932 resultados para ANNEALING AMBIENT


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Many preanalytical variables affect the results of coagulation assays. A possible way to control some of them would be to accept blood specimens shipped in the original collection tube. The aim of our study was to investigate the stability of coagulation assays in citrated whole blood transported at ambient temperature for up to two days after specimen collection. Blood samples from 59 patients who attended our haematology outpatient ward for thrombophilia screening were transported at ambient temperature (outdoor during the day, indoor overnight) for following periods of time: <1 hour, 4-6, 8-12, 24-28 and 48-52 hours prior to centrifugation and plasma-freezing. The following coagulation tests were performed: PT, aPTT, fibrinogen, FII:C, FV:C, FVII:C, FVIII:C, FIX:C, FX:C, FXI:C, VWF:RCo, VWF:Ag, AT, PC activity, total and free PS antigen, modified APC-sensitivity-ratio, thrombin-antithrombin-complex and D-dimer. Clinically significant changes, defined as a percentage change of more than 10% from the initial value, were observed for FV:C, FVIII:C and total PS antigen starting at 24-28 hours, and for PT, aPTT and FVII:C at 48-52 hours. No statistically significant differences were seen for fibrinogen, antithrombin, or thrombin-antithrombin complexes (Friedman repeated measures analysis of variance). The present data suggest that the use of whole blood samples transported at ambient temperature may be an acceptable means of delivering specimens for coagulation analysis. With the exception of factor V and VIII coagulant activity, and total PS antigen all investigated parameters can be measured 24-28 hours after specimen collection without observing clinically relevant changes.

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The monolithic integration of dissimilar microsystems is often limited by conflicts in thermal budget. One of the most prevalent examples is the fabrication of active micro-electromechanical systems (MEMS), as structural films utilized for surface micromachining such as polysilicon typically require processing at temperatures unsuitable for microelectronic circuitry. A localized annealing process could provide for the post-deposition heat treatment of integrated structures without compromising active devices. This dissertation presents a new microfabrication technology based on the inductive heating of ferromagnetic films patterned to define regions for heat treatment. Support is provided through theory, finite-element modeling, and experimentation, concluding with the demonstration of inductive annealing on polysilicon inertial sensing structures. Though still in its infancy, the results confirm the technology to be a viable option for integrated MEMS as well as any microsystem fabrication process requiring a thermal gradient.

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ZnO has proven to be a multifunctional material with important nanotechnological applications. ZnO nanostructures can be grown in various forms such as nanowires, nanorods, nanobelts, nanocombs etc. In this work, ZnO nanostructures are grown in a double quartz tube configuration thermal Chemical Vapor Deposition (CVD) system. We focus on functionalized ZnO Nanostructures by controlling their structures and tuning their properties for various applications. The following topics have been investigated: 1. We have fabricated various ZnO nanostructures using a thermal CVD technique. The growth parameters were optimized and studied for different nanostructures. 2. We have studied the application of ZnO nanowires (ZnONWs) for field effect transistors (FETs). Unintentional n-type conductivity was observed in our FETs based on as-grown ZnO NWs. We have then shown for the first time that controlled incorporation of hydrogen into ZnO NWs can introduce p-type characters to the nanowires. We further found that the n-type behaviors remained, leading to the ambipolar behaviors of hydrogen incorporated ZnO NWs. Importantly, the detected p- and n- type behaviors are stable for longer than two years when devices were kept in ambient conditions. All these can be explained by an ab initio model of Zn vacancy-Hydrogen complexes, which can serve as the donor, acceptors, or green photoluminescence quencher, depend on the number of hydrogen atoms involved. 3. Next ZnONWs were tested for electron field emission. We focus on reducing the threshold field (Eth) of field emission from non-aligned ZnO NWs. As encouraged by our results on enhancing the conductivity of ZnO NWs by hydrogen annealing described in Chapter 3, we have studied the effect of hydrogen annealing for improving field emission behavior of our ZnO NWs. We found that optimally annealed ZnO NWs offered much lower threshold electric field and improved emission stability. We also studied field emission from ZnO NWs at moderate vacuum levels. We found that there exists a minimum Eth as we scale the threshold field with pressure. This behavior is explained by referring to Paschen’s law. 4. We have studied the application of ZnO nanostructures for solar energy harvesting. First, as-grown and (CdSe) ZnS QDs decorated ZnO NBs and ZnONWs were tested for photocurrent generation. All these nanostructures offered fast response time to solar radiation. The decoration of QDs decreases the stable current level produced by ZnONWs but increases that generated by NBs. It is possible that NBs offer more stable surfaces for the attachment of QDs. In addition, our results suggests that performance degradation of solar cells made by growing ZnO NWs on ITO is due to the increase in resistance of ITO after the high temperature growth process. Hydrogen annealing also improve the efficiency of the solar cells by decreasing the resistance of ITO. Due to the issues on ITO, we use Ni foil as the growth substrates. Performance of solar cells made by growing ZnO NWs on Ni foils degraded after Hydrogen annealing at both low (300 °C) and high (600 °C) temperatures since annealing passivates native defects in ZnONWs and thus reduce the absorption of visible spectra from our solar simulator. Decoration of QDs improves the efficiency of such solar cells by increasing absorption of light in the visible region. Using a better electrolyte than phosphate buffer solution (PBS) such as KI also improves the solar cell efficiency. 5. Finally, we have attempted p-type doping of ZnO NWs using various growth precursors including phosphorus pentoxide, sodium fluoride, and zinc fluoride. We have also attempted to create p-type carriers via introducing interstitial fluorine by annealing ZnO nanostructures in diluted fluorine gas. In brief, we are unable to reproduce the growth of reported p-type ZnO nanostructures. However; we have identified the window of temperature and duration of post-growth annealing of ZnO NWs in dilute fluorine gas which leads to suppression of native defects. This is the first experimental effort on post-growth annealing of ZnO NWs in dilute fluorine gas although this has been suggested by a recent theory for creating p-type semiconductors. In our experiments the defect band peak due to native defects is found to decrease by annealing at 300 °C for 10 – 30 minutes. One of the major future works will be to determine the type of charge carriers in our annealed ZnONWs.

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Carbon dioxide (CO2) capture and storage experiments were conducted at ambient conditions in varying weight % sodium carbonate (Na2CO3) solutions. Experiments were conducted to determine the optimal amount of Na2CO3 in solution for CO2 absorption. It was concluded that a 2% Na2CO3 solution, by weight, was the most efficient solution. The 2% Na2CO3 solution is able to absorb 0.5 g CO2/g Na2CO3. These results led to studies to determine how the gas bubble size affected carbon dioxide absorption in the solution. Studies were conducted using ASTM porosity gas diffusers to vary the bubble size. Gas diffusers with porosities of fine, medium, and extra coarse were used. Results found that the medium porosity gas diffuser was the most efficient at absorbing CO2 at 50%. Variation in the bubble size concluded that absorption of carbon dioxide into the sodium carbonate solution does depend on the bubble size, thus is mass transfer limited. Once the capture stage was optimized (amount of Na2CO3 in solution and bubble size), the next step was to determine if carbon dioxide could be stored as a calcium carbonate mineral using calcium rich industrial waste and if the sodium carbonate solution could be simultaneously regenerated. Studies of CO2 sequestration at ambient conditions have shown that it is possible to permanently sequester CO2 in the form of calcium carbonate using a calcium rich industrial waste. Studies have also shown that it is possible to regenerate a fraction of the sodium carbonate solution.

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Atmospheric aerosol water-soluble organic compounds (WSOC) exist in a complex mixture of thousands of organic compounds which may have a significant influence on the climate-relevant properties of the atmospheric aerosol. To understand the potential influences, the ambient aerosol was collected at a nonurban mountainous site near Steamboat Springs, CO. The WSOC fraction was analyzed using positive and negative electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry. Approximately 2400 and 4000 molecular formulas were identified from the detected positive and negative ions, respectively. The formulas contained carbon (C), hydrogen (H), oxygen (O), nitrogen (N), and sulfur (S) atoms over the mass range of 100-800 Da in both ionization modes. The number range of double bond equivalents (DBE), the mean O:C, H:C, and oxidation state of carbon for the positive ions were 0 – 18, 0.25 ± 0.15, 1.39 ± 0.29, and -0.89 ± 0.23, respectively. Comparatively, the negative ion values were 0 – 14, 0.53 ± 0.20, 1.48 ± 0.30, and -0.41 ± 0.45, respectively. Overall, the positive ion molecular formulas were less oxygenated than negative ions as seen with the lower O:C and OSc values. Molecular formulas of the positive ions classified as aliphatic, olefinic, and aromatic compound classes based on the aromaticity index values. Aliphatic compounds were the CHNO and CHO formulas that had mean DBE values of about 5 and 3, respectively. However, a majority of the CHOS, CHNOS, and CHS formulas were defined as olefinic compounds and had mean DBE values of about 12, 13, and 10, respectively. Overall, more than half of the assigned molecular formulas contained sulfur and were olefinic to aromatic compounds with a DBE range of 7-18. Source of the unsaturated sulfur containing compounds is currently unknown. Several nitrogen containing compounds were in common with the field and laboratory studies of the biomass burning aerosol and aged secondary organic aerosol products of the limonene ozonolysis.

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The most important element in the alloying of steels, has also been used quite extensively as a third constituent in copper-zinc alloys. The chief characteristics of nickel which make it desirable as an alloying element are its toughness, high strength, and resistance to corrosion.

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Funded by the US-EU Atlantis Program, the International Cooperation in Ambient Computing Education Project is establishing an international knowledge-building community for developing a broader computer science curriculum aimed at preparing students for real-world problems in a multidisciplinary, global world. The project is collaboration among Troy University (USA), University of Sunderland (UK), FernUniversität in Hagen (Germany), Universidade do Algarve (Portugal), University of Arkansas at Little Rock (USA) and San Diego State University (USA). The curriculum will include aspects of social science, cognitive science, human-computer interaction, organizational studies, global studies, and particular application areas as well as core computer science subjects. Programs offered at partner institutions will form trajectories through the curriculum. A degree will be defined in terms of combinations of trajectories which will satisfy degree requirements set by accreditation organizations. This is expected to lead to joint- or dual-degree programs among the partner institutions in the future. This paper describes the goals and activities of the project and discusses implementation issues.

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The 222Radon tracer method is a powerful tool to estimate local and regional surface emissions of, e.g., greenhouse gases. In this paper we demonstrate that in practice, the method as it is commonly used, produces inaccurate results in case of nonhomogeneously spread emission sources, and we propose a different approach to account for this. We have applied the new methodology to ambient observations of CO2 and 222Radon to estimate CO2 surface emissions for the city of Bern, Switzerland. Furthermore, by utilizing combined measurements of CO2 and δ(O2/N2) we obtain valuable information about the spatial and temporal variability of the main emission sources. Mean net CO2 emissions based on 2 years of observations are estimated at (11.2 ± 2.9) kt km−2 a−1. Oxidative ratios indicate a significant influence from the regional biosphere in summer/spring and fossil fuel combustion processes in winter/autumn. Our data indicate that the emissions from fossil fuels are, to a large degree, related to the combustion of natural gas which is used for heating purposes.

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BACKGROUND The number of older adults in the global population is increasing. This demographic shift leads to an increasing prevalence of age-associated disorders, such as Alzheimer's disease and other types of dementia. With the progression of the disease, the risk for institutional care increases, which contrasts with the desire of most patients to stay in their home environment. Despite doctors' and caregivers' awareness of the patient's cognitive status, they are often uncertain about its consequences on activities of daily living (ADL). To provide effective care, they need to know how patients cope with ADL, in particular, the estimation of risks associated with the cognitive decline. The occurrence, performance, and duration of different ADL are important indicators of functional ability. The patient's ability to cope with these activities is traditionally assessed with questionnaires, which has disadvantages (eg, lack of reliability and sensitivity). Several groups have proposed sensor-based systems to recognize and quantify these activities in the patient's home. Combined with Web technology, these systems can inform caregivers about their patients in real-time (e.g., via smartphone). OBJECTIVE We hypothesize that a non-intrusive system, which does not use body-mounted sensors, video-based imaging, and microphone recordings would be better suited for use in dementia patients. Since it does not require patient's attention and compliance, such a system might be well accepted by patients. We present a passive, Web-based, non-intrusive, assistive technology system that recognizes and classifies ADL. METHODS The components of this novel assistive technology system were wireless sensors distributed in every room of the participant's home and a central computer unit (CCU). The environmental data were acquired for 20 days (per participant) and then stored and processed on the CCU. In consultation with medical experts, eight ADL were classified. RESULTS In this study, 10 healthy participants (6 women, 4 men; mean age 48.8 years; SD 20.0 years; age range 28-79 years) were included. For explorative purposes, one female Alzheimer patient (Montreal Cognitive Assessment score=23, Timed Up and Go=19.8 seconds, Trail Making Test A=84.3 seconds, Trail Making Test B=146 seconds) was measured in parallel with the healthy subjects. In total, 1317 ADL were performed by the participants, 1211 ADL were classified correctly, and 106 ADL were missed. This led to an overall sensitivity of 91.27% and a specificity of 92.52%. Each subject performed an average of 134.8 ADL (SD 75). CONCLUSIONS The non-intrusive wireless sensor system can acquire environmental data essential for the classification of activities of daily living. By analyzing retrieved data, it is possible to distinguish and assign data patterns to subjects' specific activities and to identify eight different activities in daily living. The Web-based technology allows the system to improve care and provides valuable information about the patient in real-time.

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We present a new approach to the issues of spacetime singularities and cosmic censorship in general relativity. This is based on the idea that standard 4-dimensional spacetime is the conformal infinity of an ambient metric for the 5-dimensional Einstein equations with fluid sources. We then find that the existence of spacetime singularities in four dimensions is constrained by asymptotic properties of the ambient 5-metric, while the non-degeneracy of the latter crucially depends on cosmic censorship holding on the boundary.

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Smart homes for the aging population have recently started attracting the attention of the research community. The "health state" of smart homes is comprised of many different levels; starting with the physical health of citizens, it also includes longer-term health norms and outcomes, as well as the arena of positive behavior changes. One of the problems of interest is to monitor the activities of daily living (ADL) of the elderly, aiming at their protection and well-being. For this purpose, we installed passive infrared (PIR) sensors to detect motion in a specific area inside a smart apartment and used them to collect a set of ADL. In a novel approach, we describe a technology that allows the ground truth collected in one smart home to train activity recognition systems for other smart homes. We asked the users to label all instances of all ADL only once and subsequently applied data mining techniques to cluster in-home sensor firings. Each cluster would therefore represent the instances of the same activity. Once the clusters were associated to their corresponding activities, our system was able to recognize future activities. To improve the activity recognition accuracy, our system preprocessed raw sensor data by identifying overlapping activities. To evaluate the recognition performance from a 200-day dataset, we implemented three different active learning classification algorithms and compared their performance: naive Bayesian (NB), support vector machine (SVM) and random forest (RF). Based on our results, the RF classifier recognized activities with an average specificity of 96.53%, a sensitivity of 68.49%, a precision of 74.41% and an F-measure of 71.33%, outperforming both the NB and SVM classifiers. Further clustering markedly improved the results of the RF classifier. An activity recognition system based on PIR sensors in conjunction with a clustering classification approach was able to detect ADL from datasets collected from different homes. Thus, our PIR-based smart home technology could improve care and provide valuable information to better understand the functioning of our societies, as well as to inform both individual and collective action in a smart city scenario.