Search results for: octave and network neuronal

Authors: Sourour Ramzi, Claudia Sarrico

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Little has been done on network DEA in education, and nobody has attempted to model the whole education supply chain using network DEA. As such the contribution of the present paper is to propose a model for measuring the efficiency of education supply chains using network DEA. First, we use a general survey of data envelopment analysis (DEA) to establish the emergent themes for research in DEA, and focus on the theme of Network DEA. Second, we use a survey on two-stage DEA models, and Network DEA to write a state of the art on Network DEA, particularly applied to supply chain management. Third, we use a survey on DEA applications to establish the most influential papers on DEA education applications, in order to establish the state of the art on applications of DEA in education, in general, and applications of DEA to education using network DEA, in particular. Finally, we propose a model for measuring the performance of education supply chains of different education systems (countries or states within a country, for instance). We then use this model on some empirical data.

Keywords: supply chain, education, data envelopment analysis, network DEA

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Authors: Sandeep Singh Waraich

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Wireless sensor network (WSN ) consists of a large number of sensor nodes. The disparity in their energy consumption usually lead to the loss of equilibrium in wireless sensor network which may further results in an energy hole problem in wireless network. In this paper, we have considered the inclusion of orphan nodes which usually remain unutilized as intermediate nodes in multi-hop routing. The Orphan Node Inclusion (ONI) Protocol lets the cluster member to bring the orphan nodes into their clusters, thereby saving important resources and increasing network lifetime in critical applications of WSN.

Keywords: wireless sensor network, orphan node, clustering, ONI protocol

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Authors: Surinder Singh, Meenakshi

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In this paper MZI-FBG based optical add drop multiplexer is designed and its performance is analyzed in the ring network. In the ring network nodes are composed of optical add drop multiplexer, transmitter and receiver. OADM is used to add or drop any frequency at intermediate nodes without affecting other channels. In this paper the performance of the ring network is carried out by varying various kinds of fiber with or without amplifiers.

Keywords: OADM, ring network, MZI-FBG, transmitter

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Authors: Belbahi Ahlam

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With the phenomenal growth in the Internet, network security has become an integral part of computer and information security. In order to come up with measures that make networks more secure, it is important to learn about the vulnerabilities that could exist in a computer network and then have an understanding of the typical attacks that have been carried out in such networks. The first half of this paper will expose the readers to the classical network attacks that have exploited the typical vulnerabilities of computer networks in the past and solutions that have been adopted since then to prevent or reduce the chances of some of these attacks. The second half of the paper will expose the readers to the different network security controls including the network architecture, protocols, standards and software/ hardware tools that have been adopted in modern day computer networks.

Keywords: network security, attacks and controls, computer and information, solutions

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Authors: Yong Xue, Daniel A. Menascé

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Automated and end-to-end network resource management and provisioning for virtual service networks in a multiple autonomous systems (a.k.a multi-AS) environment is a challenging and open problem. This paper proposes a novel, scalable and interoperable high-level architecture that incorporates a number of emerging enabling technologies including Software Defined Network (SDN), Network Function Virtualization (NFV), Service Oriented Architecture (SOA), and Autonomic Computing. The proposed architecture can be used to not only automate network resource management and provisioning for virtual service networks across multiple autonomous substrate networks, but also provide an adaptive capability for achieving optimal network resource management and maintaining network-level end-to-end network performance as well. The paper argues that this SDN and autonomic computing based architecture lays a solid foundation that can facilitate the development of the future Internet based on the pluralistic paradigm.

Keywords: virtual network, software defined network, virtual service network, adaptive resource management, SOA, multi-AS, inter-domain

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Authors: Tet H. Yeap

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An analog restricted Hopfield Network is presented in this paper. It consists of two layers of nodes, visible and hidden nodes, connected by directional weighted paths forming a bipartite graph with no intralayer connection. An energy or Lyapunov function was derived to show that the proposed network will converge to stable states. By introducing hidden nodes, the proposed network can be trained to store patterns and has increased memory capacity. Training to be an associative memory, simulation results show that the associative memory performs better than a classical Hopfield network by being able to perform better memory recall when the input is noisy.

Keywords: restricted Hopfield network, Lyapunov function, simultaneous perturbation stochastic approximation

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Authors: Liang Bai, Yandong Xiao, Haorang Wang, Songyang Lao

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The directedness of links is crucial to determine the controllability in complex networks. Even the edge directions can determine the controllability of complex networks. Obviously, for a given network, we wish to design its edge directions that make this network approach the optimal controllability. In this work, we firstly introduce two methods to enhance network by assigning edge directions. However, these two methods could not completely mitigate the negative effects of inaccessibility and dilations. Thus, to approach the optimal network controllability, the edge directions must mitigate the negative effects of inaccessibility and dilations as much as possible. Finally, we propose the edge direction for optimal controllability. The optimal method has been found to be successfully useful on real-world and synthetic networks.

Keywords: complex network, dynamics, network control, optimization

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Authors: Asma Ben Yaghlane, Mohamed Naceur Azaiez

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We consider the problem of attacks on networks. We define the concept of system survivability in networks in the presence of intelligent threats. Our setting of the problem assumes a flow to be sent from one source node to a destination node. The attacker attempts to disable the network by preventing the flow to reach its destination while the defender attempts to identify the best path-set to use to maximize the chance of arrival of the flow to the destination node. Our concept is shown to be different from the classical concept of network reliability. We distinguish two types of network survivability related to the defender and to the attacker of the network, respectively. We prove that the defender-based-network survivability plays the role of a lower bound while the attacker-based-network survivability plays the role of an upper bound of network reliability. We also prove that both concepts almost never agree nor coincide with network reliability. Moreover, we use the shortest-path problem to determine the defender-based-network survivability and the min-cut problem to determine the attacker-based-network survivability. We extend the problem to a variety of models including the minimum-spanning-tree problem and the multiple source-/destination-network problems.

Keywords: defense/attack strategies, information, networks, reliability, survivability

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Authors: Salma A. El-Marasy, Rehab F. Abdel-Rahman, Reham M. Abd-Elsalam

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The burden of stroke is intensely increasing worldwide. Brain injury following transient or permanent focal cerebral ischemia develops ischemic stroke as a consequence of a complex series of pathophysiological events. The aim of this study is to evaluate the possible neuroprotective effect of a dipeptidyl peptidase-4 inhibitor, vildagliptin, independent on its insulinotropic properties in non-diabetic rats subjected to cerebral ischemia. Anaesthetized Wistar rats were subjected to either left middle cerebral artery occlusion (MCAO) or sham operation followed by reperfusion after 30 min of MCAO. The other three groups were orally administered vildagliptin at 3 dose levels (2.5, 5, 10 mg/kg) for 3 successive weeks before subjected to left focal cerebral ischemia/reperfusion and till the end of the study. Neurological deficit scores and motor activity were assessed 24h following reperfusion. 48h following reperfusion, rats were euthanized and their left brain hemispheres were harvested and used in the biochemical, histopathological, and immunohistochemical investigations. Vildagliptin pretreatment improved neurological score deficit, locomotor activity and motor coordination in MCAO rats. Moreover, vildagliptin reduced malondialdehyde (MDA), elevated reduced glutathione (GSH), phosphotylinosital 3 kinase (PI3K), phosphorylated of protein kinase B (p-AKT), and mechanistic target of rapamycin (mTOR) brain contents in addition to reducing protein expression of caspase-3. Also, vildagliptin showed a dose-dependent attenuation in neuronal cell loss and histopathological alterations in MCAO rats. This study proves that vildagliptin exerted the neuroprotective effect in a dose-dependent manner as shown in amelioration of neuronal cell loss and histopathological damage in MCAO rats, which may be mediated by attenuating neuronal and motor deficits, it’s anti-oxidant property, activation of PI3K/AKT/mTOR pathway and its anti-apoptotic effect.

Keywords: caspase-3, cerebral ischemia, dipeptidyl peptidase-4 inhibitor, oxidative stress, PI3K/AKT/mTOR pathway, rats, vildagliptin

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Authors: Yagya Raj Pandeya, Joonwhoan Lee

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The dynamic behavior of music and video makes it difficult to evaluate musical instrument playing in a video by computer system. Any television or film video clip with music information are rich sources for analyzing musical instruments using modern machine learning technologies. In this research, we integrate the audio and video information sources using convolutional neural network (CNN) and pass network learned features through recurrent neural network (RNN) to preserve the dynamic behaviors of audio and video. We use different pre-trained CNN for music and video feature extraction and then fine tune each model. The music network use 2D convolutional network and video network use 3D convolution (C3D). Finally, we concatenate each music and video feature by preserving the time varying features. The long short term memory (LSTM) network is used for long-term dynamic feature characterization and then use late fusion with generalized mean. The proposed network performs better performance to recognize the musical instrument using audio-video multimodal neural network.

Keywords: multimodal, 3D convolution, music-video feature extraction, generalized mean

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Authors: Hazem J. Smadi

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Performance of a supply chain is directly related to a distribution network that entails the location of storing materials or products and how products are delivered to the end customer through different stages in the supply chain. This study analyses the current distribution network used for delivering gas cylinders to end customer in Jordan. Evaluation of current distribution has been conducted across customer service components. A modification on the current distribution network in terms of central warehousing in each city in the country improves the response time and customer experience. 

Keywords: distribution network, gas cylinder, Jordan, supply chain

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Authors: R. Poonkuzhali, M. Y. Sanavullah, M. R. Gurupriya

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Opportunistic routing is used, where the network has the features like dynamic topology changes and intermittent network connectivity. In Delay Tolerant network or Disruption tolerant network opportunistic forwarding technique is widely used. The key idea of opportunistic routing is selecting forwarding nodes to forward data and coordination among these nodes to avoid duplicate transmissions. This paper gives the analysis of pros and cons of various opportunistic routing techniques used in MANET.

Keywords: ETX, opportunistic routing, PSR, throughput

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Authors: Ava Salmanpour, Hanieh Saeedi, Payam Rouhi, Elahe Hamzeil, Shima Alimohammadi, Siamak Hossein Khalaj, Mohammad Asadian

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Software-defined network (SDN) is a network architecture designed to control network using software application in a central manner. This ability enables remote control of the whole network regardless of the network technology. In fact, in this architecture network intelligence is separated from physical infrastructure, it means that required network components can be implemented virtually using software applications. Today, power networks are characterized by a high range of complexity with a large number of intelligent devices, processing both huge amounts of data and important information. Therefore, reliable and secure communication networks are required. SDNs are the best choice to meet this issue. In this paper, SDN networks capabilities and characteristics will be reviewed and different basic controllers will be compared. The importance of using SDNs to escalate efficiency and reliability in utility power networks is going to be discussed and the comparison between the SDN-based power networks and traditional networks will be explained.

Keywords: software-defined network, SDNs, utility network, open flow, communication, gas and electricity, controller

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Authors: Krishan Kumar, Mohit Mittal, Pramod Kumar

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Wireless sensor network is one of the most promising communication networks for monitoring remote environmental areas. In this network, all the sensor nodes are communicated with each other via radio signals. The sensor nodes have capability of sensing, data storage and processing. The sensor nodes collect the information through neighboring nodes to particular node. The data collection and processing is done by data aggregation techniques. For the data aggregation in sensor network, clustering technique is implemented in the sensor network by implementing self-organizing feature map (SOFM) neural network. Some of the sensor nodes are selected as cluster head nodes. The information aggregated to cluster head nodes from non-cluster head nodes and then this information is transferred to base station (or sink nodes). The aim of this paper is to manage the huge amount of data with the help of SOM neural network. Clustered data is selected to transfer to base station instead of whole information aggregated at cluster head nodes. This reduces the battery consumption over the huge data management. The network lifetime is enhanced at a greater extent.

Keywords: artificial neural network, data clustering, self organization feature map, wireless sensor network

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Authors: Wei Liu, Shuquan Wang, Yang Gao

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Microgravity Science Experiment Rack (MSER) will be onboard TianHe (TH) spacecraft planned to be launched in 2018. TH is one module of Chinese Space Station. Microgravity Vibration Isolation System (MVIS), which is MSER’s core part, is used to isolate disturbance from TH and provide high-level microgravity for science experiment payload. MVIS is two stage vibration isolation system, consisting of Follow Unit (FU) and Experiment Support Unit (ESU). FU is linked to MSER by umbilical cables, and ESU suspends within FU and without physical connection. The FU’s position and attitude relative to TH is measured by binocular vision measuring system, and the acceleration and angular velocity is measured by accelerometers and gyroscopes. Air-jet thrusters are used to generate force and moment to control FU’s motion. Measurement module on ESU contains a set of Position-Sense-Detectors (PSD) sensing the ESU’s position and attitude relative to FU, accelerometers and gyroscopes sensing ESU’s acceleration and angular velocity. Electro-magnetic actuators are used to control ESU’s motion. Firstly, the linearized equations of FU’s motion relative to TH and ESU’s motion relative to FU are derived, laying the foundation for control system design and simulation analysis. Subsequently, two control schemes are proposed. One control scheme is that ESU tracks FU and FU tracks TH, shorten as E-F-T. The other one is that FU tracks ESU and ESU tracks TH, shorten as F-E-T. In addition, motion spaces are constrained within ±15 mm、±2° between FU and ESU, and within ±300 mm between FU and TH or between ESU and TH. A Proportional-Integrate-Differentiate (PID) controller is designed to control FU’s position and attitude. ESU’s controller includes an acceleration feedback loop and a relative position feedback loop. A Proportional-Integrate (PI) controller is designed in the acceleration feedback loop to reduce the ESU’s acceleration level, and a PID controller in the relative position feedback loop is used to avoid collision. Finally, simulations of E-F-T and F-E-T are performed considering variety uncertainties, disturbances and motion space constrains. The simulation results of E-T-H showed that control performance was from 0 to -20 dB for vibration frequency from 0.01 to 0.1 Hz, and vibration was attenuated 40 dB per ten octave above 0.1Hz. The simulation results of T-E-H showed that vibration was attenuated 20 dB per ten octave at the beginning of 0.01Hz.

Keywords: microgravity science experiment rack, microgravity vibration isolation system, PID control, vibration isolation performance

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Authors: Amos Sunday Onikanni, Bashir Lawal, Babatunji Emmanuel Oyinloye, Gomaa Mostafa-Hedeab, Mohammed Alorabi, Simona Cavalu, Augustine O. Olusola, Chih-Hao Wang, Gaber El-Saber Batiha

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The increasing global burden of diabetes mellitus has called for the search for a therapeutic alternative that offers better activities and safety than conventional chemotherapy. Herein, we evaluated the neuroprotective and antioxidant properties of different fractions (ethyl acetate, N-butanol and residual aqueous) of Clompanus pubescens leaves in streptozotocin (STZ)-induced diabetic rats. Our results revealed a significant elevation in the levels of blood glucose, pro-inflammatory cytokines, lipid peroxidation, neuronal activities of acetylcholinesterase, butyrylcholinesterase, nitric oxide, epinephrine, norepinephrine, and Na+/K+-ATPase in diabetic non treated rats. In addition, decreased levels of enzymatic and non-enzymatic antioxidants were observed. Treatment with different fractions of C. pubescens leaves resulted in a significant reversal of the biochemical alteration and improved the neurocognitive deficit in STZ-induced diabetic rats. However, the ethyl-acetate fraction demonstrated higher activities than the other fractions and was characterized for its phytoconstituents, revealing the presence of Gallic acid (713.00 ppm), catechin (0.91 ppm), ferulic acid (0.98 ppm), rutin (59.82 ppm), quercetin (3.22 ppm) and kaempferol (4.07 ppm). Our molecular docking analysis revealed that these compounds exhibited different binding affinities and potentials for targeting BChE/AChE/ IL-1 β/Na+-K+-ATPase. However, only Kampferol and ferulic exhibited good drug-like, ADMET, and permeability properties suitable for use as a neuronal drug target agent. Hence, the ethyl-acetate fraction of C. pubescent leaves could be considered a source of promising bioactive metabolite for the treatment and management of cognitive impairments related to type II diabetes mellitus.

Keywords: diabetes mellitus, neuroprotective, antioxidant, pro-inflammatory cytokines

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Authors: Zhiyong Shan, Preethi Santhanam, Vinod Namboodiri, Rajiv Bagai

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In recent years, the emerging network worms and attacks have distributive characteristics, which can spread globally in a very short time. Security management crossing networks to co-defense network-wide attacks and improve the efficiency of security administration is urgently needed. We propose a hierarchical distributed network security management system (HD-NSMS), which can integrate security management across multiple networks. First, we describe the system in macrostructure and microstructure; then discuss three key problems when building HD-NSMS: device model, alert mechanism, and emergency response mechanism; lastly, we describe the implementation of HD-NSMS. The paper is valuable for implementing NSMS in that it derives from a practical network security management system (NSMS).

Keywords: network security management, device organization, emergency response, cross-network

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Authors: Christian H. Sanabria-Montaña, Rodrigo Huerta-Quintanilla

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A lattice network is a special type of network in which all nodes have the same number of links, and its boundary conditions are periodic. The most basic lattice network is the ring, a one-dimensional network with periodic border conditions. In contrast, the Cartesian product of d rings forms a d-dimensional lattice network. An analytical expression currently exists for the clustering coefficient in this type of network, but the theoretical value is valid only up to certain connectivity value; in other words, the analytical expression is incomplete. Here we obtain analytically the clustering coefficient expression in d-dimensional lattice networks for any link density. Our analytical results show that the clustering coefficient for a lattice network with density of links that tend to 1, leads to the value of the clustering coefficient of a fully connected network. We developed a model on criminology in which the generalized clustering coefficient expression is applied. The model states that delinquents learn the know-how of crime business by sharing knowledge, directly or indirectly, with their friends of the gang. This generalization shed light on the network properties, which is important to develop new models in different fields where network structure plays an important role in the system dynamic, such as criminology, evolutionary game theory, econophysics, among others.

Keywords: clustering coefficient, criminology, generalized, regular network d-dimensional

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Authors: Sasiphan Nitayaprapha

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A commercially-supported social network has become an emerging channel for an organization to communicate with and provide services to customers. The success of the commercially-supported social network depends on the ability of the organization to keep the customers in participating in the network. Drawing from the theories of information adoption, information systems continuance, and web usability, the author develops a model to explore how a commercially-supported social network can encourage customers to continue participating and using the information in the network. The theoretical model will be proved through an online survey of customers using the commercially-supported social networking sites of several high technology companies operating in the same sector. The result will be compared with previous studies to learn about the explanatory power of the research model, and to identify the main factors determining users’ intention to continue using a commercially-supported social network. Theoretical and practical implications, and limitations are discussed.

Keywords: social network, information adoption, information systems continuance, web usability, user satisfaction

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Authors: Alireza Shams, Ali Zamanian, Atefehe Shamosi, Farnaz Ghorbani

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Introduction: Although the application of a new strategy remains a remarkable challenge for treatment of disabilities due to neuronal defects, progress in Nanomedicine and tissue engineering, suggesting the new medical methods. One of the promising strategies for reconstruction and regeneration of nervous tissue is replacing of lost or damaged cells by specific scaffolds after Compressive, ischemic and traumatic injuries of central nervous system. Furthermore, ultrastructure, composition, and arrangement of tissue scaffolds are effective on cell grafts. We followed implantation and differentiation of mesenchyme stem cells to neural cells on Gelatin Polylactic-co-glycolic acid (PLGA) scaffolds coated with iron nanoparticles. The aim of this study was to evaluate the capability of stem cells to differentiate into motor neuron-like cells under topographical cues and morphogenic factors. Methods and Materials: Bone marrow mesenchymal stem cells (BMMSCs) was obtained by primary cell culturing of adult rat bone marrow got from femur bone by flushing method. BMMSCs were incubated with DMEM/F12 (Gibco), 15% FBS and 100 U/ml pen/strep as media. Then, BMMSCs seeded on Gel/PLGA scaffolds and tissue culture (TCP) polystyrene embedded and incorporated by Fe Nano particles (FeNPs) (Fe3o4 oxide (M w= 270.30 gr/mol.). For neuronal differentiation, 2×10 5 BMMSCs were seeded on Gel/PLGA/FeNPs scaffolds was cultured for 7 days and 0.5 µ mol. Retinoic acid, 100 µ mol. Ascorbic acid,10 ng/ml. Basic fibroblast growth factor (Sigma, USA), 250 μM Iso butyl methyl xanthine, 100 μM 2-mercaptoethanol, and 0.2 % B27 (Invitrogen, USA) added to media. Proliferation of BMMSCs was assessed by using MTT assay for cell survival. The morphology of BMMSCs and scaffolds was investigated by scanning electron microscopy analysis. Expression of neuron-specific markers was studied by immunohistochemistry method. Data were analyzed by analysis of variance, and statistical significance was determined by Turkey’s test. Results: Our results revealed that differentiation and survival of BMMSCs into motor neuron-like cells on Gel/PLGA/FeNPs as a biocompatible and biodegradable scaffolds were better than those cultured in Gel/PLGA in absence of FeNPs and TCP scaffolds. FeNPs had raised physical power but decreased capacity absorption of scaffolds. Well defined oriented pores in scaffolds due to FeNPs may activate differentiation and synchronized cells as a mechanoreceptor. Induction effects of magnetic FeNPs by One way flow of channels in scaffolds help to lead the cells and can facilitate direction of their growth processes. Discussion: Progression of biological properties of BMMSCs and the effects of FeNPs spreading under magnetic field was evaluated in this investigation. In vitro study showed that the Gel/PLGA/FeNPs scaffold provided a suitable structure for motor neuron-like cells differentiation. This could be a promising candidate for enhancing repair and regeneration in neural defects. Dynamic and static magnetic field for inducing and construction of cells can provide better results for further experimental studies.

Keywords: differentiation, mesenchymal stem cells, nano particles, neuronal defects, Scaffolds

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Authors: Bahar Hazal Yalçınkaya, Bayram Yılmaz, Mustafa Özilgen

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Brain information transmission in the neuronal network occurs in the form of electrical signals. Neural work transmits information between the neurons or neurons and target cells by moving charged particles in a voltage field; a fraction of the energy utilized in this process is dissipated via entropy generation. Exergy loss and entropy generation models demonstrate the inefficiencies of the communication along the dendritic trees. In this study, neurons of 4 different animals were analyzed with one dimensional cable model with N=6 identical dendritic trees and M=3 order of symmetrical branching. Each branch symmetrically bifurcates in accordance with the 3/2 power law in an infinitely long cylinder with the usual core conductor assumptions, where membrane potential is conserved in the core conductor at all branching points. In the model, exergy loss and entropy generation rates are calculated for each branch of equivalent cylinders of electrotonic length (L) ranging from 0.1 to 1.5 for four different dendritic branches, input branch (BI), and sister branch (BS) and two cousin branches (BC-1 & BC-2). Thermodynamic analysis with the data coming from two different cat motoneuron studies show that in both experiments nearly the same amount of exergy is lost while generating nearly the same amount of entropy. Guinea pig vagal motoneuron loses twofold more exergy compared to the cat models and the squid exergy loss and entropy generation were nearly tenfold compared to the guinea pig vagal motoneuron model. Thermodynamic analysis show that the dissipated energy in the dendritic tress is directly proportional with the electrotonic length, exergy loss and entropy generation. Entropy generation and exergy loss show variability not only between the vertebrate and invertebrates but also within the same class. Concurrently, single action potential Na⁺ ion load, metabolic energy utilization and its thermodynamic aspect contributed for squid giant axon and mammalian motoneuron model. Energy demand is supplied to the neurons in the form of Adenosine triphosphate (ATP). Exergy destruction and entropy generation upon ATP hydrolysis are calculated. ATP utilization, exergy destruction and entropy generation showed differences in each model depending on the variations in the ion transport along the channels.

Keywords: ATP utilization, entropy generation, exergy loss, neuronal information transmittance

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Authors: O. P. Oladipo, O. A. Falode

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The determination of Recovery Factor is of great importance to the reservoir engineer since it relates reserves to the initial oil in place. Reserves are the producible portion of reservoirs and give an indication of the profitability of a field Development. The core objective of this project is to develop an artificial neural network model using selected reservoir data to predict Recovery Factors (RF) of hydrocarbon reservoirs and compare the model with a couple of the existing correlations. The type of Artificial Neural Network model developed was the Single Layer Feed Forward Network. MATLAB was used as the network simulator and the network was trained using the supervised learning method, Afterwards, the network was tested with input data never seen by the network. The results of the predicted values of the recovery factors of the Artificial Neural Network Model, API Correlation for water drive reservoirs (Sands and Sandstones) and Guthrie and Greenberger Correlation Equation were obtained and compared. It was noted that the coefficient of correlation of the Artificial Neural Network Model was higher than the coefficient of correlations of the other two correlation equations, thus making it a more accurate prediction tool. The Artificial Neural Network, because of its accurate prediction ability is helpful in the correct prediction of hydrocarbon reservoir factors. Artificial Neural Network could be applied in the prediction of other Petroleum Engineering parameters because it is able to recognise complex patterns of data set and establish a relationship between them.

Keywords: recovery factor, reservoir, reserves, artificial neural network, hydrocarbon, MATLAB, API, Guthrie, Greenberger

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Authors: Mansi Srivastava, Uzma Saqib, Adnan Naim, Anjali Roy, Dongfang Liu, Deepak Bhatnagar, Ravinder Ravinder, Mirza S. Baig

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Macrophages polarize to proinflammatory M1 or anti-inflammatory M2 states with distinct physiological functions. This transition within the M1 to M2 phenotypes decides the nature, duration, and severity of an inflammatory response. However, inspite of a substantial understanding of the fate of these phenotypes, the underlying molecular mechanisms are not well understood. We have investigated the role of Neuronal nitric oxide synthase (NOS1) mediated regulation of Activator protein 1 (AP-1) transcription factor in macrophages as a critical effector of macrophage phenotypic change. Activator protein 1 (AP-1) is a group of dimeric transcription factors composed of jun, Fos, and ATF family proteins. We determined that NOS1-derived nitric oxide (NO) facilitate Fos and jun interaction which induces IL12 & IL23 expression. Pharmacological inhibition of NOS1 inhibits Fos and jun interaction but increases ATF2 and Fos dimerization. Switching of Fos and jun dimer to ATF2 and jun dimerization switches phenotype from IL–12high IL-23high IL-10low to IL–12low IL-23lowIL-10high phenotype, respectively. Together, these findings highlight a key role of the TLR4-NOS1-AP1 signaling axis in regulating macrophage polarization.

Keywords: inflammation, macrophage, lipopolysaccharide (LPS), proinflammatory cytokines, activator protein 1 (AP-1), neuronal nitric oxide synthase (NOS1)

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Authors: Yan Lu, Song Hong, Janakiraman Udaiyappan, Aarti Nagayach, Quoc-Viet A. Duong, Masao Morita, Shun Saito, Yuichi Kobayashi, Yuhai, Zhao, Hongying Peng, Nicholas B. Pham, Walter J Lukiw, Christopher A. Vuong, Nicolas G. Bazan

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Aims: Neurodegeneration and behavior dysfunction occurs in patients with Alzheimer's Disease (AD), and as the disease progresses many patients develop cognitive impairment. 5XFAD mouse model of AD is widely used to study AD pathogenesis and treatment. This study aimed to investigate the effect of maresin like 1 (MaR-L1) treatment in AD pathology using 5XFAD mice. Methods: We tested 12-month-old male 5XFAD mice and wild type control mice treated with MaR-L1 in a battery of behavioral tasks. We performed open field test, beam walking test, clasping test, inverted grid test, acetone test, marble burring test, elevated plus maze test, cross maze test and novel object recognition test. We also studied neuronal loss, amyloid β burden, and inflammation in the brains of 5XFAD mice using immunohistology and Western blotting. Results: MaR-L1 treatment to the 5XFAD mice showed improved cognitive function of 5XFAD mice. MaR-L1 showed decreased anxiety behavior in open field test and marble burring test, increased muscular strength in the beam walking test, clasping test and inverted grid test. Cognitive function was improved in MaR-L1 treated 5XFAD mice in the novel object recognition test. MaR-L1 prevented neuronal loss and aberrant inflammation. Conclusion: Our finding suggests that behavioral abnormalities were normalized by the administration of MaR-L1 and the neuroprotective role of MaR-L1 in the AD. It also indicates that MaR-L1 treatment is able to prevent and or ameliorate neuronal loss and aberrant inflammation. Further experiments to validate the results are warranted using other AD models in the future.

Keywords: Alzheimer's disease, motor and cognitive behavior, 5XFAD mice, Maresin Like 1, microglial cell, astrocyte, neurodegeneration, inflammation, resolution of inflammation

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Authors: O. A. Lawal, O. A Ojesanmi

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The demand for wireless cellular services continues to increase while the radio resources remain limited. Thus, network operators have to continuously manage the scarce radio resources in order to have an improved quality of service for mobile users. This paper proposes how to handle the problem of congestion in the mobile network by prioritizing handoff call, using the guard channel allocation scheme. The research uses specific threshold value for the time of allocation of the channel in the algorithm. The scheme would be simulated by generating various data for different traffics in the network as it would be in the real life. The result would be used to determine the probability of handoff call dropping and the probability of the new call blocking as a way of measuring the network performance.

Keywords: call block, channel, handoff, mobile cellular network

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Authors: Sello Mokwena, Monyepao Thabang

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In this study, we propose a comprehensive approach to address the challenges in person re-identification models. By combining a centroid tracking algorithm with a Siamese convolutional neural network model, our method excels in detecting, tracking, and capturing robust person features across non-overlapping camera views. The algorithm efficiently identifies individuals in the camera network, while the neural network extracts fine-grained global features for precise cross-image comparisons. The approach's effectiveness is further accentuated by leveraging the camera network topology for guidance. Our empirical analysis on benchmark datasets highlights its competitive performance, particularly evident when background subtraction techniques are selectively applied, underscoring its potential in advancing person re-identification techniques.

Keywords: camera network, convolutional neural network topology, person tracking, person re-identification, siamese

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Authors: Kamalpreet Kaur, Harjit Pal Singh, Vikas Khullar

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In Wireless Sensor Network (WSN), the main limitation is generally inimitable energy consumption during processing of the sensor nodes. Cluster head (CH) election is one of the main issues that can reduce the energy consumption. Therefore, discovering energy saving routing protocol is the focused area for research. In this paper, fuzzy-based energy aware routing protocol is presented, which enhances the stability and network lifetime of the network. Fuzzy logic ensures the well-organized selection of CH by taking four linguistic variables that are concentration, energy, centrality, and distance to base station (BS). The results show that the proposed protocol shows better results in requisites of stability and throughput of the network.

Keywords: ERA, fuzzy logic, network model, WSN

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Authors: Mohamed Othmani, Yassine Khlifi

Abstract:

This paper presents a technique for compact three dimensional (3D) object model reconstruction using wavelet networks. It consists to transform an input surface vertices into signals,and uses wavelet network parameters for signal approximations. To prove this, we use a wavelet network architecture founded on several mother wavelet families. POLYnomials WindOwed with Gaussians (POLYWOG) wavelet families are used to maximize the probability to select the best wavelets which ensure the good generalization of the network. To achieve a better reconstruction, the network is trained several iterations to optimize the wavelet network parameters until the error criterion is small enough. Experimental results will shown that our proposed technique can effectively reconstruct an irregular 3D object models when using the optimized wavelet network parameters. We will prove that an accurateness reconstruction depends on the best choice of the mother wavelets.

Keywords: 3d object, optimization, parametrization, polywog wavelets, reconstruction, wavelet networks

Procedia PDF Downloads 253

Authors: Omar Khan, Shana Krstevska, Edwin George, Veronica Gorden, Fen Bao, Christina Caon, NP-C, Carla Santiago, Imad Zak, Navid Seraji-Bozorgzad

Abstract:

Objective: To quantify cellular injury in the substantia nigra (SN) in patients with Parkinson's disease (PD) and to examine the effect of rasagiline of tissue injury in the SN in patients with PD. Background: N-acetylaspartate (NAA) quantified with MRS is a reliable marker of neuronal metabolic function. Fractional anisotropy (FA) and mean diffusivity (MD) obtained with DTI, characterize tissue alignment and integrity. Rasagline, has been shown to exert anti-apototic effect. We applied these advanced MRI techniques to examine: (i) the effect of rasagiline on cellular injury and metabolism in patients with early PD, and (ii) longitudinal changes seen over time in PD. Methods: We conducted a prospective longitudinal study in patients with mild PD, naive to dopaminergic treatment. The imaging protocol included multi-voxel proton-MRS and DTI of the SN, acquired on a 3T scanner. Scans were performed at baseline and month 3, during which the patient was on no treatment. At that point, rasagiline 1 mg orally daily was initiated and MRI scans are were obtained at 6 and 12 months after starting rasagiline. The primary objective was to compare changes during the 3-month period of “no treatment” to the changes observed “on treatment” with rasagiline at month 12. Age-matched healthy controls were also imaged. Image analysis was performed blinded to treatment allocation and period. Results: 25 patients were enrolled in this study. Compared to the period of “no treatment”, there was significant increase in the NAA “on treatment” period (-3.04 % vs +10.95 %, p= 0.0006). Compared to the period of “no treatment”, there was significant increase in following 12 month in the FA “on treatment” (-4.8% vs +15.3%, p<0.0001). The MD increased during “no treatment” and decreased in “on treatment” (+2.8% vs -7.5%, p=0.0056). Further analysis and clinical correlation are ongoing. Conclusions: Advanced MRI techniques quantifying cellular injury in the SN in PD is a feasible approach to investigate dopaminergic neuronal injury and could be developed as an outcome in exploratory studies. Rasagiline appears to have a stabilizing effect on dopaminergic cell loss and metabolism in the SN in PD, that warrants further investigation in long-term studies.

Keywords: substantia nigra, Parkinson's disease, MRI, neuronal loss, biomarker

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Authors: Wei Wang, Yilun Xu

Abstract:

With the development of knowledge economy era, deepening the mechanism of cooperation and adhering to sharing and win-win cooperation has become new direction of urban development nowadays. In recent years, innovative collaborations between cities are becoming more and more frequent, whose influence on urban network space has aroused many scholars' attention. Taking 46 cities in China as the research object, the paper builds the connectivity of innovative network between cities and the linkages of urban external innovation using patent cooperation data among cities, and explores urban network space in China by the application of GIS, which is a beneficial exploration to the study of social network space in China in the era of information network. The result shows that the urban innovative network space and geographical entity space exist differences, and the linkages of external innovation are not entirely related to the city innovative capacity and the level of economy development. However, urban innovative network space and geographical entity space are similar in hierarchical clustering. They have both formed Beijing-Tianjin-Hebei, Yangtze River Delta, Pearl River Delta three metropolitan areas and Beijing-Shenzhen-Shanghai-Hangzhou four core cities, which lead the development of innovative network space in China.

Keywords: innovative collaboration, urban network space, the connectivity of innovative network, the linkages of external innovation

Procedia PDF Downloads 152