4,664 research outputs found
Information actors beyond modernity and coloniality in times of climate change:A comparative design ethnography on the making of monitors for sustainable futures in Curaçao and Amsterdam, between 2019-2022
In his dissertation, Mr. Goilo developed a cutting-edge theoretical framework for an Anthropology of Information. This study compares information in the context of modernity in Amsterdam and coloniality in Curaçao through the making process of monitors and develops five ways to understand how information can act towards sustainable futures. The research also discusses how the two contexts, that is modernity and coloniality, have been in informational symbiosis for centuries which is producing negative informational side effects within the age of the Anthropocene. By exploring the modernity-coloniality symbiosis of information, the author explains how scholars, policymakers, and data-analysts can act through historical and structural roots of contemporary global inequities related to the production and distribution of information. Ultimately, the five theses propose conditions towards the collective production of knowledge towards a more sustainable planet
Digitalization and Development
This book examines the diffusion of digitalization and Industry 4.0 technologies in Malaysia by focusing on the ecosystem critical for its expansion. The chapters examine the digital proliferation in major sectors of agriculture, manufacturing, e-commerce and services, as well as the intermediary organizations essential for the orderly performance of socioeconomic agents.
The book incisively reviews policy instruments critical for the effective and orderly development of the embedding organizations, and the regulatory framework needed to quicken the appropriation of socioeconomic synergies from digitalization and Industry 4.0 technologies. It highlights the importance of collaboration between government, academic and industry partners, as well as makes key recommendations on how to encourage adoption of IR4.0 technologies in the short- and long-term.
This book bridges the concepts and applications of digitalization and Industry 4.0 and will be a must-read for policy makers seeking to quicken the adoption of its technologies
Spatial Distribution of Meso- and Microplastics in Floodplain Soilscapes: Novel Insights from Rural to Urban Floodplains in Central Germany
Plastics and especially microplastics have become an emerging threat to global ecosystems. Despite the manifold benefits and applications of the human-made material plastic, the uncontrolled release of plastics into the environment has led to a “global plastic crisis”. During the last decades it becomes apparent that this crisis leads to the presence of plastics within different environments including marine, aquatic and terrestrial systems under worldwide evidence. Furthermore, environmental plastic research was able to reveal that although plastic often ends up in oceans, the majority of plastics in the environment are transported as part of a “global plastic cycle” from the land to sea via river systems. Those river systems are not isolated in the landscape, but rather a part of an “aquatic-terrestrial interface” which also encompasses floodplains and their soilscapes.
The present thesis focuses on the spatial distribution and spatio-temporal accumulation of meso- and microplastics in floodplain soilscapes following the overall objective to unravel the role of floodplain soilscapes as depositional areas of plastics within the global plastic cycle. In this context, a number of individual contributions have been published, reaching from conceptual spatial research approaches, over case studies conducted within two different floodplain soilscapes, to further opinions on the scientific benefit of plastic residues in floodplain soils. The individual contributions are linked by the major hypothesis that floodplain soilscapes act as temporal accumulation sites for plastics, driven by flood-related processes and land use over the last 70 years. To proof this major hypothesis and to overcome the lack of spatial reference in microplastics research, a geospatial sampling approach was conducted. Initial spatial data on meso- and microplastics in floodplain soils were obtained by a holistic analysis approach including the analysis of basic soil feature and metal analysis, the quantification of meso- and microplastics as well as sediment dating.
Within both studied river floodplains geospatial sampling enables a detection of meso- and microplastics over the entire floodplain area and within the entire soil column reaching depths of two meters. Additionally, a frequent accumulation of plastics was found within the upper 50 cm of floodplain soils. In combination with dating of near-channel floodplain sites, it could be demonstrated that those plastic accumulations are related to recent sedimentary deposits since the 1960s. However, evidence of plastic from deeper soil layers suggests that vertical displacements in floodplain soils occur and that plastics become mobilized. Furthermore, the presence of plastics in upstream areas suggests that plastics are released to river systems and deposited via flood dynamics already in rural areas. Additionally it appears that anthropogenic impacts, such as tillage or floodplain restoration influence plastic distributions.
The findings of this thesis clarify that floodplain soilscapes are part of the global plastic cycle as temporally depositional areas of plastics, but raising further questions on the mobility of plastics in soils and about the exact contribution of different environmental drivers towards plastic deposition. Finally, the present thesis indicates that the spatial reference of environmental plastic research should be rethought, in order to understand the spatial dynamics of plastics within the aquatic-terrestrial interface
Digital Innovations for a Circular Plastic Economy in Africa
Plastic pollution is one of the biggest challenges of the twenty-first century that requires innovative and varied solutions. Focusing on sub-Saharan Africa, this book brings together interdisciplinary, multi-sectoral and multi-stakeholder perspectives exploring challenges and opportunities for utilising digital innovations to manage and accelerate the transition to a circular plastic economy (CPE).
This book is organised into three sections bringing together discussion of environmental conditions, operational dimensions and country case studies of digital transformation towards the circular plastic economy. It explores the environment for digitisation in the circular economy, bringing together perspectives from practitioners in academia, innovation, policy, civil society and government agencies. The book also highlights specific country case studies in relation to the development and implementation of different innovative ideas to drive the circular plastic economy across the three sub-Saharan African regions. Finally, the book interrogates the policy dimensions and practitioner perspectives towards a digitally enabled circular plastic economy.
Written for a wide range of readers across academia, policy and practice, including researchers, students, small and medium enterprises (SMEs), digital entrepreneurs, non-governmental organisations (NGOs) and multilateral agencies, policymakers and public officials, this book offers unique insights into complex, multilayered issues relating to the production and management of plastic waste and highlights how digital innovations can drive the transition to the circular plastic economy in Africa.
The Open Access version of this book, available at https://www.taylorfrancis.com, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives (CC-BY-NC-ND) 4.0 license
Differences in well-being:the biological and environmental causes, related phenotypes, and real-time assessment
Well-being is a complex, and multifaceted construct that includes feeling good and functioning well. There is a growing global recognition of well-being as an important research topic and public policy goal. Well-being is related to less behavioral and emotional problems, and is associated with many positive aspects of daily life, including longevity, higher educational achievement, happier marriage, and more productivity at work. People differ in their levels of well-being, i.e., some people are in general happier or more satisfied with their lives than others. These individual differences in well-being can arise from many different factors, including biological (genetic) influences and environmental influences. To enhance the development of future mental health prevention and intervention strategies to increase well-being, more knowledge about these determinants and factors underlying well-being is needed. In this dissertation, I aimed to increase the understanding of the etiology in a series of studies using different methods, including systematic reviews, meta-analyses, twin designs, and molecular genetic designs. In part I, we brought together all published studies on the neural and physiological factors underlying well-being. This overview allowed us to critically investigate the claims made about the biology involved in well-being. The number of studies on the neural and physiological factors underlying well-being is increasing and the results point towards potential correlates of well-being. However, samples are often still small, and studies focus mostly on a single biomarker. Therefore, more well-powered, data-driven, and integrative studies across biological categories are needed to better understand the neural and physiological pathways that play a role in well-being. In part II, we investigated the overlap between well-being and a range of other phenotypes to learn more about the etiology of well-being. We report a large overlap with phenotypes including optimism, resilience, and depressive symptoms. Furthermore, when removing the genetic overlap between well-being and depressive symptoms, we showed that well-being has unique genetic associations with a range of phenotypes, independently from depressive symptoms. These results can be helpful in designing more effective interventions to increase well-being, taking into account the overlap and possible causality with other phenotypes. In part III, we used the extreme environmental change during the COVID-19 pandemic to investigate individual differences in the effects of such environmental changes on well-being. On average, we found a negative effect of the pandemic on different aspects of well-being, especially further into the pandemic. Whereas most previous studies only looked at this average negative effect of the pandemic on well-being, we focused on the individual differences as well. We reported large individual differences in the effects of the pandemic on well-being in both chapters. This indicates that one-size-fits-all preventions or interventions to maintain or increase well-being during the pandemic or lockdowns will not be successful for the whole population. Further research is needed for the identification of protective factors and resilience mechanisms to prevent further inequality during extreme environmental situations. In part IV, we looked at the real-time assessment of well-being, investigating the feasibility and results of previous studies. The real-time assessment of well-being, related variables, and the environment can lead to new insights about well-being, i.e., results that we cannot capture with traditional survey research. The real-time assessment of well-being is therefore a promising area for future research to unravel the dynamic nature of well-being fluctuations and the interaction with the environment in daily life. Integrating all results in this dissertation confirmed that well-being is a complex human trait that is influenced by many interrelated and interacting factors. Future directions to understand individual differences in well-being will be a data-driven approach to investigate the complex interplay of neural, physiological, genetic, and environmental factors in well-being
POTENTIAL OF COMPUTATIONAL METHODS FOR THE CATEGORIZATION OF ARCHITECTURAL OBJECTS ON THE EXAMPLE OF MEDIA ARCHITECTURE
The paper presents an example of the categorization of architectural objects and assessment of the characteristics of urban space, based on the analysis of specific features of architectural objects and urban landscape. The conducted analysis refers to media architecture and is presented in the complex context of the development of media solutions. The field of influence of IT on architecture is also stressed, both on the architect’s work and the image of the city, including with regard to smart city strategies. A gradual simplification approach was proposed for a targeted analysis. Data on media architecture were collected and, on their basis, significant features of each architectural object and its surrounding space were identified. The qualification of representative categories of media solutions was made based on the function of the object and the role of the media architecture object in the visual structure of the space, indicating the method of determining the degree of legibility of the space for a given category. The proposed process of categorization is a starting point in the discussion about the need and opportunities to use computational methods and databases supporting the assessment of the architectural typologies and characteristics of space, in reference to urban development
From CAD models to soft point cloud labels: An automatic annotation pipeline for cheaply supervised 3D semantic segmentation
We propose a fully automatic annotation scheme which takes a raw 3D point
cloud with a set of fitted CAD models as input, and outputs convincing
point-wise labels which can be used as cheap training data for point cloud
segmentation. Compared to manual annotations, we show that our automatic labels
are accurate while drastically reducing the annotation time, and eliminating
the need for manual intervention or dataset-specific parameters. Our labeling
pipeline outputs semantic classes and soft point-wise object scores which can
either be binarized into standard one-hot-encoded labels, thresholded into weak
labels with ambiguous points left unlabeled, or used directly as soft labels
during training. We evaluate the label quality and segmentation performance of
PointNet++ on a dataset of real industrial point clouds and Scan2CAD, a public
dataset of indoor scenes. Our results indicate that reducing supervision in
areas which are more difficult to label automatically is beneficial, compared
to the conventional approach of naively assigning a hard "best guess" label to
every point
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