232 resultados para SENSITIVE DETERMINATION


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Collagen crosslinking (CXL) has shown promising results in the prevention of the progression of keratoconus and corneal ectasia. However, techniques for in vivo and in situ assessment of the treatment are limited. In this study, ex vivo porcine eyes were treated with a chemical CXL agent (glutaraldehyde), during which polarization sensitive optical coherence tomography (PS-OCT) recordings were acquired simultaneously to assess the sensitivity of the technique to assess changes in the cornea. The results obtained in this study suggest that PS-OCT may be a suitable technique to measure CXL changes in situ and to assess the local changes in the treated region of the cornea.

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This thesis investigates the use of near infrared (NIR) spectroscopic methods for rapid measurement of nutrient elements in mill mud and mill ash. Adoption of NIR-based analyses for carbon, nitrogen, phosphorus, potassium and silicon will allow Australian sugarcane farmers to comply with recent legislative changes, and act within recommended precision farming frameworks. For these analyses, NIR spectroscopic methods surpass several facets of traditional wet chemistry techniques, dramatically reducing costs, required expertise and chemical exposure, while increasing throughput and access to data. Further, this technology can be applied in various modes, including laboratory, at-line and on-line installations, allowing targeted measurement.

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Isofraxidin is one of the main bioactive constituents in the root of Acanthopanax senticosus, which has antifatigue, antistress, and immuno-accommondating effects. In this study, an ultraperformance LC (UPLC)-ESI MS method was developed for analyzing isofraxidin and its metabolites in rat plasma. The analysis was performed on a UPLC coupled with ESI MS (quadropole MS tandem TOF MS). The lower LOD (LLOD) for isofraxidin was 0.25 ng/mL, the intraday precision was less than 10%, the interday precision was less than 10%, and the extraction recovery was more than 80%. Isofraxidin and two metabolites (M1 and M2) were detected in rat plasma after oral administration of isofraxidin, and the molecular polarities of M1 and M2 were both increased compared to isofraxidin. The metabolites were identified as 5,6-dihydroxyl-7-methoxycoumarin and 5-hydroxyl-6,7-dimethoxycoumarin when subjected to parent ion spectra, product ion spectra, and extract mass and element composition analyses.

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Electrochemical processes in mesoporous TiO2-Nafion thin films deposited on indium tin oxide (ITO) electrodes are inherently complex and affected by capacitance, Ohmic iR-drop, RC-time constant phenomena, and by potential and pH-dependent conductivity. In this study, large-amplitude sinusoidally modulated voltammetry (LASMV) is employed to provide access to almost purely Faradaic-based current data from second harmonic components, as well as capacitance and potential domain information from the fundamental harmonic for mesoporous TiO2-Nafion film electrodes. The LASMV response has been investigated with and without an immobilized one-electron redox system, ferrocenylmethyltrimethylammonium+. Results clearly demonstrate that the electron transfer associated with the immobilized ferrocene derivative follows two independent pathways i) electron hopping within the Nafion network and ii) conduction through the TiO2 backbone. The pH effect on the voltammetric response for the TiO2 reduction pathway (ii) can be clearly identified in the 2nd harmonic LASMV response with the diffusion controlled ferrocene response (i) acting as a pH independent reference. Application of second harmonic data derived from LASMV measurement, because of the minimal contribution from capacitance currents, may lead to reference-free pH sensing with systems like that found for ferrocene derivatives.

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We present a mini-review of the development and contemporary applications of diffusion-sensitive nuclear magnetic resonance (NMR) techniques in biomedical sciences. Molecular diffusion is a fundamental physical phenomenon present in all biological systems. Due to the connection between experimentally measured diffusion metrics and the microscopic environment sensed by the diffusing molecules, diffusion measurements can be used for characterisation of molecular size, molecular binding and association, and the morphology of biological tissues. The emergence of magnetic resonance was instrumental to the development of biomedical applications of diffusion. We discuss the fundamental physical principles of diffusion NMR spectroscopy and diffusion MR imaging. The emphasis is placed on conceptual understanding, historical evolution and practical applications rather than complex technical details. Mathematical description of diffusion is presented to the extent that it is required for the basic understanding of the concepts. We present a wide range of spectroscopic and imaging applications of diffusion magnetic resonance, including colloidal drug delivery vehicles; protein association; characterisation of cell morphology; neural fibre tractography; cardiac imaging; and the imaging of load-bearing connective tissues. This paper is intended as an accessible introduction into the exciting and growing field of diffusion magnetic resonance.

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The majority of patients with non-small-cell lung cancer (NSCLC) present with advanced disease, with targeted therapies providing some improvement in clinical outcomes. The epidermal growth factor receptor (EGFR) tyrosine kinase (TK) plays an important role in the pathogenesis of NSCLC. Tyrosine kinase inhibitors (TKIs), which target the EGFR TK domain, have proven to be an effective treatment strategy; however, patient responses to treatment vary considerably. Therefore, the identification of patients most likely to respond to treatment is essential to optimise the benefit of TKIs. Tumour-associated activating mutations in EGFR can identify patients with NSCLC who are likely to have a good response to TKIs. Nonetheless, the majority of patients relapse within a year of starting treatment. Studies of tumours at relapse have demonstrated expression of a T790M mutation in exon 20 of the EGFR TK domain in approximately 50% of cases. Although conferring resistance to reversible TKIs, these patients may remain sensitive to new-generation irreversible/panerb inhibitors. A number of techniques have been employed for genotypic assessment of tumourassociated DNA to identify EGFR mutations, each of which has advantages and disadvantages. This review presents an overview of the current methodologies used to identify such molecular markers. Recent developments in technology may make the monitoring of changes in patients' tumour genotypes easier in clinical practice, which may enable patients' treatment regimens to be tailored during the course of their disease, potentially leading to improved patient outcomes.

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The focus of this paper is on an Australian research project that evaluated the effectiveness of a resource called the Ask Health Diary, which is used in the school curriculum to promote self-determination for better health and wellbeing for adolescents who have an intellectual disability. Education and health researchers used questionnaires and interviews to gather data from adolescents attending special schools and special education units located in secondary schools in south-east Queensland, their teachers and their parents/carers. This paper reports on two research questions: First, ‘How did the teachers use the Ask Health Diary to promote self-determination in health?’, and second, ‘How did teachers, parents/carers and students perceive the benefits and value of the Ask Health Diary?’ The findings indicate that the Ask Health Diary provides a sound curriculum framework for teachers, adolescents and parents/carers to work together to promote self-determination and better health outcomes for young people who have an intellectual disability.

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Big Data presents many challenges related to volume, whether one is interested in studying past datasets or, even more problematically, attempting to work with live streams of data. The most obvious challenge, in a ‘noisy’ environment such as contemporary social media, is to collect the pertinent information; be that information for a specific study, tweets which can inform emergency services or other responders to an ongoing crisis, or give an advantage to those involved in prediction markets. Often, such a process is iterative, with keywords and hashtags changing with the passage of time, and both collection and analytic methodologies need to be continually adapted to respond to this changing information. While many of the data sets collected and analyzed are preformed, that is they are built around a particular keyword, hashtag, or set of authors, they still contain a large volume of information, much of which is unnecessary for the current purpose and/or potentially useful for future projects. Accordingly, this panel considers methods for separating and combining data to optimize big data research and report findings to stakeholders. The first paper considers possible coding mechanisms for incoming tweets during a crisis, taking a large stream of incoming tweets and selecting which of those need to be immediately placed in front of responders, for manual filtering and possible action. The paper suggests two solutions for this, content analysis and user profiling. In the former case, aspects of the tweet are assigned a score to assess its likely relationship to the topic at hand, and the urgency of the information, whilst the latter attempts to identify those users who are either serving as amplifiers of information or are known as an authoritative source. Through these techniques, the information contained in a large dataset could be filtered down to match the expected capacity of emergency responders, and knowledge as to the core keywords or hashtags relating to the current event is constantly refined for future data collection. The second paper is also concerned with identifying significant tweets, but in this case tweets relevant to particular prediction market; tennis betting. As increasing numbers of professional sports men and women create Twitter accounts to communicate with their fans, information is being shared regarding injuries, form and emotions which have the potential to impact on future results. As has already been demonstrated with leading US sports, such information is extremely valuable. Tennis, as with American Football (NFL) and Baseball (MLB) has paid subscription services which manually filter incoming news sources, including tweets, for information valuable to gamblers, gambling operators, and fantasy sports players. However, whilst such services are still niche operations, much of the value of information is lost by the time it reaches one of these services. The paper thus considers how information could be filtered from twitter user lists and hash tag or keyword monitoring, assessing the value of the source, information, and the prediction markets to which it may relate. The third paper examines methods for collecting Twitter data and following changes in an ongoing, dynamic social movement, such as the Occupy Wall Street movement. It involves the development of technical infrastructure to collect and make the tweets available for exploration and analysis. A strategy to respond to changes in the social movement is also required or the resulting tweets will only reflect the discussions and strategies the movement used at the time the keyword list is created — in a way, keyword creation is part strategy and part art. In this paper we describe strategies for the creation of a social media archive, specifically tweets related to the Occupy Wall Street movement, and methods for continuing to adapt data collection strategies as the movement’s presence in Twitter changes over time. We also discuss the opportunities and methods to extract data smaller slices of data from an archive of social media data to support a multitude of research projects in multiple fields of study. The common theme amongst these papers is that of constructing a data set, filtering it for a specific purpose, and then using the resulting information to aid in future data collection. The intention is that through the papers presented, and subsequent discussion, the panel will inform the wider research community not only on the objectives and limitations of data collection, live analytics, and filtering, but also on current and in-development methodologies that could be adopted by those working with such datasets, and how such approaches could be customized depending on the project stakeholders.

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The μO-conotoxins are an intriguing class of conotoxins targeting various voltage-dependent sodium channels and molluscan calcium channels. In the current study, we have shown MrVIA and MrVIB to be the first known peptidic inhibitors of the transient tetrodotoxin-resistant (TTX-R) Na+ current in rat dorsal root ganglion neurons, in addition to inhibiting tetrodotoxin-sensitive Na+ currents. Human TTX-R sodium channels are a therapeutic target for indications such as pain, highlighting the importance of the μO-conotoxins as potential leads for drug development. Furthermore, we have used NMR spectroscopy to provide the first structural information on this class of conotoxins. MrVIA and MrVIB are hydrophobic peptides that aggregate in aqueous solution but were solubilized in 50% acetonitrile/water. The three-dimensional structure of MrVIB consists of a small β-sheet and a cystine knot arrangement of the three-disulfide bonds. It contains four backbone “loops” between successive cysteine residues that are exposed to the solvent to varying degrees. The largest of these, loop 2, is the most disordered part of the molecule, most likely due to flexibility in solution. This disorder is the most striking difference between the structures of MrVIB and the known δ- and ω-conotoxins, which along with the μO-conotoxins are members of the O superfamily. Loop 2 of ω-conotoxins has previously been shown to contain residues critical for binding to voltage-gated calcium channels, and it is interesting to speculate that the flexibility observed in MrVIB may accommodate binding to both sodium and molluscan calcium channels.

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The safe working lifetime of a structure in a corrosive or other harsh environment is frequently not limited by the material itself but rather by the integrity of the coating material. Advanced surface coatings are usually crosslinked organic polymers such as epoxies and polyurethanes which must not shrink, crack or degrade when exposed to environmental extremes. While standard test methods for environmental durability of coatings have been devised, the tests are structured more towards determining the end of life rather than in anticipation of degradation. We have been developing prognostic tools to anticipate coating failure by using a fundamental understanding of their degradation behaviour which, depending on the polymer structure, is mediated through hydrolytic or oxidation processes. Fourier transform infrared spectroscopy (FTIR) is a widely-used laboratory technique for the analysis of polymer degradation and with the development of portable FTIR spectrometers, new opportunities have arisen to measure polymer degradation non-destructively in the field. For IR reflectance sampling, both diffuse (scattered) and specular (direct) reflections can occur. The complexity in these spectra has provided interesting opportunities to study surface chemical and physical changes during paint curing, service abrasion and weathering, but has often required the use of advanced statistical analysis methods such as chemometrics to discern these changes. Results from our studies using this and related techniques and the technical challenges that have arisen will be presented.

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Using Gray and McNaughton’s revised RST, this study investigated the extent to which the Behavioural Approach System (BAS) and the Fight-Flight-Freeze System (FFFS) influence the processing of gain-framed and loss-framed road safety messages and subsequent message acceptance. It was predicted that stronger BAS sensitivity and FFFS sensitivity would be associated with greater processing and acceptance of the gain-framed messages and loss-framed messages, respectively. Young drivers (N = 80, aged 17–25 years) viewed one of four road safety messages and completed a lexical decision task to assess message processing. Both self-report (e.g., Corr-Cooper RST-PQ) and behavioural measures (i.e., CARROT and Q-Task) were used to assess BAS and FFFS traits. Message acceptance was measured via self-report ratings of message effectiveness, behavioural intentions, attitudes and subsequent driving behaviour. The results are discussed in the context of the effect that differences in reward and punishment sensitivities may have on message processing and message acceptance.

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This paper presents a new method to determine feeder reconfiguration scheme considering variable load profile. The objective function consists of system losses, reliability costs and also switching costs. In order to achieve an optimal solution the proposed method compares these costs dynamically and determines when and how it is reasonable to have a switching operation. The proposed method divides a year into several equal time periods, then using particle swarm optimization (PSO), optimal candidate configurations for each period are obtained. System losses and customer interruption cost of each configuration during each period is also calculated. Then, considering switching cost from a configuration to another one, dynamic programming algorithm (DPA) is used to determine the annual reconfiguration scheme. Several test systems were used to validate the proposed method. The obtained results denote that to have an optimum solution it is necessary to compare operation costs dynamically.

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Modern lipidomics relies heavily on mass spectrometry for the structural characterization and quantification of lipids of biological origins. Structural information is gained by tandem mass spectrometry (MS/MS) whereby lipid ions are fragmented to elucidate lipid class, fatty acid chain length, and degree of unsaturation. Unfortunately, however, in most cases double bond position cannot be assigned based on MS/MS data alone and thus significant structural diversity is hidden from such analyses. For this reason, we have developed two online methods for determining double bond position within unsaturated lipids; ozone electrospray ionization mass spectrometry (OzESI-MS) and ozone-induced dissociation (OzID). Both techniques utilize ozone to cleave C-C double bonds that result in chemically induced fragment ions that locate the position(s) of unsaturation

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Rapidly increasing electricity demands and capacity shortage of transmission and distribution facilities are the main driving forces for the growth of Distributed Generation (DG) integration in power grids. One of the reasons for choosing a DG is its ability to support voltage in a distribution system. Selection of effective DG characteristics and DG parameters is a significant concern of distribution system planners to obtain maximum potential benefits from the DG unit. This paper addresses the issue of improving the network voltage profile in distribution systems by installing a DG of the most suitable size, at a suitable location. An analytical approach is developed based on algebraic equations for uniformly distributed loads to determine the optimal operation, size and location of the DG in order to achieve required levels of network voltage. The developed method is simple to use for conceptual design and analysis of distribution system expansion with a DG and suitable for a quick estimation of DG parameters (such as optimal operating angle, size and location of a DG system) in a radial network. A practical network is used to verify the proposed technique and test results are presented.