Bridging languages through images with deep partial canonical correlation analysis

We present a deep neural network that leverages images to improve bilingual text embeddings. Relying on bilingual image tags and descriptions, our approach conditions text embedding induction on the shared visual information for both languages, producing highly correlated bilingual embeddings. In particular, we propose a novel model based on Partial Canonical Correlation Analysis (PCCA). While the original PCCA finds linear projections of two views in order to maximize their canonical correlation conditioned on a shared third variable, we introduce a non-linear Deep PCCA (DPCCA) model, and develop a new stochastic iterative algorithm for its optimization. We evaluate PCCA and DPCCA on multilingual word similarity and cross-lingual image description retrieval. Our models outperform a large variety of previous methods, despite not having access to any visual signal during test time inference. Our code and data are available at: https://github.com/rotmanguy/DPCCA

Exactness of the Original Grover Search Algorithm

It is well-known that when searching one out of four, the original Grover's search algorithm is exact; that is, it succeeds with certainty. It is natural to ask the inverse question: If we are not searching one out of four, is Grover's algorithm definitely not exact? In this article we give a complete answer to this question through some rationality results of trigonometric functions.Comment: 8 pages, 2 figure

Idiopathic desquamative interstitial pneumonia in a child: a case report.

Desquamative interstitial pneumonia is a rare form of interstitial lung disease in children. Respiratory symptoms appear progressively, are often subtle, and diagnosis is often delayed by a mean of 6 months after onset. High resolution chest computed tomography is the most sensitive imaging technique for demonstrating and identifying interstitial pneumonia. The typical histologic pattern of desquamative interstitial pneumonia, with prominent clustered alveolar macrophages, diffuse reactive alveolar epithelial hyperplasia and globular proteinaceous material, is diagnostic. Desquamative interstitial pneumonia in children can be idiopathic, though it is mostly related to an inborn error of surfactant metabolism. We present the complex clinical course and pathologic findings of a 30-months-old Mauritian and Senegalese girl with idiopathic desquamative interstitial pneumonia and multiple extrapulmonary manifestations. To our knowledge, this is the first case report of desquamative interstitial pneumonia to occur as part of a syndrome with multiple organ involvement. We believe that desquamative interstitial pneumonia is not always associated with mutations of the surfactant proteins, and can still be idiopathic, especially when occurring as part of a syndrome with multiple organ involvement, as described in other interstitial lung diseases

An open source Python library for environmental isotopic modelling

Altres ajuts: from the Balearic Island Government through the Margalida Comas postdoctoral fellowship programme (PD/036/2020).Isotopic composition modelling is a key aspect in many environmental studies. This work presents Isocompy, an open source Python library that estimates isotopic compositions through machine learning algorithms with user-defined variables. Isocompy includes dataset preprocessing, outlier detection, statistical analysis, feature selection, model validation and calibration and postprocessing. This tool has the flexibility to operate with discontinuous inputs in time and space. The automatic decision-making procedures are knitted in different stages of the algorithm, although it is possible to manually complete each step. The extensive output reports, figures and maps generated by Isocompy facilitate the comprehension of stable water isotope studies. The functionality of Isocompy is demonstrated with an application example involving the meteorological features and isotopic composition of precipitation in N Chile, which are compared with the results produced in previous studies. In essence, Isocompy offers an open source foundation for isotopic studies that ensures reproducible research in environmental fields

UTILIZING SAR AND MULTISPECTRAL INTEGRATED DATA FOR EMERGENCY RESPONSE

Satellite images are used widely in the risk cycle to understand the exposure, refine hazard maps and quickly provide an assessment after a natural or man-made disaster. Though there are different types of satellite images (e.g. optical, radar) these have not been combined for risk assessments. The characteristics of different remote sensing data type may be extremely valuable for monitoring and evaluating the impacts of disaster events, to extract additional information thus making it available for emergency situations. To base this approach, two different change detection methods, for two different sensor's data were used: Coherence Change Detection (CCD) for SAR data and Covariance Equalization (CE) for multispectral imagery. The CCD provides an identification of the stability of an area, and shows where changes have occurred. CCD shows subtle changes with an accuracy of several millimetres to centimetres. The CE method overcomes the atmospheric effects differences between two multispectral images, taken at different times. Therefore, areas that had undergone a major change can be detected. To achieve our goals, we focused on the urban areas affected by the tsunami event in Sendai, Japan that occurred on March 11, 2011 which affected the surrounding area, coastline and inland. High resolution TerraSAR-X (TSX) and Landsat 7 images, covering the research area, were acquired for the period before and after the event. All pre-processed and processed according to each sensor. Both results, of the optical and SAR algorithms, were combined by resampling the spatial resolution of the Multispectral data to the SAR resolution. This was applied by spatial linear interpolation. A score representing the damage level in both products was assigned. The results of both algorithms, high level of damage is shown in the areas closer to the sea and shoreline. Our approach, combining SAR and multispectral images, leads to more reliable information and provides a complete scene for the emergency response following an event

Renal Fanconi Syndrome and Hypophosphatemic Rickets in the Absence of Xenotropic and Polytropic Retroviral Receptor in the Nephron.

Tight control of extracellular and intracellular inorganic phosphate (Pi) levels is critical to most biochemical and physiologic processes. Urinary Pi is freely filtered at the kidney glomerulus and is reabsorbed in the renal tubule by the action of the apical sodium-dependent phosphate transporters, NaPi-IIa/NaPi-IIc/Pit2. However, the molecular identity of the protein(s) participating in the basolateral Pi efflux remains unknown. Evidence has suggested that xenotropic and polytropic retroviral receptor 1 (XPR1) might be involved in this process. Here, we show that conditional inactivation of Xpr1 in the renal tubule in mice resulted in impaired renal Pi reabsorption. Analysis of Pi transport in primary cultures of proximal tubular cells or in freshly isolated renal tubules revealed that this Xpr1 deficiency significantly affected Pi efflux. Further, mice with conditional inactivation of Xpr1 in the renal tubule exhibited generalized proximal tubular dysfunction indicative of Fanconi syndrome, characterized by glycosuria, aminoaciduria, calciuria, and albuminuria. Dramatic alterations in the renal transcriptome, including a significant reduction in NaPi-IIa/NaPi-IIc expression, accompanied these functional changes. Additionally, Xpr1-deficient mice developed hypophosphatemic rickets secondary to renal dysfunction. These results identify XPR1 as a major regulator of Pi homeostasis and as a potential therapeutic target in bone and kidney disorders