954 resultados para rapid-thermal-annealing


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A rapid electrochemical method based on using a clean hydrogen-bubble template to form a bimetallic porous honeycomb Cu/Pd structure has been investigated. The addition of palladium salt to a copper-plating bath under conditions of vigorous hydrogen evolution was found to influence the pore size and bulk concentration of copper and palladium in the honeycomb bimetallic structure. The surface was characterised by X-ray photoelectron spectroscopy, which revealed that the surface of honeycomb Cu/Pd was found to be rich with a Cu/Pd alloy. The inclusion of palladium in the bimetallic structure not only influenced the pore size, but also modified the dendritic nature of the internal wall structure of the parent copper material into small nanometre-sized crystallites. The chemical composition of the bimetallic structure and substantial morphology changes were found to significantly influence the surface-enhanced Raman spectroscopic response for immobilised rhodamine B and the hydrogen-evolution reaction. The ability to create free-standing films of this honeycomb material may also have many advantages in the areas of gas- and liquid-phase heterogeneous catalysis.

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Multi-Objective optimization for designing of a benchmark cogeneration system known as CGAM cogeneration system has been performed. In optimization approach, the thermoeconomic and Environmental aspects have been considered, simultaneously. The environmental objective function has been defined and expressed in cost terms. One of the most suitable optimization techniques developed using a particular class of search algorithms known as; Multi-Objective Particle Swarm Optimization (MOPSO) algorithm has been used here. This approach has been applied to find the set of Pareto optimal solutions with respect to the aforementioned objective functions. An example of fuzzy decision-making with the aid of Bellman-Zadeh approach has been presented and a final optimal solution has been introduced.

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The Australian Commission on Safety and Quality in Health Care commissioned this rapid review to identify recent evidence in relation to three key questions: 1. What is the current evidence of quality and safety issues regarding the hospital experience of people with cognitive impairment (dementia/delirium)? 2. What are the existing evidence-based pathways, best practice or guidelines for cognitive impairment in hospitals? 3. What are the key components of an ideal patient journey for a person with dementia and/or delirium? The purpose of this review is to identify best practice in caring for patients with cognitive impairment (CI) in acute hospital settings. CI refers to patients with dementia and delirium but can include other conditions. For the purposes of this report, ‘Hospitals’ is defined as acute care settings and includes care provided by acute care institutions in other settings (e.g. Multipurpose Services and Hospital in the Home). It does not include residential aged care settings nor palliative care services that are not part of a service provided by an acute care institution. Method Both peer-reviewed publications and the grey literature were comprehensively searched for recent (primarily post 2010) publications, reports and guidelines that addressed the three key questions. The literature was evaluated and graded according to the National Health and Medical Research Council (NHMRC) levels of criteria (see Evidence Summary – Appendix B). Results Thirty-one recent publications were retrieved in relation to quality and safety issues faced by people with CI in acute hospitals. The results indicate that CI is a common problem in hospitals (upwards of 30% - the rate increases with increasing patient age), although this is likely to be an underestimate, in part, due to numbers of patients without a formal dementia diagnosis. There is a large body of evidence showing that patients with CI have worse outcomes than patients without CI following hospitalisation including increased mortality, more complications, longer hospital stays, increased system costs as well as functional and cognitive decline. 4 To improve the care of patients with CI in hospital, best practice guidelines have been developed, of which sixteen recent guidelines/position statements/standards were identified in this review (Table 2). Four guidelines described standards or quality indicators for providing optimal care for the older person with CI in hospital, in general, while three focused on delirium diagnosis, prevention and management. The remaining guidelines/statements focused on specific issues in relation to the care of patients with CI in acute hospitals including hydration, nutrition, wandering and care in the Emergency Department (ED). A key message in several of the guidelines was that older patients should be assessed for CI at admission and this is particularly important in the case of delirium, which can indicate an emergency, in order to implement treatment. A second clear mess...

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Faulted stacking layers are ubiquitously observed during the crystal growth of semiconducting nanowires (NWs). In this paper, we employ the reverse non-equilibrium molecular dynamics simulation to elucidate the effect of various faulted stacking layers on the thermal conductivity (TC) of silicon (Si) NWs. We find that the stacking faults can greatly reduce the TC of the Si NW. Among the different stacking faults that are parallel to the NW's axis, the 9R polytype structure, the intrinsic and extrinsic stacking faults (iSFs and eSFs) exert more pronounced effects in the reduction of TC than the twin boundary (TB). However, for the perpendicularly aligned faulted stacking layers, the eSFs and 9R polytype structures are observed to induce a larger reduction to the TC of the NW than the TB and iSFs. For all considered NWs, the TC does not show a strong relation with the increasing number of faulted stacking layers. Our studies suggest the possibility of tuning the thermal properties of Si NWs by altering the crystal structure via the different faulted stacking layers.

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Acoustic sensing is a promising approach to scaling faunal biodiversity monitoring. Scaling the analysis of audio collected by acoustic sensors is a big data problem. Standard approaches for dealing with big acoustic data include automated recognition and crowd based analysis. Automatic methods are fast at processing but hard to rigorously design, whilst manual methods are accurate but slow at processing. In particular, manual methods of acoustic data analysis are constrained by a 1:1 time relationship between the data and its analysts. This constraint is the inherent need to listen to the audio data. This paper demonstrates how the efficiency of crowd sourced sound analysis can be increased by an order of magnitude through the visual inspection of audio visualized as spectrograms. Experimental data suggests that an analysis speedup of 12× is obtainable for suitable types of acoustic analysis, given that only spectrograms are shown.

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Motivation: Gene silencing, also called RNA interference, requires reliable assessment of silencer impacts. A critical task is to find matches between silencer oligomers and sites in the genome, in accordance with one-to-many matching rules (G-U matching, with provision for mismatches). Fast search algorithms are required to support silencer impact assessments in procedures for designing effective silencer sequences.Results: The article presents a matching algorithm and data structures specialized for matching searches, including a kernel procedure that addresses a Boolean version of the database task called the skyline search. Besides exact matches, the algorithm is extended to allow for the location-specific mismatches applicable in plants. Computational tests show that the algorithm is significantly faster than suffix-tree alternatives. © The Author 2010. Published by Oxford University Press. All rights reserved.

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A very simple leaf assay is described that rapidly and reliably identifies transgenic plants expressing the hygromycin resistance gene, hph or the phosphinothricin resistance gene, bar. Leaf tips were cut from plants propagated either in the glasshouse or in tissue culture and the cut surface embedded in solid medium containing the appropriate selective agent. Non-transgenic barley or rice leaf tips had noticeable symptoms of either bleaching or necrosis after three days on the medium and were completely bleached or necrotic after one week. Transgenic leaf tips remained green and healthy over this period. This gave unambiguous discrimination between transgenic and non-transgenic plants. The leaf assay was also effective for dicot plants tested (tobacco and peas).

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A series of NR composites filled with modified kaolinite (MK), carbon black (CB) and the hybrid fillercontained MK and CB, were prepared by melt blending. The microstructure, combustion and thermaldecomposition behaviors of NR composites were characterized by TEM, XRD, infrared spectroscopy, conecalorimeter test (CCT) and thermal-gravimetric analysis (TG). The results show that the filler hybridizationcan improve the dispensability and shape of the kaolinite sheets in the rubber matrix and change theinterface bond between kaolinite particles and rubber molecules. NR-3 filled by 10 phr MK and 40 phr CBhas the lowest heat release rate (HRR), mass loss rate (MLR), total heat release (THR), smoke productionrate (SPR) and the highest char residue among all the NR composites. Therefore, the hybridization ofthe carbon black particles with the kaolinite particles can effectively improve the thermal stability andcombustion properties of NR composites.

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Flow induced shear stress plays an important role in regulating cell growth and distribution in scaffolds. This study sought to correlate wall shear stress and chondrocytes activity for engineering design of micro-porous osteochondral grafts based on the hypothesis that it is possible to capture and discriminate between the transmitted force and cell response at the inner irregularities. Unlike common tissue engineering therapies with perfusion bioreactors in which flow-mediated stress is the controlling parameter, this work assigned the associated stress as a function of porosity to influence in vitro proliferation of chondrocytes. D-optimality criterion was used to accommodate three pore characteristics for appraisal in a mixed level fractional design of experiment (DOE); namely, pore size (4 levels), distribution pattern (2 levels) and density (3 levels). Micro-porous scaffolds (n=12) were fabricated according to the DOE using rapid prototyping of an acrylic-based bio-photopolymer. Computational fluid dynamics (CFD) models were created correspondingly and used on an idealized boundary condition with a Newtonian fluid domain to simulate the dynamic microenvironment inside the pores. In vitro condition was reproduced for the 3D printed constructs seeded by high pellet densities of human chondrocytes and cultured for 72 hours. The results showed that cell proliferation was significantly different in the constructs (p<0.05). Inlet fluid velocity of 3×10-2mms-1 and average shear stress of 5.65×10-2 Pa corresponded with increased cell proliferation for scaffolds with smaller pores in hexagonal pattern and lower densities. Although the analytical solution of a Poiseuille flow inside the pores was found insufficient for the description of the flow profile probably due to the outside flow induced turbulence, it showed that the shear stress would increase with cell growth and decrease with pore size. This correlation demonstrated the basis for determining the relation between the induced stress and chondrocyte activity to optimize microfabrication of engineered cartilaginous constructs.

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Objective This investigation utilised the expertise of allied members of multidisciplinary teams working in emergency care settings to develop and validate a Rapid Assessment Prioritisation and Referral Tool (RAPaRT). This instrument is intended for use among patients (with non-life threatening acuity) presenting to emergency care settings to indicate when referral to an allied member of the multidisciplinary team is warranted. Method This three stage instrument development and validation study included: a Delphi panel process to determine key criteria to guide instrument development and identify potential items to be carried forward for testing (stage 1); a prospective cohort of consecutive admissions (n=153) to investigate item sensitivity and specificity and retain only the most suitable items (stage 2); then final consultation with the Delphi panel to ensure the final instrument was clinically amenable (stage 3). Results 23 potential items were identified following stage 1. At the completion of item sensitivity and specificity analysis and in consultation with the Delphi panel, seven items were retained in the instrument. Area under the receiver operating characteristic curve was 0.803 for these seven items in predicting when a referral was warranted. Final consultation with the Delphi panel members also resulted in the addition of an open ended (eighth) item to allow description of any infrequent, but important, reason for referral. Conclusions The RAPaRT has demonstrated substantial promise as an efficient clinically amenable instrument to assist multidisciplinary teams in emergency care settings. Further research to investigate the wider implementation of the RAPaRT is warranted.

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This paper presents mathematical models for BRT station operation, calibrated using microscopic simulation modelling. Models are presented for station capacity and bus queue length. No reliable model presently exists to estimate bus queue length. The proposed bus queue model is analogous to an unsignalized intersection queuing model.

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Stations on Bus Rapid Transit (BRT) lines ordinarily control line capacity because they act as bottlenecks. At stations with passing lanes, congestion may occur when buses maneuvering into and out of the platform stopping lane interfere with bus flow, or when a queue of buses forms upstream of the station blocking inflow. We contend that, as bus inflow to the station area approaches capacity, queuing will become excessive in a manner similar to operation of a minor movement on an unsignalized intersection. This analogy is used to treat BRT station operation and to analyze the relationship between station queuing and capacity. In the first of three stages, we conducted microscopic simulation modeling to study and analyze operating characteristics of the station under near steady state conditions through output variables of capacity, degree of saturation and queuing. A mathematical model was then developed to estimate the relationship between average queue and degree of saturation and calibrated for a specified range of controlled scenarios of mean and coefficient of variation of dwell time. Finally, simulation results were calibrated and validated.

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Railway crew scheduling problem is the process of allocating train services to the crew duties based on the published train timetable while satisfying operational and contractual requirements. The problem is restricted by many constraints and it belongs to the class of NP-hard. In this paper, we develop a mathematical model for railway crew scheduling with the aim of minimising the number of crew duties by reducing idle transition times. Duties are generated by arranging scheduled trips over a set of duties and sequentially ordering the set of trips within each of duties. The optimisation model includes the time period of relief opportunities within which a train crew can be relieved at any relief point. Existing models and algorithms usually only consider relieving a crew at the beginning of the interval of relief opportunities which may be impractical. This model involves a large number of decision variables and constraints, and therefore a hybrid constructive heuristic with the simulated annealing search algorithm is applied to yield an optimal or near-optimal schedule. The performance of the proposed algorithms is evaluated by applying computational experiments on randomly generated test instances. The results show that the proposed approaches obtain near-optimal solutions in a reasonable computational time for large-sized problems.

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The support for typically out-of-vocabulary query terms such as names, acronyms, and foreign words is an important requirement of many speech indexing applications. However, to date many unrestricted vocabulary indexing systems have struggled to provide a balance between good detection rate and fast query speeds. This paper presents a fast and accurate unrestricted vocabulary speech indexing technique named Dynamic Match Lattice Spotting (DMLS). The proposed method augments the conventional lattice spotting technique with dynamic sequence matching, together with a number of other novel algorithmic enhancements, to obtain a system that is capable of searching hours of speech in seconds while maintaining excellent detection performance

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Long-term autonomy in robotics requires perception systems that are resilient to unusual but realistic conditions that will eventually occur during extended missions. For example, unmanned ground vehicles (UGVs) need to be capable of operating safely in adverse and low-visibility conditions, such as at night or in the presence of smoke. The key to a resilient UGV perception system lies in the use of multiple sensor modalities, e.g., operating at different frequencies of the electromagnetic spectrum, to compensate for the limitations of a single sensor type. In this paper, visual and infrared imaging are combined in a Visual-SLAM algorithm to achieve localization. We propose to evaluate the quality of data provided by each sensor modality prior to data combination. This evaluation is used to discard low-quality data, i.e., data most likely to induce large localization errors. In this way, perceptual failures are anticipated and mitigated. An extensive experimental evaluation is conducted on data sets collected with a UGV in a range of environments and adverse conditions, including the presence of smoke (obstructing the visual camera), fire, extreme heat (saturating the infrared camera), low-light conditions (dusk), and at night with sudden variations of artificial light. A total of 240 trajectory estimates are obtained using five different variations of data sources and data combination strategies in the localization method. In particular, the proposed approach for selective data combination is compared to methods using a single sensor type or combining both modalities without preselection. We show that the proposed framework allows for camera-based localization resilient to a large range of low-visibility conditions.