1,458 research outputs found
TiK‐means: Transformation‐infused K ‐means clustering for skewed groups
The K ‐means algorithm is extended to allow for partitioning of skewed groups. Our algorithm is called TiK‐means and contributes a K ‐means‐type algorithm that assigns observations to groups while estimating their skewness‐transformation parameters. The resulting groups and transformation reveal general‐structured clusters that can be explained by inverting the estimated transformation. Further, a modification of the jump statistic chooses the number of groups. Our algorithm is evaluated on simulated and real‐life data sets and then applied to a long‐standing astronomical dispute regarding the distinct kinds of gamma ray bursts
Extending K-means
In the unsupervised learning setting, where data labels are not available and few constraints are put on data structure before analysis, having a robust procedure is paramount for any method tasked with analyzing that data. This dissertation presents three distinct papers, each of which provides a mechanic for extending the use cases of the K-means algorithm.
Paper 1. Clustering is a difficult problem that is further challenged in higher dimensions where some of the information can be redundant. Such redundancy can be in the form of dimensions that have group information that is already present in other variables, or are simply irrelevant and contribute no useful information with regard to clustering. The K-means algorithm is arguably the most widely used clustering tool, but its performance is degraded by the presence of redundant dimensions. We provide a formal approach to identifying and removing these redundant features and demonstrate improved performance, as well as interpretability of the derived groupings. Our methodology also simultaneously estimates the number of groups while selecting dimensions informative for clustering. We evaluate performance on datasets simulated under many complexities and conditions as well as on a set of handwritten digits, and is used to identify different running styles among participants in a 100 km ultra-marathon race.
Paper 2. The K-means algorithm is extended to allow for partitioning of skewed groups. Our algorithm is called TiK-Means and contributes a K-means type algorithm that assigns observations to groups while estimating their skewness-transformation parameters. The resulting groups and transformation reveal general-structured clusters that can be explained by inverting the estimated transformation. Further, a modification of the jump statistic chooses the number of groups. Our algorithm is evaluated on simulated and real- life datasets and then applied to a long-standing astronomical dispute regarding the distinct kinds of gamma ray bursts.
Paper 3. This paper presents a method for processing handwritten documents and clustering components of the writing into groups based on structural attributes. The obtained cluster membership information is used to develop a statistical model for writer identification. The presented clustering algorithm creates a grouping structure for glyphs, which are small pieces of handwriting extracted using the handwriter R package developed by Berry. To facilitate the clustering of glyphs, a distance measure inspired by the graph edit distance and a method for calculating the center of a set of glyphs are both introduced. The clustering algorithm is applied to the MNIST dataset for demonstration and exploratory purposes. Various behaviors of the algorithm are explored using its relatively simple digit glyphs. We also establish a Bayesian hierarchical model for modeling a set of writers based on their propensity for writing glyphs that are assigned to certain clusters. We then perform a full scale writer identification analysis on handwritten documents from 27 writers in the Computer Vision Lab dataset
A Uniform Approximation for the Fidelity in Chaotic Systems
In quantum/wave systems with chaotic classical analogs, wavefunctions evolve
in highly complex, yet deterministic ways. A slight perturbation of the system,
though, will cause the evolution to diverge from its original behavior
increasingly with time. This divergence can be measured by the fidelity, which
is defined as the squared overlap of the two time evolved states. For chaotic
systems, two main decay regimes of either Gaussian or exponential behavior have
been identified depending on the strength of the perturbation. For perturbation
strengths intermediate between the two regimes, the fidelity displays both
forms of decay. By applying a complementary combination of random matrix and
semiclassical theory, a uniform approximation can be derived that covers the
full range of perturbation strengths. The time dependence is entirely fixed by
the density of states and the so-called transition parameter, which can be
related to the phase space volume of the system and the classical action
diffusion constant, respectively. The accuracy of the approximations are
illustrated with the standard map.Comment: 16 pages, 4 figures, accepted in J. Phys. A, special edition on
Random Matrix Theor
Dependence of the kinetic energy absorption capacity of bistable mechanical metamaterials on impactor mass and velocity
Using an alternative mechanism to dissipation or scattering, bistable
structures and mechanical metamaterials have shown promise for mitigating the
detrimental effects of impact by reversibly locking energy into strained
material. Herein, we extend prior works on impact absorption via bistable
metamaterials to computationally explore the dependence of kinetic energy
transmission on the velocity and mass of the impactor, with strain rates
exceeding s. We observe a large dependence on both impactor
parameters, ranging from significantly better to worse performance than a
comparative linear material. We then correlate the variability in performance
to solitary wave formation in the system and give analytical estimates of
idealized energy absorption capacity under dynamic loading. In addition, we
find a significant dependence on damping accompanied by a qualitative
difference in solitary wave propagation within the system. The complex dynamics
revealed in this study offer potential future guidance for the application of
bistable metamaterials to applications including human and engineered system
shock and impact protection devices
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Discovery of a mammalian splice variant of myostatin that stimulates myogenesis
Myostatin plays a fundamental role in regulating the size of skeletal muscles. To date, only a single myostatin gene and no splice variants have been identified in mammals. Here we describe the splicing of a cryptic intron that removes the coding sequence for the receptor binding moiety of sheep myostatin. The deduced polypeptide sequence of the myostatin splice variant (MSV) contains a 256 amino acid N-terminal domain, which is common to myostatin, and a unique C-terminus of 65 amino acids. Western immunoblotting demonstrated that MSV mRNA is translated into protein, which is present in skeletal muscles. To determine the biological role of MSV, we developed an MSV over-expressing C2C12 myoblast line and showed that it proliferated faster than that of the control line in association with an increased abundance of the CDK2/Cyclin E complex in the nucleus. Recombinant protein made for the novel C-terminus of MSV also stimulated myoblast proliferation and bound to myostatin with high affinity as determined by surface plasmon resonance assay. Therefore, we postulated that MSV functions as a binding protein and antagonist of myostatin. Consistent with our postulate, myostatin protein was
co-immunoprecipitated from skeletal muscle extracts with an MSV-specific antibody. MSV over-expression in C2C12 myoblasts blocked myostatin-induced Smad2/3-dependent signaling, thereby confirming that MSV antagonizes the
canonical myostatin pathway. Furthermore, MSV over expression increased the abundance of MyoD, Myogenin and MRF4 proteins (P,0.05), which indicates that MSV stimulates myogenesis through the induction of myogenic regulatory factors. To help elucidate a possible role in vivo, we observed that MSV protein was more abundant during early post-natal muscle development, while myostatin remained unchanged, which suggests that MSV may promote the growth of skeletal muscles. We conclude that MSV represents a unique example of intra-genic regulation in which a splice variant directly antagonizes the biological activity of the canonical gene product
Tetrahydropyrazolo[1,5-a]Pyrimidine-3-Carboxamide and N-Benzyl-6′,7′-Dihydrospiro[Piperidine-4,4′-Thieno[3,2-c]Pyran] analogues with bactericidal efficacy against Mycobacterium tuberculosis targeting MmpL3
Mycobacterium tuberculosis is a major human pathogen and the causative agent for the pulmonary disease, tuberculosis (TB). Current treatment programs to combat TB are under threat due to the emergence of multi-drug and extensively-drug resistant TB. As part of our efforts towards the discovery of new anti-tubercular leads, a number of potent tetrahydropyrazolo[1,5-a]pyrimidine-3-carboxamide(THPP) and N-benzyl-6′,7′-dihydrospiro[piperidine-4,4′-thieno[3,2-c]pyran](Spiro) analogues were recently identified against Mycobacterium tuberculosis and Mycobacterium bovis BCG through a high-throughput whole-cell screening campaign. Herein, we describe the attractive in vitro and in vivo anti-tubercular profiles of both lead series. The generation of M. tuberculosis spontaneous mutants and subsequent whole genome sequencing of several resistant mutants identified single mutations in the essential mmpL3 gene. This ‘genetic phenotype’ was further confirmed by a ‘chemical phenotype’, whereby M. bovis BCG treated with both the THPP and Spiro series resulted in the accumulation of trehalose monomycolate. In vivo efficacy evaluation of two optimized THPP and Spiro leads showed how the compounds were able to reduce >2 logs bacterial cfu counts in the lungs of infected mice
The impact of different DNA extraction kits and laboratories upon the assessment of human gut microbiota composition by 16S rRNA gene sequencing
Peer reviewedPublisher PD
Semiclassical Theory of Coulomb Blockade Peak Heights in Chaotic Quantum Dots
We develop a semiclassical theory of Coulomb blockade peak heights in chaotic
quantum dots. Using Berry's conjecture, we calculate the peak height
distributions and the correlation functions. We demonstrate that the
corrections to the corresponding results of the standard statistical theory are
non-universal and can be expressed in terms of the classical periodic orbits of
the dot that are well coupled to the leads. The main effect is an oscillatory
dependence of the peak heights on any parameter which is varied; it is
substantial for both symmetric and asymmetric lead placement. Surprisingly,
these dynamical effects do not influence the full distribution of peak heights,
but are clearly seen in the correlation function or power spectrum. For
non-zero temperature, the correlation function obtained theoretically is in
good agreement with that measured experimentally.Comment: 5 color eps figure
Effects of Stem Cell Factor on Hypoxia-Inducible Factor 1 Alpha Accumulation in Human Acute Myeloid Leukaemia and LAD2 Mast Cells
Stem cell factor (SCF) is a hematopoietic growth factor that exerts its activity by signalling through the tyrosine kinase receptor known as Kit or CD117. SCF-Kit signalling is crucial for the survival, proliferation and differentiation of hematopoietic cells of myeloid lineage. Furthermore, since myeloid leukaemia cells express the Kit receptor, SCF may play an important role in myeloid leukaemia progression too. However, the mechanisms of this pathophysiological effect remain unclear. Recent evidence shows that SCF triggers accumulation of the inducible alpha subunit of hypoxia-inducible factor 1 (HIF-1) in hematopoietic cells—a transcription complex that plays a pivotal role in cellular adaptation to low oxygen availability. However, it is unknown how SCF impacts on HIF-1α accumulation in human myeloid leukaemia and mast cells. Here we show that SCF induces HIF-1α accumulation in THP-1 human myeloid leukaemia cells but not in LAD2 mast cells. We demonstrated that LAD2 cells have a more robust glutathione (GSH)-dependent antioxidative system compared to THP-1 cells and are therefore protected against the actions of ROS generated in an SCF-dependent manner. BSO-induced GSH depletion led to a significant decrease in HIF-1α prolyl hydroxylase (PHD) activity in THP-1 cells and to near attenuation of it in LAD2 cells. In THP-1 cells, SCF-induced HIF-1α accumulation is controlled via ERK, PI3 kinase/PKC-δ/mTOR-dependent and to a certain extent by redox-dependent mechanisms. These results demonstrate for the first time an important cross-talk of signalling pathways associated with HIF-1 activation—an important stage of the myeloid leukaemia cell life cycle
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