A concept for the viticulture of 'tropical wines'.

At worldwide level, the classical viticulture produces wines is almost all places in different climate types, where it is possible to obtain only one harvest per year. In these conditions, bud burst in vines occurs as a result of temperature raising at the end of the winter?beginning of spring. With the development of the vegetative cycle, grapes arrive to maturity/harvest period at the end of the summer?beginning of the fall season. After the fall of the leaves, vines undergo a dormant period with a vegetative repose (condition found also in some intertropical producer regions). A lot of grapes are produced for a long-time in the intertropical zone, but only a little part is used to winemaking. Considered a challenge in the past, to produce quality wines in the tropics became reality. The present industry of fine wines began about 30 years ago. Today, there are many commercial wineries in several countries in Occident and Orient in the tropical zone of the globe, like in Brazil, India, Thailand and Venezuela, producing some million liters of fine wines per year - called ?tropical wines?. This article analysis these climates, in relation to the particular viticulture adapted and developed, where it is possible to have more than one cycle per year, with one or more harvests per year. Based on the particularities of this viticulture, a characterization is proposed for the viticulture of ?tropical wines?. Some examples showing different tropical climates are presented.

Climatic groups in Ibero-America viticulture compared to worldwide wine producer regions.

The wine production is an important activity in many Ibero-American countries. The wine producer regions of these countries configure a large use of different climate types and viticultural climates. In a vitivinicultural zoning project of CYTED (Ibero-American Program for Science, Technology and Development), a viticultural climatic characterization was done in this macro viticultural region. The project have assembled a climatic database that characterizes the viticultural regions, including relevant variables for viticulture: air temperature (mean, maximum, and minimum), precipitation, relative humidity, solar radiation, number of sunshine hours, wind speed, and evapotranspiration. Using indices of the Geoviticulture MCC System (HI, CI and DI), more than 70 viticultural regions in different countries (Argentina, Bolivia, Brazil, Chile, Cuba, Spain, Mexico, Peru, Portugal and Uruguay) were characterized according to its viticultural climatic. The results, which will be integrated to the worldwide database of the MCC System, showed that the Ibero-American viticulture is placed in a wide range of climatic groups of the wine producing regions around the world. This article presents the climatic groups found in Ibero-America, identifying also some new climatic groups not yet found in other regions of the world. This work also identifies some climatic groups not found in Ibero-America viticulture. The research has also highlighted viticultural areas characterized by climates with ?intra-annual climatic variability?, with the potential to produce more than one growing cycle per year. The results allow to conclude that the wide variability and climatic diversity present in Ibero-America may be one of the reasons to explain the diversity in terms of wine types, sensorial characteristics, typicity and uniqueness of wines produced on this macro-region.

6-(Methylsulfonyl) hexyl isothiocyanate as potential chemopreventive agent: molecular and cellular profile in leukaemia cell lines

Despite numerous therapeutic interventions cancer is still today the second leading cause of death. A growing interest has been addressed to isothiocytanates and more recently, the 6- (methylsulfonyl) hexyl isothiocyanate (6-MITC), the main constituent of the rhizome of Wasabia Japonica, has stimulated the interest of researchers. Aim of the research was to study if 6-MITC is able to modulate the main mechanisms underlying chemopreventive process in leukemic cells lines, verify the selectivity of action and the safety of use in terms of mutagenicity. The study was conducted on different cell types. In particular, Jurkat and HL-60 cells were treated with increasing concentrations of 6-MITC and cell viability, induction of apoptosis, cell cycle analysis, autophagy modulation and stimulation of differentiation were evaluated by flow cytometry. PBL, the non-transformed counterparty of leukemia cells, was used to analyse the selectivity of action by studying the same mechanisms previously indicated. Finally, safety of use and antimutagenicity were studied in TK6 cells adopting an automated protocol in flow cytometry. The achieved results have demonstrated that isothiocyanate modulates many signaling pathways involved in chemopreventive mechanism. In fact, 6-MITC induces apoptosis of both transformed cells, limits tumor growth by slowing down the cell cycle of Jurkat cells and blocks HL-60 cell cycle, increases the autophagic flux and induces cytodifferentiation of promyelocytic HL-60 into macrophage and granulocytic phenotypes. Furthermore, the results obtained with 6-MITC on PBL from healthy donors suggest that the isothiocyante is a good selective cytotoxic agent. Essential feature of a good chemopreventive agent is selectivity toward cancer cells and low toxicity towards non-transformed cells. Finally, the analysis of the micronuclei revealed that 6-MITC is not mutagenic, ensuring safe use, and that instead, it is able to counteract the mutagenic activity of the aneuploidogen Vinblastine, demonstrating another important and interesting chemopreventive activity.

Task analysis for HMI design. Level of automation study of aircraft navigation functions

Advancements in technology have enabled increasingly sophisticated automation to be introduced into the flight decks of modern aircraft. Generally, this automation was added to accomplish worthy objectives such as reducing flight crew workload, adding additional capability, or increasing fuel economy. Automation is necessary due to the fact that not all of the functions required for mission accomplishment in today’s complex aircraft are within the capabilities of the unaided human operator, who lacks the sensory capacity to detect much of the information required for flight. To a large extent, these objectives have been achieved. Nevertheless, despite all the benefits from the increasing amounts of highly reliable automation, vulnerabilities do exist in flight crew management of automation and Situation Awareness (SA). Issues associated with flight crew management of automation include: • Pilot understanding of automation’s capabilities, limitations, modes, and operating principles and techniques. • Differing pilot decisions about the appropriate automation level to use or whether to turn automation on or off when they get into unusual or emergency situations. • Human-Machine Interfaces (HMIs) are not always easy to use, and this aspect could be problematic when pilots experience high workload situations. • Complex automation interfaces, large differences in automation philosophy and implementation among different aircraft types, and inadequate training also contribute to deficiencies in flight crew understanding of automation.

Towards Unstructured Knowledge Integration in Natural Language Processing

In the last decades, Artificial Intelligence has witnessed multiple breakthroughs in deep learning. In particular, purely data-driven approaches have opened to a wide variety of successful applications due to the large availability of data. Nonetheless, the integration of prior knowledge is still required to compensate for specific issues like lack of generalization from limited data, fairness, robustness, and biases. In this thesis, we analyze the methodology of integrating knowledge into deep learning models in the field of Natural Language Processing (NLP). We start by remarking on the importance of knowledge integration. We highlight the possible shortcomings of these approaches and investigate the implications of integrating unstructured textual knowledge. We introduce Unstructured Knowledge Integration (UKI) as the process of integrating unstructured knowledge into machine learning models. We discuss UKI in the field of NLP, where knowledge is represented in a natural language format. We identify UKI as a complex process comprised of multiple sub-processes, different knowledge types, and knowledge integration properties to guarantee. We remark on the challenges of integrating unstructured textual knowledge and bridge connections with well-known research areas in NLP. We provide a unified vision of structured knowledge extraction (KE) and UKI by identifying KE as a sub-process of UKI. We investigate some challenging scenarios where structured knowledge is not a feasible prior assumption and formulate each task from the point of view of UKI. We adopt simple yet effective neural architectures and discuss the challenges of such an approach. Finally, we identify KE as a form of symbolic representation. From this perspective, we remark on the need of defining sophisticated UKI processes to verify the validity of knowledge integration. To this end, we foresee frameworks capable of combining symbolic and sub-symbolic representations for learning as a solution.