Cleaning of viscous drops on a flat inclined surface using gravity-driven film flows

We investigate the fluid mechanics of cleaning viscous drops attached to a flat inclined surface using thin gravity-driven film flows. We focus on the case where the drop cannot be detached from the surface by the mechanical forces exerted by the cleaning fluid on the drop surface. The fluid in the drop dissolves into the cleaning film flow, which then transports it away. To assess the impact of the drop on the velocity of the cleaning fluid, we have developed a novel experimental technique based on particle image velocimetry. We show the velocity distribution at the film surface in the situations both where the film is flowing over a smooth surface, and where it is perturbed by a solid obstacle representing a very viscous drop. We find that at intermediate Reynolds numbers the acceleration of the starting film is overestimated by a plane model using the lubrication approximation. In the perturbed case, the streamwise velocity is strongly affected by the presence of the obstacle. The upstream propagation of the disturbance is limited, but the disturbance extends downstream for distances larger than 10 obstacle diameters. Laterally, we observe small disturbances in both the streamwise and lateral velocity, owing to stationary capillary waves. The flow also exhibits a complex three-dimensional converging pattern immediately below the obstacle.J. R. Landel acknowledges financial support from Magdalene College, Cambridge, through a Nevile Research Fellowship in Applied Mathematics. This material is based upon work supported by the Defense Threat Reduction Agency under Contract No. HDTRA1-12-D- 0003-0001.This is the accepted manuscript. The final version is available from Elsevier at http://www.sciencedirect.com/science/article/pii/S0960308514001175

Gender classification based on gait analysis using ultrawide band radar augmented with artificial intelligence

The identification of individuals based on their walking patterns, also known as gait recognition, has garnered considerable interest as a biometric trait. The use of gait patterns for gender classification has emerged as a significant research domain with diverse applications across multiple fields. The present investigation centers on the classification of gender based on gait utilizing data from Ultra-wide band radar. A total of 181 participants were included in the study, and data was gathered using Ultra-wide band radar technology. This study investigates various preprocessing techniques, feature extraction methods, and dimensionality reduction approaches to efficiently process Ultra-wide band radar data. The data quality is improved through the utilization of a two-pulse canceller and discrete wavelet transform. The hybrid feature dataset is generated through the creation of gray-level co-occurrence matrices and subsequent extraction of statistical features. Principal Component Analysis is utilized for dimensionality reduction, and prediction probabilities are incorporated as features for classification optimization. The present study employs k-fold cross-validation to train and assess machine learning classifiers, Decision Tree, Random Forest, Support Vector Machine, Logistic Regression, Multi-Layer Perceptron, K-Nearest Neighbors, and Extra Tree Classifier. The Multilayer Perceptron exhibits superior performance, achieving an accuracy of 0.936. The Support Vector Machine and k-Nearest Neighbors classifiers closely trail behind, both achieving an accuracy of 0.934. This research is of the utmost importance due to its capacity to offer solutions to crucial problems in multiple domains. The findings indicate that the utilization of UWB radar data for gait-based gender classification holds promise in diverse domains, including biometrics, surveillance, and healthcare. The present study makes a valuable contribution to the progress of gender classification systems that rely on gait patterns

Convective mass transfer from a submerged drop in a thin falling film

We study the fluid mechanics of removing a passive tracer contained in small, viscous drops attached to a flat inclined substrate using thin gravity-driven film flows. A convective mass transfer establishes across the drop-film interface and the tracer in the drop diffuses into the film flow. The Peclet number for the tracer in the film is large. The Peclet number Pe_d in the drop varies from 0.01 to 1. The characteristic transport time in the drop is much larger than in the film. We model the mass transfer of the tracer from the drop bulk into the film using an empirical model based on Newton's law of cooling. This model is supported by a theoretical model solving the quasi-steady 2D advection-diffusion equation in the film coupled with a time-dependent 1D diffusion equation in the drop. We find excellent agreement between our experimental data and the 2 models, which predict an exponential decrease in time of the tracer concentration in the drop. The results are valid for all drop and film Peclet numbers studied. The transport characteristic time is related to the drop diffusion time scale, as diffusion within the drop is the limiting process. Our theoretical model predicts the well-known relationship between the Sherwood and Reynolds numbers in the case of a well-mixed drop Sh~Re_L^{1/3}=\gamma L^2/\nu_f, based on the drop length L, film shear rate \gamma and film kinematic viscosity \nu_f. We show that this relationship is mathematically equivalent to a more physically intuitive relationship Sh~Re_\delta, based on the diffusive boundary layer thickness \delta. The model also predicts a correction in the case of a non-uniform drop concentration, which depends on Re_\delta, the Schmidt number, the drop aspect ratio and the diffusivity ratio. This prediction is in agreement with experiments at low Pe_d. It also agrees as Pe_d approaches 1, although the influence of Re_\delta increases.We wish to thank D. Page-Croft and the technicians of the GK Batchelor Laboratory at the Department of Applied Mathematics and Theoretical Physics, Cambridge. We are grateful to F. Bartholomew, F. Yuen and M. Etzold from the BP Institute, Cambridge, for their help in conducting contact angle and viscosity measurements. J. R. L. wishes to thank his colleagues P. Luzzatto-Fegiz and F. Peaudecerf for fruitful discussions. J. R. L. acknowledges financial support from Magdalene College, Cambridge, through a Nevile Research Fellowship in Applied Mathematics. This material is based upon work supported by the Defense Threat Reduction Agency under Contract No. HDTRA1-12-D-0003-0001.This is the author accepted manuscript. The final version is available from Cambridge University Press via http://dx.doi.org/10.1017/jfm.2015.742

The VLT-FLAMES Tarantula Survey

We present a number of notable results from the VLT-FLAMES Tarantula Survey (VFTS), an ESO Large Program during which we obtained multi-epoch medium-resolution optical spectroscopy of a very large sample of over 800 massive stars in the 30 Doradus region of the Large Magellanic Cloud (LMC). This unprecedented data-set has enabled us to address some key questions regarding atmospheres and winds, as well as the evolution of (very) massive stars. Here we focus on O-type runaways, the width of the main sequence, and the mass-loss rates for (very) massive stars. We also provide indications for the presence of a top-heavy initial mass function (IMF) in 30 Dor.Comment: 7 Figures, 8 pages. Invited talk: IAUS 329: "The Lives and Death-Throes of Massive Stars

Cleaning of viscous droplets on an inclined planar surface using film flows

We investigate the fluid mechanics of cleaning viscous drops attached to a flat inclined surface using thin gravity-driven film flows. We focus on the case where the drop cannot be detached from the surface by the mechanical forces exerted by the cleaning fluid on the drop surface. The fluid in the drop dissolves into the cleaning film flow, which then transports it away. We present a mathematical model for the mass transfer of the viscous fluid from the droplet into the film flow. The model assumes that the droplet has a negligible impact on the film velocity. To assess the impact of the drop on the velocity of the cleaning fluid, we have developed a novel experimental technique based on particle image velocimetry. We find that at intermediate Reynolds number the streamwise velocity can be strongly affected by the presence of the droplet. We discuss this impact on the cleaning of the droplet. Using the dye attenuation technique, we also measure the convective mass transfer of some dye mixed into the droplet and diffusing into the falling film. We find that the total amount of dye in the droplet decreases exponentially in time.This material is based upon work supported by the Defense Threat Reduction Agency under Contract No. HDTRA1-12-D- 0003-0001.This is the author accepted manuscript. The final version is available from Australian Fluids Mechanics Society via http://people.eng.unimelb.edu.au/imarusic/proceedings/19%20AFMC%20TOC.htm (#275

Congenital infiltrative lipomas and retroperitoneal perirenal lipomas in a calf

BACKGROUND: Congenital lipocytic tumours have rarely been reported in cattle. Lipomas are benign tumours, but infiltrative lipomas have significant health implications due to their aggressive infiltrative growth pattern. CASE PRESENTATION: A calf was born with skeletal malformations and soft tissue proliferations, primarily on the external thoracic wall. The calf was euthanized for welfare reasons and submitted for post mortem examination. Necropsy, histopathology and post mortem computed tomography scanning revealed two types of lipocytic tumours. Widespread infiltrative lipomas were present in the muscles and connective tissues along the vertebral column and diffusely invaded the external soft tissues of the right thoracic wall. The neoplastic lipocytes had invaded intervertebral spaces thus causing congenital vertebral malformations, and further invaded the vertebral canal and the bone marrow of coccygeal vertebrae. Periosteal localization of the tumour was associated with costal hyperostosis. Two large retroperitoneal lipomas enclosed the kidneys and occupied much of the abdominal space. CONCLUSION: The development of congenital bone malformation in this calf illustrates the severe consequences of the infiltrative and aggressive growth of infiltrative lipomas during foetal development. The congenital retroperitoneal lipomas occupied a large part of abdominal cavity, but did not invade the adjacent tissues. Due to their large size, perirenal lipomas should be considered in calves with distended abdomen, even in cases without other signs of tumours

Imaging haemodynamic changes related to seizures: comparison of EEG-based general linear model, independent component analysis of fMRI and intracranial EEG

Background: Simultaneous EEG-fMRI can reveal haemodynamic changes associated with epileptic activity which may contribute to understanding seizure onset and propagation. Methods: Nine of 83 patients with focal epilepsy undergoing pre-surgical evaluation had seizures during EEG-fMRI and analysed using three approaches, two based on the general linear model (GLM) and one using independent component analysis (ICA): 1. EEGs were divided into up to three phases: early ictal EEG change, clinical seizure onset and late ictal EEG change and convolved with a canonical haemodynamic response function (HRF) (canonical GLM analysis). 2. Seizures lasting three scans or longer were additionally modelled using a Fourier basis set across the entire event (Fourier GLM analysis). 3. Independent component analysis (ICA) was applied to the fMRI data to identify ictal BOLD patterns without EEG. The results were compared with intracranial EEG. Results: The canonical GLM analysis revealed significant BOLD signal changes associated with seizures on EEG in 7/9 patients, concordant with the seizure onset zone in 4/7. The Fourier GLM analysis revealed changes in BOLD signal corresponding with the results of the canonical analysis in two patients. ICA revealed components spatially concordant with the seizure onset zone in all patients (8/9 confirmed by intracranial EEG). Conclusion: Ictal EEG-fMRI visualises plausible seizure related haemodynamic changes. The GLM approach to analysing EEG-fMRI data reveals localised BOLD changes concordant with the ictal onset zone when scalp EEG reflects seizure onset. ICA provides additional information when scalp EEG does not accurately reflect seizures and may give insight into ictal haemodynamics

Automatic User Preferences Selection of Smart Hearing Aid Using BioAid

Noisy environments, changes and variations in the volume of speech, and non-face-to-face conversations impair the user experience with hearing aids. Generally, a hearing aid amplifies sounds so that a hearing-impaired person can listen, converse, and actively engage in daily activities. Presently, there are some sophisticated hearing aid algorithms available that operate on numerous frequency bands to not only amplify but also provide tuning and noise filtering to minimize background distractions. One of those is the BioAid assistive hearing system, which is an open-source, freely available downloadable app with twenty-four tuning settings. Critically, with this device, a person suffering with hearing loss must manually alter the settings/tuning of their hearing device when their surroundings and scene changes in order to attain a comfortable level of hearing. However, this manual switching among multiple tuning settings is inconvenient and cumbersome since the user is forced to switch to the state that best matches the scene every time the auditory environment changes. The goal of this study is to eliminate this manual switching and automate the BioAid with a scene classification algorithm so that the system automatically identifies the user-selected preferences based on adequate training. The aim of acoustic scene classification is to recognize the audio signature of one of the predefined scene classes that best represent the environment in which it was recorded. BioAid, an open-source biological inspired hearing aid algorithm, is used after conversion to Python. The proposed method consists of two main parts: classification of auditory scenes and selection of hearing aid tuning settings based on user experiences. The DCASE2017 dataset is utilized for scene classification. Among the many classifiers that were trained and tested, random forests have the highest accuracy of 99.7%. In the second part, clean speech audios from the LJ speech dataset are combined with scenes, and the user is asked to listen to the resulting audios and adjust the presets and subsets. A CSV file stores the selection of presets and subsets at which the user can hear clearly against the scenes. Various classifiers are trained on the dataset of user preferences. After training, clean speech audio was convolved with the scene and fed as input to the scene classifier that predicts the scene. The predicted scene was then fed as input to the preset classifier that predicts the user’s choice for preset and subset. The BioAid is automatically tuned to the predicted selection. The accuracy of random forest in the prediction of presets and subsets was 100%. This proposed approach has great potential to eliminate the tedious manual switching of hearing assistive device parameters by allowing hearing-impaired individuals to actively participate in daily life by automatically adjusting hearing aid settings based on the acoustic scen

Imaging fast electrical activity in the brain with electrical impedance tomography.

Imaging of neuronal depolarization in the brain is a major goal in neuroscience, but no technique currently exists that could image neural activity over milliseconds throughout the whole brain. Electrical impedance tomography (EIT) is an emerging medical imaging technique which can produce tomographic images of impedance changes with non-invasive surface electrodes. We report EIT imaging of impedance changes in rat somatosensory cerebral cortex with a resolution of 2ms and <200μm during evoked potentials using epicortical arrays with 30 electrodes. Images were validated with local field potential recordings and current source-sink density analysis. Our results demonstrate that EIT can image neural activity in a volume 7×5×2mm in somatosensory cerebral cortex with reduced invasiveness, greater resolution and imaging volume than other methods. Modeling indicates similar resolutions are feasible throughout the entire brain so this technique, uniquely, has the potential to image functional connectivity of cortical and subcortical structures