443 resultados para Agar diffusion method
Resumo:
A novel method was developed for studying the genetic relatedness of Pseudomonas aeruginosa isolates from clinical and environmental sources. This bacterium is ubiquitous in the natural environment and is an important pathogen known to infect Cystic Fibrosis (CF) patients. The transmission route of strains has not yet been defined; current theories include acquisition from an environmental source or through patient-to-patient spread. A highly discriminatory, bioinformatics based, DNA typing method was developed to investigate the relatedness of clinical and environmental isolates. This study found a similarity between the environmental and several CF clonal strains and also highlighted occurrence of environmental P. aeruginosa strains in CF infections.
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We propose a cluster ensemble method to map the corpus documents into the semantic space embedded in Wikipedia and group them using multiple types of feature space. A heterogeneous cluster ensemble is constructed with multiple types of relations i.e. document-term, document-concept and document-category. A final clustering solution is obtained by exploiting associations between document pairs and hubness of the documents. Empirical analysis with various real data sets reveals that the proposed meth-od outperforms state-of-the-art text clustering approaches.
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Entity-oriented retrieval aims to return a list of relevant entities rather than documents to provide exact answers for user queries. The nature of entity-oriented retrieval requires identifying the semantic intent of user queries, i.e., understanding the semantic role of query terms and determining the semantic categories which indicate the class of target entities. Existing methods are not able to exploit the semantic intent by capturing the semantic relationship between terms in a query and in a document that contains entity related information. To improve the understanding of the semantic intent of user queries, we propose concept-based retrieval method that not only automatically identifies the semantic intent of user queries, i.e., Intent Type and Intent Modifier but introduces concepts represented by Wikipedia articles to user queries. We evaluate our proposed method on entity profile documents annotated by concepts from Wikipedia category and list structure. Empirical analysis reveals that the proposed method outperforms several state-of-the-art approaches.
Resumo:
One limitation of electrospinning stems from the charge build-up that occurs during processing, preventing further fibre deposition and limiting the scaffold overall thickness and hence their end-use in tissue engineering applications targeting large tissue defect repair. To overcome this, we have developed a technique in which thermally induced phase separation (TIPS) and electrospinning are combined. Thick three-dimensional, multilayered composite scaffolds were produced by simply stacking individual polycaprolactone (PCL) microfibrous electrospun discs into a cylindrical holder that was filled with a 3% poly(lactic-co-glycolic acid) (PLGA) solution in dimethylsulfoxide (a good solvent for PLGA but a poor one for PCL). The construct was quenched in liquid nitrogen and the solvent removed by leaching out in cold water. This technique enables the fabrication of scaffolds composed principally of electrospun membranes that have no limit to their thickness. The mechanical properties of these scaffolds were assessed under both quasi-static and dynamic conditions. The multilayered composite scaffolds had similar compressive properties to 5% PCL scaffolds fabricated solely by the TIPS methodology. However, tensile tests demonstrated that the multilayered construct outperformed a scaffold made purely by TIPS, highlighting the contribution of the electrospun component of the composite scaffold to enhancing the overall mechanical property slate. Cell studies revealed cell infiltration principally from the scaffold edges under static seeding conditions. This fabrication methodology permits the rapid construction of thick, strong scaffolds from a range of biodegradable polymers often used in tissue engineering, and will be particularly useful when large dimension electrospun scaffolds are required.
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Review question/objective What is the effect of using the teach-back method for health education to improve adherence to treatment regimen and self-management in chronic disease? Inclusion criteria Types of participants This review will consider all studies that include adult patients (aged 18 years and over) in any healthcare setting, either as inpatients (eg acute care, medical and surgical wards) or those who attend primary health care, family medical practice, general medical practice, clinics, outpatient departments, rehabilitation or community settings. Participants need to have been diagnosed as having one or more chronic diseases including heart failure, diabetes, cardiovascular disease, cancer, respiratory disease, asthma, chronic obstructive pulmonary disease, chronic kidney disease, arthritis, epilepsy or a mental health condition. Studies that include seriously ill patients, and/or those who have impairments in verbal communication and cognitive function will be excluded. Types of intervention This review will consider studies that investigate the use of the teach-back method alone or in combination with other supporting education, either in routine or research intervention education programs; regardless of how long the programs were and whether or not a follow-up was conducted. The intervention could be delivered by any healthcare professional. The comparator will be any health education for chronic disease that does not include the teach-back method. Types of outcomes Primary outcomes of interest are disease-specific knowledge, adherence, and self-management knowledge, behavior and skills measured using patient report, nursing observation or validated measurement scales. Secondary outcomes include knowledge retention, self-efficacy, hospital readmission, hospitalization, and quality of life, also measured using patient report, nursing observation, hospital records or validated measurement scales.
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The measurement of losses in high efficiency / high power converters is difficult. Measuring the losses directly from the difference between the input and output power results in large errors. Calorimetric methods are usually used to bypass this issue but introduce different problems, such as, long measurement times, limited power loss measurement range and/or large set up cost. In this paper the total losses of a converter are measured directly and switching losses are exacted. The measurements can be taken with only three multimeters and a current probe and a standard bench power supply. After acquiring two or three power loss versus output current sweeps, a series of curve fitting processes are applied and the switching losses extracted.
Resumo:
The key to reducing cost of electric vehicles is integration. All too often systems such as the motor, motor controller, batteries and vehicle chassis/body are considered as separate problems. The truth is that a lot of trade-offs can be made between these systems, causing an overall improvement in many areas including total cost. Motor controller and battery cost have a relatively simple relationship; the less energy lost in the motor controller the less energy that has to be carried in the batteries, hence the lower the battery cost. A motor controller’s cost is primarily influenced by the cost of the switches. This paper will therefore present a method of assessing the optimal switch selection on the premise that the optimal switch is the one that produces the lowest system cost, where system cost is the cost of batteries + switches.
Resumo:
A "self-exciting" market is one in which the probability of observing a crash increases in response to the occurrence of a crash. It essentially describes cases where the initial crash serves to weaken the system to some extent, making subsequent crashes more likely. This thesis investigates if equity markets possess this property. A self-exciting extension of the well-known jump-based Bates (1996) model is used as the workhorse model for this thesis, and a particle-filtering algorithm is used to facilitate estimation by means of maximum likelihood. The estimation method is developed so that option prices are easily included in the dataset, leading to higher quality estimates. Equilibrium arguments are used to price the risks associated with the time-varying crash probability, and in turn to motivate a risk-neutral system for use in option pricing. The option pricing function for the model is obtained via the application of widely-used Fourier techniques. An application to S&P500 index returns and a panel of S&P500 index option prices reveals evidence of self excitation.