Development of human visual system analysis for the implementation of a new instrument for flicker measurement

Flicker is a power quality phenomenon that applies to cycle instability of light intensity resulting from supply voltage fluctuation, which, in turn can be caused by disturbances introduced during power generation, transmission or distribution. The standard EN 61000-4-15 which has been recently adopted also by the IEEE as IEEE Standard 1453 relies on the analysis of the supply voltage which is processed according to a suitable model of the lamp – human eye – brain chain. As for the lamp, an incandescent 60 W, 230 V, 50 Hz source is assumed. As far as the human eye – brain model is concerned, it is represented by the so-called flicker curve. Such a curve was determined several years ago by statistically analyzing the results of tests where people were subjected to flicker with different combinations of magnitude and frequency. The limitations of this standard approach to flicker evaluation are essentially two. First, the provided index of annoyance Pst can be related to an actual tiredness of the human visual system only if such an incandescent lamp is used. Moreover, the implemented response to flicker is “subjective” given that it relies on the people answers about their feelings. In the last 15 years, many scientific contributions have tackled these issues by investigating the possibility to develop a novel model of the eye-brain response to flicker and overcome the strict dependence of the standard on the kind of the light source. In this light of fact, this thesis is aimed at presenting an important contribution for a new Flickermeter. An improved visual system model using a physiological parameter that is the mean value of the pupil diameter, has been presented, thus allowing to get a more “objective” representation of the response to flicker. The system used to both generate flicker and measure the pupil diameter has been illustrated along with all the results of several experiments performed on the volunteers. The intent has been to demonstrate that the measurement of that geometrical parameter can give reliable information about the feeling of the human visual system to light flicker.

Biofilms on exposed monumental stones: mechanism of formation and development of new control methods

Within the stone monumental artefacts artistic fountains are extremely favorable to formation of biofilms, giving rise to biodegradation processes related with physical-chemical and visual aspect alterations, because of their particular exposure conditions. Microbial diversity of five fountains (two from Spain and three from Italy) was investigated. It was observed an ample similarity between the biodiversity of monumental stones reported in literature and that one found in studied fountains. Mechanical procedures and toxic chemical products are usually employed to remove such phototrophic patinas. Alternative methods based on natural antifouling substances are recently experimented in the marine sector, due to their very low environmental impact and for the bio settlement prevention on partially immersed structures of ships. In the present work groups of antibiofouling agents (ABAs) were selected from literature for their ability to interfere, at molecular level, with the microbial communication system “quorum sensing”, inhibiting the initial phase of biofilm formation. The efficacy of some natural antibiofoulants agents (ABAs) with terrestrial (Capsaicine - CS, Cinnamaldehyde - CI) and marine origin (Zosteric Acid - ZA, poly-Alkyl Pyridinium Salts – pAPS and Ceramium botryocarpum extract - CBE), incorporated into two commercial coatings (Silres BS OH 100 - S and Wacker Silres BS 290 - W) commonly used in stone conservation procedures were evaluated. The formation of phototrophic biofilms in laboratory conditions (on Carrara marble specimens and Sierra Elvira stone) and on two monumental fountains (Tacca’s Fountain 2 - Florence, Italy and Fountain from Patio de la Lindaraja - Alhambra Palace, Granada, Spain) has been investigated in the presence or absence of these natural antifouling agents. The natural antibiofouling agents, at tested concentrations, demonstrated a certain inhibitory effect. The silane-siloxane based silicone coating (W) mixing with ABAs was more suitable with respect to ethyl silicate coating (S) and proved efficacy against biofilm formation only when incompletely cured. The laboratory results indicated a positive action in inhibiting the patina formation, especially for poly-alkyl pyridinium salts, zosteric acid and cinnamaldehyde, while on site tests revealed a good effect for zosteric acid.

Understanding the Combined Role of Internal and External Factors in New Service Development Process within the Professional Knowledge Intensive Business Service Firms

Our research asked the following main questions: how the characteristics of professionals service firms allow them to successfully innovate in exploiting through exploring by combining internal and external factors of innovation and how these ambidextrous organisations perceive these factors; and how do successful innovators in professional service firms use corporate entrepreneurship models in their new service development processes? With a goal to shed light on innovation in professional knowledge intensive business service firms’ (PKIBS), we concluded a qualitative analysis of ten globally acting law firms, providing business legal services. We analyse the internal and factors of innovation that are critical for PKIBS’ innovation. We suggest how these firms become ambidextrous in changing environment. Our findings show that this kind of firms has particular type of ambidexterity due to their specific characteristics. As PKIBS are very dependant on its human capital, governance structure, and the high expectations of their clients, their ambidexterity is structural, but also contextual at the same time. In addition, we suggest 3 types of corporate entrepreneurship models that international PKIBS use to enhance innovation in turbulent environments. We looked at how law firms going through turbulent environments were using corporate entrepreneurship activities as a part of their strategies to be more innovative. Using visual mapping methodology, we developed three types of innovation patterns in the law firms. We suggest that corporate entrepreneurship models depend on successful application of mainly three elements: who participates in corporate entrepreneurship initiatives; what are the formal processes that enhances these initiatives; and what are the policies applied to this type of behaviour.

Affordances and Language: How the Level of Object Familiarity modulates the Manipulation and Categorization of Objects across Development

According to much evidence, observing objects activates two types of information: structural properties, i.e., the visual information about the structural features of objects, and function knowledge, i.e., the conceptual information about their skilful use. Many studies so far have focused on the role played by these two kinds of information during object recognition and on their neural underpinnings. However, to the best of our knowledge no study so far has focused on the different activation of this information (structural vs. function) during object manipulation and conceptualization, depending on the age of participants and on the level of object familiarity (familiar vs. non-familiar). Therefore, the main aim of this dissertation was to investigate how actions and concepts related to familiar and non-familiar objects may vary across development. To pursue this aim, four studies were carried out. A first study led to the creation of the Familiar and Non-Familiar Stimuli Database, a set of everyday objects classified by Italian pre-schoolers, schoolers, and adults, useful to verify how object knowledge is modulated by age and frequency of use. A parallel study demonstrated that factors such as sociocultural dynamics may affect the perception of objects. Specifically, data for familiarity, naming, function, using and frequency of use of the objects used to create the Familiar And Non-Familiar Stimuli Database were collected with Dutch and Croatian children and adults. The last two studies on object interaction and language provide further evidence in support of the literature on affordances and on the link between affordances and the cognitive process of language from a developmental point of view, supporting the perspective of a situated cognition and emphasizing the crucial role of human experience.

Development of an innovative strategy to enhance the efficacy of gene therapy for CDKL5 deficiency disorder

CDKL5 (cyclin-dependent kinase-like 5) deficiency disorder (CDD) is a severe X-linked neurodevelopmental disease caused by mutations in the CDKL5 gene, characterized by early-onset epileptic seizures, intellectual disability, motor and visual impairment and respiratory dysregulation. Although pharmacological treatments are used to control seizures, there is currently no cure to ameliorate symptoms for CDD. Albeit delivery of a wild-type copy of the mutated gene to cells represents the most curative approach for a monogenic disease, proof-of-concept studies highlight significant efficacy caveats for brain gene therapy. The major one regards the low efficiency of gene delivery to the CNS by viral vectors. We used a secretable Igk-TATk-CDKL5 protein to enhance the efficiency of a gene therapy for CDD. In view of the properties of the Igk-chain leader sequence, the TATk-CDKL5 protein produced by infected cells is secreted via constitutive secretory pathways. Importantly, due to the transduction property of the TATk peptide, the secreted CDKL5 protein is internalized by cells. We compared the effects of a CDKL5 gene therapy with an IgK-TATk-CDKL5 gene therapy in a Cdkl5 KO mouse model to validate whether the Igk-TATk-CDKL5 approach significantly improve the therapeutic efficacy. We found that, although AAVPHP.B_Igk-TATk-CDKL5 and AAVPHP.B_CDKL5 vectors had similar brain infection efficiency, the AAVPHP.B_Igk-TATk-CDKL5 vector led to a higher CDKL5 protein replacement and Cdkl5 KO mice treated with the AAVPHP.B_Igk-TATk-CDKL5 vector showed a behavioral and neuroanatomical improvement in comparison with Cdkl5 KO mice treated with the AAVPHP.B_CDKL5 vector.

Alpha oscillations index the functionality and the plastic changes of the visual system

Alpha oscillations are linked to visual awareness and to the periodical sampling of visual information, suggesting that alpha rhythm reflect an index of the functionality of the posterior cortices, and hence of the visual system. Therefore, the present work described a series of studies investigating alpha oscillations as a biomarker of the functionality and the plastic modifications of the visual system in response to lesions to the visual cortices or to external stimulations. The studies presented in chapter 5 and 6 showed that posterior lesions alter alpha oscillations in hemianopic patients, with reduced alpha reactivity at the eyes opening and decreased alpha functional connectivity, especially in right-lesioned hemianopics, with concurrent dysfunctions in the theta range, suggesting a specialization of the right hemisphere in orchestrating alpha oscillations and coordinating complex interplays among different brain rhythms. The study presented in chapter 7 investigated a mechanism of rhythmical attentional sampling of visual information in healthy participants, showing that perceptual performance is influenced by a rhythmical mechanism of attentional allocation, occurring at lower-alpha frequencies (i.e., 7 Hz), when a single spatial location is monitored, and at lower frequencies (i.e., 5 Hz), when attention is allocated to two spatial locations. Moreover, the right hemisphere seemed to have a dominance in this rhythmical attentional sampling, distributing attentional resources to the entire visual field. Finally, the study presented in chapter 8 showed that prolonged visual entrainment induce long-term modulations of resting-state alpha activity in healthy participants, suggesting that persistent modifications in the functionality of the visual system are possible. Altogheter, these findings show that functional processes and plastic changes of the visual system are reflected in alpha oscillatory patterns. Therefore, investigating and promoting alpha oscillations may contribute to the development of rehabilitative protocols to ameliorate the functionality of the visual system, in brain lesioned patients.

Development of unsupervised learning methods with applications to life sciences data

Machine Learning makes computers capable of performing tasks typically requiring human intelligence. A domain where it is having a considerable impact is the life sciences, allowing to devise new biological analysis protocols, develop patients’ treatments efficiently and faster, and reduce healthcare costs. This Thesis work presents new Machine Learning methods and pipelines for the life sciences focusing on the unsupervised field. At a methodological level, two methods are presented. The first is an “Ab Initio Local Principal Path” and it is a revised and improved version of a pre-existing algorithm in the manifold learning realm. The second contribution is an improvement over the Import Vector Domain Description (one-class learning) through the Kullback-Leibler divergence. It hybridizes kernel methods to Deep Learning obtaining a scalable solution, an improved probabilistic model, and state-of-the-art performances. Both methods are tested through several experiments, with a central focus on their relevance in life sciences. Results show that they improve the performances achieved by their previous versions. At the applicative level, two pipelines are presented. The first one is for the analysis of RNA-Seq datasets, both transcriptomic and single-cell data, and is aimed at identifying genes that may be involved in biological processes (e.g., the transition of tissues from normal to cancer). In this project, an R package is released on CRAN to make the pipeline accessible to the bioinformatic Community through high-level APIs. The second pipeline is in the drug discovery domain and is useful for identifying druggable pockets, namely regions of a protein with a high probability of accepting a small molecule (a drug). Both these pipelines achieve remarkable results. Lastly, a detour application is developed to identify the strengths/limitations of the “Principal Path” algorithm by analyzing Convolutional Neural Networks induced vector spaces. This application is conducted in the music and visual arts domains.

Mind the gaps: cognitive-inspired AI for high-level visual sensemaking. Towards abstract concept image classification

The abundance of visual data and the push for robust AI are driving the need for automated visual sensemaking. Computer Vision (CV) faces growing demand for models that can discern not only what images "represent," but also what they "evoke." This is a demand for tools mimicking human perception at a high semantic level, categorizing images based on concepts like freedom, danger, or safety. However, automating this process is challenging due to entropy, scarcity, subjectivity, and ethical considerations. These challenges not only impact performance but also underscore the critical need for interoperability. This dissertation focuses on abstract concept-based (AC) image classification, guided by three technical principles: situated grounding, performance enhancement, and interpretability. We introduce ART-stract, a novel dataset of cultural images annotated with ACs, serving as the foundation for a series of experiments across four key domains: assessing the effectiveness of the end-to-end DL paradigm, exploring cognitive-inspired semantic intermediaries, incorporating cultural and commonsense aspects, and neuro-symbolic integration of sensory-perceptual data with cognitive-based knowledge. Our results demonstrate that integrating CV approaches with semantic technologies yields methods that surpass the current state of the art in AC image classification, outperforming the end-to-end deep vision paradigm. The results emphasize the role semantic technologies can play in developing both effective and interpretable systems, through the capturing, situating, and reasoning over knowledge related to visual data. Furthermore, this dissertation explores the complex interplay between technical and socio-technical factors. By merging technical expertise with an understanding of human and societal aspects, we advocate for responsible labeling and training practices in visual media. These insights and techniques not only advance efforts in CV and explainable artificial intelligence but also propel us toward an era of AI development that harmonizes technical prowess with deep awareness of its human and societal implications.