Effect of dog breed and body conformation on vertical ground reaction forces, impulses, and stance times

OBJECTIVES: To assess whether fully normalised vertical ground reaction forces and stance times obtained at a trot depend on dog breed or body conformations. METHODS: Peak vertical forces (PVF), vertical impulses (VI), stance times (ST), and ratio of forelimb impulse to total impulse (RVI) of 54 dogs of seven different breeds were normalised to body weight and body size according to the theory of dynamic similarity, and were tested for differences between breeds. Breeds were Borzoi, Bernese Mountain dog, Great Dane, Labrador Retriever, Landseer, Rhodesian Ridgeback, and Rottweiler. Body length ratio (BLR) and body mass index (BMI) were also compared between breeds. RESULTS: Significant differences between breeds were found for the normalised forelimb PVF, VI and ST, and hindlimb PVF. Looking at individual breeds, it was most evident that Borzois had a lower forelimb VI, and a higher hindlimb PVF than the other breeds. This resulted in Borzois having a lower RVI compared to other dogs, indicating a more caudally located centre of gravity. Only a few differences in gait parameters were found between other dog breeds. The BMI was significantly lower in Borzois than in other breeds, but was otherwise not associated with gait parameters. CLINICAL SIGNIFICANCE: Force plate data of dogs of different breeds are not necessarily comparable, even after full normalisation to body weight and body size. Group comparisons should only be made when the groups consist of breeds with similar body conformation

Modeling the complexation properties of mineral-bound organic polyelectrolyte: An attempt at comprehension using the model system alumina/polyacrylic acid/M (M = Eu, Cm, Gd)

International audienceThis paper contributes to the comprehension of kinetic and equilibrium phenomena governing metal ion sorption on organic-matter-coated mineral particles. Sorption and desorption experiments were carried out with Eu ion and polyacrylic acid (PAA)-coated alumina colloids at pH 5 in 0.1 M NaClO4 as a function of the metal ion loading. Under these conditions, M interaction with the solid is governed by sorbed PAA (PAAads). The results were compared with spectroscopic data obtained by time-resolved laser-induced fluorescence spectroscopy (TRLFS) with Cm and Gd. The interaction between M and PAAads was characterized by a kinetically controlled process: after rapid metal adsorption within less than 1 min, the speciation of complexed M changed at the particle surface till an equilibrium was reached after about 4 days. At equilibrium, one part of complexed M was shown to be not exchangeable. This process was strongly dependent on the ligand-to-metal ratio. Two models were tested to explain the data. In model 1, the kinetically controlled process was described through successive kinetically controlled reactions that follow the rapid metal ion adsorption. In model 2, the organic layer was considered as a porous medium: the kinetic process was explained by the diffusion of M from the surface into the organic layer. Model 1 allowed a very good description of equilibrium and kinetic experimental data. Model 2 could describe the data at equilibrium but could not explain the kinetic data accurately. In spite of this disagreement, model 2 appeared more realistic considering the results of the TRLFS measurements

Correlation of radiographic changes after tibial tuberosity advancement in dogs with cranial cruciate-deficient stifles with functional outcome

OBJECTIVE: To (1) evaluate radiographic changes associated with osteoarthrosis (OA) before and after tibial tuberosity advancement (TTA) and (2) determine if these changes are indicative of limb function as determined by kinetic gait analysis. STUDY DESIGN: Prospective clinical study. ANIMALS: Dogs (n=35) with cranial cruciate ligament (CCL) deficient stifles (38). METHODS: Variables recorded were: complete or partial CCL rupture, meniscal lesions, arthroscopically graded cartilage lesions, complications, and revision surgeries. Radiographic evaluation and kinetic gait analysis (vertical ground reaction forces [GRFs]) were conducted pre- and 4-16 months postoperatively (mean, 5.9 months). Radiographs were evaluated without knowledge of operative findings and functional outcome. A score (0-3) based on new bone production at 11 specific sites was used to grade OA. Soft tissue changes were classified separately as normal or excessive. Preoperative scores were correlated with clinical variables. Postoperative scores and progression of OA scores were correlated with clinical variables and GRFs. RESULTS: OA remained unchanged in 17 joints and progressed in 21 (55%). Dogs with meniscal lesions had higher OA scores preoperatively, but not at follow-up. Dogs with severe cartilage lesions at surgery had more progression of OA. GRFs improved after surgery and were not correlated with any of the radiographic OA scores. CONCLUSION: Progression of OA was greater in the presence of severe cartilage lesions at surgery. OA scores were not correlated with GRFs. CLINICAL RELEVANCE: Progression of OA is generally expected to occur after TTA despite improvement of limb function

Scalable and Interpretable One-class SVMs with Deep Learning and Random Fourier features

One-class support vector machine (OC-SVM) for a long time has been one of the most effective anomaly detection methods and extensively adopted in both research as well as industrial applications. The biggest issue for OC-SVM is yet the capability to operate with large and high-dimensional datasets due to optimization complexity. Those problems might be mitigated via dimensionality reduction techniques such as manifold learning or autoencoder. However, previous work often treats representation learning and anomaly prediction separately. In this paper, we propose autoencoder based one-class support vector machine (AE-1SVM) that brings OC-SVM, with the aid of random Fourier features to approximate the radial basis kernel, into deep learning context by combining it with a representation learning architecture and jointly exploit stochastic gradient descent to obtain end-to-end training. Interestingly, this also opens up the possible use of gradient-based attribution methods to explain the decision making for anomaly detection, which has ever been challenging as a result of the implicit mappings between the input space and the kernel space. To the best of our knowledge, this is the first work to study the interpretability of deep learning in anomaly detection. We evaluate our method on a wide range of unsupervised anomaly detection tasks in which our end-to-end training architecture achieves a performance significantly better than the previous work using separate training.Comment: Accepted at European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD) 201

Quantitative description and local structures of trivalent metal ions Eu(III) and Cm(III) complexed with polyacrylic acid

The trivalent metal ion (M(III) = Cm, Eu)/polyacrylic acid (PAA) system was studied in the pH range between 3 and 5.5 for a molar PAA-to-metal ratio above 1. The interaction was studied for a wide range of PAA (0.05 mg L−1–50 g L−1) and metal ion concentrations (2×10−9–10−3 M). This work aimed at 3 goals (i) to determine the stoichiometry of M(III)–PAA complexes, (ii) to determine the number of complexed species and the local environment of the metal ion, and (iii) to quantify the reaction processes. Asymmetric flow-field-flow fractionation (AsFlFFF) coupled to ICP-MS evidenced that size distributions of Eu–PAA complexes and PAA were identical, suggesting that Eu bound to only one PAA chain. Time-resolved laser fluorescence spectroscopy (TRLFS) measurements performed with Eu and Cm showed a continuous shift of the spectra with increasing pH. The environment of complexed metal ions obviously changes with pH. Most probably, spectral variations arose from conformational changes within the M(III)–PAA complex due to pH variation. Complexation data describing the distribution of complexed and free metal ion were measured with Cm by TRLFS. They could be quantitatively described in the whole pH-range studied by considering the existence of only a single complexed species. This indicates that the slight changes in M(III) speciation with pH observed at the molecular level do not significantly affect the intrinsic binding constant. The interaction constant obtained from the modelling must be considered as a mean interaction constant

Achieving Generalizable Robustness of Deep Neural Networks by Stability Training

We study the recently introduced stability training as a general-purpose method to increase the robustness of deep neural networks against input perturbations. In particular, we explore its use as an alternative to data augmentation and validate its performance against a number of distortion types and transformations including adversarial examples. In our image classification experiments using ImageNet data stability training performs on a par or even outperforms data augmentation for specific transformations, while consistently offering improved robustness against a broader range of distortion strengths and types unseen during training, a considerably smaller hyperparameter dependence and less potentially negative side effects compared to data augmentation.Comment: 18 pages, 25 figures; Camera-ready versio

DTPA complexation of bismuth in human blood serum

The in vivo 212Pb / 212Bi generator is promising for application in targeted alpha therapy (TAT) of cancer. One main limitation of its therapeutic application is due to potential release of 212Bi from the radioconjugate upon radioactive decay of the mother nuclide 212Pb, potentially leading to irradiation of healthy tissue. The objective of the present work is to assess whether the chelate CHX-A''-DTPA (N-(2-Aminoethyl)-trans-1,2-diaminocyclohexane-N,N',N''-pentaacetic Acid) bound to a biological carrier molecule may be able to re-complex released 212Bi under in vivo conditions to limit its translocation from the target site. CHX-A''-DTPA was bound to bovine gamma globulin (BGG) to mimic a model conjugate and the stability of the Bi-CHX-A''-DTPA-BGG conjugate was studied in blood serum by ultrafiltration. TRLFS experiments using Cm(III) as fluorescent probe demonstrated that linking CHX-A''-DTPA to an BGG does not affect the coordination properties of the ligand. Furthermore, comparable stability constants were observed between Bi(III) and free CHX-A''-DTPA, BGG-bound CHX-A''-DTPA and DTPA. The complexation constants determined between Bi(III) and the chelate molecules are sufficiently high to allow ultra trace amounts of the ligand to efficiently compete with serum transferrin controlling Bi(III) speciation in blood plasma conditions. Nevertheless, CHX-A''-DTPA is not able to complex Bi(III) generated in blood serum because of the strong competition between Bi(III) and Fe(II) for the ligand. In other words, CHX-A''-DTPA is not selective enough to limit Bi(III) release in the body when applying the 212Pb / 212Bi in vivo generator.JRC.E.5-Nuclear chemistr

Mix 'n Match: Integrating Text Matching and Product Substitutability within Product Search

Two products are substitutes if both can satisfy the same consumer need. Intrinsic incorporation of product substitutability - where substitutability is integrated within latent vector space models - is in contrast to the extrinsic re-ranking of result lists. The fusion of text matching and product substitutability objectives allows latent vector space models to mix and match regularities contained within text descriptions and substitution relations. We introduce a method for intrinsically incorporating product substitutability within latent vector space models for product search that are estimated using gradient descent; it integrates flawlessly with state-of-the-art vector space models. We compare our method to existing methods for incorporating structural entity relations, where product substitutability is incorporated extrinsically by re-ranking. Our method outperforms the best extrinsic method on four benchmarks. We investigate the effect of different levels of text matching and product similarity objectives, and provide an analysis of the effect of incorporating product substitutability on product search ranking diversity. Incorporating product substitutability information improves search relevance at the cost of diversity