Productivity and Thermal Performance Enhancements of Hollow Fiber Water Gap Membrane Distillation Modules Using Helical Fiber Configuration: 3D Computational Fluid Dynamics Modeling

Although hollow fiber water gap membrane distillation (HF-WGMD) units offer certain advantages over other MD desalination systems, they still require enhancements in terms of distillate flux and productivity. Therefore, this work proposes a novel configuration by incorporating the helical turns of HF membranes within the water gap channel of the HF-WGMD modules. A fully coupled 3D CFD model is developed and validated to simulate the multifaceted energy conservations and diffusion mechanisms that are inherent to the transport phenomena in the proposed HF-WGMD module. Single and double helical HF membrane designs with different numbers of turns are compared to the reference modules of single and double straight HF membrane designs under various operational conditions. At a feed temperature of 70 °C, a noteworthy 11.4% enhancement in the distillate flux is observed when employing 20 helical turns, compared to the single straight HF membrane module. Furthermore, the specific productivity revealed a maximum enhancement of 46.2% when using 50 helical turns. The thermal performance of the proposed HF-WGMD module shows higher energy savings of up to 35% in specific thermal energy consumption for a one-stage module. Using three stages of single helical modules can increase the gain output ratio from 0.17 for the single stage to 0.37, which represents an increase of 117.6%. These findings indicate the high potential of the proposed approach in advancing the performance of HF-WGMD systems

Assessing the Efficiency of Remote Sensing and Machine Learning Algorithms to Quantify Wheat Characteristics in the Nile Delta Region of Egypt

Monitoring strategic agricultural crops in terms of crop growth performance, by accurate cost-effective and quick tools is crucially important in site-specific management to avoid crop reductions. The availability of commercial high resolution satellite images with high resolution (spatial and spectral) as well as in situ spectra measurements can help decision takers to have deep insight on crop stress in a certain region. The research attempts to examine remote sensing dataset for forecasting wheat crop (Sakha 61) characteristics including the leaf area index (LAI), plant height (plant-h), above ground biomass (AGB) and Soil Plant Analysis Development (SPAD) value of wheat across non-stress, drought and salinity-induced stress in the Nile Delta region. In this context, the ability of in situ spectroradiometry measurements and QuickBird high resolution images was evaluated in our research. The efficiency of Random Forest (RF) and Artificial Neural Network (ANN), mathematical models was assessed to estimate the four measured wheat characteristics based on vegetation spectral reflectance indices (V-SRIs) extracted from both approaches and their interactions. Field surveys were carried out to collect in situ spectroradiometry measurements concomitant with the acquisition of QuickBird imagery. The results demonstrated that several V-SRIs extracted from in situ spectroradiometry data and the QuickBird image correlated with the LAI, plant-h, AGB, and SPAD value of wheat crop across the study site. The determination coefficient (R2) values of the association between V-SRIs of in situ spectroradiometry data and various determined wheat characteristics varied from 0.26 to 0.85. The ANN-GSIs-3 was found to be the optimum predictive model, demonstrating a greater relationship between the advanced features and LAI. The three features of V-SRIs comprised in this model were strongly significant for the prediction of LAI. The attained results indicated high R2 values of 0.94 and 0.86 for the training and validation phases. The ANN-GSIs-3 model constructed for the determination of chlorophyll in the plant which had higher performance expectations (R2 = 0.96 and 0.92 for training and validation datasets, respectively). In conclusion, the results of our study revealed that high resolution remote sensing images such as QuickBird or similar imagery, and in situ spectroradiometry measurements have the feasibility of providing necessary crop monitoring data across non-stressed and stressed (drought and salinity) conditions when integrating V-SRIs with ANN and RF algorithms

Global economic burden of unmet surgical need for appendicitis

Background There is a substantial gap in provision of adequate surgical care in many low- and middle-income countries. This study aimed to identify the economic burden of unmet surgical need for the common condition of appendicitis. Methods Data on the incidence of appendicitis from 170 countries and two different approaches were used to estimate numbers of patients who do not receive surgery: as a fixed proportion of the total unmet surgical need per country (approach 1); and based on country income status (approach 2). Indirect costs with current levels of access and local quality, and those if quality were at the standards of high-income countries, were estimated. A human capital approach was applied, focusing on the economic burden resulting from premature death and absenteeism. Results Excess mortality was 4185 per 100 000 cases of appendicitis using approach 1 and 3448 per 100 000 using approach 2. The economic burden of continuing current levels of access and local quality was USD 92 492 million using approach 1 and USD 73 141 million using approach 2. The economic burden of not providing surgical care to the standards of high-income countries was USD 95 004 million using approach 1 and USD 75 666 million using approach 2. The largest share of these costs resulted from premature death (97.7 per cent) and lack of access (97.0 per cent) in contrast to lack of quality. Conclusion For a comparatively non-complex emergency condition such as appendicitis, increasing access to care should be prioritized. Although improving quality of care should not be neglected, increasing provision of care at current standards could reduce societal costs substantially.publishedVersio

Burnout among surgeons before and during the SARS-CoV-2 pandemic: an international survey

Background: SARS-CoV-2 pandemic has had many significant impacts within the surgical realm, and surgeons have been obligated to reconsider almost every aspect of daily clinical practice. Methods: This is a cross-sectional study reported in compliance with the CHERRIES guidelines and conducted through an online platform from June 14th to July 15th, 2020. The primary outcome was the burden of burnout during the pandemic indicated by the validated Shirom-Melamed Burnout Measure. Results: Nine hundred fifty-four surgeons completed the survey. The median length of practice was 10 years; 78.2% included were male with a median age of 37 years old, 39.5% were consultants, 68.9% were general surgeons, and 55.7% were affiliated with an academic institution. Overall, there was a significant increase in the mean burnout score during the pandemic; longer years of practice and older age were significantly associated with less burnout. There were significant reductions in the median number of outpatient visits, operated cases, on-call hours, emergency visits, and research work, so, 48.2% of respondents felt that the training resources were insufficient. The majority (81.3%) of respondents reported that their hospitals were included in the management of COVID-19, 66.5% felt their roles had been minimized; 41% were asked to assist in non-surgical medical practices, and 37.6% of respondents were included in COVID-19 management. Conclusions: There was a significant burnout among trainees. Almost all aspects of clinical and research activities were affected with a significant reduction in the volume of research, outpatient clinic visits, surgical procedures, on-call hours, and emergency cases hindering the training. Trial registration: The study was registered on clicaltrials.gov "NCT04433286" on 16/06/2020

Mortality from gastrointestinal congenital anomalies at 264 hospitals in 74 low-income, middle-income, and high-income countries: a multicentre, international, prospective cohort study

Summary Background Congenital anomalies are the fifth leading cause of mortality in children younger than 5 years globally. Many gastrointestinal congenital anomalies are fatal without timely access to neonatal surgical care, but few studies have been done on these conditions in low-income and middle-income countries (LMICs). We compared outcomes of the seven most common gastrointestinal congenital anomalies in low-income, middle-income, and high-income countries globally, and identified factors associated with mortality. Methods We did a multicentre, international prospective cohort study of patients younger than 16 years, presenting to hospital for the first time with oesophageal atresia, congenital diaphragmatic hernia, intestinal atresia, gastroschisis, exomphalos, anorectal malformation, and Hirschsprung’s disease. Recruitment was of consecutive patients for a minimum of 1 month between October, 2018, and April, 2019. We collected data on patient demographics, clinical status, interventions, and outcomes using the REDCap platform. Patients were followed up for 30 days after primary intervention, or 30 days after admission if they did not receive an intervention. The primary outcome was all-cause, in-hospital mortality for all conditions combined and each condition individually, stratified by country income status. We did a complete case analysis. Findings We included 3849 patients with 3975 study conditions (560 with oesophageal atresia, 448 with congenital diaphragmatic hernia, 681 with intestinal atresia, 453 with gastroschisis, 325 with exomphalos, 991 with anorectal malformation, and 517 with Hirschsprung’s disease) from 264 hospitals (89 in high-income countries, 166 in middleincome countries, and nine in low-income countries) in 74 countries. Of the 3849 patients, 2231 (58·0%) were male. Median gestational age at birth was 38 weeks (IQR 36–39) and median bodyweight at presentation was 2·8 kg (2·3–3·3). Mortality among all patients was 37 (39·8%) of 93 in low-income countries, 583 (20·4%) of 2860 in middle-income countries, and 50 (5·6%) of 896 in high-income countries (p<0·0001 between all country income groups). Gastroschisis had the greatest difference in mortality between country income strata (nine [90·0%] of ten in lowincome countries, 97 [31·9%] of 304 in middle-income countries, and two [1·4%] of 139 in high-income countries; p≤0·0001 between all country income groups). Factors significantly associated with higher mortality for all patients combined included country income status (low-income vs high-income countries, risk ratio 2·78 [95% CI 1·88–4·11], p<0·0001; middle-income vs high-income countries, 2·11 [1·59–2·79], p<0·0001), sepsis at presentation (1·20 [1·04–1·40], p=0·016), higher American Society of Anesthesiologists (ASA) score at primary intervention (ASA 4–5 vs ASA 1–2, 1·82 [1·40–2·35], p<0·0001; ASA 3 vs ASA 1–2, 1·58, [1·30–1·92], p<0·0001]), surgical safety checklist not used (1·39 [1·02–1·90], p=0·035), and ventilation or parenteral nutrition unavailable when needed (ventilation 1·96, [1·41–2·71], p=0·0001; parenteral nutrition 1·35, [1·05–1·74], p=0·018). Administration of parenteral nutrition (0·61, [0·47–0·79], p=0·0002) and use of a peripherally inserted central catheter (0·65 [0·50–0·86], p=0·0024) or percutaneous central line (0·69 [0·48–1·00], p=0·049) were associated with lower mortality. Interpretation Unacceptable differences in mortality exist for gastrointestinal congenital anomalies between lowincome, middle-income, and high-income countries. Improving access to quality neonatal surgical care in LMICs will be vital to achieve Sustainable Development Goal 3.2 of ending preventable deaths in neonates and children younger than 5 years by 2030

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

Mortality of emergency abdominal surgery in high-, middle- and low-income countries

Background: Surgical mortality data are collected routinely in high-income countries, yet virtually no low- or middle-income countries have outcome surveillance in place. The aim was prospectively to collect worldwide mortality data following emergency abdominal surgery, comparing findings across countries with a low, middle or high Human Development Index (HDI). Methods: This was a prospective, multicentre, cohort study. Self-selected hospitals performing emergency surgery submitted prespecified data for consecutive patients from at least one 2-week interval during July to December 2014. Postoperative mortality was analysed by hierarchical multivariable logistic regression. Results: Data were obtained for 10 745 patients from 357 centres in 58 countries; 6538 were from high-, 2889 from middle- and 1318 from low-HDI settings. The overall mortality rate was 1⋅6 per cent at 24 h (high 1⋅1 per cent, middle 1⋅9 per cent, low 3⋅4 per cent; P < 0⋅001), increasing to 5⋅4 per cent by 30 days (high 4⋅5 per cent, middle 6⋅0 per cent, low 8⋅6 per cent; P < 0⋅001). Of the 578 patients who died, 404 (69⋅9 per cent) did so between 24 h and 30 days following surgery (high 74⋅2 per cent, middle 68⋅8 per cent, low 60⋅5 per cent). After adjustment, 30-day mortality remained higher in middle-income (odds ratio (OR) 2⋅78, 95 per cent c.i. 1⋅84 to 4⋅20) and low-income (OR 2⋅97, 1⋅84 to 4⋅81) countries. Surgical safety checklist use was less frequent in low- and middle-income countries, but when used was associated with reduced mortality at 30 days. Conclusion: Mortality is three times higher in low- compared with high-HDI countries even when adjusted for prognostic factors. Patient safety factors may have an important role. Registration number: NCT02179112 (http://www.clinicaltrials.gov)

Heat transfer in inclined air rectangular cavities with two localized heat sources

The present work investigates numerically the effects of cavities’ aspect ratio and tilt angle on laminar natural convection of air in inclined rectangular cavities with two localized heat sources. A mathematical model was constructed where the conservation equations governing the mass, momentum and thermal energy together with their boundary conditions were solved. The calculation grid is investigated to determine the best grid spacing, number of iterations, and other parameters which affect the accuracy of the solutions. The numerical method and computer program were tested for pure conduction and convection with full heating (ɛ = 1) to assure validity and accuracy of the numerical method. The investigation used rectangular enclosures with position ratios of the heaters, B1 = 0.25, B2 = 0.75, size ratio, ɛ = 0.25, and covered Rayleigh numbers based on scale length, s/A ranging from 103 to 106. The tilt angle from the horizontal was changed from Φ = 0° to 180°, and the aspect ratio was taken as A = 1, 5, and 10. The results are presented graphically in the form of streamlines and isotherm contour plots. The heat transfer characteristics, and average Nusselt numbers were also presented. A correlation for Nu is also given

Fusion of Feature Selection Methods and Regression Algorithms for Predicting the Canopy Water Content of Rice Based on Hyperspectral Data

Estimation of the canopy water content (CWC) is extremely important for irrigation management decisions. Machine learning and hyperspectral imaging technology have provided a potentially useful tool for precise measurement of plant water content. The tools, however, are hampered by feature selection as well as an advanced model in itself. Therefore, this study aims to propose an efficient prediction model and compare three feature selection methods including vegetation indices (VI), model-based features (MF), and principal component analysis (PCA). The selected features were applied with a back-propagation neural network (BPNN), random forest (RF), and partial least square regression (PLSR) for training the samples with minimal loss on a cross-validation set. The hyperspectral images were collected from rice crops grown under different water stress levels. A total of 128 images were used to evaluate our proposed methods. The results indicated that the integration of PCA and MF methods can provide a more robust feature selection for the proposed prediction model. The three bands of 1467, 1456, and 1106 nm were the supreme variants of CWC forecasting. These features were combined with an optimized BPNN model and significantly improved the foretelling accuracy. The accuracy and correlation coefficient of the advanced BPNN-PCA-MF model are close to 1 with an RMSE of 0.252. Thus, this study positively contributes to plant water content prediction researchers and policymakers so that well in advance and effective steps can be taken for precision irrigation

Using RGB Imaging, Optimized Three-Band Spectral Indices, and a Decision Tree Model to Assess Orange Fruit Quality

Point samples and laboratory testing have historically been used to evaluate fruit quality criteria. Although this method is precise, it is slow, expensive, and destructive, making it unsuitable for large-scale monitoring of these parameters. The main objective of this research was to develop a non-invasive protocol by combining color RGB indices (CIs) and previously published and newly developed three-band spectral reflectance indices (SRIs) with a decision tree (DT) model to evaluate the fruit quality parameters of navel orange. These parameters were brightness (L*), red–green (a*), blue–yellow (b*), chlorophyll meter (Chlm), total soluble solids (TSS), and TSS/acid ratio. The characteristics of fruit quality of navel orange samples were measured at various stages of ripening. The outcomes demonstrated that at various levels of ripening, the fruit quality parameters, RGB imaging indices, and published and newly developed three-band SRIs differed. The newly developed three-band SRIs based on the wavelengths of blue, green, red, red-edge, and NIR are most effective for estimating the six measured parameters in this study. For example, NDI574,592,724, NDI572,584,724, and NDI574,722,590 had the largest R2 value (0.90) with L*, whereas NDI526,664,700 and NDI524,700,664 exhibited the highest R2 value (0.97) with a*. Moreover, integrating CIs and SRIs with the DT model has provided a potentially useful tool for the accurate measurement of the six studied parameters. For instance, the DT-SRIs-CIs-30 model performed better in terms of measuring a* using 30 various indices. The R2 value was 0.98 and RMSE = 1.121 in the cross-validation, while R2 value was 0.964 and RMSE = 2.604 in the test set. Otherwise, based on the fusion of five various indices, the DT-SRIs-CIs-5 model was the most precise for recognizing b* (R2 = 0.957 and 0.929, with RMSE = 1.713 and 3.309 for cross-validation and test set, respectively). Overall, this work proves that integrating the different characteristics of proximal reflectance sensing systems such as color RGB indices and SRIs via the DT model may be considered a reliable instrument for evaluating the quality of different fruits