Heterogeneous multicore systems for signal processing

This thesis explores the capabilities of heterogeneous multi-core systems, based on multiple Graphics Processing Units (GPUs) in a standard desktop framework. Multi-GPU accelerated desk side computers are an appealing alternative to other high performance computing (HPC) systems: being composed of commodity hardware components fabricated in large quantities, their price-performance ratio is unparalleled in the world of high performance computing. Essentially bringing “supercomputing to the masses”, this opens up new possibilities for application fields where investing in HPC resources had been considered unfeasible before. One of these is the field of bioelectrical imaging, a class of medical imaging technologies that occupy a low-cost niche next to million-dollar systems like functional Magnetic Resonance Imaging (fMRI). In the scope of this work, several computational challenges encountered in bioelectrical imaging are tackled with this new kind of computing resource, striving to help these methods approach their true potential. Specifically, the following main contributions were made: Firstly, a novel dual-GPU implementation of parallel triangular matrix inversion (TMI) is presented, addressing an crucial kernel in computation of multi-mesh head models of encephalographic (EEG) source localization. This includes not only a highly efficient implementation of the routine itself achieving excellent speedups versus an optimized CPU implementation, but also a novel GPU-friendly compressed storage scheme for triangular matrices. Secondly, a scalable multi-GPU solver for non-hermitian linear systems was implemented. It is integrated into a simulation environment for electrical impedance tomography (EIT) that requires frequent solution of complex systems with millions of unknowns, a task that this solution can perform within seconds. In terms of computational throughput, it outperforms not only an highly optimized multi-CPU reference, but related GPU-based work as well. Finally, a GPU-accelerated graphical EEG real-time source localization software was implemented. Thanks to acceleration, it can meet real-time requirements in unpreceeded anatomical detail running more complex localization algorithms. Additionally, a novel implementation to extract anatomical priors from static Magnetic Resonance (MR) scansions has been included.

Work and Family: a complex interplay. An Italian application of the DISC Model on health care workers

The present thesis investigates the issue of work-family conflict and facilitation in a sanitarian contest, using the DISC Model (De Jonge and Dormann, 2003, 2006). The general aim has been declined in two empirical studies reported in this dissertation chapters. Chapter 1 reporting the psychometric properties of the Demand-Induced Strain Compensation Questionnaire. Although the empirical evidence on the DISC Model has received a fair amount of attention in literature both for the theoretical principles and for the instrument developed to display them (DISQ; De Jonge, Dormann, Van Vegchel, Von Nordheim, Dollard, Cotton and Van den Tooren, 2007) there are no studies based solely on psychometric investigation of the instrument. In addition, no previous studies have ever used the DISC as a model or measurement instrument in an Italian context. Thus the first chapter of the present dissertation was based on psychometric investigation of the DISQ. Chapter 2 reporting a longitudinal study contribution. The purpose was to examine, using the DISC model, the relationship between emotional job characteristics, work-family interface and emotional exhaustion among a health care population. We started testing the Triple Match Principle of the DISC Model using solely the emotional dimension of the strain-stress process (i.e. emotional demands, emotional resources and emotional exhaustion). Then we investigated the mediator role played by w-f conflict and w-f facilitation in relation to emotional job characteristics and emotional exhaustion. Finally we compared the mediator model across workers involved in chronic illness home demands and workers who are not involved. Finally, a general conclusion, integrated and discussed the main findings of the studies reported in this dissertation.

Ultrasensitive chemiluminescence bioassays based on microfluidics in miniaturized analytical devices

The activity carried out during my PhD was principally addressed to the development of portable microfluidic analytical devices based on biospecific molecular recognition reactions and CL detection. In particular, the development of biosensors required the study of different materials and procedures for their construction, with particular attention to the development of suitable immobilization procedures, fluidic systems and the selection of the suitable detectors. Different methods were exploited, such as gene probe hybridization assay or immunoassay, based on different platform (functionalized glass slide or nitrocellulose membrane) trying to improve the simplicity of the assay procedure. Different CL detectors were also employed and compared with each other in the search for the best compromise between portability and sensitivity. The work was therefore aimed at miniaturization and simplification of analytical devices and the study involved all aspects of the system, from the analytical methodology to the type of detector, in order to combine high sensitivity with easiness-of-use and rapidity. The latest development involving the use of smartphone as chemiluminescent detector paves the way for a new generation of analytical devices in the clinical diagnostic field thanks to the ideal combination of sensibility a simplicity of the CL with the day-by-day increase in the performance of the new generation smartphone camera. Moreover, the connectivity and data processing offered by smartphones can be exploited to perform analysis directly at home with simple procedures. The system could eventually be used to monitor patient health and directly notify the physician of the analysis results allowing a decrease in costs and an increase in the healthcare availability and accessibility.

The dark and bright side of remote work: social isolation, concentration, and performance of remote workers

This dissertation, comprised of three separate studies, focuses on the relationship between remote work adoption and employee job performance, analyzing employee social isolation and job concentration as the main mediators of this relationship. It also examines the impact of concern about COVID-19 and emotional stability as moderators of these relationships. Using a survey-based method in an emergency homeworking context, the first study found that social isolation had a negative effect on remote work productivity and satisfaction, and that COVID-19 concerns affected this relationship differently for individuals with high and low levels of concern. The second study, a diary study analyzing hybrid workers, found a positive correlation between work from home (WFH) adoption and job performance through social isolation and job concentration, with emotional stability serving respectively as a buffer and booster in the relationships between WFH and the mediators. The third study, even in this case a diary study of hybrid workers, confirmed the benefits of work from home on job performance and the importance of job concentration as a mediator, while suggesting that social isolation may not be significant when studying employee job performance, but it is relevant for employee well-being. Although each study provides autonomously a discussion and research and practical implications, this dissertation also presents a general discussion on remote work and its psychological implications, highlighting areas for future research