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Träfflista för sökning "WFRF:(Ansari Hossein) srt2:(2023)"

Sökning: WFRF:(Ansari Hossein) > (2023)

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  • Emami, Somayeh, et al. (författare)
  • Application of ANFIS, ELM, and ANN models to assess water productivity indicators based on agronomic techniques in the Lake Urmia Basin
  • 2023
  • Ingår i: Applied water science. - : Springer. - 2190-5487 .- 2190-5495. ; 13:2
  • Tidskriftsartikel (refereegranskat)abstract
    • Water productivity (WP) is one of the most important critical indicators in the essential planning of water consumption in the agricultural sector. For this purpose, the WP and economic water productivity (WPe) were estimated using agronomic technologies. The impact of agronomic technologies on WP and WPe was carried out in two parts of field monitoring and modeling using novel intelligent approaches. Extreme learning machine (ELM), adaptive neuro-fuzzy inference system (ANFIS), and artificial neural network (ANN) methods were used to model WP and WPe. A dataset including 200 field data was collected from five treatment and control sections in the Malekan region, located in the southeast of Lake Urmia, Iran, for the crop year 2020–2021. Six different input combinations were introduced to estimate WP and WPe. The models used were evaluated using mean squared error (RMSE), relative mean squared error (RRMSE), and efficiency measures (NSE). Field monitoring results showed that in the treatment fields, with the application of agronomic technologies, the crop yield, WP, and WPe increased by 17.9%, 30.1%, and 19.9%, respectively. The results explained that irrigation water in farms W1, W2, W3, W4, and W5 decreased by 23.9%, 21.3%, 29.5%, 16.5%, and 2.7%, respectively. The modeling results indicated that the ANFIS model with values of RMSE = 0.016, RRMSE = 0.018, and NSE = 0.960 performed better in estimating WP and WPe than ANN and ELM models. The results confirmed that the crop variety, fertilizer, and irrigation plot dimensions are the most critical influencing parameters in improving WP and WPe.
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2.
  • Sartelli, Massimo, et al. (författare)
  • Ten golden rules for optimal antibiotic use in hospital settings: the WARNING call to action
  • 2023
  • Ingår i: WORLD JOURNAL OF EMERGENCY SURGERY. - 1749-7922. ; 18:1
  • Forskningsöversikt (refereegranskat)abstract
    • Antibiotics are recognized widely for their benefits when used appropriately. However, they are often used inappropriately despite the importance of responsible use within good clinical practice. Effective antibiotic treatment is an essential component of universal healthcare, and it is a global responsibility to ensure appropriate use. Currently, pharmaceutical companies have little incentive to develop new antibiotics due to scientific, regulatory, and financial barriers, further emphasizing the importance of appropriate antibiotic use. To address this issue, the Global Alliance for Infections in Surgery established an international multidisciplinary task force of 295 experts from 115 countries with different backgrounds. The task force developed a position statement called WARNING (Worldwide Antimicrobial Resistance National/International Network Group) aimed at raising awareness of antimicrobial resistance and improving antibiotic prescribing practices worldwide. The statement outlined is 10 axioms, or "golden rules," for the appropriate use of antibiotics that all healthcare workers should consistently adhere in clinical practice.
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