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Abstract2‐methyl‐5,6,7,8‐tetrahydro‐2H‐chromen‐4(3H)‐one (called 6‐oxo) is presented as a new AI‐1 quorum sensing inhibitor for Vibrio harveyi. The development of a chemical process to afford traceable materials for new biological assays demands the development of analytical methods to ensure their purity and quality. This work describes the use of quantitative 1H nuclear magnetic resonance (NMR) spectroscopy (qNMR) to assess the purity of a sample of 6‐oxo (99.88%) and a sample of its major process impurity (E)‐1‐(2‐hydroxycyclohex‐2‐en‐1‐yl)but‐2‐en‐1‐one (called HCB; 98.28%). To explore the scope of the use of qNMR to quantify the amount of low‐content components in samples related to the chemical process for 6‐oxo synthesis, this work also determined the amount of 6‐oxo in two HCB samples: (a) the high‐purity HCB sample described above and (b) a crude HCB sample collected during the chemical process. Despite the complexity of the crude sample, the amount of 6‐oxo was readily assessed and could help to estimate the extent to which 6‐oxo was already formed during the HCB synthesis. This information can help the understanding of how the process parameters can be modified to improve the performance of the whole process, by controlling the reaction mechanisms working at each step of this chemical process. In this context, our results reinforce qNMR as a complementary analytical tool for the quantification of the main component found in a sample, contributing to the standardization of reference materials and thus allowing the development of analytical methods for process control and traceability of the samples used for biological assays.

Due to the power constraints of the current semiconductor technology, energy consumption has become an important factor for computer systems. Reducing energy consumption can mean more battery life for mobile devices or reduction of financial costs for data centers. One of the energy bottlenecks of computer systems is the information traffic between the processor and memory hierarchy. In this paper we evaluate the energy reduction of our new spill code minimization technique called color flipping in comparison with classical approaches. We implemented the Briggs' register allocator in the LLVM compiler framework with and without color flipping strategy and we ran some SPEC CPU 2006 benchmarks in a modified gem5 simulator for Cortex-A9. Then the energy consumption was estimated using the McPAT framework. Experimental results showed that our technique can reduce about 1% of the energy consumption of integer programs.