285 research outputs found
Effect of corrosion-induced hydrogen embrittlement and its degradation impact on tensile properties and fracture toughness of (Al-Cu-Mg) 2024 alloy
No full textAbstractIn the present work, the effect of artificial ageing of AA2024-T3 on the tensile mechanical properties and fracture toughness degradation due to corrosion exposure will be investigated. Tensile and fracture toughness specimens were artificially aged to tempers that correspond to Under-Ageing (UA), Peak-Ageing (PA) and Over-Ageing (OA) conditions and then were subsequently exposed to exfoliation corrosion environment. The corrosion exposure time was selected to be the least possible according to the experimental work of Alexopoulos et al. (2016) so as to avoid the formation of large surface pits, trying to simulate the hydrogen embrittlement degradation only. The mechanical test results show that minimum corrosion-induced decrease in elongation at fracture was achieved for the peak-ageing condition, while maximum was noticed at the under-ageing and over-ageing conditions. Yield stress decrease due to corrosion is less sensitive to tempering; fracture toughness decrease was sensitive to ageing heat treatment thus proving that the S΄ particles play a significant role on the corrosion-induced degradation
The Liturgical Book of the Oktoechos. Function, Forms, and Manuscript Tradition
No full textThis chapter offers a detailed investigation into the liturgical book known as the Oktoechos within the Byzantine tradition, focusing on its function, structure, and manuscript history. The Author clarifies the multiple meanings of the term "oktoechos" in Byzantine sources, distinguishing between the musical eight-mode system, the weekly liturgical cycle, and the book itself. The study explores the evolution of the Oktoechos from its early roots in the Jerusalem liturgical tradition, particularly through Georgian and Greek sources such as the Old and New Tropologion. The work highlights the interplay between the Oktoechos and other liturgical books like the Menaion, Triodion, and Pentekostarion, and traces the contribution of major hymnographers including John of Damascus and Andrew of Crete. Special attention is given to terminological ambiguities, manuscript variants, and regional adaptations. Overall, the chapter presents a nuanced reconstruction of the development and standardization of this central Byzantine liturgical book
Socioeconomic status and anxiety as predictors of antidepressant treatment response and suicidal ideation in older adults.
No full textBACKGROUND: Separate reports from the maintenance treatment for late-life depression (MTLD) trials have shown that low socioeconomic status (SES) and anxiety symptoms at the time of treatment initiation predict lower levels of response to antidepressant treatment and higher levels of suicidal ideation in older adults. AIM: To determine whether SES and anxiety independently contribute to worse treatment outcomes, as indicated by persistence of depressive symptoms during treatment and the persistence of suicidal ideation. Consistent with prior evidence that sociodemographic factors and clinical history are both prognostic of depression treatment efficacy, we hypothesized that SES and pre-existing anxiety symptoms will both predict lower levels of response to treatment and higher levels of suicidal ideation. METHOD: Secondary analyses of data from the MTLD trials. RESULTS: Regression analyses which controlled for comorbid anxiety indicated that residents of middle- and high-income census tracts were more likely to respond to treatment (HR, 1.63; 95%CI, 1.08-2.46) and less likely to report suicidal ideation during treatment (OR, 0.51; 95%CI, 0.28-0.90) than residents of low income census tracts. The same regression models indicated that pre-existing anxiety symptoms were independently related to lower treatment response (HR, 0.73; 95%CI, 0.60-0.89) and higher risk of suicidal ideation (OR, 1.45; 95%CI, 0.98-2.14). CONCLUSION: These findings demonstrate the importance of treating anxiety symptoms during the course of treatment for late-life depression and, at the same time, addressing barriers to treatment response related to low SES
Assessing the failure of Open Government Data initiatives in Brazil
No full textWhile assessing the potential of a particular digital innovation initiative, especially when it has implications for a range of societal stakeholders, it becomes pertinent to understand the possible bottlenecks in its acceptability as well. In this regard, the present study seeks to understand how the Open Government Data (OGD) initiatives in Brazil are being confronted with bottlenecks in terms of their execution and acceptability. This exploratory study adopts a qualitative cross-sectional research approach wherein interviews are being conducted with 11 managers working in public organizations and are directly associated with the OGD initiatives. Findings from the interview responses delineate internal and external factors, resource availability, data maintenance, and lack of knowledge as the key determinants for the bottlenecks associated with the execution and acceptability of OGD initiatives by the societal stakeholders. The study's originality lies in its theoretical contribution towards an understanding of how a novel digital innovation-OGD, in the present case- is fraught with impediments in terms of its execution and acceptability. The study concludes with directions for further research and practitioner implications.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Information and Communication Technolog
Early Detection of Knee Osteoarthritis using Deep Learning-based MRI Features
No full textBackground: Advancements in the field of artificial intelligence have lead to the incorporation of automated algorithms in the analysis of medical images and data. Deep learning algorithms have been applied in muscu- loskeletal research to improve the understanding of osteoarthritis and to assist in disease detection and prognosis. The majority of the developed methods examine and process X-ray images and clinical data (age, gender etc.), with a small minority using MRI as inputs. Objective: The current master thesis project aims to investigate the influence of MRI scans on the early detection of knee osteoarthritis through the use of deep learning architectures, and to develop a semi-automatic method for knee region of interest extraction for creating the MRI input of detection algorithms. Methods: The MRI scans used in this project were acquired from the publicly available database of the Os- teoarthritis Initiative. In total 593 dual echo steady state and intermediate-weighted turbo spin-echo sequences were included. The extraction of the knee joint included several processing steps. Initially, a U-Net model was trained on 507 annotated dual echo steady state MRIs for the segmentation of bone and cartilage tissue, which was followed by the registration of the output masks to intermediate-weighted turbo spin-echo sequences in order to create the joint labels for the desired MRI scans. Final step for the region of interest construction included the search of bone coordinates and the creation of the knee joint region of interest. The detection of early osteoarthri- tis progression from knee MRI scans was tested through three different deep learning architectures, a residual network (ResNet), a densely connected convolutional network (DenseNet) and a convolutional variational au- toencoder (CVAE). Furthermore, the probability output of the ResNet and DenseNet as well as the feature vector of the CVAE were coupled with clinical data (age, gender, bone mass index) and used as input to a Logistic Regression Classifier, in order to investigate the influence of osteoarthritis related features to the detection task. The U-Net segmentation method was evaluated using Dice similarity coefficient and Intersection of Union while the detection algorithms using the area under the receiver’s characteristic curve (AUC) and the precision-recall curve (PR-AUC) metrics, with two different input data configurations, only MRI and a combination of MRI and clinical data. Results: The U-Net algorithm for bone and cartilage segmentation showed adequate results, since Dice simi- larity coefficient and Intersection of Union reached mean values higher than 0.99 and 0.88. Regarding the early detection of knee osteoarthritis incidence, ResNet and DenseNet showed similar results, with both methods hav- ing an AUC value ranging from 0.5033 to 0.6269, when only MRI scans were examined. In the case of MRI and clinical data combination, the more complicated deep learning architecture (DenseNet) achieved the highest AUC at 0.6556. The best performing model was CVAE with the largest number of latent space features (1000) achieving an AUC of 0.6699 when combined with clinical data and an AUC of 0.6689 when used alone as input to the logistic regression classifier. All three deep learning algorithms yielded higher performance metrics when clinical data where combined with models’ outputs. Conclusion: The tested deep learning algorithms showed a potential in the challenging task of early detection of knee osteoarthritis through MRI scans, even though they did not reach the same level of performance metrics. The region-of-interest creation had promising results for the implementation of U-Net method for bone tissue labelling.Biomedical Engineerin
Open Data Infrastructures
No full textData represents a key asset in virtually any aspect of society and economy. Open Data in particular represents a source of immense value, as social capital (Lampoltshammer & Scholz, 2017) as well as an asset for business cases. Governments and their public administrations are generating and collecting during their service a plethora of different kinds of data, as well as an enormous amount in terms of volume. To tab into the potential this data holds in terms of stimulating economy, as well as the development and enhancement of governmental service for the benefit of the public (see Fig. 6.1), a sophisticate Open Data Infrastructure is required.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Information and Communication Technolog
Barriers towards Open Government Data Value Co-Creation: An empirical investigation
No full textWhilst extant literature on Open Government Data (OGD) focuses upon value creation and innovation, there is scant emphasis upon the Value Co-Creation (VCC) that might result with the engagement of the public sector agencies and the users at large. The present study seeks to appreciate the barriers towards OGD VCC by adopting a qualitative research methodology wherein interviews are being conducted with key personnel manning the OGD initiatives in Brazil. Impediments veering around VCC may be counted the internal, social and cultural and data factors. Findings from the present study lend credence to the fact that a systematic strategizing is important for the success of OGD VCC lest Value Co-Destruction (VCD) happen. From a developing country's perspective, the present study acts as a sounding-board for bearing in mind the caveats deduced vis-a-via the success of the VCC processes.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Information and Communication Technolog
Laser activated single-use micropumps
No full textAbstractLab on Chip technologies have enabled the possibility of novel μTAS devices (micro Total Analysis System) that could drastically improve health care services for billions of people around the world. However, serious drawbacks that reside in fluid handling technology currently available for these systems often restrict the commercialization of such devices. This work demonstrates a novel fluid handling method as a possible alternative to current micropumping techniques for disposable microfluidic chips. This technology is based on a single use, low cost, thermal micropumping system in which expandable microsphere mixtures are activated by commercial grade laser diodes to achieve flow rates as high as 2.2μl/s and total volumes over 160μl. With the addition of a volume dependent shut off valve, nanoliter repeatability is realized. Pressure and heat transfer related data are presented. Finally, the possible prospects and limitations of this technology as a core element in unified optofluidic systems are discussed
Assessing economic incentives for dairy sheep farmers: A real options approach
No full textNew policy measures have been introduced to transform Greece’s agriculture into a more modern and environmentally friendly agriculture. Adopting new technology and environmentally friendly production systems involves risk and uncertainty, which in turn stress the need for well designed policy schemes. This study attempts to examine the effects of income variability upon the decision to adopt new technology and environmentally friendly production systems by introducing the real options analysis to dairy sheep farming in Greece. The real options procedure revealed that the investment in new technology in dairy sheep farms under organic scheme is profitable. Attractive economic incentives that are offered by the applied agricultural policy to young farmers compensate for the risk and uncertainty of the activity.agricultural policy, organic sheep farming, real options, Livestock Production/Industries,
Integration of IoT into e-government
No full textPurpose: The purpose of this paper is to highlight the drivers, barriers, benefits and risks affecting the integration of Internet of Things (IoT) into the e-government and to provide a future research agenda. Design/methodology/approach: Existing literature examining the relationships between e-government and IoT is scanned and evaluated by conceptualizing the IoT concept in the e-government perspective. Findings: The study shows that there are drivers to integrate IoT in e-government, such as ensuring the economy, efficiency and effectiveness of government operations, which would largely establish a relationship between the government and the citizens. Furthermore, there are barriers to such integration, given the lack of political will, the appropriate information technology infrastructure, the training of the stakeholders with a focus on the employee and the like. Originality/value: The integration of IoT in e-government is a novel and weakly explored concept, particularly in the light of new advances such as blockchain in the e-government, which requires further exploration and conceptualization, thereby achieving a shared/common vision and body of knowledge for its further successful and sustainable adoption – to the best of the authors’ knowledge, the current study is one of these initial attempts.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Information and Communication Technolog
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