Nanoscale plasma chemistry enables fast, size-selective nanotube nucleation

The possibility of fast, narrow-size/chirality nucleation of thin single-walled carbon nanotubes (SWCNTs) at low, device-tolerant process temperatures in a plasma-enhanced chemical vapor deposition (CVD) is demonstrated using multiphase, multiscale numerical experiments. These effects are due to the unique nanoscale reactive plasma chemistry (NRPC) on the surfaces and within Au catalyst nanoparticles. The computed three-dimensional process parameter maps link the nanotube incubation times and the relative differences between the incubation times of SWCNTs of different sizes/chiralities to the main plasma- and precursor gas-specific parameters and explain recent experimental observations. It is shown that the unique NRPC leads not only to much faster nucleation of thin nanotubes at much lower process temperatures, but also to better selectivity between the incubation times of SWCNTs with different sizes and chiralities, compared to thermal CVD. These results are used to propose a time-programmed kinetic approach based on fast-responding plasmas which control the size-selective, narrow-chirality nucleation and growth of thin SWCNTs. This approach is generic and can be used for other nanostructure and materials systems.

Enhanced fast handover triggering mechanism for fast proxy mobile IPv6

Handover performance is critical to support real-time traffic applications in wireless network communications. The longer the handover delay is, the longer an Mobile Node (MN) is prevented from sending and receiving any data packet. In real-time network communication applications, such as VoIP and video-conference, a long handover delay is often unacceptable. In order to achieve better handover performance, Fast Proxy Mobile IPv6 (FPMIPv6) has been standardised as an improvement to the original Proxy Mobile IPv6 (PMIPv6) in the Internet Engineering Task Force (IETF). The FPMIPv6 adopts a link layer triggering mechanism to perform two modes of operation: predictive and reactive modes. Using the link layer triggering, the handover performance of the FPMIPv6 can be improved in the predictive mode. However, an unsuccessful predictive handover operation will lead to activation of a reactive handover. In the reactive mode, MNs still experience long handover delays and a large amount of packet loss, which significantly degrade the handover performance of the FPMIPv6. Addressing this problem, this thesis presents an Enhanced Triggering Mechanism (ETM) in the FPMIPv6 to form an enhanced FPMIPv6 (eFPMIPv6). The ETM reduces the most time consuming processes in the reactive handover: the failed Handover Initiate (HO-Initiate) delay and bidirectional tunnel establishment delay. Consequently, the overall handover performance of the FPMIPv6 is enhanced in the eFPMIPv6. To show the advantages of the proposed eFPMIPv6, a theoretical analysis is carried out to mathematically model the performance of PMIPv6, FPMIPv6 and eFPMIPv6. Extensive case studies are conducted to validate the effectiveness of the presented eFPMIPv6 mechanism. They are carried out under various scenarios with changes in network link delay, traffic load, number of hops and MN moving velocity. The case studies show that the proposed mechanism ETM reduces the reactive handover delay, and the presented eFPMIPv6 outperforms the PMIPv6 and FPMIPv6 in terms of the overall handover performance.

A fast track SAP R/3 implementation at Guilbert Niceday

This paper examines the approach of Guilbert, a European stationery company, which has chosen a fast track strategy towards implementation of enterprise resource planning.

Solar Assisted Fast Pyrolysis: A Novel Approach of Renewable Energy Production

Biofuel produced by fast pyrolysis from biomass is a promising candidate. The heart of the system is a reactor which is directly or indirectly heated to approximately 500°C by exhaust gases from a combustor that burns pyrolysis gas and some of the by-product char. In most of the cases, external biomass heater is used as heating source of the system while internal electrical heating is recently implemented as source of reactor heating. However, this heating system causes biomass or other conventional forms of fuel consumption to produce renewable energy and contributes to environmental pollution. In order to overcome these, the feasibility of incorporating solar energy with fast pyrolysis has been investigated. The main advantages of solar reactor heating include renewable source of energy, comparatively simpler devices, and no environmental pollution. A lab scale pyrolysis setup has been examined along with 1.2 m diameter parabolic reflector concentrator that provides hot exhaust gas up to 162°C. The study shows that about 32.4% carbon dioxide (CO2) emissions and almost one-third portion of fuel cost are reduced by incorporating solar heating system. Successful implementation of this proposed solar assisted pyrolysis would open a prospective window of renewable energy.

The suitability of DEAE-Cl active groups on customized poly(GMA-co-EDMA) continuous stationary phase for fast enzyme-free isolation of plasmid DNA

The creation of a commercially viable and a large-scale purification process for plasmid DNA (pDNA) production requires a whole-systems continuous or semi-continuous purification strategy employing optimised stationary adsorption phase(s) without the use of expensive and toxic chemicals, avian/bovine-derived enzymes and several built-in unit processes, thus affecting overall plasmid recovery, processing time and economics. Continuous stationary phases are known to offer fast separation due to their large pore diameter making large molecule pDNA easily accessible with limited mass transfer resistance even at high flow rates. A monolithic stationary sorbent was synthesised via free radical liquid porogenic polymerisation of ethylene glycol dimethacrylate (EDMA) and glycidyl methacrylate (GMA) with surface and pore characteristics tailored specifically for plasmid binding, retention and elution. The polymer was functionalised with an amine active group for anion-exchange purification of pDNA from cleared lysate obtained from E. coli DH5α-pUC19 pellets in RNase/protease-free process. Characterization of the resin showed a unique porous material with 70% of the pores sizes above 300 nm. The final product isolated from anion-exchange purification in only 5 min was pure and homogenous supercoiled pDNA with no gDNA, RNA and protein contamination as confirmed with DNA electrophoresis, restriction analysis and SDS page. The resin showed a maximum binding capacity of 15.2 mg/mL and this capacity persisted after several applications of the resin. This technique is cGMP compatible and commercially viable for rapid isolation of pDNA.

Moving forwards with the aim of going backwards fast : high performance rowing as a learning environment

Background and Purpose: - This paper focuses on the learning culture within the high performance levels of rowing. In doing so, we explore the case of an individual’s learning as he moves across athletic, coaching and administrative functions. This exploration draws on a cultural learning framework and complementary theorisings related to reflexivity. Method - This study makes use of an intellectually, morally and collaboratively challenging approach whereby one member of the research team was also the sole participant of this study. The participant’s careers as a high performance athlete, coach and administrator, coupled with his experience in conducting empirical research presented a rare opportunity to engage in collaborative research (involving degrees of insider and outsider status for each of the research team). We acknowledge that others have looked to combine roles of coach / athlete / administrator with that of researcher however few (if any) have attempted to combine them all in one project. Moreover, coupled with the approach to reflexivity adopted in this study and the authorship contributions we consider this scholarly direction uncommon. Data were comprised of recorded research conversations, a subsequently constructed learning narrative, reflections on the narrative, a stimulated reflective piece from the participant, and a final (re)construction of the participant’s story. Accordingly, data were integrated through an iterative process of thematic analysis. Results - The cultural (i.e., the ways things get done) and structural (e.g., the rules and regulations) properties of high performance rowing were found to shape both the opportunities to be present (e.g., secure a place in the crew) and to learn (e.g., learn the skills required to perform at an Olympic level). However, the individual’s personal properties were brought to bear on re-shaping the constraints such that many limitations could be overcome. In keeping with the theory of learning cultures, the culture of rowing was found to position individuals (a coxswain in this case) differentially. In a similar manner, a range of structural features was found to be important in shaping the cultural and personal elements in performance contexts. For example, the ‘field of play’ was found to be important as a structural feature (i.e., inability of coach to communicate with athletes) in shaping the cultural and personal elements of learning in competition (e.g., positioning the coxswain as an in-boat coach and trusted crewmate). Finally, the cultural and structural elements in rowing appeared to be activated by the participant’s personal elements, most notably his orientation towards quality performance. Conclusion - The participant in this study was found to be driven by the project that he cares about most and at each turn he has bent his understanding of his sport back on itself to see if he can find opportunities to learn and subsequently explore ways to improve performance. The story here emphasises the importance of learner agency, and this is an aspect that has often been missing in recent theorising about learning. In this study, we find an agent using his ‘personal emergent powers to activate the resources in the culture and structure of his sport in an attempt to improve performance. We conclude from this account that this particular high performance rowing culture is one that provided support but nonetheless encouraged those involved, to ‘figure things out’ for themselves – be it as athletes, coaches and/or administrators.

A fast semi-implicit difference method for a nonlinear two-sided space-fractional diffusion equation with variable diffusivity coefficients

In this paper, we derive a new nonlinear two-sided space-fractional diffusion equation with variable coefficients from the fractional Fick’s law. A semi-implicit difference method (SIDM) for this equation is proposed. The stability and convergence of the SIDM are discussed. For the implementation, we develop a fast accurate iterative method for the SIDM by decomposing the dense coefficient matrix into a combination of Toeplitz-like matrices. This fast iterative method significantly reduces the storage requirement of O(n2)O(n2) and computational cost of O(n3)O(n3) down to n and O(nlogn)O(nlogn), where n is the number of grid points. The method retains the same accuracy as the underlying SIDM solved with Gaussian elimination. Finally, some numerical results are shown to verify the accuracy and efficiency of the new method.

Fast and accurate business process drift detection

Business processes are prone to continuous and unexpected changes. Process workers may start executing a process differently in order to adjust to changes in workload, season, guidelines or regulations for example. Early detection of business process changes based on their event logs – also known as business process drift detection – enables analysts to identify and act upon changes that may otherwise affect process performance. Previous methods for business process drift detection are based on an exploration of a potentially large feature space and in some cases they require users to manually identify the specific features that characterize the drift. Depending on the explored feature set, these methods may miss certain types of changes. This paper proposes a fully automated and statistically grounded method for detecting process drift. The core idea is to perform statistical tests over the distributions of runs observed in two consecutive time windows. By adaptively sizing the window, the method strikes a trade-off between classification accuracy and drift detection delay. A validation on synthetic and real-life logs shows that the method accurately detects typical change patterns and scales up to the extent it is applicable for online drift detection.

Fast unscented transformation-based transient stability margin estimation incorporating uncertainty of wind generation

Intermittent generation from wind farms leads to fluctuating power system operating conditions pushing the stability margin to its limits. The traditional way of determining the worst case generation dispatch for a system with several semi-scheduled wind generators yields a conservative solution. This paper proposes a fast estimation of the transient stability margin (TSM) incorporating the uncertainty of wind generation. First, the Kalman filter (KF) is used to provide linear estimation of system angle and then unscented transformation (UT) is used to estimate the distribution of the TSM. The proposed method is compared with the traditional Monte Carlo (MC) method and the effectiveness of the proposed approach is verified using Single Machine Infinite Bus (SMIB) and IEEE 14 generator Australian dynamic system. This method will aid grid operators to perform fast online calculations to estimate TSM distribution of a power system with high levels of intermittent wind generation.

Scalar connectivity measures from fast-marching tractography reveal heritability of white matter architecture

Recent advances in diffusion-weighted MRI (DWI) have enabled studies of complex white matter tissue architecture in vivo. To date, the underlying influence of genetic and environmental factors in determining central nervous system connectivity has not been widely studied. In this work, we introduce new scalar connectivity measures based on a computationally-efficient fast-marching algorithm for quantitative tractography. We then calculate connectivity maps for a DTI dataset from 92 healthy adult twins and decompose the genetic and environmental contributions to the variance in these metrics using structural equation models. By combining these techniques, we generate the first maps to directly examine genetic and environmental contributions to brain connectivity in humans. Our approach is capable of extracting statistically significant measures of genetic and environmental contributions to neural connectivity.