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Corrigendum to “Utilization of thermal plasma decomposed municipal solid waste bottom ash as partial cement and fine aggregates replacements on cement mortar properties” [Constr. Build. Mater. 464 (2025) 140142]
No full textDepartures from Standard Disk Predictions in Intensive Ground-Based Monitoring of Three AGN
No full textWe present ground-based, multi-band light curves of the AGN Mrk 509, NGC 4151, and NGC 4593 obtained contemporaneously with Swiftmonitoring. We measure cross-correlation lags relative to SwiftUVW2 (1928 Å) and test the standard prediction for disk reprocessing, which assumes a geometrically thin, optically thick accretion disk where continuum interband delays follow the relation τ(λ)∝λ4/3. For Mrk 509 the 273-d Swiftcampaign gives well-defined lags that increase with wavelength as τ(λ)∝λ2.17 ± 0.2, steeper than the thin-disk prediction, and the optical lags are a factor of ∼5 longer than expected for a simple disk-reprocessing model. This “disk-size discrepancy” as well as excess lags in the u and r bands (which include the Balmer continuum and Hα, respectively) suggest a mix of short lags from the disk and longer lags from nebular continuum originating in the broad-line region. The shorter Swiftcampaigns, 69 d on NGC 4151 and 22 d on NGC 4593, yield less well-defined, shorter lags <2 d. The NGC 4593 lags are consistent with τ(λ)∝λ4/3 but with uncertainties too large for a strong test. For NGC 4151 the Swiftlags match τ(λ)∝λ4/3, with a small U-band excess, but the ground-based lags in the r, i, and z bands are significantly shorter than the B and g lags, and also shorter than expected from the thin-disk prediction. The interpretation of this unusual lag spectrum is unclear. Overall these results indicate significant diversity in the τ − λ relation across the optical/UV/NIR, which differs from the more homogeneous behavior seen in the Swiftbands
AI-Driven Continuous Integration: Automating Code Review and Deployment with LLMs
No full textThe integration of a Large Language Models (LLMs) into Continuous Integration (CI) pipelines greatly enhances the efficiency of the software development process. AI-based CI improves code quality by decreasing integration failure rates by 30 % and deployment time by 40 %. These models help in identifying bugs, enforcing coding standards, writing unit tests, and optimizing release management. But AIdriven CI comes with risks of security vulnerabilities, model bias and the need for human supervision. This paper uses case studies, surveys, and interviews to explore the effects of AI on CI/CD pipelines and identifies the pros and cons. The results of this search show that the use of AI in CI improves effectiveness, but it needs better oversight to avoid risks and improve model performance
Examining myside bias on a controversial historical event after engagement in dialogic argumentation: Insights from a think aloud study
Get PDFThe main objective of this exploratory study was to examine students' reasoning – particularly myside bias – on a controversial historical event using rich think aloud data, before and after being engaged in extensive dialogic argumentation on a non-historical topic. Elementary school students engaged in a nine-session argument-based intervention. For 30 students — a subset of the 116 participants who engaged in the intervention and who constitute the focus of this study — myside bias was assessed before and after their engagement in the intervention, using the think-aloud methodology. Students were asked to read two accounts about a recent war in their country—an own-side account from a historian of their ethnic group and an other-side account from a historian of the adversary ethnic group—and to think aloud. The analysis of the think-aloud protocols shows that participants responded differently when reading the own-side account vs. the other-side one. In particular, participants expressed significantly more statements that supported the other-side when reading the other-side's account than when reading their own-side's account. This shows that engaging with the other-side account, as revealed by the think-aloud process, can promote a deeper understanding of the other side. Moreover, they made more evaluative comments post-assessment than pre-assessment. However, their evaluative comments were still in favor of their own position, which shows how resilient myside bias is to change. Overall, our findings suggest that the think-aloud methodology is a valuable tool for identifying (changes in) myside bias and the conditions that facilitate it
Needs and experiences of families after a sudden unexplained death in childhood: a qualitative study
Get PDFBackground: Sudden unexplained death in childhood (SUDC) is a rare and devastating experience for families. In the UK, multi-agency investigation by police, health and social care of sudden, unexpected child deaths is a statutory requirement aiming to identify full causes for deaths. Families should be allocated bereavement keyworkers for support throughout the investigative process which can take several months. Previous research has focused on multi-agency investigation of sudden infant deaths, with little known about parents’ experiences for deaths of older children. Methods: Bereaved parents of children in the UK, aged 1 to 17 years who died from SUDC during 2018–2022, were recruited through SUDC-UK charity and their mailing list and word of mouth. Semi-structured interviews were conducted in 2023. Interview transcripts underwent thematic analysis. Results: Interviews were conducted with parents from 20 families across England, Scotland and Northern Ireland in 2023. Four key themes were identified: the importance of keyworkers, trauma-informed communication, proactivity from professionals and provision of medical screening for families. Keyworkers were valued by parents, but only 12/20 families had keyworkers allocated. Communication and language were important; families were often distressed by unexpected telephone calls particularly relating to post-mortem results. Parents felt they had to be proactive explaining about SUDC to professionals who lacked knowledge of the condition. Parents wanted medical screening to be proactively offered for their families. Conclusions: Every family must receive swift, proactive, knowledgeable communication from professionals, during and beyond the investigation into their child’s sudden unexpected death. This will help them through the process and mitigate the impact of poor communication on their grief. While all parents expressed that they wanted to find out why their child died, they also identified key improvements to the consistency and effectiveness of the investigation process
Sexual corruption: recognising the “abuse of power” in professional sexual misconduct
Get PDFPurpose
This study aims to draw on Bjarnegård et al. (2024) to consider the value of applying a “sexual corruption” framework within criminal justice and internal disciplinary (“administrative justice”) systems, to respond to sexual misconduct by England and Wales/UK public sector professionals.
Design/methodology/approach
The study used a comparative case study design, analysing public documents relating to four purposively selected cases involving sexual misconduct (doctor, police officer, politician and soldier).
Findings
This study’s pilot analysis suggests that abuse of power was central, pervasive and recognised in each of the case studies. The sexual gain and quid pro quo elements of the framework were more ambiguous and harder to evidence. The paper suggests that administrative justice systems may be well placed to adopt an abuse of power/abuse of position approach to sexual corruption so that it establishes a fully perpetrator-focused definition.
Practical implications
Practical implications included: To give voice to forms of behaviour which have been somewhat neglected in the corruption literature to date. Recognise the gravity of sexual corruption behaviour over and above sexual misconduct more generally. Shift focus from the victim to the perpetrators and their abuse of power. Demonstrate how some forms of sexual harassment should be given more weight because of power dynamics.
Originality/value
Definitions of sexual misconduct involving abuse of power often fall between the established remits of “sexual offending” and “corruption” in both criminal and administrative justice systems. The combined term “sexual corruption” provides a novel perspective in understanding how English/UK professions are responding to abuse of power for sexual gain
Engineering hyper-personalization: Software challenges and brand performance in AI-driven digital marketing management: An empirical study
Get PDFIn this empirical study, we delve into engineering hyper-personalization within AI-driven digital marketing management. We focus specifically on the software challenges encountered and their impact on brand performance. AI technologies are truly transforming marketing, offering capabilities like precise customer segmentation, personalized content delivery, and real-time analytics – essential tools for achieving hyper-personalization. While AI holds significant promise for creating highly relevant and effective campaigns, implementing it for hyper-personalization brings distinct software-related challenges. These include navigating data privacy, ensuring algorithmic transparency, and addressing biases. Overcoming these engineering obstacles becomes essential for leveraging AI effectively to enhance customer experiences, optimize campaign results, and ultimately build stronger brand loyalty and visibility. Our study offers insights into these specific challenges and their implications for businesses aiming to maximize brand performance through advanced AI personalization
Enhancing 5G and 6G networks through a dynamic dual-stage machine learning heuristic framework for selecting UEs as UE-VBSs
No full textAdapting mobile networks to the diverse and evolving demands of 5G and forthcoming 6G technologies requires flexible, efficient, and dynamic strategies—especially in ultra-dense environments and infrastructure-limited areas. This paper proposes a robust two-stage Machine Learning (ML) heuristic framework to dynamically select a group of User Equipment (UEs) to act as Virtual Base Stations (UE-VBSs) for network augmentation. In the first stage, Self-Organizing Maps (SOM) are employed to cluster UEs based on their spatial characteristics while preserving topological relationships, achieving a silhouette score of 0.64—a 30% improvement over conventional methods such as
-Means (0.46) and Mean-Shift (0.43). In the second stage, a Random Forest classifier enhanced via the Synthetic Minority Over-sampling Technique (SMOTE) attains an average accuracy of 97% and an F1-Score of 0.88 in identifying eligible devices to become UE-VBSs, outperforming recent frameworks that typically report accuracies ranging between 85% and 92%.
Comparative evaluation results demonstrate that our two-stage ML heuristic framework not only improves clustering accuracy and UE-VBS classification but also consistently outperforms state-of-the-art clustering methods in terms of network sum rate, power consumption, and scalability. Specifically, across all device densities (i.e., 200, 400, 600, 800, and 1000 UEs), our approach achieves the highest sum rate—peaking at nearly 1.8 billion bps (or 1.8 Gbps) at 1000 UEs—thus surpassing methods such as Affinity Propagation and Grid-based Clustering. Furthermore, by intelligently selecting UE-VBSs, the framework significantly reduces power consumption by effectively minimizing redundant transmissions and interference, making it an energy-efficient solution for large-scale 5G networks. Although the complexity of SOM clustering and Random Forest classification introduces higher computational overhead, the resulting improvements in throughput, energy efficiency, and scalability justify this cost, making it a robust and practical solution for real-world deployments. Validated on both synthetic and real-world datasets, our findings underscore the efficacy, scalability, and high impact of employing robust unsupervised and ensemble learning techniques for dynamic network optimization in next-generation architectures, delivering up to a five-fold increase in network sum rate under high-density conditions compared to state-of-the-art approaches like grid-assisted clustering and affinity propagation
The chemical and spatial variations of the bulge’s velocity ellipsoids
Get PDFWe study the velocity ellipsoids in an N-body+SPH simulation of a barred galaxy which forms a bar with a BP bulge. We focus on the 2D kinematics, and quantify the velocity ellipses by the anisotropy, βij, the correlation, ρij, and the vertex deviation, lv. We explore the variations in these quantities based on stellar age within the bulge and compare these results with the Milky Way’s bulge using data from APOGEE DR16 and Gaia DR3. We first explore the variation of the model’s velocity ellipses in galactocentric velocities, vR and vφ, for two bulge populations, a (relatively) young one and an old one. The bar imprints quadrupoles on the distribution of ellipse properties, which are stronger in the young population, as expected from their stronger bar. The quadrupoles are distorted if we use heliocentric velocities vr and vl. We then project these kinematics along the line of sight onto the (l, b)-plane. Along the minor axis βrl changes from positive at low |b| to negative at large |b|, crossing over at lower |b| in the young stars. Consequently the vertex deviation peaks at lower |b| in the young population, but reaches similar peak values in the old. The ρrl is much stronger in the young stars, and traces the bar strength. The APOGEE stars split by the median follow the same trends. Lastly we explore the velocity ellipses across the entire bulge region in (l, b) space, finding good qualitative agreement between the model and observations