55 resultados para Johan Maurits, Prince of Nassau-Siegen, 1604-1679.


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To determine whether pre-exercise muscle glycogen content influences the transcription of several early-response genes involved in the regulation of muscle growth, seven male strength-trained subjects performed one-legged cycling exercise to exhaustion to lower muscle glycogen levels (Low) in one leg compared with the leg with normal muscle glycogen (Norm) and then the following day completed a unilateral bout of resistance training (RT). Muscle biopsies from both legs were taken at rest, immediately after RT, and after 3 h of recovery. Resting glycogen content was higher in the control leg (Norm leg) than in the Low leg (435 ± 87 vs. 193 ± 29 mmol/kg dry wt; P < 0.01). RT decreased glycogen content in both legs (P < 0.05), but postexercise values remained significantly higher in the Norm than the Low leg (312 ± 129 vs. 102 ± 34 mmol/kg dry wt; P < 0.01). GLUT4 (3-fold; P < 0.01) and glycogenin mRNA abundance (2.5-fold; not significant) were elevated at rest in the Norm leg, but such differences were abolished after exercise. Preexercise mRNA abundance of atrogenes was also higher in the Norm compared with the Low leg [atrogin: ?14-fold, P < 0.01; RING (really interesting novel gene) finger: ?3-fold, P < 0.05] but decreased for atrogin in Norm following RT (P < 0.05). There were no differences in the mRNA abundance of myogenic regulatory factors and IGF-I in the Norm compared with the Low leg. Our results demonstrate that 1) low muscle glycogen content has variable effects on the basal transcription of select metabolic and myogenic genes at rest, and 2) any differences in basal transcription are completely abolished after a single bout of heavy resistance training. We conclude that commencing resistance exercise with low muscle glycogen does not enhance the activity of genes implicated in promoting hypertrophy.

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Abstract Aberrant dopaminergic signaling is a critical determinant in multiple psychiatric disorders, and in many disease states, dopamine receptor number is altered. Here we identify a molecular mechanism that selectively targets D2 receptors for degradation after their activation by dopamine. The degradative fate of D2 receptors is determined by an interaction with G protein coupled receptor-associated sorting protein (GASP). As a consequence of this GASP interaction, D2 responses in rat brain fail to resensitize after agonist treatment. Disruption of the D2-GASP interaction facilitates recovery of D2 responses, suggesting that modulation of the D2-GASP interaction is important for the functional down-regulation of D2 receptors.

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The uncertainty associated with how projected climate change will affect global C cycling could have a large impact on predictions of soil C stocks. The purpose of our study was to determine how various soil decomposition and chemistry characteristics relate to soil organic matter (SOM) temperature sensitivity. We accomplished this objective using long-term soil incubations at three temperatures (15, 25, and 35°C) and pyrolysis molecular beam mass spectrometry (py-MBMS) on 12 soils from 6 sites along a mean annual temperature (MAT) gradient (2–25.6°C). The Q10 values calculated from the CO2 respired during a long-term incubation using the Q10-q method showed decomposition of the more resistant fraction to be more temperature sensitive with a Q10-q of 1.95 ± 0.08 for the labile fraction and a Q10-q of 3.33 ± 0.04 for the more resistant fraction. We compared the fit of soil respiration data using a two-pool model (active and slow) with first-order kinetics with a three-pool model and found that the two and three-pool models statistically fit the data equally well. The three-pool model changed the size and rate constant for the more resistant pool. The size of the active pool in these soils, calculated using the two-pool model, increased with incubation temperature and ranged from 0.1 to 14.0% of initial soil organic C. Sites with an intermediate MAT and lowest C/N ratio had the largest active pool. Pyrolysis molecular beam mass spectrometry showed declines in carbohydrates with conversion from grassland to wheat cultivation and a greater amount of protected carbohydrates in allophanic soils which may have lead to differences found between the total amount of CO2 respired, the size of the active pool, and the Q10-q values of the soils.

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In September 2009 an enormous dust storm swept across eastern Australia. Dust is potentially hazardous to health as it interferes with breathing, and previous dust storms have been linked to increased risks of asthma and even death. We examined whether the 2009 Australian dust storm changed the volume or characteristics of emergency admissions to hospital. We used an observational study design, using time series analyses to examine changes in the number of admissions, and case-only analyses to examine changes in the characteristics of admissions. The admission data were from the Prince Charles Hospital, Brisbane, between 1 January 2009 and 31 October 2009. There was a 39% increase in emergency admissions associated with the storm (95% confidence interval: 5, 81%), which lasted for just one day. The health effects of the storm could not be detected using particulate matter levels. We found no significant change in the characteristics of admissions during the storm, specifically there was no increase in respiratory admissions. The dust storm had a short-lived impact on emergency hospital admissions. This may be because the public took effective avoidance measures, or because the dust was simply not toxic, being mainly composed of soil. Emergency departments should be prepared for a short-term increase in admissions during dust storms.

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The health system is one sector dealing with a deluge of complex data. Many healthcare organisations struggle to utilise these volumes of health data effectively and efficiently. Also, there are many healthcare organisations, which still have stand-alone systems, not integrated for management of information and decision-making. This shows, there is a need for an effective system to capture, collate and distribute this health data. Therefore, implementing the data warehouse concept in healthcare is potentially one of the solutions to integrate health data. Data warehousing has been used to support business intelligence and decision-making in many other sectors such as the engineering, defence and retail sectors. The research problem that is going to be addressed is, "how can data warehousing assist the decision-making process in healthcare". To address this problem the researcher has narrowed an investigation focusing on a cardiac surgery unit. This research used the cardiac surgery unit at the Prince Charles Hospital (TPCH) as the case study. The cardiac surgery unit at TPCH uses a stand-alone database of patient clinical data, which supports clinical audit, service management and research functions. However, much of the time, the interaction between the cardiac surgery unit information system with other units is minimal. There is a limited and basic two-way interaction with other clinical and administrative databases at TPCH which support decision-making processes. The aims of this research are to investigate what decision-making issues are faced by the healthcare professionals with the current information systems and how decision-making might be improved within this healthcare setting by implementing an aligned data warehouse model or models. As a part of the research the researcher will propose and develop a suitable data warehouse prototype based on the cardiac surgery unit needs and integrating the Intensive Care Unit database, Clinical Costing unit database (Transition II) and Quality and Safety unit database [electronic discharge summary (e-DS)]. The goal is to improve the current decision-making processes. The main objectives of this research are to improve access to integrated clinical and financial data, providing potentially better information for decision-making for both improved from the questionnaire and by referring to the literature, the results indicate a centralised data warehouse model for the cardiac surgery unit at this stage. A centralised data warehouse model addresses current needs and can also be upgraded to an enterprise wide warehouse model or federated data warehouse model as discussed in the many consulted publications. The data warehouse prototype was able to be developed using SAS enterprise data integration studio 4.2 and the data was analysed using SAS enterprise edition 4.3. In the final stage, the data warehouse prototype was evaluated by collecting feedback from the end users. This was achieved by using output created from the data warehouse prototype as examples of the data desired and possible in a data warehouse environment. According to the feedback collected from the end users, implementation of a data warehouse was seen to be a useful tool to inform management options, provide a more complete representation of factors related to a decision scenario and potentially reduce information product development time. However, there are many constraints exist in this research. For example the technical issues such as data incompatibilities, integration of the cardiac surgery database and e-DS database servers and also, Queensland Health information restrictions (Queensland Health information related policies, patient data confidentiality and ethics requirements), limited availability of support from IT technical staff and time restrictions. These factors have influenced the process for the warehouse model development, necessitating an incremental approach. This highlights the presence of many practical barriers to data warehousing and integration at the clinical service level. Limitations included the use of a small convenience sample of survey respondents, and a single site case report study design. As mentioned previously, the proposed data warehouse is a prototype and was developed using only four database repositories. Despite this constraint, the research demonstrates that by implementing a data warehouse at the service level, decision-making is supported and data quality issues related to access and availability can be reduced, providing many benefits. Output reports produced from the data warehouse prototype demonstrated usefulness for the improvement of decision-making in the management of clinical services, and quality and safety monitoring for better clinical care. However, in the future, the centralised model selected can be upgraded to an enterprise wide architecture by integrating with additional hospital units’ databases.

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Objective. The Effective Consumer Scale (EC-17) comprises 17 items measuring the main skills and behaviors people need to effectively manage their healthcare. We tested the responsiveness of the EC-17. Methods. Participants, in 2 waves of a 6-week Arthritis Self-Management Program (ASMP) from Arthritis Ireland, received a questionnaire at the first and last week of the weekly ASMP. The questionnaire included the EC-17 and 10 other measures for arthritis. Deficits, mean change, and standard deviations were calculated at baseline and Week 6. The EC-17 scores were compared to the Arthritis Self-Efficacy (ASE) and Patient Activation Measure (PAM) scales. Results were presented at OMERACT 9. Results. There is some overlap between the EC-17 and the ASE and PAM; however, most items of greatest deficit in the EC-17 are not covered by those scales. In 327 participants representing both intervention waves (2006 and 2007), the EC-17 was more efficient than the ASE but less efficient than the PAM for detecting improvements after the ASMP, and was moderately correlated with the PAM. Conclusion. The EC-17 appears to measure different skills and attributes than the ASE and PAM. Discussions with participants at OMERACT 9 agreed that it is worthwhile to measure the skills and attributes of an effective consumer, and supported the development of an intervention (such as proposed online decision aids) that would include education in the categories in the EC-17.

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The current investigation reports on diesel particulate matter emissions, with special interest in fine particles from the combustion of two base fuels. The base fuels selected were diesel fuel and marine gas oil (MGO). The experiments were conducted with a four-stroke, six-cylinder, direct injection diesel engine. The results showed that the fine particle number emissions measured by both SMPS and ELPI were higher with MGO compared to diesel fuel. It was observed that the fine particle number emissions with the two base fuels were quantitatively different but qualitatively similar. The gravimetric (mass basis) measurement also showed higher total particulate matter (TPM) emissions with the MGO. The smoke emissions, which were part of TPM, were also higher for the MGO. No significant changes in the mass flow rate of fuel and the brake-specific fuel consumption (BSFC) were observed between the two base fuels.

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Clinical information systems have become important tools in contemporary clinical patient care. However, there is a question of whether the current clinical information systems are able to effectively support clinicians in decision making processes. We conducted a survey to identify some of the decision making issues related to the use of existing clinical information systems. The survey was conducted among the end users of the cardiac surgery unit, quality and safety unit, intensive care unit and clinical costing unit at The Prince Charles Hospital (TPCH). Based on the survey results and reviewed literature, it was identified that support from the current information systems for decision-making is limited. Also, survey results showed that the majority of respondents considered lack in data integration to be one of the major issues followed by other issues such as limited access to various databases, lack of time and lack in efficient reporting and analysis tools. Furthermore, respondents pointed out that data quality is an issue and the three major data quality issues being faced are lack of data completeness, lack in consistency and lack in data accuracy. Conclusion: Current clinical information systems support for the decision-making processes in Cardiac Surgery in this institution is limited and this could be addressed by integrating isolated clinical information systems.

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Intellectual disability (ID) is associated with a range of risk factors that make children more vulnerable to adverse developmental outcomes including mental health problems. Nevertheless, some children with ID do much better than others, presumably because of the presence of protective factors that increase their resilience. The current study compared resiliency profiles of children with ID (n = 115, mean age 11.9 years) and their typically developing peers (n = 106, mean age 11.8 years) using the Resiliency Scales for Children and Adolescents (Prince-Embury, 2007) and the Healthy Kids Resilience Assessment (Constantine, Bernard & Diaz, 1999). In many respects children with ID and their typically developing peers reported similar levels of the protective factors that are associated with resilience. However, the children with ID reported higher levels of emotional sensitivity and lower tolerance, as well as fewer future goals. Compared with typically developing children, those with ID reported more support at school and less support within their communities. These findings have important implications for interventions that aim to promote positive developmental outcomes and to prevent the adverse sequelae that have been associated with low intelligence.

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Deciding the appropriate population size and number of is- lands for distributed island-model genetic algorithms is often critical to the algorithm’s success. This paper outlines a method that automatically searches for good combinations of island population sizes and the number of islands. The method is based on a race between competing parameter sets, and collaborative seeding of new parameter sets. This method is applicable to any problem, and makes distributed genetic algorithms easier to use by reducing the number of user-set parameters. The experimental results show that the proposed method robustly and reliably finds population and islands settings that are comparable to those found with traditional trial-and-error approaches.

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Distributed Genetic Algorithms (DGAs) designed for the Internet have to take its high communication cost into consideration. For island model GAs, the migration topology has a major impact on DGA performance. This paper describes and evaluates an adaptive migration topology optimizer that keeps the communication load low while maintaining high solution quality. Experiments on benchmark problems show that the optimized topology outperforms static or random topologies of the same degree of connectivity. The applicability of the method on real-world problems is demonstrated on a hard optimization problem in VLSI design.

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In this paper, we will discuss the issue of rostering jobs of cabin crew attendants at KLM. Generated schedules get easily disrupted by events such as illness of an employee. Obviously, reserve people have to be kept 'on duty' to resolve such disruptions. A lot of reserve crew requires more employees, but too few results in so-called secondary disruptions, which are particularly inconvenient for both the crew members and the planners. In this research we will discuss several modifications of the reserve scheduling policy that have a potential to reduce the number of secondary disruptions, and therefore to improve the performance of the scheduling process.

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Background: Evaluation of scapular posture is a fundamental component in the clinical evaluation of the upper quadrant. This study examined the intrarater reliability of scapular posture ratings. Methods: A test-retest reliability investigation was undertaken with one week between assessment sessions. At each session physical therapists conducted visual assessments of scapula posture (relative to the thorax) in five different scapula postural planes (plane of scapula, sagittal plane, transverse plane, horizontal plane, and vertical plane). These five plane ratings were performed for four different scapular posture perturbating conditions (rest, isometric shoulder; flexion, abduction, and external rotation). Results. A total of 100 complete scapular posture ratings (50 left, 50 right) were undertaken at each assessment. The observed agreement between the test and retest postural plane ratings ranged from 59% to 87%; 16 of the 20 plane-condition combinations exceeded 75% observed agreement. Kappa (and prevalence adjusted bias adjusted kappa) values were inconsistent across the postural planes and perturbating conditions. Conclusions: This investigation generally revealed fair to moderate intrarater reliability in the rating of scapular posture by visual inspection. However, enough disagreement between assessments was present to warrant caution when interpreting perceived changes in scapula position between longitudinal assessments using visual inspection alone.

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Recent research has proposed Neo-Piagetian theory as a useful way of describing the cognitive development of novice programmers. Neo-Piagetian theory may also be a useful way to classify materials used in learning and assessment. If Neo-Piagetian coding of learning resources is to be useful then it is important that practitioners can learn it and apply it reliably. We describe the design of an interactive web-based tutorial for Neo-Piagetian categorization of assessment tasks. We also report an evaluation of the tutorial's effectiveness, in which twenty computer science educators participated. The average classification accuracy of the participants on each of the three Neo-Piagetian stages were 85%, 71% and 78%. Participants also rated their agreement with the expert classifications, and indicated high agreement (91%, 83% and 91% across the three Neo-Piagetian stages). Self-rated confidence in applying Neo-Piagetian theory to classifying programming questions before and after the tutorial were 29% and 75% respectively. Our key contribution is the demonstration of the feasibility of the Neo-Piagetian approach to classifying assessment materials, by demonstrating that it is learnable and can be applied reliably by a group of educators. Our tutorial is freely available as a community resource.

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Background Non-fatal health outcomes from diseases and injuries are a crucial consideration in the promotion and monitoring of individual and population health. The Global Burden of Disease (GBD) studies done in 1990 and 2000 have been the only studies to quantify non-fatal health outcomes across an exhaustive set of disorders at the global and regional level. Neither effort quantified uncertainty in prevalence or years lived with disability (YLDs). Methods Of the 291 diseases and injuries in the GBD cause list, 289 cause disability. For 1160 sequelae of the 289 diseases and injuries, we undertook a systematic analysis of prevalence, incidence, remission, duration, and excess mortality. Sources included published studies, case notification, population-based cancer registries, other disease registries, antenatal clinic serosurveillance, hospital discharge data, ambulatory care data, household surveys, other surveys, and cohort studies. For most sequelae, we used a Bayesian meta-regression method, DisMod-MR, designed to address key limitations in descriptive epidemiological data, including missing data, inconsistency, and large methodological variation between data sources. For some disorders, we used natural history models, geospatial models, back-calculation models (models calculating incidence from population mortality rates and case fatality), or registration completeness models (models adjusting for incomplete registration with health-system access and other covariates). Disability weights for 220 unique health states were used to capture the severity of health loss. YLDs by cause at age, sex, country, and year levels were adjusted for comorbidity with simulation methods. We included uncertainty estimates at all stages of the analysis. Findings Global prevalence for all ages combined in 2010 across the 1160 sequelae ranged from fewer than one case per 1 million people to 350 000 cases per 1 million people. Prevalence and severity of health loss were weakly correlated (correlation coefficient −0·37). In 2010, there were 777 million YLDs from all causes, up from 583 million in 1990. The main contributors to global YLDs were mental and behavioural disorders, musculoskeletal disorders, and diabetes or endocrine diseases. The leading specific causes of YLDs were much the same in 2010 as they were in 1990: low back pain, major depressive disorder, iron-deficiency anaemia, neck pain, chronic obstructive pulmonary disease, anxiety disorders, migraine, diabetes, and falls. Age-specific prevalence of YLDs increased with age in all regions and has decreased slightly from 1990 to 2010. Regional patterns of the leading causes of YLDs were more similar compared with years of life lost due to premature mortality. Neglected tropical diseases, HIV/AIDS, tuberculosis, malaria, and anaemia were important causes of YLDs in sub-Saharan Africa. Interpretation Rates of YLDs per 100 000 people have remained largely constant over time but rise steadily with age. Population growth and ageing have increased YLD numbers and crude rates over the past two decades. Prevalences of the most common causes of YLDs, such as mental and behavioural disorders and musculoskeletal disorders, have not decreased. Health systems will need to address the needs of the rising numbers of individuals with a range of disorders that largely cause disability but not mortality. Quantification of the burden of non-fatal health outcomes will be crucial to understand how well health systems are responding to these challenges. Effective and affordable strategies to deal with this rising burden are an urgent priority for health systems in most parts of the world. Funding Bill & Melinda Gates Foundation.