901 resultados para LOW-COST ADSORBENTS


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HIV remains a significant global burden and without an effective vaccine, it is crucial to develop microbicides to halt the initial transmission of the virus. Several microbicides have been researched with various levels of success. Amongst these, the broadly neutralising antibodies and peptide lectins are promising in that they can immediately act on the virus and have proven efficacious in in vitro and in vivo protection studies. For the purpose of development and access by the relevant population groups, it is crucial that these microbicides be produced at low cost. For the promising protein and peptide candidate molecules, it appears that current production systems are overburdened and expensive to establish and maintain. With recent developments in vector systems for protein expression coupled with downstream protein purification technologies, plants are rapidly gaining credibility as alternative production systems. Here we evaluate the advances made in host and vector system development for plant expression as well as the progress made in expressing HIV neutralising antibodies and peptide lectins using plant-based platforms. © 2012 Elsevier Inc.

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In the past few years, plant biotechnology has gone beyond traditional agricultural production of food, feed and fibre, and moved to address more complex contemporary health, social and industrial challenges. The new era involves production of novel pharmaceutical products, speciality and fine chemicals, phytoremediation and production of renewable energy resources to replace non-renewable fossil fuels. Plants have been shown to provide a genuine and low-cost alternative production system for high-value products. Currently, the principal plant-made products include antibodies, feed additives, vaccine antigens and hormones for human and animal health, and industrial proteins. Despite the unique advantages of scalability, cost and product safety, issues of politics, environmental impact, regulation and socioeconomics still limit the adoption of biopharmaceuticals, especially in the developing world. Plant-based production systems have further complicated biosafety, gene flow and environmental impact assessments with generally genetically modified plants, topics that are already partially understood. This article provides a background to biopharming, highlighting basic considerations for risk assessment and regulation in developing countries, with an emphasis on plant-based vaccine production in South Africa.

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Saudi Arabia experiences housing shortage for mid and low-income families, which is caused by rapid population growth. This condition is worsened by the fact that the current housing supply has problems in meeting both sustainable requirements and cultural needs of those families. This paper aims to investigate the link between the unique conservative Saudi culture and the design of sustainable housing, while keeping the housing cost affordable for mid and low-income families. The paper is based on a review of literatures on the issues of the Islamic culture and how can they be integrated into the design process of a Saudi house. Findings from literature reveiw suggest several design requirements for accommodating the conservative Saudi Culture in low cost sustainable houses. Such requirements include the implementation of proper usage of windows, and house orientation with a courtyard inside rather than facing the main street will provide natural ventilation while maintaining privacy. The main contribution to the body of knowledge is that this is a new approach to sustainable housing in Saudi Arabia considering not only energy use and architectural design issues but also socio-cultural issues as an essential part of sustainability.

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This study used both content and frame analyses to test news-media representations of homelessness in The Courier-Mail newspaper for evidence of restricted journalism practice. Specifically, it sought signs of either direct manipulation of issue representation based on ideological grounds, and also evidence of news organisations prioritising low-cost news production over Public Sphere journalistic news values. The study found that news stories from the earlier parts of the longitudinal study showed stereotypical misrepresentations of homelessness for public deliberation which might be attributed to either, or both of the nominated restricting factors. However news stories from the latter part of the study saw a distinct change in the way the issue was represented, indicating a journalistic capacity to thoughtfully and sensitively represent a complex social issue to the public. Further study is recommended to ascertain how and why this change occurred, so that journalistic practice might be further improved.

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Chapter 5: Fertility and infertility. p52-70. This section describes patterns of fertility across Surveys 1 to 4 among the cohort of women who were born in 1973-1978. This section includes the examination of pregnancy outcomes including both live births and pregnancy losses (stillbirths, miscarriages, terminations and ectopic pregnancies). This section also examines the prevalence of self-reported problems with fertility and whether these women sought advice and/or treatment. As women age they are more likely to experience infertility and, with little other data available, the ALSWH provides an important opportunity to examine this problem and the related use of health services. 1. Pregnancy losses are common. Half of the women who report a pregnancy outcome at Survey 4 have experienced a pregnancy loss. 2. More than one third (39%) of women who have experienced a live birth by Survey 4 have also experienced a pregnancy loss. 3. For every ten women aged 28-33 years in 2006: four women had not had been pregnant, five women had a live birth (with or without a recognised pregnancy loss), and one woman had a recognised pregnancy loss only. 4. Among women who had tried to conceive or had been pregnant, one-in-six had experienced infertility. (i.e. tried unsuccessfully to get pregnant for 12 months or more) 5. The most significant factors associated with having infertility, seeking advice and using treatment were: polycystic ovary syndrome, endometriosis and miscarriage. 6. Of the women who reported infertility, two-thirds sought advice but only half used treatment. 7. Most of the women who used fertility treatment had used low cost and non-invasive methods.

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Debugging control software for Micro Aerial Vehicles (MAV) can be risky out of the simulator, especially with professional drones that might harm people around or result in a high bill after a crash. We have designed a framework that enables a software application to communicate with multiple MAVs from a single unified interface. In this way, visual controllers can be first tested on a low-cost harmless MAV and, after safety is guaranteed, they can be moved to the production MAV at no additional cost. The framework is based on a distributed architecture over a network. This allows multiple configurations, like drone swarms or parallel processing of drones' video streams. Live tests have been performed and the results show comparatively low additional communication delays, while adding new functionalities and flexibility. This implementation is open-source and can be downloaded from github.com/uavster/mavwork

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This paper presents a shared autonomy control scheme for a quadcopter that is suited for inspection of vertical infrastructure — tall man-made structures such as streetlights, electricity poles or the exterior surfaces of buildings. Current approaches to inspection of such structures is slow, expensive, and potentially hazardous. Low-cost aerial platforms with an ability to hover now have sufficient payload and endurance for this kind of task, but require significant human skill to fly. We develop a control architecture that enables synergy between the ground-based operator and the aerial inspection robot. An unskilled operator is assisted by onboard sensing and partial autonomy to safely fly the robot in close proximity to the structure. The operator uses their domain knowledge and problem solving skills to guide the robot in difficult to reach locations to inspect and assess the condition of the infrastructure. The operator commands the robot in a local task coordinate frame with limited degrees of freedom (DOF). For instance: up/down, left/right, toward/away with respect to the infrastructure. We therefore avoid problems of global mapping and navigation while providing an intuitive interface to the operator. We describe algorithms for pole detection, robot velocity estimation with respect to the pole, and position estimation in 3D space as well as the control algorithms and overall system architecture. We present initial results of shared autonomy of a quadrotor with respect to a vertical pole and robot performance is evaluated by comparing with motion capture data.

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The IEEE Wireless LAN standard has been a true success story by enabling convenient, efficient and low-cost access to broadband networks for both private and professional use. However, the increasing density and uncoordinated operation of wireless access points, combined with constantly growing traffic demands have started hurting the users' quality of experience. On the other hand, the emerging ubiquity of wireless access has placed it at the center of attention for network attacks, which not only raises users' concerns on security but also indirectly affects connection quality due to proactive measures against security attacks. In this work, we introduce an integrated solution to congestion avoidance and attack mitigation problems through cooperation among wireless access points. The proposed solution implements a Partially Observable Markov Decision Process (POMDP) as an intelligent distributed control system. By successfully differentiating resource hampering attacks from overload cases, the control system takes an appropriate action in each detected anomaly case without disturbing the quality of service for end users. The proposed solution is fully implemented on a small-scale testbed, on which we present our observations and demonstrate the effectiveness of the system to detect and alleviate both attack and congestion situations.

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The ultimate goal of an access control system is to allocate each user the precise level of access they need to complete their job - no more and no less. This proves to be challenging in an organisational setting. On one hand employees need enough access to the organisation’s resources in order to perform their jobs and on the other hand more access will bring about an increasing risk of misuse - either intentionally, where an employee uses the access for personal benefit, or unintentionally, through carelessness or being socially engineered to give access to an adversary. This thesis investigates issues of existing approaches to access control in allocating optimal level of access to users and proposes solutions in the form of new access control models. These issues are most evident when uncertainty surrounding users’ access needs, incentive to misuse and accountability are considered, hence the title of the thesis. We first analyse access control in environments where the administrator is unable to identify the users who may need access to resources. To resolve this uncertainty an administrative model with delegation support is proposed. Further, a detailed technical enforcement mechanism is introduced to ensure delegated resources cannot be misused. Then we explicitly consider that users are self-interested and capable of misusing resources if they choose to. We propose a novel game theoretic access control model to reason about and influence the factors that may affect users’ incentive to misuse. Next we study access control in environments where neither users’ access needs can be predicted nor they can be held accountable for misuse. It is shown that by allocating budget to users, a virtual currency through which they can pay for the resources they deem necessary, the need for a precise pre-allocation of permissions can be relaxed. The budget also imposes an upper-bound on users’ ability to misuse. A generalised budget allocation function is proposed and it is shown that given the context information the optimal level of budget for users can always be numerically determined. Finally, Role Based Access Control (RBAC) model is analysed under the explicit assumption of administrators’ uncertainty about self-interested users’ access needs and their incentives to misuse. A novel Budget-oriented Role Based Access Control (B-RBAC) model is proposed. The new model introduces the notion of users’ behaviour into RBAC and provides means to influence users’ incentives. It is shown how RBAC policy can be used to individualise the cost of access to resources and also to determine users’ budget. The implementation overheads of B-RBAC is examined and several low-cost sub-models are proposed.

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The Beauty Leaf tree (Calophyllum inophyllum) is a potential source of non-edible vegetable oil for producing future generation biodiesel because of its ability to grow in a wide range of climate conditions, easy cultivation, high fruit production rate, and the high oil content in the seed. This plant naturally occurs in the coastal areas of Queensland and the Northern Territory in Australia, and is also widespread in south-east Asia, India and Sri Lanka. Although Beauty Leaf is traditionally used as a source of timber and orientation plant, its potential as a source of second generation biodiesel is yet to be exploited. In this study, the extraction process from the Beauty Leaf oil seed has been optimised in terms of seed preparation, moisture content and oil extraction methods. The two methods that have been considered to extract oil from the seed kernel are mechanical oil extraction using an electric powered screw press, and chemical oil extraction using n-hexane as an oil solvent. The study found that seed preparation has a significant impact on oil yields, especially in the screw press extraction method. Kernels prepared to 15% moisture content provided the highest oil yields for both extraction methods. Mechanical extraction using the screw press can produce oil from correctly prepared product at a low cost, however overall this method is ineffective with relatively low oil yields. Chemical extraction was found to be a very effective method for oil extraction for its consistence performance and high oil yield, but cost of production was relatively higher due to the high cost of solvent. However, a solvent recycle system can be implemented to reduce the production cost of Beauty Leaf biodiesel. The findings of this study are expected to serve as the basis from which industrial scale biodiesel production from Beauty Leaf can be made.

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The use of Wireless Sensor Networks (WSNs) for Structural Health Monitoring (SHM) has become a promising approach due to many advantages such as low cost, fast and flexible deployment. However, inherent technical issues such as data synchronization error and data loss have prevented these distinct systems from being extensively used. Recently, several SHM-oriented WSNs have been proposed and believed to be able to overcome a large number of technical uncertainties. Nevertheless, there is limited research verifying the applicability of those WSNs with respect to demanding SHM applications like modal analysis and damage identification. This paper first presents a brief review of the most inherent uncertainties of the SHM-oriented WSN platforms and then investigates their effects on outcomes and performance of the most robust Output-only Modal Analysis (OMA) techniques when employing merged data from multiple tests. The two OMA families selected for this investigation are Frequency Domain Decomposition (FDD) and Data-driven Stochastic Subspace Identification (SSI-data) due to the fact that they both have been widely applied in the past decade. Experimental accelerations collected by a wired sensory system on a large-scale laboratory bridge model are initially used as clean data before being contaminated by different data pollutants in sequential manner to simulate practical SHM-oriented WSN uncertainties. The results of this study show the robustness of FDD and the precautions needed for SSI-data family when dealing with SHM-WSN uncertainties. Finally, the use of the measurement channel projection for the time-domain OMA techniques and the preferred combination of the OMA techniques to cope with the SHM-WSN uncertainties is recommended.

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Based on theoretical prediction, a g-C3N4@carbon metal-free oxygen reduction reaction (ORR) electrocatalyst was designed and synthesized by uniform incorporation of g-C3N4 into a mesoporous carbon to enhance the electron transfer efficiency of g-C3N4. The resulting g-C3N4@carbon composite exhibited competitive catalytic activity (11.3 mA cm–2 kinetic-limiting current density at −0.6 V) and superior methanol tolerance compared to a commercial Pt/C catalyst. Furthermore, it demonstrated significantly higher catalytic efficiency (nearly 100% of four-electron ORR process selectivity) than a Pt/C catalyst. The proposed synthesis route is facile and low-cost, providing a feasible method for the development of highly efficient electrocatalysts.

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Vision-based SLAM is mostly a solved problem providing clear, sharp images can be obtained. However, in outdoor environments a number of factors such as rough terrain, high speeds and hardware limitations can result in these conditions not being met. High speed transit on rough terrain can lead to image blur and under/over exposure, problems that cannot easily be dealt with using low cost hardware. Furthermore, recently there has been a growth in interest in lifelong autonomy for robots, which brings with it the challenge in outdoor environments of dealing with a moving sun and lack of constant artificial lighting. In this paper, we present a lightweight approach to visual localization and visual odometry that addresses the challenges posed by perceptual change and low cost cameras. The approach combines low resolution imagery with the SLAM algorithm, RatSLAM. We test the system using a cheap consumer camera mounted on a small vehicle in a mixed urban and vegetated environment, at times ranging from dawn to dusk and in conditions ranging from sunny weather to rain. We first show that the system is able to provide reliable mapping and recall over the course of the day and incrementally incorporate new visual scenes from different times into an existing map. We then restrict the system to only learning visual scenes at one time of day, and show that the system is still able to localize and map at other times of day. The results demonstrate the viability of the approach in situations where image quality is poor and environmental or hardware factors preclude the use of visual features.

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The building sector is the dominant consumer of energy and therefore a major contributor to anthropomorphic climate change. The rapid generation of photorealistic, 3D environment models with incorporated surface temperature data has the potential to improve thermographic monitoring of building energy efficiency. In pursuit of this goal, we propose a system which combines a range sensor with a thermal-infrared camera. Our proposed system can generate dense 3D models of environments with both appearance and temperature information, and is the first such system to be developed using a low-cost RGB-D camera. The proposed pipeline processes depth maps successively, forming an ongoing pose estimate of the depth camera and optimizing a voxel occupancy map. Voxels are assigned 4 channels representing estimates of their true RGB and thermal-infrared intensity values. Poses corresponding to each RGB and thermal-infrared image are estimated through a combination of timestamp-based interpolation and a pre-determined knowledge of the extrinsic calibration of the system. Raycasting is then used to color the voxels to represent both visual appearance using RGB, and an estimate of the surface temperature. The output of the system is a dense 3D model which can simultaneously represent both RGB and thermal-infrared data using one of two alternative representation schemes. Experimental results demonstrate that the system is capable of accurately mapping difficult environments, even in complete darkness.

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First-principles computational studies indicate that (B, N, or O)-doped graphene ribbon edges can substantially reduce the energy barrier for H2 dissociative adsorption. The low barrier is competitive with many widely used metal or metal oxide catalysts. This suggests that suitably functionalized graphene architectures are promising metal-free alternatives for low-cost catalytic processes.