The Landscape of the Spiked Tensor Model

We consider the problem of estimating a large rank-one tensor u ^⊗k ∈ (ℝⁿ)^⊗k , k ≥ 3 , in Gaussian noise. Earlier work characterized a critical signal-to-noise ratio λ  _Bayes = O(1) above which an ideal estimator achieves strictly positive correlation with the unknown vector of interest. Remarkably, no polynomial-time algorithm is known that achieved this goal unless λ ≥ Cn^{(k − 2)/4} , and even powerful semidefinite programming relaxations appear to fail for 1 ≪ λ ≪ n^{(k − 2)/4} . In order to elucidate this behavior, we consider the maximum likelihood estimator, which requires maximizing a degree-k homogeneous polynomial over the unit sphere in n dimensions. We compute the expected number of critical points and local maxima of this objective function and show that it is exponential in the dimensions n , and give exact formulas for the exponential growth rate. We show that (for λ larger than a constant) critical points are either very close to the unknown vector u or are confined in a band of width Θ(λ^{−1/(k − 1)}) around the maximum circle that is orthogonal to u . For local maxima, this band shrinks to be of size Θ(λ^{−1/(k − 2)}) . These “uninformative” local maxima are likely to cause the failure of optimization algorithms. © 2019 Wiley Periodicals, Inc.     

Enhancing the Water Stability of Al‐MIL‐101‐NH2 via Postsynthetic Modification

The resistance of metal–organic frameworks towards water is a very critical issue concerning their practical use. Recently, it was shown for microporous MOFs that the water stability could be increased by introducing hydrophobic pendant groups. Here, we demonstrate a remarkable stabilisation of the mesoporous MOF Al‐MIL‐101‐NH₂ by postsynthetic modification with phenyl isocyanate. In this process 86 % of the amino groups were converted into phenylurea units. As a consequence, the long‐term stability of Al‐MIL‐101‐URPh in liquid water could be extended beyond a week. In water saturated atmospheres Al‐MIL‐101‐URPh decomposed at least 12‐times slower than the unfunctionalised analogue. To study the underlying processes both materials were characterised by Ar, N₂ and H₂O sorption measurements, powder X‐ray diffraction, thermogravimetric and chemical analysis as well as solid‐state NMR and IR spectroscopy. Postsynthetic modification decreased the BET equivalent surface area from 3363 to 1555 m² g^?1 for Al‐MIL‐101‐URPh and reduced the mean diameters of the mesopores by 0.6 nm without degrading the structure significantly and reducing thermal stability. In spite of similar water uptake capacities, the relative humidity‐dependent uptake of Al‐MIL‐101‐URPh is slowed and occurs at higher relative humidity values. In combination with ¹H‐²⁷Al D ‐HMQC NMR spectroscopy experiments this favours a shielding mechanism of the Al clusters by the pendant phenyl groups and rules out pore blocking.     

Thermodynamic study of transthyretin association (wild‐type and senile forms) with heparan sulfate proteoglycan: pH effect and implication of the reactive histidine residue

The tetramer destabilization of transthyretin into monomers and its fibrillation are phenomena leading to amyloid deposition. Heparan sulfate proteoglycan (HSPG) has been found in all amyloid deposits. A chromatographic approach was developed to compare binding parameters between wild‐type transthyretin (wtTTR) and an amyloidogenic transthyretin (sTTR). Results showed a greater affinity of sTTR for HSPG at pH 7.4 compared with wtTTR owing to the monomeric form of sTTR. Analysis of the thermodynamic parameters showed that van der Waals interactions were involved at the complex interface for both transthyretin forms. For sTTR, results from the plot representing the number of protons exchanged vs pH showed that the binding mechanism was pH‐dependent with a critical value at a pH 6.5. This observation was due to the protonation of a histidine residue as an imidazolium cation, which was not accessible when TTR was in its tetrameric structure. At pH >6.5, dehydration at the binding interface and several contacts between nonpolar groups of sTTR and HSPG were also coupled to binding for an optimal hydrogen‐bond network. At pH <6.5, the protonation of the His residue from sTTR monomer when pH decreased broke the hydrogen‐bond network, leading to its destabilization and thus producing slight conformational changes in the sTTR monomer structure. Copyright © 2014 John Wiley & Sons, Ltd.     

Vehicle detection by means of stereo vision-based obstacles features extraction and monocular pattern analysis.

This paper presents a stereo vision system for the detection and distance computation of a preceding vehicle. It is divided in two major steps. Initially, a stereo vision-based algorithm is used to extract relevant three-dimensional (3-D) features in the scene, these features are investigated further in order to select the ones that belong to vertical objects only and not to the road or background. These 3-D vertical features are then used as a starting point for preceding vehicle detection; by using a symmetry operator, a match against a simplified model of a rear vehicle's shape is performed using a monocular vision-based approach that allows the identification of a preceding vehicle. In addition, using the 3-D information previously extracted, an accurate distance computation is performed.     

Velocity selective filters recursively implemented in the spatiotemporal domain.

Energy-based methods for motion estimation in image sequences process the input data either in the spatiotemporal or in the frequency domain. In both cases, the algorithms already described in the literature often require a huge number of elementary operations. In this paper, we describe a class of velocity selective filters which yield an accurate detection of the edges moving in the sequence. We first present a filtering scheme based on a convolution operation computed on a finite size neighborhood and describe its properties in the spatiotemporal and frequency domains. Then, we show that filters with similar properties can be implemented recursively, i.e., as convolutions computed on infinite-size neighborhoods. As an example, we finally show the filters' responses in the case of two superimposed translational motions.     

L’optimisation des réseaux cellulaires assistée par ordinateur: le logiciel RNO (Radio Network Optimisation)

Quality of service has become today a major concern for operators of mobile communication networks. The massive development of networks and strong competition between operators has lead to the necessary and daily follow-up of network quality of service, a key factor for its subscriber’s fidelity. This article aims at presenting the optimization methodology and proposes its illustration with a case of RNO (Radio Network Optimisation) software usage, one of the Alcatel optimization toolchain component. After a short presentation of cellular network, the optimization basic principles are described. RNO software and its main functionnalities are then detailed before a last part dedicated to a real case of optimization done with RNO software.