968 resultados para Enhanced efficiency fertiliser
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The 19 kDa carboxyl-terminal fragment of merozoite surface protein 1 (MSP119) is a major component of the invasion-inhibitory response in individual immunity to malaria. A novel ultrasonic atomization approach for the formulation of biodegradable poly(lactic-co-glycolic acid) (PLGA) microparticles of malaria DNA vaccines encoding MSP119 is presented here. After condensing the plasmid DNA (pDNA) molecules with a cationic polymer polyethylenimine (PEI), a 40 kHz ultrasonic atomization frequency was used to formulate PLGA microparticles at a flow rate of 18 mL h1. High levels of gene expression and moderate cytotoxicity in COS-7 cells were achieved with the condensed pDNA at a nitrogen to phosphate (N/P) ratio of 20, thus demonstrating enhanced cellular uptake and expression of the transgene. The ability of the microparticles to convey pDNA was examined by characterizing the formulated microparticles. The microparticles displayed Z-average hydrodynamic diameters of 1.50-2.10 lm and zeta potentials of 17.8-23.2 mV. The encapsulation efficiencies were between 78 and 83%, and 76 and 85% of the embedded malaria pDNA molecules were released under physiological conditions in vitro. These results indicate that PLGA-mediated microparticles can be employed as potential gene delivery systems to antigen-presenting cells in the prevention of malaria.
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Background A novel ultrasonic atomization approach for the formulation of biodegradable poly(lactic-co-glycolic acid) (PLGA) microparticles of a malaria DNA vaccine is presented. A 40 kHz ultrasonic atomization device was used to create the microparticles from a feedstock containing 5 volumes of 0.5% w/v PLGA in acetone and 1 volume of condensed DNA which was fed at a flow rate of 18ml h-1. The plasmid DNA vectors encoding a malaria protein were condensed with a cationic polymer before atomization. Results High levels of gene expression in vitro were observed in COS-7 cells transfected with condensed DNA at a nitrogen to phosphate (N/P) ratio of 10. At this N/P ratio, the condensed DNA exhibited a monodispersed nanoparticle size (Z-average diameter of 60.8 nm) and a highly positive zeta potential of 38.8mV. The microparticle formulations of malaria DNA vaccine were quality assessed and it was shown that themicroparticles displayed high encapsulation efficiencies between 82-96% and a narrow size distribution in the range of 0.8-1.9 μm. In vitro release profile revealed that approximately 82% of the DNA was released within 30 days via a predominantly diffusion controlledmass transfer system. Conclusions This ultrasonic atomization technique showed excellent particle size reproducibility and displayed potential as an industrially viable approach for the formulation of controlled release particles.
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Dewatering of microalgal culture is a major bottleneck towards the industrial-scale processing of microalgae for bio-diesel production. The dilute nature of harvested microalgal cultures poses a huge operation cost to dewater; thereby rendering microalgae-based fuels less economically attractive. This study explores the influence of microalgal growth phases and intercellular interactions during cultivation on dewatering efficiency of microalgae cultures. Experimental results show that microalgal cultures harvested during a low growth rate phase (LGRP) of 0.03 d-1 allowed a higher rate of settling than those harvested during a high growth rate phase (HGRP) of 0.11 d-1, even though the latter displayed a higher average differential biomass concentration of 0.2 g L-1 d-1. Zeta potential profile during the cultivation process showed a maximum electronegative value of -43.2 ± 0.7 mV during the HGRP which declined to stabilization at -34.5 ± 0.4 mV in the LGRP. The lower settling rate observed for HGRP microalgae is hence attributed to the high stability of the microalgal cells which electrostatically repel each other during this growth phase. Tangential flow filtration of 20 L HGRP culture concentrated 23 times by consuming 0.51 kWh/m3 of supernatant removed whilst 0.38 kWh/m3 was consumed to concentrate 20 L of LGRP by 48 times.
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Embedding metallic nanoparticles in organic solar cells can enhance the photoabsorption through light trapping processes. This paper investigates how gold islands obtained by annealing 1–5 nm thick Au layers affect the photoabsorption. Using finite-difference time-domain simulations, the cell efficiency for various island geometries and thicknesses are analyzed and the properties of the islands for maximal photocurrent are discussed. It is shown that a careful choice of size and concentration of gold islands could contribute to enhance the power conversion efficiencies when compared to standard organic solar cell devices. The conclusions are then compared to experimental data for thermally annealed gold islands in bulk heterojunction solar cells. The results of this paper will contribute to the optimization of plasmonic organic solar cell systems and will pave the way for the development of highly efficient organic solar cell devices.
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This study developed a comprehensive research methodology for identification and quantification of sources responsible for pollutant build-up and wash-off from urban road surfaces. The study identified soil and asphalt wear, and non-combusted diesel fuel as the most influential sources for metal and hydrocarbon pollution respectively. The study also developed mathematical models to relate contributions from identified sources to underlying site specific factors such as land use and traffic. Developed mathematical model will play a key role in urban planning practices, enabling the implementation of effective water pollution control strategies.
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Underwater wireless sensor networks (UWSNs) have become the seat of researchers' attention recently due to their proficiency to explore underwater areas and design different applications for marine discovery and oceanic surveillance. One of the main objectives of each deployed underwater network is discovering the optimized path over sensor nodes to transmit the monitored data to onshore station. The process of transmitting data consumes energy of each node, while energy is limited in UWSNs. So energy efficiency is a challenge in underwater wireless sensor network. Dual sinks vector based forwarding (DS-VBF) takes both residual energy and location information into consideration as priority factors to discover an optimized routing path to save energy in underwater networks. The modified routing protocol employs dual sinks on the water surface which improves network lifetime. According to deployment of dual sinks, packet delivery ratio and the average end to end delay are enhanced. Based on our simulation results in comparison with VBF, average end to end delay reduced more than 80%, remaining energy increased 10%, and the increment of packet reception ratio was about 70%.
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The requirement of isolated relays is one of the prime obstacles in utilizing sequential slotted cooperative protocols for Vehicular Ad-hoc Networks (VANET). Significant research advancement has taken place to improve the diversity multiplexing trade-off (DMT) of cooperative protocols in conventional mobile networks without much attention on vehicular ad-hoc networks. We have extended the concept of sequential slotted amplify and forward (SAF) protocols in the context of urban vehicular ad-hoc networks. Multiple Input Multiple Output (MIMO) reception is used at relaying vehicular nodes to isolate the relays effectively. The proposed approach adds a pragmatic value to the sequential slotted cooperative protocols while achieving attractive performance gains in urban VANETs. We have analysed the DMT bounds and the outage probabilities of the proposed scheme. The results suggest that the proposed scheme can achieve an optimal DMT similar to the DMT upper bound of the sequential SAF. Furthermore, the outage performance of the proposed scheme outperforms the SAF protocol by 2.5 dB at a target outage probability of 10-4.
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Solvothermally synthesized Ga2O3 nanoparticles are incorporated into liquid metal/metal oxide (LM/MO) frameworks in order to form enhanced photocatalytic systems. The LM/MO frameworks, both with and without incorporated Ga2O3 nanoparticles, show photocatalytic activitydue to a plasmonic effect where performance is related to the loading of Ga2O3 nanoparticles. Optimum photocatalytic efficiency is obtained with 1 wt% incorporation of Ga2O3 nanoparticles. This can be attributed to the sub-bandgap states of LM/MO frameworks, contributing to pseudo-ohmic contacts which reduce the free carrier injection barrier to Ga2O3.
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Objectives Shift workers are prone to obesity and associated co-morbidities such as diabetes and cardiovascular disease. Sleep restriction associated with shift work results in dramatic endocrine and metabolic effects that predispose shift workers to these adverse health consequences. While sleep restriction has been associated with increased caloric intake, food preference may also play a key role in weight gain associated with shift work. This study examined the impact of an overnight simulated night shift on food preference. Methods Sixteen participants [mean 20.1, standard deviation (SD) 1.4 years; 8 women] underwent a simulated night shift and control condition in a counterbalanced order. On the following morning, participants were provided an opportunity for breakfast that included high- and low-fat food options (mean 64.8% and 6.4% fat, respectively). Results Participants ate significantly more high-fat breakfast items after the simulated night shift than after the control condition [167.3, standard error of the mean (SEM 28.7) g versus 211.4 (SEM 35.6) g; P=0.012]. The preference for high-fat food was apparent among the majority of individuals following the simulated night shift (81%), but not for the control condition (31%). Shift work and control conditions did not differ, however, in the total amount of food or calories consumed. Conclusions A simulated night shift leads to preference for high-fat food during a subsequent breakfast opportunity. These results suggest that food choice may contribute to weight-related chronic health problems commonly seen among night shift workers.
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Most real-life data analysis problems are difficult to solve using exact methods, due to the size of the datasets and the nature of the underlying mechanisms of the system under investigation. As datasets grow even larger, finding the balance between the quality of the approximation and the computing time of the heuristic becomes non-trivial. One solution is to consider parallel methods, and to use the increased computational power to perform a deeper exploration of the solution space in a similar time. It is, however, difficult to estimate a priori whether parallelisation will provide the expected improvement. In this paper we consider a well-known method, genetic algorithms, and evaluate on two distinct problem types the behaviour of the classic and parallel implementations.
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Background The requirement for dual screening of titles and abstracts to select papers to examine in full text can create a huge workload, not least when the topic is complex and a broad search strategy is required, resulting in a large number of results. An automated system to reduce this burden, while still assuring high accuracy, has the potential to provide huge efficiency savings within the review process. Objectives To undertake a direct comparison of manual screening with a semi‐automated process (priority screening) using a machine classifier. The research is being carried out as part of the current update of a population‐level public health review. Methods Authors have hand selected studies for the review update, in duplicate, using the standard Cochrane Handbook methodology. A retrospective analysis, simulating a quasi‐‘active learning’ process (whereby a classifier is repeatedly trained based on ‘manually’ labelled data) will be completed, using different starting parameters. Tests will be carried out to see how far different training sets, and the size of the training set, affect the classification performance; i.e. what percentage of papers would need to be manually screened to locate 100% of those papers included as a result of the traditional manual method. Results From a search retrieval set of 9555 papers, authors excluded 9494 papers at title/abstract and 52 at full text, leaving 9 papers for inclusion in the review update. The ability of the machine classifier to reduce the percentage of papers that need to be manually screened to identify all the included studies, under different training conditions, will be reported. Conclusions The findings of this study will be presented along with an estimate of any efficiency gains for the author team if the screening process can be semi‐automated using text mining methodology, along with a discussion of the implications for text mining in screening papers within complex health reviews.
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Building energy-efficiency (BEE) is the key to drive the promotion of energy saving in building sector. A large variety of building energy-efficiency policy instrument exist. Some are mandatory, some are soft scheme, and some use economic incentives from country to country. This paper presents the current development of implementing BEE policy instruments by examining the practices of BEE in seven selected countries and regions. In the study, BEE policy instruments are classified into three groups, including mandatory administration control instruments, economic incentive instruments and voluntary scheme instruments. The study shows that different countries have adopted different instruments in their practices for achieving the target of energy-saving and gained various kinds of experiences. It is important to share these experiences gained.
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This study models the joint production of desirable and undesirable output production (that is, CO2 emissions) of airlines. The Malmquist–Luenberger productivity index is employed to measure productivity growth when undesirable output production is incorporated into the production model. The results show that pollution abatement activities of airlines lowers productivity growth, which suggests that the traditional approach of measuring productivity growth, which ignores CO2 emissions, overstates ‘true’ productivity growth. The reliability of the results is also tested and verified using confidence intervals based on bootstrapping.
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A facile and sensitive surface-enhanced Raman scattering substrate was prepared by controlled potentiostatic deposition of a closely packed single layer of gold nanostructures (AuNS) over a flat gold (pAu) platform. The nanometer scale inter-particle distance between the particles resulted in high population of ‘hot spots’ which enormously enhanced the scattered Raman photons. A renewed methodology was followed to precisely quantify the SERS substrate enhancement factor (SSEF) and it was estimated to be (2.2 ± 0.17) × 105. The reproducibility of the SERS signal acquired by the developed substrate was tested by establishing the relative standard deviation (RSD) of 150 repeated measurements from various locations on the substrate surface. A low RSD of 4.37 confirmed the homogeneity of the developed substrate. The sensitivity of pAu/AuNS was proven by determining 100 fM 2,4,6-trinitrotoluene (TNT) comfortably. As a proof of concept on the potential of the new pAu/AuNS substrate in field analysis, TNT in soil and water matrices was selectively detected after forming a Meisenheimer complex with cysteamine.
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We report rapid and ultra-sensitive detection system for 2,4,6-trinitrotoluene (TNT) using unmodified gold nanoparticles and surface-enhanced Raman spectroscopy (SERS). First, Meisenheimer complex has been formed in aqueous solution between TNT and cysteamine in less than 15 min of mixing. The complex formation is confirmed by the development of a pink colour and a new UV–vis absorption band around 520 nm. Second, the developed Meisenheimer complex is spontaneously self-assembled onto unmodified gold nanoparticles through a stable Au–S bond between the cysteamine moiety and the gold surface. The developed mono layer of cysteamine-TNT is then screened by SERS to detect and quantify TNT. Our experimental results demonstrate that the SERS-based assay provide an ultra-sensitive approach for the detection of TNT down to 22.7 ng/L. The unambiguous fingerprint identification of TNT by SERS represents a key advantage for our proposed method. The new method provides high selectivity towards TNT over 2,4 DNT and picric acid. Therefore it satisfies the practical requirements for the rapid screening of TNT in real life samples where the interim 24-h average allowable concentration of TNT in waste water is 0.04 mg/L.