Search results for: protein interaction network
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 10284

Search results for: protein interaction network

9804 Mapping Network Connection of Personality Traits and Psychiatric Symptoms in Chinese Adolescents

Authors: Yichao Lv, Minmin Cai, Yanqiang Tao, Xinyuan Zou, Chao Zhang, Xiangping Liu

Abstract:

Objective: This study aims to explore the network structure of personality traits and mental health and identify key factors for effective intervention strategies. Methods: All participants (N = 6,067; 3,368 females) underwent the Eysenck Personality Scale (EPQ) to measure personality traits and the Symptom Self-rating Scale (SCL-90) to measure psychiatric symptoms. Using the mean value of the SCL-90 total score plus one standard deviation as the cutoff, 854 participants (14.08%; 528 females) were categorized as individuals exhibiting potential psychological symptoms and were included in the follow-up network analysis. The structure and bridge centrality of the network for dimensions of EPQ and SCL-90 were estimated. Results: Between the EPQ and SCL-90, psychoticism (P), extraversion (E), and neuroticism (N) showed the strongest positive correlations with somatization (Som), interpersonal sensitivity (IS), and hostility (Hos), respectively. Extraversion (E), somatization (Som), and anxiety (Anx) were identified as the most important bridge factors influencing the overall network. Conclusions: This study explored the network structure and complex connections between mental health and personality traits from a network perspective, providing potential targets for intervening in adolescent personality traits and mental health.

Keywords: EPQ, SCL-90, Chinese adolescents, network analysis

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9803 Natural Interaction Game-Based Learning of Elasticity with Kinect

Authors: Maryam Savari, Mohamad Nizam Ayub, Ainuddin Wahid Abdul Wahab

Abstract:

Game-based Learning (GBL) is an alternative that provides learners with an opportunity to experience a volatile environment in a safe and secure place. A volatile environment requires a different technique to facilitate learning and prevent injury and other hazards. Subjects involving elasticity are always considered hazardous and can cause injuries,for instance a bouncing ball. Elasticity is a topic that necessitates hands-on practicality for learners to experience the effects of elastic objects. In this paper the scope is to investigate the natural interaction between learners and elastic objects in a safe environment using GBL. During interaction, the potentials of natural contact in the process of learning were explored and gestures exhibited during the learning process were identified. GBL was developed using Kinect technology to teach elasticity to primary school children aged 7 to 12. The system detects body gestures and defines the meanings of motions exhibited during the learning process. The qualitative approach was deployed to constantly monitor the interaction between the student and the system. Based on the results, it was found that Natural Interaction GBL (Ni-GBL) is engaging for students to learn, making their learning experience more active and joyful.

Keywords: elasticity, Game-Based Learning (GBL), kinect technology, natural interaction

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9802 Robot Movement Using the Trust Region Policy Optimization

Authors: Romisaa Ali

Abstract:

The Policy Gradient approach is one of the deep reinforcement learning families that combines deep neural networks (DNN) with reinforcement learning RL to discover the optimum of the control problem through experience gained from the interaction between the robot and its surroundings. In contrast to earlier policy gradient algorithms, which were unable to handle these two types of error because of over-or under-estimation introduced by the deep neural network model, this article will discuss the state-of-the-art SOTA policy gradient technique, trust region policy optimization (TRPO), by applying this method in various environments compared to another policy gradient method, the Proximal Policy Optimization (PPO), to explain their robust optimization, using this SOTA to gather experience data during various training phases after observing the impact of hyper-parameters on neural network performance.

Keywords: deep neural networks, deep reinforcement learning, proximal policy optimization, state-of-the-art, trust region policy optimization

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9801 NSBS: Design of a Network Storage Backup System

Authors: Xinyan Zhang, Zhipeng Tan, Shan Fan

Abstract:

The first layer of defense against data loss is the backup data. This paper implements an agent-based network backup system used the backup, server-storage and server-backup agent these tripartite construction, and we realize the snapshot and hierarchical index in the NSBS. It realizes the control command and data flow separation, balances the system load, thereby improving the efficiency of the system backup and recovery. The test results show the agent-based network backup system can effectively improve the task-based concurrency, reasonably allocate network bandwidth, the system backup performance loss costs smaller and improves data recovery efficiency by 20%.

Keywords: agent, network backup system, three architecture model, NSBS

Procedia PDF Downloads 434
9800 Intelligent Grading System of Apple Using Neural Network Arbitration

Authors: Ebenezer Obaloluwa Olaniyi

Abstract:

In this paper, an intelligent system has been designed to grade apple based on either its defective or healthy for production in food processing. This paper is segmented into two different phase. In the first phase, the image processing techniques were employed to extract the necessary features required in the apple. These techniques include grayscale conversion, segmentation where a threshold value is chosen to separate the foreground of the images from the background. Then edge detection was also employed to bring out the features in the images. These extracted features were then fed into the neural network in the second phase of the paper. The second phase is a classification phase where neural network employed to classify the defective apple from the healthy apple. In this phase, the network was trained with back propagation and tested with feed forward network. The recognition rate obtained from our system shows that our system is more accurate and faster as compared with previous work.

Keywords: image processing, neural network, apple, intelligent system

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9799 Numerical Simulation of Fluid Structure Interaction Using Two-Way Method

Authors: Samira Laidaoui, Mohammed Djermane, Nazihe Terfaya

Abstract:

The fluid-structure coupling is a natural phenomenon which reflects the effects of two continuums: fluid and structure of different types in the reciprocal action on each other, involving knowledge of elasticity and fluid mechanics. The solution for such problems is based on the relations of continuum mechanics and is mostly solved with numerical methods. It is a computational challenge to solve such problems because of the complex geometries, intricate physics of fluids, and complicated fluid-structure interactions. The way in which the interaction between fluid and solid is described gives the largest opportunity for reducing the computational effort. In this paper, a problem of fluid structure interaction is investigated with two-way coupling method. The formulation Arbitrary Lagrangian-Eulerian (ALE) was used, by considering a dynamic grid, where the solid is described by a Lagrangian formulation and the fluid by a Eulerian formulation. The simulation was made on the ANSYS software.

Keywords: ALE, coupling, FEM, fluid-structure, interaction, one-way method, two-way method

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9798 Reliability Improvement of Power System Networks Using Adaptive Genetic Algorithm

Authors: Alireza Alesaadi

Abstract:

Reliability analysis is a powerful method for determining the weak points of the electrical networks. In designing of electrical network, it is tried to design the most reliable network with minimal system shutting down, but it is usually associated with increasing the cost. In this paper, using adaptive genetic algorithm, a method was presented that provides the most reliable system with a certain economical cost. Finally, the proposed method is applied to a sample network and results will be analyzed.

Keywords: reliability, adaptive genetic algorithm, electrical network, communication engineering

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9797 Functional Characterization of Transcriptional Regulator WhiB Proteins of Mycobacterium Tuberculosis

Authors: Sonam Kumari

Abstract:

Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis, possesses a remarkable feature of entering into and emerging from a persistent state. The mechanism by which Mtb switches from the dormant state to the replicative form is still poorly characterized. Proteome studies have given us an insight into the role of certain proteins in giving stupendous virulence to Mtb, but numerous dotsremain unconnected and unaccounted. The WhiB family of proteins is one such protein that is associated with developmental processes in actinomycetes.Mtb has seven such proteins (WhiB1 to WhiB7).WhiB proteins are transcriptional regulators; their conserved C-terminal HTH motif is involved in DNA binding. They regulate various essential genes of Mtbby binding to their promoter DNA. Biophysical Analysis of the effect of DNA binding on WhiB proteins has not yet been appropriately characterized. Interaction with DNA induces conformational changes in the WhiB proteins, confirmed by steady-state fluorescence and circular dichroism spectroscopy. ITC has deduced thermodynamic parameters and the binding affinity of the interaction. Since these transcription factors are highly unstable in vitro, their stability and solubility were enhanced by the co-expression of molecular chaperones. The present study findings help determine the conditions under which the WhiB proteins interact with their interacting partner and the factors that influence their binding affinity. This is crucial in understanding their role in regulating gene expression in Mtbandin targeting WhiB proteins as a drug target to cure TB.

Keywords: tuberculosis, WhiB proteins, mycobacterium tuberculosis, nucleic acid binding

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9796 GIS-Based Topographical Network for Minimum “Exertion” Routing

Authors: Katherine Carl Payne, Moshe Dror

Abstract:

The problem of minimum cost routing has been extensively explored in a variety of contexts. While there is a prevalence of routing applications based on least distance, time, and related attributes, exertion-based routing has remained relatively unexplored. In particular, the network structures traditionally used to construct minimum cost paths are not suited to representing exertion or finding paths of least exertion based on road gradient. In this paper, we introduce a topographical network or “topograph” that enables minimum cost routing based on the exertion metric on each arc in a given road network as it is related to changes in road gradient. We describe an algorithm for topograph construction and present the implementation of the topograph on a road network of the state of California with ~22 million nodes.

Keywords: topograph, RPE, routing, GIS

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9795 Uncovering the Complex Structure of Building Design Process Based on Royal Institute of British Architects Plan of Work

Authors: Fawaz A. Binsarra, Halim Boussabaine

Abstract:

The notion of complexity science has been attracting the interest of researchers and professionals due to the need of enhancing the efficiency of understanding complex systems dynamic and structure of interactions. In addition, complexity analysis has been used as an approach to investigate complex systems that contains a large number of components interacts with each other to accomplish specific outcomes and emerges specific behavior. The design process is considered as a complex action that involves large number interacted components, which are ranked as design tasks, design team, and the components of the design process. Those three main aspects of the building design process consist of several components that interact with each other as a dynamic system with complex information flow. In this paper, the goal is to uncover the complex structure of information interactions in building design process. The Investigating of Royal Institute of British Architects Plan Of Work 2013 information interactions as a case study to uncover the structure and building design process complexity using network analysis software to model the information interaction will significantly enhance the efficiency of the building design process outcomes.

Keywords: complexity, process, building desgin, Riba, design complexity, network, network analysis

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9794 Construction and Cross-Linking of Polyelectrolyte Multilayers Based on Polysaccharides as Antifouling Coatings

Authors: Wenfa Yu, Thuva Gnanasampanthan, John Finlay, Jessica Clarke, Charlotte Anderson, Tony Clare, Axel Rosenhahn

Abstract:

Marine biofouling is a worldwide problem at vast economic and ecological costs. Historically it was combated with toxic coatings such as tributyltin. As those coatings being banned nowadays, finding environmental friendly antifouling solution has become an urgent topic. In this study antifouling coatings consisted of natural occurring polysaccharides hyaluronic acid (HA), alginic acid (AA), chitosan (Ch) and polyelectrolyte polyethylenimine (PEI) are constructed into polyelectrolyte multilayers (PEMs) in a Layer-by-Layer (LbL) method. LbL PEM construction is a straightforward way to assemble biomacromolecular coatings on surfaces. Advantages about PEM include ease of handling, highly diverse PEM composition, precise control over the thickness and so on. PEMs have been widely employed in medical application and there are numerous studies regarding their protein adsorption, elasticity and cell adhesive properties. With the adjustment of coating composition, termination layer charge, coating morphology and cross-linking method, it is possible to prepare low marine biofouling coatings with PEMs. In this study, using spin coating technology, PEM construction was achieved at smooth multilayers with roughness as low as 2nm rms and highly reproducible thickness around 50nm. To obtain stability in sea water, the multilayers were covalently cross-linked either thermally or chemically. The cross-linking method affected surface energy, which was reflected in water contact angle, thermal cross-linking led to hydrophobic surfaces and chemical cross-linking generated hydrophilic surfaces. The coatings were then evaluated regarding its protein resistance and biological species resistance. While the hydrophobic thermally cross-linked PEM had low resistance towards proteins, the resistance of chemically cross-linked PEM strongly depended on the PEM termination layer and the charge of the protein, opposite charge caused high adsorption and same charge low adsorption, indicating electrostatic interaction plays a crucial role in the protein adsorption processes. Ulva linza was chosen as the biological species for antifouling performance evaluation. Despite of the poor resistance towards protein adsorption, thermally cross-linked PEM showed good resistance against Ulva spores settlement, the chemically cross-linked multilayers showed poor resistance regardless of the termination layer. Marine species adhesion is a complex process, although it involves proteins as bioadhesives, protein resistance its own is not a fully indicator for its antifouling performance. The species will pre select the surface, responding to cues like surface energy, chemistry, or charge and so on. Thus making it difficult for one single factors to determine its antifouling performance. Preparing PEM coating is a comprehensive work involving choosing polyelectrolyte combination, determining termination layer and the method for cross-linking. These decisions will affect PEM properties such as surface energy, charge, which is crucial, since biofouling is a process responding to surface properties in a highly sensitive and dynamic way.

Keywords: hyaluronic acid, polyelectrolyte multilayers, protein resistance, Ulva linza zoospores

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9793 Low-Proficiency L2 Learners’ Dyadic Interactions in Collaborative Writing: An Exploratory Case Study

Authors: Bing-Qing Lu, Hui-Tzu Min

Abstract:

Recent research, supported by sociocultural theory, has shown that collaborative writing in the second language (L2) contexts afford students opportunities to interact with each other to co-construct knowledge during the co-composing process. To date, much research on pair interaction in L2 collaborative writing settings has centered on intermediate and advanced learners by using static categorization of pair interaction patterns. Little is known about the fluid nature of pair interaction during collaborative writing, especially among low-proficiency learners. This study, thus, is aimed to explore the interaction dynamics of low-proficiency L2 learners during collaborative writing via examining the interaction pattern, focus of interaction, and the language related episodes (LREs) of 5 low-proficiency L2 writers from Taiwan. Employing a micro-level functional analytical method to capture the changing nature of pair interaction dynamics, the researchers calculated the number of characters/words produced by each pair member during CW and then classified their utterances into four task related-aspects--content, organization, language use, and task management--to determine each pair member's relative contribution to different dimensions of the evolving text. The LREs were also identified and examined. The results show that, of the five pairs, three pairs changed their interaction patterns when discussing different aspects of writing. Regarding the focus of their interaction, all five pairs paid attention to content most, followed by language use, task management, and organization. They were able to successfully resolve the majority of language issues (75.2%) in LREs and use the correct forms in their writing. These findings lend support to the fluid nature of pairs’ interactions and the changing roles of L2 learners in collaborative writing and highlighted the necessity of examining learners’ interaction patterns from a micro-level perspective. These findings also support previous research that low-proficiency pairs are able to correctly revolve 2/3 of their produced LREs, suggesting that collaborative writing may also be suitable for L2 low-proficiency learners.

Keywords: collaborative writing, low-proficiency L2 learners, micro-level functional analysis, pair interaction pattern

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9792 Homology Modelling of Beta Defensin 3 of Bos taurus and Its Docking Studies with Molecules Responsible for Formation of Biofilm

Authors: Ravinder Singh, Ankita Gurao, Saroj Bandhan, Sudhir Kumar Kashyap

Abstract:

The Bos taurus Beta defensin 3 is a defensin peptide secreted by neutrophils and epithelial that exhibits anti-microbial activity. It is one of the crucial components forming an innate defense against intra mammary infections in livestock. The beta defensin 3 by virtue of its anti-microbial activity inhibits major mastitis pathogens including Staphylococcus aureus and Pseudomonas aeruginosa etc, which are also responsible for biofilm formation leading to antibiotic resistance phenomenon. Therefore, the defensin may prove as a non-conventional option to treat mastitis. In this study, computational analysis has been performed including sequence comparison among species and homology modeling of Bos taurus beta defensin 3 protein. The assessments of protein structure were done using the protein structure and model assessment tools integrated in Swiss Model server, which employs various local and global quality evaluation parameters. Further, molecular docking was also carried out between the defensin peptide and the components of biofilm to gain insight into various interactions and structural differences crucial for functionality of this protein.

Keywords: beta defensin 3, bos taurus, docking, homology modeling

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9791 Design an Intelligent Fire Detection System Based on Neural Network and Particle Swarm Optimization

Authors: Majid Arvan, Peyman Beygi, Sina Rokhsati

Abstract:

In-time detection of fire in buildings is of great importance. Employing intelligent methods in data processing in fire detection systems leads to a significant reduction of fire damage at lowest cost. In this paper, the raw data obtained from the fire detection sensor networks in buildings is processed by using intelligent methods based on neural networks and the likelihood of fire happening is predicted. In order to enhance the quality of system, the noise in the sensor data is reduced by analyzing wavelets and applying SVD technique. Meanwhile, the proposed neural network is trained using particle swarm optimization (PSO). In the simulation work, the data is collected from sensor network inside the room and applied to the proposed network. Then the outputs are compared with conventional MLP network. The simulation results represent the superiority of the proposed method over the conventional one.

Keywords: intelligent fire detection, neural network, particle swarm optimization, fire sensor network

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9790 Stimulation of NCAM1-14.3.3.ζδ-derived Peptide Interaction Fuels Angiogenesis and Osteogenesis in Ageing

Authors: Taha Kadir Yesin, Hanyu Liu, Zhangfan Ding, Amit Singh, Qi Tian, Yuheng Zhang, Biswajyoti Borah, Junyu Chen, Anjali P. Kusumbe

Abstract:

The skeletal structure and bone marrow endothelium collectively form a critical functional unit essential for bone development, health, and aging. At the core of osteogenesis and bone formation lies the dynamic process of angiogenesis. In this study, we reveal a potent endogenous anabolic NCAM1-14.3.3. ζδ-derived- Peptide interaction, which stimulates bone angiogenesis and osteogenesis during homeostasis, aging, and age-related bone diseases. Employing high-resolution imaging and inducible cell-specific mouse genetics, our results elucidate the pivotal role of the NCAM1-14.3.3.ζδ-derived-Peptide interaction in driving the expansion of Clec14a+ angiogenic endothelial cells. Notably, Clec14a+ endothelial cells express key osteogenic factors. The NCAM1-14.3.3.ζδ-derived-Peptide interaction in osteoblasts drives osteoblast differentiation, ultimately contributing to the genesis of bone. Moreover, the NCAM1-14.3.3.ζδ-derived-Peptide interaction leads to a reduction in bone resorption. In age-associated vascular and bone loss diseases, stimulating the NCAM1-14.3.3.ζδ-derived-Peptide interaction not only promotes angiogenesis but also reverses bone loss. Consequently, harnessing the endogenous anabolic potential of the NCAM1-14.3.3.ζδ-derived-Peptide interaction emerges as a promising therapeutic modality for managing age-related bone diseases.

Keywords: endothelial cell, NCAM1, Clec14a, 14.3.3.ζδ

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9789 Network Word Discovery Framework Based on Sentence Semantic Vector Similarity

Authors: Ganfeng Yu, Yuefeng Ma, Shanliang Yang

Abstract:

The word discovery is a key problem in text information retrieval technology. Methods in new word discovery tend to be closely related to words because they generally obtain new word results by analyzing words. With the popularity of social networks, individual netizens and online self-media have generated various network texts for the convenience of online life, including network words that are far from standard Chinese expression. How detect network words is one of the important goals in the field of text information retrieval today. In this paper, we integrate the word embedding model and clustering methods to propose a network word discovery framework based on sentence semantic similarity (S³-NWD) to detect network words effectively from the corpus. This framework constructs sentence semantic vectors through a distributed representation model, uses the similarity of sentence semantic vectors to determine the semantic relationship between sentences, and finally realizes network word discovery by the meaning of semantic replacement between sentences. The experiment verifies that the framework not only completes the rapid discovery of network words but also realizes the standard word meaning of the discovery of network words, which reflects the effectiveness of our work.

Keywords: text information retrieval, natural language processing, new word discovery, information extraction

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9788 Structural Balance and Creative Tensions in New Product Development Teams

Authors: Shankaran Sitarama

Abstract:

New Product Development involves team members coming together and working in teams to come up with innovative solutions to problems, resulting in new products. Thus, a core attribute of a successful NPD team is their creativity and innovation. They need to be creative as a group, generating a breadth of ideas and innovative solutions that solve or address the problem they are targeting and meet the user’s needs. They also need to be very efficient in their teamwork as they work through the various stages of the development of these ideas, resulting in a POC (proof-of-concept) implementation or a prototype of the product. There are two distinctive traits that the teams need to have, one is ideational creativity, and the other is effective and efficient teamworking. There are multiple types of tensions that each of these traits cause in the teams, and these tensions reflect in the team dynamics. Ideational conflicts arising out of debates and deliberations increase the collective knowledge and affect the team creativity positively. However, the same trait of challenging each other’s viewpoints might lead the team members to be disruptive, resulting in interpersonal tensions, which in turn lead to less than efficient teamwork. Teams that foster and effectively manage these creative tensions are successful, and teams that are not able to manage these tensions show poor team performance. In this paper, it explore these tensions as they result in the team communication social network and propose a Creative Tension Balance index along the lines of Degree of Balance in social networks that has the potential to highlight the successful (and unsuccessful) NPD teams. Team communication reflects the team dynamics among team members and is the data set for analysis. The emails between the members of the NPD teams are processed through a semantic analysis algorithm (LSA) to analyze the content of communication and a semantic similarity analysis to arrive at a social network graph that depicts the communication amongst team members based on the content of communication. This social network is subjected to traditional social network analysis methods to arrive at some established metrics and structural balance analysis metrics. Traditional structural balance is extended to include team interaction pattern metrics to arrive at a creative tension balance metric that effectively captures the creative tensions and tension balance in teams. This CTB (Creative Tension Balance) metric truly captures the signatures of successful and unsuccessful (dissonant) NPD teams. The dataset for this research study includes 23 NPD teams spread out over multiple semesters and computes this CTB metric and uses it to identify the most successful and unsuccessful teams by classifying these teams into low, high and medium performing teams. The results are correlated to the team reflections (for team dynamics and interaction patterns), the team self-evaluation feedback surveys (for teamwork metrics) and team performance through a comprehensive team grade (for high and low performing team signatures).

Keywords: team dynamics, social network analysis, new product development teamwork, structural balance, NPD teams

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9787 Expression Regulation of Membrane Protein by Codon Variation of Amino Acid at N-Terminal Region

Authors: Ahreum Choi, Otgontuya Tsogbadrakh, Kwang-Hwan Jung

Abstract:

Microbial rhodopsins are well-known seven-transmembrane proteins that have been extensively studied. These retinal-binding proteins have divided into two types. The type I is microbial rhodopsin, and type II (visual pigment) is expressed mostly in mammalian eyes. For type I rhodopsin, there are two main functions that are ion pumping activity and sensory transduction. Anabaena sensory rhodopsin (ASR) is one of the microbial rhodopsin with main function as photo-sensory transduction. Although ASR is expressed fairly well in Escherichia coli, the expression level is relatively less compare to Proteorhodopsin. In this study, full length of ASR was used to test for the expression influence by codon usage in E. coli. Eight amino acids of codon at N-terminal part of ASR were changed randomly with designed primers, which allow 8,192 nucleotide different cases. The codon changes were screened for the preferable codons of each residue, which have given higher expression yield. Among those 57 selected mutations, there are 24 color-enhanced E. coli colonies that contain ASR proteins, and it showed better expression level than the wild type ASR codon usage. This strongly suggests that high codon usage of only partial N-terminal of protein can increase the expression level of whole protein.

Keywords: 7-transmembrane, all-trans retinal, rhodopsin, codon-usage, protein expression

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9786 Optimization of Reliability and Communicability of a Random Two-Dimensional Point Patterns Using Delaunay Triangulation

Authors: Sopheak Sorn, Kwok Yip Szeto

Abstract:

Reliability is one of the important measures of how well the system meets its design objective, and mathematically is the probability that a complex system will perform satisfactorily. When the system is described by a network of N components (nodes) and their L connection (links), the reliability of the system becomes a network design problem that is an NP-hard combinatorial optimization problem. In this paper, we address the network design problem for a random point set’s pattern in two dimensions. We make use of a Voronoi construction with each cell containing exactly one point in the point pattern and compute the reliability of the Voronoi’s dual, i.e. the Delaunay graph. We further investigate the communicability of the Delaunay network. We find that there is a positive correlation and a negative correlation between the homogeneity of a Delaunay's degree distribution with its reliability and its communicability respectively. Based on the correlations, we alter the communicability and the reliability by performing random edge flips, which preserve the number of links and nodes in the network but can increase the communicability in a Delaunay network at the cost of its reliability. This transformation is later used to optimize a Delaunay network with the optimum geometric mean between communicability and reliability. We also discuss the importance of the edge flips in the evolution of real soap froth in two dimensions.

Keywords: Communicability, Delaunay triangulation, Edge Flip, Reliability, Two dimensional network, Voronio

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9785 HIV-1 Nef Mediates Host Invasion by Differential Expression of Alpha-Enolase

Authors: Reshu Saxena, R. K. Tripathi

Abstract:

HIV-1 transmission and spread involves significant host-virus interaction. Potential targets for prevention of HIV-1 lies at the site of mucosal barriers. Thus a better understanding of how HIV-1 infects target cells at such sites and lead their invasion is required, with prime focus on the host determinants regulating HIV-1 spread. HIV-1 Nef is important for viral infectivity and pathogenicity. It promotes HIV-1 replication, facilitating immune evasion by interacting with various host factors and altering cellular pathways via multiple protein-protein interactions. In this study nef was sequenced from HIV-1 patients, and showed specific mutations revealing sequence variability in nef. To explore the difference in Nef functionality based on sequence variability we have studied the effects of HIV-1 Nef in human SupT1 T cell line and (THP-1) monocyte-macrophage cell lines through proteomics approach. 2D-Gel Electrophoresis in control and Nef-transfected SupT1 cells demonstrated several differentially expressed proteins with significant modulation of alpha-enolase. Through further studies, effects of Nef on alpha-enolase regulation were found to be cell lineage-specific, being stimulatory in macrophages/monocytes, inhibitory in T cells and without effect in HEK-293 cells. Cell migration and invasion studies were employed to determine biological function affected by Nef mediated regulation of alpha-enolase. Cell invasion was enhanced in THP-1 cells but was inhibited in SupT1 cells by wildtype nef. In addition, the modulation of enolase and cell invasion remained unaffected by a unique nef variant. These results indicated that regulation of alpha-enolase expression and invasive property of host cells by Nef is sequence specific, suggesting involvement of a particular motif of Nef. To precisely determine this site, we designed a heptapeptide including the suggested alpha-enolase regulating sequence of nef and a nef mutant with deletion of this site. Macrophages/monocytes being the major cells affected by HIV-1 at mucosal barriers, were particularly investigated by the nef mutant and peptide. Both the nef mutant and heptapeptide led to inhibition of enhanced enolase expression and increased invasiveness in THP-1 cells. Together, these findings suggest a possible mechanism of host invasion by HIV-1 through Nef mediated regulation of alpha-enolase and identifies a potential therapeutic target for HIV-1 entry at mucosal barriers.

Keywords: HIV-1 Nef, nef variants, host-virus interaction, tissue invasion

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9784 Identification of the Putative Interactome of Escherichia coli Glutaredoxin 2 by Affinity Chromatography

Authors: Eleni Poulou-Sidiropoulou, Charalampos N. Bompas, Martina Samiotaki, Alexios Vlamis-Gardikas

Abstract:

The glutaredoxin (Grx) and thioredoxin (Trx) systems keep the intracellular environment reduced in almost all organisms. In Escherichia coli (E. coli), the Grx system relies on NADPH+ to reduce GSH reductase (GR), the latter reducing oxidized diglutathione to glutathione (GSH) which in turn reduces cytosolic Grxs, the electron donors for different intracellular substrates. In the Trx system, GR and GSH are replaced by Trx reductase (TrxR). Three of the Grxs of E. coli (Grx1, 2, 3) are reduced by GSH, while Grx4 is likely reduced by TrxR. Trx1 and Grx1 from E. coli may reduce ribonucleotide reductase Ia to ensure a constant supply of deoxyribonucleotides for the synthesis of DNA. The role of the other three Grxs is relatively unknown, especially for Grx2 that may amount up to 1 % of total cellular protein in the stationary phase of growth. The protein is known as a potent antioxidant, but no specific functions have been attributed to it. Herein, affinity chromatography of cellular extracts on immobilized Grx2, followed by MS analysis of the resulting eluates, was employed to identify protein ligands that could provide insights into the biological role of Grx2. Ionic, strong non-covalent, and covalent (disulfide) interactions with relevant proteins were detected. As a means of verification, the identified ligands were subjected to in silico docking with monothiol Grx2. In other experiments, protein extracts from E. coli cells lacking the gene for Grx2 (grxB) were compared to those of wild type. Taken together, the two approaches suggest that Grx2 is involved in protein synthesis, nucleotide metabolism, DNA damage repair, stress responses, and various metabolic processes. Grx2 appears as a versatile protein that may participate in a wide range of biological pathways beyond its known general antioxidant function.

Keywords: Escherichia coli, glutaredoxin 2, interactome, thiol-disulfide oxidoreductase

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9783 A New Method to Reduce 5G Application Layer Payload Size

Authors: Gui Yang Wu, Bo Wang, Xin Wang

Abstract:

Nowadays, 5G service-based interface architecture uses text-based payload like JSON to transfer business data between network functions, which has obvious advantages as internet services but causes unnecessarily larger traffic. In this paper, a new 5G application payload size reduction method is presented to provides the mechanism to negotiate about new capability between network functions when network communication starts up and how 5G application data are reduced according to negotiated information with peer network function. Without losing the advantages of 5G text-based payload, this method demonstrates an excellent result on application payload size reduction and does not increase the usage quota of computing resource. Implementation of this method does not impact any standards or specifications and not change any encoding or decoding functionality too. In a real 5G network, this method will contribute to network efficiency and eventually save considerable computing resources.

Keywords: 5G, JSON, payload size, service-based interface

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9782 Thermal Network Model for a Large Scale AC Induction Motor

Authors: Sushil Kumar, M. Dakshina Murty

Abstract:

Thermal network modelling has proven to be important tool for thermal analysis of electrical machine. This article investigates numerical thermal network model and experimental performance of a large-scale AC motor. Experimental temperatures were measured using RTD in the stator which have been compared with the numerical data. Thermal network modelling fairly predicts the temperature of various components inside the large-scale AC motor. Results of stator winding temperature is compared with experimental results which are in close agreement with accuracy of 6-10%. This method of predicting hot spots within AC motors can be readily used by the motor designers for estimating the thermal hot spots of the machine.

Keywords: AC motor, thermal network, heat transfer, modelling

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9781 A Recombinant Group a Streptococcus (GAS-2W) Strain Elicits Protective Immunity in Mice through Induction of an IFN-γ Dependent Humoral Response

Authors: Shiva Emami, Jenny Persson, Bengt Johansson Lindbom

Abstract:

Group A streptococcus (GAS) is a prevalent human pathogen, causing a wide range of infections and diseases. One of the most well-known virulence factors in GAS is M protein, a surface protein that facilitates bacterial invasion. In this study, we used a recombinant GAS strain (GAS-2W) expressing M protein containing a hyper immunogenic peptide (2W). Mice were immunized three times with heat-killed-GAS subcutaneously at three weeks intervals. Three weeks post last immunization, mice were challenged intraperitoneally with a lethal dose of live GAS. In order to investigate the impact of IFN-ƴ and antibodies in protection against GAS infection, we used a mouse model knock-out for IFN-ƴ (IFN-ƴ KO). We observed immunization with GAS-2W strain can increase protection against GAS infection in mice compared with the original GAS strain. Higher levels of antibodies against M1 protein were measured in GAS-2W-immunized mice. There was also a significant increase in IgG2c response in mice immunized with GAS2W. By using IFN-ƴ KO mice, we showed that not a high level of total IgG, but IgG2c was correlated with protection through the i.p challenge. It also emphasizes the importance of IFN-ƴ cytokine to combat GAS by isotype switching to IgG2c (which is opsonic for phagocytosis). Our data indicate the crucial role of IFN-ƴ in the protective immune response that, together with IgG2c, can induce protection against GAS.

Keywords: Group A streptococcus, IgG2c, IFN-γ, protection

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9780 A Two-Step Framework for Unsupervised Speaker Segmentation Using BIC and Artificial Neural Network

Authors: Ahmad Alwosheel, Ahmed Alqaraawi

Abstract:

This work proposes a new speaker segmentation approach for two speakers. It is an online approach that does not require a prior information about speaker models. It has two phases, a conventional approach such as unsupervised BIC-based is utilized in the first phase to detect speaker changes and train a Neural Network, while in the second phase, the output trained parameters from the Neural Network are used to predict next incoming audio stream. Using this approach, a comparable accuracy to similar BIC-based approaches is achieved with a significant improvement in terms of computation time.

Keywords: artificial neural network, diarization, speaker indexing, speaker segmentation

Procedia PDF Downloads 479
9779 A Multi-Arm Randomized Trial Comparing the Weight Gain of Very Low Birth Weight Neonates: High Glucose versus High Protein Intake

Authors: Farnaz Firuzian, Farhad Choobdar, Ali Mazouri

Abstract:

As Very Low Birth Weight (VLBW) neonates cannot tolerate enteral feeding, parenteral nutrition (PN) must be administered shortly after birth. To find an optimal combination of nutrition, in this study, we compare administering high glucose versus high protein intake as a component of total parenteral nutrition (TPN) to test their effect on birth weight (BW) regain in VLBW. This study employs a multi-arm randomized trial: 145 newborns with BW < 1500 g were randomized to control (C) or experimental groups: high glucose (G) or high protein (P). All samples in each group received the same TPN regimens except glucose and protein intake: Glocuse was provided by dextrose water (DW) serum: 7-15 g/kg/d (10% DW) in groups C and P versus 8.75-18.75 g/kg/d (12.5% DW) in group G. Protein provided by amino acids 3 g/kg/d for groups C and G versus 4 g/kg/d for group P. Outcomes (weight, height, and head circumference) was monitored on a daily basis until the BW was regained. Data has been gathered recently and is being processed. We hypothesize that neonates with higher amino acid intake will result in sooner BW regain than other groups. The result will be presented at the conference. The findings of this study not only can help optimize nutrition, cost reduction, and shorter NICU admission of VLBW neonates at the hospital level but eventually contribute to reduced healthcare-associated infections (HAIs) and an improved health economy.

Keywords: very low birth weight neonates, weight gain, parenteral nutrition, glucose, amino acids

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9778 Human LACE1 Functions Pro-Apoptotic and Interacts with Mitochondrial YME1L Protease

Authors: Lukas Stiburek, Jana Cesnekova, Josef Houstek, Jiri Zeman

Abstract:

Cellular function depends on mitochondrial function and integrity that is therefore maintained by several classes of proteins possessing chaperone and/or proteolytic activities. In this work, we focused on characterization of LACE1 (lactation elevated 1) function in mitochondrial protein homeostasis maintenance. LACE1 is the human homologue of yeast mitochondrial Afg1 ATPase, a member of SEC18-NSF, PAS1, CDC48-VCP, TBP family. Yeast Afg1 was shown to be involved in mitochondrial complex IV biogenesis, and based on its similarity with CDC48 (p97/VCP) it was suggested to facilitate extraction of polytopic membrane proteins. Here we show that LACE1, which is a mitochondrial integral membrane protein, exists as part of three complexes of approx. 140, 400 and 500 kDa and is essential for maintenance of fused mitochondrial reticulum and lamellar cristae morphology. Using affinity purification of LACE1-FLAG expressed in LACE1 knockdown background we show that the protein physically interacts with mitochondrial inner membrane protease YME1L. We further show that human LACE1 exhibits significant pro-apoptotic activity and that the protein is required for normal function of the mitochondrial respiratory chain. Thus, our work establishes LACE1 as a novel factor with the crucial role in mitochondrial homeostasis maintenance.

Keywords: LACE1, mitochondria, apoptosis, protease

Procedia PDF Downloads 290
9777 Identification of Soft Faults in Branched Wire Networks by Distributed Reflectometry and Multi-Objective Genetic Algorithm

Authors: Soumaya Sallem, Marc Olivas

Abstract:

This contribution presents a method for detecting, locating, and characterizing soft faults in a complex wired network. The proposed method is based on multi-carrier reflectometry MCTDR (Multi-Carrier Time Domain Reflectometry) combined with a multi-objective genetic algorithm. In order to ensure complete network coverage and eliminate diagnosis ambiguities, the MCTDR test signal is injected at several points on the network, and the data is merged between different reflectometers (sensors) distributed on the network. An adapted multi-objective genetic algorithm is used to merge data in order to obtain more accurate faults location and characterization. The proposed method performances are evaluated from numerical and experimental results.

Keywords: wired network, reflectometry, network distributed diagnosis, multi-objective genetic algorithm

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9776 Implementation and Demonstration of Software-Defined Traffic Grooming

Authors: Lei Guo, Xu Zhang, Weigang Hou

Abstract:

Since the traditional network is closed and it has no architecture to create applications, it has been unable to evolve with changing demands under the rapid innovation in services. Additionally, due to the lack of the whole network profile, the quality of service cannot be well guaranteed in the traditional network. The Software Defined Network (SDN) utilizes global resources to support on-demand applications/services via open, standardized and programmable interfaces. In this paper, we implement the traffic grooming application under a real SDN environment, and the corresponding analysis is made. In our SDN: 1) we use OpenFlow protocol to control the entire network by using software applications running on the network operating system; 2) several virtual switches are combined into the data forwarding plane through Open vSwitch; 3) An OpenFlow controller, NOX, is involved as a logically centralized control plane that dynamically configures the data forwarding plane; 4) The traffic grooming based on SDN is demonstrated through dynamically modifying the idle time of flow entries. The experimental results demonstrate that the SDN-based traffic grooming effectively reduces the end-to-end delay, and the improvement ratio arrives to 99%.

Keywords: NOX, OpenFlow, Software Defined Network (SDN), traffic grooming

Procedia PDF Downloads 233
9775 Impact of Network Workload between Virtualization Solutions on a Testbed Environment for Cybersecurity Learning

Authors: Kevin Fernagut, Olivier Flauzac, Erick M. G. Robledo, Florent Nolot

Abstract:

The adoption of modern lightweight virtualization often comes with new threats and network vulnerabilities. This paper seeks to assess this with a different approach studying the behavior of a testbed built with tools such as Kernel-Based Virtual Machine (KVM), Linux Containers (LXC) and Docker, by performing stress tests within a platform where students experiment simultaneously with cyber-attacks, and thus observe the impact on the campus network and also find the best solution for cyber-security learning. Interesting outcomes can be found in the literature comparing these technologies. It is, however, difficult to find results of the effects on the global network where experiments are carried out. Our work shows that other physical hosts and the faculty network were impacted while performing these trials. The problems found are discussed, as well as security solutions and the adoption of new network policies.

Keywords: containerization, containers, cybersecurity, cyberattacks, isolation, performance, virtualization, virtual machines

Procedia PDF Downloads 123