460 resultados para Brain monitoring
Resumo:
Airborne particles have been shown to be associated with a wide range of adverse health effects, which has led to a recent increase in medical research to gain better insight into their health effects. However, accurate evaluation of the exposure-dose-response relationship is highly dependent on the ability to track actual exposure levels of people to airborne particles. This is quite a complex task, particularly in relation to submicrometer and ultrafine particles, which can vary quite significantly in terms of particle surface area and number concentrations. Therefore, suitable monitors that can be worn for measuring personal exposure to these particles are needed. This paper presents an evaluation of the metrological performance of six diffusion charger sensors, NanoTracer (Philips Aerasense) monitors, when measuring particle number and surface area concentrations, as well as particle number distribution mean when compared to reference instruments. Tests in the laboratory (by generating monodisperse and polydisperse aerosols) and in the field (using natural ambient particles) were designed to evaluate the response of these devices under both steady-state and dynamics conditions. Results showed that the NanoTracers performed well when measuring steady state aerosols, however they strongly underestimated actual concentrations during dynamic response testing. The field experiments also showed that, when the majority of the particles were smaller than 20 nm, which occurs during particle formation events in the atmosphere, the NanoTracer underestimated number concentration quite significantly. Even though the NanoTracer can be used for personal monitoring of exposure to ultrafine particles, it also has limitations which need to be considered in order to provide meaningful results.
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Robotic systems are increasingly being utilised as fundamental data-gathering tools by scientists, allowing new perspectives and a greater understanding of the planet and its environmental processes. Today's robots are already exploring our deep oceans, tracking harmful algal blooms and pollution spread, monitoring climate variables, and even studying remote volcanoes. This article collates and discusses the significant advancements and applications of marine, terrestrial, and airborne robotic systems developed for environmental monitoring during the last two decades. Emerging research trends for achieving large-scale environmental monitoring are also reviewed, including cooperative robotic teams, robot and wireless sensor network (WSN) interaction, adaptive sampling and model-aided path planning. These trends offer efficient and precise measurement of environmental processes at unprecedented scales that will push the frontiers of robotic and natural sciences.
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The Lake Wivenhoe Integrated Wireless Sensor Network is conceptually similar to traditional SCADA monitoring and control approaches. However, it is applied in an open system using wireless devices to monitor processes that affect water quality at both a high spatial and temporal frequency. This monitoring assists scientists to better understand drivers of key processes that influence water quality and provide the operators with an early warning system if below standard water enters the reservoir. Both of these aspects improve the safety and efficient delivery of drinking water to the end users.
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Voltammetric techniques have been introduced to monitor the formation of gold nanoparticles produced via the reaction of the amino acid glycyl-L-tyrosine with Au(III) (bromoaurate) in 0.05 M KOH conditions. The alkaline conditions facilitate amino acid binding to Au(III), inhibit the rate of reduction to Au(0), and provide an excellent supporting electrolyte for voltammetric studies. Data obtained revealed that a range of time-dependent gold solution species are involved in gold nanoparticle formation and that the order in which reagents are mixed is critical to the outcome. Concomitantly with voltammetric measurements, the properties of gold nanoparticles formed are probed by examination of electronic spectra in order to understand how the solution environment present during nanoparticle growth affects the final distribution of the nanoparticles. Images obtained by the ex situ transmission electron microscopy (TEM) technique enable the physical properties of the nanoparticles isolated in the solid state to be assessed. Use of this combination of in situ and ex situ techniques provides a versatile framework for elucidating the details of nanoparticle formation.
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Scanning electrochemical microscopy (SECM), in the substrate generation–tip collection (SG-TC) mode, has been used to detect the cuprous ion intermediate formed during the course of electrodeposition of Cu metal from aqueous solution. Addition of chloride is confirmed to strongly stabilize the ion in aqueous solution and enhance the rate of Cu electrodeposition. This SECM method in the SG-TC mode offers an alternative to the rotating ring disk electrode (RRDE) technique for in situ studies on the effect of plating bath additives in metal electrodeposition. An attractive feature of the SECM relative to the RRDE method is that it allows qualitative aspects of the electrodeposition process to be studied in close proximity to the substrate in a simple and direct fashion using an inexpensive probe, and without the need for forced convection.
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Diagnosis threat is a psychosocial factor that has been proposed to contribute to poor outcomes following mild traumatic brain injury (mTBI). This threat is thought to impair the cognitive test performance of individuals with mTBI because of negative injury stereotypes. University students (N= 45, 62.2% female) with a history of mTBI were randomly allocated to a diagnosis threat (DT, n=15), reduced threat (DT-reduced, n=15) or neutral (n=15) group. The reduced threat condition invoked a positive stereotype (i.e., that people with mTBI can perform well on cognitive tests). All participants were given neutral instructions before they completed baseline tests of: a) objective cognitive function across a number of domains; b) psychological symptoms; and, c) PCS symptoms, including self-reported cognitive and emotional difficulties. Participants then received either neutral, DT or DT-reduced instructions, before repeating the tests. Results were analyzed using separate mixed model ANOVAs; one for each dependent measure. The only significant result was for the 2 X 3 ANOVA on an objective test of attention/working memory, Digit Span, p<.05, such that the DT-reduced group performed better than the other groups, which were not different from each other. Although not consistent with predictions or earlier DT studies, the absence of group differences on most tests fits with several recent DT findings. The results of this study suggest that it is timely to reconsider the role of DT as a unique contributor to poor mTBI outcome.
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Today, the majority of semiconductor fabrication plants (fabs) conduct equipment preventive maintenance based on statistically-derived time- or wafer-count-based intervals. While these practices have had relative success in managing equipment availability and product yield, the cost, both in time and materials, remains high. Condition-based maintenance has been successfully adopted in several industries, where costs associated with equipment downtime range from potential loss of life to unacceptable affects to companies’ bottom lines. In this paper, we present a method for the monitoring of complex systems in the presence of multiple operating regimes. In addition, the new representation of degradation processes will be used to define an optimization procedure that facilitates concurrent maintenance and operational decision-making in a manufacturing system. This decision-making procedure metaheuristically maximizes a customizable cost function that reflects the benefits of production uptime, and the losses incurred due to deficient quality and downtime. The new degradation monitoring method is illustrated through the monitoring of a deposition tool operating over a prolonged period of time in a major fab, while the operational decision-making is demonstrated using simulated operation of a generic cluster tool.
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This thesis examines the stewardship and investment style monitoring by managers and boards of U.S. equity funds. Results indicate that complying with a fund’s declared style, especially in value-growth dimension, remains a challenge for fund managers and boards, and that style-based investors should be aware of the risk of style drift since fund managers and boards do not always monitor the fund’s investment style as stated in the prospectus. Results also show that the quality of fund stewardship, as reflected by fund board quality, corporate culture, manager compensation, regulatory history, and fees are effective in ensuring that fund managers and boards perform their fiduciary obligation by increasing monitoring of the fund investment style.
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Purpose: To develop, using dacarbazine as a model, reliable techniques for measuring DNA damage and repair as pharmacodynamic endpoints for patients receiving chemotherapy. Methods: A group of 39 patients with malignant melanoma were treated with dacarbazine 1 g/m2 i.v. every 21 days. Tamoxifen 20 mg daily was commenced 24 h after the first infusion and continued until 3 weeks after the last cycle of chemotherapy. DNA strand breaks formed during dacarbazine-induced DNA damage and repair were measured in individual cells by the alkaline comet assay. DNA methyl adducts were quantified by measuring urinary 3-methyladenine (3-MeA) excretion using immunoaffinity ELISA. Venous blood was taken on cycles 1 and 2 for separation of peripheral blood lymphocytes (PBLs) for measurement of DNA strand breaks. Results: Wide interpatient variation in PBL DNA strand breaks occurred following chemotherapy, with a peak at 4 h (median 26.6 h, interquartile range 14.75- 40.5 h) and incomplete repair by 24 h. Similarly, there was a range of 3-MeA excretion with peak levels 4-10 h after chemotherapy (median 33 nmol/h, interquartile range 20.448.65 nmol/h). Peak 3-MeA excretion was positively correlated with DNA strand breaks at 4 h (Spearman's correlation coefficient, r = 0.39, P = 0.036) and 24 h (r = 0.46, P = 0.01). Drug-induced emesis correlated with PBL DNA strand breaks (Mann Whitney U-test, P = 0.03) but not with peak 3-MeA excretion. Conclusions: DNA damage and repair following cytotoxic chemotherapy can be measured in vivo by the alkaline comet assay and by urinary 3-MeA excretion in patients receiving chemotherapy.
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Diesel particulate matter (DPM), in particular, has been likened in a somewhat inflammatory manner to be the ‘next asbestos’. From the business change perspective, there are three areas holding the industry back from fully engaging with the issue: 1. There is no real feedback loop in any operational sense to assess the impact of investment or application of controls to manage diesel emissions. 2. DPM are getting ever smaller and more numerous, but there is no practical way of measuring them to regulate them in the field. Mass, the current basis of regulation, is becoming less and less relevant. 3. Diesel emissions management is generally wholly viewed as a cost, yet there are significant areas of benefit available from good management. This paper discusses a feedback approach to address these three areas to move the industry forward. The six main areas of benefit from providing a feedback loop by continuously monitoring diesel emissions have been identified: 1. Condition-based maintenance. Emissions change instantaneously if engine condition changes. 2. Operator performance. An operator can use a lot more fuel for little incremental work output through poor technique or discipline. 3. Vehicle utilisation. Operating hours achieved and ratios of idling to under power affect the proportion of emissions produced with no economic value. 4. Fuel efficiency. This allows visibility into other contributing configuration and environmental factors for the vehicle. 5. Emission rates. This allows scope to directly address the required ratio of ventilation to diesel emissions. 6. Total carbon emissions - for NGER-type reporting requirements, calculating the emissions individually from each vehicle rather than just reporting on fuel delivered to a site.
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Background Trials of new technologies to remotely monitor for signs and symptoms of worsening heart failure are continually emerging. The extent to which technological differences impact the effectiveness of non-invasive remote monitoring for heart failure management is unknown. Objective To examine the effect of specific technology used for non-invasive remote monitoring of people with heart failure on all-cause mortality and heart failure-related hospitalisations. Methods A sub-analysis of a large systematic review and meta-analysis was conducted. Studies were stratified according to the specific type of technology used and separate meta-analyses were performed. Four different types of non-invasive remote monitoring technologies were identified including structured telephone calls, videophone, interactive voice response devices and telemonitoring. Results Only structured telephone calls and telemonitoring were effective in reducing the risk of all-cause mortality (RR 0.87; 95% CI=0.75-1.01; p=0.06 and 0.62; 95% CI=0.50-0.77; p<0.0001) and heart failure-related hospitalisations (RR 0.77; 95% CI=0.68-0.87; p<0.001) and 0.75; 95% CI=0.63-0.91; p=0.003). More research data is required for videophone and interactive voice response technologies. Conclusions This sub-analysis identified that only two of the four specific technologies used for non-invasive remote monitoring in heart failure improved outcomes. When results of studies that involved these disparate technologies were combined in previous meta-analyses, significant improvements in outcomes were identified. As such, this study has highlighted implications for future meta-analyses of randomised controlled trials focused on evaluating the effectiveness of remote monitoring in heart failure.
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Food prices and food affordability are important determinants of food choices, obesity and non-communicable diseases. As governments around the world consider policies to promote the consumption of healthier foods, data on the relative price and affordability of foods, with a particular focus on the difference between ‘less healthy’ and ‘healthy’ foods and diets, are urgently needed. This paper briefly reviews past and current approaches to monitoring food prices, and identifies key issues affecting the development of practical tools and methods for food price data collection, analysis and reporting. A step-wise monitoring framework, including measurement indicators, is proposed. ‘Minimal’ data collection will assess the differential price of ‘healthy’ and ‘less healthy’ foods; ‘expanded’ monitoring will assess the differential price of ‘healthy’ and ‘less healthy’ diets; and the ‘optimal’ approach will also monitor food affordability, by taking into account household income. The monitoring of the price and affordability of ‘healthy’ and ‘less healthy’ foods and diets globally will provide robust data and benchmarks to inform economic and fiscal policy responses. Given the range of methodological, cultural and logistical challenges in this area, it is imperative that all aspects of the proposed monitoring framework are tested rigorously before implementation.
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Non-communicable diseases (NCDs) dominate disease burdens globally and poor nutrition increasingly contributes to this global burden. Comprehensive monitoring of food environments, and evaluation of the impact of public and private sector policies on food environments is needed to strengthen accountability systems to reduce NCDs. The International Network for Food and Obesity/NCDs Research, Monitoring and Action Support (INFORMAS) is a global network of public-interest organizations and researchers that aims to monitor, benchmark and support public and private sector actions to create healthy food environments and reduce obesity, NCDs and their related inequalities. The INFORMAS framework includes two ‘process’ modules, that monitor the policies and actions of the public and private sectors, seven ‘impact’ modules that monitor the key characteristics of food environments and three ‘outcome’ modules that monitor dietary quality, risk factors and NCD morbidity and mortality. Monitoring frameworks and indicators have been developed for 10 modules to provide consistency, but allowing for stepwise approaches (‘minimal’, ‘expanded’, ‘optimal’) to data collection and analysis. INFORMAS data will enable benchmarking of food environments between countries, and monitoring of progress over time within countries. Through monitoring and benchmarking, INFORMAS will strengthen the accountability systems needed to help reduce the burden of obesity, NCDs and their related inequalities.
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The International Network for Food and Obesity/non-communicable diseases Research, Monitoring and Action Support (INFORMAS) proposes to collect performance indicators on food policies, actions and environments related to obesity and non-communicable diseases. This paper reviews existing communications strategies used for performance indicators and proposes the approach to be taken for INFORMAS. Twenty-seven scoring and rating tools were identified in various fields of public health including alcohol, tobacco, physical activity, infant feeding and food environments. These were compared based on the types of indicators used and how they were quantified, scoring methods, presentation and the communication and reporting strategies used. There are several implications of these analyses for INFORMAS: the ratings/benchmarking approach is very commonly used, presumably because it is an effective way to communicate progress and stimulate action, although this has not been formally evaluated; the tools used must be trustworthy, pragmatic and policy-relevant; multiple channels of communication will be needed; communications need to be tailored and targeted to decision-makers; data and methods should be freely accessible. The proposed communications strategy for INFORMAS has been built around these lessons to ensure that INFORMAS's outputs have the greatest chance of being used to improve food environments.
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Government action is essential to increase the healthiness of food environments and reduce obesity, diet-related non-communicable diseases (NCDs), and their related inequalities. This paper proposes a monitoring framework to assess government policies and actions for creating healthy food environments. Recommendations from relevant authoritative organizations and expert advisory groups for reducing obesity and NCDs were examined, and pertinent components were incorporated into a comprehensive framework for monitoring government policies and actions. A Government Healthy Food Environment Policy Index (Food-EPI) was developed, which comprises a ‘policy’ component with seven domains on specific aspects of food environments, and an ‘infrastructure support’ component with seven domains to strengthen systems to prevent obesity and NCDs. These were revised through a week-long consultation process with international experts. Examples of good practice statements are proposed within each domain, and these will evolve into benchmarks established by governments at the forefront of creating and implementing food policies for good health. A rating process is proposed to assess a government's level of policy implementation towards good practice. The Food-EPI will be pre-tested and piloted in countries of varying size and income levels. The benchmarking of government policy implementation has the potential to catalyse greater action to reduce obesity and NCDs.