Analysis of reference material for use in group guidance

Thesis (Ed. M.)--Boston University, 194

Community dynamics and co-occurrence relationships of pelagic ciliates and their potential prey at a coastal and an offshore station in the ultra-oligotrophic Eastern Mediterranean Sea

Ciliates have been recognized as one of the major components of the microbial food web, especially in ultra-oligotrophic waters, such as the Eastern Mediterranean Sea, where nutrients are scarce and the microbial community is dominated by pico- and nano-sized organisms. For this reason, ciliates play an important role in these ecosystems since they are the main planktonic grazers. Regardless the importance of these organisms, little is known about the community structure of heterotrophic and mixotrophic ciliates and how they are associated to their potential prey. In this study, we used 18S V4 rRNA gene metabarcoding to analyze ciliate community dynamics and how the relationship with potential prey changes according to different seasons and depths. Samples were collected seasonally at two stations of the Eastern Mediterranean Sea (HCB: coastal, M3A: offshore) from the surface and deep chlorophyll maximum (DCM) layers. The ciliate community structure varied across depths in HCB and across seasons in M3A, and the network analysis showed that in both stations, mixotrophic oligotrichs were positively associated with diatoms and showed few negative associations with ASVs annotated as marine Stramenopiles (MAST). On the other hand, heterotrophic tintinnids showed negative relationships in both HCB and M3A stations, mostly with Ochrophyta and Chlorophyta. These results showed, in first place that, although the two stations are close to each other, the ciliate dynamics differed between them. Moreover, mixotrophic and heterotrophic ciliates may have different ecological niches since mixotrophic ciliates may be more selective compared to heterotrophic species regarding their prey. These findings are the first glimpse into an understanding of the dynamics between heterotrophic and mixotrophic ciliates and their role in microbial assemblages and dynamics of ultra-oligotrophic environments

Structural elucidation of a novel phosphoglycolipid isolated from six species of Halomonas.

The structure of a new phosphoglycolipid from the halophilic Gram-negative bacteria Halomonas elongata ATCC 33173(T), Halomonas eurihalina ATCC 49336(T), Halomonas almeriensis CECT 7050(T), strain Sharm (AM238662), Halomonas halophila DSM 4770(T), and Halomonas salina ATCC 49509(T) was elucidated by NMR and mass spectroscopy studies. In all of the species examined, the polar lipid composition consisted of 1,2-diacylglycero-3-phosphorylethanolamine, 1,2-diacylglycero-3-phosphoryl-glycerol, bisphosphatidyl glycerol, and the new phosphoglycolipid PGL1. The structure of PGL1 was established to be (2-(alpha-D-glucopyranosyloxy)-3-hydroxy-propyl)-phosphatidyl diacylglycerol. C16:0;C18:1 and C16:0;C19:cyclopropane are the most abundant acyl chains linked to the phosphatidylglycerol moiety of each isolated PGL1. All of the species presenting the lipid PGL1 belong to Halomonas rRNA group 1, suggesting that the new phosphoglycolipid could be a chemotaxonomic marker of this phylogenetic group

Analysis of Catania Flash Flood Case Study by Using Combined Microwave and Infrared Technique

Abstract In this paper, the analysis of an extreme convective event atypical for the winter season, which occurred on 21 February 2013 on the east coast of Sicily and caused a flash flood over Catania, is presented. In just 1 h, more than 50 mm of precipitation was recorded, but it was not forecast by numerical weather prediction (NWP) models and, consequently, no severe weather warnings were sent to the population. The case study proposed is first examined with respect to the synoptic situation and then analyzed by means of two algorithms based on satellite observations: the Cloud Mask Coupling of Statistical and Physical Methods (MACSP) and the Precipitation Evolving Technique (PET), developed at the National Research Council of Italy. Both of the algorithms show their ability in the near-real-time monitoring of convective cell formation and their rapid evolution. As quantitative precipitation forecasts by NWP could fail, especially for atypical convective events like in Catania, tools like MACSP and PET shall be adopted by civil protection centers to monitor the real-time evolution of deep convection events in aid to the severe weather warning service

Tuning interchain ferromagnetic instability in A2Cr3As3 ternary arsenides by chemical pressure and uniaxial strain

We analyze the effects of chemical pressure induced by alkali metal substitution and uniaxial strain on magnetism in the A2Cr3As3 (A = Na, K, Rb, Cs) family of ternary arsenides with quasi-one dimensional structure. Within the framework of the density functional theory, we predict that the non-magnetic phase is very close to a 3D collinear ferrimagnetic state, which realizes in the regime of moderate correlations, such tendency being common to all the members of the family with very small variations due to the different interchain ferromagnetic coupling. We uncover that the stability of such interchain ferromagnetic coupling has a non-monotonic behavior with increasing the cation size, being critically related to the degree of structural distortions which is parametrized by the Cr-As-Cr bonding angles along the chain direction. In particular, we demonstrate that it is boosted in the case of the Rb, in agreement with recent experiments. We also show that uniaxial strain is a viable tool to tune the non-magnetic phase towards an interchain ferromagnetic instability. The modifcation of the shape of the Cr triangles within the unit cell favors the formation of a net magnetization within the chain and of a ferromagnetic coupling among the chains. This study can provide relevant insights about the interplay between superconductivity and magnetism in this class of materials.Comment: Accepted in Phys. Rev. Materials as a regular article. 13 pages, 23 figures, 3 table

Intra-chain collinear magnetism and inter-chain magnetic phases in Cr3As3-K-based materials

We perform a comparative study of the KCr3As3 and the K2Cr3As3 quasi 1D compounds, and show that the strong interplay between the lattice and the spin degrees of freedom promotes a new collinear ferrimagnetic ground state within the chains in presence of intrachain antiferromagnetic couplings. We propose that the interchain antiferromagnetic coupling in KCr3As3 plays a crucial role for the experimentally observed spin-glass phase with low critical temperature. In the same region of the parameter space, we predict K2Cr3As3 to be non-magnetic but on the verge of the magnetism, sustaining interchain ferromagnetic spin fluctuations while the intrachain spin fluctuations are antiferromagnetic.Comment: Accepted in Phys. Rev. B as a regular articl

Combined IASI-NG and MWS observations for the retrieval of cloud liquid and ice water path: a deep learning artificial intelligence approach

A neural network (NN) approach is proposed to combine future infrared (IASI-NG) and microwave (MWS) observations to retrieve cloud liquid and ice water path. The methodology is applied to simulated IASI-NG and MWS observations in the period January–October 2019. IASI-NG and MWS observations are simulated globally at synoptic hours (00:00, 06:00, 12:00, 18:00 UTC) and on a regular spatial grid (0.125° × 0.125°) from ECMWF 5-generation reanalysis (ERA5). The state-of-the-art σ-IASI and RTTOV radiative transfer codes are used to simulate IASI-NG and MWS observations, respectively, from the earth's state vector given by ERA5. A principal component analysis of the simulated IASI-NG observations is performed. Accordingly, a NN is developed to retrieve cloud liquid and ice water path from a combination of 24 MWS channels and 30 IASI-NG PCs. Validation indicates that this combination results in liquid and ice water path retrievals with overall accuracy of 1.85 10 −2 kg/m 2 and 1.18 10 −2 kg/m 2 , respectively, and 0.97 correlation with respect to reference values. The root-mean-square error (RMSE) for CLWP results in about 30% of the mean value (5.91 10 −2 kg/m 2 ) and 22% of the variability (1-sigma). Similarly, the RMSE for CIWP results in about 41% of the mean value (2.91 10 −2 kg/m 2 ) and 22% of the variability. Two more NN are developed, retrieving cloud liquid and ice water path from microwave observations only (24 MWS channels) and infrared observations only (30 IASI-NG PCs), demonstrating quantitatively the advantage of using the combination of infrared and microwave observations with respect to either one alone

A methodological integrated approach to analyse climate change effects in agri-food sector: The TIMES water-energy-food module

The European Union’s 2030 climate and energy policy and the 2030 Agenda for Sustainable Development underline the commitment to mitigate climate change and reduce its impacts by supporting sustainable use of resources. This commitment has become stricter in light of the ambitious climate neutrality target set by the European Green Deal for 2050. Water, Energy and Food are the key variables of the “Nexus Thinking” which face the sustainability challenge with a multi-sectoral approach. The aim of the paper is to show the methodological path toward the implementation of an integrated modeling platform based on the Nexus approach and consolidated energy system analysis methods to represent the agri-food system in a circular economy perspective (from the use of water, energy, biomass, and land to food production). The final aim is to support decision-making connected to climate change mitigation. The IEA-The Integrated MARKAL-EFOM System (TIMES) model generator was used to build up the Basilicata Water, Energy and Food model (TIMES-WEF model), which allows users a comprehensive evaluation of the impacts of climate change on the Basilicata agri-food system in terms of land use, yields and water availability and a critical comparison of these indicators in different scenarios. The paper focuses on the construction of the model’s Reference Energy and Material System of the TIMES model, which integrates water and agricultural commodities into the energy framework, and on the results obtained through the calibration of the model β version to statistical data on agricultural activities.publishersversionpublishe

I DADA TEAMS: un'esperienza di didattica innovativa

Reading the needs of students, in the modern-day reality, requires teacher to intervene with innovative teaching methodologies, able to integrate the two dimensions (analog and digital) of teaching and to promote talents. With these aims the comprehensive institute "Foscolo-Gabelli" in Foggia, formerly DADA school, signatory of a memorandum of understanding with the University of Foggia has included the DADA Teams in the Three-Year Plan of the Training Offer. They are cooperative working groups, carried out in curricular time. Within the DADA Teams, students are supported in learning by multimedia tools and learn to learn through transversal educational paths, discovering their talents passions and attitudes. This study aims to document the experimentation contextualizing it in the panorama of research on the interactions between teaching and talent development, where the use of flexible and "open" technologies and learning environments can be a driving force for change

Fog Detection Based on Meteosat Second Generation-Spinning Enhanced Visible and InfraRed Imager High Resolution Visible Channel

In this study, the Meteosat Second Generation (MSG)-Spinning Enhanced Visible and Infrared Imager (SEVIRI) High Resolution Visible channel (HRV) is used in synergy with the narrow band MSG-SEVIRI channels for daytime fog detection. A new algorithm, named MSG-SEVIRI SatFog, has been designed and implemented. MSG-SEVIRI SatFog provides the indication of the presence of fog in near real time and at the high spatial resolution of the HRV channel. The HRV resolution is useful for detecting small scale daytime fog that would be missed in the MSG-SEVIRI low spatial resolution channels. By combining textural, physical and tonal tests, a distinction between fog and low stratus is performed for pixels identified as low/middle clouds or clear by the Classification-MAsk Coupling of Statistical and Physical Methods (C-MACSP) cloud detection algorithm. Suitable thresholds have been determined using a specific dataset covering different geographical areas, seasons and time of the day. MSG-SEVIRI SatFog is evaluated against METeorological Aerodrome Reports (METAR) data observations. Evaluation results in an accuracy of 69.9%, a probability of detection of 68.7%, a false alarm ratio of 31.3% and a probability of false detection of 30.0%