Deprivation and volunteering by general practices: cross sectional analysis of a national primary care system

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A parameter identifying a Kalman filter observer for vehicle handling dynamics

The paper presents a method for designing a non-linear (i.e. extended) Kalman filter that is also parameter adaptive and hence capable of online identification of its model. The filter model is deliberately simple in structure and low order, yet includes non-linear, load-varying tyre force calculations to ensure accuracy over a range of test conditions. Shape parameters within the (Pacejka) tyre model are adapted rapidly in real time, to maintain excellent state reconstruction accuracy, and provide valuable real-time lateral and vertical tyre force information. The filter is tested in both simulated and test vehicle environments and provides good results. The paper also provides an illustration of the importance of good Kalman filter design practice in terms of selection and tuning of the noise matrices, particularly in terms of the influence of model/sensor error cross-correlations

Searches for dark photons at accelerators

Dark matter particles may interact with other dark matter particles via a new force mediated by a dark photon, $A^{\prime}$, which would be the dark-sector analog to the ordinary photon of electromagnetism. The dark photon can obtain a highly suppressed mixing-induced coupling to the electromagnetic current, providing a portal through which dark photons can interact with ordinary matter. This review focuses on $A^{\prime}$ scenarios that are potentially accessible to accelerator-based experiments. We summarize the existing constraints placed by such experiments on dark photons, highlight what could be observed in the near future, and discuss the major experimental challenges that must be overcome to improve sensitivities.Comment: 27 pages, 7 figures; Invited contribution for Annual Review of Nuclear and Particle Scienc

Information Systems and the Problem of Work: Protocol for a Systematic Review

There is a sense in America that there is a growing crisis regarding the availability or quality of rewarding, satisfying work. A variety of competing framings of and reasons for this are offered, including some claims that information technologies and systems are to blame for the decline in work satisfaction. A number of streams of research in diverse disciplines have sought to understand what constitutes good , or meaningful , or decent work, how we can achieve it, and what happens when it is lacking, yet we know little about what contributions the information systems discipline has made, or could make, to solving this challenge of our times. In this paper we chart the conceptual landscape of the problem of work as it is framed by reference disciplines, and develop a protocol for a systematic literature review of contributions from IS research to creating good work or making work better

Low Dimensionality in Gene Expression Data Enables the Accurate Extraction of Transcriptional Programs from Shallow Sequencing

A tradeoff between precision and throughput constrains all biological measurements, including sequencing-based technologies. Here, we develop a mathematical framework that defines this tradeoff between mRNA-sequencing depth and error in the extraction of biological information. We find that transcriptional programs can be reproducibly identified at 1% of conventional read depths. We demonstrate that this resilience to noise of “shallow” sequencing derives from a natural property, low dimensionality, which is a fundamental feature of gene expression data. Accordingly, our conclusions hold for ∼350 single-cell and bulk gene expression datasets across yeast, mouse, and human. In total, our approach provides quantitative guidelines for the choice of sequencing depth necessary to achieve a desired level of analytical resolution. We codify these guidelines in an open-source read depth calculator. This work demonstrates that the structure inherent in biological networks can be productively exploited to increase measurement throughput, an idea that is now common in many branches of science, such as image processing

CFD Modeling of LNG Flammable Vapor Cloud Dispersion

PresentationThe simulation of LNG flammable vapor cloud dispersion plays a key role in the safe design of LNG terminals and other facilities. With large scale and often complex release scenarios, the scope for model testing is limited and so computational fluid dynamics (CFD) offers a valuable predictive tool, particularly where uneven terrain or obstructions are present and simpler simulation methods may be insufficient. In this study, CFD is used to simulate a range of published LNG vapor and other dense gas dispersion experiments. Details of the setup used to model both the model scale and full scale releases included in the different datasets is presented with emphasis placed on the key model setup choices made in each case. In particular, factors such as the computational mesh and processing and interpretation of data from the completed run were examined. Finally, the numerical results computed are compared with experimental point-wise and arc-wise maximum concentration data to validate the CFD models. The individual challenges presented by each dataset and ability of the CFD model to reproduce experimental measurements in each case is analyzed and discussed

Acute effects of different warm-up protocols on highly skilled golfers’ drive performance

Previous research has highlighted the positive effect that different warm-up protocols have on golf performance (e.g. Sorbie et al., 2016; Tilley & MacFarlane, 2012) with the design of warm-ups and programmes targeting and improving golf performance through the activation and development of specific muscle groups. This study aimed to examine the acute effects of two warm-up protocols on golf drive performance in comparison to a control condition. Using a randomised counter-balanced design over three testing sessions, twenty-three highly skilled golfers completed the control, dynamic and resistance-band warm-up conditions. Following each condition, a GC2 launch monitor was used to record ball velocity and other launch parameters of ten shots hit with the participants own driver. A repeated-measures ANOVA found significant increases in ball velocity (ηp² = .217) between the control and both the dynamic and resistance-band warm-up conditions but no difference between these latter two, and a reduction in launch angle between control and dynamic conditions. The use of either a dynamic stretching or resistance-band warm-up can have acute benefits on ball velocity but golfers should liaise with a PGA Professional golf coach to effectively integrate this into their golf driving performance

The development of eye tracking in aviation (ETA) technique to investigate pilot's cognitive processes of attention and decision-making

Eye tracking device had provided researchers a promising way to investigate what pilot‘s cognitive processes when they see information present on the flight deck. There are 35 participants consisted by pilots and avionics engineers participated in current research. The research apparatus include an eye tracker and a flight simulator divided by five AOIs for data collection. The research aims are to develop cost-efficiency of eye tracking technique in order to facilitate scientific research of cognition and decision-making in aviation. The results indicated that participants’ eye movement patterns did have significant differences on the following variables including fixation count, F(4, 136) = 601.01, p < .001; average fixation duration, F(4, 136) = 100.87, p < .001; percentage of total fixations, F(4, 136) = 779.92, p < .001, and average pupil area, F(4, 136)=2.51, p < .05. The findings demonstrated that eye tracker is a suitable tool to investigate pilots’ cognitive process of attention and decision-making on flight deck. Furthermore, it can be applied to improve pilots’ SA and decision-making during flight operations