Variational approximation for mixtures of linear mixed models

Mixtures of linear mixed models (MLMMs) are useful for clustering grouped data and can be estimated by likelihood maximization through the EM algorithm. The conventional approach to determining a suitable number of components is to compare different mixture models using penalized log-likelihood criteria such as BIC.We propose fitting MLMMs with variational methods which can perform parameter estimation and model selection simultaneously. A variational approximation is described where the variational lower bound and parameter updates are in closed form, allowing fast evaluation. A new variational greedy algorithm is developed for model selection and learning of the mixture components. This approach allows an automatic initialization of the algorithm and returns a plausible number of mixture components automatically. In cases of weak identifiability of certain model parameters, we use hierarchical centering to reparametrize the model and show empirically that there is a gain in efficiency by variational algorithms similar to that in MCMC algorithms. Related to this, we prove that the approximate rate of convergence of variational algorithms by Gaussian approximation is equal to that of the corresponding Gibbs sampler which suggests that reparametrizations can lead to improved convergence in variational algorithms as well.Comment: 36 pages, 5 figures, 2 tables, submitted to JCG

Semiclassical Analysis of Extended Dynamical Mean Field Equations

The extended Dynamical Mean Field Equations (EDMFT) are analyzed using semiclassical methods for a model describing an interacting fermi-bose system. We compare the semiclassical approach with the exact QMC (Quantum Montecarlo) method. We found the transition to an ordered state to be of the first order for any dimension below four.Comment: RevTex, 39 pages, 16 figures; Appendix C added, typos correcte

A finite element analysis study from 3D CT to predict transcatheter heart valve thrombosis

Background: Transcatheter aortic valve replacement has proved its safety and effectiveness in intermediate- to high-risk and inoperable patients with severe aortic stenosis. However, despite current guideline recommendations, the use of transcatheter aortic valve replacement (TAVR) to treat severe aortic valve stenosis caused by degenerative leaflet thickening and calcification has not been widely adopted in low-risk patients. This reluctance among both cardiac surgeons and cardiologists could be due to concerns regarding clinical and subclinical valve thrombosis. Stent performance alongside increased aortic root and leaflet stresses in surgical bioprostheses has been correlated with complications such as thrombosis, migration and structural valve degeneration. Materials and Methods: Self-expandable catheter-based aortic valve replacement (Medtronic, Minneapolis, MN, USA), which was received by patients who developed transcatheter heart valve thrombosis, was investigated using high-resolution biomodelling from computed tomography scanning. Calcific blocks were extracted from a 250 CT multi-slice image for precise three-dimensional geometry image reconstruction of the root and leaflets. Results: Distortion of the stent was observed with incomplete cranial and caudal expansion of the device. The incomplete deployment of the stent was evident in the presence of uncrushed refractory bulky calcifications. This resulted in incomplete alignment of the device within the aortic root and potential dislodgment. Conclusion: A Finite Element Analysis (FEA) investigation can anticipate the presence of calcified refractory blocks, the deformation of the prosthetic stent and the development of paravalvular orifice, and it may prevent subclinical and clinical TAVR thrombosis. Here we clearly demonstrate that using exact geometry from high-resolution CT scans in association with FEA allows detection of persistent bulky calcifications that may contribute to thrombus formation after TAVR procedure

Structured Multi-Hashing for Model Compression

Despite the success of deep neural networks (DNNs), state-of-the-art models are too large to deploy on low-resource devices or common server configurations in which multiple models are held in memory. Model compression methods address this limitation by reducing the memory footprint, latency, or energy consumption of a model with minimal impact on accuracy. We focus on the task of reducing the number of learnable variables in the model. In this work we combine ideas from weight hashing and dimensionality reductions resulting in a simple and powerful structured multi-hashing method based on matrix products that allows direct control of model size of any deep network and is trained end-to-end. We demonstrate the strength of our approach by compressing models from the ResNet, EfficientNet, and MobileNet architecture families. Our method allows us to drastically decrease the number of variables while maintaining high accuracy. For instance, by applying our approach to EfficentNet-B4 (16M parameters) we reduce it to to the size of B0 (5M parameters), while gaining over 3% in accuracy over B0 baseline. On the commonly used benchmark CIFAR10 we reduce the ResNet32 model by 75% with no loss in quality, and are able to do a 10x compression while still achieving above 90% accuracy.Comment: Elad and Yair contributed equally to the paper. They jointly proposed the idea of structured-multi-hashing. Elad: Wrote most of the code and ran most of the experiments Yair: Main contributor to the manuscript Hao: Coding and experiments Yerlan: Coding and experiments Miguel: advised Yerlan about optimization and model compression Mark:experiments Andrew: experiment

Universal Parametric Correlations of Conductance Peaks in Quantum Dots

We compute the parametric correlation function of the conductance peaks in chaotic and weakly disordered quantum dots in the Coulomb blockade regime and demonstrate its universality upon an appropriate scaling of the parameter. For a symmetric dot we show that this correlation function is affected by breaking time-reversal symmetry but is independent of the details of the channels in the external leads. We derive a new scaling which depends on the eigenfunctions alone and can be extracted directly from the conductance peak heights. Our results are in excellent agreement with model simulations of a disordered quantum dot.Comment: 12 pages, RevTex, 2 Postscript figure

Gastrocnemius medialis contractile behavior during running differs between simulated Lunar and Martian gravities

The international partnership of space agencies has agreed to proceed forward to the Moon sustainably. Activities on the Lunar surface (0.16 g) will allow crewmembers to advance the exploration skills needed when expanding human presence to Mars (0.38 g). Whilst data from actual hypogravity activities are limited to the Apollo missions, simulation studies have indicated that ground reaction forces, mechanical work, muscle activation, and joint angles decrease with declining gravity level. However, these alterations in locomotion biomechanics do not necessarily scale to the gravity level, the reduction in gastrocnemius medialis activation even appears to level off around 0.2 g, while muscle activation pattern remains similar. Thus, it is difficult to predict whether gastrocnemius medialis contractile behavior during running on Moon will basically be the same as on Mars. Therefore, this study investigated lower limb joint kinematics and gastrocnemius medialis behavior during running at 1 g, simulated Martian gravity, and simulated Lunar gravity on the vertical treadmill facility. The results indicate that hypogravity-induced alterations in joint kinematics and contractile behavior still persist between simulated running on the Moon and Mars. This contrasts with the concept of a ceiling effect and should be carefully considered when evaluating exercise prescriptions and the transferability of locomotion practiced in Lunar gravity to Martian gravity

Controlled-source electromagnetic and seismic delineation of sub-seafloor fluid flow structures in a gas hydrate province, offshore Norway

Deep sea pockmarks underlain by chimney-like or pipe structures that contain methane hydrate are abundant along the Norwegian continental margin. In such hydrate provinces the interaction between hydrate formation and fluid flow has significance for benthic ecosystems and possibly climate change. The Nyegga region, situated on the western Norwegian continental slope, is characterized by an extensive pockmark field known to accommodate substantial methane gas hydrate deposits. The aim of this study is to detect and delineate both the gas hydrate and free gas reservoirs at one of Nyegga's pockmarks. In 2012, a marine controlled-source electromagnetic (CSEM) survey was performed at a pockmark in this region, where high-resolution three-dimensional seismic data were previously collected in 2006. Two-dimensional CSEM inversions were computed using the data acquired by ocean bottom electrical field receivers. Our results, derived from unconstrained and seismically constrained CSEM inversions, suggest the presence of two distinctive resistivity anomalies beneath the pockmark: a shallow vertical anomaly at the underlying pipe structure, likely due to gas hydrate accumulation, and a laterally extensive anomaly attributed to a free gas zone below the base of the gas hydrate stability zone. This work contributes to a robust characterization of gas hydrate deposits within sub-seafloor fluid flow pipe structures

Corevalve vs. Sapien 3 transcatheter aortic valve replacement: A finite element analysis study

Aim: to investigate the factors implied in the development of postoperative complications in both self-expandable and balloon-expandable transcatheter heart valves by means of finite element analysis (FEA). Materials and methods: FEA was integrated into CT scans to investigate two cases of postoperative device failure for valve thrombosis after the successful implantation of a CoreValve and a Sapien 3 valve. Data were then compared with two patients who had undergone uncomplicated transcatheter heart valve replacement (TAVR) with the same types of valves. Results: Computational biomechanical modeling showed calcifications persisting after device expansion, not visible on the CT scan. These calcifications determined geometrical distortion and elliptical deformation of the valve predisposing to hemodynamic disturbances and potential thrombosis. Increased regional stress was also identified in correspondence to the areas of distortion with the associated paravalvular leak. Conclusion: the use of FEA as an adjunct to preoperative imaging might assist patient selection and procedure planning as well as help in the detection and prevention of TAVR complications

Contractile behavior of the gastrocnemius medialis muscle during running in simulated hypogravity

Vigorous exercise countermeasures in microgravity can largely attenuate muscular degeneration, albeit the extent of applied loading is key for the extent of muscle wasting. Running on the International Space Station is usually performed with maximum loads of 70% body weight (0.7 g). However, it has not been investigated how the reduced musculoskeletal loading affects muscle and series elastic element dynamics, and thereby force and power generation. Therefore, this study examined the effects of running on the vertical treadmill facility, a ground-based analog, at simulated 0.7 g on gastrocnemius medialis contractile behavior. The results reveal that fascicle−series elastic element behavior differs between simulated hypogravity and 1 g running. Whilst shorter peak series elastic element lengths at simulated 0.7 g appear to be the result of lower muscular and gravitational forces acting on it, increased fascicle lengths and decreased velocities could not be anticipated, but may inform the development of optimized running training in hypogravity. However, whether the alterations in contractile behavior precipitate musculoskeletal degeneration warrants further study