Microflotation performance for algal separation

The performance of microflotation, dispersed air flotation with microbubble clouds with bubble size about 50 μm, for algae separation using fluidic oscillation for microbubble generation is investigated. This fluidic oscillator converts continuous air supply into oscillatory flow with a regular frequency to generate bubbles of the scale of the exit pore. Bubble characterization results showed that average bubble size generated under oscillatory air flow state was 86 μm, approximately twice the size of the diffuser pore size of 38 μm. In contrast, continuous air flow at the same rate through the same diffusers yielded an average bubble size of 1,059 μm, 28 times larger than the pore size. Following microbubble generation, the separation of algal cells under fluidic oscillator generated microbubbles was investigated by varying metallic coagulant types, concentration and pH. Best performances were recorded at the highest coagulant dose (150 mg/L) applied under acidic conditions (pH 5). Amongst the three metallic coagulants studied, ferric chloride yielded the overall best result of 99.2% under the optimum conditions followed closely by ferric sulfate (98.1%) and aluminum sulfate with 95.2%. This compares well with conventional dissolved air flotation (DAF) benchmarks, but has a highly turbulent flow, whereas microflotation is laminar with several orders of magnitude lower energy density.     

Promising high monetary rewards for future task performance increases intermediate task performance

In everyday life contexts and work settings, monetary rewards are often contingent on future performance. Based on research showing that the anticipation of rewards causes improved task performance through enhanced task preparation, the present study tested the hypothesis that the promise of monetary rewards for future performance would not only increase future performance, but also performance on an unrewarded intermediate task. Participants performed an auditory Simon task in which they responded to two consecutive tones. While participants could earn high vs. low monetary rewards for fast responses to every second tone, their responses to the first tone were not rewarded. Moreover, we compared performance under conditions in which reward information could prompt strategic performance adjustments (i.e., when reward information was presented for a relatively long duration) to conditions preventing strategic performance adjustments (i.e., when reward information was presented very briefly). Results showed that high (vs. low) rewards sped up both rewarded and intermediate, unrewarded responses, and the effect was independent of the duration of reward presentation. Moreover, long presentation led to a speed-accuracy trade-off for both rewarded and unrewarded tones, whereas short presentation sped up responses to rewarded and unrewarded tones without this trade-off. These results suggest that high rewards for future performance boost intermediate performance due to enhanced task preparation, and they do so regardless whether people respond to rewards in a strategic or non-strategic manner.     

EEG applications for sport and performance

One approach to understanding processes that underlie skilled performing has been to study electrical brain activity using electroencephalography (EEG). A notorious problem with EEG is that genuine cerebral data is often contaminated by artifacts of non-cerebral origin. Unfortunately, such artifacts tend to be exacerbated when the subject is in motion, meaning that obtaining reliable data during exercise is inherently problematic. These problems may explain the limited number of studies using EEG as a methodological tool in the sports sciences. This paper discusses how empirical studies have generally tackled the problem of movement artifact by adopting alternative paradigms which avoid recording during actual physical exertion. Moreover, the specific challenges that motion presents to obtaining reliable EEG data are discussed along with practical and computational techniques to confront these challenges. Finally, as EEG recording in sports is often underpinned by a desire to optimise performance, a brief review of EEG-biofeedback and peak performance studies is also presented. A knowledge of practical aspects of EEG recording along with the advent of new technology and increasingly sophisticated processing models offer a promising approach to minimising, if perhaps not entirely circumventing, the problem of obtaining reliable EEG data during motion.     

Swine performance model for summer conditions

The Missouri model was developed using swine performance data from three-way cross hogs fed a ration closely approximating National Research Council (1973) recommendations raised in confinement facilities at the Northeast Nebraska Experiment Station. The Missouri model was validated using independent data collected during the summers of 1977 and 1978 at the University of Missouri Swine Research Center. Weight gain predictions averaged 93 and 92% of measured gains and feed intake predictions were 112 and 107% of the measured feed consumption. These predictions were 45 and 61% better than those from the original model of Teter et al. (1973). To the extent that the Missouri and Nebraska swine data are representative of growing swine performance in typical commercial confinement facilities the Missouri model can be expected to predict average hog weight gain and feed consumption within 10% of actual performance in most well managed commercial confinement facilities during moderate and hot weather conditions. Weight gain and feed intake predictions can be expected to be accurate to within 15% for shorter term (2 week) predictions.The work described in this paper was performed while the principle author was at the University of Missouri, Columbia.     

New racing equation for championship performance

A separate investigation of swimming endurance has led to a family of expressions relating maximal human locomotor activity to time and/or distance having such wide application to medicine, physiology, and sports as to merit independent publication. Specifically, variations of a single racing equation with one variable parameter suffice to predict record times, speeds, energy, power, and endurance accurately for cycling, running, and swimming, provided only that performance be categorized as steady-state, aerobic effort.     

Nanopillar array structures for enhancing biosensing performance

Fabrication of metallic nanopillar array structures and their application as electrodes in electrochemical-based biosensors are discussed in this report. Vertically standing nanopillar array structures were fabricated using an electrodeposition technique and their electrochemical characteristics were evaluated. For possible use in biosensing applications, these standing nanopillars should have sufficient mechanical stability to sustain the capillary forces caused by the nanopillar-liquid interactions in aqueous environment and should provide increased signal response in an electrochemical process. Our results showed that the developed nanopillar arrays were mechanically stable in aqueous environments and the nanostructured electrodes exhibited increased electrochemical response compared with flat electrodes.     

Malleable applications for scalable high performance computing

Iterative applications are known to run as slow as their slowest computational component. This paper introduces malleability, a new dynamic reconfiguration strategy to overcome this limitation. Malleability is the ability to dynamically change the data size and number of computational entities in an application. Malleability can be used by middleware to autonomously reconfigure an application in response to dynamic changes in resource availability in an architecture-aware manner, allowing applications to optimize the use of multiple processors and diverse memory hierarchies in heterogeneous environments. The modular Internet Operating System (IOS) was extended to reconfigure applications autonomously using malleability. Two different iterative applications were made malleable. The first is used in astronomical modeling, and representative of maximum-likelihood applications was made malleable in the SALSA programming language. The second models the diffusion of heat over a two dimensional object, and is representative of applications such as partial differential equations and some types of distributed simulations. Versions of the heat application were made malleable both in SALSA and MPI. Algorithms for concurrent data redistribution are given for each type of application. Results show that using malleability for reconfiguration is 10 to 100 times faster on the tested environments. The algorithms are also shown to be highly scalable with respect to the quantity of data involved. While previous work has shown the utility of dynamically reconfigurable applications using only computational component migration, malleability is shown to provide up to a 15% speedup over component migration alone on a dynamic cluster environment. This work is part of an ongoing research effort to enable applications to be highly reconfigurable and autonomously modifiable by middleware in order to efficiently utilize distributed environments. Grid computing environments are becoming increasingly heterogeneous and dynamic, placing new demands on applications’ adaptive behavior. This work shows that malleability is a key aspect in enabling effective dynamic reconfiguration of iterative applications in these environments.

Thermal performance of quartz capillaries for vitrification

In this paper we report the thermal behavior of a new approach for vitrification. Thermal performance of traditional open pulled straws is compared with a new technique based on the combined use of quartz capillaries with slush nitrogen. This new method of vitrification achieved ultrafast cooling rates of 250,000 °C/min. As a result, a much lower concentration of cryoprotectant was needed to reach vitrification. In fact, a cryoprotectant solution typically used in oocyte slow freezing protocols was shown to remain transparent after cooling to liquid nitrogen temperatures indicating apparent “vitrification”. This approach offers a new and very promising technique for vitrification of cells using low levels of cryoprotectants.     

Learning-aided predictor integration for system performance prediction

The integration of multiple predictors promises higher prediction accuracy than the accuracy that can be obtained with a single predictor. The challenge is how to select the best predictor at any given moment. Traditionally, multiple predictors are run in parallel and the one that generates the best result is selected for prediction. In this paper, we propose a novel approach for predictor integration based on the learning of historical predictions. Compared with the traditional approach, it does not require running all the predictors simultaneously. Instead, it uses classification algorithms such as k-Nearest Neighbor (k-NN) and Bayesian classification and dimension reduction technique such as Principal Component Analysis (PCA) to forecast the best predictor for the workload under study based on the learning of historical predictions. Then only the forecasted best predictor is run for prediction. Our experimental results show that it achieved 20.18% higher best predictor forecasting accuracy than the cumulative MSE based predictor selection approach used in the popular Network Weather Service system. In addition, it outperformed the observed most accurate single predictor in the pool for 44.23% of the performance traces.

Biphasic mini-reactor for characterization of biocatalyst performance

Biphasic reaction media are extending the scope of technical biocatalysis. Thorough investigation of the factors affecting catalyst performance under these conditions is of key importance for the successful implementation of catalytic processes. Here, we present a reactor setup suitable for comprehensive systematic characterization and optimization of biocatalyzed reactions in biphasic systems with distinct phases. It is distinguished by small volumes allowing reproducible experimentation with minimum amounts of solvent and catalyst. The interfacial area is kept constant and independent stirring of both phases is allowed in order to minimize superimposing effects. Evaporation of low-volatile organic solvents is prevented by use of airtight construction. The broad applicability of this mini-reactor is demonstrated with regard to determination of mass transfer, enzyme productivity, and enzyme stability in both batch and continuous mode.     

Directed evolution strategies for improved enzymatic performance

The engineering of enzymes with altered activity, specificity and stability, using directed evolution techniques that mimic evolution on a laboratory timescale, is now well established. However, the general acceptance of these methods as a route to new biocatalysts for organic synthesis requires further improvement of the methods for both ease-of-use and also for obtaining more significant changes in enzyme properties than is currently possible. Recent advances in library design, and methods of random mutagenesis, combined with new screening and selection tools, continue to push forward the potential of directed evolution. For example, protein engineers are now beginning to apply the vast body of knowledge and understanding of protein structure and function, to the design of focussed directed evolution libraries, with striking results compared to the previously favoured random mutagenesis and recombination of entire genes. Significant progress in computational design techniques which mimic the experimental process of library screening is also now enabling searches of much greater regions of sequence-space for those catalytic reactions that are broadly understood and, therefore, possible to model.     

Genomic selection of purebreds for crossbred performance

Background

One of the main limitations of many livestock breeding programs is that selection is in pure breeds housed in high-health environments but the aim is to improve crossbred performance under field conditions. Genomic selection (GS) using high-density genotyping could be used to address this. However in crossbred populations, 1) effects of SNPs may be breed specific, and 2) linkage disequilibrium may not be restricted to markers that are tightly linked to the QTL. In this study we apply GS to select for commercial crossbred performance and compare a model with breed-specific effects of SNP alleles (BSAM) to a model where SNP effects are assumed the same across breeds (ASGM). The impact of breed relatedness (generations since separation), size of the population used for training, and marker density were evaluated. Trait phenotype was controlled by 30 QTL and had a heritability of 0.30 for crossbred individuals. A Bayesian method (Bayes-B) was used to estimate the SNP effects in the crossbred training population and the accuracy of resulting GS breeding values for commercial crossbred performance was validated in the purebred population.

Results

Results demonstrate that crossbred data can be used to evaluate purebreds for commercial crossbred performance. Accuracies based on crossbred data were generally not much lower than accuracies based on pure breed data and almost identical when the breeds crossed were closely related breeds. The accuracy of both models (ASGM and BSAM) increased with marker density and size of the training data. Accuracies of both models also tended to decrease with increasing distance between breeds. However the effect of marker density, training data size and distance between breeds differed between the two models. BSAM only performed better than AGSM when the number of markers was small (500), the number of records used for training was large (4000), and when breeds were distantly related or unrelated.

Conclusion

In conclusion, GS can be conducted in crossbred population and models that fit breed-specific effects of SNP alleles may not be necessary, especially with high marker density. This opens great opportunities for genetic improvement of purebreds for performance of their crossbred descendents in the field, without the need to track pedigrees through the system.     

Encapsulation performance of layer-by-layer microcapsules for proteins

This study reports on the encapsulation efficiency of proteins in dextran sulfate/poly-L-arginine-based microcapsules, fabricated via layer-by-layer assembly (LbL). For this purpose, radiolabeled proteins are entrapped in CaCO(3) microparticles, followed by LbL coating of the CaCO(3) cores and subsequent dissolving of the CaCO(3) using EDTA. To allow to improve protein encapsulation in LbL microcapsules, we studied all steps in the preparation of the microcapsules where loss of protein load might occur. The encapsulation efficiency of proteins in LbL microcapsules turns out to be strongly dependent on both the charge and molecular weight of the protein as well as on the number of polyelectrolyte bilayers the microcapsules consist of.     

Engineering bifunctional laccase-xylanase chimeras for improved catalytic performance

Two bifunctional enzymes exhibiting combined xylanase and laccase activities were designed, constructed, and characterized by biochemical and biophysical methods. The Bacillus subtilis cotA and xynA genes were used as templates for gene fusion, and the xynA coding sequence was inserted into a surface loop of the cotA. A second chimera was built replacing the wild-type xynA gene by a thermostable variant (xynAG3) previously obtained by in vitro molecular evolution. Kinetic measurements demonstrated that the pH and temperature optima of the catalytic domains in the chimeras were altered by less than 0.5 pH units and 5 °C, respectively, when compared with the parental enzymes. In contrast, the catalytic efficiency (k(cat)/K(m)) of the laccase activity in both chimeras was 2-fold higher than for the parental laccase. Molecular dynamics simulations of the CotA-XynA chimera indicated that the two domains are in close contact, which was confirmed by the low resolution structure obtained by small angle x-ray scattering. The simulation also indicates that the formation of the inter-domain interface causes the dislocation of the loop comprising residues Leu-558 to Lys-573 in the laccase domain, resulting in a more accessible active site and exposing the type I Cu(2+) ion to the solvent. These structural changes are consistent with the results from UV-visible electronic and EPR spectroscopy experiments of the type I copper between the native and chimeric enzymes and are likely to contribute to the observed increase in catalytic turnover number.     

Autonomic power and performance management for computing systems

With the increased complexity of platforms, the growing demand of applications and data centers’ servers sprawl, power consumption is reaching unsustainable limits. The need to improved power management is becoming essential for many reasons including reduced power consumption & cooling, improved density, reliability & compliance with environmental standards. This paper presents a theoretical framework and methodology for autonomic power and performance management in e-business data centers. We optimize for power and performance (performance-per-watt) at each level of the hierarchy while maintaining scalability. We adopt mathematically-rigorous optimization approach to minimize power while meeting performance constraints. Our experimental results show around 72% savings in power while maintaining performance as compared to static power management techniques and 69.8% additional savings with both global and local optimizations.

Guidelines for evaluating performance of oyster habitat restoration

Restoration of degraded ecosystems is an important societal goal, yet inadequate monitoring and the absence of clear performance metrics are common criticisms of many habitat restoration projects. Funding limitations can prevent adequate monitoring, but we suggest that the lack of accepted metrics to address the diversity of restoration objectives also presents a serious challenge to the monitoring of restoration projects. A working group with experience in designing and monitoring oyster reef projects was used to develop standardized monitoring metrics, units, and performance criteria that would allow for comparison among restoration sites and projects of various construction types. A set of four universal metrics (reef areal dimensions, reef height, oyster density, and oyster size–frequency distribution) and a set of three universal environmental variables (water temperature, salinity, and dissolved oxygen) are recommended to be monitored for all oyster habitat restoration projects regardless of their goal(s). In addition, restoration goal‐based metrics specific to four commonly cited ecosystem service‐based restoration goals are recommended, along with an optional set of seven supplemental ancillary metrics that could provide information useful to the interpretation of prerestoration and postrestoration monitoring data. Widespread adoption of a common set of metrics with standardized techniques and units to assess well‐defined goals not only allows practitioners to gauge the performance of their own projects but also allows for comparison among projects, which is both essential to the advancement of the field of oyster restoration and can provide new knowledge about the structure and ecological function of oyster reef ecosystems.