Sensitivity analysis and parameter estimation for distributed hydrological modeling: potential of variational methods

Variational methods are widely used for the analysis and control of computationally intensive spatially distributed systems. In particular, the adjoint state method enables a very efficient calculation of the derivatives of an objective function (response function to be analysed or cost function to be optimised) with respect to model inputs. In this contribution, it is shown that the potential of variational methods for distributed catchment scale hydrology should be considered. A distributed flash flood model, coupling kinematic wave overland flow and Green Ampt infiltration, is applied to a small catchment of the Thoré basin and used as a relatively simple (synthetic observations) but didactic application case. It is shown that forward and adjoint sensitivity analysis provide a local but extensive insight on the relation between the assigned model parameters and the simulated hydrological response. Spatially distributed parameter sensitivities can be obtained for a very modest calculation effort (~6 times the computing time of a single model run) and the singular value decomposition (SVD) of the Jacobian matrix provides an interesting perspective for the analysis of the rainfall-runoff relation. For the estimation of model parameters, adjoint-based derivatives were found exceedingly efficient in driving a bound-constrained quasi-Newton algorithm. The reference parameter set is retrieved independently from the optimization initial condition when the very common dimension reduction strategy (i.e. scalar multipliers) is adopted. Furthermore, the sensitivity analysis results suggest that most of the variability in this high-dimensional parameter space can be captured with a few orthogonal directions. A parametrization based on the SVD leading singular vectors was found very promising but should be combined with another regularization strategy in order to prevent overfitting

Physical modeling of bilabial plosives production

International audienceThe context of this study is the physical modeling of speech production. The first step of our approach is to realize in-vivo measurements during the production of the vowel-consonant-vowel sequence /apa/. This measurements concerns intra-oral pressure, acoustic pressure radiated at the lips and labial parameters (aperture and width of the lips) derived from a high-speed video recording of the subject face. In a second time, theoretical models from speech production literature are under investigation to predict the air flow trough the lips. A model is validated by comparing his predictions with results obtained from measurements on a replica of phonatory system. Then, the same experimental set-up is used to introduce an aerodynamic model of supraglottal cavity expansion. Finally, we achieve numerical simulations of a vowel-bilabial plosive-vowel utterance, by using these models. Simulation results highlight the influence of the cheeks expansion during the production of bilabial plosives

Is interleukin-1 a good target for therapeutic intervention in intervertebral disc degeneration: lessons from the osteoarthritic experience

IL-1 plays a key role in disc degeneration and could be a valid target for inhibiting this process. IL-1 receptor antagonist (IL-1ra) might be a good candidate to inhibit IL-1 activity. However, many questions need to be addressed before contemplating therapy in humans. IL-1 blockade is also a great challenge in osteoarthritis and results from animal models suggest that IL-1ra may have beneficial effects. The clinical benefit of a local injection of IL-1ra in knee osteoarthritis may be limited by the antagonist's short half-life. Further studies with longer-lasting antagonists are needed to explore this new therapeutic approach

Multi-method 2D and 3D reconstruction of gold grains morphology in alluvial deposits : a review and application to the Rivière du Moulin (Québec, Canada)

The aim of this paper is to document and compare the 2D qualitative and semi-quantitative methods currently used to describe the shape of gold grains in fluvial environments with the 3D quantitative methods using X-ray microtomography and SEM photogrammetry. These 3D methods are used to compute flatness, roundness, convexity, sphericity and ellipticity shape descriptors of 13 gold grains from the Rivière du Moulin (Québec, Canada) in order to quantify the morphological change along 9 km of fluvial transport. Gold grains have moderate to high values of flatness, compactness, sphericity and ellipticity indices that do not change significantly with distance of transport, whereas the roundness increases during transport. Gold grains are used to compare 2D and 3D methods, and the results show small differences (<8%) when shape descriptors are computed using image analysis software, whereas the difference (up to 70%) is more important for 2D measurements performed by a human operator. For application and characterization on a large set of gold grains, the 2D methods offer the advantage of speed, whereas, for a more detailed study on a limited number of gold grains, 3D methods enable estimation of the volume and yield more detailed shape descriptor changes during fluvial transport

Quantification of the morphology of gold grains in 3D using X-ray microscopy and SEM photogrammetry

The shape of gold is widely used in mineral exploration and in sedimentology to estimate the distance of transport from the source to the site of deposition. However, estimation of the morphology is based on qualitative observations or on the quantification of shape in 2D. The 3D analysis of grain shape is useful for accurate morphometric quantification and to evaluate its volume, which is related to particle size. This study compares X-ray 3D microscope and 3D SEM photogrammetry to reconstruct the shape of gold particles. These new methods are exploited to quantify the shape of gold grains 85 to 300 μm in size. The shape parameters, such as axial lengths, surface area, volume, diameter of curvature of all corners, and diameter of the largest inscribed sphere and smallest circumscribed sphere are measured on a particle in order to estimate shape factors such as flatness ratios, shape indices, sphericity, and roundness. Most shape parameters and shape factors estimated on the same gold grain with simple geometry are similar between the two approaches. This result validates these methods for the 3D description of gold particles with simple morphology, while providing a methodology for describing grains with more complex geometry

Cardiovascular risk factors and determinants of clinical outcomes in type 2 diabetic patients at a tertiary-care centre

Background: The prevalence of type 2 diabetes mellitus (T2DM) is growing rapidly worldwide. The global burden of T2DM in 2013 was 382 million and projected to 592 million by 2035, accounting for 7.8% of the adult population. The objective of this study was to record treatments, risk factor control, determinants of glycaemic control and cardiovascular outcomes in type 2 diabetes (T2DM).Methods: We included adult T2DM patients and followed up for 6 months. Patients were categorised into good (HbA1c 8.5%). We used multiple logistic regression to identify determinants of glycaemic control and outcomes.Results: We recruited 785 patients with a mean age of 55.43 (±11.1) years, and 43.8% were women. At baseline, patients with poor control (45%) were younger and from lower socioeconomic strata (73.5%). At 6 months, the American Diabetes Association (ADA) targets of HbA1c was met only in 27.52%, systolic blood pressure (SBP) in 81.47% and low density lipoprotein (LDL) cholesterol in 48.86% patients. Patients with sedentary or low physical activity (Odds ratio 11.51, 95% confidence interval 3.48, 37.98; p<0.001) and with diabetes for a longer duration (OR 1.14 [1.07-1.22], p<0.001) were more likely to be in poor glucose control. Patients having sedentary or low physical activity (OR 6.66 [1.730-25.63] p = 0.006) and higher LDL cholesterol (OR 1.04 [1.01-1.07], p = 0.008) were more likely to get microvascular complications.Conclusions: Management of modifiable risk factors and early control of hyperglycaemia should be given more importance

Computational classification of animals for a highway detection system

As colisões entre veículos e animais representam um sério problema na infraestrutura rodoviária. Para evitar tais acidentes, medidas mitigatórias têm sido aplicadas em diferentes regiões do mundo. Neste projeto é apresentado um sistema de detecção de animais em rodovias utilizando visão computacional e algoritmo de aprendizado de máquina. Os modelos foram treinados para classificar dois grupos de animais: capivaras e equídeos. Foram utilizadas duas variantes da rede neural convolucional chamada Yolo (você só vê uma vez) — Yolov4 e Yolov4-tiny (versão mais leve da rede) — e o treinamento foi realizado a partir de modelos pré-treinados. Testes de detecção foram realizados em 147 imagens e os resultados de precisão obtidos foram de 84,87% e 79,87% para Yolov4 e Yolov4-tiny, respectivamente. O sistema proposto tem o potencial de melhorar a segurança rodoviária reduzindo ou prevenindo acidentes com animais.Vehicle-animal collisions represent a serious problem in roadway infrastructure. To avoid these roadway collisions, different mitigation systems have been applied in various regions of the world. In this article, a system for detecting animals on highways is presented using computer vision and machine learning algorithms. The models were trained to classify two groups of animals: capybaras and donkeys. Two variants of the convolutional neural network called Yolo (You only look once) were used, Yolov4 and Yolov4-tiny (a lighter version of the network). The training was carried out using pre-trained models. Detection tests were performed on 147 images. The accuracy results obtained were 84.87% and 79.87% for Yolov4 and Yolov4-tiny, respectively. The proposed system has the potential to improve road safety by reducing or preventing accidents with animals