Re-initialization Process Research Articles

Synthesis of Hybrid Silica Nanoparticles Densely Grafted with Thermo and pH Dual-Responsive Brushes via Surface-Initiated ATRP

This work introduces a synthesis of well-defined thermo and pH dual-responsive poly(N-isopropylacrylamide)-b-poly(4-vinylpyridine)-grafted silica nanoparticles (SNPs-g-PNIPAM-b-P4VP) via surface-initiated atom transfer radical polymerization (ATRP). ATRP initiators were attached onto the surfaces of silica nanoparticles followed by ATRP of N-isopropylacrylamide (NIPAM). During the surface-initiated ATRP, free sacrificial initiator and halogen exchange were utilized to render the polymerization in a controlled manner. Because of the retention of the polymer chain’s end-group functionality, chain extension with 4-vinylpyridine (4VP) from the obtained PNIPAM-grafted SNPs (SNPs-g-PNIPAM) was successfully conducted. Kinetics of the chain extension was studied in detail, showing the livingness of this reinitiation process. Subsequent quaternization of the outer P4VP block with methyl iodide led to the synthesized hybrid nanoparticles being well dispersed in aqueous solution. This well dispersibility affords the...

A fast and robust segmentation of magnetic resonance brain images using a combination of the pyramidal approach and level set method

We propose in this article an approach to optimize the processing time and to improve the quality of brain magnetic resonance images segmentation. Level set method LSM was adopted with a periodic reinitialization process to prevent the LS function from being too steep or too flat near the interface. Although it is used to maintain the stability of the interface evolution and gives interesting results, it requires a longer processing time.

Detonation re-initiation in a concentric tube arrangement for C $$_2$$ 2 H $$_2$$ 2 /O $$_2$$ 2 /Ar mixtures

Re-initiation of detonation in a concentric tube arrangement where a detonation exiting from a small diameter inner tube to a large diameter outer tube has been investigated. The outer tube diameter D is 50.8 mm and inner tube diameters d are 38, 25.4, and 12.7 mm giving diameter ratios \(D/d=1.34\), 2, and 4. Stoichiometric C\(_2\)H\(_2\)–O\(_2\) mixtures with argon dilution of 0, 25, 50, and 70% are used in the present study. Velocity measurements are made using photodiodes, and smoked foils downstream of the exit of the inner tube are also used to record the re-initiation process. Upon exit from the inner tube, the detonation suffers an abrupt decrease in velocity and at critical conditions, the velocity downstream of the exit is of the order of 50% of the Chapman–Jouguet velocity. It is found that re-initiation generally occurs within 10 tube diameters downstream of the exit. If re-initiation is not successful, the detonation continues to propagate at a low velocity for distances of the order of 30 tube diameters without any indication of flame acceleration of deflagration-to-detonation transition (DDT). Thus, the re-initiation process is clearly defined and distinct from the usual DDT in a smooth tube. The critical \(d/\lambda \) value ratio in the concentric tube is significantly lower than the usual unconfined case of \(d/\lambda =13\) where \(\lambda \) is the detonation cell size. Thus, it is a result of re-initiation at the Mach stem of the reflected shock from the wall of the outer concentric tube. If re-initiation is not successful upon the first reflection, then subsequent multiple reflections at the tube axis and wall of the outer tube can also result in re-initiation. However, this is only observed for undiluted mixtures. For high-argon-diluted mixtures, re-initiation only occurs at the Mach stem of the first reflection.

Multiple consecutive initiation of replication producing novel brush-like intermediates at the termini of linear viral dsDNA genomes with hairpin ends.

Linear dsDNA replicons with hairpin ends are found in the three domains of life, mainly associated with plasmids and viruses including the poxviruses, some phages and archaeal rudiviruses. However, their replication mechanism is not clearly understood. In this study, we find that the rudivirus SIRV2 undergoes multiple consecutive replication reinitiation events at the genomic termini. Using a strand-displacement replication strategy, the multiple reinitiation events from one parental template yield highly branched intermediates corresponding to about 30 genome units which generate exceptional ‘brush-like’ structures. Moreover, our data support the occurrence of an additional strand-coupled bidirectional replication from a circular dimeric intermediate. The multiple reinitiation process ensures rapid copying of the parental viral genome and will enable protein factors involved in viral genome replication to be specifically localised intracellularly, thereby helping the virus to avoid host defence mechanisms.

A two-stage image segmentation via global and local region active contours

Based on popular active contours, this paper proposes a novel two-stage image segmentation method, which incorporates the global and local image region fitting energies. In the first stage, according to the global region active contour, we preliminarily segment the image by globally using the Gaussian distribution, which can rapidly get a coarse segmentation result. Subsequently, by employing a window function, we further segment the image by using the local region active contour, where we use the final active contour of the first stage as the initialization. Compared with the first stage, the local object details are accurately segmented in the second stage, which can be considered as an accurate segmentation result. Due to the suitable initialization from the first stage, the second stage works well in accurately segmenting the image, especially in local details. To regularize the level set function, we introduce a Laplace operator, which efficiently eliminates the expensive re-initialization process of traditional level set methods. Compared with the state-of-the-art methods, experiment results demonstrate the effectiveness and performance of the proposed method with applications to synthetical and real-world images, which usually contain noise, blurry boundaries, and intensity inhomogeneities.

The Basic Results on Reinitiation Processes in Diffracting Multifront Detonations. Part I.

The basic results of experimental investigations on reinitiation processes in diffracting multifront detonation wave (DW) are discussed in connection with problem of practical application of new ecological technology for worn-out tire destruction, where the cooled worn-out tire destroys with the help of gaseous detonation. The experimental results for various fuel-oxygen and fuel-air mixtures are presented at wide range of mixture compositions, initial pressure and temperature, geometrical sizes of experimental equipment, symmetry types, dilution of inert gases, etc. Classical and nontraditional schema of DW-diffraction are investigated, such as multipointed initiation, DW-excitation by circular charge, initiation space-oriented longitudinal charges, initiation by circular charge, diffraction on concave boundary, diffraction on contact surface of different mixtures, flame diffraction, etc. The main characteristic parameters are identified for each diffraction schema. The physical processes taking place directly in the DW-front plays the governing role in reinitiation. The most important among these processes are collisions of transverse waves, which stick out as microscopic initiators. The optimization problem of DW-initiation from spatial and temporary distribution of energy is discussed carefully. This data can be used at hazard estimation also.

Stabilized finite element methods for solving the level set equation without reinitialization

New stabilized finite element methods are proposed for solving moving interface flow problems using the level set approach. The formulations enhance the interface resolution without the need to resort to the reinitialization process. These are established by adding a perturbation term that depends on the local residual of the Eikonal equation to the SUPG variational formulation of the level set equation. These methods are numerically evaluated for well-known benchmark flow problems and compared with a modified variant of the penalty method of Li et al. (2005). The proposed stabilized finite element methods employing second-order time and space approximations are promising simple and accurate techniques for solving complex moving interface flows.

Brain Tumour Segmentation using Level Set Method and Affected Area Calculation

Medical image processing is the most important and challenging field now a days. MRI image processing is one of the parts of this field. Brain tumour segmentation in magnetic resonance imaging (MRI) has become an emergent research area in the field of medical imaging system. In this paper we proposed a variational level set method and some morphological operation to segment the brain tumour from MRI image by using MATLAB. Actually we describe variational formulation on geometric active contours that forces the level set function at zero level to be close to signed distance function and without re-initialization process. The variational formulation uses energy function and partial diferential equation to evolve the level set function. Tumourshape area is connected component in binary image and calculated this connected area using some properties of morphological operation .

UV-Induced Micropatterning of Complex Functional Surfaces by Photopolymerization Controlled by Alkoxyamines.

We report on the use of an alkoxyamine (AA) for fabrication of functional micropatterns with complex structures by UV mask lithography. The living character of the polymer surface and the vertical spatial control of the repolymerization reaction from few tens of nanometers to few micrometers were demonstrated. The impact of the main parameters governing the controlled polymerization and the reinitiation process activated by light or heat was investigated. Micropatterning is shown to be a powerful method to investigate the physicochemical molecular phenomena. It is possible to control the polymer microstructure thickness from few tens of nanometers to few micrometers. In the last section, some applications are provided showing the potential of the AA for generating covalently bonded hydrophilic/hydrophobic micropatterns or luminescent surfaces. This demonstrates the high versatility and interest of this route.

A hybrid segmentation method based on Gaussian kernel fuzzy clustering and region based active contour model for ultrasound medical images

Segmentation is a very crucial task for the ultrasound medical images due to the presence of various imaging artifacts and noise. This paper presents a hybrid segmentation method for the ultrasound medical images that utilize both the features of the Gaussian kernel induced fuzzy C-means (GKFCM) clustering and active contour model driven by region scalable fitting (RSF) energy function. In this method, the result obtained from the GKFCM method is utilized to initialize the contour that spreads to identify the estimated regions. It also helps to estimate the several controlling parameters used in the curve evolution process. The RSF formulation that is responsible for attracting the contour toward the object boundaries removes the requirement of the re-initialization process. The performance of the proposed method is evaluated by conducting several experiments on both the synthetic and real ultrasound images. Experimental results demonstrate that the proposed method produces better results by successfully detecting the object boundaries and also ensures an improvement in segmentation accuracy compared to others.

An experimental study on the onset processes of detonation waves downstream of a perforated plate

Detonation waves propagating steadily in a rectangular tube were destroyed upon transmission through a perforated plate placed perpendicular to the direction of propagation. Subsequent re-initiation of the detonation waves downstream are investigated. Two explosive mixtures of C2H2+2.5O2+70%Ar (stable detonation with regular cellular pattern) and H2+N2O (unstable detonation with irregular cellular structure) are studied to illustrate the difference in the re-initiation processes. Simultaneous schlieren photography and smoked foil record permit the different features of the onset of detonation in the stable and unstable mixtures to be observed and analyzed in detail. It is found that two types of re-initiation processes are present. In the stable mixture, the onset of detonation is via multiple localized explosions distributed in the reaction zone, which gradually couple the reaction zones with the precursor shock to develop the original cellular structures. Whereas in the unstable mixtures, local perturbations usually at the boundary layer region near the wall lead to one or two strong local explosions forming overdriven detonation wave that decay to C–J detonation subsequently.

Self-Updating One-Time Password Mutual Authentication Protocol for Ad Hoc Network

As a new type of wireless network, Ad hoc network does not depend on any pre-founded infrastructure, and it has no centralized control unit. The computation and transmission capability of each node are limited. In this paper, a self-updating one-time password mutual authentication protocol for Ad hoc network is proposed. The most significant feature is that a hash chain can update by itself smoothly and securely through capturing the secure bit of the tip. The updating process does not need any additional protocol or re-initialization process and can be continued indefinitely to give rise to an infinite length hash chain, that is, the times of authentication is unlimited without reconstructing a new hash chain. Besides, two random variable are added into the messages interacted during the mutual authentication, enabling the protocol to resist man-in-the-middle attack. Also, the user’s identity information is introduced into the seed of hash chain, so the scheme achieves anonymity and traceability at the same time.

Cellular mRNAs access second ORFs using a novel amino acid sequence-dependent coupled translation termination–reinitiation mechanism

Polycistronic transcripts are considered rare in the human genome. Initiation of translation of internal ORFs of eukaryotic genes has been shown to use either leaky scanning or highly structured IRES regions to access initiation codons. Studies on mammalian viruses identified a mechanism of coupled translation termination-reinitiation that allows translation of an additional ORF. Here, the ribosome terminating translation of ORF-1 translocates upstream to reinitiate translation of ORF-2. We have devised an algorithm to identify mRNAs in the human transcriptome in which the major ORF-1 overlaps a second ORF capable of encoding a product of at least 50 aa in length. This identified 4368 transcripts representing 2214 genes. We investigated 24 transcripts, 22 of which were shown to express a protein from ORF-2 highlighting that 3' UTRs contain protein-coding potential more frequently than previously suspected. Five transcripts accessed ORF-2 using a process of coupled translation termination-reinitiation. Analysis of one transcript, encoding the CASQ2 protein, showed that the mechanism by which the coupling process of the cellular mRNAs was achieved was novel. This process was not directed by the mRNA sequence but required an aspartate-rich repeat region at the carboxyl terminus of the terminating ORF-1 protein. Introduction of wobble mutations for the aspartate codon had no effect, whereas replacing aspartate for glutamate repeats eliminated translational coupling. This is the first description of a coordinated expression of two proteins from cellular mRNAs using a coupled translation termination-reinitiation process and is the first example of such a process being determined at the amino acid level.

A novel design method for optimal IIR system identification using opposition based harmony search algorithm

In this paper a population based evolutionary optimization methodology called Opposition based Harmony Search Algorithm (OHS) is applied for the optimization of system coefficients of adaptive infinite impulse response (IIR) system identification problem. The original Harmony Search (HS) algorithm is chosen as the parent one and opposition based approach is applied to it with an intention to exhibit accelerated near global convergence profile. During the initialization, for choosing the randomly generated population/solution opposite solutions are also considered and the fitter one is selected as apriori guess for having faster convergence profile. Each solution in Harmony Memory (HM) is generated on the basis of memory consideration rule, a pitch adjustment rule and a re-initialization process which gives the optimum result corresponding to the least error fitness in multidimensional search space. Incorporation of different control parameters in basic HS algorithm results in balancing of exploration and exploitation of search space. The proposed OHS based system identification approach has alleviated from inherent drawbacks of premature convergence and stagnation, unlike Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Differential Evolution (DE). The simulation results obtained for some well known benchmark examples justify the efficacy of the proposed OHS based system identification approach over GA, PSO and DE in terms of convergence speed, identifying the system plant coefficients and mean square error (MSE) fitness values produced for both same order and reduced order models of adaptive IIR filters.

A VARIATIONAL MULTIPHASE LEVEL SET ALGORITHM FOR IMAGE SEGMENTATION BASED ON ACTIVE CONTOUR MODEL

A novel variational multiphase level set mathematical model is derived for image segmentation with two contributions. By virtue of eliminating the time-consuming re-initialization procedure and neglecting the property of the level set function during the evolution process, we in this paper present two strategies that may be taken as our contributions to solving these problems. Two scenarios are considered, namely, first, the distance regularization term which is defined by double-well potential function with two minimum points is introduced to our mathematical model for avoiding the re-initialization process. Second, by combining a Tikhonov-like regularization term which can guarantee the smoothness for the evolution curve over the previous method. Numerical simulation studies are presented to verify our new model via evaluating and comparing with existing algorithms.

Conservative Level Set Method Without Re-Initialization Process: Application to Multiphase Flows

To describe the interface evolution in multiphase flows, the numerical simulation requires special approaches. The Lagrangian-based methods (front tracking) are not adequate when the interface curvature is sharp and time dependent. The volume of fluid method is numerically prohibitive. The level set method (LSM) presents many advantages, when a very high accuracy in the interface curvature is needed. In this paper, the LSM is treated in more detail. A finite element (FEM ) formulation has been used to model a two-phase flows involving interface propagation. A variational formulation is introduced in order to suppress the costly re-initialization procedure, and a new mass conservation correction method based on penalty factor is proposed.The performance of the method is then presented using several reported cases. The results showed that the accuracy of the proposed approach is drastically improved in comparison with other reported methods. The method is applied to the dam-break and to the rising bubble in water column problems. Good agreements with the reported solutions are presented, which corroborates the accuracy of the method.

Intracranial hemorrhage detection using spatial fuzzy c-mean and region-based active contour on brain CT imaging

Intracranial hemorrhage (ICH) detection is the primary task for the patients suffering from neurological disturbances and head injury. This paper presents a segmentation technique that combines the features of fuzzy c-mean (FCM) clustering and region-based active contour method. In the suggested method, the fuzzy membership degree from FCM clustering is first used to initialize the active contour, which propagates for the detection of the desired object. In addition to active contour initialization, the fuzzy clustering is also used to estimate the contour propagation controlling parameters. The level set function as used by active contour in the proposed method does not need re-initialization process; thus, it fastens the convergent speed of the contour propagation. The efficacy of the suggested method is demonstrated on a dataset of 20 brain computed tomography (CT) images suffered with ICH. Experimental results show that the proposed method has advantages in accuracy in comparison with standard region growing method and FCM for the detection of hemorrhage from brain CT images.

A Micro Artificial Immune System

In this paper, we present a new algorithm, namely, a micro artificial immune system (Micro-AIS) based on the Clonal Selection Theory for solving numerical optimization problems. For our study, we consider the algorithm CLONALG, a widely used artificial immune system. During the process of cloning, CLONALG greatly increases the size of its population. We propose a version with reduced population. Our hypothesis is that reducing the number of individuals in a population will decrease the number of evaluations of the objective function, increasing the speed of convergence and reducing the use of data memory. Our proposal uses a population of 5 individuals (antibodies), from which only 15 clones are obtained. In the maturation stage of the clones, two simple and fast mutation operators are used in a nominal convergence that works together with a reinitialization process to preserve the diversity. To validate our algorithm, we use a set of test functions taken from the specialized literature to compare our approach with the standard version of CLONALG. The same method can be applied in many other problems, for example, in text processing.

New Variational Formulations for Level Set Evolution Without Reinitialization with Applications to Image Segmentation

Interface evolution problems are often solved elegantly by the level set method, which generally requires the time-consuming reinitialization process. In order to avoid reinitialization, we reformulate the variational model as a constrained optimization problem. Then we present an augmented Lagrangian method and a projection Lagrangian method to solve the constrained model and propose two gradient-type algorithms. For the augmented Lagrangian method, we employ the Uzawa scheme to update the Lagrange multiplier. For the projection Lagrangian method, we use the variable splitting technique and get an explicit expression for the Lagrange multiplier. We apply the two approaches to the Chan-Vese model and obtain two efficient alternating iterative algorithms based on the semi-implicit additive operator splitting scheme. Numerical results on various synthetic and real images are provided to compare our methods with two others, which demonstrate effectiveness and efficiency of our algorithms.

Joint Feature Correspondences and Appearance Similarity for Robust Visual Object Tracking

A novel visual object tracking scheme is proposed by using joint point feature correspondences and object appearance similarity. For point feature-based tracking, we propose a candidate tracker that simultaneously exploits two separate sets of point feature correspondences in the foreground and in the surrounding background, where background features are exploited for the indication of occlusions. Feature points in these two sets are then dynamically maintained. For object appearance-based tracking, we propose a candidate tracker based on an enhanced anisotropic mean shift with a fully tunable (five degrees of freedom) bounding box that is partially guided by the above feature point tracker. Both candidate trackers contain a reinitialization process to reset the tracker in order to prevent accumulated tracking error propagation in frames. In addition, a novel online learning method is introduced to the enhanced mean shift-based candidate tracker. The reference object distribution is updated in each time interval if there is an indication of stable and reliable tracking without background interferences. By dynamically updating the reference object model, tracking is further improved by using a more accurate object appearance similarity measure. An optimal selection criterion is applied to the final tracker based on the results of these candidate trackers. Experiments have been conducted on several videos containing a range of complex scenarios. To evaluate the performance, the proposed scheme is further evaluated using three objective criteria, and compared with two existing trackers. All our results have shown that the proposed scheme is very robust and has yielded a marked improvement in terms of tracking drift, tightness, and accuracy of tracked bounding boxes, especially for complex video scenarios containing long-term partial occlusions or intersections, deformation, or background clutter with similar color distributions to the foreground object.