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Digital literacy in contemporary mental healthcare: electronic patient records, outcome measurements and social media
No full textDigital psychiatry has become increasingly important and understanding of certain aspects is essential for practising clinicians. This article discusses electronic patient records (EPRs), from their origins to current and future use, the growth and embedding of outcome measurements, the use of social media, and learning and research in virtual arenas
Ethical Implications of WannaCry: A Cybersecurity Dilemma
No full textThe WannaCry ransomware attack that happened in May 2017 represented a turning point for the modern cybersecurity landscape and, at the same time, spawned many lines of ethical debate related to discovering, using, and disclosing software vulnerabilities. This paper discusses ethical lessons from the WannaCry attack; it explores what this might mean for the respective roles and responsibilities of governments, technology companies, and cybersecurity professionals in managing zero-day vulnerabilities. It contemplates the broader implications for society as a whole of such decisions, and tensions between interests of national security and those of global cybersecurity. Ethical frameworks guiding future cybersecurity practices are proposed in the conclusio
Identification and responses by nurses to sexual exploitation of young people
No full textNurses are uniquely positioned to identify and respond to the sexual exploitation of young people. They treat sexually transmitted infections, unplanned pregnancies, and mental health issues, often collaborating with social services and law enforcement to safeguard young people.
This narrative review explores the pivotal role of nurses in identifying and responding to sexual exploitation among young people.
Empirical evidence from 1997 to 2021 was examined through a comprehensive search of databases such as CINAHL-EBSCO, ASSIA, PubMed (including Medline), and manual screening of abstracts. The PRISMA guideline was applied. Thematic analysis of 12 selected studies revealed three overarching themes.
The themes identified were the influence of technology on the sexual exploitation of young people, identification and response to sexual exploitation in both clinical and non-clinical settings, and organisational support.
These findings shed light on sexual exploitation and underscore the significance of a person-centred approach to nursing care that addresses the health and social impacts of sexual exploitation. It emphasises the importance of interagency collaboration and appropriate clinical interventions to effectively support young people at risk. Increased professional development, support, and supervision for nurses are relevant to identifying, responding to, and preventing the sexual exploitation of young people
Configuring international entrepreneurial orientation and dynamic internationalization capability to predict international performance
No full textIn recent years, the dynamics of international business have changed. This has largely been attributed to uncertainties caused by the COVID-19 pandemic and global trends towards individualistic behaviours. To remain competitive, international entrepreneurial firms (IEFs) renew their behaviours and reconfigure their capabilities. However, scholars have hitherto not uncovered the configurational interplay connecting behaviours and capabilities between the pre-and-post-COVID periods. Drawing on the configurational perspective of dynamic capability theory, we explored the configurational specificities of dynamic internationalisation capability and an international entrepreneurial orientation (IEO) as the behavioural aspect of IEFs. Adopting a longitudinal approach, we applied fsQCA to data drawn from Malaysia. Results show that whereas, in the pre-COVID period, IEFs exhibited an IEO along with threshold and disruption capabilities, in the wake of the pandemic, they are gingerly manifesting an IEO with an overwhelming priority on value-adding and consolidation capabilities suited to weather crises and secure international performance.•COVID-19 has caused a behavioural shift among international entrepreneurial firms (IEFs), particularly in manifesting international entrepreneurial orientation (IEO).•IEFs to shift focus from threshold and disruption capabilities to value-adding and consolidation capabilities to enhance international performance in the post-COVID period.•The effectiveness of dynamic internationalisation capabilities hinges on the alignment with firms' orientation, especially IEO configurations for IEFs
Performance of machine learning versus the national early warning score for predicting patient deterioration risk: a single-site study of emergency admissions
No full textObjectives Increasing operational pressures on emergency departments (ED) make it imperative to quickly and accurately identify patients requiring urgent clinical intervention. The widespread adoption of electronic health records (EHR) makes rich feature patient data sets more readily available. These large data stores lend themselves to use in modern machine learning (ML) models. This paper investigates the use of transformer-based models to identify critical deterioration in unplanned ED admissions, using free-text fields, such as triage notes, and tabular data, including early warning scores (EWS).Design A retrospective ML study.Setting A large ED in a UK university teaching hospital.Methods We extracted rich feature sets of routine clinical data from the EHR and systematically measured the performance of tree- and transformer-based models for predicting patient mortality or admission to critical care within 24 hours of presentation to ED. We compared our proposed models to the National EWS (NEWS).Results Models were trained on 174 393 admission records. We found that models including free-text triage notes outperform structured tabular data models, achieving an average precision of 0.92, compared with 0.75 for tree-based models and 0.12 for NEWS.Conclusions Our findings suggests that machine learning models using free-text data have the potential to improve clinical decision-making in the ED; our techniques significantly reduce alert rate while detecting most high-risk patients missed by NEWS
Conv1D-LSTM Autonomous Breast Cancer Detection Using a One-Dimensional Convolutional Neural Network With Long Short-Term Memory
No full textBreast cancer is an increasingly serious problem in contemporary society, with millions of women and men worldwide affected by the disease. While traditional cancer detection strategies are at times effective, they typically require costly and time-intensive methods for implementation. The major drawback of using conventional methods for identifying breast cancer using the available data sets is that a single algorithm is not sufficient for accurate breast cancer diagnosis due to the heterogeneity of tumors, diverse data types, pattern complexity, feature engineering and dataset overfitting. The aim is to surpass the constraints of the conventional models and develop a hybrid model. The idea is to attain higher accuracy and lower computational time than existing models. This paper introduces a new method for detecting breast cancer using a one-dimensional convolutional neural network (1D CNN) and long short-term memory (LSTM). The model combines the strengths of both approaches, extracting sequential features from local data and modeling temporal dependencies and relationships. To detect and classify breast cancer, the 1D CNN and LSTM are used to automatically extract and analyze features from distinguishing features from a real dataset generated from mammography reports. The developed model has been assessed on on the extracted feature of the primary available dataset consisting of mammograms from over 760 patients. The developed model achieves 99% accuracy on the test data, demonstrating its potential to provide an automated approach to breast cancer detection. The work emphasizes a significant improvement in feature extraction, accuracy, and robustness. Additionally, the proposed model's versatility allows it to handle diverse data types, achieve better generalization and lower computational time. The model offers a high level of interpretability, which is crucial for medical professionals to understand and trust the decision-making process of the system. The developed hybrid model outperforms various other state-of-the-art techniques like ANN, CNN, CNN-Bi-LSTM-GRU-AM (Convolutional Neural Network-Bidirectional Long Short-Term Memory-Gated Recurrent Unit-Attention Mechanism), and CNN-GRU (Convolutional Neural Network- Gated Recurrent Unit) in terms of accuracy, feature extraction and computational time. This work emphasises the potential of 1D CNN augmented with LSTM to create an automated system for identifying breast cancer. Hence, provides a promising foundation for further development and practical usage of deep learning for automated cancer diagnosis
The management of coma
No full textComa is a medical emergency that can challenge the diagnostic and management skills of any clinician. A systematic and logical approach is necessary to make the correct diagnosis, the broad diagnostic categories being neurological, metabolic, diffuse physiological dysfunction and functional. Even when the diagnosis is not immediately clear, appropriate measures to resuscitate, stabilize and support a comatose patient must be rapidly performed. The key components in the assessment and management of a patient, namely history, examination, investigation and treatment, are performed in parallel, not sequentially. Unless the cause of coma is immediately obvious and reversible, help from senior and critical care colleagues is necessary. In particular, senior help is needed to make difficult management decisions in patients with a poor prognosis
RETRACTION : SVM ‐based Generative Adverserial Networks for Federated Learning and Edge Computing Attack Model and Outpoising
No full textRETRACTION : P. Manoharan , R. Walia , C. Iwendi , T. A. Ahanger , S. T. Suganthi , M. M. Kamruzzaman , S. Bourouis , W. Alhakami and M. Hamdi , “,” Expert Systems 40 , no. ( 2023 ): , https://doi.org/10.1111/exsy.13072 .The above article, published online on 09 August 2022 in Wiley Online Library ( wileyonlinelibrary.com ), has been retracted by agreement between the journal Editor‐in‐Chief, David Camacho; and John Wiley & Sons Ltd. The article was submitted as part of a guest‐edited special issue. Following publication, it has come to the attention of the journal that the experimental methods in this manuscript are insufficiently described. Accordingly, the results cannot be reproduced and the research is not comprehensible for readers. The editors have therefore decided to retract this article. The authors disagree with the retraction
Effective photo-electrochemical production of H2O2 and green Fenton reaction on hierarchical Fe/C/N @ ZIF-8 @ACF for abatement of antibiotics in water
No full textHeterogeneous photo-electro-Fenton (HPEF) reaction is a highly efficient process using H2O2 produced by in-situ two electron oxygen reduction reaction (2e ORR) after aerating for the elimination of refractory organic pollutants. Herein, an effective MOFs derived Fe/C/N @ ZIF-8 @ACF composite electrode for HPEF was prepared by loading Fe/C/N derived from Fe-based metal-organic frameworks (Fe-MOFs) and zeolitic imidazolate framework-8 (ZIF-8) on activated carbon felt (ACF). By supplying air, solar light, and low external electric current (32 mA·cm−2) to the cathode, ZIF-8 could generate H2O2 by 2e- ORR process, and Fe/C/N could react with H2O2 to form strong oxidative radicals (·OH). Photocatalysis accelerates the Fenton reaction greatly with the abundant photo-generated electrons. The HPEF activity of different systems for the degradation of antibiotics was compared. The results showed that the degradation rate of antibiotics can be greatly increased with the best of ∼100% within 100 min. Moreover, the electrode could still maintain a high activity after reuse for 4 times, which proved to be highly active, stable, and well recyclable for a rapid HPEF oxidation for abatement of antibiotic pollutants in water.
•A novel Fe/C/N @ ZIF-8 @ACF composite electrode has been prepared by hydrothermal synthesis.•H2O2 can be produced in-situ through the ORR catalysis of ZIF-8 then to be catalytic decomposed into·OH by Fe/C/N.•The Fe/C/N @ ZIF-8 @ACF showed enhanced adsorption and photoelectro-Fenton performance.•It provides a new method for the field of water treatment to treat waste water with fast, green and economic methods
Introduction to Contextualising African Studies: Challenges and the way forward
No full textThe study of Africa is inundated with inherent complexity. It has provoked a couple of questions. For example, how can we contextualise African studies, what are the best approaches to studying Africa, what are the challenges, and what does the future hold? Such questions remain prevalent and there is a clarion call to address them.In the first book of the New Frontiers of African Business and Society Series titled African Context of Business and Society (Omeihe & Harrison, 2022a), we took stock of scholarly capital researched across the continent and focused on Business and Society. In this book, Contextualising African Studies: Challenges and the Way Forward, we go further to examine Africa in more detail and its challenges. Africa represents the youngest and fastest-growing population in the world. Its unparalleled eco-diversity and culture have made it a vital region with one of the fastest-growing economies across the globe. However, research within and about Africa is still limited compared to other continents. The preferable stance for scholars is to apply frameworks originating from the West which arguably may be ineffective within the African context. As a result, it is pertinent that more research in and about Africa is conducted to learn lessons rather than apply them. Through this book, we draw on empirical and conceptual evidence within Africa providing recommendations and ways forward, especially during such times of global uncertainty. The prevalent issues affecting the continent from the perspective of renowned authors in African research are discussed