935 resultados para Gemstone Team PANACEA: Promoting A Novel Approach to Cellular (gene) Expression Alteration


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In this paper we propose an approach based on self-interested autonomous cameras, which exchange responsibility for tracking objects in a market mechanism, in order to maximise their own utility. A novel ant-colony inspired mechanism is used to grow the vision graph during runtime, which may then be used to optimise communication between cameras. The key benefits of our completely decentralised approach are on the one hand generating the vision graph online which permits the addition and removal cameras to the network during runtime and on the other hand relying only on local information, increasing the robustness of the system. Since our market-based approach does not rely on a priori topology information, the need for any multi-camera calibration can be avoided. © 2011 IEEE.

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Purpose: Energy security is a major concern for India and many rural areas remain un-electrified. Thus, innovations in sustainable technologies to provide energy services are required. Biomass and solar energy in particular are resources that are widely available and underutilised in India. This paper aims to provide an overview of a methodology that was developed for designing and assessing the feasibility of a hybrid solar-biomass power plant in Gujarat. Design/methodology/approach: The methodology described is a combination of engineering and business management studies used to evaluate and design solar thermal collectors for specific applications and locations. For the scenario of a hybrid plant, the methodology involved: the analytical hierarchy process, for solar thermal technology selection; a cost-exergy approach, for design optimisation; quality function deployment, for designing and evaluating a novel collector - termed the elevation linear Fresnel reflector (ELFR); and case study simulations, for analysing alternative hybrid plant configurations. Findings: The paper recommended that for a hybrid plant in Gujarat, a linear Fresnel reflector of 14,000 m2 aperture is integrated with a 3 tonne per hour biomass boiler, generating 815 MWh per annum of electricity for nearby villages and 12,450 tonnes of ice per annum for local fisheries and food industries. However, at the expense of a 0.3 ¢/kWh increase in levelised energy costs, the ELFR can increase savings of biomass (100 t/a) and land (9 ha/a). Research limitations/implications: The research reviewed in this paper is primarily theoretical and further work will need to be undertaken to specify plant details such as piping layout, pump sizing and structure, and assess plant performance during real operational conditions. Originality/value: The paper considers the methodology adopted proved to be a powerful tool for integrating technology selection, optimisation, design and evaluation and promotes interdisciplinary methods for improving sustainable engineering design and energy management. © Emerald Group Publishing Limited.

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Purpose – The purpose of this paper is to develop a comprehensive framework for improving intensive care unit performance. Design/methodology/approach – The study introduces a quality management framework by combining cause and effect diagram and logical framework. An intensive care unit was identified for the study on the basis of its performance. The reasons for not achieving the desired performance were identified using a cause and effect diagram with the stakeholder involvement. A logical framework was developed using information from the cause and effect diagram and a detailed project plan was developed. The improvement projects were implemented and evaluated. Findings – Stakeholders identified various intensive care unit issues. Managerial performance, organizational processes and insufficient staff were considered major issues. A logical framework was developed to plan an improvement project to resolve issues raised by clinicians and patients. Improved infrastructure, state-of-the-art equipment, well maintained facilities, IT-based communication, motivated doctors, nurses and support staff, improved patient care and improved drug availability were considered the main project outputs for improving performance. The proposed framework is currently being used as a continuous quality improvement tool, providing a planning, implementing, monitoring and evaluating framework for the quality improvement measures on a sustainable basis. Practical implications – The combined cause and effect diagram and logical framework analysis is a novel and effective approach to improving intensive care performance. Similar approaches could be adopted in any intensive care unit. Originality/value – The paper focuses on a uniform model that can be applied to most intensive care units.

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This article describes the approach adopted and the results obtained by the international team developing WBLST (Web Based Learning in Sciences and Technologies) a Web-based application for e-learning, developed for the students of “UVPL: Université Virtuelle des Pays de la Loire”. The developed e-learning system covers three levels of learning activities - content, exercises, and laboratory. The delivery model is designed to operate with domain concepts as relevant providers of semantic links. The aim is to facilitate the overview and to help the establishment of a mental map of the learning material. The implemented system is strongly based on the organization of the instruction in virtual classes. The obtained quality of the system is evaluated on the bases of feedback form students and professors.

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This thesis describes the design and development of an eye alignment/tracking system which allows self alignment of the eye’s optical axis with a measurement axis. Eye alignment is an area of research largely over-looked, yet it is a fundamental requirement in the acquisition of clinical data from the eye. New trends in the ophthalmic market, desiring portable hand-held apparatus, and the application of ophthalmic measurements in areas other than vision care have brought eye alignment under new scrutiny. Ophthalmic measurements taken in hand-held devices with out an clinician present requires alignment in an entirely new set of circumstances, requiring a novel solution. In order to solve this problem, the research has drawn upon eye tracking technology to monitor the eye, and a principle of self alignment to perform alignment correction. A handheld device naturally lends itself to the patient performing alignment, thus a technique has been designed to communicate raw eye tracking data to the user in a manner which allows the user to make the necessary corrections. The proposed technique is a novel methodology in which misalignment to the eye’s optical axis can be quantified, corrected and evaluated. The technique uses Purkinje Image tracking to monitor the eye’s movement as well as the orientation of the optical axis. The use of two sets of Purkinje Images allows quantification of the eye’s physical parameters needed for accurate Purkinje Image tracking, negating the need for prior anatomical data. An instrument employing the methodology was subsequently prototyped and validated, allowing a sample group to achieve self alignment of their optical axis with an imaging axis within 16.5-40.8 s, and with a rotational precision of 0.03-0.043°(95% confidence intervals). By encompassing all these factors the technique facilitates self alignment from an unaligned position on the visual axis to an aligned position on the optical axis. The consequence of this is that ophthalmic measurements, specifically pachymetric measurements, can be made in the absence of an optician, allowing the use of ophthalmic instrumentation and measurements in health professions other than vision care.

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As the volume of image data and the need of using it in various applications is growing significantly in the last days it brings a necessity of retrieval efficiency and effectiveness. Unfortunately, existing indexing methods are not applicable to a wide range of problem-oriented fields due to their operating time limitations and strong dependency on the traditional descriptors extracted from the image. To meet higher requirements, a novel distance-based indexing method for region-based image retrieval has been proposed and investigated. The method creates premises for considering embedded partitions of images to carry out the search with different refinement or roughening level and so to seek the image meaningful content.

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In nonlinear and stochastic control problems, learning an efficient feed-forward controller is not amenable to conventional neurocontrol methods. For these approaches, estimating and then incorporating uncertainty in the controller and feed-forward models can produce more robust control results. Here, we introduce a novel inversion-based neurocontroller for solving control problems involving uncertain nonlinear systems which could also compensate for multi-valued systems. The approach uses recent developments in neural networks, especially in the context of modelling statistical distributions, which are applied to forward and inverse plant models. Provided that certain conditions are met, an estimate of the intrinsic uncertainty for the outputs of neural networks can be obtained using the statistical properties of networks. More generally, multicomponent distributions can be modelled by the mixture density network. Based on importance sampling from these distributions a novel robust inverse control approach is obtained. This importance sampling provides a structured and principled approach to constrain the complexity of the search space for the ideal control law. The developed methodology circumvents the dynamic programming problem by using the predicted neural network uncertainty to localise the possible control solutions to consider. A nonlinear multi-variable system with different delays between the input-output pairs is used to demonstrate the successful application of the developed control algorithm. The proposed method is suitable for redundant control systems and allows us to model strongly non-Gaussian distributions of control signal as well as processes with hysteresis. © 2004 Elsevier Ltd. All rights reserved.

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We introduce a novel algorithm for medial surfaces extraction that is based on the density-corrected Hamiltonian analysis. The approach extracts the skeleton directly from a triangulated mesh and adopts an adaptive octree-based approach in which only skeletal voxels are refined to a lower level of the hierarchy, resulting in robust and accurate skeletons at extremely high resolution. The quality of the extracted medial surfaces is confirmed by an extensive set of experiments. © 2012 IEEE.

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Mannitol is an essential excipient employed in orally disintegrating tablets due to its high palatability. However its fundamental disadvantage is its fragmentation during direct compression, producing mechanically weak tablets. The primary aim of this study was to assess the fracture behaviour of crystalline mannitol in relation to the energy input during direct compression, utilising ball milling as the method of energy input, whilst assessing tablet characteristics of post-milled powders. Results indicated that crystalline mannitol fractured at the hydrophilic (011) plane, as observed through SEM, alongside a reduction in dispersive surface energy. Disintegration times of post-milled tablets were reduced due to the exposure of the hydrophilic plane, whilst more robust tablets were produced. This was shown through higher tablet hardness and increased plastic deformation profiles of the post-milled powders, as observed with a lower yield pressure through an out-of-die Heckel analysis. Evaluation of crystal state using x-ray diffraction/differential scanning calorimetry showed that mannitol predominantly retained the β-polymorph; however x-ray diffraction provided a novel method to calculate energy input into the powders during ball milling. It can be concluded that particle size reduction is a pragmatic strategy to overcome the current limitation of mannitol fragmentation and provide improvements in tablet properties.

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The euro area‘s sovereign debt crisis continues though significant steps have been taken to resolve it. This paper proposes a comprehensive solution to the crisis based on three pillars: a plan to restore banking sector soundness in the whole euro area, a resolution of sovereign debt crisis -including a revision of EU assistance facilities and a reduction of the Greek public debt- and a strategy to foster growth and competitiveness. The paper provides novel estimates and analysis focusing on the current situation of Greece, Ireland, Portugal and Spain.

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This dissertation reports an investigation of the utility of two intervention programs to facilitate identity formation by way of exploration, one designed from an explicitly self-construction point of view and the other designed from an explicitly self-discovery point of view. The self-construction program was implemented using cognitive skills and orientations derived from Berzonsky (1989), Grotevant (1987), and Kurtines (1999). The self-discovery program was implemented using affective insight development strategies derived from Csikszentmihalyi (1990), Maslow (1968), and Waterman (1990). Three sets of measures were used: (a) cognitive identity measures, (b) affective identity measures, and (c) overall identity measures. Ninety undergraduates from Florida International University completed the intervention. Participants were assigned to one of three intervention conditions (Cognitive, Affective, and Control) and were pretested and posttested on cognitive, affective, and overall identity measures. Intervention strategies were introduced and discussed in the context of specific goals and choices that participants brought to group. Intervention results were then analyzed in terms of the effectiveness of the intervention conditions in promoting their respective developmental domains. The intervention was effective in promoting identity development in comparison to the control condition, with the cognitive condition facilitating cognitive competence and the affective condition facilitating affective insight. Results are discussed in the context of the constructivist and discovery perspectives, as well as in light of the broadened view of exploration offered in this paper. ^

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One in 3,000 people in the US are born with cystic fibrosis (CF), a genetic disorder affecting the reproductive system, pancreas, and lungs. Lung disease caused by chronic bacterial and fungal infections is the leading cause of morbidity and mortality in CF. Identities of the microbes are traditionally determined by culturing followed by phenotypic and biochemical assays. It was first thought that the bacterial infections were caused by a select handful of bacteria such as S. aureus, H. influenzae, B. cenocepacia, and P. aeruginosa. With the advent of PCR and molecular techniques, the polymicrobial nature of the CF lung became evident. The CF lung contains numerous bacteria and the communities are diverse and unique to each patient. The total complexity of the bacterial infections is still being determined. In addition, only a few members of the fungal communities have been identified. Much of the fungal community composition is still a mystery. This dissertation addresses this gap in knowledge. A snap shot of CF sputa bacterial community was obtained using the length heterogeneity-PCR community profiling technique. The profiles show that south Florida CF patients have a unique, diverse, and dynamic bacterial community which changes over time. The identities of the bacteria and fungi present were determined using the state-of-the-art 454 sequencing. Sequencing results show that the CF lung microbiome contains commonly cultured pathogenic bacteria, organisms considered a part of the healthy core biome, and novel organisms. Understanding the dynamic changes of these identified microbes will ultimately lead to better therapeutical interventions. Early detection is key in reducing the lung damage caused by chronic infections. Thus, there is a need for accurate and sensitive diagnostic tests. This issue was addressed by designing a bacterial diagnostic tool targeted towards CF pathogens using SPR. By identifying the organisms associated with the CF lung and understanding their community interactions, patients can receive better treatment and live longer.

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This dissertation develops an image processing framework with unique feature extraction and similarity measurements for human face recognition in the thermal mid-wave infrared portion of the electromagnetic spectrum. The goals of this research is to design specialized algorithms that would extract facial vasculature information, create a thermal facial signature and identify the individual. The objective is to use such findings in support of a biometrics system for human identification with a high degree of accuracy and a high degree of reliability. This last assertion is due to the minimal to no risk for potential alteration of the intrinsic physiological characteristics seen through thermal infrared imaging. The proposed thermal facial signature recognition is fully integrated and consolidates the main and critical steps of feature extraction, registration, matching through similarity measures, and validation through testing our algorithm on a database, referred to as C-X1, provided by the Computer Vision Research Laboratory at the University of Notre Dame. Feature extraction was accomplished by first registering the infrared images to a reference image using the functional MRI of the Brain’s (FMRIB’s) Linear Image Registration Tool (FLIRT) modified to suit thermal infrared images. This was followed by segmentation of the facial region using an advanced localized contouring algorithm applied on anisotropically diffused thermal images. Thermal feature extraction from facial images was attained by performing morphological operations such as opening and top-hat segmentation to yield thermal signatures for each subject. Four thermal images taken over a period of six months were used to generate thermal signatures and a thermal template for each subject, the thermal template contains only the most prevalent and consistent features. Finally a similarity measure technique was used to match signatures to templates and the Principal Component Analysis (PCA) was used to validate the results of the matching process. Thirteen subjects were used for testing the developed technique on an in-house thermal imaging system. The matching using an Euclidean-based similarity measure showed 88% accuracy in the case of skeletonized signatures and templates, we obtained 90% accuracy for anisotropically diffused signatures and templates. We also employed the Manhattan-based similarity measure and obtained an accuracy of 90.39% for skeletonized and diffused templates and signatures. It was found that an average 18.9% improvement in the similarity measure was obtained when using diffused templates. The Euclidean- and Manhattan-based similarity measure was also applied to skeletonized signatures and templates of 25 subjects in the C-X1 database. The highly accurate results obtained in the matching process along with the generalized design process clearly demonstrate the ability of the thermal infrared system to be used on other thermal imaging based systems and related databases. A novel user-initialization registration of thermal facial images has been successfully implemented. Furthermore, the novel approach at developing a thermal signature template using four images taken at various times ensured that unforeseen changes in the vasculature did not affect the biometric matching process as it relied on consistent thermal features.

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One-third of botanical remedies from southern Italy are used to treat skin and soft tissue infections (SST's). Methicillin-resistant Staphylococcus aureus (MRSA), a common cause of SSTIs, is responsible for increased morbidity and mortality from infections. Therapeutic options are limited by antibiotic resistance. Many plants possess potent antimicrobial compounds for these disorders. Validation of traditional medical practices is important for the people who rely on medicinal plants. Moreover, identification of novel antibiotics and anti-pathogenic agents for MRSA is important to global healthcare.^ I took an ethnopharmacological approach to understand how Italian medicinal plants used for the treatment of SSTIs affect MRSA growth and virulence. My hypothesis was that plants used in folk remedies for SSTI would exhibit lower cytotoxicity and greater inhibition of bacterial growth, biofilm formation and toxin production in MRSA than plants used for remedies unrelated to the skin or for plants with no ethnomedical application. The field portion of my research was conducted in the Vulture-Alto Bradano area of southern Italy. I collected 104 plant species and created 168 crude extracts. In the lab, I screened samples for activity against MRSA in a battery of bioassays. Growth inhibition was analyzed using broth microtiter assays for determination of the minimum inhibitory concentration. Interference with quorum-sensing (QS) processes, which mediate pathogenicity, was quantified through RP-HPLC of δ-toxin production. Interference with biofilm formation and adherence was assessed using staining methods. The mammalian cytotoxicity of natural products was analyzed using MTT cell proliferation assay techniques.^ Although bacteriostatic activity was limited, extracts from six plants used in Italian folk medicine (Arundo donax, Ballota nigra, Juglans regia, Leopoldia comosa, Marrubium vulgare, and Rubus ulmifolius ) significantly inhibited biofilm formation and adherence. Moreover, plants used to treat SSTI demonstrated significantly greater anti-biofilm activity when compared to plants with no ethnomedical application. QSI activity was evident in 90% of the extracts tested and extracts from four plants ( Ballota nigra, Castanea saliva, Rosmarinus officinalis, and Sambucus ebulus) exhibited a significant dose-dependent response. Some of the plant remedies for SSTI identified in this study can be validated due to anti-MRSA activity.^

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One in 3,000 people in the US are born with cystic fibrosis (CF), a genetic disorder affecting the reproductive system, pancreas, and lungs. Lung disease caused by chronic bacterial and fungal infections is the leading cause of morbidity and mortality in CF. Identities of the microbes are traditionally determined by culturing followed by phenotypic and biochemical assays. It was first thought that the bacterial infections were caused by a select handful of bacteria such as S. aureus, H. influenzae, B. cenocepacia, and P. aeruginosa. With the advent of PCR and molecular techniques, the polymicrobial nature of the CF lung became evident. The CF lung contains numerous bacteria and the communities are diverse and unique to each patient. The total complexity of the bacterial infections is still being determined. In addition, only a few members of the fungal communities have been identified. Much of the fungal community composition is still a mystery. This dissertation addresses this gap in knowledge. A snap shot of CF sputa bacterial community was obtained using the length heterogeneity-PCR community profiling technique. The profiles show that south Florida CF patients have a unique, diverse, and dynamic bacterial community which changes over time. The identities of the bacteria and fungi present were determined using the state-of-the-art 454 sequencing. Sequencing results show that the CF lung microbiome contains commonly cultured pathogenic bacteria, organisms considered a part of the healthy core biome, and novel organisms. Understanding the dynamic changes of these identified microbes will ultimately lead to better therapeutical interventions. Early detection is key in reducing the lung damage caused by chronic infections. Thus, there is a need for accurate and sensitive diagnostic tests. This issue was addressed by designing a bacterial diagnostic tool targeted towards CF pathogens using SPR. By identifying the organisms associated with the CF lung and understanding their community interactions, patients can receive better treatment and live longer.