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

Prediction of Ecofriendly Concrete Compressive Strength Using Gradient Boosting Regression Tree Combined with GridSearchCV Hyperparameter-Optimization Techniques

A crucial factor in the efficient design of concrete sustainable buildings is the compressive strength (Cs) of eco-friendly concrete. In this work, a hybrid model of Gradient Boosting Regression Tree (GBRT) with grid search cross-validation (GridSearchCV) optimization technique was used to predict the compressive strength, which allowed us to increase the precision of the prediction models. In addition, to build the proposed models, 164 experiments on eco-friendly concrete compressive strength were gathered for previous researches. The dataset included the water/binder ratio (W/B), curing time (age), the recycled aggregate percentage from the total aggregate in the mixture (RA%), ground granulated blast-furnace slag (GGBFS) material percentage from the total binder used in the mixture (GGBFS%), and superplasticizer (kg). The root mean square error (RMSE) and coefficient of determination (R2) between the observed and forecast strengths were used to evaluate the accuracy of the predictive models. The obtained results indicated that—when compared to the default GBRT model—the GridSearchCV approach can capture more hyperparameters for the GBRT prediction model. Furthermore, the robustness and generalization of the GSC-GBRT model produced notable results, with RMSE and R2 values (for the testing phase) of 2.3214 and 0.9612, respectively. The outcomes proved that the suggested GSC-GBRT model is advantageous. Additionally, the significance and contribution of the input factors that affect the compressive strength were explained using the Shapley additive explanation (SHAP) approach

Development of Prediction Models for the Torsion Capacity of Reinforced Concrete Beams Using M5P and Nonlinear Regression Models

Torsional strength is related with one of the most critical failure types for the design and assessment of reinforced concrete (RC) members due to the complexity of the associated stress state and low ductility. Previous studies have shown that reliable methods to predict the torsional strength of RC beams are still needed, namely for over-reinforced and high-strength RC beams. This research aims to offer a novel set of models to predict the torsional strength of RC beams with a wide range of design attributes and geometries by using advanced M5P tree and nonlinear regression models. For this, a broad database with 202 experimental tests is used to generate highly reliable and resilient models. To build the models, three independent variables related with the properties of the RC beams are considered: concrete cross-section area (area enclosed within the outer perimeter of the cross-section), concrete compressive strength, and torsional reinforcement factor (which accounts for the type—longitudinal or transverse—amount, and yielding strength of the torsional reinforcement). In contrast to multiple nonlinear regression approaches, the findings show that the M5P tree approach has the best estimation in terms of both accuracy and safety. Furthermore, M5P model predictions are far more accurate and safer than the most prevalent design equations. Finally, sensitivity and parametric studies are used to confirm the robustness of the presented models

Mechanism of Haibat Sultan Mountain Landslide in Koya, North Iraq

Haibat Sultan Mountain is a long range with elevation of about 860 m (a.s.l.); the PilaSpi Formation forms its carapace in Koya vicinity, with relief difference of about 300 m from Koisanjaq plain. The PilaSpi Formation consists of well thickly to massively bedded dolostone and dolomitic limestone with thickness of about 120 m in Koya vicinity. The main trend is NW - SE being a limb of Bustana anticline representing part of the southwestern limb, with dip amount that ranges from (15 - 30). On 11th of November 2015 a landslide had occurred after a heavy rainfall along Koya - Dukan main road. The type of the slide was plane sliding due to daylight slope, which was formed afterthe road cut. The length of the slide area: along the road is 90 m with height of 40 m forming almost a parallelogram shape; the thickness of the slid beds is about 2.5 m. The estimated volume of the slid mass is 9000 m3. The main cause of the landslide is the presence of daylight slope, high slope angle; more than the dip angle, presence of old crack surfaces which are filled by reddish brown clayey residual soil. After the he heavy rain fall, which lasted for 20 hours, the infiltrated rain water in the bedding planes in the well bedded, cracked, and jointed beds has increased the pore pressure and decreased the internal friction angle; therefore, the sliding has occurred. The root of the slid mass is below the base of the paved road; therefore, that part which is above the paved road has slid. The remaining part is highly cracked and partly accumulated in the base of the slid mass. Fortunately, the height of the slid mass is only 40 m and the relief difference between the crown area and the toe area is about 50 m; otherwise the slid mass would be larger than the present slid mass. From the field inspection, it is very clear that the involved area is very unstable and in critical equilibrium. The presence of daylight bedding above the crown area, clayey soil in the fractures and open joints and steep slope all are very favorable conditions for triggering the unstable slope, consequently developing of another landslide with larger mass.Validerad; 2016; Nivå 1; 20160825 (nadhir

BJS commission on surgery and perioperative care post-COVID-19

Background: Coronavirus disease 2019 (COVID-19) was declared a pandemic by the WHO on 11 March 2020 and global surgical practice was compromised. This Commission aimed to document and reflect on the changes seen in the surgical environment during the pandemic, by reviewing colleagues experiences and published evidence. Methods: In late 2020, BJS contacted colleagues across the global surgical community and asked them to describe how severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) had affected their practice. In addition to this, the Commission undertook a literature review on the impact of COVID-19 on surgery and perioperative care. A thematic analysis was performed to identify the issues most frequently encountered by the correspondents, as well as the solutions and ideas suggested to address them. Results: BJS received communications for this Commission from leading clinicians and academics across a variety of surgical specialties in every inhabited continent. The responses from all over the world provided insights into multiple facets of surgical practice from a governmental level to individual clinical practice and training. Conclusion: The COVID-19 pandemic has uncovered a variety of problems in healthcare systems, including negative impacts on surgical practice. Global surgical multidisciplinary teams are working collaboratively to address research questions about the future of surgery in the post-COVID-19 era. The COVID-19 pandemic is severely damaging surgical training. The establishment of a multidisciplinary ethics committee should be encouraged at all surgical oncology centres. Innovative leadership and collaboration is vital in the post-COVID-19 era