A Logical Descriptor for Regular Languages via Stone Duality

In this paper we introduce a class of descriptors for regular languages arising from an application of the Stone duality between finite Boolean algebras and finite sets. These descriptors, called classical fortresses, are object specified in classical propositional logic and capable to accept exactly regular languages. To prove this, we show that the languages accepted by classical fortresses and deterministic finite automata coincide. Classical fortresses, besides being propositional descriptors for regular languages, also turn out to be an efficient tool for providing alternative and intuitive proofs for the closure properties of regular languages.

Prediction of Trabecular Bone Anisotropy from Quantitative Computed Tomography using Supervised Learning and a Novel Morphometric Feature Descriptor

Patient-specific biomechanical models including local bone mineral density and anisotropy have gained importance for assessing musculoskeletal disorders. However the trabecular bone anisotropy captured by high-resolution imaging is only available at the peripheral skeleton in clinical practice. In this work, we propose a supervised learning approach to predict trabecular bone anisotropy that builds on a novel set of pose invariant feature descriptors. The statistical relationship between trabecular bone anisotropy and feature descriptors were learned from a database of pairs of high resolution QCT and clinical QCT reconstructions. On a set of leave-one-out experiments, we compared the accuracy of the proposed approach to previous ones, and report a mean prediction error of 6% for the tensor norm, 6% for the degree of anisotropy and 19◦ for the principal tensor direction. These findings show the potential of the proposed approach to predict trabecular bone anisotropy from clinically available QCT images.

The multiscenario multienvironment BioSecure Multimodal Database (BMDB)

A new multimodal biometric database designed and acquired within the framework of the European BioSecure Network of Excellence is presented. It is comprised of more than 600 individuals acquired simultaneously in three scenarios: 1) over the Internet, 2) in an office environment with desktop PC, and 3) in indoor/outdoor environments with mobile portable hardware. The three scenarios include a common part of audio/video data. Also, signature and fingerprint data have been acquired both with desktop PC and mobile portable hardware. Additionally, hand and iris data were acquired in the second scenario using desktop PC. Acquisition has been conducted by 11 European institutions. Additional features of the BioSecure Multimodal Database (BMDB) are: two acquisition sessions, several sensors in certain modalities, balanced gender and age distributions, multimodal realistic scenarios with simple and quick tasks per modality, cross-European diversity, availability of demographic data, and compatibility with other multimodal databases. The novel acquisition conditions of the BMDB allow us to perform new challenging research and evaluation of either monomodal or multimodal biometric systems, as in the recent BioSecure Multimodal Evaluation campaign. A description of this campaign including baseline results of individual modalities from the new database is also given. The database is expected to be available for research purposes through the BioSecure Association during 2008.

[Arterial-adaptive dilatation and Doppler velocimetry in normal fetuses with a single umbilical artery]

PURPOSE: In this study we examined the arterial-adaptive dilatation and Doppler velocimetry, especially RI values, in normal fetuses with a single umbilical artery (SUA). MATERIALS AND METHODS: We studied 195 fetuses from 18 to 39 weeks of gestational age with a prenatally identified SUA retrospectively. They were enrolled in this study if the following information applied: > 18 weeks of gestational age, no structural or chromosomal abnormalities, and histopathological confirmation of SUA. Sonographic examination included evaluation of the umbilical artery resistance and the cross-sectional area of the umbilical cord, and its vessels were measured in all cases. Small for gestational age (SGA) was diagnosed when the birth weight was below the 10th percentile for gestational age. Fetuses with intrauterine growth restriction were defined as those with biometric data below the 5th percentile. RESULTS: There were 119 cases of prenatally identified SUA which met the inclusion criteria. RI values were below the 10th percentile in 33/119 (27.33) and below the 50th percentile in 73/119 (61.33). RI values below the 10th percentile were significantly more likely to be in the normal collective than in the growth restricted collective [31/87 (35.63%) vs. 2/32 (6.25%); p = 0.001]. Even more significant differences became apparent when comparing the RI values below the 50th percentile of both groups. An umbilical artery diameter over the 90th percentile was found in 49 (41.9%) of cases and was significantly more likely to be present in normal growing fetuses than in the growth restricted group. CONCLUSION: Normal fetuses with SUA are at higher risk to be born as SGA. With our study results we can confirm the hypothesis that Doppler flow measurements and arterial diameter in SUA are different from those found in normal fetal umbilical arteries. RI values over the 50th percentile or a cross-sectional area of the artery below 95th percentile after 26th week of gestation significantly increases the risk of SGA.

Brain electrical microstates in subjects with panic disorder

Brain electrical microstates represent spatial configurations of scalp recorded brain electrical activity and are considered to be the basic elements of stepwise processing of information in the brain. In the present study, the hypothesis of a temporo-limbic dysfunction in panic disorder (PD) was tested by investigating the topographic descriptors of brain microstates, in particular the one corresponding to the Late Positive Complex (LPC), an event-related potential (ERP) component with generators in these regions. ERPs were recorded in PD patients and matched healthy subjects during a target detection task, in a central (CC) and a lateral condition (LC). In the CC, a leftward shift of the LPC microstate positive centroid was observed in the patients with PD versus the healthy control subjects. In the LC, the topographic descriptor of the first microstate showed a rightward shift, while those of both the second and the fourth microstate, corresponding to the LPC, revealed a leftward shift in the PD patients versus the healthy control subjects. These findings indicate an overactivation of the right hemisphere networks involved in early visual processing and a hypoactivation of the right hemisphere circuits involved in LPC generators in PD. In line with this interpretation, the abnormal topography of the LPC microstate, observed in the CC, was associated with a worse performance on a test exploring right temporo-hippocampal functioning. Topographical abnormalities found for the LPC microstate in the LC were associated with a higher number of panic attacks, suggesting a pathogenetic role of the right temporo-hippocampal dysfunction in PD.

Improved detection of amnestic MCI by means of discriminative vector quantization of single-trial cognitive ERP responses

Cognitive event-related potentials (ERPs) are widely employed in the study of dementive disorders. The morphology of averaged response is known to be under the influence of neurodegenerative processes and exploited for diagnostic purposes. This work is built over the idea that there is additional information in the dynamics of single-trial responses. We introduce a novel way to detect mild cognitive impairment (MCI) from the recordings of auditory ERP responses. Using single trial responses from a cohort of 25 amnestic MCI patients and a group of age-matched controls, we suggest a descriptor capable of encapsulating single-trial (ST) response dynamics for the benefit of early diagnosis. A customized vector quantization (VQ) scheme is first employed to summarize the overall set of ST-responses by means of a small-sized codebook of brain waves that is semantically organized. Each ST-response is then treated as a trajectory that can be encoded as a sequence of code vectors. A subject's set of responses is consequently represented as a histogram of activated code vectors. Discriminating MCI patients from healthy controls is based on the deduced response profiles and carried out by means of a standard machine learning procedure. The novel response representation was found to improve significantly MCI detection with respect to the standard alternative representation obtained via ensemble averaging (13% in terms of sensitivity and 6% in terms of specificity). Hence, the role of cognitive ERPs as biomarker for MCI can be enhanced by adopting the delicate description of our VQ scheme.

Robust meta-analytic-predictive priors in clinical trials with historical control information.

Historical information is always relevant for clinical trial design. Additionally, if incorporated in the analysis of a new trial, historical data allow to reduce the number of subjects. This decreases costs and trial duration, facilitates recruitment, and may be more ethical. Yet, under prior-data conflict, a too optimistic use of historical data may be inappropriate. We address this challenge by deriving a Bayesian meta-analytic-predictive prior from historical data, which is then combined with the new data. This prospective approach is equivalent to a meta-analytic-combined analysis of historical and new data if parameters are exchangeable across trials. The prospective Bayesian version requires a good approximation of the meta-analytic-predictive prior, which is not available analytically. We propose two- or three-component mixtures of standard priors, which allow for good approximations and, for the one-parameter exponential family, straightforward posterior calculations. Moreover, since one of the mixture components is usually vague, mixture priors will often be heavy-tailed and therefore robust. Further robustness and a more rapid reaction to prior-data conflicts can be achieved by adding an extra weakly-informative mixture component. Use of historical prior information is particularly attractive for adaptive trials, as the randomization ratio can then be changed in case of prior-data conflict. Both frequentist operating characteristics and posterior summaries for various data scenarios show that these designs have desirable properties. We illustrate the methodology for a phase II proof-of-concept trial with historical controls from four studies. Robust meta-analytic-predictive priors alleviate prior-data conflicts ' they should encourage better and more frequent use of historical data in clinical trials.

The Chemical Space of Flavours

The flavour of foods is determined by the interaction of taste molecules with receptors in the mouth, and fragrances or aroma with receptors in the upper part of the nose. Here, we discuss the properties of taste and fragrance molecules, from the public databases Superscent, Flavornet, SuperSweet and BitterDB, taken collectively as flavours, in the perspective of the chemical space. We survey simple descriptor profiles in comparison with the public collections ChEMBL (bioactive small molecules), ZINC (commercial drug-like molecules) and GDB-13 (all possible organic molecules up to 13 atoms of C, N, O, S, Cl). A global analysis of the chemical space of flavours is also presented based on molecular quantum numbers (MQN) and SMILES fingerprints (SMIfp). While taste molecules span a very broad property range, fragrances occupy a narrow area of the chemical space consisting of generally very small and relatively nonpolar molecules distinct of standard drug molecules. Proximity searching in the chemical space is exemplified as a simple method to facilitate the search for new fragrances.