FORTY FIVE YEARS OF ANTICOAGULANT RODENTICIDES — PAST, PRESENT AND FUTURE TRENDS

The anticoagulant rodenticides were discovered in the 1940s and their advantages of efficacy and safety quickly resulted in their use dominating the practice of rodent control in temperate countries. However, the development of resistance to the early compounds within a decade stimulated research culminating in the invention of anew class of anticoagulant, the second generation compounds, active against resistant strains but also overall far more potent than those previously available. A novel baiting strategy, pulsed baiting, was developed to make full use of this valuable characteristic. Pulsed baiting has enabled the use of second generation anticoagulants in situations where early products were of limited value, particularly in tropical agriculture. The future of this highly-successful group of compounds is reviewed in relation to resistance and the difficulty and cost of developing further rodenticides

The effect of particle size distribution on froth stability in flotation

Separation of particles of different surface properties using froth flotation is a widely-used industrial process, particularly in the minerals industry where it is used to concentrate minerals from ore. One of the key challenges in developing models to predict flotation performance is the interdependent nature of the process variables and operating parameters, which limits the application of optimising process control strategies at industrial scale. Froth stability, which can be quantified using air recovery (the fraction of air entering a flotation cell that overflows in the concentrate as unburst bubbles), has been shown to be linked to flotation separation performance, with stable froths yielding improved mineral recoveries. While it is widely acknowledged that there is an optimum particle size range for collection of particles in the pulp phase, the role of particle size on the measured air recovery and the resulting link to changes in flotation performance is less well understood. This is related to the difficulty in separating particle size and liberation effects. In this work, the effects of particle size distribution on air recovery are studied in a single species (silica) system using a continuous steady-state laboratory flotation cell. This allows an investigation into the effects of particle size distribution only on froth stability, using solids content and solids recovery as indicators of flotation performance. It is shown that, as the cell air rate is increased, the air recovery of the silica system passes through a peak, exhibiting the same froth behaviour as measured industrially. The air recovery profiles of systems with three different particle size distributions (d80 of 89.6, 103.5 and 157.1 μm) are compared. The results show that, at lower air rates, the intermediate particle size distribution (103.5 μm) yields the most stable froth, while at higher air rates, the finest particles (89.6 μm) result in higher air recoveries. This is subsequently linked to changes in flotation performance. The results presented here highlight, for the first time, the link between particle size distribution in flotation feeds, air recovery and flotation performance. The results demonstrate that there is an optimal air rate for each particle size distribution, therefore changes in particle size distribution in the feed to flotation cells require a change in air rate in order to maximise mineral recovery

Performance Study of MXene/Carbon Nanotube Composites for Current Collector‐ and Binder‐Free Mg–S Batteries

The realization of sustainable and cheap Mg-S batteries depends on significant improvements in cycling stability. Building on the immense research on cathode optimization from Li-S batteries, for the first time a beneficial role of MXenes for Mg-S batteries is reported. Through a facile, low-temperature vacuum-filtration technique, several novel current collector- and binder-free cathode films were developed, with either dipenthamethylene thiuram tetrasulfide (PMTT) or $S_{8}$ nanoparticles as the source of redox-active sulfur. The importance of combining MXene with a high surface area co-host material, such as carbon nanotubes, was demonstrated. A positive effect of MXenes on the average voltage and reduced self-discharge was also discovered. Ascribed to the rich polar surface chemistry of $Ti_{3}C_{2}T_{x}$ MXene, an almost doubling of the discharge capacity (530 vs. 290 mA h $g^{−1}$) was achieved by using MXene as a polysulfide-confining interlayer, obtaining a capacity retention of 83 % after 25 cycles

A universal framework for Space Resource Utilisation (SRU)

Space Resource Utilisation (SRU) or In Situ Resource Utilisation (ISRU) is the use of natural resources from the Moon, Mars and other bodies for use in situ or elsewhere in the Solar System. The implementation of SRU technologies will provide the breakthrough for humankind to explore further into space. A range of extraction processes to produce usable resources have been proposed, such as oxygen production from lunar regolith, extraction of lunar ice and construction of habitation by 3D printing. Practical and successful implementation of SRU requires that all the stages of the process flowsheet (excavation, beneficiation and extraction) are considered. This requires a complete ‘mine-to-market’ type approach, analogous to that of terrestrial mineral extraction. One of the key challenges is the unique cross-disciplinary nature of SRU; it integrates space systems, robotics, materials handling and beneficiation, and chemical process engineering. This is underpinned by knowledge of the lunar or planetary geology, including mineralogy, physical characteristics, and the variability in local materials. Combining such diverse fields in a coordinated way requires the use of a universal framework. The framework will enable integration of operations and comparison of technologies, and will define a global terminology to be used across all fields. In this paper, a universal SRU flowsheet and terminology are described, and a matrix approach to describing regolith characteristics specifically for SRU is proposed. This is the first time that such an approach has been taken to unify this rapidly-developing sector

Proteases in Plasma and Kidney of db/db Mice as Markers of Diabetes-Induced Nephropathy

Db/db mice are overweight, dyslipidemic and develop diabetic complications, relevant for similar complications in human type 2 diabetes. We have used db/db and db/+ control mice to investigate alterations in proteinase expression and activity in circulation and kidneys by SDS-PAGE zymography, electron microscopy, immunohistochemistry, Western blotting, and in situ zymography. Plasma from db/db mice contained larger amounts of serine proteinases compared to db/+ mice. Kidneys from the db/db mice had a significantly larger glomerular surface area and somewhat thicker glomerular basement membranes compared to the db/+ mice. Furthermore, kidney extracts from db/+ mice contained metalloproteinases with Mr of approximately 92000, compatible with MMP-9, not observed in db/db mice. These results indicate that higher levels of serine proteinases in plasma may serve as potential markers for kidney changes in db/db mice, whereas a decrease in MMP-9 in the kidney may be related to the glomerular changes

Comperative analysis of the DI diesel engine in-cylinder fluid flow applying PIV measurements and CFD simulations

Paper presented to the 10th International Conference on Heat Transfer, Fluid Mechanics and Thermodynamics, Florida, 14-16 July 2014.To improve the efficiency of diesel engines several actions have been performed. Beside the reduction of internal friction by applying new and more effective materials, the thermodynamics offer different opportunities to influence the engine performance and emissions. Especially the interaction of fuel and air flow within the combustion chamber should be investigated. Therefore an optimized in-cylinder flow can enhance air-fuel mixing and lead to lower exhaust emissions and less fuel consumption. In addition the turbulent flow within the cylinder exhibits large- and small-scale cyclic variations[1]. The turbulence characteristics and cycle to cycle fluctuations of the in-cylinder flow can also have a pronounced influence on the combustion process and evoke the need to be thoroughly investigated. Nowadays CFD simulations are widely used to predict and optimise the air flow within internal combustion engines, but such numerical calculations require a comparison with experimental data. Particle Image Velocimetry (PIV) was applied on an optically accessible single cylinder diesel engine to receive data sets for validation purpose. This engine provides access through a glass ring with 30 mm height and a modified piston bowl with an integrated glass bottom. In order to detect the local dependencies of the air flow, the velocity fields were quantified in two horizontal and three vertical measurement planes. A high resolution double shutter camera and a high energy double pulse laser were applied to measure the velocity fields during the intake and compression phases. In order to study the cyclic fluctuations, instantaneous snapshot pairs from 100 successive cycles were taken. As a result of the strong turbulences inside the internal combustion chamber strong cyclic fluctuations were observed at all investigated measurement planes. The measured averaged in-cylinder velocities and indicated pressures were compared with a k-ε turbulence model simulation, based on an Unsteady Reynolds Averaged NavierStockes (URANS) approach. In addition, the swirl and tumble characteristics were calculated and checked against the measured ones. Despite a sufficient accordance between the experimentally determined and k-ε model calculated in-cylinder velocities, discrepancies in swirl and the tumble flow could be observed. Therefore the air flow was also simulated using a Scale-Adaptive Simulation (SAS) turbulence model in order to resolve the small scale turbulences inside the combustion chamber. The achieved solution was compared with the velocities fields, averaged over 100 cycles, as well as the single cycle velocities to avoid the elimination of small scale turbulences due to cyclic variations.cf201

Comparison of manual and artificial intelligence based quantification of myocardial strain by feature tracking - a cardiovascular MR study in health and disease

OBJECTIVES: The analysis of myocardial deformation using feature tracking in cardiovascular MR allows for the assessment of global and segmental strain values. The aim of this study was to compare strain values derived from artificial intelligence (AI)-based contours with manually derived strain values in healthy volunteers and patients with cardiac pathologies. MATERIALS AND METHODS: A cohort of 136 subjects (60 healthy volunteers and 76 patients; of those including 46 cases with left ventricular hypertrophy (LVH) of varying etiology and 30 cases with chronic myocardial infarction) was analyzed. Comparisons were based on quantitative strain analysis and on a geometric level by the Dice similarity coefficient (DSC) of the segmentations. Strain quantification was performed in 3 long-axis slices and short-axis (SAX) stack with epi- and endocardial contours in end-diastole. AI contours were checked for plausibility and potential errors in the tracking algorithm. RESULTS: AI-derived strain values overestimated radial strain (+ 1.8 ± 1.7% (mean difference ± standard deviation); p = 0.03) and underestimated circumferential (- 0.8 ± 0.8%; p = 0.02) and longitudinal strain (- 0.1 ± 0.8%; p = 0.54). Pairwise group comparisons revealed no significant differences for global strain. The DSC showed good agreement for healthy volunteers (85.3 ± 10.3% for SAX) and patients (80.8 ± 9.6% for SAX). In 27 cases (27/76; 35.5%), a tracking error was found, predominantly (24/27; 88.9%) in the LVH group and 22 of those (22/27; 81.5%) at the insertion of the papillary muscle in lateral segments. CONCLUSIONS: Strain analysis based on AI-segmented images shows good results in healthy volunteers and in most of the patient groups. Hypertrophied ventricles remain a challenge for contouring and feature tracking. CLINICAL RELEVANCE STATEMENT: AI-based segmentations can help to streamline and standardize strain analysis by feature tracking. KEY POINTS: • Assessment of strain in cardiovascular magnetic resonance by feature tracking can generate global and segmental strain values. • Commercially available artificial intelligence algorithms provide segmentation for strain analysis comparable to manual segmentation. • Hypertrophied ventricles are challenging in regards of strain analysis by feature tracking

Success Factors of European Syndromic Surveillance Systems: A Worked Example of Applying Qualitative Comparative Analysis

Introduction: Syndromic surveillance aims at augmenting traditional public health surveillance with timely information. To gain a head start, it mainly analyses existing data such as from web searches or patient records. Despite the setup of many syndromic surveillance systems, there is still much doubt about the benefit of the approach. There are diverse interactions between performance indicators such as timeliness and various system characteristics. This makes the performance assessment of syndromic surveillance systems a complex endeavour. We assessed if the comparison of several syndromic surveillance systems through Qualitative Comparative Analysis helps to evaluate performance and identify key success factors. Materials and Methods: We compiled case-based, mixed data on performance and characteristics of 19 syndromic surveillance systems in Europe from scientific and grey literature and from site visits. We identified success factors by applying crisp-set Qualitative Comparative Analysis. We focused on two main areas of syndromic surveillance application: seasonal influenza surveillance and situational awareness during different types of potentially health threatening events. Results: We found that syndromic surveillance systems might detect the onset or peak of seasonal influenza earlier if they analyse non-clinical data sources. Timely situational awareness during different types of events is supported by an automated syndromic surveillance system capable of analysing multiple syndromes. To our surprise, the analysis of multiple data sources was no key success factor for situational awareness. Conclusions: We suggest to consider these key success factors when designing or further developing syndromic surveillance systems. Qualitative Comparative Analysis helped interpreting complex, mixed data on small-N cases and resulted in concrete and practically relevant findings