85000 research outputs found
Sort by
<b>Default Viewing: Reconceptualising Choice and Habit in Television Audience Research</b>
No full textWhen choosing what to watch, television audiences habitually default to particular channels, shows and apps as part of their everyday routines. Additionally, streaming platforms and devices also default to particular content, services or ads as determined by their software settings. In other words, television viewing is commonly shaped by both behavioural and technological defaults. How can television audience research account for these two distinct, yet related, phenomena? What does defaulting mean for our understanding of media choice in the streaming age? Drawing on the authors’ recent empirical work, this article develops a conceptual framework for understanding the role of defaults in contemporary television viewing. Our analysis synthesises ideas from fields of knowledge that are rarely considered together – television audience studies, platform studies, and the sociology of habit – to revise longstanding debates about defaults, and to update them for the present context of streaming television.</p
Time-dependent reliability of corroded mild steel pipes by different failure modes
No full textThis study aims to analytically assess the time-dependent failure of corrosion-induced mild steel pipes by employing two fracture failure criteria: the fracture toughness-based criterion and the stress-based criterion. The investigation intends to identify the influential factors that impinge upon the assessment of failure probability within this context. It is found that there is a linear relationship between the ratio of wall thickness to inner radius and the probability of failure and that between the internal pressure and the probability of failure. Notably, the influence on the evaluation of failure probability by the ratio of wall thickness to inner radius is more prominent than the internal pressure. It is also found that a comprehensive criterion is necessary for evaluating the fracture resistance of corroded mild steel pipes, which considers both initial fracture toughness and ultimate stress. These findings can provide theoretical evidence for pipe engineers to develop maintenance or repair strategies in mild steel pipes. The significance of this paper is the development of an analytical framework for predicting the probability of failure of corroded mild steel pipes, considering the complexities of elastic-plastic fracture mechanics
Composite nanofibrous membranes with two-dimensional ZIF-L and PVDF-HFP for CO2 separation
No full textMembrane gas-solvent contactors show effective CO2 capture as compared to solvent absorption. However, the overall efficiency of the capture process is compromised by the relatively low CO2 transfer rate of existing commercial membranes. Herein, we propose the integration of a two-dimensional zeolitic imidazolate framework (ZIF-L) with outstanding CO2 adsorption properties into porous poly(vinylidene fluoride-co-hexafluoropropylene) (PVDF-HFP) nanofibre membranes for energy-efficient CO2 separation through membrane gas absorption. Well-defined composite structures of the nanofibre membranes with ZIF-L are fabricated using the electrospinning technique. The favourable adsorption of CO2 molecules in the unique cushion-shaped cavities of ZIF-L enhances CO2 flux during both absorption and stripping processes even under mild temperature conditions when utilised in the composite nanofibre membranes. Consequently, the PVDF-HFP membrane with 5 wt% ZIF-L presents 26.7 mmol m−2 s−1 of CO2 stripping flux at 100 °C
New model of nutrient utilization and salt regulation of anaerobic digestate from food waste
No full textAnaerobic digestion (AD) treatment of food waste (FW) has become increasingly popular, in the meantime, it creates a challenge for effective management of its by-products. The study of biogas slurry (BS) treatment methods is an ongoing endeavor. In this study, we formulated the following scenarios for the treatment of BS: S1 as sewage treatment, S2 as a base rice fertilizer, and S3 as an additional rice fertilizer. The results of the material flow analysis and comprehensive evaluation showed that the nitrogen and phosphorus recovery of S2 reached 42.4 % and 14.9 %, respectively. Without causing soil salt accumulation, it shows the best economic efficiency and minimizes the environmental impact, which is the preferred feasible solution worth popularizing. Based on the predicted FW production in China in 2030, the adoption of S2 could replace the use of 155.2 kt of chemical fertilizers, irrigate about 689.6 kha of paddy fields, and save 2177.1 million. In conclusion, this study offers a new idea for large-scale treatment of BS and provide scientific knowledge to improve the sustainable management of FW anaerobic digestate
Exploring the contributors to the digital economy: Insights from Vietnam with comparisons to Thailand
No full textThis paper introduces a practical framework to quantify the digital economy and evaluates its growth in Vietnam, utilizing available Input-Output (I–O) tables from the OECD statistics database. Additionally, it conducts a direct comparison between Vietnam and Thailand, shedding light on their relative standings. The primary contribution of this paper lies in its devised approach for measuring the digital economy. This methodology generates meaningful estimations of the digital economy's size and drivers within a specific country. Moreover, these estimated results are suitable for cross-country comparisons. Concurrently, applying this approach to analyze Vietnam and comparing it with Thailand reveals valuable insights. Firstly, Vietnam's digital economy, amounting to US$17,458 and comprising 7.9% of GDP in 2018, exhibited consistent expansion during the 2012–2018 period. Secondly, the ICT sector, particularly foreign-invested ICT hardware manufacturing, contributes roughly 50% to Vietnam's digital economy, while contributions from backward linkages and digital transformation each account for 20–30%. Thirdly, the non-ICT sectors' contribution to the digital economy is quantifiable through three avenues: purchasing digital products and services, supplying the ICT sector, and generating value-added from within-sector digital transformation. Lastly, compared to Thailand, Vietnam lags in key digital economy metrics. Notably, the Thailand/Vietnam ratio for value-added in 2018 was 3.9 for the total digital economy, 3.2 for the ICT sector, 3.1 for contributions from backward linkages, and 6.4 for non-ICT sector digital transformation, while the ratio for GDP stood at 2.1. This insight underscores that while investing in digital infrastructure, promoting internet adoption, and attracting FDI to ICT hardware manufacturing are essential, they alone are insufficient for the rapid progress needed in advancing Vietnam's digital economy
Transformative capabilities of MedTech organizations in driving circularity in the healthcare industry: Insights from multiple cases
No full textThe healthcare industry's significant environmental impact has prompted the urgent need for sustainable practices. MedTech companies play a crucial role in advancing circularity within the sector by adopting sustainable approaches to product design, resource management, and waste reduction. This research aims to explore how MedTech companies initiate and drive transformation towards circular practices and the key factors influencing their successful transition. Using a qualitative approach, four multinational MedTech companies' case studies are conducted, employing semi-structured interviews with 33 managers and healthcare professionals. The results reveal a model grounded in dynamic capabilities, comprising three stages: sensing, seizing, and transforming, guided by adaptability and flexibility. The study extends the understanding of how MedTech companies can proactively respond to environmental challenges and embrace circular economy practices. Furthermore, the model offers practical implications for MedTech companies to foster sustainable practices, optimize resources, and enhance circularity in the healthcare industry
Drosophila expressing mutant human KCNT1 transgenes make an effective tool for targeted drug screening in a whole animal model of KCNT1-epilepsy
No full textMutations in the KCNT1 potassium channel cause severe forms of epilepsy which are poorly controlled
with current treatments. In vitro studies have shown that KCNT1-epilepsy mutations are gain of
function, signifcantly increasing K+
current amplitudes. To investigate if Drosophila can be used
to model human KCNT1 epilepsy, we generated Drosophila melanogaster lines carrying human
KCNT1 with the patient mutation G288S, R398Q or R928C. Expression of each mutant channel in
GABAergic neurons gave a seizure phenotype which responded either positively or negatively to
5 frontline epilepsy drugs most commonly administered to patients with KCNT1-epilepsy, often
with little or no improvement of seizures. Cannabidiol showed the greatest reduction of the seizure
phenotype while some drugs increased the seizure phenotype. Our study shows that Drosophila has
the potential to model human KCNT1- epilepsy and can be used as a tool to assess new treatments for
KCNT1- epilepsy
A new approach to finding overlapping community structure in signed networks based on Neutrosophic theory
No full textOne of the longstanding challenges in network science is the identification of overlapping community structures. Real-world networks often exhibit a complex interplay of positive and negative relationships, making the recognition of overlapping communities a crucial area of research. Current community detection methods in signed networks primarily focus on discovering disjoint communities, where each node belongs exclusively to a single community. However, these algorithms often fail to detect overlapping communities, where nodes can belong to multiple communities simultaneously. To address this limitation, we propose a novel approach called Neutrosophic c-means Overlapping Community Detection (NOCD) based on neutrosophic set (NS) theory. By incorporating NS theory, our approach effectively handles the uncertainty associated with ambiguous community boundaries and appropriately handles nodes on the community boundaries and isolated nodes. The NOCD method comprises two phases: firstly, a signed graph convolutional neural network is employed to learn the structural features of the signed network in a lower-dimensional representation; secondly, overlapping communities are detected using the neutrosophic c-means algorithm applied to the embedded network. To evaluate the effectiveness of our proposed NOCD method, we conducted comprehensive experiments on both real and artificial networks. The experimental results demonstrate the effectiveness and robustness of NOCD in identifying overlapping communities, outperforming existing methods
QoE-aware budgeted edge data caching online: A primal–dual approach
No full textData caching has garnered significant attention in the field of edge computing due to the low-latency services offered by nearby edge servers. To efficiently utilize the data cache budget and ensure minimal data transmission latency, selecting appropriate edge servers for data caching is crucial. While the users’ Quality of Experience (QoE) plays a vital role in the service providers’ benefits, it has not been adequately considered in dynamic edge computing environments. This is primarily due to the non-linear correlation between QoE and Quality-of-Service (QoS), making cost-effective edge data caching challenging within the service provider’s limited budget. In this paper, we formally define the QoE-aware budgeted online edge data caching (QoE-BOEDC) problem, aiming to maximize the average user QoE while adhering to the service provider’s budget in a dynamic edge computing environment. Here, we formulate a formal optimization model for QoE-BOEDC, which can be proven to be NP-complete. Subsequently, we propose an online algorithm, PDOQ (Primal–Dual Optimization for QoE), based on the primal–dual technique, and theoretically establish its comparative ratio. Additionally, we conduct both small-scale and large-scale experimental tests, and the experimental results demonstrate that PDOQ significantly outperforms other representative algorithms
Attachment style and premenstrual symptom severity: the mediating role of maladaptive emotion regulation
No full textObjective: The present study examined the relationship between attachment and premenstrual symptoms, and the mediating role of maladaptive emotion regulation. Method: Attachment orientation, maladaptive emotion regulation, and premenstrual symptom severity were measured using a cross-sectional design among female university students who were naturally cycling (n = 165) or currently using hormonal contraception (HC) (n = 124). Results: Partial correlations, controlling for age, cycle regularity, and general symptoms of psychopathology (depression, anxiety, and stress), revealed positive associations between maladaptive emotion regulation and premenstrual symptoms, and between anxious attachment and maladaptive emotion regulation for both groups of women. Moreover, among women who were naturally cycling, maladaptive emotion regulation positively mediated the relationship between anxious (but not avoidant) attachment and premenstrual symptom severity; anxious attachment was associated with more severe premenstrual symptoms via increased maladaptive emotion regulation. This same mediation pathway was not observed for participants currently using HC. Conclusions: The findings highlight that a negative model of the self, which is characteristic of an anxious attachment style, may be a useful psychotherapeutic target for naturally cycling women who experience premenstrual symptoms. Further research and replication are required to confirm the potential moderating effect of HC and hormonal changes on these relationships