Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Investigating Science teachers` technology integration in classrooms

Use of technology in all fields of education have expanded, investigating the level of technology integration in schools becomes increasingly significant because it offers data-driven technology integration for policymakers, school administrators, and educators to make better budgeting decisions, determine educator professional development needs, and ensure effective and efficient use of technology in schools. This study investigated science teachers’ technology integration in classrooms at a private higher secondary school in Karachi. In this study, the SAMR model and TPACK framework were used to evaluate the technology integration. The SAMR model was used to see at what levels teachers are in technology integration, where substitution is the lowest and redefinition is the highest level of technology integration. While The TPACK framework was used to explore the technological, pedagogical, and content knowledge of the teachers. This study employed a qualitative single-embedded case study design. Multiple data were collected through document review (syllabus breakup), observations, and participant interviews. Purposive sampling was used to select six in-service science teachers. Even though this case was chosen for its well-established use of technology, the findings of the study indicated, teachers’ use of technology and knowledge about technology integration was at the basic level. The result of the study showed that most of the science teacher participants were at the substitution level and demonstrated low TPACK knowledge. The study concludes by suggesting that sustainable teacher professional development focusing on technology integration and teacher-sustained commitment to learn and use of technology can enhance teachers\u27 TPACK knowledge and enable them to practice transformative technology integration in classrooms

Investigating science teachers’ technology integration in classrooms: A case study of a private higher secondary school in Karachi, Pakistan

The use of technology in all fields of education has expanded, and investigating the level of technology integration in schools becomes increasingly significant because it offers data-driven technology integration for policymakers, school administrators, and educators to make better budgeting decisions, determine educator professional development needs, and ensure effective and efficient use of technology in schools. This study investigated science teachers’ technology integration in classrooms at a private higher secondary school in Karachi. In this study, the SAMR model and TPACK framework were used to evaluate the technology integration. The SAMR model was used to see at what levels teachers are in technology integration, where substitution is the lowest and redefinition is the highest level of technology integration. The TPACK framework was used to explore the technological, pedagogical, and content knowledge of the teachers. This study employed a qualitative single embedded case study design. Multiple data were collected through document review (syllabus breakup), observations, and participant interviews. Purposive sampling was used to select six in-service science teachers. Even though this case was chosen for its well-established use of technology, the findings of the study indicated that teachers’ use of technology and knowledge about technology integration was at the basic level. The result of the study showed that most of the science teacher participants were at the substitution level and demonstrated low TPACK knowledge. The study concludes by suggesting that sustainable teacher professional development focusing on technology integration and teacher-sustained commitment to learning and use of technology can enhance teachers’ TPACK knowledge and enable them to practice transformative technology integration in classrooms

E-commerce today and tomorrow: A truly generalized and active framework for the definition of electronic

E-commerce can be viewed from different perspectives by different people. Existing e-commerce frameworks consist of rigid and specific fundamental components of e-commerce. E-commerce field is constantly facing new challenges and new situations. To deal with these challenges, an Active E-commerce Framework is being proposed. This framework consists of six important e-commerce components each composed of several instances. The components and instances of the framework are subject to the rule of Component Flexibility (CF) and Instance Flexibility (IF) respectively. The user perspective is considered as the most important and vital component in this model. By using the user perspective component as the guiding ground, different e-commerce definitions can be constructed. This paper aims at providing an e-commerce framework that can cater for different views of e-commerce as well as assist a person in constructing e-commerce definition from his own perspective

Runtime Management of Service Level Agreements through Proactive Resource Provisioning for a Cloud Environment

By leveraging the Internet, cloud computing allows users to have on-demand access to large pools of configurable computing resources. PaaS (Platform as a Service), IaaS (Infrastructure as a Service), and SaaS (Software as a Service) are three basic categories for the services provided by cloud the computing environments. Quality of service (QoS) metrics like reliability, availability, performance, and cost determine which resources and services are available in a cloud computing scenario. Provider and the user-specified performance characteristics, such as, rejection rate, throughput, response time, financial cost, and energy consumption, form the basis for QoS. To fulfil the needs of its customers, cloud computing must ensure that its services are given with the appropriate quality of service QoS. A “A legally enforceable agreement known as a “Service Level Agreement” (SLA) between a service provider and a customer that outlines service objectives, quality of service requirements, and any associated financial penalties for falling short. We, therefore, presented “A Proactive Resource Supply based Run-time Monitoring of SLA in Cloud Computing”, which allows for the proactive management of SLAs during run-time via the provisioning of cloud services and resources. Within the framework of the proposed work, SLAs are negotiated between cloud users and providers at run-time utilizing SLA Manager. Resources are proactively allocated via the Resource Manager to cut down on SLA violations and misdetection costs. As metrics of performance, we looked at the frequency with which SLAs were broken and the money lost due to false positives. We compared the proposed PRP-RM-SLA model’s simulated performance to the popular existing SLA-based allocation strategy SCOOTER. According to simulation data, the suggested PRP-RM-SLA model is 25% more effective than the current work SCOOTER at reducing SLA breaches and the cost of misdetection