Will your article be found? Authors choose a confusing variety of words to describe dental survival analyses

OBJECTIVES: Identify the words and phrases that authors used to describe time-to-event outcomes of dental treatments in patients.

MATERIALS AND METHODS: A systematic handsearch of 50 dental journals with the highest Citation Index for 2008 identified articles reporting dental treatment with time-to-event statistics (included "case" articles, n = 95), without time-to-event statistics (active "control" articles, n = 91), and all other articles (passive "control" articles n = 6796). The included and active controls were read, identifying 43 English words across the title, aim and abstract, indicating that outcomes were studied over time. Once identified, these words were sought within the 6796 passive controls. Words were divided into six groups. Differences in use of words were analyzed with Pearson's chi-square across these six groups, and the three locations (title, aim, and abstract).

RESULTS: In the abstracts, included articles used group 1 (statistical technique) and group 2 (statistical terms) more frequently than the active and passive controls (group 1: 35%, 2%, 0.37%, P < 0.001 and group 2: 31%, 1%, 0.06%, P < 0.001). The included and active controls used group 3 (quasi-statistical) equally, but significantly more often than the passive controls (82%, 78%, 3.21%, P < 0.001). In the aims, use of target words was similar for included and active controls, but less frequent for groups 1-4 in the passive controls (P < 0.001). In the title, group 2 (statistical techniques) and groups 3-5 (outcomes) were similar for included and active controls, but groups 2 and 3 were less frequent in the passive controls (P < 0.001). Significantly more included articles used group 6 words (stating the study duration) (54%, 30%, P = 0.001).

CONCLUSION: All included articles used time-to-event analyses, but two-thirds did not include words to highlight this in the abstract. There is great variation in the words authors used to describe dental time-to-event outcomes. Electronic identification of such articles would be inconsistent, with low sensitivity and specificity. Authors should improve the reporting quality. Journals should allow sufficient space in abstracts to summarize research, and not impose unrealistic word limits. Readers should be mindful of these problems when searching for relevant articles. Additional research is required in this field.

Inference in Polytrees with Sets of Probabilities

Inferences in directed acyclic graphs associated with probability intervals and sets of probabilities are NP-hard, even for polytrees. We propose: 1) an improvement on Tessem’s A/R algorithm for inferences on polytrees associated with probability intervals; 2) a new algorithm for approximate inferences based on local search; 3) branch-and-bound algorithms that combine the previous techniques. The first two algorithms produce complementary approximate solutions, while branch-and-bound procedures can generate either exact or approximate solutions. We report improvements on existing techniques for inference with probability sets and intervals, in some cases reducing computational effort by several orders of magnitude.

Distributional Similarity of Words with Different Frequencies

Distributional semantics tries to characterize the meaning of words by the contexts in which they occur. Similarity of words hence can be derived from the similarity of contexts. Contexts of a word are usually vectors of words appearing near to that word in a corpus. It was observed in previous research that similarity measures for the context vectors of two words depend on the frequency of these words. In the present paper we investigate this dependency in more detail for one similarity measure, the Jensen-Shannon divergence. We give an empirical model of this dependency and propose the deviation of the observed Jensen-Shannon divergence from the divergence expected on the basis of the frequencies of the words as an alternative similarity measure. We show that this new similarity measure is superior to both the Jensen-Shannon divergence and the cosine similarity in a task, in which pairs of words, taken from Wordnet, have to be classified as being synonyms or not.

Dynamic power- and failure-aware cloud resources allocation for Sets of independent tasks

Cloud computing is increasingly being adopted in different scenarios, like social networking, business applications, scientific experiments, etc. Relying in virtualization technology, the construction of these computing environments targets improvements in the infrastructure, such as power-efficiency and fulfillment of users’ SLA specifications. The methodology usually applied is packing all the virtual machines on the proper physical servers. However, failure occurrences in these networked computing systems can induce substantial negative impact on system performance, deviating the system from ours initial objectives. In this work, we propose adapted algorithms to dynamically map virtual machines to physical hosts, in order to improve cloud infrastructure power-efficiency, with low impact on users’ required performance. Our decision making algorithms leverage proactive fault-tolerance techniques to deal with systems failures, allied with virtual machine technology to share nodes resources in an accurately and controlled manner. The results indicate that our algorithms perform better targeting power-efficiency and SLA fulfillment, in face of cloud infrastructure failures.

Appreciating the power of words and imaginative organizing: A triadic model of ethics practiced in everyday conversations

This thesis provides an alternative framework to analyze power and ethics practiced in everyday conversations, which constitute processes of organizing. Drawing upon narrative frameworks, the analyses of messages posted on an online message board demonstrate people’s imaginative capacity to create relevant stories, in respect of their precise grasp of factual understandings, contextual relevance and evaluative/moral appropriateness, by appropriating others’ words. Based on the empirical analyses, the thesis indicates that studies on power and ethics in organizations can be re-oriented towards appreciating irremediable power imbalances by offering alternative ways of member’s denoting experiences of power.

Ranking Sets of Objects

We provide a survey of the literature on ranking sets of objects. The interpretations of those set rankings include those employed in the theory of choice under complete uncertainty, rankings of opportunity sets, set rankings that appear in matching theory, and the structure of assembly preferences. The survey is prepared for the Handbook of Utility Theory, vol. 2, edited by Salvador Barberà, Peter Hammond, and Christian Seidl, to be published by Kluwer Academic Publishers. The chapter number is provisional.

Fair Sets of Some Classes of Graphs

Given a non empty set S of vertices of a graph, the partiality of a vertex with respect to S is the di erence between maximum and minimum of the distances of the vertex to the vertices of S. The vertices with minimum partiality constitute the fair center of the set. Any vertex set which is the fair center of some set of vertices is called a fair set. In this paper we prove that the induced subgraph of any fair set is connected in the case of trees and characterise block graphs as the class of chordal graphs for which the induced subgraph of all fair sets are connected. The fair sets of Kn, Km;n, Kn e, wheel graphs, odd cycles and symmetric even graphs are identi ed. The fair sets of the Cartesian product graphs are also discussed

On Solution Sets of Information Inequalities

We investigate solution sets of a special kind of linear inequality systems. In particular, we derive characterizations of these sets in terms of minimal solution sets. The studied inequalities emerge as information inequalities in the context of Bayesian networks. This allows to deduce important properties of Bayesian networks, which is important within causal inference.

Evaluation of sets of oriented and non-oriented receptive fields as local descriptors

Local descriptors are increasingly used for the task of object recognition because of their perceived robustness with respect to occlusions and to global geometrical deformations. We propose a performance criterion for a local descriptor based on the tradeoff between selectivity and invariance. In this paper, we evaluate several local descriptors with respect to selectivity and invariance. The descriptors that we evaluated are Gaussian derivatives up to the third order, gray image patches, and Laplacian-based descriptors with either three scales or one scale filters. We compare selectivity and invariance to several affine changes such as rotation, scale, brightness, and viewpoint. Comparisons have been made keeping the dimensionality of the descriptors roughly constant. The overall results indicate a good performance by the descriptor based on a set of oriented Gaussian filters. It is interesting that oriented receptive fields similar to the Gaussian derivatives as well as receptive fields similar to the Laplacian are found in primate visual cortex.

The sound of words.

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