Tick saliva inhibits the chemotactic function of MIP-1 alpha and selectively impairs chemotaxis of immature dendritic cells by down-regulating cell-surface CCR5

Ticks are blood-feeding arthropods that secrete immunomodulatory molecules through their saliva to antagonize host inflammatory and immune responses. As dendritic cells (DCs) play a major role in host immune responses, we studied the effects of Rhipicephalus sanguineus tick saliva on DC migration and function. Bone marrow-derived immature DCs pre-exposed to tick saliva showed reduced migration towards macrophage inflammatory protein (MIP)-1 alpha, MIP-1 beta and regulated upon activation, normal T cell expressed and secreted (RANTES) chemokines in a Boyden microchamber assay. This inhibition was mediated by saliva which significantly reduced the percentage and the average cell-surface expression of CC chemokine receptor CCR5. In contrast, saliva did not alter migration of DCs towards MIP-3 beta, not even if the cells were induced for maturation. Next, we evaluated the effect of tick saliva on the activity of chemokines related to DC migration and showed that tick saliva per se inhibits the chemotactic function of MIP-1 alpha, while it did not affect RANTES, MIP-1 beta and MIP-3 beta. These data suggest that saliva possibly reduces immature DC migration, while mature DC chemotaxis remains unaffected. In support of this, we have analyzed the percentage of DCs on mice 48 h after intradermal inoculation with saliva and found that the DC turnover in the skin was reduced compared with controls. Finally, to test the biological activity of the saliva-exposed DCs, we transferred DCs pre-cultured with saliva and loaded with the keyhole limpet haemocyanin (KLH) antigen to mice and measured their capacity to induce specific T cell cytokines. Data showed that saliva reduced the synthesis of both T helper (Th)1 and Th2 cytokines, suggesting the induction of a non-polarised T cell response. These findings propose that the inhibition of DCs migratory ability and function may be a relevant mechanism used by ticks to subvert the immune response of the host. (c) 2007 Australian Society for Parasitology Inc. Published by Elsevier Ltd. All rights reserved.

Altered left ventricular diastolic function in subjects with spinal cord injury

Study design: This is cross-sectional study. Objectives: The aim of this study is to investigate the cardiac structure and function of subjects with spinal cord injury (SCI) and the impact of metabolic, hemodynamic and inflammatory factors on these parameters. Setting: Sao Paulo, Brazil. Methods: Sixty-five nondiabetic, nonhypertensive, sedentary, nonsmoker men (34 with SCI and 31 healthy subjects) were evaluated by medical history, anthropometry, laboratory tests, analysis of hemodynamic and inflammatory parameters and echocardiography. Results: Subjects with SCI had lower systolic blood pressure and higher levels of C-reactive protein and tumor necrosis factor receptors than the healthy ones. Echocardiography data showed that the SCI group presented similar left ventricular (LV) structural and systolic parameters, but lower initial diastolic velocity (Em) (9.2 +/- 0.5 vs 12.3 +/- 0.5 cm s(-1); P<0.001) and higher peak early inflow velocity (E)/Em ratio (7.7 +/- 0.5 vs 6.1 +/- 0.3; P = 0.009) compared with the able-bodied group, even after adjustment for systolic blood pressure and C-reactive protein levels. Furthermore, injured subjects with E/Em >8 had lower peak spectral longitudinal contraction (Sm) (9.0 +/- 0.7 vs 11.6 +/- 0.4cm s(-1); P<0.001) and cardiac output (4.2 +/- 0.2 vs 5.0 +/- 0.21 min(-1); P = 0.029), as well as higher relative wall thickness (0.38 +/- 0.01 vs 0.35 +/- 0.01; P = 0.005), than individuals with SCI with E/Em<8, but similar age, body mass index, blood pressure, injury level, metabolic parameters and inflammatory marker levels. Conclusion: Subjects with SCI presented impaired LV diastolic function in comparison with able-bodied ones. Moreover, worse LV diastolic function was associated with a pattern of LV concentric remodeling and subclinical decreases in systolic function among injured subjects. Overall, these findings might contribute to explain the increased cardiovascular risk reported for individuals with SCI. Spinal Cord (2011) 49, 65-69; doi: 10.1038/sc.2010.88; published online 27 July 2010

Node-Depth Encoding and Multiobjective Evolutionary Algorithm Applied to Large-Scale Distribution System Reconfiguration

The power loss reduction in distribution systems (DSs) is a nonlinear and multiobjective problem. Service restoration in DSs is even computationally hard since it additionally requires a solution in real-time. Both DS problems are computationally complex. For large-scale networks, the usual problem formulation has thousands of constraint equations. The node-depth encoding (NDE) enables a modeling of DSs problems that eliminates several constraint equations from the usual formulation, making the problem solution simpler. On the other hand, a multiobjective evolutionary algorithm (EA) based on subpopulation tables adequately models several objectives and constraints, enabling a better exploration of the search space. The combination of the multiobjective EA with NDE (MEAN) results in the proposed approach for solving DSs problems for large-scale networks. Simulation results have shown the MEAN is able to find adequate restoration plans for a real DS with 3860 buses and 632 switches in a running time of 0.68 s. Moreover, the MEAN has shown a sublinear running time in function of the system size. Tests with networks ranging from 632 to 5166 switches indicate that the MEAN can find network configurations corresponding to a power loss reduction of 27.64% for very large networks requiring relatively low running time.

Connection Admission Control for a WDM Optical Network Based on Traffic Monitoring and Bandwidth Release

We proposed a connection admission control (CAC) to monitor the traffic in a multi-rate WDM optical network. The CAC searches for the shortest path connecting source and destination nodes, assigns wavelengths with enough bandwidth to serve the requests, supervises the traffic in the most required nodes, and if needed activates a reserved wavelength to release bandwidth according to traffic demand. We used a scale-free network topology, which includes highly connected nodes ( hubs), to enhance the monitoring procedure. Numerical results obtained from computational simulations show improved network performance evaluated in terms of blocking probability.

Performance analysis of an optical network employing waveband and traffic grooming

This paper analyses an optical network architecture composed by an arrangement of nodes equipped with multi-granular optical cross-connects (MG-OXCs) in addition to the usual optical cross-connects (OXCs). Then, selected network nodes can perform both waveband as well as traffic grooming operations and our goal is to assess the improvement on network performance brought by these additional capabilities. Specifically, the influence of the MG-OXC multi-granularity on the blocking probability is evaluated for 16 classes of service over a network based on the NSFNet topology. A mechanism of fairness in bandwidth capacity is also added to the connection admission control to manage the blocking probabilities of all kind of bandwidth requirements. Comprehensive computational simulation are carried out to compare eight distinct node architectures, showing that an adequate combination of waveband and single-wavelength ports of the MG-OXCs and OXCs allow a more efficient operation of a WDM optical network carrying multi-rate traffic.

Neural network model for designing automotive devices using SMD LED

The advantages offered by the electronic component LED (Light Emitting Diode) have resulted in a quick and extensive application of this device in the replacement of incandescent lights. In this combined application, however, the relationship between the design variables and the desired effect or result is very complex and renders it difficult to model using conventional techniques. This paper consists of the development of a technique using artificial neural networks that makes it possible to obtain the luminous intensity values of brake lights using SMD (Surface Mounted Device) LEDs from design data. This technique can be utilized to design any automotive device that uses groups of SMD LEDs. The results of industrial applications using SMD LED are presented to validate the proposed technique.

Neural network-based H(infinity) control for fully actuated and underactuated cooperative manipulators

This paper develops H(infinity) control designs based on neural networks for fully actuated and underactuated cooperative manipulators. The neural networks proposed in this paper only adapt the uncertain dynamics of the robot manipulators. They work as a complement of the nominal model. The H(infinity) performance index includes the position errors as well the squeeze force errors between the manipulator end-effectors and the object, which represents a complete disturbance rejection scenario. For the underactuated case, the squeeze force control problem is more difficult to solve due to the loss of some degrees of manipulator actuation. Results obtained from an actual cooperative manipulator, which is able to work as a fully actuated and an underactuated manipulator, are presented. (C) 2008 Elsevier Ltd. All rights reserved.

Decision making in fuzzy environment and multicriteria power engineering problems

This paper presents results of research into the use of the Bellman-Zadeh approach to decision making in a fuzzy environment for solving multicriteria power engineering problems. The application of the approach conforms to the principle of guaranteed result and provides constructive lines in computationally effective obtaining harmonious solutions on the basis of solving associated maxmin problems. The presented results are universally applicable and are already being used to solve diverse classes of power engineering problems. It is illustrated by considering problems of power and energy shortage allocation, power system operation, optimization of network configuration in distribution systems, and energetically effective voltage control in distribution systems. (c) 2011 Elsevier Ltd. All rights reserved.

Implementation of a Control Loop Experiment in a Network-Based Control System With LonWorks Technology and IP Networks

Considering the increasing popularity of network-based control systems and the huge adoption of IP networks (such as the Internet), this paper studies the influence of network quality of service (QoS) parameters over quality of control parameters. An example of a control loop is implemented using two LonWorks networks (CEA-709.1) interconnected by an emulated IP network, in which important QoS parameters such as delay and delay jitter can be completely controlled. Mathematical definitions are provided according to the literature, and the results of the network-based control loop experiment are presented and discussed.

Whirlwind: a new cryptographic hash function

A new cryptographic hash function Whirlwind is presented. We give the full specification and explain the design rationale. We show how the hash function can be implemented efficiently in software and give first performance numbers. A detailed analysis of the security against state-of-the-art cryptanalysis methods is also provided. In comparison to the algorithms submitted to the SHA-3 competition, Whirlwind takes recent developments in cryptanalysis into account by design. Even though software performance is not outstanding, it compares favourably with the 512-bit versions of SHA-3 candidates such as LANE or the original CubeHash proposal and is about on par with ECHO and MD6.

Fuzzy risk index for power transformer failures due to external short-circuits

A novel methodology to assess the risk of power transformer failures caused by external faults, such as short-circuit, taking the paper insulation condition into account, is presented. The risk index is obtained by contrasting the insulation paper condition with the probability that the transformer withstands the short-circuit current flowing along the winding during an external fault. In order to assess the risk, this probability and the value of the degree of polymerization of the insulating paper are regarded as inputs of a type-2 fuzzy logic system (T2-FLS), which computes the fuzzy risk level. A Monte Carlo simulation has been used to find the survival function of the currents flowing through the transformer winding during a single-phase or a three-phase short-circuit. The Roy Billinton Test System and a real power system have been used to test the results. (C) 2008 Elsevier B.V. All rights reserved.

Debris flow affecting the Cubatauo Oil Refinery, Brazil

On February 6, 1994, a large debris flow developed because of intense rains in a 800-m-high mountain range called Serra do Cubatao, the local name for the Serra do Mar, located along the coast of the state of Sao Paulo, Brazil. It affected the Presidente Bernardes Refinery, owned by Petrobras, in Cubatao. The damages amounted to about US $40 million because of the muck cleaning, repairs, and 3-week interruption of the operations. This prompted Petrobras to conduct studies, carried out by the authors, to develop protection works, which were done at a cost of approximately US $12 million. The paper describes the studies conducted on debris flow mechanics. A new criteria to define rainfall intensities that trigger debris flows is presented, as well as a correlation of slipped area with soil porosity and rain intensity. Also presented are (a) an actual grain size distribution of a deposited material, determined by laboratory and a large-scale field test, and (b) the size distribution of large boulders along the river bed. Based on theory, empirical experience and back-analysis of the events, the main parameters as the front velocity, the peak discharge and the volume of the transported sediments were determined in a rational basis for the design of the protection works. Finally, the paper describes the set of the protection works built, emphasizing their concept and function. They also included some low-cost innovative works.

Comparison between detailed model simulation and artificial neural network for forecasting building energy consumption

There are several ways to attempt to model a building and its heat gains from external sources as well as internal ones in order to evaluate a proper operation, audit retrofit actions, and forecast energy consumption. Different techniques, varying from simple regression to models that are based on physical principles, can be used for simulation. A frequent hypothesis for all these models is that the input variables should be based on realistic data when they are available, otherwise the evaluation of energy consumption might be highly under or over estimated. In this paper, a comparison is made between a simple model based on artificial neural network (ANN) and a model that is based on physical principles (EnergyPlus) as an auditing and predicting tool in order to forecast building energy consumption. The Administration Building of the University of Sao Paulo is used as a case study. The building energy consumption profiles are collected as well as the campus meteorological data. Results show that both models are suitable for energy consumption forecast. Additionally, a parametric analysis is carried out for the considered building on EnergyPlus in order to evaluate the influence of several parameters such as the building profile occupation and weather data on such forecasting. (C) 2008 Elsevier B.V. All rights reserved.

Estudo de variabilidade e otimização do circuito de moagem SAG da Usina do Sossego

Sossego was the first Vale SAG mill operation to process copper-gold ore. It is located in the State of Para, southeastern Amazon region of Brazil. In the first three years of continuous operation, Vale investigated different alternatives for improving the circuit`s performance by investigating operating conditions, mainly focusing on the SAG mill. It was decided to further assess the performance of the comminution circuit as a function of ore characteristics. A comprehensive ore characterization program was then conducted, together with the calibration of mathematical models on the basis of surveys carried out at the industrial circuit. The simulator was then used to predict the throughput associated to each ore type, as well as to establish the optimized circuit configuration and tailored operating conditions. This paper describes in detail the main aspects of optimizing the industrial circuit performance, as well as the successful method for predicting the production as a function of ore characteristics and circuit configuration.

Topology optimization for designing strain-gauge load cells

Load cells are used extensively in engineering fields. This paper describes a novel structural optimization method for single- and multi-axis load cell structures. First, we briefly explain the topology optimization method that uses the solid isotropic material with penalization (SIMP) method. Next, we clarify the mechanical requirements and design specifications of the single- and multi-axis load cell structures, which are formulated as an objective function. In the case of multi-axis load cell structures, a methodology based on singular value decomposition is used. The sensitivities of the objective function with respect to the design variables are then formulated. On the basis of these formulations, an optimization algorithm is constructed using finite element methods and the method of moving asymptotes (MMA). Finally, we examine the characteristics of the optimization formulations and the resultant optimal configurations. We confirm the usefulness of our proposed methodology for the optimization of single- and multi-axis load cell structures.