As the global energy transition takes place, the importance of AI in grid management will grow as it will be increasingly vital to have accurate energy consumption estimates.
. One of the main ways in which AI will support an effective transition away from fossil fuels to greener alternatives is through grid management. AI and machine learning use data analytics to estimate the level of energy consumption across households in any given area. It considers a variety of factors such as time of year, peak and off-peak times, and weather conditions.
When it comes to solar power, AI can be used to determine the best sites to construct solar farms, based on the hours of sunlight and intensity. It can also help operators to plan the layout of the site so that solar systems catch the most sunlight. Once operational, AI technology can be used for automated decision-making to control solar panels as they rotate toward the sunlight throughout the day.
In terms of wind power, Danish renewable energy major Vestas Wind Systems has led the way in the digitalization of wind farms, using machine learning to constantly adapt and improve operations. On-site AI technology learns from the environment in real-time, mainly through trial and error, to create changes to enhance wind energy production.
Espen Mehlum, the head of the energy and materials program on benchmarking at the World Economic Forum, “You can use AI to both optimize the construction, siting and the operations of a wind farm, but more importantly, you can use AI to optimize across different systems, both when it comes to consumption but also production.” He added, “That’s where the huge untapped potential is for AI – we’re just scratching the surface and seeing the first use cases.
The digitalization of the energy sector is well underway, with almost all oil and gas and renewables majors incorporating a wide range of innovative technologies into their operations, for greater efficiency and production stability. AI technologies allow energy companies to predict a range of scenarios, ensure a reliable energy output for consumers, support grid efficiency, and adapt to anticipated and real-time changes to establish optimal conditions for production.
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The rate and assessment of muscle wasting during critical illness: a systematic review and meta-analysis - Critical CareBackground Patients with critical illness can lose more than 15% of muscle mass in one week, and this can have long-term detrimental effects. However, there is currently no synthesis of the data of intensive care unit (ICU) muscle wasting studies, so the true mean rate of muscle loss across all studies is unknown. The aim of this project was therefore to systematically synthetise data on the rate of muscle loss and to identify the methods used to measure muscle size and to synthetise data on the prevalence of ICU-acquired weakness in critically ill patients. Methods We conducted a systematic literature search of MEDLINE, PubMed, AMED, BNI, CINAHL, and EMCARE until January 2022 (International Prospective Register of Systematic Reviews [PROSPERO] registration: CRD420222989540. We included studies with at least 20 adult critically ill patients where the investigators measured a muscle mass-related variable at two time points during the ICU stay. We followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and assessed the study quality using the Newcastle–Ottawa Scale. Results Fifty-two studies that included 3251 patients fulfilled the selection criteria. These studies investigated the rate of muscle wasting in 1773 (55%) patients and assessed ICU-acquired muscle weakness in 1478 (45%) patients. The methods used to assess muscle mass were ultrasound in 85% (n = 28/33) of the studies and computed tomography in the rest 15% (n = 5/33). During the first week of critical illness, patients lost every day −1.75% (95% CI −2.05, −1.45) of their rectus femoris thickness or −2.10% (95% CI −3.17, −1.02) of rectus femoris cross-sectional area. The overall prevalence of ICU-acquired weakness was 48% (95% CI 39%, 56%). Conclusion On average, critically ill patients lose nearly 2% of skeletal muscle per day during the first week of ICU admission.
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Virginia teacher shot by boy, 6, 'showing signs of improvement' but still in critical condition'It is almost impossible to wrap our minds around the fact that a six-year-old brought a loaded handgun to school and shot a teacher; however, this is exactly what our community is grappling with', the mayor of Newport News, Virginiasaid
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Woman in 'critical' condition after being mowed down by Seat Ibiza in PaisleyA 26-year-old woman was rushed to the Queen Elizabeth Hospital after she and a 27-year-old man were struck by the car which was allegedly being driven by a man, aged 20.
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Flight PS752: Families of victims met with harassment from IranCanadian intelligence is probing 'hostile state actors' who are intimidating Iranian dissidents.
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Two Glasgow hospitals close to collapse as 27 ambulances queue outside Royal InfirmaryTop A&E medics have demanded “critical incident status” options for Scotland's crisis-hit hospitals as patients face waits of over 12 hours and being treated in corridors.
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