This study describes a semi-empirical model developed to estimate volumetric soil moisture (<mml:semantics>theta v</mml:semantics>) in bare soils during the dry season (March-May) using C-band (5.42 GHz) synthetic aperture radar (SAR) imagery acquired from the Sentinel-1 European satellite platform at a 20 m spatial resolution. The semi-empirical model was developed using backscatter coefficient (<mml:semantics>sigma degrees dB</mml:semantics>) and in situ soil moisture collected from Siruguppa taluk (sub-district) in the Karnataka state of India.

In remote storage services, delays in the time to retrieve data can cause economic losses to the data owners. In this paper, we address the problem of properly establishing specific clauses in the service level agreement (SLA), intended to guarantee a short and predictable retrieval time. Based on the rationale that the retrieval time mainly depends on the storage media used at the server side, we introduce the concept of Provable Storage Medium (PSM), to denote the ability of a user to efficiently verify that the provider is complying to this aspect of the SLA.

Visibility has an encompassing importance in humans' perception of the landscape, since the first encounter with a new environment normally occurs through sight. In historical and archaeological studies, two main methods (i.e., the geometric method and the Geographical Information System [GIS] computation) have been employed to determine the distance from which an object can be recognized. However, neither is exhaustive when applied to a maritime context, where the main factor affecting the visibility radius is weather.

Operated by the H2020 SOMA Project, the recently established Social Observatory for Disinformation and Social Media Analysis supports researchers, journalists and fact-checkers in their quest for quality information. At the core of the Observatory lies the DisInfoNet Toolbox, designed to help a wide spectrum of users understand the dynamics of (fake) news dissemination in social networks. DisInfoNet combines text mining and classification with graph analysis and visualization to offer a comprehensive and user-friendly suite.

The paper concerns the weighted uniform approximation of a real function on the d-cube [-1, 1]^d, with d > 1, by means of some multivariate filtered polynomials. These polynomials have been deduced, via tensor product, from certain de la Vallée Poussin type means on [-1, 1], which generalize classical delayed arithmetic means of Fourier partial sums. They are based on arbitrary sequences of filter coefficients, not necessarily connected with a smooth filter function.

Systems medicine (SM) has emerged as a powerful tool for studying the human body at the systems level with the aim of improving our understanding, prevention and treatment of complex diseases. Being able to automatically extract relevant features needed for a given task from high-dimensional, heterogeneous data, deep learning (DL) holds great promise in this endeavour. This review paper addresses the main developments of DL algorithms and a set of general topics where DL is decisive, namely, within the SM landscape.

GPU version of AMG preconditioner

This work presents a methodology to monitor the dynamic behaviour of tall metallic towers based on ground-based radar interferometry, and apply it to the case of telecommunication towers. Ground-based radar displacement measurements of metallic towers are acquired without installing any Corner Reflector (CR) on the structure. Each structural element of the tower is identified based on its range distance with respect to the radar.

Recent years have witnessed a massive push towards reproducible research in neuroscience. Unfortunately, this endeavor is often challenged by the large diversity of tools used, project-specific custom code and the difficulty to track all user-defined parameters. NeuroPycon is an open-source multi-modal brain data analysis toolkit which provides Python-based template pipelines for advanced multi-processing of MEG, EEG, functional and anatomical MRI data, with a focus on connectivity and graph theoretical analyses.

Effective treatment of glioma and other central nervous system (CNS) diseases is hindered by the presence of the blood-brain barrier (BBB). A novel nano-delivery vehicle system composed of PLGA-lysoGM1/DOX micelles was developed to cross the BBB for CNS treatment. We have shown that doxorubicin (DOX) as a model drug encapsulated in PLGA-lysoGM1 micelles can achieve up to 3.8% loading efficiency and 61.6% encapsulation efficiency by the orthogonal test design.