A Model of Green Acceptance and Intentions to Use Bike-Sharing: YouBike Users in Taiwan

With the emphasis on sustainability in transportation, bike-sharing systems are gaining popularity. This paper investigates the attitudes of users of a bike-sharing system with the aim of identifying their priorities, thus allowing local governments to focus their efforts most effectively on enhancing users’ intentions to use such systems. The relationships among green perceived usefulness (the extent to which individuals believe that a bike-sharing system will improve the environmental performance of some part of their life within a specific context), user attitude and perceived ease of use with green intentions, and the mediation effect of user attitude towards bike-sharing are explored. The focus of the study is on how to enhance green intentions via perceived usefulness, perceived ease of use and user attitude of the green technology acceptance model (green TAM) (Davis 1989). The two-step approach of structural equation modeling was applied to analyze the empirical results, which indicated that green perceived usefulness and user attitude have positive influences on the green intentions of 262 users and 262 non-users from ten sampled bike-sharing sites around the central administrative districts of Taipei. However, user attitude has the highest mediation effect on green intentions, and perceived ease of use does not have a significant effect on intentions for either users or non-users. Therefore, governmental institutions can strive to improve the attitudes of bike-sharing users and non-users, their green perceived usefulness, and perceived ease of use to strengthen their intentions to use this mode of sustainable transportation.     

One-step implementation of a Toffoli gate of separated superconducting qubits via quantum Zeno dynamics

Based on the quantum Zeno dynamics, a scheme is presented to implement a Toffoli gate of three separated superconducting qubits (SQs) by one step. Three separated SQs are connected by two resonators. The scheme is insensitive to the resonator decay because the Zeno subspace does not include the state of the resonators being excited. Numerical simulations indicate that the scheme is robust to the fluctuation of the parameters and the Toffoli gate can be implemented with high fidelity.     

Efficient electrochemomechanical energy conversion in nanochannels grafted with polyelectrolyte layers with pH-dependent charge density

Nanochannels, functionalized by grafting with a layer of charged polyelectrolyte (PE), have been employed for a large number of applications such as flow control, ion sensing, ion manipulation, current rectification and nanoionic diode fabrication. Recently, we established that such PE-grafted nanochannels, often denoted as “soft” nanochannels, can be employed for highly efficient, streaming-current-induced electrochemomechanical energy conversion in the presence of a background pressure-driven transport. In this paper, we extend our calculation for the practically realizable situation when the PE layer demonstrates a pH-dependent charge density. Consideration of such pH dependence necessitates consideration of hydrogen and hydroxyl ions in the electric double layer charge distribution, cubic distribution of the monomer profile, and a PE layer-induced drag force that accounts for this given distribution of the monomer profile. Our results express a hitherto unknown dependence of the streaming electric field (or the streaming potential) and the efficiency of the resultant energy conversion on parameters such as the pH of the surrounding electrolyte and the \(\hbox {pK}_{\mathrm{a}}\) of the ionizable group that ionizes to produce the PE charge—we demonstrate that increase in the pH and the PE layer thickness and decrease in the \(\hbox {pK}_{\mathrm{a}}\) and the ion concentration substantially enhance the energy conversion efficiency.     

Characterizing and optimizing TPC-C workloads on large-scale systems using SSD arrays在大规模系统上优化 TPC-C 评测程序

Transaction processing performance council benchmark C (TPC-C) is the de facto standard for evaluating the performance of high-end computers running on-line transaction processing applications. Differing from other standard benchmarks, the transaction processing performance council only defines specifications for the TPC-C benchmark, but does not provide any standard implementation for end-users. Due to the complexity of the TPC-C workload, it is a challenging task to obtain optimal performance for TPC-C evaluation on a large-scale high-end computer. In this paper, we designed and implemented a large-scale TPC-C evaluation system based on the latest TPC-C specification using solid-state drive (SSD) storage devices. By analyzing the characteristics of the TPC-C workload, we propose a series of system-level optimization methods to improve the TPC-C performance. First, we propose an approach based on SmallFile table space to organize the test data in a round-robin method on all of the disk array partitions; this can make full use of the underlying disk arrays. Second, we propose using a NOOP-based disk scheduling algorithm to reduce the utilization rate of processors and improve the average input/output service time. Third, to improve the system translation lookaside buffer hit rate and reduce the processor overhead, we take advantage of the huge page technique to manage a large amount of memory resources. Lastly, we propose a locality-aware interrupt mapping strategy based on the asymmetry characteristic of non-uniform memory access systems to improve the system performance. Using these optimization methods, we performed the TPC-C test on two large-scale high-end computers using SSD arrays. The experimental results show that our methods can effectively improve the TPC-C performance. For example, the performance of the TPC-C test on an Intel Westmere server reached 1.018 million transactions per minute.