which all the constraints in the source and destination nodes are met and all the shipments are delivered on time. One of the main constraints in this problem is the loading/unloading capacity in each source/destination node at each time slot (e.g., per week/day/hour). Because of the different characteristics of different products/groups of products, the capacity of each node might differ based on each group of products. In most supply chain networks (especially in the Fast-moving consumer goods (FMCG) industry), there are different planners/planning teams working separately in different nodes to determine the loading/unloading timeslots in source/destination nodes to send/receive the shipments. In this paper, a mathematical problem has been proposed to find the best timeslots for loading/unloading the shipments minimizing the overall delays subject to respecting the capacity of loading/unloading of each node, the required delivery date of each shipment (considering the lead-times), and working-days of each node. This model was implemented on Python and solved using Python-MIP on a sample data set. Finally, the idea of a heuristic algorithm has been proposed as a way of improving the solution method that helps to implement the model on larger data sets in real business cases, including more nodes and shipments.

Keywords: Supply chain management, transportation, multiple-multiple network, timeslots management, mathematical modeling, mixed integer programming.

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730 A New Approach for the Fingerprint Classification Based On Gray-Level Co- Occurrence Matrix

Authors: Mehran Yazdi, Kazem Gheysari

Abstract:

In this paper, we propose an approach for the classification of fingerprint databases. It is based on the fact that a fingerprint image is composed of regular texture regions that can be successfully represented by co-occurrence matrices. So, we first extract the features based on certain characteristics of the cooccurrence matrix and then we use these features to train a neural network for classifying fingerprints into four common classes. The obtained results compared with the existing approaches demonstrate the superior performance of our proposed approach.

Keywords: Biometrics, fingerprint classification, gray level cooccurrence matrix, regular texture representation.

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729 Application of Single Tuned Passive Filters in Distribution Networks at the Point of Common Coupling

Authors: M. Almutairi, S. Hadjiloucas

Abstract:

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

Keywords: Harmonics, passive filter, power factor, power quality.

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728 The Comparison of Data Replication in Distributed Systems

Authors: Iman Zangeneh, Mostafa Moradi, Ali Mokhtarbaf

Abstract:

The necessity of ever-increasing use of distributed data in computer networks is obvious for all. One technique that is performed on the distributed data for increasing of efficiency and reliablity is data rplication. In this paper, after introducing this technique and its advantages, we will examine some dynamic data replication. We will examine their characteristies for some overus scenario and the we will propose some suggestion for their improvement.

Keywords: data replication, data hiding, consistency, dynamicdata replication strategy

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727 A Numerical Model to Study the Rapid Buffering Approximation near an Open Ca2+ Channel for an Unsteady State Case

Authors: Leena Sharma

Abstract:

Chemical reaction and diffusion are important phenomena in quantitative neurobiology and biophysics. The knowledge of the dynamics of calcium Ca2+ is very important in cellular physiology because Ca2+ binds to many proteins and regulates their activity and interactions Calcium waves propagate inside cells due to a regenerative mechanism known as calcium-induced calcium release. Buffer-mediated calcium diffusion in the cytosol plays a crucial role in the process. A mathematical model has been developed for calcium waves by assuming the buffers are in equilibrium with calcium i.e., the rapid buffering approximation for a one dimensional unsteady state case. This model incorporates important physical and physiological parameters like dissociation rate, diffusion rate, total buffer concentration and influx. The finite difference method has been employed to predict [Ca2+] and buffer concentration time course regardless of the calcium influx. The comparative studies of the effect of the rapid buffered diffusion and kinetic parameters of the model on the concentration time course have been performed.

Keywords: Calcium Profile, Rapid Buffering Approximation, Influx, Dissociation rate constant.

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