This work presents a methodology for the short-term forecast of intense rainfall based on a neural network and the integration of Global Navigation and Positioning System (GNSS) and meteorological data. Precipitable water vapor (PWV) derived from GNSS is combined with surface pressure, surface temperature and relative humidity obtained continuously from a ground-based meteorological station. Five years of GNSS data from one station in Lisbon, Portugal, are processed. Data for precipitation forecast are also collected from the meteorological station.

Motivated by the upcoming Internet of Things, designing light-weight authentication protocols for resource constrained devices is among the main research directions of the last decade. Current solutions in the literature attempt either to improve the computational efficiency of cryptographic authentication schemes, or to build a provably-secure scheme relying on the hardness of a specific mathematical problem.

Derivations of the Jarzynski equality (JE) appear to be quite general, and applicable to any particle system, whether deterministic or stochastic, under equally general perturbations of an initial equilibrium state at given temperatureT. At the same time, the definitions of the quantities appearing in the JE, in particular the work, have been questioned. Answers have been given, but a deeper understanding of the range of phenomena to which the JE applies is necessary, both conceptually and in order to interpret the experiments in which it is used.

We investigate the influence of the perturbed (by a solar X-ray flare) ionospheric D-region on the global navigation satellite systems (GNSS) and synthetic aperture radar (SAR) signals. We calculate a signal delay in the D-region based on the low ionospheric monitoring by very-low-frequency (VLF) radio waves. The results show that the ionospheric delay in the perturbed D-region can be important and, therefore, should be taken into account in modeling the ionospheric influence on the GNSS and SAR signal propagation and in calculations relevant for space geodesy.

A Round Robin exercise was implemented by ESA to compare different classification methods in detecting clouds from images taken by the PROBA-V sensor. A high-quality dataset of 1350 reflectances and Clear/Cloudy corresponding labels had been prepared by ESA in the framework of the exercise. Motivated by both the experience acquired by one of the authors in this exercise and the availability of such a reliable annotated dataset, we present a full assessment of the methodology proposed therein.

In Mobile Unattended Wireless Sensor Networks (MUWSNs), nodes sense the environment and store the acquired data until the arrival of a trusted data sink. MUWSNs, other than being a reference model for an increasing number of military and civilian applications, also capture a few important characteristics of emerging computing paradigms like Participatory Sensing (PS). In this paper, we start by identifying the main features and issues of MUWSNs, revising the related work in the area and highlighting their shortcomings.

ZBTB2 is a protein belonging to the BTB/POZ zinc-finger family whose members typically contain a BTB/POZ domain at the N-terminus and several zinc-finger domains at the C-terminus. Studies have been carried out to disclose the role of ZBTB2 in cell proliferation, in human cancers and in regulating DNA methylation. Moreover, ZBTB2 has been also described as an ARF, p53 and p21 gene repressor as well as an activator of genes modulating pluripotency. In this scenario, ZBTB2 seems to play many functions likely associated with other proteins.