Influence of Various Stator Parameters on the Open-Water Performance of Pump-Jet Propulsion

In order to improve the hydrodynamic performance of pump-jet propulsion (PJP) when matching stator with the rotor, the RANS method with SST k-ω turbulence model is employed to study the influence of six kinds of stator parameters, which are classified into three groups, i.e., stator solidity, stator angles and rotor–stator spacing (S). Results show that the stator solidity involves the blade number (Ns) and chord length (L), has an obvious acceleration effect at and after stator, and produces a higher thrust and torque with a slight efficiency change. Further comparing Ns and L results, we find greater distinctions between the two cases when stator solidity is greatly adjusted. Three stator angles, i.e., stagger angle (α), lean angle (γ), and sweep angle (β), are studied. The α has the biggest effect on the thrust, torque, and efficiency; meanwhile, it shifts the advance number that corresponds to maximum efficiency. The effect of γ is similar to α, but its influence is far less than α. However, there is little difference between various β cases except for off-design conditions, where the efficiency drops dramatically as β increases. The S has a slight effect on PJP performance. Even though S decreases 34% relative to the original PJP, the rotor thrust and torque increase by less than 1%. In addition, we compare torque balance locations under various parameters, and each component force is analyzed in detail to explain the reason for performance variation. The present work is conducive to future optimization in PJP design.

Plasticity of the gastrocnemius elastic system in response to decreased work and power demand during growth

Elastic energy storage and release can enhance performance that would otherwise be limited by the force-velocity constraints of muscle. While functional influence of a biological spring depends on tuning between components of an elastic system (the muscle, spring, driven mass, and lever system), we do not know whether elastic systems systematically adapt to functional demand. To test whether altering work and power generation during maturation alters the morphology of an elastic system, we prevented growing guinea fowl (Numida Meleagris) from jumping. At maturity, we compared the jump performance of our treatment group to that of controls and measured the morphology of the gastrocnemius elastic system. We found that restricted birds jumped with lower jump power and work, yet there were no significant between-group differences in the components of the elastic system. Further, subject-specific models revealed no difference in energy storage capacity between groups, though energy storage was most sensitive to variations in muscle properties (most significantly operating length and least dependent on tendon stiffness). We conclude that the gastrocnemius elastic system in the guinea fowl displays little to no plastic response to decreased demand during growth and hypothesize that neural plasticity may explain performance variation.

Dynamic Performance Characterization Techniques in Gallium Nitride-Based Electronic Devices

In this paper, we compare and discuss the main techniques for the analysis of the dynamic performance of GaN-based transistors. The pulsed current-voltage characterization provides information on the effect of different trapping voltages on various bias points of the device under test, leading to the detection of all the possible effects, as well as to the choice of the optimal filling and measure bias conditions in other techniques. The drain current transients use one of the identified bias configurations to extract information on the deep level signature responsible for the performance variation and, thus, they can pinpoint the corresponding physical crystal lattice configuration, providing useful information to the growers on how the issue can be solved. Finally, given the complex interplay between the filling and emission time constants, the gate frequency sweeps can be used to obtain the real performance in the target operating condition.

Regional performance variation in external validation of four prediction models for severity of COVID-19 at hospital admission: An observational multi-centre cohort study

Background Prediction models should be externally validated to assess their performance before implementation. Several prediction models for coronavirus disease-19 (COVID-19) have been published. This observational cohort study aimed to validate published models of severity for hospitalized patients with COVID-19 using clinical and laboratory predictors. Methods Prediction models fitting relevant inclusion criteria were chosen for validation. The outcome was either mortality or a composite outcome of mortality and ICU admission (severe disease). 1295 patients admitted with symptoms of COVID-19 at Kings Cross Hospital (KCH) in London, United Kingdom, and 307 patients at Oslo University Hospital (OUH) in Oslo, Norway were included. The performance of the models was assessed in terms of discrimination and calibration. Results We identified two models for prediction of mortality (referred to as Xie and Zhang1) and two models for prediction of severe disease (Allenbach and Zhang2). The performance of the models was variable. For prediction of mortality Xie had good discrimination at OUH with an area under the receiver-operating characteristic (AUROC) 0.87 [95% confidence interval (CI) 0.79–0.95] and acceptable discrimination at KCH, AUROC 0.79 [0.76–0.82]. In prediction of severe disease, Allenbach had acceptable discrimination (OUH AUROC 0.81 [0.74–0.88] and KCH AUROC 0.72 [0.68–0.75]). The Zhang models had moderate to poor discrimination. Initial calibration was poor for all models but improved with recalibration. Conclusions The performance of the four prediction models was variable. The Xie model had the best discrimination for mortality, while the Allenbach model had acceptable results for prediction of severe disease.

Relative Power Correlates With the Decoding Performance of Motor Imagery Both Across Time and Subjects

One of the most significant challenges in the application of brain-computer interfaces (BCI) is the large performance variation, which often occurs over time or across users. Recent evidence suggests that the physiological states may explain this performance variation in BCI, however, the underlying neurophysiological mechanism is unclear. In this study, we conducted a seven-session motor-imagery (MI) experiment on 20 healthy subjects to investigate the neurophysiological mechanism on the performance variation. The classification accuracy was calculated offline by common spatial pattern (CSP) and support vector machine (SVM) algorithms to measure the MI performance of each subject and session. Relative Power (RP) values from different rhythms and task stages were used to reflect the physiological states and their correlation with the BCI performance was investigated. Results showed that the alpha band RP from the supplementary motor area (SMA) within a few seconds before MI was positively correlated with performance. Besides, the changes of RP between task and pre-task stage from theta, alpha, and gamma band were also found to be correlated with performance both across time and subjects. These findings reveal a neurophysiological manifestation of the performance variations, and would further provide a way to improve the BCI performance.

Evidence of an Inverted U–Shaped Relationship between Stakeholder Management Performance Variation and Firm Performance

Empirical research is largely supportive of the assertion of instrumental stakeholder theory that a positive relationship exists between “managing for stakeholders” and firm performance. However, despite considerable debate on the subject, the amount of variation across firm investments in stakeholders (stakeholder management performance) has not been adequately investigated. We address this gap using a sample of more than eighteen thousand firm-level observations over ten years. We find evidence to support an inverted U–shaped relationship between variation in stakeholder management performance and Tobin’s q, suggesting that firms that have some imbalance in their stakeholder management, but not too much, perform best. We discuss the implications of our study for instrumental stakeholder theory and managerial practice.