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An empirical analysis of state-of-art classification models in an IT incident severity prediction framework
Get PDFLarge-scale companies across various sectors maintain substantial IT infrastructure to support their operations and provide quality services for their customers and employees. These IT operations are managed by teams who deal directly with incident reports (i.e., those generated automatically through autonomous systems or human operators). (1) Background: Early identification of major incidents can provide a significant advantage for reducing the disruption to normal business operations, especially for preventing catastrophic disruptions, such as a complete system shutdown. (2) Methods: This study conducted an empirical analysis of eleven (11) state-of-the-art models to predict the severity of these incidents using an industry-led use-case composed of 500,000 records collected over one year. (3) Results: The datasets were generated from three stakeholders (i.e., agency, customer, and employee). Separately, the bidirectional encoder representations from transformers (BERT), the robustly optimized BERT pre-training approach (RoBERTa), the enhanced representation through knowledge integration (ERNIE 2.0), and the extreme gradient boosting (XGBoost) methods performed the best for the agency records (93% AUC), while the convolutional neural network (CNN) was the best model for the rest (employee records at 95% AUC and customer records at 74% AUC, respectively). The average prediction horizon was approximately 150 min, which was significant for real-time deployment. (4) Conclusions: The study provided a comprehensive analysis that supported the deployment of artificial intelligence for IT operations (AIOps), specifically for incident management within large-scale organizations
The future of drug development with quantum computing.
No full textNovel medication development is a time-consuming and expensive multistage procedure. Recent technology developments have lowered timeframes, complexity, and cost dramatically. Current research projects are driven by AI and machine learning computational models. This chapter will introduce quantum computing (QC) to drug development issues and provide an in-depth discussion of how quantum computing may be used to solve various drug discovery problems. We will first discuss the fundamentals of QC, a review of known Hamiltonians, how to apply Hamiltonians to drug discovery challenges, and what the noisy intermediate-scale quantum (NISQ) era methods and their limitations are.We will further discuss how these NISQ era techniques can aid with specific drug discovery challenges, including protein folding, molecular docking, AI-/ML-based optimization, and novel modalities for small molecules and RNA secondary structures. Consequently, we will discuss the latest QC landscape's opportunities and challenges. [Abstract copyright: © 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.
Evaluating private prosecutions: reform or abolition?
Get PDFThis article contributes to the ongoing debate as to the extent to which the right to bring a private prosecution should be reformed by arguing a case for abolition. The issue of private prosecutions has recently been brought to the foreground by a series of Court of Appeal decisions quashing the convictions of 59 sub-postmasters who were convicted in private prosecutions brought by the Post Office. The Criminal Cases Review Commission referred the first group of cases to the Court of Appeal, also triggering a review of the safeguards of private prosecutions by the House of Commons Justice Committee in 2020.
After a brief overview of the historical background and contemporary use of private prosecutions, the second part of this paper will focus on the need for an independent review of the case to protect the rights of the defendant. The third part will argue that private prosecutions conflict with the conceptual basis of the contemporary criminal justice system that criminal prosecutions are brought by the State. Finally, in the fourth part, the case for reform will be considered concluding that private prosecutions in their current form should be abolished
A conceptual approach to transform and enhance academic mentorship: through open educational practices
Get PDFThis paper offers guidance for policymakers and institutions keen on embracing Open Educational Practices within their mentorship strategies, advocating for co-creation and collaboration as foundational principles, to promote a wide range of open practices to foster transparency, inclusivity, creativeness, innovation and collaboration in academic mentorship. This conceptual paper explores the transformative potential of Open Educational Practices in the context of academic mentorship, which is per-se an open practice. We have adopted an integrative approach for our literature review, which is a non-systematic model, to help us to mitigate algorithmic biases presented in scholarly databases, for analysing and discussing literature, alongside the review of case studies to explore the intersection of open practices and mentorship in academia. We aim to highlight the profound impact mentorship has on professional development, knowledge dissemination, and collaborative learning. Drawing on a diverse selection of literature and case studies reflecting mentorship programmes both formally and informally in academic contexts, this paper provides concrete examples from practice of how Open Educational Practices can be seamlessly integrated into formal and informal academic mentorship as a driver to enhance knowledge sharing, foster inclusivity, and bolster the quality of mentorship relationships
Child criminal exploitation and community development in Befordshire
No full textThis report is one of three site reports examining responses to County Line’s criminal exploitation. County Lines is a criminal business model which involves the ‘transportation of illegal drugs, by gangs and organised criminal networks, from one area to another within the UK, using dedicated mobile telephone lines (National Crime Agency, 2017). The decision to select Bedfordshire as a research site was the result of evidence uncovered in our early research that a significant amount of Child Criminal Exploitation (CCE) emanated from within the County and a realisation that the County was both an importer and exporter of illegal drugs via County Lines. Our findings suggest a clear need to formulate responses that do not underplay or overplay safeguarding and criminal justice interventions in and beyond Bedfordshire. The resulting recommendations detailed in this report seek to:
Highlight the proximity of criminal exploitation to local organised crime
Equip policymakers and practitioners to manage the risks arising from County Lines
Identify how more local neighbourhood interventions combined with a County-wide strategic overview might build resilience to gangs and local organised crime groups and effectively disrupt County Lines activities
Multidimensionality within the Edinburgh postnatal depression scale: application issues of specific structure
Get PDFObjective and background
The 10-item Edinburgh Postnatal Depression Scale (EPDS) is a widely-used screening measure for postnatal depression. Factor analysis studies have suggested an embedded sub-scale could be used for screening for anxiety disorders. The current investigation sought to replicate and extend a recent study supporting this assertion.
Methods
A cross-sectional design. EPDS data were collected at up to two years postpartum. Confirmatory factor analysis, correlational and distributional characteristics of the measure were examined. Participants were a large sample (N = 985) of postpartum women in the Czech Republic.
Results
Factor structure findings substantially replicated the models evaluated by Della Vedova et al. (2022). Bifactor models, however, offered a better fit to data. A general factor of depression explained most of the variance in data in most models compared to embedded sub-scales across models.
Conclusion
The model proposed by Della Vedova et al. (2022) offered an excellent fit to data. However, the findings from the bifactor modelling suggest the dominance of a general factor of depression which indicates the potential application of an embedded anxiety sub-scale for screening may be overstated
The concise guide to pharmacology 2023/24: introduction and other protein targets
Get PDFThe Concise Guide to PHARMACOLOGY 2023/24 is the sixth in this series of biennial publications. The Concise Guide provides concise overviews, mostly in tabular format, of the key properties of approximately 1800 drug targets, and about 6000 interactions with about 3900 ligands. There is an emphasis on selective pharmacology (where available), plus links to the open access knowledgebase source of drug targets and their ligands (www.guidetopharmacology.org), which provides more detailed views of target and ligand properties. Although the Concise Guide constitutes almost 500 pages, the material presented is substantially reduced compared to information and links presented on the website. It provides a permanent, citable, point‐in‐time record that will survive database updates. The full contents of this section can be found at http://onlinelibrary.wiley.com/doi/10.1111/bph.16176. In addition to this overview, in which are identified ‘Other protein targets’ which fall outside of the subsequent categorisation, there are six areas of focus: G protein‐coupled receptors, ion channels, nuclear hormone receptors, catalytic receptors, enzymes and transporters. These are presented with nomenclature guidance and summary information on the best available pharmacological tools, alongside key references and suggestions for further reading. The landscape format of the Concise Guide is designed to facilitate comparison of related targets from material contemporary to mid‐2023, and supersedes data presented in the 2021/22, 2019/20, 2017/18, 2015/16 and 2013/14 Concise Guides and previous Guides to Receptors and Channels. It is produced in close conjunction with the Nomenclature and Standards Committee of the International Union of Basic and Clinical Pharmacology (NC‐IUPHAR), therefore, providing official IUPHAR classification and nomenclature for human drug targets, where appropriate
The concise guide to pharmacology 2023/24: nuclear hormone receptors
Get PDFThe Concise Guide to PHARMACOLOGY 2023/24 is the sixth in this series of biennial publications. The Concise Guide provides concise overviews, mostly in tabular format, of the key properties of approximately 1800 drug targets, and nearly 6000 interactions with about 3900 ligands. There is an emphasis on selective pharmacology (where available), plus links to the open access knowledgebase source of drug targets and their ligands (https://www.guidetopharmacology.org/), which provides more detailed views of target and ligand properties. Although the Concise Guide constitutes almost 500 pages, the material presented is substantially reduced compared to information and links presented on the website. It provides a permanent, citable, point‐in‐time record that will survive database updates. The full contents of this section can be found at http://onlinelibrary.wiley.com/doi/10.1111/bph.16179. Nuclear hormone receptors are one of the six major pharmacological targets into which the Guide is divided, with the others being: G protein‐coupled receptors, catalytic receptors, enzymes and transporters. These are presented with nomenclature guidance and summary information on the best available pharmacological tools, alongside key references and suggestions for further reading. The landscape format of the Concise Guide is designed to facilitate comparison of related targets from material contemporary to mid‐2023, and supersedes data presented in the 2021/22, 2019/20, 2017/18, 2015/16 and 2013/14 Concise Guides and previous Guides to Receptors and Channels. It is produced in close conjunction with the Nomenclature and Standards Committee of the International Union of Basic and Clinical Pharmacology (NC‐IUPHAR), therefore, providing official IUPHAR classification and nomenclature for human drug targets, where appropriate
Particulates monitoring: guide for planning and case study
No full textThis document reports on a project undertaken by University of Suffolk for West Suffolk Council within their Local Government Association funded Net Zero Innovation Programme. The project sought to improve the process for including air quality monitoring, specifically particulates, as a planning condition, and was based on a case study of a previous such planning condition. This project has built upon and worked closely with specialist officers from West Suffolk Council and other district councils across Suffolk.
Air pollution is the lead environmental health problem in the UK and EU, impacting human health causing serious illnesses, and also ecosystem damage.
Particulate matter (PM) is the non-gas component in the air, forming physical particles which can be a wide range of chemical materials. It is classified by size, and named by a number representing the largest diameter of the particles (hence PM2.5 is particles with a diameter less than 2.5m). In the UK, approximately 15% of PM is considered to be naturally occurring, around 35% from international migration, and around 50% from UK-based anthropogenic sources. PM can travel long distances in the air over time periods of
weeks or more, so sources may not be close to the measurement location and therefore do not correlate with local traffic volume. UK-based anthropogenic emissions of PM2.5 are understood by DEFRA to include:
• 12.9% road transport including exhaust and non-exhaust (brake, tyre and road wear)
• 27.3% domestic combustion
• 26.0% industrial combustion
• 13.4% industrial processes (construction work can lead to local increases)
• 20.4% from other sources
Planning and development plans influence air quality and take into account impact and designated areas.
UK policy has developed targets including reduction targets as well as objectives not to exceed.
A ten-step guide is presented for inclusion of air quality monitoring as a planning condition:
Step Action
1 Identify concern appropriate for planning or other condition
2 Identify air quality and related parameters to monitor
3 Specify sensor requirements, including calibration.
Identify location, power, and access
4 Identify period of monitoring, including pre-, during and post-development
5 Identify other data to collect
6 Identify other organisations collaborating or contributing
7 Analysis requirements
8 Specify reporting requirements, frequency of intermediate and final reporting
9 Monitor implementation, receipt of reporting and values
10 Assess any additional action required
This is included as a stand-alone two-page guide, with brief explanations of the steps and potential draft planning condition. It is further expanded with details and reasoning within the main body of this report. Incorporating air quality monitoring as a condition of planning applications can support the protection of public health and the environment, and the guide may support the formulation of such a planning condition to request and implement air quality monitoring measures.
The case study also analysed data provided from a sensor installed during previous monitoring condition, incorporating additional data from NO2 diffusion tubes, traffic sensor and road closure periods, and regional DEFRA monitoring. This indicated that DEFRA objectives were met over the monitoring period, and that PM varied closely with regional PM, including elevated measurements during a period of international migration (Saharan dust storm). During closure of the adjacent road, NO2 was observed to decrease but PM did not appear to be similarly affected. Strongest correlations with PM values were observed regionally rather than with traffic volumes, indicating geographical spread from national and international sources. Variation during November considered to be associated with bonfires and fireworks was observed.
It is concluded that incorporation of air quality monitoring as a planning condition where appropriate can be useful and well managed
County lines and the transformation of middle drug markets within a local organised crime context
No full textThe chapter draws upon a critical realist analysis to demonstrate recent changes in the UK Middle Market of Class A drugs and responses to them. The chapter contends that previous definitions of the "middle market" specified from agencies charged with disruption have overly relied upon definitions which best suit the professionals involved to the detriment of young and vulnerable people caught up in what has become known as County lines. The chapter provides a new analysis of this part of the distribution network and discusses criminal exploitation and transitions of some street gangs to local organised crime networks