Hyperbranched polymers containing oxazoline monomers andsuccinic anhydride: applications in fast drying, low solvent coating formulations

tMelt-polycondensation of succinic acid anhydride with oxazoline-based diol monomers gave hyper-branched polymers with carboxylicacids terminal groups.1H NMR and quantitative13C NMRspectroscopy coupled with DEPT-13513C NMR experiment showed high degrees of branching (over 60%).Esterification of the acid end groups by addition of citronellol at 160◦C produced novel white spirit solubleresins which were characterized by Fourier transform-infrared (FTIR) spectroscopy, gel permeation chro-matography (GPC), differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA). Blendsof the new hyperbranched materials with commercial alkyd resins resulted in a dramatic, concentrationdependent drop in viscosity. Solvent-borne coatings were formulated containing the hyperbranchedpolymers. Dynamic mechanical analysis studies revealed that the air drying rates of the new coatingsystems were enhanced compared with identical formulations containing only commercial alkyd resins.

Fast three dimensional r-adaptive mesh redistribution

This paper describes a fast and reliable method for redistributing a computational mesh in three dimensions which can generate a complex three dimensional mesh without any problems due to mesh tangling. The method relies on a three dimensional implementation of the parabolic Monge–Ampère (PMA) technique, for finding an optimally transported mesh. The method for implementing PMA is described in detail and applied to both static and dynamic mesh redistribution problems, studying both the convergence and the computational cost of the algorithm. The algorithm is applied to a series of problems of increasing complexity. In particular very regular meshes are generated to resolve real meteorological features (derived from a weather forecasting model covering the UK area) in grids with over 2×107 degrees of freedom. The PMA method computes these grids in times commensurate with those required for operational weather forecasting.

Bit-index sort: a fast non-comparison integer sorting algorithm for permutations

This paper describes a fast integer sorting algorithm, herein referred as Bit-index sort, which is a non-comparison sorting algorithm for partial per-mutations, with linear complexity order in execution time. Bit-index sort uses a bit-array to classify input sequences of distinct integers, and exploits built-in bit functions in C compilers supported by machine hardware to retrieve the ordered output sequence. Results show that Bit-index sort outperforms in execution time to quicksort and counting sort algorithms. A parallel approach for Bit-index sort using two simultaneous threads is included, which obtains speedups up to 1.6.

Two fast radiative transfer methods to improve the temporal sampling of clouds in numerical weather prediction and climate models

The high computational cost of calculating the radiative heating rates in numerical weather prediction (NWP) and climate models requires that calculations are made infrequently, leading to poor sampling of the fast-changing cloud field and a poor representation of the feedback that would occur. This paper presents two related schemes for improving the temporal sampling of the cloud field. Firstly, the ‘split time-stepping’ scheme takes advantage of the independent nature of the monochromatic calculations of the ‘correlated-k’ method to split the calculation into gaseous absorption terms that are highly dependent on changes in cloud (the optically thin terms) and those that are not (optically thick). The small number of optically thin terms can then be calculated more often to capture changes in the grey absorption and scattering associated with cloud droplets and ice crystals. Secondly, the ‘incremental time-stepping’ scheme uses a simple radiative transfer calculation using only one or two monochromatic calculations representing the optically thin part of the atmospheric spectrum. These are found to be sufficient to represent the heating rate increments caused by changes in the cloud field, which can then be added to the last full calculation of the radiation code. We test these schemes in an operational forecast model configuration and find a significant improvement is achieved, for a small computational cost, over the current scheme employed at the Met Office. The ‘incremental time-stepping’ scheme is recommended for operational use, along with a new scheme to correct the surface fluxes for the change in solar zenith angle between radiation calculations.

Fast adaptive real-time classification for data streams with concept drift

An important application of Big Data Analytics is the real-time analysis of streaming data. Streaming data imposes unique challenges to data mining algorithms, such as concept drifts, the need to analyse the data on the fly due to unbounded data streams and scalable algorithms due to potentially high throughput of data. Real-time classification algorithms that are adaptive to concept drifts and fast exist, however, most approaches are not naturally parallel and are thus limited in their scalability. This paper presents work on the Micro-Cluster Nearest Neighbour (MC-NN) classifier. MC-NN is based on an adaptive statistical data summary based on Micro-Clusters. MC-NN is very fast and adaptive to concept drift whilst maintaining the parallel properties of the base KNN classifier. Also MC-NN is competitive compared with existing data stream classifiers in terms of accuracy and speed.

Contrasting fast precipitation responses to tropospheric and stratospheric ozone forcing

The precipitation response to radiative forcing (RF) can be decomposed into a fast precipitation response (FPR), which depends on the atmospheric component of RF, and a slow response, which depends on surface temperature change. We present the first detailed climate model study of the FPR due to tropospheric and stratospheric ozone changes. The FPR depends strongly on the altitude of ozone change. Increases below about 3 km cause a positive FPR; increases above cause a negative FPR. The FPR due to stratospheric ozone change is, per unit RF, about 3 times larger than that due to tropospheric ozone. As historical ozone trends in the troposphere and stratosphere are opposite in sign, so too are the FPRs. Simple climate model calculations of the time-dependent total (fast and slow) precipitation change, indicate that ozone's contribution to precipitation change in 2011, compared to 1765, could exceed 50% of that due to CO2 change.

Preconditioning 2D integer data for fast convex hull computations

In order to accelerate computing the convex hull on a set of n points, a heuristic procedure is often applied to reduce the number of points to a set of s points, s ≤ n, which also contains the same hull. We present an algorithm to precondition 2D data with integer coordinates bounded by a box of size p × q before building a 2D convex hull, with three distinct advantages. First, we prove that under the condition min(p, q) ≤ n the algorithm executes in time within O(n); second, no explicit sorting of data is required; and third, the reduced set of s points forms a simple polygonal chain and thus can be directly pipelined into an O(n) time convex hull algorithm. This paper empirically evaluates and quantifies the speed up gained by preconditioning a set of points by a method based on the proposed algorithm before using common convex hull algorithms to build the final hull. A speedup factor of at least four is consistently found from experiments on various datasets when the condition min(p, q) ≤ n holds; the smaller the ratio min(p, q)/n is in the dataset, the greater the speedup factor achieved.

Fast and slow precipitation responses to individual climate forcers: a PDRMIP multi-model study

Precipitation is expected to respond differently to various drivers of anthropogenic climate change. We present the first results from the Precipitation Driver and Response Model Intercomparison Project (PDRMIP), where nine global climate models have perturbed CO2, CH4, black carbon, sulfate, and solar insolation. We divide the resulting changes to global mean and regional precipitation into fast responses that scale with changes in atmospheric absorption and slow responses scaling with surface temperature change. While the overall features are broadly similar between models, we find significant regional intermodel variability, especially over land. Black carbon stands out as a component that may cause significant model diversity in predicted precipitation change. Processes linked to atmospheric absorption are less consistently modeled than those linked to top-of-atmosphere radiative forcing. We identify a number of land regions where the model ensemble consistently predicts that fast precipitation responses to climate perturbations dominate over the slow, temperature-driven responses.

Fast and slow responses of Southern Ocean sea surface temperature to SAM in coupled climate models

We investigate how sea surface temperatures (SSTs) around Antarctica respond to the Southern An- nular Mode (SAM) on multiple timescales. To that end we examine the relationship between SAM and SST within unperturbed preindustrial control simulations of coupled general circulation models (GCMs) included in the Climate Modeling Intercomparison Project phase 5 (CMIP5). We develop a technique to extract the re- sponse of the Southern Ocean SST (55◦S−70◦S) to a hypothetical step increase in the SAM index. We demonstrate that in many GCMs, the expected SST step re- sponse function is nonmonotonic in time. Following a shift to a positive SAM anomaly, an initial cooling regime can transition into surface warming around Antarctica. However, there are large differences across the CMIP5 ensemble. In some models the step response function never changes sign and cooling persists, while in other GCMs the SST anomaly crosses over from negative to positive values only three years after a step increase in the SAM. This intermodel diversity can be related to differences in the models’ climatological thermal ocean stratification in the region of seasonal sea ice around Antarctica. Exploiting this relationship, we use obser- vational data for the time-mean meridional and vertical temperature gradients to constrain the real Southern Ocean response to SAM on fast and slow timescales.

Design and analysis of a haptic device design for large and fast movements

Haptic devices tend to be kept small as it is easier to achieve a large change of stiffness with a low associated apparent mass. If large movements are required there is a usually a reduction in the quality of the haptic sensations which can be displayed. The typical measure of haptic device performance is impedance-width (z-width) but this does not account for actuator saturation, usable workspace or the ability to do rapid movements. This paper presents the analysis and evaluation of a haptic device design, utilizing a variant of redundant kinematics, sometimes referred to as a macro-micro configuration, intended to allow large and fast movements without loss of impedance-width. A brief mathematical analysis of the design constraints is given and a prototype system is described where the effects of different elements of the control scheme can be examined to better understand the potential benefits and trade-offs in the design. Finally, the performance of the system is evaluated using a Fitts’ Law test and found to compare favourably with similar evaluations of smaller workspace devices.

A fast adaptive tunable RBF network for nonstationary systems

This paper describes a novel on-line learning approach for radial basis function (RBF) neural network. Based on an RBF network with individually tunable nodes and a fixed small model size, the weight vector is adjusted using the multi-innovation recursive least square algorithm on-line. When the residual error of the RBF network becomes large despite of the weight adaptation, an insignificant node with little contribution to the overall system is replaced by a new node. Structural parameters of the new node are optimized by proposed fast algorithms in order to significantly improve the modeling performance. The proposed scheme describes a novel, flexible, and fast way for on-line system identification problems. Simulation results show that the proposed approach can significantly outperform existing ones for nonstationary systems in particular.

Effect of enzymatic pretreatment and increasing the organic loading rate of lipid-rich wastewater treated in a hybrid UASB reactor

This study aimed at evaluating the effect of increasing organic loading rates and of enzyme pretreatment on the stability and efficiency of a hybrid upflow anaerobic sludge blanket reactor (UASBh) treating dairy effluent. The UASBh was submitted to the following average organic loading rates (OLR) 0.98 Kg.m(-3).d(-1), 4.58 Kg.m(-3).d(-1), 8.89 Kg.m(-3).d(-1) and 15.73 Kg.m(-3).d(-1), and with the higher value, the reactor was fed with effluent with and without an enzymatic pretreatment to hydrolyze fats. The hydraulic detention time was 24 h, and the temperature was 30 +/- 2 degrees C. The reactor was equipped with a superior foam bed and showed good efficiency and stability until an OLR of 8.89 Kg.m(-3).d(-1). The foam bed was efficient for solid retention and residual volatile acid concentration consumption. The enzymatic pretreatment did not contribute to the process stability, propitiating loss in both biomass and system efficiency. Specific methanogenic activity tests indicated the presence of inhibition after the sludge had been submitted to the pretreated effluent It was concluded that continuous exposure to the hydrolysis products or to the enzyme caused a dramatic drop in the efficiency and stability of the process, and the single exposure of the biomass to this condition did not inhibit methane formation. (C) 2011 Elsevier B.V. All rights reserved.

Effect of agitation on the performance of an anaerobic sequencing batch biofilm reactor in the treatment of dairy effluents

Agitation rate is an important parameter in the operation of Anaerobic Sequencing Biofilm Batch Reactors (ASBBRs), and a proper agitation rate guarantees good mixing, improves mass transfer, and enhances the solubility of the particulate organic matter. Dairy effluents have a high amount of particulate organic matter, and their anaerobic digestion presents inhibitory intermediates (e. g., long-chain fatty acids). The importance of studying agitation in such batch systems is clear. The present study aimed to evaluate how agitation frequency influences the anaerobic treatment of dairy effluents. The ASBBR was fed with wastewater from milk pasteurisation process and cheese manufacture with no whey segregation. The organic matter concentration, measured as chemical oxygen demand (COD), was maintained at approximately 8,000 mg/L. The reactor was operated with four agitation frequencies: 500 rpm, 350 rpm, 200 rpm, and no agitation. In terms of COD removal efficiency, similar results were observed for 500 rpm and 350 rpm (around 90%) and for 200 rpm and no agitation (around 80%). Increasing the system`s agitation thus not only improved the global efficiency of organic matter removal but also influenced volatile acid production and consumption and clearly modified this balance in each experimental condition.

Fast magnetic reconnection and energetic particle acceleration

Our numerical simulations show that the reconnection of magnetic field becomes fast in the presence of weak turbulence in the way consistent with the Lazarian and Vishniac (1999) model of fast reconnection. We trace particles within our numerical simulations and show that the particles can be efficiently accelerated via the first order Fermi acceleration. We discuss the acceleration arising from reconnection as a possible origin of the anomalous cosmic rays measured by Voyagers. (C) 2010 Elsevier Ltd. All rights reserved.