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A novel isobaric adiabatic compressed air energy storage (IA-CAES) system was proposed based on the volatile fluid in our previous work. At the same time, a large amount of waste heat should be employed, which may restrict its applications. Two modified A-CAES (configuration 1&2) without using waste heat are proposed in this work. The volatile fluid has two functions: driving the air out of storage vessels and evaporating in a heat exchanger to generate cooling energy. Carbon dioxide (CO2) is selected as the volatile fluid due to its environmentally properties and high saturation pressure at ambient temperature. The thermodynamic analysis is evaluated by using a steady-state mathematical model and thermodynamic laws. The calculation results show the configuration 1 has the same round trip efficiency (RTE) as conventional A-CAES, while 36.59% additional cooling energy can be obtained, and the total exergy efficiency (TEE) improves by more than 2%. Moreover, configuration 1 saves nearly 35% of the total volume of the air storage unit. Compared with conventional A-CAES, configuration 2 has obtained 42.71% additional cooling energy, the RTE and TEE improve 0.14% and 2.83%, respectively. Meanwhile, parametric analyses are also carried out to evaluate the effects of several critical parameters on the system performance of two modified A-CAES systems.

The MYB- basic helix-loop-helix (bHLH)-WD40 complexes regulating anthocyanin and proanthocyanidin (PA) biosynthesis in plants are not fully understood. Here Medicago truncatula bHLH MtTT8 was characterized as a central component of these ternary complexes that control anthocyanin and PA biosynthesis. Mttt8 mutant seeds have a transparent testa phenotype with reduced PAs and anthocyanins. MtTT8 restores PA and anthocyanin productions in Arabidopsis tt8 mutant. Ectopic expression of MtTT8 restores anthocyanins and PAs in mttt8 plant and hairy roots and further enhances both productions in wild-type hairy roots. Transcriptomic analyses and metabolite profiling of mttt8 mutant seeds and M. truncatula hairy roots (mttt8 mutant, mttt8 mutant complemented with MtTT8, or MtTT8 overexpression lines) indicate that MtTT8 regulates a subset of genes involved in PA and anthocyanin biosynthesis. MtTT8 is genetically regulated by MtLAP1, MtPAR and MtWD40-1. Combinations of MtPAR, MtLAP1, MtTT8 and MtWD40-1 activate MtTT8 promoter in yeast assay. MtTT8 interacts with these transcription factors to form regulatory complexes. MtTT8, MtWD40-1 and an MYB factor, MtPAR or MtLAP1, interacted and activated promoters of anthocyanidin reductase and anthocyanidin synthase to regulate PA and anthocyanin biosynthesis, respectively. Our results provide new insights into the complex regulation of PA and anthocyanin biosynthesis in M. truncatula.

Adiabatic compressed air energy storage (A-CAES) has been accepted as a promising and emerging storage technology due to its excellent power and storage capacities. Traditional A-CAES systems often store the compressed air in nature storage vessels, such as underground hard-rock and salt caverns, thus depending heavily on geographical conditions. This problem can be mitigated by introducing artificial vessels. However, the artificial vessels could be very costly since their construction requires a large number of steels, accounting for a large proportion of the capital investment of A-CAES. For a given output, the capital investment and the performance of A-CAES system are depend on the operation pressure of each component (compression train, expansion train, thermal energy storage tanks and artificial vessels). In this work, both thermodynamic and economic performance of A-CAES have been investigated through a multi-objective evolutionary optimization, and the four operation pressures from different components are considered. Experimental results show that the Round trip efficiency (RTE) is improved by 4.41%, the system total investment cost (TIC) is decreased by 4.55% and the Profit is increased by 8.91% compared with conventional A-CAES. Hence, the designed A-CAES is more efficient and more economic than the conventional one.

A thorough survey of energy efficient techniques for linear algebra operations.A complete list of valuable research efforts.A deeply review of all aspects of feasible solutions.Detailed discussion and comprehensive comparison.Thought-provoking directions of future research are provided. Extreme scale supercomputers available before the end of this decade are expected to have 100 million to 1billion computing cores. The power and energy efficiency issue has become one of the primary concerns of extreme scale high performance scientific computing. This paper surveys the research on saving power and energy for numerical linear algebra algorithms in high performance scientific computing on supercomputers around the world. We first stress the significance of numerical linear algebra algorithms in high performance scientific computing nowadays, followed by a background introduction on widely used numerical linear algebra algorithms and software libraries and benchmarks. We summarize commonly deployed power management techniques for reducing power and energy consumption in high performance computing systems by presenting power and energy models and two fundamental types of power management techniques: static and dynamic. Further, we review the research on saving power and energy for high performance numerical linear algebra algorithms from four aspects: profiling, trading off performance, static saving, and dynamic saving, and summarize state-of-the-art techniques for achieving power and energy efficiency in each category individually. Finally, we discuss potential directions of future work and summarize the paper.

The demands of improving energy efficiency for high performance scientific applications arise crucially nowadays. Software-controlled hardware solutions directed by Dynamic Voltage and Frequency Scaling (DVFS) have shown their effectiveness extensively. Although DVFS is beneficial to green computing, introducing DVFS itself can incur non-negligible overhead, if there exist a large number of frequency switches issued by DVFS. In this paper, we propose a strategy to achieve the optimal energy savings for distributed matrix multiplication via algorithmically trading more computation and communication at a time adaptively with user-specified memory costs for less DVFS switches, which saves 7.5% more energy on average than a classic strategy. Moreover, we leverage a high performance communication scheme for fully exploiting network bandwidth via pipeline broadcast. Overall, the integrated approach achieves substantial energy savings (up to 51.4%) and performance gain (28.6% on average) compared to ScaLAPACK pdgemm() on a cluster with an Ethernet switch, and outperforms ScaLAPACK and DPLASMA pdgemm() respectively by 33.3% and 32.7% on average on a cluster with an Infiniband switch.

Soft errors are one-time events that corrupt the state of a computing system but not its overall functionality. Soft errors normally do not interrupt the execution of the affected program, but the affected computation results cannot be trusted any more. A well known technique to correct soft errors in matrix–matrix multiplication is algorithm-based fault tolerance (ABFT). While ABFT achieves much better efficiency than triple modular redundancy (TMR) – a traditional general technique to correct soft errors, both ABFT and TMR detect errors off-line after the computation is finished. This paper extends the traditional ABFT technique from off-line to on-line so that soft errors in matrix–matrix multiplication can be detected in the middle of the computation during the program execution and higher efficiency can be achieved by correcting the corrupted computations in a timely manner. Experimental results demonstrate that the proposed technique can correct one error every ten seconds with negligible (i.e. less than 1%) performance penalty over the ATLAS dgemm() .

Polydimethylsiloxane (PDMS)/organic montmorillonite (OMMT)/polyether polyethersulfone (PES) composite membranes were prepared by in situ anionic polymerization using 3-aminopropyltrimethoxy (AMEO) as a crosslinker. The morphology, thermal properties and interaction of PDMSAMEO/OMMT membranes were characterized by using a scanning electron microscope (SEM), Fourier transform infrared spectroscopy (FT-IR) and a thermal gravimetric analysis (TGA). The swelling behavior of membranes without PES support was investigated. The effects of AMEO content and OMMT content on separation properties were also studied. The results show that the addition of appropriate OMMT could improve the hydrophobic and pro-acetic acid properties of a membrane. The acetic acid selectivity of membranes was best when AMEO content was 0.1. The membrane, loading 2 wt.% OMMT, exhibited the highest separation factor for a feed concentration of 10 wt.% at 313 K. An increase in feed concentration resulted in the enhancement of flux and selectivity. When the feed concentration was above 20 wt.%, the separation factor of a filled membrane was larger than for an unfilled membrane. With increases in the feed temperature, the permeation flux of membranes increased. However, the acetic acid selectivity of an unfilled membrane decreased but for filled membranes initially increased before decreasing.

Silica-filled polydimethylsiloxane (PDMS) composite membranes are prepared on a polytetrafluoroethylene support structure. The structure and the performance of the membranes are characterized by scanning electron microscope, Fourier transform infrared spectroscopy, X-ray diffraction, and thermogravimetry. The pervaporation process for acetic/water separation is performed within the PDMS membranes. The vulcanization temperature was found to have a great influence on the separation performance of the membrane. The addition of silica can significantly improve the pervaporation flux and enhance the thermal stability of the membrane. With an increase in the feed temperature, selectivity decreases and permeation flux increases. Performed with a pure PDMS membrane vulcanized at 30°C, the separation factor at first will increase, then decrease when the feed flow rate was increased from 14 to 38 L · h−1. The maximum separation factor is achieved when the feed flow rate is 26 L · h−1. POLYM. ENG. SCI., 2011. © 2011 Society of Plastics Engineers

Active control of a flexible cantilever plate with multiple time delays is investigated using the discrete optimal control method. A controller with multiple time delays is presented. In this controller, time delay effect is incorporated in the mathematical model of the dynamic system throughout the control design and no approximations and assumptions are made in the controller derivation, so the system stability is easily guaranteed. Furthermore, this controller is available for both small time delays and large time delays. The feasibility and efficiency of the proposed controller are verified through numerical simulations in the end of this paper.

This work presented a system to encourage children and adolescents with autism and cerebral palsy (CP) to improve their abilities of self-care, mobility and sociality. A study was conducted with 51 children with autism and 36 children with CP using the Game System for Rehabilitation with Kinect at intervals of one month. The scope of this study was aimed to evaluate the effects of Game System for Rehabilitation in terms of self-care, mobility and social function of children and adolescents with autism and CP. Pediatric Evaluation of Disability Inventory (PEDI) was used to determine the functional abilities of self-care, mobility and sociability. Data obtained allowed us to conclude that the positive effects of the Game System for Rehabilitation on the func- tional abilities of self-care, mobility and social function with disabilities were significant. The Game System for Rehabilitation applied for children and adolescents with autism and CP was effective for the targeted population. And it gives a new light for children with autism and CP to continue their rehabilitation successfully.

As the size and complexity of high performance computers increase, more soft errors will be encountered during computations. Algorithm-Based Fault Tolerance (ABFT) has been proved to be a highly efficient technique to detect soft errors in dense linear algebra operations including matrix multiplication, Cholesky and LU factorization. While ABFT can also be applied to a iterative sparse linear algebra algorithm via applying it to every individual matrix-vector multiplication in the algorithm, it often introduces considerable overhead. In this paper, we propose novel extensions to ABFT to not only reduce the overhead but also protect computations that can not be protected by existing ABFT. Instead of maintaining checksums in every individual matrix-vector multiplication, we modified the algorithms so that checksums established at the beginning of the algorithms can be maintained at every iterations throughout the algorithms. Because soft errors in most iterative sparse linear algebra algorithms will propagate from one iteration to another, we do not have to verify the correctness of the checksums at each iteration to detect errors. By reducing the frequency of verification, the fault tolerance overhead can be greatly reduced. Experimental results demonstrate that, when used with local diskless checkpoints together, our approach introduces much less overhead than the existing ABFT techniques.

Polydimethylsiloxane (PDMS) membranes with different silica content were prepared without support. The characterization and performance of the membranes were investigated by scanning electron microscope (SEM), thermogravimetry analysis (TGA), contact angle meter and swelling experiment. The pervaporation process was investigated with acetic acid/water mixture. And the process of mass transfer was analysed depending on the solution-diffusion model. The addition of silica could greatly improve the pervaporation flux and enhance the thermal stability of membrane. With an increase in feed temperature, selectivity decreased and permeation flux increased for the unfilled PDMS membrane. However, the separation factor of silica loading of 10 wt. % membranes, exhibited a maximum at 50 °C, and it was higher than unfilled membrane when feed temperature was above 40 °C. With the enhancement of acetic acid concentration, flux and separation factor increased. And the unfilled membrane and the silica filled membrane were prior permeation membranes for water when the downstream pressure of unfilled membrane and silica filled membrane was over 1000 Pa and 1500 Pa respectively.

Soft errors are one-time events that corrupt the state of a computing system but not its overall functionality. Soft errors normally do not interrupt the execution of the affected program, but the affected computation results can not be trusted any more. A well known technique to correct soft errors in matrix-matrix multiplication is algorithm-based fault tolerance (ABFT). While ABFT achieves much better efficiency than triple modular redundancy (TMR) - a traditional general technique to correct soft errors, both ABFT and TMR detect errors off-line after the computation is finished. This paper extends the traditional ABFT technique from off-line to on-line so that soft errors in matrix-matrix multiplication can be detect in the middle of the computation during the program execution and higher efficiency can be achieved by correcting the corrupted computations in a timely manner. Experimental results demonstrate that the proposed technique can correct one error every ten seconds with negligible (i.e., less than 1%) performance penalty over the ATLAS dgemm().