Fine-scale hydrodynamics influence the spatio-temporal distribution of harbour porpoises at a coastal hotspot

The coastal Runnelstone Reef, off southwest Cornwall (UK), is characterised by complex topography and strong tidal flows and is a known high-density site for harbour porpoise (. Phocoena phocoena); a European protected species. Using a multidisciplinary dataset including: porpoise sightings from a multi-year land-based survey, Acoustic Doppler Current Profiling (ADCP), vertical profiling of water properties and high-resolution bathymetry; we investigate how interactions between tidal flow and topography drive the fine-scale porpoise spatio-temporal distribution at the site. Porpoise sightings were distributed non-uniformly within the survey area with highest sighting density recorded in areas with steep slopes and moderate depths. Greater numbers of sightings were recorded during strong westward (ebbing) tidal flows compared to strong eastward (flooding) flows and slack water periods. ADCP and Conductivity Temperature Depth (CTD) data identified fine-scale hydrodynamic features, associated with cross-reef tidal flows in the sections of the survey area with the highest recorded densities of porpoises. We observed layered, vertically sheared flows that were susceptible to the generation of turbulence by shear instability. Additionally, the intense, oscillatory near surface currents led to hydraulically controlled flow that transitioned from subcritical to supercritical conditions; indicating that highly turbulent and energetic hydraulic jumps were generated along the eastern and western slopes of the reef. The depression and release of isopycnals in the lee of the reef during cross-reef flows revealed that the flow released lee waves during upslope currents at specific phases of the tidal cycle when the highest sighting rates were recorded. The results of this unique, fine-scale field study provide new insights into specific hydrodynamic features, produced through tidal forcing, that may be important for creating predictable foraging opportunities for porpoises at a local scale. Information on the functional mechanisms linking porpoise distribution to static and dynamic physical habitat variables is extremely valuable to the monitoring and management of the species within the context of European conservation policies and marine renewable energy infrastructure development

Determining Phase Separation Dynamics with an Automated Image Processing Algorithm

The problems of extracting products efficiently from reaction workups are often overlooked. Issues such as emulsions and rag layer formation can cause long separation times and slow production, thus resulting in manufacturing inefficiencies. To better understand science within this area and to support process development, an image processing methodology has been developed that can automatically track the interface between liquid–liquid phases and provide a quantitative measure of the separation rate of two immiscible liquids. The algorithm is automated and has been successfully applied to 29 cases. Its robustness has been demonstrated with a variety of different liquid mixtures that exhibit a wide range of separation behavior─making such an algorithm suited to high-throughput experimentation. The information gathered from applying the algorithm shows how issues resulting from poor separations can be detected early in process development

Inhalation characteristics of asthma patients, COPD patients and healthy volunteers with the Spiromax® and Turbuhaler® devices: a randomised, cross-over study.

BACKGROUND: Spiromax® is a novel dry-powder inhaler containing formulations of budesonide plus formoterol (BF). The device is intended to provide dose equivalence with enhanced user-friendliness compared to BF Turbuhaler® in asthma and chronic obstructive pulmonary disease (COPD). The present study was performed to compare inhalation parameters with empty versions of the two devices, and to investigate the effects of enhanced training designed to encourage faster inhalation. METHODS: This randomised, open-label, cross-over study included children with asthma (n = 23), adolescents with asthma (n = 27), adults with asthma (n = 50), adults with COPD (n = 50) and healthy adult volunteers (n = 50). Inhalation manoeuvres were recorded with each device after training with the patient information leaflet (PIL) and after enhanced training using an In-Check Dial device. RESULTS: After PIL training, peak inspiratory flow (PIF), maximum change in pressure (∆P) and the inhalation volume (IV) were significantly higher with Spiromax than with the Turbuhaler device (p values were at least <0.05 in all patient groups). After enhanced training, numerically or significantly higher values for PIF, ∆P, IV and acceleration remained with Spiromax versus Turbuhaler, except for ∆P in COPD patients. After PIL training, one adult asthma patient and one COPD patient inhaled <30 L/min through the Spiromax compared to one adult asthma patient and five COPD patients with the Turbuhaler. All patients achieved PIF values of at least 30 L/min after enhanced training. CONCLUSIONS: The two inhalers have similar resistance so inhalation flows and pressure changes would be expected to be similar. The higher flow-related values noted for Spiromax versus Turbuhaler after PIL training suggest that Spiromax might have human factor advantages in real-world use. After enhanced training, the flow-related differences between devices persisted; increased flow rates were achieved with both devices, and all patients achieved the minimal flow required for adequate drug delivery. Enhanced training could be useful, especially in COPD patients

Controlling Level of Unconsciousness by Titrating Propofol with Deep Reinforcement Learning

Reinforcement Learning (RL) can be used to fit a mapping from patient state to a medication regimen. Prior studies have used deterministic and value-based tabular learning to learn a propofol dose from an observed anesthetic state. Deep RL replaces the table with a deep neural network and has been used to learn medication regimens from registry databases. Here we perform the first application of deep RL to closed-loop control of anesthetic dosing in a simulated environment. We use the cross-entropy method to train a deep neural network to map an observed anesthetic state to a probability of infusing a fixed propofol dosage. During testing, we implement a deterministic policy that transforms the probability of infusion to a continuous infusion rate. The model is trained and tested on simulated pharmacokinetic/pharmacodynamic models with randomized parameters to ensure robustness to patient variability. The deep RL agent significantly outperformed a proportional-integral-derivative controller (median absolute performance error 1.7% +/- 0.6 and 3.4% +/- 1.2). Modeling continuous input variables instead of a table affords more robust pattern recognition and utilizes our prior domain knowledge. Deep RL learned a smooth policy with a natural interpretation to data scientists and anesthesia care providers alike.Comment: International Conference on Artificial Intelligence in Medicine 202

Logarithmic operators in the SL(2,R) WZNW model

We find some exact solutions of the Knizhnik-Zamolodchikov equation for the four point correlation functions that occur in the SL(2,R) WZNW model. They exhibit logarithmic behaviour in both the Kac-Moody and Virasoro parts. We discuss their implication for the operator product expansion. We also observe the appearance of several symmetries of the correlation functions.Comment: 23 pages, LATEX, Revised Version. More references adde

Aerodynamic Drag Reduction of Emergency Response Vehicles

This paper presents the first experimental and computational investigation into the aerodynamics of emergency response vehicles and focusses on reducing the additional drag that results from the customary practice of adding light-bars onto the vehicles’ roofs. A series of wind tunnel experiments demonstrate the significant increase in drag that results from the light bars and show these can be minimized by reducing the flow separation caused by them. Simple potential improvements in the aerodynamic design of the light bars are investigated by combining Computational Fluid Dynamics (CFD) with Design of Experiments and metamodelling methods. An aerofoil-based roof design concept is shown to reduce the overall aerodynamic drag by up to 20% and an analysis of its effect on overall fuel consumption indicates that it offers a significant opportunity for improving the fuel economy and reducing emissions from emergency response vehicles. These benefits are now being realised by the UK’s ambulance service

Residual effects of esmirtazapine on actual driving performance: overall findings and an exploratory analysis into the role of CYP2D6 phenotype

INTRODUCTION: Esmirtazapine is evaluated as a novel drug for treatment of insomnia. PURPOSE: The present study was designed to assess residual effects of single and repeated doses of esmirtazapine 1.5 and 4.5 mg on actual driving in 32 healthy volunteers in a double-blind, placebo-controlled study. Treatment with single doses of zopiclone 7.5 mg was included as active control. METHODS: Treatments were administered in the evening. Driving performance was assessed in the morning, 11 h after drug intake, in a standardized on-the-road highway driving test. The primary study parameter was standard deviation of lateral position (SDLP), a measure of "weaving". All subjects were subjected to CYP2D6 phenotyping in order to distinguish poor metabolizers from extensive metabolizers of esmirtazapine. RESULTS: Overall, esmirtazapine 1.5 mg did not produce any clinically relevant change in SDLP after single and repeated dosing. Driving impairment, i.e., a rise in SDLP, did occur after a single-dose administration of esmirtazapine 4.5 mg but was resolved after repeated doses. Acute driving impairment was more pronounced after both doses of esmirtazapine in a select group of poor metabolizers (N = 7). A single-dose zopiclone 7.5 mg also increased SDLP as expected. CONCLUSION: It is concluded that single and repeated doses of 1.5 mg esmirtazapine are generally not associated with residual impairment. Single-dose administration of 4.5 mg esmirtazapine was associated with residual impairment that generally resolved after repeated administration. Exploratory analysis in a small group of poor CYP 2D6 metabolizers suggested that these subjects are more sensitive to the impairing effects of esmirtazapine on car driving

Stochastic descriptors to study the fate and potential of naive T cell clonotypes in the periphery

The population of naive T cells in the periphery is best described by determining both its T cell receptor diversity, or number of clonotypes, and the sizes of its clonal subsets. In this paper, we make use of a previously introduced mathematical model of naive T cell homeostasis, to study the fate and potential of naive T cell clonotypes in the periphery. This is achieved by the introduction of several new stochastic descriptors for a given naive T cell clonotype, such as its maximum clonal size, the time to reach this maximum, the number of proliferation events required to reach this maximum, the rate of contraction of the clonotype during its way to extinction, as well as the time to a given number of proliferation events. Our results show that two fates can be identified for the dynamics of the clonotype: extinction in the short-term if the clonotype experiences too hostile a peripheral environment, or establishment in the periphery in the long-term. In this second case the probability mass function for the maximum clonal size is bimodal, with one mode near one and the other mode far away from it. Our model also indicates that the fate of a recent thymic emigrant (RTE) during its journey in the periphery has a clear stochastic component, where the probability of extinction cannot be neglected, even in a friendly but competitive environment. On the other hand, a greater deterministic behaviour can be expected in the potential size of the clonotype seeded by the RTE in the long-term, once it escapes extinction

Advances in mass spectrometry-based post-column bioaffinity profiling of mixtures

In the screening of complex mixtures, for example combinatorial libraries, natural extracts, and metabolic incubations, different approaches are used for integrated bioaffinity screening. Four major strategies can be used for screening of bioactive mixtures for protein targets—pre-column and post-column off-line, at-line, and on-line strategies. The focus of this review is on recent developments in post-column on-line screening, and the role of mass spectrometry (MS) in these systems. On-line screening systems integrate separation sciences, mass spectrometry, and biochemical methodology, enabling screening for active compounds in complex mixtures. There are three main variants of on-line MS based bioassays: the mass spectrometer is used for ligand identification only; the mass spectrometer is used for both ligand identification and bioassay readout; or MS detection is conducted in parallel with at-line microfractionation with off-line bioaffinity analysis. On the basis of the different fields of application of on-line screening, the principles are explained and their usefulness in the different fields of drug research is critically evaluated. Furthermore, off-line screening is discussed briefly with the on-line and at-line approaches