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161 p., The neurocognitive mechanisms that support the generalization of semantic representations across different languages remain to be determined. Current psycholinguistic models propose that semantic representations are likely to overlap across languages, although there is evidence also to the contrary. Neuroimaging studies observed that brain activity patterns associated with the meaning of words may be similar across languages. However, the factors that mediate cross-language generalization of semantic representations are not known. In a series of functional MRI research studies, we investigate how factors including state of visual awareness, depth of word processing and lexico-semantic characteristics of words influence cross-language generalization of semantic representations. Using multivariate pattern analysis, we found that fully conscious and deep processing of high concrete and high frequency words leads to above-chance cross-language generalization in putative areas of the semantic network. These results have ramifications for existing psycholinguistic models and theories of meaning representation.

The paper presents a systematic approach for solving complex prediction problems with a focus on energy efficiency. The approach involves using neural networks, specifically recurrent and sequential networks, as the main tool for prediction. In order to test the methodology, a case study was conducted in the telecommunications industry to address the problem of energy efficiency in data centers. The case study involved comparing four recurrent and sequential neural networks, including Recurrent Neural Networks (RNN), Long Short Term Memory (LSTM), Gated Recurrent Units (GRU), and Online Sequential Extreme Learning Machine (OS-ELM), to determine the best network in terms of prediction accuracy and computational time. The results showed that OS-ELM outperformed the other networks in both accuracy and computational efficiency. The simulation was applied to real traffic data and showed a potential energy savings of up to 12.2% in a single day. This highlights the importance of energy efficiency and the potential for the methodology to be applied to other industries. The methodology can be further developed as technology and data continue to advance, making it a promising solution for a wide range of prediction problems.

This study explores the potential use of frass, the larval excrement residue obtained from mealworm rearing, as organic fertilizer for crops. Its high organic matter content means that its joint application with a biostimulant based on efficient microorganisms, favoring its mineralization, is of interest. An experiment with lettuce plants (Lactuca sativa L.) was conducted with two factors and six replicates under greenhouse conditions. The first factor was frass amendment at 0%, 1%, 2.5%, and 5% of the peat substrate, and the second factor was a Bacillus-based BS at two levels, with and without efficient microorganism application. The results reveal that frass shows great potential as an organic fertilizer, providing macronutrients and increasing lettuce aerial biomass, although its effect is mediated by the application rate. Rates of 2.5% or higher proved negative for lettuce plant growth, especially root development, probably due to an increased incidence of potentially pathogenic fungi. The negative effect of medium–high frass rates was counteracted by the addition of a PGP-based biostimulant, enhancing lettuce plant nutrient uptake, aerial biomass, and quality in terms of succulence, but also favoring microbial diversity in the rhizosphere, increasing the incidence of beneficial microorganisms, and decreasing potentially pathogenic fungi. This positive synergy observed between frass and the PGP-based biostimulant is of interest for the design of new organic fertilization strategies.

Studying life history strategies is crucial for understanding the diversity among organisms. The trade-offs in traits related to survival, self-maintenance and reproduction play an important role in the variation of life histories and can be adjusted in response to environmental and physiological factors. Telomeres, which are repetitive DNA sequences found at the ends of chromosomes, can serve as molecular markers linking these factors and ultimately fitness. Telomeres naturally shorten with age and stress, such as diseases, and when they become too short, they trigger cellular senescence and ageing. However, some telomere restoration mechanisms can counteract this process.In this thesis, first I have adopted a theoretical approach to review the telomere research field and develop hypotheses for future exploration. Then, I also included an empirical section that aimed to evaluate and test some of these hypotheses' general patterns using data from a wild population of the polygynous bird species, the great reed warbler (Acrocephalus arundinaceus). I have taken advantage of the longitudinal study conducted for 40 years at Lake Kvismaren that have collected a comprehensive dataset on life history, behaviours and fitness components, along with a sampling of all the bird born and breeding in the area. I measured telomere length using the quantitative PCR method, and to investigate the ecological and evolutionary implications of parasites, I used the multiplex PCR method to detect the presence of avian malaria parasites in the birds' blood. In the first part of this thesis, I and my collaborators present a summary of telomere hypotheses that apply to the fields of ecology and evolution. We also classify and group these hypotheses based on their research context and hierarchical similarities. Furthermore, we identify gaps in the knowledge, such as the lack of hypotheses that can clarify telomere elongation patterns in the wild. As a result, we propose and expand on a novel

Nowadays, Ni@C nanostructured materials are attracting a great deal of attention due to their multiple catalytic or magnetic functionalities. In this article we report on the investigation of the correlation between the microstructure and magnetic properties of Ni nanoparticles embedded in a carbon matrix. The samples were obtained following a two-step procedure that ensures protection against nanoparticle oxidation, and was carried out in the following way: (i) the synthesis of a nickel-imidazole-based metal-organic framework (MOF) by a simple method in an aqueous medium at moderate temperature (95 °C); and (ii) carbonization of the MOF at different temperatures between 400 and 600 °C to obtain a carbon-supported hybrid material, containing Ni nanoparticles with an “artichoke-like” morphology, where a Ni-FCC core is surrounded by “bracts” of Ni-HCP and Ni3C. The average size of the nanoparticle slightly changes from 7 to 10 nm as the carbonization temperature is increased, but the Ni-FCC core diameter ranges from 3 to around 6 nm. We show how the information obtained on the evolution of the magnetic behaviour with carbonization temperature, using X-ray diffraction and electron microscopy, complements each other by providing consistent structural and magnetic characteristics of the investigated Ni@C nanoparticles. In fact, this joint analysis allows us to explain the formation and transformation of different Ni-based crystalline phases along the synthesis process, including Ni3C and Ni with both hexagonal and cubic crystalline structures. The amount of conventional Ni-FCC is below 10 wt% for the sample treated at 400 °C and it can reach up to 50 wt% for that treated at 600 °C. Finally, based on our current findings we propose an explanation for understanding the magnetic properties of Ni@C, in which the Ni-FCC core spins mainly govern the magnetic coupling of the whole system.

The North Anatolian Fault is the ∼1200-km-long active continental transform boundary between Anatolia and Eurasia. This strike-slip system initiated around 10–12 Ma and experienced diachronous episodes of strain localization along its strike. The structural evolution of the ∼350-km-long fault segments crossing the North Aegean Sea remains to be accurately investigated. There, the modern North Anatolian Fault is localized along two main branches: the northern branch ends at the North Aegean Trough and the southern branch ends at the Edremit-Skyros Trough. The Evia Basin is located in the North Aegean Domain between the North Anatolian Fault and the Corinth Rift. This study presents seismic reflection lines crossing the aforementioned structures of the North Aegean Domain, which document their subsurface structure and the sedimentary record of their activity since the Messinian. The seismic-reflection data set is tied to regional-scale stratigraphic markers, which constrains the age of main tectonic events related to the formation of the North Anatolian Fault. The seismic-reflection lines show that the two main branches of the North Anatolian Fault became localized structures at 1.3–2 Ma, coevally with the formation of the Evia Basin. Since 2 Ma, the North Aegean Troughs developed as a series of horsetail basins propagating westwards at the termination of the branches of the North Anatolian Fault. On a regional scale, the wide and diffuse North Anatolian transtensive shear zone active from Serravalian to Late Pliocene turned into a narrower shear zone at the two main branches of the North Anatolian Fault since the Early Pleistocene. This abrupt episode of strain localization occurred in the frame of the major Early Pleistocene change in stress regime from NE–SW to N–S extension, which has been observed throughout the Aegean Sea