Abstract
We analyzed the current status (as of the end of August 2008) of human mitochondrial genomes deposited in GenBank, amounting to 5140 complete or coding-region sequences, in order to present an overall picture of the diversity present in the mitochondrial DNA of the global human population. To perform this task, we developed mtDNA-GeneSyn, a computer tool that identifies and exhaustedly classifies the diversity present in large genetic data sets. The diversity observed in the 5140 human mitochondrial genomes was compared with all possible transitions and transversions from the standard human mitochondrial reference genome. This comparison showed that tRNA and rRNA secondary structures have a large effect in limiting the diversity of the human mitochondrial sequences, whereas for the protein-coding genes there is a bias toward less variation at the second codon positions. The analysis of the observed amino acid variations showed a tolerance of variations that convert between the amino acids V, 1, A, M, and T. This defines a group of amino acids with similar chemical properties that can interconvert by a single transition.

Abstract
The execution model on which most tabling engines are based allocates a choice point whenever a new tabled subgoal is called. This happens even when the call is deterministic. however, sortie of the information from the choice point; is never used when evaluating deterministic tabled calls with batched scheduling. Moreover, when a deterministic answer is found for a. deterministic tabled call, the call can be completed early and the corresponding choice point can be removed. Thus, if applying batched scheduling to a long deterministic computation the system may end up consuming memory and evaluating calls unnecessarily. In this paper, we propose a solution that, tries to reduce this memory and execution overhead to a minimum. Our experimental results show that;, for deterministic tabled calls and tabled answers with batched scheduling, it; is possible not. only to reduce the memory usage overhead, but also the running time of tire execution.

Abstract
A critical component in the implementation of an efficient tabling system is the design of the data structures and algorithms to access and manipulate tabled data. Arguably, the most successful data structure for tabling is tries. However, when used in applications that pose many queries and/or have a large number of answers, tabling call build arbitrarily many and/or very large tables, quickly filling Lip memory. In this paper, we propose a new design for the table space organization where all terms in tabled subgoal calls and tabled answers are represented only once in a common global trie instead of being spread over several different trie data structures. Our initial experiments using the YapTab tabling system show significant reductions oil memory usage without compromising running time.

Abstract
Resolution strategies based on tabling are considered to be particularly effective in Logic Programming. Unfortunately, when faced with applications that compute large and/or many answers, memory exhaustion is a potential problem. In such cases, table deletion is the most common approach to recover space. In this work, we propose a different approach, storing tables into a relational database. Subsequent calls to stored tables import answers from the database, rather than performing a complete re-computation. To validate this approach, we have extended the YapTab tabling system, providing engine support for exporting and importing tables to and from the MySQL RDBMS. Three different relational models for data storage and two recordset retrieval strategies are compared.

Abstract
Tabling is all implementation technique that overcomes some limitations of traditional Prolog systems in dealing with redundant sub-computations and recursion. The performance of tabled evaluation largely depends on the implementation of the table space. Arguably, the most successful data structure for tabling is tries. However, while tries are efficient for variant based tabled evaluation, they are limited ill their ability to recognize and represent repeated answers for different calls. In this paper, we propose a new design for the table space where tabled subgoal calls and/or answers are stored only once in a common global trie instead of being spread over several different tries. Our preliminary experiments using the YapTab tabling system show very promising reductions on memory usage.

Abstract
Prolog is the most; well-known and widely used logic programming language. A large number of Prolog applications maintains information by asserting and retracting clauses from the database. Such dynamic predicates raise a number of issues for Prolog implementations, such as what are the semantics of a procedure where clauses can be retracted and asserted while the procedure is being executed. One advantage of Logical Update semantics is that it allows indexing. In this paper, we discuss how one call implement just-in-time indexing with Logical Update semantics. Our algorithm is based on two ideas: stable structure and fragmented index trees. By stable structure one means that we define a structure for the indexing tree that not change, even as we assert and as we retract clauses. Second, by fragmented index tree we mean that the indexing tree will be built in such a way that the updates will be local to each fragment. The algorithm was implemented and results indicate significant speedups and reduction of memory usage in test applications.