Resilience of protein-protein interaction networks as determined by their large-scale topological features

The relationship between the structure and function of biological networks constitutes a fundamental issue in systems biology. Particularly, the structure of protein-protein interaction networks is related to important biological functions. In this work, we investigated how such a resilience is determined by the large scale features of the respective networks. Four species are taken into account, namely yeast Saccharomyces cerevisiae, worm Caenorhabditis elegans, fly Drosophila melanogaster and Homo sapiens. We adopted two entropy-related measurements (degree entropy and dynamic entropy) in order to quantify the overall degree of robustness of these networks. We verified that while they exhibit similar structural variations under random node removal, they differ significantly when subjected to intentional attacks (hub removal). As a matter of fact, more complex species tended to exhibit more robust networks. More specifically, we quantified how six important measurements of the networks topology (namely clustering coefficient, average degree of neighbors, average shortest path length, diameter, assortativity coefficient, and slope of the power law degree distribution) correlated with the two entropy measurements. Our results revealed that the fraction of hubs and the average neighbor degree contribute significantly for the resilience of networks. In addition, the topological analysis of the removed hubs indicated that the presence of alternative paths between the proteins connected to hubs tend to reinforce resilience. The performed analysis helps to understand how resilience is underlain in networks and can be applied to the development of protein network models.

ANALYSIS & STUDY OF AI TECHNIQUES FORAUTOMATIC CONDITION MONITORING OFRAILWAY TRACK INFRASTRUCTURE : Artificial Intelligence Techniques

Since the last decade the problem of surface inspection has been receiving great attention from the scientific community, the quality control and the maintenance of products are key points in several industrial applications.The railway associations spent much money to check the railway infrastructure. The railway infrastructure is a particular field in which the periodical surface inspection can help the operator to prevent critical situations. The maintenance and monitoring of this infrastructure is an important aspect for railway association.That is why the surface inspection of railway also makes importance to the railroad authority to investigate track components, identify problems and finding out the way that how to solve these problems. In railway industry, usually the problems find in railway sleepers, overhead, fastener, rail head, switching and crossing and in ballast section as well. In this thesis work, I have reviewed some research papers based on AI techniques together with NDT techniques which are able to collect data from the test object without making any damage. The research works which I have reviewed and demonstrated that by adopting the AI based system, it is almost possible to solve all the problems and this system is very much reliable and efficient for diagnose problems of this transportation domain. I have reviewed solutions provided by different companies based on AI techniques, their products and reviewed some white papers provided by some of those companies. AI based techniques likemachine vision, stereo vision, laser based techniques and neural network are used in most cases to solve the problems which are performed by the railway engineers.The problems in railway handled by the AI based techniques performed by NDT approach which is a very broad, interdisciplinary field that plays a critical role in assuring that structural components and systems perform their function in a reliable and cost effective fashion. The NDT approach ensures the uniformity, quality and serviceability of materials without causing any damage of that materials is being tested. This testing methods use some way to test product like, Visual and Optical testing, Radiography, Magnetic particle testing, Ultrasonic testing, Penetrate testing, electro mechanic testing and acoustic emission testing etc. The inspection procedure has done periodically because of better maintenance. This inspection procedure done by the railway engineers manually with the aid of AI based techniques.The main idea of thesis work is to demonstrate how the problems can be reduced of thistransportation area based on the works done by different researchers and companies. And I have also provided some ideas and comments according to those works and trying to provide some proposal to use better inspection method where it is needed.The scope of this thesis work is automatic interpretation of data from NDT, with the goal of detecting flaws accurately and efficiently. AI techniques such as neural networks, machine vision, knowledge-based systems and fuzzy logic were applied to a wide spectrum of problems in this area. Another scope is to provide an insight into possible research methods concerning railway sleeper, fastener, ballast and overhead inspection by automatic interpretation of data.In this thesis work, I have discussed about problems which are arise in railway sleepers,fastener, and overhead and ballasted track. For this reason I have reviewed some research papers related with these areas and demonstrated how their systems works and the results of those systems. After all the demonstrations were taking place of the advantages of using AI techniques in contrast with those manual systems exist previously.This work aims to summarize the findings of a large number of research papers deploying artificial intelligence (AI) techniques for the automatic interpretation of data from nondestructive testing (NDT). Problems in rail transport domain are mainly discussed in this work. The overall work of this paper goes to the inspection of railway sleepers, fastener, ballast and overhead.

Optimized Water Demand Management Through Intelligent Sensing And Analytics: The WISDOM Approach

New business and technology platforms are required to sustainably manage urban water resources [1,2]. However, any proposed solutions must be cognisant of security, privacy and other factors that may inhibit adoption and hence impact. The FP7 WISDOM project (funded by the European Commission - GA 619795) aims to achieve a step change in water and energy savings via the integration of innovative Information and Communication Technologies (ICT) frameworks to optimize water distribution networks and to enable change in consumer behavior through innovative demand management and adaptive pricing schemes [1,2,3]. The WISDOM concept centres on the integration of water distribution, sensor monitoring and communication systems coupled with semantic modelling (using ontologies, potentially connected to BIM, to serve as intelligent linkages throughout the entire framework) and control capabilities to provide for near real-time management of urban water resources. Fundamental to this framework are the needs and operational requirements of users and stakeholders at domestic, corporate and city levels and this requires the interoperability of a number of demand and operational models, fed with data from diverse sources such as sensor networks and crowsourced information. This has implications regarding the provenance and trustworthiness of such data and how it can be used in not only the understanding of system and user behaviours, but more importantly in the real-time control of such systems. Adaptive and intelligent analytics will be used to produce decision support systems that will drive the ability to increase the variability of both supply and consumption [3]. This in turn paves the way for adaptive pricing incentives and a greater understanding of the water-energy nexus. This integration is complex and uncertain yet being typical of a cyber-physical system, and its relevance transcends the water resource management domain. The WISDOM framework will be modeled and simulated with initial testing at an experimental facility in France (AQUASIM – a full-scale test-bed facility to study sustainable water management), then deployed and evaluated in in two pilots in Cardiff (UK) and La Spezia (Italy). These demonstrators will evaluate the integrated concept providing insight for wider adoption.

Windows of opportunities and knowledge networks: implications for the catch-up in developing countries

This document represents a doctoral thesis held under the Brazilian School of Public and Business Administration of Getulio Vargas Foundation (EBAPE/FGV), developed through the elaboration of three articles. The research that resulted in the articles is within the scope of the project entitled “Windows of opportunities and knowledge networks: implications for catch-up in developing countries”, funded by Support Programme for Research and Academic Production of Faculty (ProPesquisa) of Brazilian School of Public and Business Administration (EBAPE) of Getulio Vargas Foundation.

Using Neo4J geospatial data storage and integration

Online geographic-databases have been growing increasingly as they have become a crucial source of information for both social networks and safety-critical systems. Since the quality of such applications is largely related to the richness and completeness of their data, it becomes imperative to develop adaptable and persistent storage systems, able to make use of several sources of information as well as enabling the fastest possible response from them. This work will create a shared and extensible geographic model, able to retrieve and store information from the major spatial sources available. A geographic-based system also has very high requirements in terms of scalability, computational power and domain complexity, causing several difficulties for a traditional relational database as the number of results increases. NoSQL systems provide valuable advantages for this scenario, in particular graph databases which are capable of modeling vast amounts of inter-connected data while providing a very substantial increase of performance for several spatial requests, such as finding shortestpath routes and performing relationship lookups with high concurrency. In this work, we will analyze the current state of geographic information systems and develop a unified geographic model, named GeoPlace Explorer (GE). GE is able to import and store spatial data from several online sources at a symbolic level in both a relational and a graph databases, where several stress tests were performed in order to find the advantages and disadvantages of each database paradigm.

Equalização neural aplicada a sistemas com modulação bidimensional em fibra óptica

Nowadays, optic fiber is one of the most used communication methods, mainly due to the fact that the data transmission rates of those systems exceed all of the other means of digital communication. Despite the great advantage, there are problems that prevent full utilization of the optical channel: by increasing the transmission speed and the distances involved, the data is subjected to non-linear inter symbolic interference caused by the dispersion phenomena in the fiber. Adaptive equalizers can be used to solve this problem, they compensate non-ideal responses of the channel in order to restore the signal that was transmitted. This work proposes an equalizer based on artificial neural networks and evaluates its performance in optical communication systems. The proposal is validated through a simulated optic channel and the comparison with other adaptive equalization techniques

Mathematical tests about the existence and applications of PPS-wavelets in function approximation problems

Neural networks and wavelet transform have been recently seen as attractive tools for developing eficient solutions for many real world problems in function approximation. Function approximation is a very important task in environments where computation has to be based on extracting information from data samples in real world processes. So, mathematical model is a very important tool to guarantee the development of the neural network area. In this article we will introduce one series of mathematical demonstrations that guarantee the wavelets properties for the PPS functions. As application, we will show the use of PPS-wavelets in pattern recognition problems of handwritten digit through function approximation techniques.

EFFICIENT FAULT LOCATION IN UNDERGROUND DISTRIBUTION SYSTEMS THROUGH OPTIMUM-PATH FOREST

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Disorder effects produced by the Mn and H incorporations on the optical absorption edge of Ga1-xMnxAs:H nanocrystalline films

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Fast optical preparation, control, and readout of a single quantum dot spin

We propose and demonstrate the sequential initialization, optical control, and readout of a single spin trapped in a semiconductor quantum dot. Hole spin preparation is achieved through ionization of a resonantly excited electron-hole pair. Optical control is observed as a coherent Rabi rotation between the hole and charged-exciton states, which is conditional on the initial hole spin state. The spin-selective creation of the charged exciton provides a photocurrent readout of the hole spin state.

Application of intelligent systems for specification of automotive equipments using LEDs

The advantages offered by the electronic component light emitting diode ( LED) have caused a quick and wide application of this device in replacement of incandescent lights. However, in its combined application, the relationship between the design variables and the desired effect or result is very complex and it becomes difficult to model by conventional techniques. This work consists of the development of a technique, through artificial neural networks, to make possible to obtain the luminous intensity values of brake lights using LEDs from design data. (C) 2005 Elsevier B.V. All rights reserved.

Optical and structural properties of PEO-like plasma polymers

This paper deals with the study of optical, structural and biocompatible properties of PEO-like plasma polymerized films resulting from RF excited diethylene glycol dimethyl ether (CH3O(CH2CH2O)(2)CH3 diglyme) glow discharges. The study was carried out using visible-ultraviolet and FTIR spectroscopies and contact angle measurements. FTIR spectra of plasma polymerized diglyme showed a stronger presence of ethylene glycol groups in film structure for lower RF power levels. The contact angle measurements for water revealed an increasing from 30degrees to 62,5degrees when the RF power was varied from 2 to 45 W, indicating the decreasing of the hydrophilic character of diglyme films with the increasing of RF power. This trend is in agreement with FTIR results. The data from visible-ultraviolet reflectance and transmittance spectra revealed alterations on optical properties of plasma polymerized diglyme films. The film's optical gap varied from 3.8 to 3 eV for RF power running from 5 to 45 W.

DCM Boost interleaved converter for operation in AC and DC to trolleybus application

This paper is based on the development and experimental analysis of a DCM Boost interleaved converter suitable for application in traction systems of electrical vehicles pulled by electrical motors (Trolleybus), which are powered by urban DC or AC distribution networks. This front-end structure is capable of providing significant improvements in trolleybuses systems and in the urban distribution network costs, and efficiency. The architecture of proposed converter is composed by five boost power cells in interleaving connection, operating in discontinuous conduction mode. Furthermore, the converter can operate as AC-DC converter, or as DC-DC converter providing the proper DC output voltage range required by DC or AC adjustable speed drivers. Therefore, when supplied by single-phase AC distribution networks, and operating as AC-DC converter, it is capable to provide high power factor, reduced harmonic distortion in the input current, complying with the restrictions imposed by the IEC 61000-3-4 standards. The digital controller has been implemented using a low cost FPGA and developed totally using a hardware description language VHDL and fixed point arithmetic. Thus, two control strategies are evaluated considering the compliance with input current restrictions imposed by IEC 61000-3-4 standards, the regular PWM modulation and a current correction PWM modulation. In order to verify the feasibility and performance of the proposed system, experimental results from a 15 kW low power scale prototype are presented, operating in DC and AC conditions.

Exposed collagen in aged resin-dentin bonds produced on sound and caries-affected dentin in the presence of chlorhexidine

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Bond strength durability of a resin composite on a reinforced ceramic using various repair systems

Objectives. This study compared the durability of repair bond strength of a resin composite to a reinforced ceramic after three repair systems.Methods. Alumina-reinforced feldspathic ceramic blocks (Vitadur-alpha(R)) (N=30) were randomly divided into three groups according to the repair method: PR-Porcelain Repair Kit (Bisco) [etching with 9.5% hydrofluoric acid + silanization + adhesive]; CJ-CoJet Repair Kit (3M ESPE) [(chairside silica coating with 30 mu m SiO2 + silanization (ESPE(R)-Sil) + adhesive (Visio(TM)-Bond)]; CL-Clearfil Repair Kit [diamond surface roughening, etching with 40% H3PO4 + Clearfil Porcelain Bond Activator + Clearfil SE Bond)]. Resin composite was photo-polymerized on each conditioned ceramic block. Non-trimmed beam specimens were produced for the microtensile bond strength (mu TBS) tests. In order to study the hydrolytic durability of the repair methods, the beam specimens obtained from each block were randomly assigned to two conditions. Half of the specimens were tested either immediately after beam production (Dry) or after long-term water storage (37 degrees C, 150 days) followed by thermocyling (12,000 cycles, 5-55 degrees C) in a universal testing machine (1 mm/min). Failure types were analyzed under an optical microscope and SEM.Results. mu TBS results were significantly affected by the repair method (p=0.0001) and the aging conditions (p=0.0001) (two-way ANOVA, Tukey's test). In dry testing conditions, PR method showed significantly higher (p < 0.001) repair bond strength (19.8 +/- 3.8 MPa) than those of CJ and CL (12.4 +/- 4.7 and 9.9 +/- 2.9, respectively). After long-term water storage and thermocycling, CJ revealed significantly higher results (14.5 +/- 3.1 MPa) than those of PR (12.1 +/- 2.6 MPa) (p < 0.01) and CL (4.2 +/- 2.1 MPa) (p < 0.001). In all groups when tested in dry conditions, cohesive failure in the composite accompanied with adhesive failure at the interface (mixed failures), was frequently observed (76%, 80%, 65% for PR, CJ and CL, respectively). After aging conditions, while the specimens treated with PR and CJ presented primarily mixed failure types (52% and 87%, respectively), CL group presented mainly complete adhesive failures at the interface (70%).Significance. Hydrolytic stability of the repair method based on silica coating and silanization was superior to the other repair strategies for the ceramic tested. (C) 2009 Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.