Improving the voltage quality of Abu Hummus network in Egypt

In this paper the performance of the electrical network of Egypt is studied by considering a small part on the network (Abu Hummus city). The transmission network of Abu Hummus city was created for 66 kV, 11 kV, and 0.4 kV in the digital simulation and electrical network calculation (DIgSILENT power factory software) to study the voltage profiles. The load flow operational analysis was performed to obtain the voltage magnitudes at every bus bar. The voltage magnitudes in 11 kV and 0.4 kV networks were 10% to 15% less than the nominal value due to overloading off the transmission lines and the voltage magnitudes in 66 kV was within permissible limits. By using automatic tap-changing transformer or Static VAR System, the main idea of this paper is to obtain the voltage profiles at every bus bar to improve the voltage quality of the networks, so as to achieve better voltage profiles on the low voltage side without much effect on high voltage side under various operating conditions

Advancements in tetronic acid chemistry. Part 1: Synthesis and reactions

AbstractThe preparation and the properties of the elusive tetronic acid are reviewed, including its synthesis, chemical reactivity and reactions

Future-ai:International consensus guideline for trustworthy and deployable artificial intelligence in healthcare

Despite major advances in artificial intelligence (AI) for medicine and healthcare, the deployment and adoption of AI technologies remain limited in real-world clinical practice. In recent years, concerns have been raised about the technical, clinical, ethical and legal risks associated with medical AI. To increase real world adoption, it is essential that medical AI tools are trusted and accepted by patients, clinicians, health organisations and authorities. This work describes the FUTURE-AI guideline as the first international consensus framework for guiding the development and deployment of trustworthy AI tools in healthcare. The FUTURE-AI consortium was founded in 2021 and currently comprises 118 inter-disciplinary experts from 51 countries representing all continents, including AI scientists, clinicians, ethicists, and social scientists. Over a two-year period, the consortium defined guiding principles and best practices for trustworthy AI through an iterative process comprising an in-depth literature review, a modified Delphi survey, and online consensus meetings. The FUTURE-AI framework was established based on 6 guiding principles for trustworthy AI in healthcare, i.e. Fairness, Universality, Traceability, Usability, Robustness and Explainability. Through consensus, a set of 28 best practices were defined, addressing technical, clinical, legal and socio-ethical dimensions. The recommendations cover the entire lifecycle of medical AI, from design, development and validation to regulation, deployment, and monitoring. FUTURE-AI is a risk-informed, assumption-free guideline which provides a structured approach for constructing medical AI tools that will be trusted, deployed and adopted in real-world practice. Researchers are encouraged to take the recommendations into account in proof-of-concept stages to facilitate future translation towards clinical practice of medical AI

FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare

Despite major advances in artificial intelligence (AI) for medicine and healthcare, the deployment and adoption of AI technologies remain limited in real-world clinical practice. In recent years, concerns have been raised about the technical, clinical, ethical and legal risks associated with medical AI. To increase real world adoption, it is essential that medical AI tools are trusted and accepted by patients, clinicians, health organisations and authorities. This work describes the FUTURE-AI guideline as the first international consensus framework for guiding the development and deployment of trustworthy AI tools in healthcare. The FUTURE-AI consortium was founded in 2021 and currently comprises 118 inter-disciplinary experts from 51 countries representing all continents, including AI scientists, clinicians, ethicists, and social scientists. Over a two-year period, the consortium defined guiding principles and best practices for trustworthy AI through an iterative process comprising an in-depth literature review, a modified Delphi survey, and online consensus meetings. The FUTURE-AI framework was established based on 6 guiding principles for trustworthy AI in healthcare, i.e. Fairness, Universality, Traceability, Usability, Robustness and Explainability. Through consensus, a set of 28 best practices were defined, addressing technical, clinical, legal and socio-ethical dimensions. The recommendations cover the entire lifecycle of medical AI, from design, development and validation to regulation, deployment, and monitoring. FUTURE-AI is a risk-informed, assumption-free guideline which provides a structured approach for constructing medical AI tools that will be trusted, deployed and adopted in real-world practice. Researchers are encouraged to take the recommendations into account in proof-of-concept stages to facilitate future translation towards clinical practice of medical AI

Untapped potential of 2D charge density wave chalcogenides as negative supercapacitor electrode materials

Two-dimensional (2D) materials have opened new avenues for the fabrication of ultrathin, transparent, and flexible functional devices. However, the conventional inorganic graphene analogues are either semiconductors or insulators with low electronic conductivity, hindering their use as supercapacitor electrode materials, which require high conductivity and large surface area. Recently, 2D charge density wave (CDW) materials, such as 2D chalcogenides, have attracted extensive attention as high performance functional nanomaterials in sensors, energy conversion, and spintronic devices. Herein, TaS2 is investigated as a potential CDW material for supercapacitors. The quantum capacitance (CQ) of the different TaS2 polymorphs (1T, 2H, and 3R) was estimated using density functional theory calculations for different numbers of TaS2 layers and alkali-metal ion (Li, Na and K) intercalants. The results demonstrate the potential of 2H- and 3R-polymorphs as efficient negative electrode materials for supercapacitor devices. The intercalation of K and Na ions in 1T-TaS2 led to an increase in the CQ with the intercalation of Li ions resulting in a decrease in the CQ. In contrast, Li ions were found to be the best intercalant for the 2H-TaS2 phase (highest CQ), while K ion intercalation was the best for the 3R-TaS2 phase. Moreover, increasing the number of layers of the1T-TaS2 resulted in the highest CQ. In contrast, CQ increases upon decreasing the number of layers of 2H-TaS2. Both 1T-MoS2 and 2H-TaS2 can be combined to construct a highly performing supercapacitor device as the positive and negative electrodes, respectively

Diagnosis, treatment, and prevention of community-acquired pneumonia in children: an evidence-based clinical practice guideline adapted for the use in Egypt using ‘Adapted ADAPTE’

Abstract Background We recently adapted a guideline for Community-Acquired Pneumonia (CAP) in children to the Egyptian health system. Adaptation of evidence-based clinical practice guidelines to the local healthcare context is a valid alternative to de novo development that can upgrade their application without enforcing a major burden on resources. The objective of this manuscript is to elucidate diagnosis, treatment, and prevention of CAP as well as methods used for the adaptation process to produce the 1st National Guideline for Community-Acquired Pneumonia in children in Egypt using Adapted ADAPTE method. The full process was described extensively with all three phases of set up, adaptation, and finalization. An adaptation group and an external review including clinical content experts and methodologists conducted the process. Results The authors adapted 10 principal categories of recommendations from three source Clinical Practice Guidelines. Recommendations incorporate; common clinical manifestations, indications for hospitalization and intensive care unit admission, indications for laboratory investigations and radiology in diagnosis, choice of empiric antibiotic therapy in the outpatient and hospitalized children with non-complicated CAP and the duration of therapy, the role of influenza antiviral therapy, follow-up anticipated response to therapy, management of non-responding pneumonia, criteria of safe discharge, and prevention of CAP. Many tools were gathered and established to improve implement ability containing two clinical algorithms for management of non-complicated CAP and for non-responding pneumonia in children, pathway for assessment of severity of CAP in primary care facilities, medication tables, simplified Arabic patient information, PowerPoint slide presentation lecture for management of CAP, and online resources. Conclusion The final clinical guideline supports pediatricians and related healthcare workers with evidence-based applicable guidance for managing community-acquired pneumonia in Egypt. This work demonstrated the efficiency of Adapted ADAPTE and highlighted the importance of a cooperative clinical and methodological professional group for adaptation of national guidelines