Unstable Clusters Research Articles

A stochastic model based on fiber breakage and matrix creep for the stress-rupture failure of unidirectional continuous fiber composites

Stress rupture is a time-dependent failure mode occurring in unidirectional fiber composites under sustained tensile loads, resulting in highly variable lifetimes. Stress-rupture is of particular concern in composite overwrapped pressure vessels (COPVs) since it is unpredictable, and has catastrophic consequences. At the micromechanical level, stress rupture begins with the breakdown of individual fibers at random flaws, followed by local load-transfer to intact neighbors through shear stress in the matrix. Over time, the matrix creeps in shear causing lengthening overload zones around fiber breaks, resulting in even more fiber breaks, and eventually, formation of a catastrophically unstable break cluster. Current reliability models are direct extensions of classic stochastic breakdown models for a single fiber, and do not reflect such micromechanical activity. These models are adequate for modeling composite stress rupture under a constant load, however, they may be unrealistic under more complex loading profiles, such as a constant load that follows a brief ‘proof test’ at a load level up to 1.5 times this constant load. For carbon fiber/epoxy COPVs, current models predict a reliability, conditioned on survival of a proof test, that is always higher than the reliability without such a proof test. Concern exists that this is incorrect, and that a proof test may result in reduced reliability over time. While the failure probability during a proof test may be very low, overwrap damage occurs nonetheless in the form of a large number of fibers breaks that would not occur otherwise based on fiber Weibull strength statistics. This phenomenon of increased fiber breakage during a proof test is captured in the model we develop and that specifically builds on the micromechanical failure process described above. For typical proof-test load ratios, the model predicts conditional reliabilities for lifetime that are typically much lower than those calculated in the absence of a proof test.

Enhanced weight-based clustering algorithm to provide reliable delivery for VANET safety applications.

A vehicular ad hoc network (VANET) is an emerging and promising wireless technology aimed to improve traffic safety and provide comfort to road users. However, the high mobility of vehicles and frequent topology changes pose a considerable challenge to the reliable delivery of safety applications. Clustering is one of the control techniques used in VANET to make the frequent topology changes less dynamic. Nevertheless, research has shown that most of the existing clustering algorithms focus on cluster head (CH) election with very few addressing other critical issues such as cluster formation and maintenance. This has led to unstable clusters which could affect the timely delivery of safety applications. In this study, enhanced weight-based clustering algorithm (EWCA) was developed to address these challenges. We considered any vehicle moving on the same road segment with the same road ID and within the transmission range of its neighbour to be suitable for the cluster formation process. This was attributed to the fact that all safety messages are expected to be shared among the vehicles within the vicinity irrespective of their relative speedto avoid any hazardous situation. To elect a CH, we identified some metrics on the basis of the vehicle mobility information. Each vehicle was associated with a predefined weight value based on its relevance. A vehicle with the highest weight value was elected as the primary cluster head (PCH). We also introduced a secondary cluster head (SeCH) as a backup to the PCH to improve the cluster stability. SeCH took over the leadership whenever the PCH was not suitable for continuing with the leadership. The simulation results of the proposed approach showed a better performance with an increase of approximately40%– 45% in the cluster stability when compared with the existing approaches. Similarly, cluster formation messages were significantly minimized, hence reducing the communication overhead to the system and improving the reliable delivery of the safety applications.

Organ system network analysis and biological stability in critically ill patients

BackgroundContinuous coordination among organ systems is necessary to maintain biological stability in humans. Organ system network analysis in addition to organ-oriented medicine is expected to improve patient outcomes. However, organ system networks remain beyond clinical application with little evidence for their importance on homeostatic mechanisms. This proof-of-concept study examined the impact of organ system networks on systemic stability in severely ill patients.MethodsPatients admitted to the intensive care unit of the University of Tokyo Hospital with one representative variable reflecting the condition of each of the respiratory, cardiovascular, renal, hepatic, coagulation, and inflammatory systems were enrolled. Relationships among the condition of individual organ systems, inter-organ connections, and systemic stability were evaluated between non-survivors and survivors whose organ system conditions were matched to those of the non-survivors (matched survivors) as well as between non-survivors and all survivors. We clustered these six organ systems using principal component analysis and compared the dispersion of the principal component scores of each cluster using the Ansari-Bradley test to evaluate systemic stability involving multiple organ systems. Inter-organ connections were evaluated using Spearman’s rank test.ResultsAmong a total of 570 enrolled patients, 91 patients died. The principal component analysis yielded the respiratory-renal-inflammatory and cardiovascular-hepatic-coagulation system clusters. In the respiratory-renal-inflammatory cluster, organ systems were connected in both the survivors and the non-survivors. The principal component scores of the respiratory-renal-inflammatory cluster were dispersed similarly (stable cluster) in the non-survivors, the matched survivors, and the total survivors irrespective of the severity of individual organ system dysfunction. Conversely, in the cardiovascular-hepatic-coagulation cluster, organ systems were connected only in the survivors, and the principal component scores of the cluster were significantly dispersed (unstable cluster) in the non-survivors compared to the total survivors (P = 0.002) and the matched survivors (P = 0.004).ConclusionsThis study demonstrated that systemic instability was closely associated with network disruption among organ systems irrespective of their dysfunction severity. Organ system network analysis is necessary to improve outcomes in severely ill patients.

Matrix Coordination Induced Emission in a Three-Dimensional Silver Cluster-Assembled Material.

Developing highly luminescent and extensively stable silver cluster-assembled materials (SCAMs) from the inferior luminogens and unstable silver cluster is an important and challenging issue. Herein, a new luminescent three-dimensional SCAM (Ag12 CPPP, [Ag12 (StBu)6 (CF3 COO)6 (CPPP)2 (DMAc)12 ]n ; CPPP=2,5-bis(4-cyanophenyl)-1,4-bis(4-(pyridine-4-yl)-phenyl)-1,4-dihydropyrrolo[3,2-b]pyrrole, DMAc=dimethylacetamide) was designed and synthesized with a quadridentate rigid emission ligand (CPPP) and a silver-chalcogenolate cluster (SCC) containing 12 AgI atoms. The luminescence study indicates that CPPP is an aggregation-caused quenching (ACQ) molecule with twisted intramolecular charge transfer (TICT) character. Benefiting from the strong immobilization effect in the robust framework, the quantum yield of CPPP is greatly enhanced in Ag12 CPPP compared with that of CPPP in solution or in the solid state. As a result, Ag12 CPPP exhibits typical matrix coordination induced emission (MCIE) effect. Such efficient rigidifying methodology provides a promising approach for enhancing luminescence of ACQ molecules in an aggregated state and strengthening the silver cluster in an unstable state.

An efficient seed points selection approach in dominant color descriptors (DCD)

The content-based image retrieval (CBIR) system accepts the input in the form of images and retrieves the relevant images from the database. The CBIR system automatically extracts the prominent key information from the image involved in the retrieval task. The color is one of the key information of the image and it is represented by dominant color descriptors (DCD). Here, similar colors get clustered and the mean value of each cluster represents the dominant color. The random number of unstable cluster formation in DCD alleviates the CBIR system performance. The proposed work has minimized the drawback of DCD by introducing seed points selection based on the mean, maximum and minimum value of the color pixels present in the image. Moreover, this work suggests the optimal cluster number by validating the different combinations of the proposed stable dominant color clusters. The retrieval precision of the proposed CBIR has improved since this work gives equal weight for both the dominant color and its occurrence probability in distance metric calculation. Finally, four standard datasets namely Wang’s, Corel-10k, OT-scene, and Oxford flower are considered for evaluation, and it gives more number of relevant images compared to the state-of-the-art dominant color feature extraction techniques used on these datasets.

Characterization of GnRH Pulse Generator Activity in Male Mice Using GCaMP Fiber Photometry.

Kisspeptin neurons located in the hypothalamic arcuate nucleus are thought to represent the GnRH pulse generator responsible for driving pulsatile LH secretion. The recent development of GCaMP6 fiber photometry technology has made it possible to perform long-term recordings of the population activity of the arcuate nucleus kisspeptin (ARNKISS) neurons in conscious-behaving mice. Using this approach, we show that ARNKISS neurons in intact male mice exhibit episodes of synchronized activity that last ∼2 minutes and have a mean inter-episode interval of 166 minutes, with a very wide range (43 to 347 minutes). Gonadectomy resulted in dramatic changes in the dynamics of ARNKISS neuron behavior with temporally distinct alterations in synchronization episode (SE) amplitude (sevenfold increase), inter-SE frequency (range, 2 to 58 minutes), and duration (up to 28 minutes), including the frequent appearance of seemingly unstable clusters of doublet and triplet SEs. The combination of photometry with repeated blood sampling revealed a perfect correlation between ARNKISS neuron population SEs and LH pulses in intact and short-term gonadectomized (GDX) mice. No differences were detected in SE frequency across 24 hours in either intact or GDX mice. These observations further support a role for ARNKISS neurons as the GnRH pulse generator and show that it operates in a stochastic manner without diurnal variation in both intact and GDX male mice. The removal of gonadal steroids has multiple time-dependent effects upon ARNKISS neuron synchronizations, indicating their critical role in shaping pulse generator behavior.

Ligand-Dependent Colloidal Stability Controls the Growth of Aluminum Nanocrystals.

The precise size- and shape-controlled synthesis of monodisperse Al nanocrystals remains an open challenge, limiting their utility for numerous applications that would take advantage of their size and shape-dependent optical properties. Here we pursue a molecular-level understanding of the formation of Al nanocrystals by titanium(IV) isopropoxide-catalyzed decomposition of AlH3 in Lewis base solvents. As determined by electron paramagnetic resonance spectroscopy of intermediates, the reaction begins with the formation of Ti3+-AlH3 complexes. Proton nuclear magnetic resonance spectroscopy indicates isopropoxy ligands are removed from Ti by Al, producing aluminum(III) isopropoxide and low-valent Ti3+ catalysts. These Ti3+ species catalyze elimination of H2 from AlH3 inducing the polymerization of AlH3 into colloidally unstable low-valent aluminum hydride clusters. These clusters coalesce and grow while expelling H2 to form colloidally stable Al nanocrystals. The colloidal stability of the Al nanocrystals and their size is determined by the molecular structure and density of coordinating atoms in the reaction, which is controlled by choice of solvent composition.

Red blood cell concentrate transfusion strategies utilised at a tertiary-level paediatric intensive care unit: A descriptive study on impact and cost

Background. Optimal haemoglobin threshold for red blood cell (RBC) transfusions in critically ill anaemic children in a paediatric intensive care unit (PICU) is uncertain. Objective. To describe outcomes and costs associated with different RBC transfusion strategies in anaemic patients admitted to a tertiary PICU in Durban, South Africa. Methods. Transfusion data gathered over a 1-year period were analysed retrospectively. RBC transfusion strategies were classified as restrictive, ‘modified liberal’ or mixed. The ‘modified liberal’ group was subdivided into haemodynamically stable or unstable clusters. Transfusion-related effects, comorbidities and mortality were described. Costs associated with RBC transfusions in the various strategy groups were analysed. Results. Over the 118 transfusion records analysed, a restrictive strategy was adopted in 27 cases (22.9%) and a modified liberal strategy was used in 68 cases (57.6%). A mixed strategy was followed in 23 (19.5%) cases. Although mortality was higher in the modified liberal group than in the restrictive group (27.9% v. 11.1%), the difference was not statistically different ( p =0.09). There were no differences in the duration of intermittent positive pressure ventilation, length of PICU stay or post-transfusion effects between the restrictive and modified liberal transfusion strategies. A saving of R155 280.15 could have been realised if a restrictive transfusion strategy had been used for haemodynamically stable patients assigned to the modified liberal group. A further R28 988.67 was spent on avoidable after-hours transfusions levies. Conclusion. Adopting a restrictive daytime strategy for RBC transfusions at a PICU could introduce considerable cost savings without affecting outcomes.

Properties of the single Jovian planet population and the pursuit of Solar system analogues

While the number of exoplanets discovered continues to increase at a rapid rate, we are still to discover any system that truly resembles the Solar system. Existing and near future surveys will likely continue this trend of rapid discovery. To see if these systems are Solar system analogues, we will need to efficiently allocate resources to carry out intensive follow-up observations. We seek to uncover the properties and trends across systems that indicate how much of the habitable zone is stable in each system to provide focus for planet hunters. We study the dynamics of all known single Jovian planetary systems, to assess the dynamical stability of the habitable zone around their host stars. We perform a suite of simulations of all systems where the Jovian planet will interact gravitationally with the habitable zone, and broadly classify these systems. Besides the system's mass ratio (Mpl/Mstar), and the Jovian planet's semi-major axis (apl) and eccentricity (epl), we find that there are no underlying system properties which are observable that indicate the potential for planets to survive within the system's habitable zone. We use Mpl/Mstar, apl and epl to generate a parameter space over which the unstable systems cluster, thus allowing us to predict which systems to exclude from future observational or numerical searches for habitable exoplanets. We also provide a candidate list of 20 systems that have completely stable habitable zones and Jovian planets orbiting beyond the habitable zone as potential first order Solar system analogues.

Mutual Constraint Based GA Suggested Routing Algorithm for Improving QoS in Clustered MANETS

Mobile Ad-Hoc Network is a compilation of self-organized wireless devices that momentarily interconnects to support communication. In conjunction with the network characteristics like mobile nature and infrastructure less, some external factors also influence network Quality of Service (QoS). To ensure QoS in the network, QoS based optimizations and routing algorithms have been anticipated that concentrate limited metrics or result in sub-optimal solutions. To bridge the gap between QoS sustainability and to resolve sub optimal solution, Genetic Algorithm (GA) based Quality of Service Routing (QR) is proposed. This routing incorporates clustering algorithm based on preference that is designed to co-exist with GA based QR under undisputed constraints. This generates prolonged communication with higher convergence, preventing earlier optimal solution drain caused due to unstable clusters and frequent neighbor replacements. The proposed GA–QR is evaluated using the network metrics: throughput, end-to-end delay, overhead, etc.

Diffusion, Nucleation, and Self-Optimization in the Forming Process of Graphene in Annealed Nickel–Carbon Alloy

Reactive molecular dynamics simulation is used to explore the forming mechanism of graphene in an annealed nickel–carbon alloy. Results show that after internal carbon atoms diffuse to the surface of the alloy spontaneously with a large diffusion coefficient, graphene nuclei are formed due to the catalysis of nickel atoms. The nuclei can grow into large graphene and then the large graphene optimizes itself when annealing time is sufficient, accompanied by some nickel–carbon compounds and unstable nickel clusters in this alloy. The substrate, carbon concentration, annealing temperature, and alloy thickness could affect the morphology of the obtained graphene. Our simulation provides insight into the structural evolution of annealed nickel–carbon alloys at the atomistic level and will be valuable to the preparation of graphene.

Stable Vortex Clusters in Two-Dimensional Bose-Einstein Condensates with Spatially Modulated Defocusing Nonlinearity

We investigate the vortex dynamic behavior of Bose-Einstein condensate in a spatially two-dimensional harmonic potential with spatially modulated defocusing nonlinearity. Kinds of exact vortex solutions of the Gross-Pitaevskii equation are obtained by designing various laser potentials which can be experimentally realized. In particular, we demonstrate that the spatially modulated defocusing nonlinearity supports stable vortex clusters. For the stationary vortex solutions, the vortex clusters are dynamically stable, and the circulation direction of each vortex and vortex core positions remain unchanged. However, for the non-stationary vortex solutions, stable and unstable vortex clusters exist. For the stable vortex clusters, the vortex core positions are constant during dynamical evolution, while the phase increase directions vary periodically. Additionally, corresponding to the unstable vortex clusters, vortices disappear and appear periodically in the condensate.

Preferred alignments of angular momentum vectors of galaxies in six dynamically unstable Abell clusters

A spatial orientation of angular momentum vectors of galaxies in six dynamically unstable Abell clusters (S1171, S0001, A1035, A1373, A1474 and A4053) is studied. For this, two-dimensional observed parameters (e.g., positions, diameters and position angles) are converted into three-dimensional (3D) rotation axes of the galaxy using the ‘position angle - inclination’ method. The expected isotropic distribution curves for angular momentum vectors are obtained by performing random simulations. The observed and expected distributions are compared using several statistical tests. No preferred alignments of angular momentum vectors of galaxies are noticed in all six dynamically unstable clusters, supporting the hierarchy model of galaxy formation. These clusters have a larger value of velocity dispersion. However, local effects are noticed in the clusters that have substructures in the 1D-3D number density maps.

Forests of unstable hierarchical clusters for pattern classification

Classification of patterns is a key ability shared by intelligent systems. One of the crucial components of a pattern classification pipeline is the classifier. There have been many classifiers that have been proposed in literature, and it has been shown recently that ensembles of decisions trees tend to perform and generalize well to unseen test data. In this paper, we propose a novel ensemble classifier that consists of a diverse group of hierarchical clusterings on data. The proposed algorithm is fast to train, fully automatic and outperforms existing decision tree ensemble techniques and other state-of-the-art classifiers. We empirically show the effectiveness of the algorithm by evaluating on four publicly available datasets.

Phenotyping of difficult asthma using longitudinal physiological and biomarker measurements reveals significant differences in stability between clusters.

BackgroundAlthough the heterogeneous nature of asthma has prompted asthma phenotyping with physiological or biomarker data, these studies have been mostly cross-sectional. Longitudinal studies that assess the stability of phenotypes based on a combination of physiological, clinical and biomarker data are currently lacking.Our objective was to assess the longitudinal stability of clusters derived from repeated measures of airway and physiological data over a 1-year period in moderate and severe asthmatics.MethodsA total of 125 subjects, 48 with moderate asthma (MA) and 77 with severe asthma (SA) were evaluated every 3 months and monthly, respectively, over a 1-year period. At each 3-month time point, subjects were grouped into 4 asthma clusters (A, B, C, D) based on a combination of clinical (duration of asthma), physiological (FEV1 and BMI) and biomarker (sputum eosinophil count) variables, using k-means clustering.ResultsMajority of subjects in clusters A and C had severe asthma (93 % of subjects in cluster A and 79.5 % of subjects in cluster C at baseline). Overall, a total of 59 subjects (47 %) had stable cluster membership, remaining in clusters with the same subjects at each evaluation time. Cluster A was the least stable (21 % stability) and cluster B was the most stable cluster (71 % stability). Cluster stability was not influenced by changes in the dosage of inhaled corticosteroids.ConclusionAsthma phenotyping based on clinical, physiologic and biomarker data identified clusters with significant differences in longitudinal stability over a 1-year period. This finding indicates that the majority of patients within stable clusters can be phenotyped with reasonable accuracy after a single measurement of lung function and sputum eosinophilia, while patients in unstable clusters will require more frequent evaluation of these variables to be properly characterized.

Exploring the complete mutational space of the LDL receptor LA5 domain using molecular dynamics: linking SNPs with disease phenotypes in familial hypercholesterolemia.

Familial hypercholesterolemia (FH), a genetic disorder with a prevalence of 0.2%, represents a high-risk factor to develop cardiovascular and cerebrovascular diseases. The majority and most severe FH cases are associated to mutations in the receptor for low-density lipoproteins receptor (LDL-r), but the molecular basis explaining the connection between mutation and phenotype is often unknown, which hinders early diagnosis and treatment of the disease. We have used atomistic simulations to explore the complete SNP mutational space (227 mutants) of the LA5 repeat, the key domain for interacting with LDL that is coded in the exon concentrating the highest number of mutations. Four clusters of mutants of different stability have been identified. The majority of the 50 FH known mutations (33) appear distributed in the unstable clusters, i.e. loss of conformational stability explains two-third of FH phenotypes. However, one-third of FH phenotypes (17 mutations) do not destabilize the LR5 repeat. Combining our simulations with available structural data from different laboratories, we have defined a consensus-binding site for the interaction of the LA5 repeat with LDL-r partner proteins and have found that most (16) of the 17 stable FH mutations occur at binding site residues. Thus, LA5-associated FH arises from mutations that cause either the loss of stability or a decrease in domain's-binding affinity. Based on this finding, we propose the likely phenotype of each possible SNP in the LA5 repeat and outline a procedure to make a full computational diagnosis for FH.

Isomer differentiation through supramolecular self-assembly in microdroplets of milliseconds life-time.

Supramolecular recognition of thymine (or its analogs) with various central cations can form magic number clusters. Dual nano-ESI via theta tip emitters was used to on-line synthesize clusters. Even thermodynamically unstable clusters can be detected by MS thanks to the very short life-time (∼ms) of the generated microdroplets. By recording characteristic cluster distributions, isomers can be clearly differentiated in a novel "bottom-up" way. Theoretical calculations were performed to explain the MS results.

The morphological and structural features of ferrite compositions (1−x) MeFe2O4xP2O5 prepared by plasma spraying

Structural features of spinel ferrites formed by rapid quenched from the liquid state, has been studied. It was found that higher quenching rates cause sequential disorder of the spinel structure. Process starts with statistically uniform redistribution of cations at lattice points, then collapse of the anionic frame leads to the topological disorder. This process results in formation of the thermodynamically unstable cluster state and heating of these hardened ferrites leads to a stepwise release of energy. Therefore the described process improves activity of ferrite powders in solid-phase and catalytic reactions.

Mechanical properties and tribological behavior of fullerene-like hydrogenated carbon films prepared by changing the flow rates of argon gas

Fullerene-like hydrogenated carbon (FL-C:H) films as carbon materials were prepared by direct current plasma enhanced chemical vapor deposition (dc-PECVD) technique. The content of FL nanostructure was confirmed by high-resolution transmission electron microscopy (HRTEM), visible Raman spectroscopy, and X-ray photoelectron spectroscopy (XPS). The effect of fullerene-like nanostructure on the friction behavior of the films was studied using a reciprocating ball-on-flat tribometer in humid environment. It is concluded that the curved FL nanostructure provide the film excellent mechanical properties and friction performance. Interestingly, combining with the results of Raman analyses of the wear debris, we find that new FL nanostructure form during the friction process. These new FL nanostructure may originate from the rapid annealing and stress relaxation of unstable carbon clusters.

Periodic and quasiperiodic motions of many particles falling in a viscous fluid.

The dynamics of regular clusters of many nontouching particles falling under gravity in a viscous fluid at low Reynolds number are analyzed within the point-particle model. The evolution of two families of particle configurations is determined: two or four regular horizontal polygons (called "rings") centered above or below each other. Two rings fall together and periodically oscillate. Four rings usually separate from each other with chaotic scattering. For hundreds of thousands of initial configurations, a map of the cluster lifetime is evaluated in which the long-lasting clusters are centered around periodic solutions for the relative motions, and they are surrounded by regions of chaotic scattering in a similar way to what was observed by Janosi et al. [Phys. Rev. E. 56, 2858 (1997)] for three particles only. These findings suggest that we should consider the existence of periodic orbits as a possible physical mechanism of the existence of unstable clusters of particles falling under gravity in a viscous fluid.