The integration of immigrant-origin youths in Japan

The steadily growing immigration phenomenon in today’s Japan is showing a tangible and expanding presence of immigrant-origin youths residing in the country. International research in the migration studies area has underlined the importance of focusing on immigrant-origin youths to shed light on the character of the way immigrant incorporate in countries of destinations. In-deed, immigrants’ offspring, the adults of tomorrow, embody the interlocutor between first-generation immigrants and the receiving societal context. The extent of the presence of immigrants’ children in countries of destination is also a reliable yardstick to assess the maturation of the migration process, transforming it from a temporary phenomenon to a long-term settlement. Within this framework, the school is a privileged site to observe and analyze immigrant-origin youths’ integration. Alongside their family and peers, school constitutes one of the main agents of socialization. Here, children learn norms and rules and acquire the necessary tools to eventually compete in the pursuit of an occupation, determining their future socioeconomic standing. This doctoral research aims to identify which theoretical model articulated in the area of migration studies best describes the adaptation process of immigrant-origin youths in Japan. In particular, it examines whether (and to what extent) any of the pre-existing frameworks can help explain the Japanese occurring circumstances, or whether further elaboration and adjustment are needed. Alternatively, it studies whether it is necessary to produce a new model based on the peculiarities of the Japanese social context. This study provides a theoretical-oriented contribution to the (mainly descriptive but maturing) literature on immigrant-origin youths’ integration in Japan. Considering past growth trends of Japanese immigration and its expanding prospective projections (Korekawa 2018c), this study might be considered pioneering for future development of the phenomenon.

Development of JADE, a new software for the verification and validation of nuclear data libraries

Nuclear cross sections are the pillars onto which the transport simulation of particles and radiations is built on. Since the nuclear data libraries production chain is extremely complex and made of different steps, it is mandatory to foresee stringent verification and validation procedures to be applied to it. The work here presented has been focused on the development of a new python based software called JADE, whose objective is to give a significant help in increasing the level of automation and standardization of these procedures in order to reduce the time passing between new libraries releases and, at the same time, increasing their quality. After an introduction to nuclear fusion (which is the field where the majority of the V\&V action was concentrated for the time being) and to the simulation of particles and radiations transport, the motivations leading to JADE development are discussed. Subsequently, the code general architecture and the implemented benchmarks (both experimental and computational) are described. After that, the results coming from the major application of JADE during the research years are presented. At last, after a final discussion on the objective reached by JADE, the possible brief, mid and long time developments for the project are discussed.

PCM-based in-memory computing: architectures, circuits and applications

Analog In-memory Computing (AIMC) has been proposed in the context of Beyond Von Neumann architectures as a valid strategy to reduce internal data transfers energy consumption and latency, and to improve compute efficiency. The aim of AIMC is to perform computations within the memory unit, typically leveraging the physical features of memory devices. Among resistive Non-volatile Memories (NVMs), Phase-change Memory (PCM) has become a promising technology due to its intrinsic capability to store multilevel data. Hence, PCM technology is currently investigated to enhance the possibilities and the applications of AIMC. This thesis aims at exploring the potential of new PCM-based architectures as in-memory computational accelerators. In a first step, a preliminar experimental characterization of PCM devices has been carried out in an AIMC perspective. PCM cells non-idealities, such as time-drift, noise, and non-linearity have been studied to develop a dedicated multilevel programming algorithm. Measurement-based simulations have been then employed to evaluate the feasibility of PCM-based operations in the fields of Deep Neural Networks (DNNs) and Structural Health Monitoring (SHM). Moreover, a first testchip has been designed and tested to evaluate the hardware implementation of Multiply-and-Accumulate (MAC) operations employing PCM cells. This prototype experimentally demonstrates the possibility to reach a 95% MAC accuracy with a circuit-level compensation of cells time drift and non-linearity. Finally, empirical circuit behavior models have been included in simulations to assess the use of this technology in specific DNN applications, and to enhance the potentiality of this innovative computation approach.

New biomaterials for packaging: a green approach to biopolymers and biocomposites

The impellent global environmental issues related to plastic materials can be addressed by following two different approaches: i) the development of synthetic strategies towards novel bio-based polymers, deriving from biomasses and thus identifiable as CO2-neutral materials, and ii) the development of new plastic materials, such as biocomposites, which are bio-based and biodegradable and therefore able to counteract the accumulation of plastic waste. In this framework, this dissertation presents extensive research efforts have been devoted to the synthesis and characterization of polyesters based on various bio-based monomers, including ω-pentadecalactone, vanillic acid, 2,5-furan dicarboxylic acid, and 5-hydroxymethylfurfural. With the aim of achieving high molecular weight polyesters, different synthetic strategies have been used as melt polycondensation, enzymatic polymerization, ring-opening polymerization and chain extension reaction. In particular, poly(ethylene vanillate) (PEV), poly(ω-pentadecalactone) (PPDL), poly(ethylene vanillate-co-pentadecalactone) (P(EV-co-PDL)), poly(2-hydroxymethyl 5-furancarboxylate) (PHMF), poly(ethylene 2,5-furandicarboxylate) (PEF) with different amount of diethylene glycol (DEG) unit amount, poly(propylene 2,5-furandicarboxylate) (PPF), poly(hexamethylene 2,5-furandicarboxylate), (PHF) have been prepared and extensively characterized. To improve the lacks of poly(hydroxybutyrate-co-valerate) (PHBV), its minimal formulations with natural additives and its blending with medium chain length PHAs (mcl-PHAs) have been tested. Additionally, this dissertation presents new biocomposites based on polylactic acid (PLA), poly(butylene succinate) (PBS), and PHBV, which are polymers both bio-based and biodegradable. To maintain their biodegradability only bio-fillers have been taken into account as reinforcing agents. Moreover, the commitment to sustainability has further limited the selection and led to the exclusive use of agricultural waste as fillers. Detailly, biocomposites have been obtained and discussed by using the following materials: PLA and agro-wastes like tree pruning, potato peels, and hay leftovers; PBS and exhausted non-compliant coffee green beans; PHBV and industrial starch extraction residues.