Moving toward stock units identification based on spatial population structure of marine species in the Mediterranean Sea and adjacent waters through multidisciplinary and holistic approaches for the sustainability of fisheries resources

Investigating stock identity of marine species in a multidisciplinary holistic approach can reveal patterns of complex spatial population structure and signatures of potential local adaptation. The population structure of common sole (Solea solea) in the Mediterranean Sea was delineated using genomic and otolith data, including single nucleotide polymorphisms (SNPs) markers and otolith data. SNPs were correlated with environmental and spatial variables to evaluate the impact of these features on the actual genetic population structure. Integrated holistic approach was applied to combine the tracers with different spatio-temporal scales. SNPs data was also used to illustrate the population structure of European hake (Merluccius merluccius) within the Alboran Sea, extending into the neighboring Mediterranean Sea and Atlantic Ocean. The aim was to identify patterns of neutral and potential adaptive genetic variation by applying seascape genomic framework. Results from both genetic and otolith data suggested significant divergence among putative populations of common sole, confirming a clear separation between Western, Adriatic Sea and Eastern Mediterranean Sea. Evidence of fine-scale population structure in the Western Mediterranean Sea was observed at outlier loci level and in the Adriatic. Our study not only indicates that separation among Mediterranean sole population is led primarily by neutral processes, but it also suggests the presence of local adaptation influenced by environmental and spatial factors. The holistic approach by considering the spatio-temporal scales of variation confirmed that the same pattern of separation between these geographical sites is currently occurring and has occurred for many generations. Results showed the occurrence of population structure in Merluccius merluccius by detecting westward–eastward differentiation among populations and distinct subgroups at a fine geographical scale using outlier SNPs. These results enhance the knowledge of the population structure of commercially relevant species to support the application of spatial stock assessment models, including a redefinition of fishery management units.

Trasmission and Reflection (ATR)Far-Infrared Spectroscopy Applied in the Analysis of Cultural Heritage Materials

FIR spectroscopy is an alternative way of collecting spectra of many inorganic pigments and corrosion products found on art objects, which is not normally observed in the MIR region. Most FIR spectra are traditionally collected in transmission mode but as a real novelty it is now also possible to record FIR spectra in ATR (Attenuated Total Reflectance) mode. In FIR transmission we employ polyethylene (PE) for preparation of pellets by embedding the sample in PE. Unfortunately, the preparation requires heating of the PE in order to produces at transparent pellet. This will affect compounds with low melting points, especially those with structurally incorporated water. Another option in FIR transmission is the use of thin films. We test the use of polyethylene thin film (PETF), both commercial and laboratory-made PETF. ATR collection of samples is possible in both the MIR and FIR region on solid, powdery or liquid samples. Changing from the MIR to the FIR region is easy as it simply requires the change of detector and beamsplitter (which can be performed within a few minutes). No preparation of the sample is necessary, which is a huge advantage over the PE transmission method. The most obvious difference, when comparing transmission with ATR, is the distortion of band shape (which appears asymmetrical in the lower wavenumber region) and intensity differences. However, the biggest difference can be the shift of strong absorbing bands moving to lower wavenumbers in ATR mode. The sometimes huge band shift necessitates the collection of standard library spectra in both FIR transmission and ATR modes, provided these two methods of collecting are to be employed for analyses of unknown samples. Standard samples of 150 pigment and corrosion compounds are thus collected in both FIR transmission and ATR mode in order to build up a digital library of spectra for comparison with unknown samples. XRD, XRF and Raman spectroscopy assists us in confirming the purity or impurity of our standard samples. 24 didactic test tables, with known pigment and binder painted on the surface of a limestone tablet, are used for testing the established library and different ways of collecting in ATR and transmission mode. In ATR, micro samples are scratched from the surface and examined in both the MIR and FIR region. Additionally, direct surface contact of the didactic tablets with the ATR crystal are tested together with water enhanced surface contact. In FIR transmission we compare the powder from our test tablet on the laboratory PETF and embedded in PE. We also compare the PE pellets collected using a 4x beam condenser, focusing the IR beam area from 8 mm to 2 mm. A few samples collected from a mural painting in a Nepalese temple, corrosion products collected from archaeological Chinese bronze objects and samples from a mural paintings in an Italian abbey, are examined by ATR or transmission spectroscopy.

Reaching to a target in the 3-D space

Reaching and grasping an object is an action that can be performed in light, under visual guidance, as well as in darkness, under proprioceptive control only. Area V6A is a visuomotor area involved in the control of reaching movements. V6A, besides neurons activated by the execution of reaching movements, shows passive somatosensory and visual responses. This suggests fro V6A a multimodal capability of integrating sensory and motor-related information, We wanted to know whether this integration occurrs in reaching movements and in the present study we tested whether the visual feedback influenced the reaching activity of V6A neurons. In order to better address this question, we wanted to interpret the neural data in the light of the kinematic of reaching performance. We used an experimental paradigm that could examine V6A responses in two different visual backgrounds, light and dark. In these conditions, the monkey performed an istructed-delay reaching task moving the hand towards different target positions located in the peripersonal space. During the execution of reaching task, the visual feedback is processed in a variety of patterns of modulation, sometimes not expected. In fact, having already demonstrated in V6A reach-related discharges in absence of visual feedback, we expected two types of neural modulation: 1) the addition of light in the environment enhanced reach-related discharges recorded in the dark; 2) the light left the neural response unmodified. Unexpectedly, the results show a complex pattern of modulation that argues against a simple additive interaction between visual and motor-related signals.

Portfolio optimization in the energy market

Let’s put ourselves in the shoes of an energy company. Our fleet of electricity production plants mainly includes gas, hydroelectric and waste-to-energy plants. We also sold contracts for the supply of gas and electricity. For each year we have to plan the trading of the volumes needed by the plants and customers: better to fix the price of these volumes in advance with the so-called forward contracts, instead of waiting for the delivery months, exposing ourselves to price uncertainty. Here’s the thing: trying to keep uncertainty under control in a market that has never shown such extreme scenarios as in recent years: a pandemic, a worsening climate crisis and a war that is affecting economies around the world have made the energy market more volatile than ever. How to make decisions in such uncertain contexts? There is an optimization problem: given a year, we need to choose the optimal planning of volume trading times, to meet the needs of our portfolio at the best prices, taking into account the liquidity constraints given by the market and the risk constraints imposed by the company. Algorithms are needed for the generation of market scenarios over a finite time horizon, that is, a probabilistic distribution that allows a view of all the dates between now and the end of the year of interest. Algorithms are needed to solve the optimization problem: we have proposed more than one and compared them; a very simple one, which avoids considering part of the complexity, moving on to a scenario approach and finally a reinforcement learning approach.

Adaptable security in the cloud-to-thing continuum

Recent technological advancements have played a key role in seamlessly integrating cloud, edge, and Internet of Things (IoT) technologies, giving rise to the Cloud-to-Thing Continuum paradigm. This cloud model connects many heterogeneous resources that generate a large amount of data and collaborate to deliver next-generation services. While it has the potential to reshape several application domains, the number of connected entities remarkably broadens the security attack surface. One of the main problems is the lack of security measures to adapt to the dynamic and evolving conditions of the Cloud-To-Thing Continuum. To address this challenge, this dissertation proposes novel adaptable security mechanisms. Adaptable security is the capability of security controls, systems, and protocols to dynamically adjust to changing conditions and scenarios. However, since the design and development of novel security mechanisms can be explored from different perspectives and levels, we place our attention on threat modeling and access control. The contributions of the thesis can be summarized as follows. First, we introduce a model-based methodology that secures the design of edge and cyber-physical systems. This solution identifies threats, security controls, and moving target defense techniques based on system features. Then, we focus on access control management. Since access control policies are subject to modifications, we evaluate how they can be efficiently shared among distributed areas, highlighting the effectiveness of distributed ledger technologies. Furthermore, we propose a risk-based authorization middleware, adjusting permissions based on real-time data, and a federated learning framework that enhances trustworthiness by weighting each client's contributions according to the quality of their partial models. Finally, since authorization revocation is another critical concern, we present an efficient revocation scheme for verifiable credentials in IoT networks, featuring decentralization, demanding minimum storage and computing capabilities. All the mechanisms have been evaluated in different conditions, proving their adaptability to the Cloud-to-Thing Continuum landscape.