3,051 research outputs found
Proceedings of the 10th International congress on architectural technology (ICAT 2024): architectural technology transformation.
The profession of architectural technology is influential in the transformation of the built environment regionally, nationally, and internationally. The congress provides a platform for industry, educators, researchers, and the next generation of built environment students and professionals to showcase where their influence is transforming the built environment through novel ideas, businesses, leadership, innovation, digital transformation, research and development, and sustainable forward-thinking technological and construction assembly design
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
Introduction to Facial Micro Expressions Analysis Using Color and Depth Images: A Matlab Coding Approach (Second Edition, 2023)
The book attempts to introduce a gentle introduction to the field of Facial
Micro Expressions Recognition (FMER) using Color and Depth images, with the aid
of MATLAB programming environment. FMER is a subset of image processing and it
is a multidisciplinary topic to analysis. So, it requires familiarity with
other topics of Artifactual Intelligence (AI) such as machine learning, digital
image processing, psychology and more. So, it is a great opportunity to write a
book which covers all of these topics for beginner to professional readers in
the field of AI and even without having background of AI. Our goal is to
provide a standalone introduction in the field of MFER analysis in the form of
theorical descriptions for readers with no background in image processing with
reproducible Matlab practical examples. Also, we describe any basic definitions
for FMER analysis and MATLAB library which is used in the text, that helps
final reader to apply the experiments in the real-world applications. We
believe that this book is suitable for students, researchers, and professionals
alike, who need to develop practical skills, along with a basic understanding
of the field. We expect that, after reading this book, the reader feels
comfortable with different key stages such as color and depth image processing,
color and depth image representation, classification, machine learning, facial
micro-expressions recognition, feature extraction and dimensionality reduction.
The book attempts to introduce a gentle introduction to the field of Facial
Micro Expressions Recognition (FMER) using Color and Depth images, with the aid
of MATLAB programming environment.Comment: This is the second edition of the boo
Seamless Multimodal Biometrics for Continuous Personalised Wellbeing Monitoring
Artificially intelligent perception is increasingly present in the lives of
every one of us. Vehicles are no exception, (...) In the near future, pattern
recognition will have an even stronger role in vehicles, as self-driving cars
will require automated ways to understand what is happening around (and within)
them and act accordingly. (...) This doctoral work focused on advancing
in-vehicle sensing through the research of novel computer vision and pattern
recognition methodologies for both biometrics and wellbeing monitoring. The
main focus has been on electrocardiogram (ECG) biometrics, a trait well-known
for its potential for seamless driver monitoring. Major efforts were devoted to
achieving improved performance in identification and identity verification in
off-the-person scenarios, well-known for increased noise and variability. Here,
end-to-end deep learning ECG biometric solutions were proposed and important
topics were addressed such as cross-database and long-term performance,
waveform relevance through explainability, and interlead conversion. Face
biometrics, a natural complement to the ECG in seamless unconstrained
scenarios, was also studied in this work. The open challenges of masked face
recognition and interpretability in biometrics were tackled in an effort to
evolve towards algorithms that are more transparent, trustworthy, and robust to
significant occlusions. Within the topic of wellbeing monitoring, improved
solutions to multimodal emotion recognition in groups of people and
activity/violence recognition in in-vehicle scenarios were proposed. At last,
we also proposed a novel way to learn template security within end-to-end
models, dismissing additional separate encryption processes, and a
self-supervised learning approach tailored to sequential data, in order to
ensure data security and optimal performance. (...)Comment: Doctoral thesis presented and approved on the 21st of December 2022
to the University of Port
Systemic Circular Economy Solutions for Fiber Reinforced Composites
This open access book provides an overview of the work undertaken within the FiberEUse project, which developed solutions enhancing the profitability of composite recycling and reuse in value-added products, with a cross-sectorial approach. Glass and carbon fiber reinforced polymers, or composites, are increasingly used as structural materials in many manufacturing sectors like transport, constructions and energy due to their better lightweight and corrosion resistance compared to metals. However, composite recycling is still a challenge since no significant added value in the recycling and reprocessing of composites is demonstrated. FiberEUse developed innovative solutions and business models towards sustainable Circular Economy solutions for post-use composite-made products. Three strategies are presented, namely mechanical recycling of short fibers, thermal recycling of long fibers and modular car parts design for sustainable disassembly and remanufacturing. The validation of the FiberEUse approach within eight industrial demonstrators shows the potentials towards new Circular Economy value-chains for composite materials
Oscillatory mechanisms of conscious perception and attention
Although the prominent role of neural oscillations in perception and cognition has been continuously investigated, some critical questions remain unanswered. My PhD thesis was aimed at addressing some of them.
First, can we dissociate oscillatory underpinnings of perceptual accuracy and subjective awareness? Current work would strongly suggest that this dissociation can be drawn. While the fluctuations in alpha-amplitude decide perceptual bias and metacognitive abilities, the speed of alpha activity (i.e., alpha-frequency) dictates sensory sampling, shaping perceptual accuracy.
Second, how are these oscillatory mechanisms integrated during attention? The obtained results indicate that a top-down visuospatial mechanism modulates neural assemblies in visual areas via oscillatory re-alignment and coherence in the alpha/beta range within the fronto-parietal brain network. These perceptual predictions are reflected in the retinotopically distributed posterior alpha-amplitude, while perceptual accuracy is explained by the higher alpha-frequency at the to-be-attended location. Finally, sensory input, elaborated via fast gamma oscillations, is linked to specific phases of this slower activity via oscillatory nesting, enabling integration of the feedback-modulated oscillatory activity with sensory information.
Third, how can we relate this oscillatory activity to other neural markers of behaviour (i.e., event-related potentials)? The obtained results favour the oscillatory model of ERP genesis, where alpha-frequency shapes the latency of early evoked-potentials, namely P1, with both neural indices being related to perceptual accuracy. On the other hand, alpha-amplitude dictates the amplitude of later P3 evoked-response, whereas both indices shape subjective awareness.
Crucially, by combining different methodological approaches, including neurostimulation (TMS) and neuroimaging (EEG), current work identified these oscillatory-behavior links as causal and not just as co-occurring events. Current work aimed at ameliorating the use of the TMS-EEG approach by explaining inter-individual differences in the stimulation outcomes, which could be proven crucial in the way we design entrainment experiments and interpret the results in both research and clinical settings
Co-designing the inflammatory arthritis self-management (aiM) intervention.
Self-management is an integral part of care for people living with inflammatory arthritis. The benefits of self-management interventions for people living with long-term conditions are well established. To date, most of the inflammatory arthritis self-management interventions have targeted only rheumatoid arthritis. Therefore, there is a need for a self-management intervention that reaches beyond just people living with rheumatoid arthritis. The overarching aim of this project was to co-design a self-management intervention for people across the inflammatory arthritis spectrum, based on the needs and preferences of co-designers (i.e. both people living with IA and healthcare professionals), as well as on the scientific literature. This project commenced with a mixed-method systematic review exploring the effectiveness and acceptability of existing inflammatory arthritis self-management interventions. Then, a two-phase, sequential multi-methods approach was employed. The first phase involved five asynchronous co-design workshops, guided by the Intervention Mapping Framework (Bartholomew et al. 2016). The second phase then explored participants' experience in participating in co-design research, including the barriers and facilitators to co-design. The mixed-method systematic review demonstrated that inflammatory arthritis self-management interventions produced a clinically meaningful reduction in fatigue and pain in people living with inflammatory arthritis. There was also some data to suggest that inflammatory arthritis self-management interventions have a beneficial effect on self-efficacy; knowledge; communication; health- related quality of life; and engagement with self-management behaviours. Additionally, the review found that inflammatory arthritis self-management interventions are generally acceptable to people living with inflammatory arthritis and healthcare professionals. Workshop findings provided important insight into the health problems and self-management needs of people living with inflammatory arthritis. The workshops also helped to identify the key content and features of the developed self-management intervention - i.e. the inflAmmatory arthrItis self-Management (aiM) intervention. Participants reported having an overall positive experience participating in the workshops, which provided them with an opportunity to meet others living with IA. The use of asynchronous workshops was felt to contribute to the participants' high attendance rate and the study's low attrition, despite IT-issues that were reported as a barrier to the participants' ability to fully participate in the workshops. This project developed a novel self-management intervention, which aims to improve the health status of people living with inflammatory arthritis through increased engagement with self-management strategies. The aiM intervention is based on the needs and preferences of the co-designers, and is grounded in theory and evidence. The findings have also provided new knowledge regarding the health problems related to people living with inflammatory arthritis, their self-management needs, and mechanisms that facilitate and inhibit co-design processes in an asynchronous remote context. Moving forward, it is recommended that the aiM intervention be tested for its feasibility and acceptability
Southern Adventist University Undergraduate Catalog 2022-2023
Southern Adventist University\u27s undergraduate catalog for the academic year 2022-2023.https://knowledge.e.southern.edu/undergrad_catalog/1121/thumbnail.jp
Selected Analytical Techniques of Solid State, Structure Identification, and Dissolution Testing in Drug Life Cycle
The textbook provides an overview of the main techniques applied in pharmaceutical industry, with the focus on solid-state analysis. It discusses spectral methods, thermal analysis, and dissolution testing, explains the theoretical background for each method and shows practical examples from a real-life drug-design and quality control applications. The textbook is thus intended for both pharmacy students and early career professionals
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