We consider the issue of securing dark pools/markets in the financial services sector. These markets currently are executed via trusted third parties, leading to potential fraud being able to be conducted by the market operators. We present a potential solution to this problem by using Multi-Party Computation to enable a trusted third party to be emulated in software. Our experiments show that whilst the standard market clearing mechanism of Continuous Double Auction in lit markets is not currently viable when executed using MPC, a popular mechanism for evaluating dark markets, namely the volume matching methodology, is viable. We present experimental validation of this conclusion by presenting the expected throughputs for such markets in two popular MPC paradigms; namely the two party dishonest majority setting and the honest majority three party setting.

While standard evolutionary algorithms employ a static, absolute fitness metric, co-evolutionary algorithms assess individuals by their performance relative to populations of opponents that are themselves evolving. Although this arrangement offers the possibility of avoiding long-standing difficulties such as premature convergence, it suffers from its own unique problems, cycling, over-focusing and disengagement. Here, we introduce a novel technique for dealing with the third and least explored of these problems. Inspired by studies of natural host-parasite systems, we show that disengagement can be avoided by selecting for individuals that exhibit reduced levels of “virulence”, rather than maximum ability to defeat coevolutionary adversaries. Experiments in both simple and complex domains are used to explain how this counterintuitive approach may be used to improve the success of coevolutionary algorithms.

We previously reported excessive apoptosis and high levels of tumor necrosis factor-alpha (TNF-alpha) in the bone marrows of patients with myelodysplastic syndromes (MDS), using histochemical techniques. The present studies provide further circumstantial evidence for the involvement of TNF-alpha in apoptotic death of the marrow cells in MDS. Using our newly developed in situ double-labeling technique that sequentially employs DNA polymerase (DNA Pol) followed by terminal deoxynucleotidyl transferase (TdT) to label cells undergoing apoptosis, we have characterized DNA fragmentation patterns during spontaneous apoptosis in MDS bone marrow and in HL60 cells treated with TNF-alpha or etoposide (VP16). Clear DNA laddering detected by gel electrophoresis in MDS samples confirmed the unique length of apoptotic DNA fragments (180-200 bp). Surprisingly, however, phenotypically heterogeneous population of MDS cells as well as the homogenous population of HL60 cells showed three distinct labeling patterns after double labeling--only DNA-Pol reaction, only TdT reaction, and a combined DNA Pol + TdT reaction, albeit in different cohorts of cells. Each labeling pattern was found at all morphological stages of apoptosis. MDS mononuclear cells, during spontaneous apoptosis in 4 hr cultures, showed highest increase in double-labeled cells (DNA Pol + TdT reaction). Interestingly, this was paralleled by TNF-alpha-induced apoptosis in HL60 cells. In contrast, VP16 treatment of HL60 cells led to increased apoptosis in cells showing only TdT reaction. The double-labeling technique was applied to normal bone marrow and peripheral blood mononuclear cells after treatment with known endonucleases that specifically cause 3' recessed (BamHI), 5' recessed (PstI), or blunt ended (DraI) double-stranded DNA breaks. It was found that the DNA-Pol reaction in MDS and HL60 cells corresponds to 3' recessed DNA fragments, the TdT reaction to 5' recessed and/or blunt ended fragments, and a combined "DNA Pol + TdT reaction" corresponds to a copresence of 3' recessed with 5' recessed and/or blunt ended fragments. Clearly, therefore, apoptotic DNA fragments, in spite of a unique length, may have differently staggered ends that could be cell (or tissue) specific and be selectively triggered by different inducers of apoptosis. The presence of TNF-alpha-inducible apoptotic DNA fragmentation pattern in MDS supports its involvement in these disorders and suggests that anti-TNF-alpha (or anticytokine) therapy may be of special benefit to MDS patients, where no definitive treatment is yet available.

In recent years, recommender systems have been employed in domains like e-commerce, tourism, and multimedia streaming, where personalising users’ experience based on their interactions is a fundamental aspect to consider. Recent recommender system developments have also focused on well-being, yet existing solutions have been entirely designed considering one single well-being aspect in isolation, such as a healthy diet or an active lifestyle. This research introduces EvoRecSys, a novel recommendation framework that proposes evolutionary algorithms as the main recommendation engine, thereby modelling the problem of generating personalised well-being recommendations as a multi-objective optimisation problem. EvoRecSys captures the interrelation between multiple aspects of well-being by constructing configurable recommendations in the form of bundled items with dynamic properties. The preferences and a predefined well-being goal by the user are jointly considered. By instantiating the framework into an implemented model, we illustrate the use of a genetic algorithm as the recommendation engine. Finally, this implementation has been deployed as a Web application in order to conduct a users’ study.