Surgical fusion of early onset severe scoliosis increases survival in Rett syndrome: A cohort study

Aim Scoliosis is a common co-morbidity in Rett syndrome and spinal fusion may be recommended if severe. We investigated the impact of spinal fusion on survival and risk of severe lower respiratory tract infection in Rett syndrome. Method Data were ascertained from hospital medical records, the Australian Rett Syndrome Database, a longitudinal and population-based registry, and from the Australian Institute of Health and Welfare National Death Index database. Cox regression and generalized estimating equation models were used to estimate the effects of spinal surgery on survival and severe respiratory infection respectively in 140 females who developed severe scoliosis (Cobb angle ≥45°) before adulthood. Results After adjusting for mutation type and age of scoliosis onset, the rate of death was lower in the surgery group (hazard ratio [HR] 0.30, 95% confidence interval [CI] 0.12–0.74; p=0.009) compared to those without surgery. Rate of death was particularly reduced for those with early onset scoliosis (HR 0.17, 95% CI 0.06–0.52; p=0.002). There was some evidence to suggest that spinal fusion was associated with a reduction in risk of severe respiratory infection among those with early onset scoliosis (risk ratio 0.41, 95% CI 0.16–1.03; p=0.06). Interpretation With appropriate cautions, spinal fusion confers an advantage to life expectancy in Rett syndrome.

Problems and Algorithms for Sequence Segmentations

The analysis of sequential data is required in many diverse areas such as telecommunications, stock market analysis, and bioinformatics. A basic problem related to the analysis of sequential data is the sequence segmentation problem. A sequence segmentation is a partition of the sequence into a number of non-overlapping segments that cover all data points, such that each segment is as homogeneous as possible. This problem can be solved optimally using a standard dynamic programming algorithm. In the first part of the thesis, we present a new approximation algorithm for the sequence segmentation problem. This algorithm has smaller running time than the optimal dynamic programming algorithm, while it has bounded approximation ratio. The basic idea is to divide the input sequence into subsequences, solve the problem optimally in each subsequence, and then appropriately combine the solutions to the subproblems into one final solution. In the second part of the thesis, we study alternative segmentation models that are devised to better fit the data. More specifically, we focus on clustered segmentations and segmentations with rearrangements. While in the standard segmentation of a multidimensional sequence all dimensions share the same segment boundaries, in a clustered segmentation the multidimensional sequence is segmented in such a way that dimensions are allowed to form clusters. Each cluster of dimensions is then segmented separately. We formally define the problem of clustered segmentations and we experimentally show that segmenting sequences using this segmentation model, leads to solutions with smaller error for the same model cost. Segmentation with rearrangements is a novel variation to the segmentation problem: in addition to partitioning the sequence we also seek to apply a limited amount of reordering, so that the overall representation error is minimized. We formulate the problem of segmentation with rearrangements and we show that it is an NP-hard problem to solve or even to approximate. We devise effective algorithms for the proposed problem, combining ideas from dynamic programming and outlier detection algorithms in sequences. In the final part of the thesis, we discuss the problem of aggregating results of segmentation algorithms on the same set of data points. In this case, we are interested in producing a partitioning of the data that agrees as much as possible with the input partitions. We show that this problem can be solved optimally in polynomial time using dynamic programming. Furthermore, we show that not all data points are candidates for segment boundaries in the optimal solution.

A data fusion approach of multiple maintenance data sources for real-world reliability modelling

A central tenet in the theory of reliability modelling is the quantification of the probability of asset failure. In general, reliability depends on asset age and the maintenance policy applied. Usually, failure and maintenance times are the primary inputs to reliability models. However, for many organisations, different aspects of these data are often recorded in different databases (e.g. work order notifications, event logs, condition monitoring data, and process control data). These recorded data cannot be interpreted individually, since they typically do not have all the information necessary to ascertain failure and preventive maintenance times. This paper presents a methodology for the extraction of failure and preventive maintenance times using commonly-available, real-world data sources. A text-mining approach is employed to extract keywords indicative of the source of the maintenance event. Using these keywords, a Naïve Bayes classifier is then applied to attribute each machine stoppage to one of two classes: failure or preventive. The accuracy of the algorithm is assessed and the classified failure time data are then presented. The applicability of the methodology is demonstrated on a maintenance data set from an Australian electricity company.

Molecular modeling of Bt Cry1Ac (DI–DII)–ASAL (Allium sativum lectin)–fusion protein and its interaction with aminopeptidase N (APN) receptor of Manduca sexta

Genetic engineering of Bacillus thuringiensis (Bt) Cry proteins has resulted in the synthesis of various novel toxin proteins with enhanced insecticidal activity and specificity towards different insect pests. In this study, a fusion protein consisting of the DI–DII domains of Cry1Ac and garlic lectin (ASAL) has been designed in silico by replacing the DIII domain of Cry1Ac with ASAL. The binding interface between the DI–DII domains of Cry1Ac and lectin has been identified using protein–protein docking studies. Free energy of binding calculations and interaction profiles between the Cry1Ac and lectin domains confirmed the stability of fusion protein. A total of 18 hydrogen bonds was observed in the DI–DII–lectin fusion protein compared to 11 hydrogen bonds in the Cry1Ac (DI–DII–DIII) protein. Molecular mechanics/Poisson–Boltzmann (generalized-Born) surface area [MM/PB (GB) SA] methods were used for predicting free energy of interactions of the fusion proteins. Protein–protein docking studies based on the number of hydrogen bonds, hydrophobic interactions, aromatic–aromatic, aromatic–sulphur, cation–pi interactions and binding energy of Cry1Ac/fusion proteins with the aminopeptidase N (APN) of Manduca sexta rationalised the higher binding affinity of the fusion protein with the APN receptor compared to that of the Cry1Ac–APN complex, as predicted by ZDOCK, Rosetta and ClusPro analysis. The molecular binding interface between the fusion protein and the APN receptor is well packed, analogously to that of the Cry1Ac–APN complex. These findings offer scope for the design and development of customized fusion molecules for improved pest management in crop plants.

Bio-inspired multifunctional metallic foams through the fusion of different biological solutions

Nature is a school for scientists and engineers. Inherent multiscale structures of biological materials exhibit multifunctional integration. In nature, the lotus, the water strider, and the flying bird evolved different and optimized biological solutions to survive. In this contribution, inspired by the optimized solutions from the lotus leaf with superhydrophobic self-cleaning, the water strider leg with durable and robust superhydrophobicity, and the lightweight bird bone with hollow structures, multifunctional metallic foams with multiscale structures are fabricated, demonstrating low adhesive superhydrophobic self-cleaning, striking loading capacity, and superior repellency towards different corrosive solutions. This approach provides an effective avenue to the development of water strider robots and other aquatic smart devices floating on water. Furthermore, the resultant multifunctional metallic foam can be used to construct an oil/water separation apparatus, exhibiting a high separation efficiency and long-term repeatability. The presented approach should provide a promising solution for the design and construction of other multifunctional metallic foams in a large scale for practical applications in the petro-chemical field. Optimized biological solutions continue to inspire and to provide design idea for the construction of multiscale structures with multifunctional integration. Inspired by the optimized biological solutions from the lotus leaf with superhydrophobic self-cleaning, the water strider leg with durable and robust superhydrophobicity, and the lightweight bird bone with hollow structures, multifunctional metallic foams with multiscale structures are fabricated, demonstrating low adhesive superhydrophobic self-cleaning, striking loading capacity, stable corrosion resistance, and oil/water separation.

Decision fusion for reliable flood mapping using remote sensing images

Flood extent mapping is a basic tool for flood damage assessment, which can be done by digital classification techniques using satellite imageries, including the data recorded by radar and optical sensors. However, converting the data into the information we need is not a straightforward task. One of the great challenges involved in the data interpretation is to separate the permanent water bodies and flooding regions, including both the fully inundated areas and the wet areas where trees and houses are partly covered with water. This paper adopts the decision fusion technique to combine the mapping results from radar data and the NDVI data derived from optical data. An improved capacity in terms of identifying the permanent or semi-permanent water bodies from flood inundated areas has been achieved. Computer software tools Multispec and Matlab were used.

Energy efficient change detection over a MAC using physical layer fusion

We propose a simple and energy efficient distributed change detection scheme for sensor networks based on Page's parametric CUSUM algorithm. The sensor observations are IID over time and across the sensors conditioned on the change variable. Each sensor runs CUSUM and transmits only when the CUSUM is above some threshold. The transmissions from the sensors are fused at the physical layer. The channel is modeled as a multiple access channel (MAC) corrupted with IID noise. The fusion center which is the global decision maker, performs another CUSUM to detect the change. We provide the analysis and simulation results for our scheme and compare the performance with an existing scheme which ensures energy efficiency via optimal power selection.

Decentralized sequential change detection using physical layer fusion

We study the problem of decentralized sequential change detection with conditionally independent observations. The sensors form a star topology with a central node called fusion center as the hub. The sensors transmit a simple function of their observations in an analog fashion over a wireless Gaussian multiple access channel and operate under either a power constraint or an energy constraint. Simulations demonstrate that the proposed techniques have lower detection delays when compared with existing schemes. Moreover we demonstrate that the energy-constrained formulation enables better use of the total available energy than a power-constrained formulation.

Phase-Field Simulation of Fusion Interface Events during Solidification of Dissimilar Welds: Effect of Composition Inhomogeneity

We investigate the events near the fusion interfaces of dissimilar welds using a phase-field model developed for single-phase solidification of binary alloys. The parameters used here correspond to the dissimilar welding of a Ni/Cu couple. The events at the Ni and the Cu interface are very different, which illustrate the importance of the phase diagram through the slope of the liquidus curves. In the Ni side, where the liquidus temperature decreases with increasing alloying, solutal melting of the base metal takes place; the resolidification, with continuously increasing solid composition, is very sluggish until the interface encounters a homogeneous melt composition. The growth difficulty of the base metal increases with increasing initial melt composition, which is equivalent to a steeper slope of the liquidus curve. In the Cu side, the initial conditions result in a deeply undercooled melt and contributions from both constrained and unconstrained modes of growth are observed. The simulations bring out the possibility of nucleation of a concentrated solid phase from the melt, and a secondary melting of the substrate due to the associated recalescence event. The results for the Ni and Cu interfaces can be used to understand more complex dissimilar weld interfaces involving multiphase solidification.

Sticking and erosion at carbon-containing plasma-facing materials in fusion reactors

Controlled nuclear fusion is one of the most promising sources of energy for the future. Before this goal can be achieved, one must be able to control the enormous energy densities which are present in the core plasma in a fusion reactor. In order to be able to predict the evolution and thereby the lifetime of different plasma facing materials under reactor-relevant conditions, the interaction of atoms and molecules with plasma first wall surfaces have to be studied in detail. In this thesis, the fundamental sticking and erosion processes of carbon-based materials, the nature of hydrocarbon species released from plasma-facing surfaces, and the evolution of the components under cumulative bombardment by atoms and molecules have been investigated by means of molecular dynamics simulations using both analytic potentials and a semi-empirical tight-binding method. The sticking cross-section of CH3 radicals at unsaturated carbon sites at diamond (111) surfaces is observed to decrease with increasing angle of incidence, a dependence which can be described by a simple geometrical model. The simulations furthermore show the sticking cross-section of CH3 radicals to be strongly dependent on the local neighborhood of the unsaturated carbon site. The erosion of amorphous hydrogenated carbon surfaces by helium, neon, and argon ions in combination with hydrogen at energies ranging from 2 to 10 eV is studied using both non-cumulative and cumulative bombardment simulations. The results show no significant differences between sputtering yields obtained from bombardment simulations with different noble gas ions. The final simulation cells from the 5 and 10 eV ion bombardment simulations, however, show marked differences in surface morphology. In further simulations the behavior of amorphous hydrogenated carbon surfaces under bombardment with D^+, D^+2, and D^+3 ions in the energy range from 2 to 30 eV has been investigated. The total chemical sputtering yields indicate that molecular projectiles lead to larger sputtering yields than atomic projectiles. Finally, the effect of hydrogen ion bombardment of both crystalline and amorphous tungsten carbide surfaces is studied. Prolonged bombardment is found to lead to the formation of an amorphous tungsten carbide layer, regardless of the initial structure of the sample. In agreement with experiment, preferential sputtering of carbon is observed in both the cumulative and non-cumulative simulations

Interatomic potentials for fusion reactor material simulations

Fusion energy is a clean and safe solution for the intricate question of how to produce non-polluting and sustainable energy for the constantly growing population. The fusion process does not result in any harmful waste or green-house gases, since small amounts of helium is the only bi-product that is produced when using the hydrogen isotopes deuterium and tritium as fuel. Moreover, deuterium is abundant in seawater and tritium can be bred from lithium, a common metal in the Earth's crust, rendering the fuel reservoirs practically bottomless. Due to its enormous mass, the Sun has been able to utilize fusion as its main energy source ever since it was born. But here on Earth, we must find other means to achieve the same. Inertial fusion involving powerful lasers and thermonuclear fusion employing extreme temperatures are examples of successful methods. However, these have yet to produce more energy than they consume. In thermonuclear fusion, the fuel is held inside a tokamak, which is a doughnut-shaped chamber with strong magnets wrapped around it. Once the fuel is heated up, it is controlled with the help of these magnets, since the required temperatures (over 100 million degrees C) will separate the electrons from the nuclei, forming a plasma. Once the fusion reactions occur, excess binding energy is released as energetic neutrons, which are absorbed in water in order to produce steam that runs turbines. Keeping the power losses from the plasma low, thus allowing for a high number of reactions, is a challenge. Another challenge is related to the reactor materials, since the confinement of the plasma particles is not perfect, resulting in particle bombardment of the reactor walls and structures. Material erosion and activation as well as plasma contamination are expected. Adding to this, the high energy neutrons will cause radiation damage in the materials, causing, for instance, swelling and embrittlement. In this thesis, the behaviour of a material situated in a fusion reactor was studied using molecular dynamics simulations. Simulations of processes in the next generation fusion reactor ITER include the reactor materials beryllium, carbon and tungsten as well as the plasma hydrogen isotopes. This means that interaction models, {\it i.e. interatomic potentials}, for this complicated quaternary system are needed. The task of finding such potentials is nonetheless nearly at its end, since models for the beryllium-carbon-hydrogen interactions were constructed in this thesis and as a continuation of that work, a beryllium-tungsten model is under development. These potentials are combinable with the earlier tungsten-carbon-hydrogen ones. The potentials were used to explain the chemical sputtering of beryllium due to deuterium plasma exposure. During experiments, a large fraction of the sputtered beryllium atoms were observed to be released as BeD molecules, and the simulations identified the swift chemical sputtering mechanism, previously not believed to be important in metals, as the underlying mechanism. Radiation damage in the reactor structural materials vanadium, iron and iron chromium, as well as in the wall material tungsten and the mixed alloy tungsten carbide, was also studied in this thesis. Interatomic potentials for vanadium, tungsten and iron were modified to be better suited for simulating collision cascades that are formed during particle irradiation, and the potential features affecting the resulting primary damage were identified. Including the often neglected electronic effects in the simulations was also shown to have an impact on the damage. With proper tuning of the electron-phonon interaction strength, experimentally measured quantities related to ion-beam mixing in iron could be reproduced. The damage in tungsten carbide alloys showed elemental asymmetry, as the major part of the damage consisted of carbon defects. On the other hand, modelling the damage in the iron chromium alloy, essentially representing steel, showed that small additions of chromium do not noticeably affect the primary damage in iron. Since a complete assessment of the response of a material in a future full-scale fusion reactor is not achievable using only experimental techniques, molecular dynamics simulations are of vital help. This thesis has not only provided insight into complicated reactor processes and improved current methods, but also offered tools for further simulations. It is therefore an important step towards making fusion energy more than a future goal.

Translational fusion of two beta-subunits of human chorionic gonadotropin results in production of a novel antagonist of

The strategy of translationally fusing the alpha-and beta-subunits of human chorionic gonadotropin (hCG) into a single-chain molecule has been used to produce novel analogs of hCG. Previously we reported expression of a biologically active singlechain analog hCG alpha beta expressed using Pichia expression system. Using the same expression system, another analog, in which the alpha-subunit was replaced with the second beta-subunit, was expressed (hCG beta beta) and purified. hCG beta beta could bind to LH receptor with an affinity three times lower than that of hCG but failed to elicit any response. However, it could inhibit response to the hormone in vitro in a dose- dependent manner. Furthermore, it inhibited response to hCG in vivo indicating the antagonistic nature of the analog. However, it was unable inhibit human FSH binding or response to human FSH, indicating the specificity of the effect. Characterization of hCG alpha beta and hCG beta beta using immunological tools showed alterations in the conformation of some of the epitopes, whereas others were unaltered. Unlike hCG, hCG beta beta interacts with two LH receptor molecules. These studies demonstrate that the presence of the second beta-subunit in the single-chain molecule generated a structure that can be recognized by the receptor. However, due to the absence of alpha-subunit, the molecule is unable to elicit response. The strategy of fusing two beta-subunits of glycoprotein hormones can be used to produce antagonists of these hormones.

Fusion of Multisensor Data:Review and Comparative Analysis

Image fusion is a formal framework which is expressed as means and tools for the alliance of multisensor, multitemporal, and multiresolution data. Multisource data vary in spectral, spatial and temporal resolutions necessitating advanced analytical or numerical techniques for enhanced interpretation capabilities. This paper reviews seven pixel based image fusion techniques - intensity-hue-saturation, brovey, high pass filter (HPF), high pass modulation (HPM), principal component analysis, fourier transform and correspondence analysis.Validation of these techniques on IKONOS data (Panchromatic band at I m spatial resolution and Multispectral 4 bands at 4 in spatial resolution) reveal that HPF and HPM methods synthesises the images closest to those the corresponding multisensors would observe at the high resolution level.