Segments vs. Clusters: Postaspiration in Sevillian Spanish

Sevillian Spanish is undergoing a change from preaspiration to postaspiration in /s ptk/ sequences ([pahta] -> [patha]) (Ruch & Peters, 2016). Some previous work suggests that postaspirated stops are phonologizing in Sevillian Spanish (O'Neill, 2009; Gylfadottir, 2015). In this paper, I argue that postaspirated stops are underlyingly clusters. Evidence for the cluster representation comes from two sources: sociolinguistically-conditioned variation and phonologically-conditioned alternations across word and morpheme boundaries. I then present the results of a perception experiment showing that Sevillian listeners perceive postaspiration and map it onto an underlying cluster. Listeners of another dialect (Mexican Spanish) do not perceive or interpret postaspiration. Finally, I outline an analysis in which postaspiration is the result of gradual coda reduction followed by metathesis. This kind of metathesis may be possible due, in part, to perceptual difficulties in perceiving aspiration.

A new Zn(ii) MOF assembled from metal–organic cubes (MOCs) as a highly efficient adsorbent for cationic dyes

A new MOC [Zn3(Tz)2(tpa)2(DMSO)4] was synthesized. The cluster representation reveals an interwoven pcu 6/4/c1 sqc1 topological type. The MOC exhibits excellent water stability, recyclability, adsorption and separation abilities toward selected dyes.

Renewal in Hawkes processes with self-excitation and inhibition

We investigate the Hawkes processes on the positive real line exhibiting both self-excitation and inhibition. Each point of such a point process impacts its future intensity by the addition of a signed reproduction function. The case of a nonnegative reproduction function corresponds to self-excitation, and has been widely investigated in the literature. In particular, there exists a cluster representation of the Hawkes process which allows one to apply known results for Galton–Watson trees. We use renewal techniques to establish limit theorems for Hawkes processes that have reproduction functions which are signed and have bounded support. Notably, we prove exponential concentration inequalities, extending results of Reynaud-Bouret and Roy (2006) previously proven for nonnegative reproduction functions using a cluster representation no longer valid in our case. Importantly, we establish the existence of exponential moments for renewal times of M/G/$\infty$ queues which appear naturally in our problem. These results possess interest independent of the original problem.

Consensus Function Based on Clusters Clustering and Iterative Fusion of Base Clusters

In clustering ensemble, it is desired to combine several clustering outputs in order to create better results than the output results of the basic individual clustering methods in terms of consistency, robustness and performance. In this research, we want to present a clustering ensemble method with a new aggregation function. The proposed method is named Robust Clustering Ensemble based on Iterative Fusion of Base Clusters (RCEIFBC). This method takes into account the two similarity criteria: (a) one of them is the cluster-cluster similarity and (b) the other one is the object-cluster similarity. The proposed method has two steps and has been done on the binary cluster representation of the given ensemble. Indeed, before doing any step, the primary partitions are converted into a binary cluster representation where the primary ensemble has been broken into a number of primary binary clusters. The first step is to combine the primary binary clusters with the highest cluster-cluster similarity. This phase will be replicated as long as our desired candidate clusters are ready. The second step is to improve the merged clusters by assigning the data points to the merged clusters. The performance and robustness of the proposed method have been evaluated over different machine learning datasets. The experimentation indicates the effectiveness of the proposed method comparing to the state-of-the-art clustering methods in terms of performance and robustness.