NP-hardness of MAP in Ternary Tree Bayesian Networks

This paper strengthens the NP-hardness result for the (partial) maximum a posteriori (MAP) problem in Bayesian networks with topology of trees (every variable has at most one parent) and variable cardinality at most three. MAP is the problem of querying the most probable state configuration of some (not necessarily all) of the network variables given evidence. It is demonstrated that the problem remains hard even in such simplistic networks.

Finite domination and Novikov rings. Laurent polynomial rings in several variables

We present a homological characterisation of those chain complexes of modules over a Laurent polynomial ring in several indeterminates which are finitely dominated over the ground ring (that is, are a retract up to homotopy of a bounded complex of finitely generated free modules). The main tools, which we develop in the paper, are a non-standard totalisation construction for multi-complexes based on truncated products, and a high-dimensional mapping torus construction employing a theory of cubical diagrams that commute up to specified coherent homotopies.

Averaged Extended Tree Augmented Naive Classifier

This work presents a new general purpose classifier named Averaged Extended Tree Augmented Naive Bayes (AETAN), which is based on combining the advantageous characteristics of Extended Tree Augmented Naive Bayes (ETAN) and Averaged One-Dependence Estimator (AODE) classifiers. We describe the main properties of the approach and algorithms for learning it, along with an analysis of its computational time complexity. Empirical results with numerous data sets indicate that the new approach is superior to ETAN and AODE in terms of both zero-one classification accuracy and log loss. It also compares favourably against weighted AODE and hidden Naive Bayes. The learning phase of the new approach is slower than that of its competitors, while the time complexity for the testing phase is similar. Such characteristics suggest that the new classifier is ideal in scenarios where online learning is not required.

Learning Extended Tree Augmented Naive Structures

This work proposes an extended version of the well-known tree-augmented naive Bayes (TAN) classifier where the structure learning step is performed without requiring features to be connected to the class. Based on a modification of Edmonds' algorithm, our structure learning procedure explores a superset of the structures that are considered by TAN, yet achieves global optimality of the learning score function in a very efficient way (quadratic in the number of features, the same complexity as learning TANs). We enhance our procedure with a new score function that only takes into account arcs that are relevant to predict the class, as well as an optimization over the equivalent sample size during learning. These ideas may be useful for structure learning of Bayesian networks in general. A range of experiments shows that we obtain models with better prediction accuracy than naive Bayes and TAN, and comparable to the accuracy of the state-of-the-art classifier averaged one-dependence estimator (AODE). We release our implementation of ETAN so that it can be easily installed and run within Weka.

Learning Bounded Tree-Width Bayesian Networks via Sampling

Learning Bayesian networks with bounded tree-width has attracted much attention recently, because low tree-width allows exact inference to be performed efficiently. Some existing methods [12, 14] tackle the problem by using k-trees to learn the optimal Bayesian network with tree-width up to k. In this paper, we propose a sampling method to efficiently find representative k-trees by introducing an Informative score function to characterize the quality of a k-tree. The proposed algorithm can efficiently learn a Bayesian network with tree-width at most k. Experiment results indicate that our approach is comparable with exact methods, but is much more computationally efficient.

Microbicide Vaginal Rings: Technological Challenges and Clinical Development

Vaginal rings (VRs) are flexible, torus-shaped, polymeric devices designed to sustain delivery of pharmaceutical drugs to the vagina for clinical benefit. Following first report in a 1970 patent application, several steroid-releasing VR products have since been marketed for use in hormone replacement therapy and contraception. Since 2002, there has been growing interest in the use of VR technology for delivery of drugs that can reduce the risk of sexual acquisition of human immunodeficiency virus type 1 (HIV-1), the causative agent of acquired immunodeficiency syndrome (AIDS). Although no vaginally-administered product has yet been approved for HIV reduction/prevention, extensive research efforts are continuing and a number of VR devices offering sustained release of so-called ‘HIV microbicide’ compounds are currently being evaluated in late-stage clinical studies. This review article provides an overview of the published scientific literature within this important field of research, focusing primarily on articles published within peer-reviewed journal publications. Many important aspects of microbicide-releasing VR technology are discussed, with a particular emphasis on the technological, manufacturing and clinical challenges that have emerged in recent years.

Learning Bayesian Networks with Bounded Tree-Width via Guided Search

Bounding the tree-width of a Bayesian network can reduce the chance of overfitting, and allows exact inference to be performed efficiently. Several existing algorithms tackle the problem of learning bounded tree-width Bayesian networks by learning from k-trees as super-structures, but they do not scale to large domains and/or large tree-width. We propose a guided search algorithm to find k-trees with maximum Informative scores, which is a measure of quality for the k-tree in yielding good Bayesian networks. The algorithm achieves close to optimal performance compared to exact solutions in small domains, and can discover better networks than existing approximate methods can in large domains. It also provides an optimal elimination order of variables that guarantees small complexity for later runs of exact inference. Comparisons with well-known approaches in terms of learning and inference accuracy illustrate its capabilities.

Evaluation of the in vitro biological activities of extracts from carob tree and mediterranean oaks

Dissertação mest., Engenharia Biológica, Universidade do Algarve, 2009

Chemical and microbial changes during the natural fermentation of strawberry tree (Arbutus unedo L.) fruits

Aguardente de medronho is the name given in Portugal to a spirit made from the fermented fruit of Arbutus unedo (strawberry tree), a plant grown in the Mediterranean region. In order to gain a better understanding of the fermentation process, as it is performed in the farms, a natural fermentation with wild microbiota was carried out during 36 days, and some physicochemical and microbiological parameters were studied. The microbial parameters analyzed were total viable, lactic and acetic acids bacteria, and yeast counts. The physicochemical parameters monitored were sugars, minerals, ethanol, organic acids and pH. Yeasts were the main responsible for the fermentation of the fruits, as the lactic and acetic acids bacteria are absent. As the fermentation progressed, the sugars increased during the first 2 days and gradually decreased along the fermentation period. Maintaining the good quality of the product could contribute to the preservation and valorization of traditional resources that are of great importance to prevent their disappearance.

Entomofauna associated with the olive tree in southern Portugal

Since 2004 several studies have been carried out in order to identify the main insect species that usually inhabiting the olive ecosystem. The field trials have taken place in two olive groves, one situated in Olhão and the other one in Loulé, both in Algarve and also under Integrated Pest Management (IPM). The sampling techniques used differ according to their purpose (sticky traps, pheromone traps, pitfall traps and samples of aerial parts of the trees such as inflorescences, leaves, fruits and branches). Results showed that the main insect pests of olive tree in southern Portugal were the olive fruit fly Bactrocera oleae Gmelin (Diptera: Tephritidae) and the olive moth Prays oleae Bernard (Lepidoptera: Hyponeumetidae). Other insect pests were also found in our olive groves namely the olive psyllid Euphyllura olivina Costa (Homoptera: Psyllidae), the olive dark beetle Phloeotribus scarabaeoides Bernard (Coleoptera: Curculionidae), the mediterranean black scale Saissetia oleae (Olivier) (Homoptera: Coccidae) and the olive thrip Liothripes oleae Costa (Thysanoptera: Phlaeothripidae). Concerning the auxiliary insects that were found in our olives groves they belong to the following orders and families: Diptera (Syrphidae), Coleoptera (Carabidae, Coccinelidae and Staphylinidae), Hemiptera (Anthocoridae and Miridae), Neuroptera (Chrysopidae) and Hymenoptera (Braconidae, Encyrtidae, Eulophidae, Formicidae and Trichogrammatidae).

Yeast diversity in the Mediterranean strawberry tree (Arbutus unedo L.) fruits' fermentations

In the Mediterranean region the fruits of the strawberry tree (Arbutus unedo L.) may be fermented and distilled to produce a traditional beverage very much appreciated in Southern Europe. The aim of the present work was to study the diversity of the yeast population and the killer activity of the isolates identified as Saccharomyces cerevisiae, obtained during solid state industrial fermentations of the arbutus berries. The identification of the isolates was performed by the 5.8S rRNA-ITS region restriction analysis and by sequencing the D1/D2 region of the large subunit of the rRNA gene. At the start of the fermentations, various non-Saccharomyces species were detected including Aureobasidium pullulans, Dothichiza pithyophila, Dioszegia zsoltii, Hanseniaspora uvarum and yeasts belonging to the genera Metschnikowia, Cryptococcus and Rhodotorula. However, as the biological processes progressed the number of different species decreased with S. cerevisiae and Pichia membranaefaciens becoming dominant at advanced stages of the must fermentation that is characterized by high concentrations of ethanol. Forty three isolates identified as S. cerevisiae were tested for killer activity against two sensitive reference strains and Zygosaccharomyces bailii. Their killer sensitivity in relation to five killer referenced toxins (K2, K5, K8, K9 and K10) was also studied. Out of the isolates analyzed, 95.3% were sensitive and 4.7% were tolerant against the killer toxins tested. Only three isolates revealed killer activity against one sensitive strain and two of them against the spoiler yeast Z. bailii. The microbiota obtained revealed an interesting potential to be used as starter cultures to overcome unpredictable uncontrolled fermentations of the arbutus fruits as well as in other applications of biotechnological interest. (C) 2012 Elsevier Ltd. All rights reserved.