PAC-learnability of probabilistic deterministic finite state automata in terms of variation distance

We consider the problem of PAC-learning distributions over strings, represented by probabilistic deterministic finite automata (PDFAs). PDFAs are a probabilistic model for the generation of strings of symbols, that have been used in the context of speech and handwriting recognition, and bioinformatics. Recent work on learning PDFAs from random examples has used the KL-divergence as the error measure; here we use the variation distance. We build on recent work by Clark and Thollard, and show that the use of the variation distance allows simplifications to be made to the algorithms, and also a strengthening of the results; in particular that using the variation distance, we obtain polynomial sample size bounds that are independent of the expected length of strings.     

The murine Tcl1 oncogene: embryonic and lymphoid cell expression

In human leukemias and lymphomas nonrandom chromosomal rearrangements cause changes in cell growth and/or survival in such a way as to promote malignancy. The detailed study of the biochemical and genetic pathways altered in human cancer requires the identification or development of models to allow the study and manipulation of cancer gene function. Recently, the breakpoint gene TCL1, involved in chromosome translocations observed mostly in mature T-cell proliferations and chronic lymphocytic leukemias (CLL), was isolated and characterized, and showed to be part of a new gene family of proteins involved in these tumors. The murine Tcl1 gene, is similar in sequence to the murine and human MTCP1 gene also involved in T cell leukemias. The murine Tcl1 gene was shown to reside on mouse chromosome 12 in a region syntenic to human chromosome 14. Furthermore, we show that the murine Tcl1 gene is expressed early in mouse embryonic development and demonstrates expression in fetal hematopoietic organs as well as in immature T and B cells. Characterization of the murine Tcl1 gene will help in developing a mouse model of CLL and would provide the best opportunity to study and decipher the role of TCL1 in malignant transformation.     

Using Automated Negotiation for Grid Services

The popularity of grid services has widened their application to numerous domains and increased the utilization of computational resources. In order to create more incentives for the resources owners to lease their resources and prevent users from wasting the resources, the introduction of a market-oriented grid is inevitable. However, the issues for the negotiation between service provider and consumer over the supply and demand of resources can be complex, with highly interdependent issues. In this research, a simulated automated negotiation mechanism including a co-evolutionary mechanism and a modified game theory approach is proposed, to assist them in reaching an agreement over the conflicting issues. In the proposed architecture, the co-evolution process is able to reduce the multiple dimensional search space into a two-dimension search space and identify the appropriate negotiation strategies for the negotiating agents to form a payoff matrix which can be used for the game theory related stage of their interaction. The multiple stage negotiation process is introduced to improve the negotiation result. In this paper, an application which requires a large amount of computational resources to process the data generated from mobile devises is used to demonstrate that the proposed system is able to resolve the conflicts and obtain a valid solution.     

The lipid composition of selected tissues from a Mediterranean monk seal,Monachus monachus

The lipid composition of blubber, brain, muscle and heart from a Mediterranean monk sealMonachus monachus (an endangered species) were examined to allow comparisons with more common species of seals. Only neutral lipids (mainly triacylglycerols) were detectable in the blubber lipids, whereas polar lipids predominated in the heart and in the brain. Neutral and polar lipids comprised almost equal proportions in both liver and muscle. Choline glycerophospholipids (CGP) were the major polar lipids, followed by ethanolamine glycerophospholipids (EGP) in the liver, heart and muscle. Cerebrosides accounted for 28.8% of the brain lipids. All lipid classes of the liver contained high levels (31–47%) of polyunsaturated fatty acids (PUFA), with the exception of phosphatidylserine. The total proportion of n−6 PUFA exceeded that of n−3 PUFA in all lipid classes of the liver, due mainly to the high levels of 20∶4n−6. The highest level of 20∶4n−6 occurred in phosphatidylinositol, where it comprised 32.4% of the total fatty acids. The CGP and EGP of the brain contained lower levels of PUFA than those of the liver, muscle and heart. Alkenyl ethers accounted for 35.8% of the total long-chain moieties in brain EGP. The fatty acid composition of blubber triacylglycerols differed from those of the lipid classes from other tissues in that it had a very low ratio of n−6 to n−3 PUFA (0.3) as a result of a lower content of 20∶4n−6.     

Rainbow smelt population responses to species invasions and change in environmental condition

Invasive species can cause major disruptions in native food webs, yet the impact of species introductions and whether they will become invasive appears to be context-dependent. Rainbow smelt and alewife co-exist as invasive species in the Laurentian Great Lakes and as native species on the Atlantic coast of North America, but in Lake Champlain rainbow smelt is the dominant native forage fish and alewife are invasive. Alewife became abundant by 2007, providing an opportunity to explore the dynamics of these two species in a system where only one is invasive. We used data from a 28-year forage fish survey to compare demographics of rainbow smelt populations in three basins of Lake Champlain with different volumes, nutrient levels, and predator abundances. Rainbow smelt catch-per-unit-effort (CPUE) remained constant in the large, deep Main Lake before and after alewife invaded, but decreased in the two smaller basins. Declines were primarily a result of increased age-0 and age-1 mortality. Predation by top piscivores, system productivity, and competition for resources alone could not explain the patterns in CPUE across the basins. The mechanisms that allow alewife and rainbow smelt to co-exist could be related to system volume and oxythermal habitat availability, and may explain why the two species do not negatively affect each other in the Great Lakes. Summer hypoxia in the smaller basins could force individuals into smaller habitat volumes with higher densities of competitors and cannibalistic adult rainbow smelt. Habitat availability may mediate the impact of invasive alewife on native rainbow smelt.     

Biomarkers for Cancer Cachexia: A Mini Review

Cancer cachexia is a common condition in many cancer patients, particularly those with advanced disease. Cancer cachexia patients are generally less tolerant to chemotherapies and radiotherapies, largely limiting their treatment options. While the search for treatments of this condition are ongoing, standards for the efficacy of treatments have yet to be developed. Current diagnostic criteria for cancer cachexia are primarily based on loss of body mass and muscle function. However, these criteria are rather limiting, and in time, when weight loss is noticeable, it may be too late for treatment. Consequently, biomarkers for cancer cachexia would be valuable adjuncts to current diagnostic criteria, and for assessing potential treatments. Using high throughput methods such as “omics approaches”, a plethora of potential biomarkers have been identified. This article reviews and summarizes current studies of biomarkers for cancer cachexia.