Do we need more evidence-based survey guidance?

As ecologists and environmental managers, we rely on good quality baseline information. However, the survey methods we currently employ are often unsupported by scientific testing and are not proven to provide high quality outputs. As a community of practitioners, we should seek to change this, taking on board new research and technological developments – and building more evidence explicitly into our survey guidance

Identification and validation of a driver steering control model incorporating human sensory dynamics

Most existing models of driver steering control do not consider the driver's sensory dynamics, despite many aspects of human sensory perception having been researched extensively. The authors recently reported development of a driver model that incorporates sensory transfer functions, noise and delays. The present paper reports the experimental identification and validation of this model. An experiment was carried out with five test subjects in a driving simulator, aiming to replicate a real-world driving scenario with no motion scaling. The results of this experiment are used to identify parameter values for the driver model, and the model is found to describe the results of the experiment well. Predicted steering angles match the linear component of measured results with an average `variance accounted for' of 98% using separate parameter sets for each trial, and 93% with a single fixed parameter set. The identified parameter values are compared with results from the literature and are found to be physically plausible, supporting the hypothesis that driver steering control can be predicted using models of human perception and control mechanisms

Development of a novel model of driver-vehicle steering control incorporating sensory dynamics

This is the author accepted manuscript. The final version is available from CRC Press via http://dx.doi.org/10.1201/b21185-8A novel model of driver steering control is proposed, incorporating models of the driver’s sensory dynamics and limitations. The model is based on the hypothesis that the driver’s steering strategy minimises an internal cost function optimally based on the noisy, delayed information received from the sensory systems. Published results from experiments carried out on pilots were used to identify parameter values for the new model, and to assess the validity of the new modelling approach. The new model was found to fit the results very well, with variance accounted for (VAF) values greater than 90% for all but one trial. The model was found to fit the results almost as well with a single fixed set of parameter values as with separate parameter values for each trial, indicating that a fixed-parameter model is able to predict variations in control behaviour under different conditions.EPSR

Measurement and Modeling of the Effect of Sensory Conflicts on Driver Steering Control

In previous work, a new model of driver steering control incorporating sensory dynamics was derived and used to explain the performance of drivers in a simulator with full-scale motion feedback. This paper describes further experiments investigating how drivers steer with conflicts between their visual and vestibular measurements, caused by scaling or filtering the physical motion of the simulator relative to the virtual environment. The predictions of several variations of the new driver model are compared with the measurements to understand how drivers perceive sensory conflicts. Drivers are found to adapt well in general, unless the conflict is large, in which case they ignore the physical motion and rely on visual measurements. Drivers make greater use of physical motion which they rate as being more helpful, achieving a better tracking performance. Sensory measurement noise is shown to be signal-dependent, allowing a single set of parameters to be found to fit the results of all the trials. The model fits measured linear steering behavior with an average “variance accounted for (VAF)” of 86%.EPSRC EP/P505445/

Modelling the influence of sensory dynamics on linear and nonlinear driver steering control

A recent review of the literature has indicated that sensory dynamics play an important role in the driver–vehicle steering task, motivating the design of a new driver model incorporating human sensory systems. This paper presents a full derivation of the linear driver model developed in previous work, and extends the model to control a vehicle with nonlinear tyres. Various nonlinear controllers and state estimators are compared with different approximations of the true system dynamics. The model simulation time is found to increase significantly with the complexity of the controller and state estimator. In general the more complex controllers perform best, although with certain vehicle and tyre models linearised controllers perform as well as a full nonlinear optimisation. Various extended Kalman filters give similar results, although the driver’s sensory dynamics reduce control performance compared with full state feedback. The new model could be used to design vehicle systems which interact more naturally and safely with a human driver.This work was supported by the UK Engineering and Physical Sciences Research Council (EP/P505445/1, studentship for Nash)

Do logarithmic proximity measures outperform plain ones in graph clustering?

We consider a number of graph kernels and proximity measures including commute time kernel, regularized Laplacian kernel, heat kernel, exponential diffusion kernel (also called "communicability"), etc., and the corresponding distances as applied to clustering nodes in random graphs and several well-known datasets. The model of generating random graphs involves edge probabilities for the pairs of nodes that belong to the same class or different predefined classes of nodes. It turns out that in most cases, logarithmic measures (i.e., measures resulting after taking logarithm of the proximities) perform better while distinguishing underlying classes than the "plain" measures. A comparison in terms of reject curves of inter-class and intra-class distances confirms this conclusion. A similar conclusion can be made for several well-known datasets. A possible origin of this effect is that most kernels have a multiplicative nature, while the nature of distances used in cluster algorithms is an additive one (cf. the triangle inequality). The logarithmic transformation is a tool to transform the first nature to the second one. Moreover, some distances corresponding to the logarithmic measures possess a meaningful cutpoint additivity property. In our experiments, the leader is usually the logarithmic Communicability measure. However, we indicate some more complicated cases in which other measures, typically, Communicability and plain Walk, can be the winners.Comment: 11 pages, 5 tables, 9 figures. Accepted for publication in the Proceedings of 6th International Conference on Network Analysis, May 26-28, 2016, Nizhny Novgorod, Russi

Development of an invasively monitored porcine model of acetaminophen-induced acute liver failure

Background: The development of effective therapies for acute liver failure (ALF) is limited by our knowledge of the pathophysiology of this condition, and the lack of suitable large animal models of acetaminophen toxicity. Our aim was to develop a reproducible invasively-monitored porcine model of acetaminophen-induced ALF. Method: 35kg pigs were maintained under general anaesthesia and invasively monitored. Control pigs received a saline infusion, whereas ALF pigs received acetaminophen intravenously for 12 hours to maintain blood concentrations between 200-300 mg/l. Animals surviving 28 hours were euthanased. Results: Cytochrome p450 levels in phenobarbital pre-treated animals were significantly higher than non pre-treated animals (300 vs 100 pmol/mg protein). Control pigs (n=4) survived 28-hour anaesthesia without incident. Of nine pigs that received acetaminophen, four survived 20 hours and two survived 28 hours. Injured animals developed hypotension (mean arterial pressure; 40.8+/-5.9 vs 59+/-2.0 mmHg), increased cardiac output (7.26+/-1.86 vs 3.30+/-0.40 l/min) and decreased systemic vascular resistance (8.48+/-2.75 vs 16.2+/-1.76 mPa/s/m3). Dyspnoea developed as liver injury progressed and the increased pulmonary vascular resistance (636+/-95 vs 301+/-26.9 mPa/s/m3) observed may reflect the development of respiratory distress syndrome. Liver damage was confirmed by deterioration in pH (7.23+/-0.05 vs 7.45+/-0.02) and prothrombin time (36+/-2 vs 8.9+/-0.3 seconds) compared with controls. Factor V and VII levels were reduced to 9.3 and 15.5% of starting values in injured animals. A marked increase in serum AST (471.5+/-210 vs 42+/-8.14) coincided with a marked reduction in serum albumin (11.5+/-1.71 vs 25+/-1 g/dL) in injured animals. Animals displayed evidence of renal impairment; mean creatinine levels 280.2+/-36.5 vs 131.6+/-9.33 mumol/l. Liver histology revealed evidence of severe centrilobular necrosis with coagulative necrosis. Marked renal tubular necrosis was also seen. Methaemoglobin levels did not rise >5%. Intracranial hypertension was not seen (ICP monitoring), but there was biochemical evidence of encephalopathy by the reduction of Fischer's ratio from 5.6 +/- 1.1 to 0.45 +/- 0.06. Conclusion: We have developed a reproducible large animal model of acetaminophen-induced liver failure, which allows in-depth investigation of the pathophysiological basis of this condition. Furthermore, this represents an important large animal model for testing artificial liver support systems

Translational outcomes in a full gene deletion of ubiquitin protein ligase E3A rat model of Angelman syndrome.

Angelman syndrome (AS) is a rare neurodevelopmental disorder characterized by developmental delay, impaired communication, motor deficits and ataxia, intellectual disabilities, microcephaly, and seizures. The genetic cause of AS is the loss of expression of UBE3A (ubiquitin protein ligase E6-AP) in the brain, typically due to a deletion of the maternal 15q11-q13 region. Previous studies have been performed using a mouse model with a deletion of a single exon of Ube3a. Since three splice variants of Ube3a exist, this has led to a lack of consistent reports and the theory that perhaps not all mouse studies were assessing the effects of an absence of all functional UBE3A. Herein, we report the generation and functional characterization of a novel model of Angelman syndrome by deleting the entire Ube3a gene in the rat. We validated that this resulted in the first comprehensive gene deletion rodent model. Ultrasonic vocalizations from newborn Ube3am-/p+ were reduced in the maternal inherited deletion group with no observable change in the Ube3am+/p- paternal transmission cohort. We also discovered Ube3am-/p+ exhibited delayed reflex development, motor deficits in rearing and fine motor skills, aberrant social communication, and impaired touchscreen learning and memory in young adults. These behavioral deficits were large in effect size and easily apparent in the larger rodent species. Low social communication was detected using a playback task that is unique to rats. Structural imaging illustrated decreased brain volume in Ube3am-/p+ and a variety of intriguing neuroanatomical phenotypes while Ube3am+/p- did not exhibit altered neuroanatomy. Our report identifies, for the first time, unique AS relevant functional phenotypes and anatomical markers as preclinical outcomes to test various strategies for gene and molecular therapies in AS

Post-exercise skimmed milk, but not a sucrose beverage decreases energy intake at the next meal compared to a placebo beverage in active males

This study compared the appetite and energy intake effects of three post-exercise beverages at a subsequent post-exercise meal. On three occasions, ten active males: (mean ± sd) age 21.3 ± 1.2 y, V̇ O2peak 58 ± 5 mL/kg/min) performed 30-min cycling at ∼60% V̇ O2peak and five 4-min intervals at 85% V̇ O2peak. Post-exercise, placebo (PLA: 57 kJ), skimmed milk (MILK: 1002 kJ) or sucrose (CHO: 1000 kJ) beverages (615 mL) were consumed. Sixty min post-beverage, subjects consumed an ad-libitum pasta lunch in a 30 min eating period. Subjective appetite and plasma acylated ghrelin and plasma glucose were determined pre-exercise, post-exercise and pre-meal, with sensory characteristics of beverages rated. Ad-libitum energy intake in MILK (6746 ± 2035) kJ) was lower than CHO (7762 ± 1921) kJ) (P = 0.038; dz = 0.98; large effect) and tended to be lower than PLA (7672 (2005) kJ) (P = 0.078; dz = 0.76; medium effect). Including energy consumed in beverages, energy intake was greater in CHO than PLA (P = 0.010; dz = 1.24; large effect) or MILK (P = 0.026; dz = 0.98; large effect), with PLA and MILK not different (P = 0.960; dz = 0.02; trial effect). Plasma ghrelin, plasma glucose and appetite were not different between trials. MILK was perceived thicker than CHO (P = 0.020; dz = 1.11; large effect) and creamier than PLA (P = 0.026; dz = 1.06; large effect). These results suggest that when energy balance is important for an exerciser, post-exercise skimmed milk ingestion reduces energy intake compared to a sucrose beverage and might therefore help facilitate recovery/adaptation without affecting energy balance