Invariant-driven specifications in Maude

This work presents a general mechanism for executing specifications that comply with given invariants, which may be expressed in different formalisms and logics. We exploit Maude’s reflective capabilities and its properties as a general semantic framework to provide a generic strategy that allows us to execute Maude specifications taking into account user-defined invariants. The strategy is parameterized by the invariants and by the logic in which such invariants are expressed. We experiment with different logics, providing examples for propositional logic, (finite future time) linear temporal logic and metric temporal logic.     

Learning a color distance metric for region-based image segmentation

In this paper we describe an experiment where we studied empirically the application of a learned distance metric to be used as discrimination function for an established color image segmentation algorithm. For this purpose we chose the Mumford–Shah energy functional and the Mahalanobis distance metric. The objective was to test our approach in an objective and quantifiable way on this specific algorithm employing this particular distance model, without making generalization claims. The empirical validation of the results was performed in two experiments: one applying the resulting segmentation method on a subset of the Berkeley Image Database, an exemplar image set possessing ground-truths and validating the results against the ground-truths using two well-known inter-cluster validation methods, namely, the Rand and BGM indexes, and another experiment using images of the same context divided into training and testing set, where the distance metric is learned from the training set and then applied to segment all the images. The obtained results suggest that the use of the specified learned distance metric provides better and more robust segmentations, even if no other modification of the segmentation algorithm is performed.     

Underwater Vehicle Localization with Complementary Filter: Performance Analysis in the Shallow Water Environment

Rapid development of underwater technology during the last two decades yielded more affordable sensors and underwater vehicles, and, as a result, expanded their use from exclusively offshore industry towards smaller interdisciplinary research groups. Regardless of application, knowing the location of the vehicle operating underwater is crucial. Relatively inexpensive solution is sensor fusion based on a dynamic model of the vehicle aided by a Doppler Velocity Log and a Ultra-Short Base Line position system. Raw data from the sensors are highly asynchronous and susceptible to outliers, especially in shallow water environment. This paper presents detailed sensor analysis based on experimental data gathered in shallow waters, identifies outliers, presents an intuitive and simple sensor fusion algorithm and finally, discusses outlier rejection. The approach has been experimentally verified on medium size remotely operated vehicle.     

Inflating examples to obtain rules

A new machine learning system is presented in this article. It is called INNER and induces classification rules from a set of training examples. The process followed by this system starts with the random selection of a subset of examples that are iteratively inflated in order to cover the surroundings provided that they are inhabited by examples of the same class, thus becoming rules that will be applied by means of a partial matching mechanism. The rules so obtained can be seen as clusters of examples and represent clear evidence to support explanations about their future classifications and may be used to build intelligent advisors. The whole algorithm can be seen as a set of elastic transformations of examples and rules and produces concise, accurate rule sets, as is experimentally demonstrated in the final section of the article. © 2003 Wiley Periodicals, Inc.     

Development and Characterization of a Factor V-Deficient CRISPR Cell Model for the Correction of Mutations

Factor V deficiency, an ultra-rare congenital coagulopathy, is characterized by bleeding episodes that may be more or less intense as a function of the levels of coagulation factor activity present in plasma. Fresh-frozen plasma, often used to treat patients with factor V deficiency, is a scarcely effective palliative therapy with no specificity to the disease. CRISPR/Cas9-mediated gene editing, following precise deletion by non-homologous end-joining, has proven to be highly effective for modeling on a HepG2 cell line a mutation similar to the one detected in the factor V-deficient patient analyzed in this study, thus simulating the pathological phenotype. Additional CRISPR/Cas9-driven non-homologous end-joining precision deletion steps allowed correction of 41% of the factor V gene mutated cells, giving rise to a newly developed functional protein. Taking into account the plasma concentrations corresponding to the different levels of severity of factor V deficiency, it may be argued that the correction achieved in this study could, in ideal conditions, be sufficient to turn a severe phenotype into a mild or asymptomatic one.     

Preface: Volume 68, Number 3

Modern information systems rely more and more on combining concurrent, distributed, mobile and heterogenous components. This move from old systems, typically conceived in isolation, induces the need for new languages and software architectures. In particular, coordination languages have been proposed to cleanly separate computational aspects and communication. On the other hand, software architects face the problem of specifying and reasoning about non-functional requirements. All these issues are widely perceived as fundamental to improve software productivity, to enhance maintainability, to advocate modularity, to promote reusability, and to lead to systems more tractable and more amenable to verification and global analysis.The FOCLASA workshop was organized on August 24th 2002 as a satellite event of Concur'02 with the aim of bringing together researchers working on the foundations of component-based computing, coordination, and software architectures.This volume contains selected 12 papers presented at the workshop. They were reviewed by the program committee, consisting, besides the editors, of

• Rocco De Nicola (University of Firenze, Italy)

• Jos Luiz Fiadeiro (ATX Software and University of Lisbon, Portugal)

• Roberto Gorrieri (University of Bologna, Italy)

• Paola Inverardi (University L'Aquila, Italy)

• Joost Kok (University of Leiden, The Netherlands)

• Antonio Porto (New University of Lisbon, Portugal)

We would like to thank them together with the authors of the papers for their contribution to the meeting. We would also like to thank Michael Mislove for his help in editing this volume. Finally, we are grateful to L. Brim, M. Kretinsky, and A. Kucera for their help in organizing the workshop in Brno.     

ILB®, a Low Molecular Weight Dextran Sulphate,Restores Glutamate Homeostasis,Amino Acid Metabolism and Neurocognitive Functions in a Rat Model of Severe Traumatic Brain Injury

In a previous study, we found that administration of ILB^®, a new low molecular weight dextran sulphate, significantly improved mitochondrial functions and energy metabolism, as well as decreased oxidative/nitrosative stress, of brain tissue of rats exposed to severe traumatic brain injury (sTBI), induced by the closed-head weight-drop model of diffused TBI. Using aliquots of deproteinized brain tissue of the same animals of this former study, we here determined the concentrations of 24 amino acids of control rats, untreated sTBI rats (sacrificed at 2 and 7 days post-injury) and sTBI rats receiving a subcutaneous ILB^® administration (at the dose levels of 1, 5 and 15 mg/kg b.w.) 30 min post-impact (sacrificed at 2 and 7 days post-injury). Additionally, in a different set of experiments, new groups of control rats, untreated sTBI rats and ILB^®-treated rats (administered 30 min after sTBI at the dose levels of 1 or 5 mg/kg b.w.) were studied for their neurocognitive functions (anxiety, locomotor capacities, short- and long-term memory) at 7 days after the induction of sTBI. Compared to untreated sTBI animals, ILB^® significantly decreased whole brain glutamate (normalizing the glutamate/glutamine ratio), glycine, serine and γ-aminobutyric acid. Furthermore, ILB^® administration restored arginine metabolism (preventing nitrosative stress), levels of amino acids involved in methylation reactions (methionine, L-cystathionine, S-adenosylhomocysteine), and N-acetylaspartate homeostasis. The macroscopic evidences of the beneficial effects on brain metabolism induced by ILB^® were the relevant improvement in neurocognitive functions of the group of animals treated with ILB^® 5 mg/kg b.w., compared to the marked cognitive decline measured in untreated sTBI animals. These results demonstrate that ILB^® administration 30 min after sTBI prevents glutamate excitotoxicity and normalizes levels of amino acids involved in crucial brain metabolic functions. The ameliorations of amino acid metabolism, mitochondrial functions and energy metabolism in ILB^®-treated rats exposed to sTBI produced significant improvement in neurocognitive functions, reinforcing the concept that ILB^® is a new effective therapeutic tool for the treatment of sTBI, worth being tested in the clinical setting.     

Modeling Self-Rollable Elastomeric Films for Building Bioinspired Hierarchical 3D Structures

In this work, an innovative model is proposed as a design tool to predict both the inner and outer radii in rolled structures based on polydimethylsiloxane bilayers. The model represents an improvement of Timoshenko’s formula taking into account the friction arising from contacts between layers arising from rolling by more than one turn, hence broadening its application field towards materials based on elastomeric bilayers capable of large deformations. The fabricated structures were also provided with surface topographical features that would make them potentially usable in different application scenarios, including cell/tissue engineering ones. The bilayer design parameters were varied, such as the initial strain (from 20 to 60%) and the bilayer thickness (from 373 to 93 µm). The model matched experimental data on the inner and outer radii nicely, especially when a high friction condition was implemented in the model, particularly reducing the error below 2% for the outer diameter while varying the strain. The model outperformed the current literature, where self-penetration is not excluded, and a single value of the radius of spontaneous rolling is used to describe multiple rolls. A complex 3D bioinspired hierarchical elastomeric microstructure made of seven spirals arranged like a hexagon inscribed in a circumference, similar to typical biological architectures (e.g., myofibrils within a sarcolemma), was also developed. In this case also, the model effectively predicted the spirals’ features (error smaller than 18%), opening interesting application scenarios in the modeling and fabrication of bioinspired materials.     

Crohn’s Disease,Host–Microbiota Interactions,and Immunonutrition: Dietary Strategies Targeting Gut Microbiome as Novel Therapeutic Approaches

Crohn’s disease (CD) is a complex, disabling, idiopathic, progressive, and destructive disorder with an unknown etiology. The pathogenesis of CD is multifactorial and involves the interplay between host genetics, and environmental factors, resulting in an aberrant immune response leading to intestinal inflammation. Due to the high morbidity and long-term management of CD, the development of non-pharmacological approaches to mitigate the severity of CD has recently attracted great attention. The gut microbiota has been recognized as an important player in the development of CD, and general alterations in the gut microbiome have been established in these patients. Thus, the gut microbiome has emerged as a pre-eminent target for potential new treatments in CD. Epidemiological and interventional studies have demonstrated that diet could impact the gut microbiome in terms of composition and functionality. However, how specific dietary strategies could modulate the gut microbiota composition and how this would impact host–microbe interactions in CD are still unclear. In this review, we discuss the most recent knowledge on host–microbe interactions and their involvement in CD pathogenesis and severity, and we highlight the most up-to-date information on gut microbiota modulation through nutritional strategies, focusing on the role of the microbiota in gut inflammation and immunity.