Linear, Deterministic, and Order-Invariant Initialization Methods for the K-Means Clustering Algorithm

Over the past five decades, k-means has become the clustering algorithm of choice in many application domains primarily due to its simplicity, time/space efficiency, and invariance to the ordering of the data points. Unfortunately, the algorithm's sensitivity to the initial selection of the cluster centers remains to be its most serious drawback. Numerous initialization methods have been proposed to address this drawback. Many of these methods, however, have time complexity superlinear in the number of data points, which makes them impractical for large data sets. On the other hand, linear methods are often random and/or sensitive to the ordering of the data points. These methods are generally unreliable in that the quality of their results is unpredictable. Therefore, it is common practice to perform multiple runs of such methods and take the output of the run that produces the best results. Such a practice, however, greatly increases the computational requirements of the otherwise highly efficient k-means algorithm. In this chapter, we investigate the empirical performance of six linear, deterministic (non-random), and order-invariant k-means initialization methods on a large and diverse collection of data sets from the UCI Machine Learning Repository. The results demonstrate that two relatively unknown hierarchical initialization methods due to Su and Dy outperform the remaining four methods with respect to two objective effectiveness criteria. In addition, a recent method due to Erisoglu et al. performs surprisingly poorly.Comment: 21 pages, 2 figures, 5 tables, Partitional Clustering Algorithms (Springer, 2014). arXiv admin note: substantial text overlap with arXiv:1304.7465, arXiv:1209.196

Asteroseismology and Interferometry

Asteroseismology provides us with a unique opportunity to improve our understanding of stellar structure and evolution. Recent developments, including the first systematic studies of solar-like pulsators, have boosted the impact of this field of research within Astrophysics and have led to a significant increase in the size of the research community. In the present paper we start by reviewing the basic observational and theoretical properties of classical and solar-like pulsators and present results from some of the most recent and outstanding studies of these stars. We centre our review on those classes of pulsators for which interferometric studies are expected to provide a significant input. We discuss current limitations to asteroseismic studies, including difficulties in mode identification and in the accurate determination of global parameters of pulsating stars, and, after a brief review of those aspects of interferometry that are most relevant in this context, anticipate how interferometric observations may contribute to overcome these limitations. Moreover, we present results of recent pilot studies of pulsating stars involving both asteroseismic and interferometric constraints and look into the future, summarizing ongoing efforts concerning the development of future instruments and satellite missions which are expected to have an impact in this field of research.Comment: Version as published in The Astronomy and Astrophysics Review, Volume 14, Issue 3-4, pp. 217-36

Characterization of Inhibitory Anti-Duffy Binding Protein II Immunity: Approach to Plasmodium vivax Vaccine Development in Thailand

Plasmodium vivax Duffy binding protein region II (DBPII) is an important vaccine candidate for antibody-mediated immunity against vivax malaria. A significant challenge for vaccine development of DBPII is its highly polymorphic nature that alters sensitivity to neutralizing antibody responses. Here, we aim to characterize naturally-acquired neutralizing antibodies against DBPII in individual Thai residents to give insight into P. vivax vaccine development in Thailand. Anti-DBPII IgG significantly increased in acute vivax infections compared to uninfected residents and naive controls. Antibody titers and functional anti-DBPII inhibition varied widely and there was no association between titer and inhibition activity. Most high titer plasmas had only a moderate to no functional inhibitory effect on DBP binding to erythrocytes, indicating the protective immunity against DBPII binding is strain specific. Only 5 of 54 samples were highly inhibitory against DBP erythrocyte-binding function. Previously identified target epitopes of inhibitory anti-DBPPII IgG (H1, H2 and H3) were localized to the dimer interface that forms the DARC binding pocket. Amino acid polymorphisms (monomorphic or dimorphic) in H1 and H3 protective epitopes change sensitivity of immune inhibition by alteration of neutralizing antibody recognition. The present study indicates Thai variant H1.T1 (R308S), H3.T1 (D384G) and H3.T3 (K386N) are the most important variants for a DBPII candidate vaccine needed to protect P. vivax in Thai residents

The shear viscosity of carbon fibre suspension and its application for fibre length measurement

The viscosity of short carbon fibre suspensions in glycerol aqueous solution was measured using a bespoke vane-in-cup viscometer, where the carbon fibre has an aspect ratio from 450 to 2209. In the semi-concentrated regime, nL3 ranging from 20 to 4400, the suspensions demonstrated strong shear-thinning characteristics particularly at higher concentrations. The shear-thinning characteristic is strongly related to the crowding factor proposed by Kerekes, indicating that non-hydrodynamic interactions occur in the suspensions. The influence of fibre bending on viscosity emerges when the bending ratio is lower than 0.0028. An empirical model based on transient network formation and rupture was proposed and used to correlate the relative viscosity with fibre concentration nL3 and shear rate. Based on the model, a viscosity method is established to analyse the fibre length by measuring the viscosity of the fibre suspension using a bespoke vane-in-cup viscometer

Impact of therapy on quality of life, neurocognitive function and their correlates in glioblastoma multiforme: a review

The maintenance of quality of life (QoL) in patients with high-grade glioma is an important endpoint during treatment, particularly in those with glioblastoma multiforme (GBM) given its dismal prognosis despite limited advances in standard therapy. It has proven difficult to identify new therapies that extend survival in patients with recurrent GBM, so one of the primary aims of new therapies is to reduce morbidity, restore or preserve neurologic functions, and the capacity to perform daily activities. Apart from temozolomide, cytotoxic chemotherapeutic agents do not appear to significantly impact response or survival, but produce toxicity that is likely to negatively impact QoL. New biological agents, such as bevacizumab, can induce a clinically meaningful proportion of durable responses among patients with recurrent GBM with an acceptable safety profile. Emerging evidence suggests that bevacizumab produces an improvement or preservation of neurocognitive function in GBM patients, suggestive of QoL improvement, in most poor-prognosis patients who would otherwise be expected to show a sudden and rapid deterioration in QoL

Adaptable Functionality of Transcriptional Feedback in Bacterial Two-Component Systems

A widespread mechanism of bacterial signaling occurs through two-component systems, comprised of a sensor histidine kinase (SHK) and a transcriptional response regulator (RR). The SHK activates RR by phosphorylation. The most common two-component system structure involves expression from a single operon, the transcription of which is activated by its own phosphorylated RR. The role of this feedback is poorly understood, but it has been associated with an overshooting kinetic response and with fast recovery of previous interrupted signaling events in different systems. Mathematical models show that overshoot is only attainable with negative feedback that also improves response time. Our models also predict that fast recovery of previous interrupted signaling depends on high accumulation of SHK and RR, which is more likely in a positive feedback regime. We use Monte Carlo sampling of the parameter space to explore the range of attainable model behaviors. The model predicts that the effective feedback sign can change from negative to positive depending on the signal level. Variations in two-component system architectures and parameters may therefore have evolved to optimize responses in different bacterial lifestyles. We propose a conceptual model where low signal conditions result in a responsive system with effectively negative feedback while high signal conditions with positive feedback favor persistence of system output

Nanomechanical detection of antibiotic-mucopeptide binding in a model for superbug drug resistance

The alarming growth of the antibiotic-resistant superbugs methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant Enterococcus (VRE) is driving the development of new technologies to investigate antibiotics and their modes of action. We report the label-free detection of vancomycin binding to bacterial cell wall precursor analogues (mucopeptides) on cantilever arrays, with 10 nM sensitivity and at clinically relevant concentrations in blood serum. Differential measurements quantified binding constants for vancomycin-sensitive and vancomycin-resistant mucopeptide analogues. Moreover, by systematically modifying the mucopeptide density we gain new insights into the origin of surface stress. We propose that stress is a product of a local chemical binding factor and a geometrical factor describing the mechanical connectivity of regions affected by local binding in terms of a percolation process. Our findings place BioMEMS devices in a new class of percolative systems. The percolation concept will underpin the design of devices and coatings to significantly lower the drug detection limit and may also impact on our understanding of antibiotic drug action in bacteria.Comment: Comments: This paper consists of the main article (6 pages, 5 figures) plus Supplemental Material (6 pages, 3 figures). More details are available at http://www.london-nano.co

Minichromosome Maintenance 2 Bound with Retroviral Gp70 Is Localized to Cytoplasm and Enhances DNA-Damage-Induced Apoptosis

The interaction of viral proteins with host-cellular proteins elicits the activation of cellular signal transduction pathways and possibly leads to viral pathogenesis as well as cellular biological events. Apoptotic signals induced by DNA-damage are remarkably up-regulated by Friend leukemia virus (FLV) exclusively in C3H hosts; however, the mechanisms underlying the apoptosis enhancement and host-specificity are unknown. Here, we show that C3H mouse-derived hematopoietic cells originally express higher levels of the minichromosome maintenance (MCM) 2 protein than BALB/c- or C57BL/6-deriverd cells, and undergo more frequent apoptosis following doxorubicin-induced DNA-damage in the presence of the FLV envelope protein gp70. Dual transfection with gp70/Mcm2 reproduced doxorubicin-induced apoptosis even in BALB/c-derived 3T3 cells. Immunoprecipitation assays using various deletion mutants of MCM2 revealed that gp70 bound to the nuclear localization signal (NLS) 1 (amino acids 18–24) of MCM2, interfered with the function of NLS2 (amino acids 132–152), and suppressed the normal nuclear-import of MCM2. Cytoplasmic MCM2 reduced the activity of protein phosphatase 2A (PP2A) leading to the subsequent hyperphosphorylation of DNA-dependent protein kinase (DNA-PK). Phosphorylated DNA-PK exhibited elevated kinase activity to phosphorylate P53, thereby up-regulating p53-dependent apoptosis. An apoptosis-enhancing domain was identified in the C-terminal portion (amino acids 703–904) of MCM2. Furthermore, simultaneous treatment with FLV and doxorubicin extended the survival of SCID mice bearing 8047 leukemia cells expressing high levels of MCM2. Thus, depending on its subcellular localization, MCM2 plays different roles. It participates in DNA replication in the nucleus as shown previously, and enhances apoptosis in the cytoplasm

Muscle Dystroglycan Organizes the Postsynapse and Regulates Presynaptic Neurotransmitter Release at the Drosophila Neuromuscular Junction

International audienceBACKGROUND: The Dystrophin-glycoprotein complex (DGC) comprises dystrophin, dystroglycan, sarcoglycan, dystrobrevin and syntrophin subunits. In muscle fibers, it is thought to provide an essential mechanical link between the intracellular cytoskeleton and the extracellular matrix and to protect the sarcolemma during muscle contraction. Mutations affecting the DGC cause muscular dystrophies. Most members of the DGC are also concentrated at the neuromuscular junction (NMJ), where their deficiency is often associated with NMJ structural defects. Hence, synaptic dysfunction may also intervene in the pathology of dystrophic muscles. Dystroglycan is a central component of the DGC because it establishes a link between the extracellular matrix and Dystrophin. In this study, we focused on the synaptic role of Dystroglycan (Dg) in Drosophila. METHODOLOGY/PRINCIPAL FINDINGS: We show that Dg was concentrated postsynaptically at the glutamatergic NMJ, where, like in vertebrates, it controls the concentration of synaptic Laminin and Dystrophin homologues. We also found that synaptic Dg controlled the amount of postsynaptic 4.1 protein Coracle and alpha-Spectrin, as well as the relative subunit composition of glutamate receptors. In addition, both Dystrophin and Coracle were required for normal Dg concentration at the synapse. In electrophysiological recordings, loss of postsynaptic Dg did not affect postsynaptic response, but, surprisingly, led to a decrease in glutamate release from the presynaptic site. CONCLUSION/SIGNIFICANCE: Altogether, our study illustrates a conservation of DGC composition and interactions between Drosophila and vertebrates at the synapse, highlights new proteins associated with this complex and suggests an unsuspected trans-synaptic function of Dg

Adjusting Phenotypes by Noise Control

Genetically identical cells can show phenotypic variability. This is often caused by stochastic events that originate from randomness in biochemical processes involving in gene expression and other extrinsic cellular processes. From an engineering perspective, there have been efforts focused on theory and experiments to control noise levels by perturbing and replacing gene network components. However, systematic methods for noise control are lacking mainly due to the intractable mathematical structure of noise propagation through reaction networks. Here, we provide a numerical analysis method by quantifying the parametric sensitivity of noise characteristics at the level of the linear noise approximation. Our analysis is readily applicable to various types of noise control and to different types of system; for example, we can orthogonally control the mean and noise levels and can control system dynamics such as noisy oscillations. As an illustration we applied our method to HIV and yeast gene expression systems and metabolic networks. The oscillatory signal control was applied to p53 oscillations from DNA damage. Furthermore, we showed that the efficiency of orthogonal control can be enhanced by applying extrinsic noise and feedback. Our noise control analysis can be applied to any stochastic model belonging to continuous time Markovian systems such as biological and chemical reaction systems, and even computer and social networks. We anticipate the proposed analysis to be a useful tool for designing and controlling synthetic gene networks