Food Price Volatility over the Last Decade in Niger and Malawi: Extent, Sources and Impact on Child Malnutrition

Recently, considerable attention has rightly been paid to the nutritional impact of the sharp hikes in international food prices which took place in 2007-8 and, again, in 2010-11. While sacrosanct, this growing focus has somewhat obscured the effect of other factors which do affect malnutrition in the Sub-Saharan Africa context, i.e. the long term impact of agricultural policies, huge and persistent seasonal variation in domestic food prices, and the impact of famines which still regularly stalk the continent. This paper focuses on the relative weight of these factors in explaining child malnutrition (proxied by the number of child admissions to feeding centers) in Malawi and Niger, two prototypical countries in the region. The analysis shows that the drivers of domestic food staple prices and of the ensuing child malnutrition have to be found not only – or not primarily – in the changes of international food prices but mainly in the impact of agricultural policies on food production, the persistence of a strong food price seasonality, and recurrent and often poorly attended famines. Indeed, even during years of declines in international food prices, these factors often exert a huge upward pressures on domestic food prices and child malnutrition

Predicting human eye fixations via an LSTM-Based saliency attentive model

Data-driven saliency has recently gained a lot of attention thanks to the use of convolutional neural networks for predicting gaze fixations. In this paper, we go beyond standard approaches to saliency prediction, in which gaze maps are computed with a feed-forward network, and present a novel model which can predict accurate saliency maps by incorporating neural attentive mechanisms. The core of our solution is a convolutional long short-term memory that focuses on the most salient regions of the input image to iteratively refine the predicted saliency map. In addition, to tackle the center bias typical of human eye fixations, our model can learn a set of prior maps generated with Gaussian functions. We show, through an extensive evaluation, that the proposed architecture outperforms the current state-of-the-art on public saliency prediction datasets. We further study the contribution of each key component to demonstrate their robustness on different scenarios

Direct exoplanet detection and characterization using the ANDROMEDA method: Performance on VLT/NaCo data

Context. The direct detection of exoplanets with high-contrast imaging requires advanced data processing methods to disentangle potential planetary signals from bright quasi-static speckles. Among them, angular differential imaging (ADI) permits potential planetary signals with a known rotation rate to be separated from instrumental speckles that are either statics or slowly variable. The method presented in this paper, called ANDROMEDA for ANgular Differential OptiMal Exoplanet Detection Algorithm is based on a maximum likelihood approach to ADI and is used to estimate the position and the flux of any point source present in the field of view. Aims. In order to optimize and experimentally validate this previously proposed method, we applied ANDROMEDA to real VLT/NaCo data. In addition to its pure detection capability, we investigated the possibility of defining simple and efficient criteria for automatic point source extraction able to support the processing of large surveys. Methods. To assess the performance of the method, we applied ANDROMEDA on VLT/NaCo data of TYC-8979-1683-1 which is surrounded by numerous bright stars and on which we added synthetic planets of known position and flux in the field. In order to accommodate the real data properties, it was necessary to develop additional pre-processing and post-processing steps to the initially proposed algorithm. We then investigated its skill in the challenging case of a well-known target, $\beta$ Pictoris, whose companion is close to the detection limit and we compared our results to those obtained by another method based on principal component analysis (PCA). Results. Application on VLT/NaCo data demonstrates the ability of ANDROMEDA to automatically detect and characterize point sources present in the image field. We end up with a robust method bringing consistent results with a sensitivity similar to the recently published algorithms, with only two parameters to be fine tuned. Moreover, the companion flux estimates are not biased by the algorithm parameters and do not require a posteriori corrections. Conclusions. ANDROMEDA is an attractive alternative to current standard image processing methods that can be readily applied to on-sky data

Computer Vision in Human Analysis: From Face and Body to Clothes

For decades, researchers of different areas, ranging from artificial intelligence to computer vision, have intensively investigated human-centered data, i.e., data in which the human plays a significant role, acquired through a non-invasive approach, such as cameras. This interest has been largely supported by the highly informative nature of this kind of data, which provides a variety of information with which it is possible to understand many aspects including, for instance, the human body or the outward appearance. Some of the main tasks related to human analysis are focused on the body (e.g., human pose estimation and anthropocentric measurement estimation), the hands (e.g., gesture detection and recognition), the head (e.g., head pose estimation), or the face (e.g., emotion and expression recognition). Additional tasks are based on non-corporal elements, such as motion (e.g., action recognition and human behavior understanding) and clothes (e.g., garment-based virtual try-on and attribute recognition). Unfortunately, privacy issues severely limit the usage and the diffusion of this kind of data, making the exploitation of learning approaches challenging. In particular, privacy issues behind the acquisition and the use of human-centered data must be addressed by public and private institutions and companies. Thirteen high-quality papers have been published in this Special Issue and are summarized in the following: four of them are focused on the human face (facial geometry, facial landmark detection, and emotion recognition), two on eye image analysis (eye status classification and 3D gaze estimation), five on the body (pose estimation, conversational gesture analysis, and action recognition), and two on the outward appearance (transferring clothing styles and fashion-oriented image captioning). These numbers confirm the high interest in human-centered data and, in particular, the variety of real-world applications that it is possible to develop

Tunneling Splittings in Mn12-Acetate Single Crystals

A Landau-Zener multi-crossing method has been used to investigate the tunnel splittings in high quality Mn$_{12}$-acetate single crystals in the pure quantum relaxation regime and for fields applied parallel to the magnetic easy axis. With this method several individual tunneling resonances have been studied over a broad range of time scales. The relaxation is found to be non-exponential and a distribution of tunnel splittings is inferred from the data. The distributions suggest that the inhomogeneity in the tunneling rates is due to disorder that produces a non-zero mean value of the average transverse anisotropy, such as in a solvent disorder model. Further, the effect of intermolecular dipolar interaction on the magnetic relaxation has been studied.Comment: Europhysics Letters (in press). 7 pages, including 3 figure

Field-induced level crossings in spin clusters: Thermodynamics and magneto-elastic instability

Quantum spin clusters with dominant antiferromagnetic Heisenberg exchange interactions typically exhibit a sequence of field-induced level crossings in the ground state as function of magnetic field. For fields near a level crossing, the cluster can be approximated by a two-level Hamiltonian at low temperatures. Perturbations, such as magnetic anisotropy or spin-phonon coupling, sensitively affect the behavior at the level-crossing points. The general two-level Hamiltonian of the spin system is derived in first-order perturbation theory, and the thermodynamic functions magnetization, magnetic torque, and magnetic specific heat are calculated. Then a magneto-elastic coupling is introduced and the effective two-level Hamilitonian for the spin-lattice system derived in the adiabatic approximation of the phonons. At the level crossings the system becomes unconditionally unstable against lattice distortions due to the effects of magnetic anisotropy. The resultant magneto-elastic instabilities at the level crossings are discussed, as well as the magnetic behavior.Comment: 13 pages, 8 figures, REVTEX

Spin dynamics in molecular ring nanomagnets: Significant effect of acoustic phonons and magnetic anisotropies

The nuclear spin-lattice relaxation rate 1/T_1_ is calculated for magnetic ring clusters by fully diagonalizing their microscopic spin Hamiltonians. Whether the nearest-neighbor exchange interaction J is ferromagnetic or antiferromagnetic, 1/T_1_ versus temperature T in ring nanomagnets may be peaked at around k_B_T=|J| provided the lifetime broadening of discrete energy levels is in proportion to T^3^. Experimental findings for ferromagnetic and antiferromagnetic Cu^II^ rings are reproduced with crucial contributions of magnetic anisotropies as well as acoustic phonons.Comment: 5 pages with 5 figures embedded, to be published in J. Phys. Soc. Jpn. 75, No. 10 (2006

Electric Field Controlled Magnetic Anisotropy in a Single Molecule

We have measured quantum transport through an individual Fe$_4$ single-molecule magnet embedded in a three-terminal device geometry. The characteristic zero-field splittings of adjacent charge states and their magnetic field evolution are observed in inelastic tunneling spectroscopy. We demonstrate that the molecule retains its magnetic properties, and moreover, that the magnetic anisotropy is significantly enhanced by reversible electron addition / subtraction controlled with the gate voltage. Single-molecule magnetism can thus be electrically controlled

Observation of a Distribution of Internal Transverse Magnetic Fields in a Mn12-Based Single Molecule Magnet

A distribution of internal transverse magnetic fields has been observed in single molecule magnet (SMM) Mn12-BrAc in the pure magnetic quantum tunneling (MQT) regime. Magnetic relaxation experiments at 0.4 K are used to produce a hole in the distribution of transverse fields whose angle and depth depend on the orientation and amplitude of an applied transverse ``digging field.'' The presence of such transverse magnetic fields can explain the main features of resonant MQT in this material, including the tunneling rates, the form of the relaxation and the absence of tunneling selection rules. We propose a model in which the transverse fields originate from a distribution of tilts of the molecular magnetic easy axes.Comment: 4 page