To make phenotypic characters of organisms widely useful for computerized biology research, biocurators manually convert character descriptions to a structured format, for example the Entity-Quality (EQ) format. The manual approach is time consuming and affected by inter-curator variations. In this paper we report a software application, CharaParser+EQ, to our knowledge the first software that produces EQ statements from textual character descriptions. We report a recent experiment that evaluates the performance of the software against three experienced biocurators. While the software is still far from being able to compete with biocurators on this highly intellectual task, the results show (1) CharaParser+EQ's performance (precision and recall) is greatly improved compared to a previous version, (2) the completeness of the ontologies used in the process has significant impact both on the software's EQ generation performance and on the agreement among curators, and (3) unlimited access to external knowledge (published papers, books) by curators has no significant impact on inter-curator agreements. A detailed error analysis that compares machine and curator generated EQs is included.

a b s t r a c tThis paper is concerned with short-term (up to 24 h) operational planning in combined heat and power plants for district energy applications. In such applications, heat and power demands fluctuate on an hourly basis due to changing weather conditions, time-of-day factors and consumer requirements. Plant energy efficiency is highly dependent on ambient temperature and operating load since equipment efficiencies are nonlinear functions of these parameters. In operational planning strategies, nonlinear equipment characteristics are seldom taken into account, resulting in plants being operated at sub-par efficiencies. In order to operate plants at highest possible efficiencies, scheduling strategies which take into account nonlinear equipment characteristics need to be developed. For such strategies, a mixed 0-1 nonlinear programming formulation is proposed. The problem is nonconvex and hence global optimality conditions are unknown. Classical techniques like branch-and-bound may not produce integer feasible solutions, may cut off the global optima and have an exponential increase in CPU time for a linear increase in planning horizon size. As an alternative, a solution method through genetic algorithms is proposed in which genetic search is applied only on 0-1 variables and gradient search is applied on continuous variables. The proposed method is a nonlinear extension of the one originally developed by Sakawa et al. [Sakawa M, Kato K, Ushiro S. Operational planning of district heating and cooling plants through genetic algorithms for mixed 0-1 linear programming. Eur J Operat Res 2002;137(3):677-87].Numerical experiments show the proposed genetic algorithm method is more consistent in finding integer feasible solutions, finds solutions with lower optimality gaps and has reasonable CPU time as compared to branch-and-bound. From an application perspective, the proposed scheduling strategy results in 5-11% increase in plant energy efficiency.

We present WiscKey, a persistent LSM-tree-based key-value store with a performance-oriented data layout that separates keys from values to minimize I/O amplification. The design of WiscKey is highly SSD optimized, leveraging both the sequential and random performance characteristics of the device. We demonstrate the advantages of WiscKey with both microbenchmarks and YCSB workloads. Microbenchmark results show that WiscKey is 2.5× to 111× faster than LevelDB for loading a database (with significantly better tail latencies) and 1.6× to 14× faster for random lookups. WiscKey is faster than both LevelDB and RocksDB in all six YCSB workloads.

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This paper describes a traveling wave model for describing the lightning stroke by the Haar wavelet method (HWM) is proposed. Numerical example is included and illustrated for applicability and validity of the proposed method. The fundamental idea of Haar wavelet method is to convert the differential equations into a group of algebraic equations that involves a finite number of variables. The power of the manageable method is confirmed. The results show that the proposed way is quite reasonable when compared to exact solution. Moreover the use of Haar wavelets is found to be accurate, simple, fast, flexible, convenient, small computation costs and computationally attractive.