On the detection of nearly optimal solutions in the context of single-objective space mission design problems

When making decisions, having multiple options available for a possible realization of the same project can be advantageous. One way to increase the number of interesting choices is to consider, in addition to the optimal solution x*, also nearly optimal or approximate solutions; these alternative solutions differ from x* and can be in different regions – in the design space – but fulfil certain proximity to its function value f(x*). The scope of this article is the efficient computation and discretization of the set E of e–approximate solutions for scalar optimization problems. To accomplish this task, two strategies to archive and update the data of the search procedure will be suggested and investigated. To make emphasis on data storage efficiency, a way to manage significant and insignificant parameters is also presented. Further on, differential evolution will be used together with the new archivers for the computation of E. Finally, the behaviour of the archiver, as well as the efficiency of the resulting search procedure, will be demonstrated on some academic functions as well as on three models related to space mission design

Improving the precision of sea level data from satellite altimetry with high-frequency and regional Sea State Bias corrections

The sea state bias (SSB) is a large source of uncertainty in the estimation of sea level from satellite altimetry. It is still unclear to what extent it depends on errors in parameter estimations (numerical source) or to the wave physics (physical source). By improving the application of this correction we compute 20-Hz sea level anomalies that are about 30% more precise (i.e. less noisy) than the current standards. The improvement is two-fold: _rst we prove that the SSB correction should be applied directly to the 20-Hz data (12 to 19% noise decrease); secondly, we show that by recomputing a regional SSB model (based on the 20-Hz estimations) even a simple parametric relation is su_cient to further improve the correction (further 15 to 19% noise decrease). We test our methodology using range, wave height and wind speed estimated with two retrackers applied to Jason-1 waveform data: the MLE4 retracked-data available in the Sensor Geophysical Data Records of the mission and the ALES retracked-data available in the OpenADB repository (https://openadb.dg_.tum.de/). The regional SSB models are computed parametrically by means of a crossover analysis in the Mediterranean Sea and North Sea. Correcting the high-rate data for the SSB reduces the correlation between retracked parameters. Regional variations in the proposed models might be due to di_erences in wave climate and remaining sea-state dependent residual errors. The variations in the empirical model with respect to the retracker used recall the need for a speci_c SSB correction for any retracker. This study, while providing a signi_cantly more precise solution to exploit high-rate sea level data, calls for a re-thinking of the SSB correction in both its physical and numerical component, gives robustness to previous theories and provides an immediate improvement for the application of satellite altimetry in the regions of study

Annual sea level variability of the coastal ocean: The Baltic Sea-North Sea transition zone

The annual cycle is a major contribution to the non-tidal variability in sea level. Its characteristics can vary substantially even at a regional scale, particularly in an area of high variability such as the coastal ocean. This study uses previously validated coastal altimetry solutions (from ALES dataset) and the reference ESA Sea Level Climate Change Initiative dataset to improve the understanding of the annual cycle during the Envisat years (2002-2010) in the North Sea - Baltic Sea transition area. This area of study is chosen because of the complex coastal morphology and the availability of in-situ measurements. To our knowledge, this is the first time that the improvements brought by coastal satellite altimetry to the description of the annual variability of the sea level have been evaluated and discussed. The findings are interpreted with the help of a local climatology and wind stress from a reanalysis model. The coastal amplitude of the annual cycle estimated from ALES altimetry data is in better agreement with estimations derived from in-situ data than the one from the reference dataset. Wind stress is found to be the main driver of annual cycle variability throughout the domain, while different steric contributions are responsible for the differences within and among the sub-basins. We conclude that the ALES coastal altimetry product is a reliable dataset to study the annual cycle of the sea level at a regional scale and the strategy described in this research can be applied to other areas of the coastal ocean where the coverage from the tide gauges is not sufficient

COST-EFFECTIVE USE OF MOLECULAR MARKERS IN THE PRACTICAL RESOLUTION OF COMMON HORTICULTURAL CHALLENGES

Genetic molecular markers (DNA markers) represent genetic differences between individual organisms or species placed directly into DNA sequence. They are widely used as powerful scientific instruments to accomplish different tasks, from genes mapping to forensic discrimination. The tremendous advance in DNA genotyping tools has lead to the development of impressive high- throughput technologies, such as Next Generation Sequencing platforms, that may revolutionize horticulture research and applications. However the cost of such technologies not always make them the most rationale approach, particularly when working on minor crop species or with large number of samples. The present work aims to the exploring a multi-purpose and cost-effective use of different kinds of molecular markers, for assisting fruit tree plants breeding and valorization. For this scope, three cases of study were presented, spanning from cultivar discrimination and phylogeny reconstruction to marker assisted selection (MAS) for Sharka resistance. D.NA markers such as SSR and AFLP, were successfully used to discriminate the \u2018common\u2019 Chinotto from \u2018Chinotto di Savona\u2019, an uninvestigated traditional Citrus species cultivated in Liguria (italy) that is gaining increasing interest for the production of high-quality niche food and beverages. New polymorphisms on candidate genes, that could explain some of observed differences between the two accessions, were suggested. SSR markers were used for the first time to the large-scale application of MAS on apricot (Prunus armeniaca) to boost the conventional breeding programmes. They were found new resistant breeding selections against the most important viral disease of stone fruits, Sharka, caused by Plum Pox Virus (PPV). Novel candidate accessions were also characterized for PPV-resistance, enriching and complementing the apricot germplasm available for breeding. Moreover the number of significant markers required for this task was reduced from seven to two, decreasing the overall cost, in terms of time and resources, usually required for the conventional breeding programmes. A further reduction of resources for the application of MAS in apricot was achieved developing new SNP markers linked to Sharka resistance, and able to be screened using fluorescence on Real Time PCR machine with or without High Resolution Melting (HRM) technology. The performed works demonstrate that the correct choice of molecular instruments together with the implementation of new techniques could easily led to cost-effective, time-saving, and reliable results even without the facility and resources reserved for main crops research and applications

EVALITA 2020: Overview of the 7th evaluation campaign of natural language processing and speech tools for Italian

The Evaluation Campaign of Natural Language Processing and Speech Tools for Italian (EVALITA) is the biennial initiative aimed at promoting the development of language and speech technologies for the Italian language. EVALITA is promoted by the Italian Association of Computational Linguistics (AILC) and it is endorsed by the Italian Association for Artificial Intelligence (AIxIA) and the Italian Association for Speech Sciences (AISV). EVALITA provides a shared framework where different systems and approaches can be scientifically evaluated and compared with each other with respect to a large variety of tasks, suggested and organized by the Italian research community. The proposed tasks represent scientific challenges where methods, resources, and systems can be tested against shared benchmarks representing linguistic open issues or real world applications, possibly in a multilingual and/or multi-modal perspective. The collected data sets provide big opportunities for scientists to explore old and new problems concerning NLP in Italian as well as to develop solutions and to discuss the NLP-related issues within the community. Some tasks are traditionally present in the evaluation campaign, while others are completely new. This paper introduces the tasks proposed at EVALITA 2020 and provides an overview to the participants and systems whose descriptions and obtained results are reported in these Proceedings

MicroRNA Roles in Cell Reprogramming Mechanisms

Cell reprogramming is a groundbreaking technology that, in few decades, generated a new paradigm in biomedical science. To date we can use cell reprogramming to potentially generate every cell type by converting somatic cells and suitably modulating the expression of key transcription factors. This approach can be used to convert skin fibroblasts into pluripotent stem cells as well as into a variety of differentiated and medically relevant cell types, including cardiomyocytes and neural cells. The molecular mechanisms underlying such striking cell phenotypes are still largely unknown, but in the last decade it has been proven that cell reprogramming approaches are significantly influenced by non-coding RNAs. Specifically, this review will focus on the role of microRNAs in the reprogramming processes that lead to the generation of pluripotent stem cells, neurons, and cardiomyocytes. As highlighted here, non-coding RNA-forced expression can be sufficient to support some cell reprogramming processes, and, therefore, we will also discuss how these molecular determinants could be used in the future for biomedical purposes