Basement membrane and provisional matrix components (collagen type IV, laminins and von Willebrand factor) in rheumatoid arthritis and Sjögren s syndrome

The aim of this study was twofold- Firstly, to determine the composition of the type IV collagen which are the major components of the basement membrane (BM), in the synovial lining of the rheumatoid arthritis (RA) patient and in the BM in the labial salivary gland of the Sjögrens syndrome (SS) patient. Secondly, this thesis aimed to investigate the role of the BM component laminin α4 and laminin α5 in the migration of neutrophils from the blood vessels thorough the synovial lining layer into synovial fluid and the presence of vWF in the microvasculature of labial salivary gland in SS. Our studies showed that certain α chains type IV collagen are low in RA compared to control synovial linings, while laminin α5 exhibited a pattern of low expression regions at the synovial lining interface towards the joint cavity and fluid. Also, high numbers of macrophage-like lining cells containing MMP-9 were found in the lining. MMP-9 was also found in the synovial fluid. Collagen α1/2 (IV) mRNA was found to be present in high amount compared to the other α(IV) chains and also showed intense labelling in immunohistochemical staining in normal and SS patients. In healthy glands α5(IV) and α6(IV) chains were found to be continuous around ducts but discontinuous around acini. The α5(IV) and α6(IV) mRNAs were present in LSG explants and HSG cell line, while in SS these chains seemed to be absent or appear only in patches around the ductal BM and tended to be absent around acini in immunohistochemical staining, indicating that their synthesis and/or degradation seemed to be locally regulated around acinar cells. The provisional matrix component vWF serves as a marker of vascular damage. Microvasculature in SS showed signs of focal damage which in turn might impair arteriolar feeding, capillary transudation and venular drainage of blood. However, capillary density was not decreased but rather increased, perhaps as a result of angiogenesis compensatory to microvascular damage. Microvascular involvement of LSG may contribute to the pathogenesis of this syndrome. This twofold approach allows us to understand the intricate relation between the ECM components and the immunopathological changes that occur during the pathogenesis of these inflammatory rheumatic disease processes. Also notably this study highlights the importance of maintaining a healthy ECM to prevent the progression or possibly allow reversal of the disease to a considerable level. Furthermore, it can be speculated that a healthy BM could quarantine the inflamed region or in case of cancer cells barricade the movement of malignant cells thereby preventing further spread to the surrounding areas. This understanding can be further applied to design appropriate drugs which act specifically to maintain a proper BM/BM like intercellular matrix composition.

Seismic damage estimation through measurable dynamic characteristics

Ductility based design of reinforced concrete structures implicitly assumes certain damage under the action of a design basis earthquake. The damage undergone by a structure needs to be quantified, so as to assess the post-seismic reparability and functionality of the structure. The paper presents an analytical method of quantification and location of seismic damage, through system identification methods. It may be noted that soft ground storied buildings are the major casualties in any earthquake and hence the example structure is a soft or weak first storied one, whose seismic response and temporal variation of damage are computed using a non-linear dynamic analysis program (IDARC) and compared with a normal structure. Time period based damage identification model is used and suitably calibrated with classic damage models. Regenerated stiffness of the three degrees of freedom model (for the three storied frame) is used to locate the damage, both on-line as well as after the seismic event. Multi resolution analysis using wavelets is also used for localized damage identification for soft storey columns.

Fuzzy-logic-based health monitoring and residual-life prediction for composite helicopter rotor

A health-monitoring and life-estimation strategy for composite rotor blades is developed in this work. The cross-sectional stiffness reduction obtained by physics-based models is expressed as a function of the life of the structure using a recent phenomenological damage model. This stiffness reduction is further used to study the behavior of measurable system parameters such as blade deflections, loads, and strains of a composite rotor blade in static analysis and forward flight. The simulated measurements are obtained using an aeroelastic analysis of the composite rotor blade based on the finite element in space and time with physics-based damage modes that are then linked to the life consumption of the blade. The model-based measurements are contaminated with noise to simulate real data. Genetic fuzzy systems are developed for global online prediction of physical damage and life consumption using displacement- and force-based measurement deviations between damaged and undamaged conditions. Furthermore, local online prediction of physical damage and life consumption is done using strains measured along the blade length. It is observed that the life consumption in the matrix-cracking zone is about 12-15% and life consumption in debonding/delamination zone is about 45-55% of the total life of the blade. It is also observed that the success rate of the genetic fuzzy systems depends upon the number of measurements, type of measurements and training, and the testing noise level. The genetic fuzzy systems work quite well with noisy data and are recommended for online structural health monitoring of composite helicopter rotor blades.

Estimation of remaining life of power transformers

Inadvertent failure of power transformers has serious consequences on the power system reliability, economics and the revenue accrual. Insulation is the weakest link in the power transformer prompting periodic inspection of the status of insulation at different points in time. A close Monitoring of the electrical, chemical and such other properties on insulation as are sensitive to the amount of time-dependent degradation becomes mandatory to judge the status of the equipment. Data-driven Diagnostic Testing and Condition Monitoring (DTCM) specific to power transformer is the aspect in focus. Authors develop a Monte Carlo approach for augmenting the rather scanty experimental data normally acquired using Proto-types of power transformers. Also described is a validation procedure for estimating the accuracy of the Model so developed.

Highly stable Ag nanoparticles in agar-agar matrix as inorganic-organic hybrid

A novel synthesis of inorganic-organic hybrid films containing well dispersed and almost uniform size Ag nanoparticles in agar-agar matrix has been reported. The films are found to be highly stable for more than a year. The colloidal particles of Ag can be obtained in large quantities in the form of a film or in the gel form when dispersed in agar-agar or by dissolving in a suitable solvent as solution. Characterization has been done by UV-visible spectroscopy and TEM. The hybrid may be of interest to study third-order non-linear susceptibility.

Hanle-Zeeman redistribution matrix. I. Classical theory expressions in the laboratory frame

Polarized scattering in spectral lines is governed by a 4; 4 matrix that describes how the Stokes vector is scattered and redistributed in frequency and direction. Here we develop the theory for this redistribution matrix in the presence of magnetic fields of arbitrary strength and direction. This general magnetic field case is called the Hanle- Zeeman regime, since it covers both of the partially overlapping weak- and strong- field regimes in which the Hanle and Zeeman effects dominate the scattering polarization. In this general regime, the angle-frequency correlations that describe the so-called partial frequency redistribution (PRD) are intimately coupled to the polarization properties. We develop the theory for the PRD redistribution matrix in this general case and explore its detailed mathematical properties and symmetries for the case of a J = 0 -> 1 -> 0 scattering transition, which can be treated in terms of time-dependent classical oscillator theory. It is shown how the redistribution matrix can be expressed as a linear superposition of coherent and noncoherent parts, each of which contain the magnetic redistribution functions that resemble the well- known Hummer- type functions. We also show how the classical theory can be extended to treat atomic and molecular scattering transitions for any combinations of quantum numbers.

Estimation of thermal breakdown voltage of HVDC cables - A theoretical framework

The insulation in a dc cable is subjected to both thermal and electric stress at the same time. While the electric stress is generic to the cable, the temperature rise in the insulation is, by and large, due to the Ohmic losses in the conductor. The consequence of this synergic effect is to reduce the maximum operating voltage and causes a premature failure of the cable. The authors examine this subject in some detail and propose a comprehensive theoretical formulation relating the maximum thermal voltage (MTV) to the physical and geometrical parameters of the insulation. The heat flow patterns and boundary conditions considered by the authors here and those found in earlier literature are provided. The MTV of a dc cable is shown to be a function of the load current apart from the resistance of the insulation. The results obtained using the expressions, developed by the authors, are compared with relevant results published in the literature and found to be in close conformity.

Performance estimation of streaming applications for hierarchical MPSoCs

Parallel programming and effective partitioning of applications for embedded many-core architectures requires optimization algorithms. However, these algorithms have to quickly evaluate thousands of different partitions. We present a fast performance estimator embedded in a parallelizing compiler for streaming applications. The estimator combines a single execution-based simulation and an analytic approach. Experimental results demonstrate that the estimator has a mean error of 2.6% and computes its estimation 2848 times faster compared to a cycle accurate simulator.

Matrix proteinases in lung injury in the preterm infant

During inflammation, excess production and release of matrix proteinases, including matrix metalloproteinases (MMPs) and serine proteinases, may result in dysregulated extracellular proteolysis leading to development of tissue damage. Pulmonary inflammation may play an important role in the pathogenesis of lung injury in the preterm infant. The aims of this study were to evaluate involvement of MMPs and serine proteinase trypsin in acute and chronic lung injury in preterm infants and to study the role of these enzymes in acute lung injury by means of an animal model of hyperoxic lung injury. Molecular forms and levels of MMP-2, -8, and -9, and their specific inhibitor, tissue inhibitor of metalloproteinases (TIMP)-2, as well as trypsin were studied in tracheal aspirate fluid (TAF) samples collected from preterm infants with respiratory distress. Expression and distribution of trypsin-2 and proteinase-activated receptor 2 (PAR2) was examined in autopsy lung specimens from fetuses, from preterm infants with respiratory distress syndrome (RDS) or bronchopulmonary dysplasia (BPD), and from newborn infants without lung injury. We detected higher MMP-8 and trypsin-2 and lower TIMP-2 in TAF from preterm infants with more severe acute respiratory distress. Infants subsequently developing BPD had higher levels of MMP-8 and trypsin-2 early postnatally than did those who survived without this chronic lung injury. Immunohistochemically, trypsin-2 was mainly detectable in bronchial epithelium, but also in alveolar epithelium, and its expression was strongest in prolonged RDS. Since trypsin-2 is potent activator of PAR2, a G-protein coupled receptor involved in inflammation, we studied PAR2 expression in the lung. PAR2 co-localized with trypsin-2 in bronchoalveolar epithelium and its expression was significantly higher in bronchoalveolar epithelium in preterm infants with prolonged RDS than in newborn controls. In the experimental study, rats were exposed to >95% oxygen for 24, 48, and 60 hours, or room air. At 48 hours of hyperoxia, MMP-8 and trypsin levels sharply increased in bronchoalveolar lavage fluid, and expression of trypsin appeared in alveolar epithelium, and MMP-8 predominantly in macrophages. In conclusion, high pulmonary MMP-8 and trypsin-2 early postnatally are associated with severity of acute lung injury and subsequent development of BPD in preterm infants. In the injured preterm lung, trypsin-2 co-localizes with PAR2 in bronchoalveolar epithelium, suggesting that PAR2 activated by high levels of trypsin-2 is involved in lung inflammation associated with development of BPD. Marked increase in MMP-8 and trypsin early in the course of experimental hyperoxic lung injury suggests that these enzymes play a role in the pathogenesis of acute lung injury. Further exploration of the roles of trypsin and MMP-8 in lung injury may offer new targets for therapeutic intervention.

Analytical models for capacity estimation of IEEE 802.11 WLANs using DCF for internet applications

We provide analytical models for capacity evaluation of an infrastructure IEEE 802.11 based network carrying TCP controlled file downloads or full-duplex packet telephone calls. In each case the analytical models utilize the attempt probabilities from a well known fixed-point based saturation analysis. For TCP controlled file downloads, following Bruno et al. (In Networking '04, LNCS 2042, pp. 626-637), we model the number of wireless stations (STAs) with ACKs as a Markov renewal process embedded at packet success instants. In our work, analysis of the evolution between the embedded instants is done by using saturation analysis to provide state dependent attempt probabilities. We show that in spite of its simplicity, our model works well, by comparing various simulated quantities, such as collision probability, with values predicted from our model. Next we consider N constant bit rate VoIP calls terminating at N STAs. We model the number of STAs that have an up-link voice packet as a Markov renewal process embedded at so called channel slot boundaries. Analysis of the evolution over a channel slot is done using saturation analysis as before. We find that again the AP is the bottleneck, and the system can support (in the sense of a bound on the probability of delay exceeding a given value) a number of calls less than that at which the arrival rate into the AP exceeds the average service rate applied to the AP. Finally, we extend the analytical model for VoIP calls to determine the call capacity of an 802.11b WLAN in a situation where VoIP calls originate from two different types of coders. We consider N-1 calls originating from Type 1 codecs and N-2 calls originating from Type 2 codecs. For G711 and G729 voice coders, we show that the analytical model again provides accurate results in comparison with simulations.

Optimal Nonlinear Control and Estimation for a Reusable Launch Vehicle During Reentry Phase

In this paper a nonlinear optimal controller has been designed for aerodynamic control during the reentry phase of the Reusable Launch Vehicle (RLV). The controller has been designed based on a recently developed technique Optimal Dynamic Inversion (ODI). For full state feedback the controller has required full information about the system states. In this work an Extended Kalman filter (EKF) is developed to estimate the states. The vehicle (RLV) has been has been consider as a nonlinear Six-Degree-Of-Freedom (6-DOF) model. The simulation results shows that EKF gives a very good estimation of the states and it is working well with ODI. The resultant trajectories are very similar to those obtained by perfect state feedback using ODI only.

Bayesian estimation of small effects in exercise and sports science

The aim of this paper is to provide a Bayesian formulation of the so-called magnitude-based inference approach to quantifying and interpreting effects, and in a case study example provide accurate probabilistic statements that correspond to the intended magnitude-based inferences. The model is described in the context of a published small-scale athlete study which employed a magnitude-based inference approach to compare the effect of two altitude training regimens (live high-train low (LHTL), and intermittent hypoxic exposure (IHE)) on running performance and blood measurements of elite triathletes. The posterior distributions, and corresponding point and interval estimates, for the parameters and associated effects and comparisons of interest, were estimated using Markov chain Monte Carlo simulations. The Bayesian analysis was shown to provide more direct probabilistic comparisons of treatments and able to identify small effects of interest. The approach avoided asymptotic assumptions and overcame issues such as multiple testing. Bayesian analysis of unscaled effects showed a probability of 0.96 that LHTL yields a substantially greater increase in hemoglobin mass than IHE, a 0.93 probability of a substantially greater improvement in running economy and a greater than 0.96 probability that both IHE and LHTL yield a substantially greater improvement in maximum blood lactate concentration compared to a Placebo. The conclusions are consistent with those obtained using a ‘magnitude-based inference’ approach that has been promoted in the field. The paper demonstrates that a fully Bayesian analysis is a simple and effective way of analysing small effects, providing a rich set of results that are straightforward to interpret in terms of probabilistic statements.

Exploiting ground-based measurements of the Global Positioning System for numerical weather prediction

Data assimilation provides an initial atmospheric state, called the analysis, for Numerical Weather Prediction (NWP). This analysis consists of pressure, temperature, wind, and humidity on a three-dimensional NWP model grid. Data assimilation blends meteorological observations with the NWP model in a statistically optimal way. The objective of this thesis is to describe methodological development carried out in order to allow data assimilation of ground-based measurements of the Global Positioning System (GPS) into the High Resolution Limited Area Model (HIRLAM) NWP system. Geodetic processing produces observations of tropospheric delay. These observations can be processed either for vertical columns at each GPS receiver station, or for the individual propagation paths of the microwave signals. These alternative processing methods result in Zenith Total Delay (ZTD) and Slant Delay (SD) observations, respectively. ZTD and SD observations are of use in the analysis of atmospheric humidity. A method is introduced for estimation of the horizontal error covariance of ZTD observations. The method makes use of observation minus model background (OmB) sequences of ZTD and conventional observations. It is demonstrated that the ZTD observation error covariance is relatively large in station separations shorter than 200 km, but non-zero covariances also appear at considerably larger station separations. The relatively low density of radiosonde observing stations limits the ability of the proposed estimation method to resolve the shortest length-scales of error covariance. SD observations are shown to contain a statistically significant signal on the asymmetry of the atmospheric humidity field. However, the asymmetric component of SD is found to be nearly always smaller than the standard deviation of the SD observation error. SD observation modelling is described in detail, and other issues relating to SD data assimilation are also discussed. These include the determination of error statistics, the tuning of observation quality control and allowing the taking into account of local observation error correlation. The experiments made show that the data assimilation system is able to retrieve the asymmetric information content of hypothetical SD observations at a single receiver station. Moreover, the impact of real SD observations on humidity analysis is comparable to that of other observing systems.