The Ethnographic Quest in the Midst of COVID-19

The outbreak of SARS-CoV-2 has threatened ethnographic inquiry, undermining its quintessential characteristic. Participant observation, then, has been thoroughly dismembered by the radical measures implemented to prevent the spread of the virus. This phenomenon, in short, has dragged anthropologists to a liminal state within which ethnography is paradoxically caught in an onto-epistemological unstable vortex. The question of being here and not there, during the pandemic, is epitomised in the instability of different spatio-temporal contexts that overlap through technological mediations. Reflecting on previous fieldwork experiences and current virtual inquiries with the Shuar of the Ecuadorian Amazon unfolds how COVID-19 has thoroughly reshaped how the author approaches subjects' socio-ecological settings. Against this background, the article argues that corporeal immersion remains a necessary condition for the anthropological scrutiny of multispecies relationalities amidst the challenging times of the Anthropocene. The article nevertheless demonstrates that the intellectual efforts to grasp the different material temporalities of virtual spaces embrace the ethical principles concerning the renunciation of fieldwork with vulnerable communities. Furthermore, a reflective and speculative stance is proposed to actualise the snapshots of faraway physicalities linking them to past embodied and multi-sensory experiences. It is ultimately theorised how these mnemonic devices operate as creative forms of inquiry that overcome the pandemic consequences, extra-stimulating our cognitive capabilities to reflect on prior and possible socio-material interactions

Deep Learning for Automated Experimentation in Scanning Transmission Electron Microscopy

Machine learning (ML) has become critical for post-acquisition data analysis in (scanning) transmission electron microscopy, (S)TEM, imaging and spectroscopy. An emerging trend is the transition to real-time analysis and closed-loop microscope operation. The effective use of ML in electron microscopy now requires the development of strategies for microscopy-centered experiment workflow design and optimization. Here, we discuss the associated challenges with the transition to active ML, including sequential data analysis and out-of-distribution drift effects, the requirements for the edge operation, local and cloud data storage, and theory in the loop operations. Specifically, we discuss the relative contributions of human scientists and ML agents in the ideation, orchestration, and execution of experimental workflows and the need to develop universal hyper languages that can apply across multiple platforms. These considerations will collectively inform the operationalization of ML in next-generation experimentation.Comment: Review Articl

Seafarers, Silk, and Science: Oceanographic Data in the Making

This thesis comprises an empirical case study of scientific data production in oceanography and a philosophical analysis of the relations between newly created scientific data and the natural world. Based on qualitative interviews with researchers, I reconstruct research practices that lead to the ongoing production of digital data related to long-term developments of plankton biodiversity in the oceans. My analysis is centred on four themes: materiality, scientific representing with data, methodological continuity, and the contribution of non-scientists to epistemic processes. These are critically assessed against the background of today’s data-intensive sciences and increased automation and remoteness in oceanographic practices. Sciences of the world’s oceans have by and large been disregarded in philosophical scholarship thus far. My thesis opens this field for philosophical analysis and reveals various conditions and constraints of data practices that are largely uncontrollable by ocean scientists. I argue that the creation of useful scientific data depends on the implementation and preservation of material, methodological, and social continuities. These allow scientists to repeatedly transform visually perceived characteristics of research samples into meaningful scientific data stored in a digital database. In my case study, data are not collected but result from active intervention and subsequent manipulation and processing of newly created material objects. My discussion of scientific representing with data suggests that scientists do not extract or read any intrinsic representational relation between data and a target, but make data gradually more computable and compatible with already existing representations of natural systems. My arguments shed light on the epistemological significance of materiality, on limiting factors of scientific agency, and on an inevitable balance between changing conditions of concrete research settings and long-term consistency of data practices.European Research Counci

Immersive virtual reality and education: a study into the effectiveness of using this technology with preservice teachers.

Immersive virtual reality (IVR) is a rapidly advancing technology utilized across varying education fields for learning and educational applications. IVR provides the capabilities of computer simulations and embodied cognition experiences through a hands-on activity, making it a natural step to improve learning. Creating educational applications in IVR for use with students and preservice teachers could be a laborious and costly endeavor and require teacher belief in its effectiveness, so research is essential to investigate whether these applications are useful in advancing prekindergarten through Grade 12 (P-12) student learning. Research in this field is new, limited, and practically void of its use in P-12 learning environments. This inquiry expanded upon the literature on IVR technology in education and preservice teacher use of technology. Specifically, the purpose of this study was to investigate the impact of IVR technology on preservice teachers through an experience focused on the American Civil Rights Movement, specifically on knowledge attainment, lesson planning effectiveness, and motivation for future use in their instructional practice. Participants were 21 elementary preservice teachers in a diverse metropolitan university. Results indicated participants in the IVR group significantly increased scores on a content test, reported engagement with the experience, and indicated likelihood to use IVR with their future students

Visualization and Human-Machine Interaction

The digital age offers a lot of challenges in the eld of visualization. Visual imagery has been effectively used to communicate messages through the ages, to express both abstract and concrete ideas. Today, visualization has ever-expanding applications in science, engineering, education, medicine, entertainment and many other areas. Different areas of research contribute to the innovation in the eld of interactive visualization, such as data science, visual technology, Internet of things and many more. Among them, two areas of renowned importance are Augmented Reality and Visual Analytics. This thesis presents my research in the fields of visualization and human-machine interaction. The purpose of the proposed work is to investigate existing solutions in the area of Augmented Reality (AR) for maintenance. A smaller section of this thesis presents a minor research project on an equally important theme, Visual Analytics. Overall, the main goal is to identify the most important existing problems and then design and develop innovative solutions to address them. The maintenance application domain has been chosen since it is historically one of the first fields of application for Augmented Reality and it offers all the most common and important challenges that AR can arise, as described in chapter 2. Since one of the main problem in AR application deployment is reconfigurability of the application, a framework has been designed and developed that allows the user to create, deploy and update in real-time AR applications. Furthermore, the research focused on the problems related to hand-free interaction, thus investigating the area of speech-recognition interfaces and designing innovative solutions to address the problems of intuitiveness and robustness of the interface. On the other hand, the area of Visual Analytics has been investigated: among the different areas of research, multidimensional data visualization, similarly to AR, poses specific problems related to the interaction between the user and the machine. An analysis of the existing solutions has been carried out in order to identify their limitations and to point out possible improvements. Since this analysis delineates the scatterplot as a renowned visualization tool worthy of further research, different techniques for adapting its usage to multidimensional data are analyzed. A multidimensional scatterplot has been designed and developed in order to perform a comparison with another multidimensional visualization tool, the ScatterDice. The first chapters of my thesis describe my investigations in the area of Augmented Reality for maintenance. Chapter 1 provides definitions for the most important terms and an introduction to AR. The second chapter focuses on maintenance, depicting the motivations that led to choose this application domain. Moreover, the analysis concerning open problems and related works is described along with the methodology adopted to design and develop the proposed solutions. The third chapter illustrates how the adopted methodology has been applied in order to assess the problems described in the previous one. Chapter 4 describes the methodology adopted to carry out the tests and outlines the experimental results, whereas the fifth chapter illustrates the conclusions and points out possible future developments. Chapter 6 describes the analysis and research work performed in the eld of Visual Analytics, more specifically on multidimensional data visualizations. Overall, this thesis illustrates how the proposed solutions address common problems of visualization and human-machine interaction, such as interface de- sign, robustness of the interface and acceptance of new technology, whereas other problems are related to the specific research domain, such as pose tracking and reconfigurability of the procedure for the AR domain

Nucleus segmentation : towards automated solutions

Single nucleus segmentation is a frequent challenge of microscopy image processing, since it is the first step of many quantitative data analysis pipelines. The quality of tracking single cells, extracting features or classifying cellular phenotypes strongly depends on segmentation accuracy. Worldwide competitions have been held, aiming to improve segmentation, and recent years have definitely brought significant improvements: large annotated datasets are now freely available, several 2D segmentation strategies have been extended to 3D, and deep learning approaches have increased accuracy. However, even today, no generally accepted solution and benchmarking platform exist. We review the most recent single-cell segmentation tools, and provide an interactive method browser to select the most appropriate solution.Peer reviewe

The Ethnographic Quest in the Midst of COVID-19

The outbreak of SARS-CoV-2 has threatened ethnographic inquiry, undermining its quintessential characteristic. Participant observation, then, has been thoroughly dismembered by the radical measures implemented to prevent the spread of the virus. This phenomenon, in short, has dragged anthropologists to a liminal state within which ethnography is paradoxically caught in an onto-epistemological unstable vortex. The question of being here and not there, during the pandemic, is epitomised in the instability of different spatio-temporal contexts that overlap through technological mediations. Reflecting on previous fieldwork experiences and current virtual inquiries with the Shuar of the Ecuadorian Amazon unfolds how COVID-19 has thoroughly reshaped how the author approaches subjects' socio-ecological settings. Against this background, the article argues that corporeal immersion remains a necessary condition for the anthropological scrutiny of multispecies relationalities amidst the challenging times of the Anthropocene. The article nevertheless demonstrates that the intellectual efforts to grasp the different material temporalities of virtual spaces embrace the ethical principles concerning the renunciation of fieldwork with vulnerable communities. Furthermore, a reflective and speculative stance is proposed to actualise the snapshots of faraway physicalities linking them to past embodied and multi-sensory experiences. It is ultimately theorised how these mnemonic devices operate as creative forms of inquiry that overcome the pandemic consequences, extra-stimulating our cognitive capabilities to reflect on prior and possible socio-material interactions

The Ethnographic Quest in the Midst of COVID-19

The outbreak of SARS-CoV-2 has threatened ethnographic inquiry, undermining its quintessential characteristic. Participant observation, then, has been thoroughly dismembered by the radical measures implemented to prevent the spread of the virus. This phenomenon, in short, has dragged anthropologists to a liminal state within which ethnography is paradoxically caught in an onto-epistemological unstable vortex. The question of being here and not there, during the pandemic, is epitomised in the instability of different spatio-temporal contexts that overlap through technological mediations. Reflecting on previous fieldwork experiences and current virtual inquiries with the Shuar of the Ecuadorian Amazon unfolds how COVID-19 has thoroughly reshaped how the author approaches subjects' socio-ecological settings. Against this background, the article argues that corporeal immersion remains a necessary condition for the anthropological scrutiny of multispecies relationalities amidst the challenging times of the Anthropocene. The article nevertheless demonstrates that the intellectual efforts to grasp the different material temporalities of virtual spaces embrace the ethical principles concerning the renunciation of fieldwork with vulnerable communities. Furthermore, a reflective and speculative stance is proposed to actualise the snapshots of faraway physicalities linking them to past embodied and multi-sensory experiences. It is ultimately theorised how these mnemonic devices operate as creative forms of inquiry that overcome the pandemic consequences, extra-stimulating our cognitive capabilities to reflect on prior and possible socio-material interactions

Picture this: the value of multiple visual representations for student learning of quantum concepts in general chemistry

Mental models for scientific learning are often defined as, "cognitive tools situated between experiments and theories" (Duschl & Grandy, 2012). In learning, these cognitive tools are used to not only take in new information, but to help problem solve in new contexts. Nancy Nersessian (2008) describes a mental model as being [loosely] characterized as a representation of a system with interactive parts with representations of those interactions. Models can be qualitative, quantitative, and/or simulative (mental, physical, computational)" (p. 63). If conceptual parts used by the students in science education are inaccurate, then the resulting model will not be useful. Students in college general chemistry courses are presented with multiple abstract topics and often struggle to fit these parts into complete models. This is especially true for topics that are founded on quantum concepts, such as atomic structure and molecular bonding taught in college general chemistry. The objectives of this study were focused on how students use visual tools introduced during instruction to reason with atomic and molecular structure, what misconceptions may be associated with these visual tools, and how visual modeling skills may be taught to support students' use of visual tools for reasoning. The research questions for this study follow from Gilbert's (2008) theory that experts use multiple representations when reasoning and modeling a system, and Kozma and Russell's (2005) theory of representational competence levels. This study finds that as students developed greater command of their understanding of abstract quantum concepts, they spontaneously provided additional representations to describe their more sophisticated models of atomic and molecular structure during interviews. This suggests that when visual modeling with multiple representations is taught, along with the limitations of the representations, it can assist students in the development of models for reasoning about abstract topics such as atomic and molecular structure. There is further gain if students’ difficulties with these representations are targeted through the use additional instruction such as a workbook that requires the students to exercise their visual modeling skills