Automated Reasoning and Presentation Support for Formalizing Mathematics in Mizar

This paper presents a combination of several automated reasoning and proof presentation tools with the Mizar system for formalization of mathematics. The combination forms an online service called MizAR, similar to the SystemOnTPTP service for first-order automated reasoning. The main differences to SystemOnTPTP are the use of the Mizar language that is oriented towards human mathematicians (rather than the pure first-order logic used in SystemOnTPTP), and setting the service in the context of the large Mizar Mathematical Library of previous theorems,definitions, and proofs (rather than the isolated problems that are solved in SystemOnTPTP). These differences poses new challenges and new opportunities for automated reasoning and for proof presentation tools. This paper describes the overall structure of MizAR, and presents the automated reasoning systems and proof presentation tools that are combined to make MizAR a useful mathematical service.Comment: To appear in 10th International Conference on. Artificial Intelligence and Symbolic Computation AISC 201

Evaluating general purpose automated theorem proving systems

AbstractA key concern of ATP research is the development of more powerful systems, capable of solving more difficult problems within the same resource limits. In order to build more powerful systems, it is important to understand which systems, and hence which techniques, work well for what types of problems. This paper deals with the empirical evaluation of general purpose ATP systems, to determine which systems work well for what types of problems. This requires also dealing with the issues of assigning ATP problems into classes that are reasonably homogeneous with respect to the ATP systems that (attempt to) solve the problems, and assigning ratings to problems based on their difficulty

Parallel computing for brain simulation

[Abstract] Background: The human brain is the most complex system in the known universe, it is therefore one of the greatest mysteries. It provides human beings with extraordinary abilities. However, until now it has not been understood yet how and why most of these abilities are produced. Aims: For decades, researchers have been trying to make computers reproduce these abilities, focusing on both understanding the nervous system and, on processing data in a more efficient way than before. Their aim is to make computers process information similarly to the brain. Important technological developments and vast multidisciplinary projects have allowed creating the first simulation with a number of neurons similar to that of a human brain. Conclusion: This paper presents an up-to-date review about the main research projects that are trying to simulate and/or emulate the human brain. They employ different types of computational models using parallel computing: digital models, analog models and hybrid models. This review includes the current applications of these works, as well as future trends. It is focused on various works that look for advanced progress in Neuroscience and still others which seek new discoveries in Computer Science (neuromorphic hardware, machine learning techniques). Their most outstanding characteristics are summarized and the latest advances and future plans are presented. In addition, this review points out the importance of considering not only neurons: Computational models of the brain should also include glial cells, given the proven importance of astrocytes in information processing.Galicia. Consellería de Cultura, Educación e Ordenación Universitaria; GRC2014/049Galicia. Consellería de Cultura, Educación e Ordenación Universitaria; R2014/039Instituto de Salud Carlos III; PI13/0028

Experimental evolution of Paracoccus denitrificans in anoxic chemostats

Natural microbial communities play a central role in ecosystems and global cycles of elements. The microbial community compositions, functions as well as interactions between species and the environment have been studied with increasing effort. However, it is challenging to understand which parameters determine for the success of individual species to survive in a specific habitat. The often highly diverse microbial communities are continuously subjected to environmental stress such as biotic and abiotic fluctuations that cannot be completely tracked. To investigate the influence of different parameters on the ability of microorganisms to adapt to the environment, simple microbial communities, often single species are cultivated in the laboratory under strictly controlled conditions with reduced complexity. Such long-term experiments provide insight into the association between genetic and phenotypic alterations that evolve over hundreds or even thousands of generations. The availability of nutrients often affects microbial growth. This thesis describes the experimental evolution of Paracoccus denitrificans Pd1222, a model denitrifying soil bacterium, to study the adaptation on acetate or nitrate limitation. Initially, nutrient limitation for the anaerobic growth of P. denitrificans was addressed with focus on trace elements (Chapter 2). New trace element solutions were designed based on previous reports and tested to exclude growth limitation or inhibition by these nutrients during long-term cultivation. Improved generation times of 4.4 hours were achieved with a chelated trace element solution and lower concentrations than frequently used media. Chapter 3 describes the adaptive responses of P. denitrificans to acetate and nitrate limitation during experimental evolution in chemostats. In the course of at least 800 generations of P. denitrificans under denitrifying conditions the metabolic conversions of substrates were monitored. For deeper insights into different adaptive mechanisms of P. denitrificans under both conditions we investigated the transcriptomes and genome variations. Throughout the experiment the different treatments led to significantly different substrate conversion rates and transcriptomic profiles. Specifically, in nitrate limited cultures genes of the citric acid cycle and the nitrogen metabolism showed higher transcriptional activities than in acetate limited cultures. In the latter the transcription of genes encoding regulators and transporters was more pronounced. Additionally, more changes in transcriptional activities and in metabolism were observed over time than under nitrate limitation. Most notably, denitrification became more efficient resulting in the depletion of nitrite that accumulated in the culture during the first 500 generations. Although numerous mutations were detected in DNA obtained from this culture, they could not be related to the observed phenotypic changes. In all cultures the types and numbers of genetic variations did not considerably differ. The study indicated that P. denitrificans had a stronger potential to adapt to acetate limitation than to nitrate limitation and underlines the capacity of this bacterium to improve denitrification even in absence of environmental fluctuations. The possible explanation that phenotypic changes may have been independent of genetic variations is discussed in Chapter 4. The relevance of the insights gained in this study for natural, in particular denitrifying communities is presented and future studies towards the understanding of natural microbial community functions are suggested

The role of the gut microbiota in the subsistence of antibiotic resistance

"Antibiotic resistance is one of the major contemporary threats to global health. Studies on evolutionary biology, molecular biology and genetics have revealed that many phenomena contribute for the subsistence of resistant bacteria. The environment has been shown to be a key factor, capable of altering fitness costs and the epistasis patterns between resistance determinants. Still, few studies have ventured to assess the costs of antibiotic resistance in natural environments, and such studies are centered on pathogens. It is now known that commensal bacteria can act as reservoirs of resistance, and that resistant commensals can evolve to express pathogenicity and share resistance genes with pathogens. Here, we explore how selection acts on resistant, commensal E. coli in the mouse gut. (...)

Computational Approaches: Drug Discovery and Design in Medicinal Chemistry and Bioinformatics

This book is a collection of original research articles in the field of computer-aided drug design. It reports the use of current and validated computational approaches applied to drug discovery as well as the development of new computational tools to identify new and more potent drugs

Biosensors

A biosensor is defined as a detecting device that combines a transducer with a biologically sensitive and selective component. When a specific target molecule interacts with the biological component, a signal is produced, at transducer level, proportional to the concentration of the substance. Therefore biosensors can measure compounds present in the environment, chemical processes, food and human body at low cost if compared with traditional analytical techniques. This book covers a wide range of aspects and issues related to biosensor technology, bringing together researchers from 11 different countries. The book consists of 16 chapters written by 53 authors. The first four chapters describe several aspects of nanotechnology applied to biosensors. The subsequent section, including three chapters, is devoted to biosensor applications in the fields of drug discovery, diagnostics and bacteria detection. The principles behind optical biosensors and some of their application are discussed in chapters from 8 to 11. The last five chapters treat of microelectronics, interfacing circuits, signal transmission, biotelemetry and algorithms applied to biosensing