Mind the gap! An exploration of the role of lifelong learning in promoting co-production and citizenship within social care for older people

Contemporary themes in public policy have emphasised co-productive approaches within both the access and provision of support services to older people. This paper provides a cross disciplinary exploration from its respective authors perspectives on social work and educational gerontology to examine the potential for lifelong learning and learning interventions from which co-production with those using social care services in later life might be better facilitated. Using an example from the UK, we specifically elicit how co-produced care can enhance the horizon of learning and learning research. The synthesis of ideas across these two disciplines could enrich understanding and provide essential levers for moving towards empowerment and emancipation by engaging with a more co-productive approach in social care for older people. (DIPF/Orig.)

Cooperative learning and its influences on the diminishing of the digital divide

Digital divide is an issue that concerns our technology dominated society. The parents of ubiquitous computing dreamt of a total proliferation of information technology. But the reality we live in is not yet prepared for this future. There is current a need to develop programs in order to diminish this difference between the digitally included and the excluded one. PROEJA-Transiarte is a project ran by Universidade de Brasília in the city of Ceilândia, Federal District of Brazil. It proposes a different approach on the issue of digital divide, by introducing the cooperative creation of cyberart, based on the life stories of each participant, into the regular curriculum of EJA (Educação de Jovens e Adultos) classes, thus implementing the concept of solidary education. This research project investigated the role played by the cooperative learning the students put in practice during the workshops of the project in the diminishing of the digital exclusion a great part of the students feel. It looked into their activities, analyzing the development of their cooperation, putting it next in the context of the digital and social inclusion. After a multi-dimensional research on the theme, in the context of PROEJA-Transiarte, the conclusion shows the impact cooperative learning has in the reduction of the digital divide, analyzing the perception of the currently involved students, the researchers active in the project, or the former students that had their lives improved because of the workshops they participated in.

The Planned and the Emergent: An Alternative Model of Learning and Literacy

Within academic institutions, writing centers are uniquely situated, socially rich sites for exploring learning and literacy. I examine the work of the Michigan Tech Writing Center's UN 1002 World Cultures study teams primarily because student participants and Writing Center coaches are actively engaged in structuring their own learning and meaning-making processes. My research reveals that learning is closely linked to identity formation and leading the teams is an important component of the coaches' educational experiences. I argue that supporting this type of learning requires an expanded understanding of literacy and significant changes to how learning environments are conceptualized and developed. This ethnographic study draws on data collected from recordings and observations of one semester of team sessions, my own experiences as a team coach and UN 1002 teaching assistant, and interviews with Center coaches prior to their graduation. I argue that traditional forms of assessment and analysis emerging from individualized instruction models of learning cannot fully account for the dense configurations of social interactions identified in the Center's program. Instead, I view the Center as an open system and employ social theories of learning and literacy to uncover how the negotiation of meaning in one context influences and is influenced by structures and interactions within as well as beyond its boundaries. I focus on the program design, its enaction in practice, and how engagement in this type of writing center work influences coaches' learning trajectories. I conclude that, viewed as participation in a community of practice, the learning theory informing the program design supports identity formation —a key aspect of learning as argued by Etienne Wenger (1998). The findings of this study challenge misconceptions of peer learning both in writing centers and higher education that relegate peer tutoring to the role of support for individualized models of learning. Instead, this dissertation calls for consideration of new designs that incorporate peer learning as an integral component. Designing learning contexts that cultivate and support the formation of new identities is complex, involves a flexible and opportunistic design structure, and requires the availability of multiple forms of participation and connections across contexts.

Supporting Scientific Research Through Machine and Deep Learning: Fluorescence Microscopy and Operational Intelligence Use Cases

Although the debate of what data science is has a long history and has not reached a complete consensus yet, Data Science can be summarized as the process of learning from data. Guided by the above vision, this thesis presents two independent data science projects developed in the scope of multidisciplinary applied research. The first part analyzes fluorescence microscopy images typically produced in life science experiments, where the objective is to count how many marked neuronal cells are present in each image. Aiming to automate the task for supporting research in the area, we propose a neural network architecture tuned specifically for this use case, cell ResUnet (c-ResUnet), and discuss the impact of alternative training strategies in overcoming particular challenges of our data. The approach provides good results in terms of both detection and counting, showing performance comparable to the interpretation of human operators. As a meaningful addition, we release the pre-trained model and the Fluorescent Neuronal Cells dataset collecting pixel-level annotations of where neuronal cells are located. In this way, we hope to help future research in the area and foster innovative methodologies for tackling similar problems. The second part deals with the problem of distributed data management in the context of LHC experiments, with a focus on supporting ATLAS operations concerning data transfer failures. In particular, we analyze error messages produced by failed transfers and propose a Machine Learning pipeline that leverages the word2vec language model and K-means clustering. This provides groups of similar errors that are presented to human operators as suggestions of potential issues to investigate. The approach is demonstrated on one full day of data, showing promising ability in understanding the message content and providing meaningful groupings, in line with previously reported incidents by human operators.

Populism as a battlefield Populist actors and their representation on social and legacy media during the european parliament elections 2019 in Finland, Italy and the Netherlands

The objective of the present research is to describe and explain populist actors and populism as a concept and their representation on social and legacy media during the 2019 EU elections in Finland, Italy and The Netherlands. This research tackles the topic of European populism in the context of political communication and its relation to both the legacy and digital media within the hybrid media system. Departing from the consideration that populism and populist rhetoric are challenging concepts to define, I suggest that they should be addressed and analyzed through the usage of a combination of methods and theoretical perspectives, namely Communication Studies, Corpus Linguistics, Political theory, Rhetoric and Corpus-Assisted Discourse Studies. This thesis considers data of different provenance. On the one hand, for the Legacy media part, newspapers articles were collected in the three countries under study from the 1st until the 31st of May 2019. Each country’s legacy system is represented by three different quality papers and the articles were collected according to a selection of keywords (European Union Elections and Populism in each of the three languages). On the other hand, the Digital media data takes into consideration Twitter tweets collected during the same timeframe based on particular country-specific hashtags and tweets by identified populist actors. In order to meet the objective of this study, three research questions are posed and the analysis leading to the results are exhaustively presented and further discussed. The results of this research provide valuable and novel insights on how populism as a theme and a concept is being portrayed in the context of the European elections both in legacy and digital media and political communication in general.

RICORDACI: Research on the Conservation, Restoration and Diagnosis of Cinematographic Films

This thesis is the result of the RICORDACI project, a three-year European-funded initiative involving the collaboration between the University of Bologna and the restoration laboratory of the Cineteca di Bologna, L'immagine Ritrovata, which aimed to develop innovative solutions and technologies for the preservation of cinematographic film heritage. In particular, this thesis presents new analytical methodologies to exploit two types of portable miniaturized Near Infrared spectrometers working in Diffuse Reflectance over the Short Wave Infrared (SWIR) range, to study the near infrared (NIR) spectral behavior of film base materials for an accurate, non-invasive and fast characterization of the polymer type; and for films with cellulose acetate supports, they can be employed as a diagnostic tool for monitoring the Degree of substitution (DS) affected by the loss of acetyl groups. The proposed methods offer non-invasive, fast, inexpensive and simple alternatives for the characterization and diagnosis of film bases to help the strategic planning and decision-making regarding storage, digitalization and intervention of film collections. Secondly, the thesis includes the evaluation of new green cleaning systems and solvents for the effective, fast and innocuous removal of undesired substances from degraded cinematographic films bases; these tests compared the efficiency of traditional systems and solvents against the new proposals. Firstly, the use of Deep Eutectic Solvent formulations for removing softened gelatin residues from cellulose nitrate bases; and secondly, the employment of green volatile solvents with different application methods, including the use of new electrospun nylon mats, for avoiding the dangerous use of friction for the removal of Triphenyl Phosphate blooms from the surface of cellulose acetate bases. The results obtained will help improving the efficiency of the interventions needed before the digitalization of historical cinematographic films and will pave the way for further investigation on the use of green solvents for cleaning polymeric heritage objects.

The European legal approach to Open Science and research data

This dissertation proposes an analysis of the governance of the European scientific research, focusing on the emergence of the Open Science paradigm: a new way of doing science, oriented towards the openness of every phase of the scientific research process, able to take full advantage of the digital ICTs. The emergence of this paradigm is relatively recent, but in the last years it has become increasingly relevant. The European institutions expressed a clear intention to embrace the Open Science paradigm (eg., think about the European Open Science Cloud, EOSC; or the establishment of the Horizon Europe programme). This dissertation provides a conceptual framework for the multiple interventions of the European institutions in the field of Open Science, addressing the major legal challenges of its implementation. The study investigates the notion of Open Science, proposing a definition that takes into account all its dimensions related to the human and fundamental rights framework in which Open Science is grounded. The inquiry addresses the legal challenges related to the openness of research data, in light of the European Open Data framework and the impact of the GDPR on the context of Open Science. The last part of the study is devoted to the infrastructural dimension of the Open Science paradigm, exploring the e-infrastructures. The focus is on a specific type of computational infrastructure: the High Performance Computing (HPC) facility. The adoption of HPC for research is analysed from the European perspective, investigating the EuroHPC project, and the local perspective, proposing the case study of the HPC facility of the University of Luxembourg, the ULHPC. This dissertation intends to underline the relevance of the legal coordination approach, between all actors and phases of the process, in order to develop and implement the Open Science paradigm, adhering to the underlying human and fundamental rights.

Deep learning and embeddings for problems of computational biology

The development of Next Generation Sequencing promotes Biology in the Big Data era. The ever-increasing gap between proteins with known sequences and those with a complete functional annotation requires computational methods for automatic structure and functional annotation. My research has been focusing on proteins and led so far to the development of three novel tools, DeepREx, E-SNPs&GO and ISPRED-SEQ, based on Machine and Deep Learning approaches. DeepREx computes the solvent exposure of residues in a protein chain. This problem is relevant for the definition of structural constraints regarding the possible folding of the protein. DeepREx exploits Long Short-Term Memory layers to capture residue-level interactions between positions distant in the sequence, achieving state-of-the-art performances. With DeepRex, I conducted a large-scale analysis investigating the relationship between solvent exposure of a residue and its probability to be pathogenic upon mutation. E-SNPs&GO predicts the pathogenicity of a Single Residue Variation. Variations occurring on a protein sequence can have different effects, possibly leading to the onset of diseases. E-SNPs&GO exploits protein embeddings generated by two novel Protein Language Models (PLMs), as well as a new way of representing functional information coming from the Gene Ontology. The method achieves state-of-the-art performances and is extremely time-efficient when compared to traditional approaches. ISPRED-SEQ predicts the presence of Protein-Protein Interaction sites in a protein sequence. Knowing how a protein interacts with other molecules is crucial for accurate functional characterization. ISPRED-SEQ exploits a convolutional layer to parse local context after embedding the protein sequence with two novel PLMs, greatly surpassing the current state-of-the-art. All methods are published in international journals and are available as user-friendly web servers. They have been developed keeping in mind standard guidelines for FAIRness (FAIR: Findable, Accessible, Interoperable, Reusable) and are integrated into the public collection of tools provided by ELIXIR, the European infrastructure for Bioinformatics.

Nectar Robbery By A Hermit Hummingbird: Association To Floral Phenotype And Its Influence On Flowers And Network Structure.

Interactions between flowers and their visitors span the spectrum from mutualism to antagonism. The literature is rich in studies focusing on mutualism, but nectar robbery has mostly been investigated using phytocentric approaches focused on only a few plant species. To fill this gap, we studied the interactions between a nectar-robbing hermit hummingbird, Phaethornis ruber, and the array of flowers it visits. First, based on a literature review of the interactions involving  P. ruber, we characterized the association of floral larceny to floral phenotype. We then experimentally examined the effects of nectar robbing on nectar standing crop and number of visits of the pollinators to the flowers of Canna paniculata. Finally, we asked whether the incorporation of illegitimate interactions into the analysis affects plant-hummingbird network structure. We identified 97 plant species visited by P. ruber and found that P. ruber engaged in floral larceny in almost 30 % of these species. Nectar robbery was especially common in flowers with longer corolla. In terms of the effect on C. paniculata, the depletion of nectar due to robbery by P. ruber was associated with decreased visitation rates of legitimate pollinators. At the community level, the inclusion of the illegitimate visits of P. ruber resulted in modifications of how modules within the network were organized, notably giving rise to a new module consisting of P. ruber and mostly robbed flowers. However, although illegitimate visits constituted approximately 9 % of all interactions in the network, changes in nestedness, modularity, and network-level specialization were minor. Our results indicate that although a flower robber may have a strong effect on the pollination of a particular plant species, the inclusion of its illegitimate interactions has limited capacity to change overall network structure.

Endophytic and pathogenic isolates of the cacao fungal pathogen Moniliophthora perniciosa (Tricholomataceae) are indistinguishable based on genetic and physiological analysis

We evaluated the genetic and physiological variability of Moniliophthora perniciosa obtained from healthy and diseased branches of cacao (Theobroma cacao) plants. The diversity of the isolates was evaluated by RAPD technique and by studies of virulence and exoenzyme production. The genetic variability of endophytic and pathogenic M. perniciosa was evaluated in association with pathogenicity assays. RAPD analysis showed eight genetic groups, which were not related to plant disease status (healthy versus diseased branches). Isolates from cacao were included in three groups, excluding isolates from other host plants. Pathogenicity and enzyme analysis showed that the virulence of the isolates is not related to exoenzyme production. This is the first evidence that M. perniciosa colonizes healthy parenchymatic tissues, showing that endophytic behavior may occur in this species.

Separating politics and scientific research on heroin prescription - In reply [Letter]

No Abstract

Accumulation and Gaps in the Research on Argentine Rock

Based on a comprehensive study in research centers and libraries, a panorama of the critical response to Argentine rock in academic circles has been traced in various fields of knowledge. Research works including books, trade magazines, and academic papers on this musical movement spanning four decades have been consulted. The results show that the criticism has generated a ""developing tradition"" around the movement, mainly in the Social and Communication Sciences, and it has presented the following predominant traits: approaching rock essentially as a determinant of ""social identities""; periodization in the genre according to political regime: and analysis of the lyrics based solely on content. These traits contribute to a delimitation of rock as an exclusive phenomenon of the mass media, which relegates to secondary importance its aesthetic function and its relationship with other artistic series. Furthermore, we have observed a scarcity of approaches to rock lyrics as a linguistic-discursive surface.

Special issue on methods and learning in functional MRI: Introductory remarks

This special issue represents a further exploration of some issues raised at a symposium entitled “Functional magnetic resonance imaging: From methods to madness” presented during the 15th annual Theoretical and Experimental Neuropsychology (TENNET XV) meeting in Montreal, Canada in June, 2004. The special issue’s theme is methods and learning in functional magnetic resonance imaging (fMRI), and it comprises 6 articles (3 reviews and 3 empirical studies). The first (Amaro and Barker) provides a beginners guide to fMRI and the BOLD effect (perhaps an alternative title might have been “fMRI for dummies”). While fMRI is now commonplace, there are still researchers who have yet to employ it as an experimental method and need some basic questions answered before they venture into new territory. This article should serve them well. A key issue of interest at the symposium was how fMRI could be used to elucidate cerebral mechanisms responsible for new learning. The next 4 articles address this directly, with the first (Little and Thulborn) an overview of data from fMRI studies of category-learning, and the second from the same laboratory (Little, Shin, Siscol, and Thulborn) an empirical investigation of changes in brain activity occurring across different stages of learning. While a role for medial temporal lobe (MTL) structures in episodic memory encoding has been acknowledged for some time, the different experimental tasks and stimuli employed across neuroimaging studies have not surprisingly produced conflicting data in terms of the precise subregion(s) involved. The next paper (Parsons, Haut, Lemieux, Moran, and Leach) addresses this by examining effects of stimulus modality during verbal memory encoding. Typically, BOLD fMRI studies of learning are conducted over short time scales, however, the fourth paper in this series (Olson, Rao, Moore, Wang, Detre, and Aguirre) describes an empirical investigation of learning occurring over a longer than usual period, achieving this by employing a relatively novel technique called perfusion fMRI. This technique shows considerable promise for future studies. The final article in this special issue (de Zubicaray) represents a departure from the more familiar cognitive neuroscience applications of fMRI, instead describing how neuroimaging studies might be conducted to both inform and constrain information processing models of cognition.