866 resultados para Potatoes as feed.


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The conventional approach to setting a milling unit is essentially based on the desire to achieve a particular bagasse moisture content or fibre fill in each nip of the mill. This approach relies on the selection of the speed at which the mill will operate for the selected fibre rate. There is rarely any checking that the selected speed or the selected fibre fill is achieved and the same set of assumptions is generally carried over to use again in the next year. The conventional approach largely ignores the fact that the selection of mill settings actually determines the speed at which the mill will operate. Making an adjustment with the intent of changing the performance of the mill often also changes the speed of the mill as an unintended consequence. This paper presents an alternative approach to mill setting. The approach discussed makes use of mill feeding theory to define the relationship between fibre rate, mill speed and mill settings and uses that theory to provide an alternative means of determining the settings in some nips of the mill. Mill feeding theory shows that, as the feed work opening reduces, roll speed increases. The theory also shows that there is an optimal underfeed opening and Donnelly chute exit opening that will minimise roll speed and that the current South African guidelines appear to be well away from those optimal values.

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Nitrogen is an important nutrient that can impact the quality of aquatic environments when present in high concentration. Even though low concentration levels of ammonium-nitrogen have been observed in laboratory studies in bioretention basins, poor removal or even the production of nitrate-nitrogen within the filter is often recorded in such studies. Ten Perspex biofilter columns of 94 mm (internal diameter) were packed with a filter layer, transition layer and a gravel layer. While the filter layer was packed to a height of 800 mm, transition and gravel layers were packed to a composite height of 220 mm and operated with simulated stormwater in the laboratory. The filter layer contained 8% organic material by weight. A free board of 350 mm provided detention storage and head to facilitate infiltration. The columns were operated with different antecedent dry days (0 d to 21 d) and constant inflow concentration at a feed rate of 100 mL/min. Samples were collected from the outflow at different time intervals, between 2 min and 150 min from the start of outflow, and were tested for nitrate-nitrogen and total organic carbon. Washoff of organic carbon from the filter layer was observed to occur for 30 min of outflow. This indicated washoff of organic carbon from the filter itself. At the same time, a very low concentration of nitrate-nitrogen was recorded at the beginning of the outflow, indicating the effective removal of nitrate-nitrogen. We conclude that the removal of nitrate-nitrogen is insignificant during the wetting phase of a rainfall event and the process of denitrification is more pronounced during the drying phase of a rainfall event. Thus intermittent wetting and drying is crucial for the removal of nitrate-nitrogen in bioretention basins.

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Objectives Recent research has shown that machine learning techniques can accurately predict activity classes from accelerometer data in adolescents and adults. The purpose of this study is to develop and test machine learning models for predicting activity type in preschool-aged children. Design Participants completed 12 standardised activity trials (TV, reading, tablet game, quiet play, art, treasure hunt, cleaning up, active game, obstacle course, bicycle riding) over two laboratory visits. Methods Eleven children aged 3–6 years (mean age = 4.8 ± 0.87; 55% girls) completed the activity trials while wearing an ActiGraph GT3X+ accelerometer on the right hip. Activities were categorised into five activity classes: sedentary activities, light activities, moderate to vigorous activities, walking, and running. A standard feed-forward Artificial Neural Network and a Deep Learning Ensemble Network were trained on features in the accelerometer data used in previous investigations (10th, 25th, 50th, 75th and 90th percentiles and the lag-one autocorrelation). Results Overall recognition accuracy for the standard feed forward Artificial Neural Network was 69.7%. Recognition accuracy for sedentary activities, light activities and games, moderate-to-vigorous activities, walking, and running was 82%, 79%, 64%, 36% and 46%, respectively. In comparison, overall recognition accuracy for the Deep Learning Ensemble Network was 82.6%. For sedentary activities, light activities and games, moderate-to-vigorous activities, walking, and running recognition accuracy was 84%, 91%, 79%, 73% and 73%, respectively. Conclusions Ensemble machine learning approaches such as Deep Learning Ensemble Network can accurately predict activity type from accelerometer data in preschool children.

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In this chapter, we draw out the relevant themes from a range of critical scholarship from the small body of digital media and software studies work that has focused on the politics of Twitter data and the sociotechnical means by which access is regulated. We highlight in particular the contested relationships between social media research (in both academic and non-academic contexts) and the data wholesale, retail, and analytics industries that feed on them. In the second major section of the chapter we discuss in detail the pragmatic edge of these politics in terms of what kinds of scientific research is and is not possible in the current political economy of Twitter data access. Finally, at the end of the chapter we return to the much broader implications of these issues for the politics of knowledge, demonstrating how the apparently microscopic level of how the Twitter API mediates access to Twitter data actually inscribes and influences the macro level of the global political economy of science itself, through re-inscribing institutional and traditional disciplinary privilege We conclude with some speculations about future developments in data rights and data philanthropy that may at least mitigate some of these negative impacts.

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Preneel, Govaerts and Vandewalle (PGV) analysed the security of single-block-length block cipher based compression functions assuming that the underlying block cipher has no weaknesses. They showed that 12 out of 64 possible compression functions are collision and (second) preimage resistant. Black, Rogaway and Shrimpton formally proved this result in the ideal cipher model. However, in the indifferentiability security framework introduced by Maurer, Renner and Holenstein, all these 12 schemes are easily differentiable from a fixed input-length random oracle (FIL-RO) even when their underlying block cipher is ideal. We address the problem of building indifferentiable compression functions from the PGV compression functions. We consider a general form of 64 PGV compression functions and replace the linear feed-forward operation in this generic PGV compression function with an ideal block cipher independent of the one used in the generic PGV construction. This modified construction is called a generic modified PGV (MPGV). We analyse indifferentiability of the generic MPGV construction in the ideal cipher model and show that 12 out of 64 MPGV compression functions in this framework are indifferentiable from a FIL-RO. To our knowledge, this is the first result showing that two independent block ciphers are sufficient to design indifferentiable single-block-length compression functions.

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DNA vaccines or proteins are capable of inducing specific immunity; however, the translation to the clinic has generally been problematic, primarily due to the reduced magnitude of immune response and poor pharmacokinetics. Herein we demonstrate a composite microsphere formulation, composed of mesoporous silica spheres (MPS) and poly(d,l-lactide-co-glycolide) (PLGA), enables the controlled delivery of a prime-boost vaccine via the encapsulation of plasmid DNA (pDNA) and protein in different compartments. Method with modified dual-concentric-feeding needles attached to a 40 kHz ultrasonic atomizer was studied. These needles focus the flow of two different solutions, which passed through the ultrasonic atomizer. The process synthesis parameters, which are important to the scale-up of composite microspheres, were also studied. These parameters include polymer concentration, feed flowrate, and volumetric ratio of polymer and pDNA-PEI/MPS-BSA. This fabrication technique produced composite microspheres with mean D[4,3] ranging from 6 to 34 μm, depending upon the microsphere preparation. The resultant physical morphology of composite microspheres was largely influenced by the volumetric ratio of pDNA-PEI/MPS-BSA to polymer, and this was due to the precipitation of MPS at the surface of the microspheres. The encapsulation efficiencies were predominantly in the range of 93-98% for pDNA and 46-68% for MPS. In the in vitro studies, the pDNA and protein showed different release kinetics in a 40 day time frame. The dual-concentric-feeding in ultrasonic atomization was shown to have excellent reproducibility. It was concluded that this fabrication technique is an effective method to prepare formulations containing a heterologous prime-boost vaccine in a single delivery system.

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Microalgae biotechnology has recently emerged into the lime light owing to numerous consumer products that can be harnessed from microalgae. Product portfolio stretches from straightforward biomass production for food and animal feed to valuable products extracted from microalgal biomass, including triglycerides which can be converted into biodiesel. For most of these applications, the production process is moderately economically viable and the market is developing. Considering the enormous biodiversity of microalgae and recent developments in genetic and metabolic engineering, this group of organisms represents one of the most promising sources for new products and applications. With the development of detailed culture and screening techniques, microalgal biotechnology can meet the high demands of food, energy and pharmaceutical industries. This review article discusses the technology and production platforms for development and creation of different valuable consumer products from microalgal biomass.

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An effective means of facilitating DNA vaccine delivery to antigen presenting cells is through biodegradable microspheres. Microspheres offer distinct advantages over other delivery technologies by providing release of DNA vaccine in its bioactive form in a controlled fashion. In this study, biodegradable poly(D,L-lactide-coglycolide) (PLGA) microspheres containing polyethylenimine (PEI) condensed plasmid DNA (pDNA) were prepared using a 40 kHz ultrasonic atomization system. Process synthesis parameters, which are important to the scale-up of microspheres that are suitable for nasal delivery (i.e., less than 20 μm), were studied. These parameters include polymer concentration; feed flowrate; volumetric ratio of polymer and pDNA-PEI (plasmid DNA-polyethylenimine) complexes; and nitrogen to phosphorous (N/P) ratio. PDNA encapsulation efficiencies were predominantly in the range 82-96%, and the mean sizes of the particle were between 6 and 15 μm. The ultrasonic synthesis method was shown to have excellent reproducibility. PEI affected morphology of the microspheres, as it induced the formation of porous particles that accelerate the release rate of pDNA. The PLGA microspheres displayed an in vitro release of pDNA of 95-99% within 30 days and demonstrated zero order release kinetics without an initial spike of pDNA. Agarose electrophoresis confirmed conservation of the supercoiled form of pDNA throughout the synthesis and in vitro release stages. It was concluded that ultrasonic atomization is an efficient technique to overcome the key obstacles in scaling-up the manufacture of encapsulated vaccine for clinical trials and ultimately, commercial applications.

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Plasmid DNA for therapeutic and vaccination purposes must be highly purified. The high selectivity of affinity chromatography makes it ideal for the isolation of pDNA from complex biological feed stocks. Affinity chromatography makes use of the biological function and/or individual chemical structure of the interacting molecules. However, the success of any affinity purification protocol is dependent on the availability of suitable ligands. In this study, surface plasmon resonance (SPR) based Biacore system has been employed for the detection and quantification of the binding between lac operon (lacO) sequence contained in a pDNA and synthetic peptides based on the DNA-binding domain of the lac repressor protein, lad. The equilibrium dissociation constant (K D) and association and dissociation rate constants (ka, kd) for the interaction between plasmid DNA and designed peptides were determined.

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Current approaches for purifying plasmids from bacterial production systems exploit the physiochemical properties of nucleic acids in non-specific capture systems. In this study, an affinity system for plasmid DNA (pDNA) purification has been developed utilizing the interaction between the lac operon (lacO) sequence contained in the pDNA and a 64mer synthetic peptide representing the DNA-binding domain of the lac repressor protein, LacI. Two plasmids were evaluated, the native pUC19 and pUC19 with dual lacO3/lacOs operators (pUC19lacO3/lacOs), where the lacOs operator is perfectly symmetrical. The DNA-protein affinity interaction was evaluated by surface plasmon resonance using a Biacore system. The affinity capture of DNA in a chromatography system was evaluated using LacI peptide that had been immobilized to Streamline™ adsorbent. The KD-values for double stranded DNA (dsDNA) fragments containing lacO1 and lacO3 and lacOs and lacO3 were 5.7 ± 0.3 × 10 -11 M and 4.1 ± 0.2 × 10-11 M respectively, which compare favorably with literature reports of 5 × 10-10 - 1 × 10-9 M for native laCO1 and 1-1.2 × 10-10 M for lacO1 in a saline buffer. Densitometric analysis of the gel bands from the affinity chromatography run clearly showed a significant preference for capture of the supercoiled fraction from the feed pDNA sample. The results indicate the feasibility of the affinity approach for pDNA capture and purification using native protein-DNA interaction.

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Improved biopharmaceutical delivery may be achieved via the use of biodegradable microspheres as delivery vehicles. Biodegradable microspheres offer the advantages of maintaining sustained protein release over time whilst simultaneously protecting the biopharmaceutical from degradation. Particle samples produced by ultrasonic atomization were studied in order to determine a feed stock capable of producing protein loaded poly-ε-caprolactone (PCL) particles suitable for nasal delivery (i.e., less than 20 μm). A 40 kHz atomization system was used with a 6 mm full wave atomization probe. The effect of solids percent, feed flow rate, volumetric ratio of the polymer stock to the protein stock, and protein concentration in the protein stock on particle size characteristics were determined. It was shown that feed stocks containing 100 parts of 0.5 or 1.0% w/v PCL in acetone with one part 100 mg ml -1 BSA and 15 mg ml -1 PVA produced particles with a mass moment diameter (D[4,3]) of 13.17 μm and 9.10 μm, respectively in addition to displaying high protein encapsulation efficiencies of 93 and 95%, respectively. The biodegradable PCL particles were shown to be able to deliver encapsulated protein in vitro under physiological conditions.

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This chapter takes as its central premise the human capacity to adapt to changing environments. It is an idea that is central to complexity theory but receives only modest attention in relation to learning. To do this we will draw from a range of fields and then consider some recent research in motor control that may extend the discussion in ways not yet considered, but that will build on advances already made within pedagogy and motor control synergies. Recent work in motor control indicates that humans have far greater capacity to adapt to the ‘product space’ than was previously thought, mainly through fast heuristics and on-line corrections. These are changes that can be made in real (movement) time and are facilitated by what are referred to as ‘feed-forward’ mechanisms that take advantage of ultra-fast ways of recognizing the likely outcomes of our movements and using this as a source of feedback. We conclude by discussing some possible ideas for pedagogy within the sport and physical activity domains, the implications of which would require a rethink on how motor skill learning opportunities might best be facilitated.

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Astaxanthin is a high value carotenoid produced by some bacteria, a few green algae, several fungi but only a limited number of plants from the genus Adonis. Astaxanthin has been industrially exploited as a feed supplement in poultry farming and aquaculture. Consumption of ketocarotenoids, most notably astaxanthin, is also increasingly associated with a wide range of health benefits,as demonstrated in numerous clinical studies. Currently astaxanthin is produced commercially by chemical synthesis or from algal production systems. Several studies have used a metabolic engineering approach to produce astaxanthin in transgenic plants. Previous attempts to produce transgenic potato tubers biofortified with astaxanthin have met with limited success. In this study we have investigated approaches to optimising tuber astaxanthin content. It is demonstrated that the selection of appropriate parental genotype for transgenic approaches and stacking carotenoid biosynthetic pathway genes with the cauliflower Or gene result in enhanced astaxanthin content, to give six-fold higher tuber astaxanthin content than has been achieved previously. Additionally we demonstrate the effects of growth environment on tuber carotenoid content in both wild type and astaxanthin-producing transgenic lines and describe the associated transcriptome and metabolome restructuring.

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In this paper, dynamic modeling and simulation of the hydropurification reactor in a purified terephthalic acid production plant has been investigated by gray-box technique to evaluate the catalytic activity of palladium supported on carbon (0.5 wt.% Pd/C) catalyst. The reaction kinetics and catalyst deactivation trend have been modeled by employing artificial neural network (ANN). The network output has been incorporated with the reactor first principle model (FPM). The simulation results reveal that the gray-box model (FPM and ANN) is about 32 percent more accurate than FPM. The model demonstrates that the catalyst is deactivated after eleven months. Moreover, the catalyst lifetime decreases about two and half months in case of 7 percent increase of reactor feed flowrate. It is predicted that 10 percent enhancement of hydrogen flowrate promotes catalyst lifetime at the amount of one month. Additionally, the enhancement of 4-carboxybenzaldehyde concentration in the reactor feed improves CO and benzoic acid synthesis. CO is a poison to the catalyst, and benzoic acid might affect the product quality. The model can be applied into actual working plants to analyze the Pd/C catalyst efficient functioning and the catalytic reactor performance.

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Weblogs, or blogs, constitute a form and genre of online publishing that emerged in the mid-1990s as a logical consequence of the confluence of personal and professional home pages and new web publishing technologies. To overcome technological limitations, where news updates had to be manually inserted by editing the underlying HTML code, the early content-management systems in the second half of the 1990s built on server-side database technology to dynamically generate web pages; this enabled more convenient and more frequent content updates. Weblogs utilised such technologies to provide an up-to-date news feed, presenting individual news items in reverse chronological order. Most blogging platforms provide commenting functions that enable readers to respond to and discuss individual blog posts...