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The packed-memory array (PMA) is a data structure that maintains a dynamic set of N elements in sorted order in a Θ(N)-sized array. The idea is to intersperse Θ(N) empty spaces or gaps among the elements so that only a small number of elements need to be shifted around on an insert or delete. Because the elements are stored physically in sorted order in memory or on disk, the PMA can be used to support extremely efficient range queries. Specifically, the cost to scan L consecutive elements is O(1 + L/B) memory transfers.This paper gives the first adaptive packed-memory array (APMA), which automatically adjusts to the input pattern. Like the original PMA, any pattern of updates costs only O(log 2 N) amortized element moves and O(1 + (log 2 N)/B) amortized memory transfers per update. However, the APMA performs even better on many common input distributions achieving only O(log N) amortized element moves and O(1 + (log N)/B) amortized memory transfers. The paper analyzes sequential inserts, where the insertions are to the front of the APMA, hammer inserts, where the insertions "hammer" on one part of the APMA, random inserts, where the insertions are after random elements in the APMA, and bulk inserts, where for constant α ∈ [0, 1], N α elements are inserted after random elements in the APMA. The paper then gives simulation results that are consistent with the asymptotic bounds. For sequential insertions of roughly 1.4 million elements, the APMA has four times fewer element moves per insertion than the traditional PMA and running times that are more than seven times faster.

The packed-memory array (PMA) is a data structure that maintains a dynamic set of N elements in sorted order in a Θ(N)-sized array. The idea is to intersperse Θ(N) empty spaces or gaps among the elements so that only a small number of elements need to be shifted around on an insert or delete. Because the elements are stored physically in sorted order in memory or on disk, the PMA can be used to support extremely efficient range queries. Specifically, the cost to scan L consecutive elements is O(1 + L/B) memory transfers.This paper gives the first adaptive packed-memory array (APMA), which automatically adjusts to the input pattern. Like the traditional PMA, any pattern of updates costs only O(log 2 N) amortized element moves and O(1 + (log 2 N)/B) amortized memory transfers per update. However, the APMA performs even better on many common input distributions achieving only O(logN) amortized element moves and O(1 + (logN)/B) amortized memory transfers. The paper analyzes sequential inserts, where the insertions are to the front of the APMA, hammer inserts, where the insertions "hammer" on one part of the APMA, random inserts, where the insertions are after random elements in the APMA, and bulk inserts, where for constant α ∈ [0, 1], N α elements are inserted after random elements in the APMA. The paper then gives simulation results that are consistent with the asymptotic bounds. For sequential insertions of roughly 1.4 million elements, the APMA has four times fewer element moves per insertion than the traditional PMA and running times that are more than seven times faster.

Recovery of both latent heat and condensate from boiler flue gas is significant for improving boiler efficiency and water conservation. The condensation experiments are carried out to investigate the simultaneous heat and mass transfer across the nanoporous ceramic membranes (NPCMs) which are treated to be hydrophilic and hydrophobic surfaces using the semicontinuous supercritical reactions. The effects of typical parameters including coolant flow rate, vapor/nitrogen gas mixture temperature, water vapor volume fraction and transmembrane pressure on heat and mass transfer performance are studied. The experimental results show that the hydrophilic NPCM exhibits higher performances of condensation heat transfer and condensate recovery. However, the hydrophobic modification results in remarkable degradation of heat and condensate recovery from the mixture. Molecular dynamics simulations are conducted to establish a hydrophilic/hydrophobic nanopore/water liquid system, and the infiltration characteristics of the single hydrophilic/hydrophobic nanopore is revealed.

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We study the problem of sorting binary sequences and permutations by length-weighted reversals. We consider a wide class of cost functions, namely f ( ) = α for all α 0, where is the length of the reversed subsequence. We present tight or nearly tight upper and lower bounds on the worst-case cost of sorting by reversals. Then we develop algorithms to approximate the optimal cost to sort a given input. Furthermore, we give polynomial-time algorithms to determine the optimal reversal sequence for a restricted but interesting class of sequences and cost functions. Our results have direct application in computational biology to the field of comparative genomics.