An automated system for detection, classification and rehabilitation of defects in sewer pipes

The poor status of sewer pipes in North America has been reported by many researchers, revealing the presence of many defects that impact their performance. Inadequate inspection is considered as one of the main causes behind the declining condition of this class of pipes. This could be attributed to high cost of inspection and inadequate funds allocated to this purpose. The high cost is due to the current manual and high labor intensive inspection practice. Sewer rehabilitation methods are numerous and are constantly being developed. One of the rapidly expanding fields in the sewer rehabilitation industry is trenchless technology. Due to the large number of methods associated with this field, selecting the most suitable method manually can be a challenging task. Selection in this environment may also suffer from the limited knowledge and/or experience of the decision-maker. This research presents two developed automated systems: AUTO-DETECT and AUTO-SELECT. AUTO-DETECT detects and classifies defects in sewer pipes automatically. The system utilizes image analysis techniques, artificial intelligence (AI) and Visual Basic programming language for performing its task. A multiple classifier module encompassing a total of fifteen classifiers was developed to counter-check the results generated by the system. A solution strategy was also developed for efficient utilization of the developed specialized classifiers in an effort to improve the system's performance. The automated system was validated using actual data from randomly selected sections of the sewer network of a major Canadian municipality. The system's accuracy was found to range from 80% to 100%. AUTO-SELECT is essentially a multi-attribute decision support system designed to select and rank the most suitable trenchless rehabilitation methods for sewer pipes. The system utilizes two modules: (1) database management system (DBMS) and (2) decision support system (DSS). The developed relational database assists in identifying suitable trenchless rehabilitation techniques that satisfy a total of sixteen factors which account for technical, contractual and cost requirements of projects as well as user specified preferences. In case of having more than one suitable rehabilitation method, a DSS was developed to evaluate and rank them and, accordingly, suggest the most suitable one. A case example has been worked out to demonstrate the use and capabilities of the developed system

Update of the Scientific Opinion on opium alkaloids in poppy seeds

The CONTAM Panel wishes to thank the hearing experts: Pavel Cihlar, Daniel Doerge and Vaclav Lohr for the support provided to this scientific output. The CONTAM Panel acknowledges all European competent institutions and other stakeholders that provided occurrence data on opium alkaloids in food, and supported the data collection for the Comprehensive European Food Consumption Database. Adopted: 22 March 2018 Reproduction of the images listed below is prohibited and permission must be sought directly from the copyright holder:Figure A.1 in Appendix A: © Elsevier.Peer reviewedPublisher PD

Effects of hospital facilities on patient outcomes after cancer surgery: an international, prospective, observational study

Background Early death after cancer surgery is higher in low-income and middle-income countries (LMICs) compared with in high-income countries, yet the impact of facility characteristics on early postoperative outcomes is unknown. The aim of this study was to examine the association between hospital infrastructure, resource availability, and processes on early outcomes after cancer surgery worldwide.Methods A multimethods analysis was performed as part of the GlobalSurg 3 study-a multicentre, international, prospective cohort study of patients who had surgery for breast, colorectal, or gastric cancer. The primary outcomes were 30-day mortality and 30-day major complication rates. Potentially beneficial hospital facilities were identified by variable selection to select those associated with 30-day mortality. Adjusted outcomes were determined using generalised estimating equations to account for patient characteristics and country-income group, with population stratification by hospital.Findings Between April 1, 2018, and April 23, 2019, facility-level data were collected for 9685 patients across 238 hospitals in 66 countries (91 hospitals in 20 high-income countries; 57 hospitals in 19 upper-middle-income countries; and 90 hospitals in 27 low-income to lower-middle-income countries). The availability of five hospital facilities was inversely associated with mortality: ultrasound, CT scanner, critical care unit, opioid analgesia, and oncologist. After adjustment for case-mix and country income group, hospitals with three or fewer of these facilities (62 hospitals, 1294 patients) had higher mortality compared with those with four or five (adjusted odds ratio [OR] 3.85 [95% CI 2.58-5.75]; p<0.0001), with excess mortality predominantly explained by a limited capacity to rescue following the development of major complications (63.0% vs 82.7%; OR 0.35 [0.23-0.53]; p<0.0001). Across LMICs, improvements in hospital facilities would prevent one to three deaths for every 100 patients undergoing surgery for cancer.Interpretation Hospitals with higher levels of infrastructure and resources have better outcomes after cancer surgery, independent of country income. Without urgent strengthening of hospital infrastructure and resources, the reductions in cancer-associated mortality associated with improved access will not be realised

Automated detection of surface defects in water and sewer pipes

Automation is gaining momentum in industry, particularly in rehabilitation and inspection works of underground infrastructure facilities. This paper describes a model for automating inspection and identification of surface defects in underground water and sewer pipes. The paper describes the current efforts in identification of surface defects in underground water and sewer mains, and presents an automated system designed to assist infrastructure engineers in diagnosing defects in this class of pipe networks. It describes the general architecture of the system and its basic components, and focuses primarily on four modules designed for automating image acquisition, image processing, features extraction and classification of defects.

Serum Neutrophil Gelatinase-Associated Lipocalin (NGAL) in HCV-Positive Egyptian Patients Treated with Sofosbuvir

Background. Direct-acting antivirals (DAAs) made a drastic change in the management of HCV infection. Sofosbuvir is one of the highly potent DAAs, eliminated mainly through the kidney. But concerns about renal safety during treatment may limit its use. Neutrophil gelatinase-associated lipocalin (NGAL) has been proven as a predictor of renal tubular injury. Hence, the aim of this work was to assess serum neutrophil gelatinase-associated lipocalin (NGAL) in HCV-positive patients before and after treatment with the sofosbuvir-based antiviral regimen. Methods. This prospective study included 87 Egyptian patients with chronic HCV infection treated with sofosbuvir plus daclatasvir with or without ribavirin for 12 weeks. Serum NGAL was measured before and at the end of treatment (EOT). Analysis of NGAL and estimated glomerular filtration rate (eGFR) evolution was done. Results. Our results showed a statistically significant decrease in serum NGAL (P=0.02) with a nonsignificant reduction in eGFR (P=0.06). Moreover, changes in serum NGAL levels (baseline compared to EOT) in patients ranked by KDIGO-CKD classification showed a significant decrease in stages 1 and 2 (P=0.14 and 0.034, respectively) and a nonsignificant decrease in stage 3 (P=0.25). Also, eGFR changes after treatment in patients ranked by the same classifications showed a nonsignificant reduction in all stages (P>0.05). Conclusions. Sofosbuvir appears to have no nephrotoxic effects and is safe to treat patients with chronic HCV infection

Factors Affecting Hospitalization Length and in-Hospital Death Due to COVID-19 Infection in Saudi Arabia: A Single-Center Retrospective Analysis

Omar A Al Omair,1 Abdallah Essa,2,3 Khaled Elzorkany,4,5 Somaia Shehab-Eldeen,2,3 Hamzah M Alarfaj,6 Sumaia M Alarfaj,7 Fatimah Alabdulqader,7 Alghaydaa Aldoughan,7 Mohammed Agha,8 Sayed I Ali,9 Ehab Darwish3,10 1Internal Medicine Department, College of Medicine, King Faisal University, Al-Ahsa, Kingdom of Saudi Arabia; 2Tropical Medicine Department, Faculty of Medicine, Menoufia University, Shebin Elkom, Egypt; 3Gastroenterology and Infectious Diseases Unit, College of Medicine, King Faisal University, Al-Ahsa, Kingdom of Saudi Arabia; 4Internal Medicine Department, Faculty of Medicine, Menoufia University, Shebin Elkom, Egypt; 5Nephrology Unit, College of Medicine, King Faisal University, Al-Ahsa, Kingdom of Saudi Arabia; 6King Faisal Specialist Hospital and Research Center, Riyadh, Kingdom of Saudi Arabia; 7Medical Student at the College of Medicine, King Faisal University, Al-Ahsa, Kingdom of Saudi Arabia; 8Chest Department, Faculty of Medicine, Menoufia University, Shebin Elkom, Egypt; 9Family Medicine Department, College of Medicine, King Faisal University, Al-Ahsa, Kingdom of Saudi Arabia; 10Tropical Medicine Department, Faculty of Medicine, Zagazig University, Zagazig, EgyptCorrespondence: Somaia Shehab-Eldeen, Tropical Medicine Department, Faculty of Medicine, Menoufia University, Shebin Elkom, 32511, Egypt, Tel +201117251523, Email [email protected]: The emerging COVID-19 coronavirus disease has widely spread, causing a serious worldwide pandemic. Disease severity and mortality risk can be predicted using an analysis of COVID-19 clinical characteristics. Finding out what influences patients’ hospitalization length and in-hospital mortality is crucial for decision-making and planning for emergencies. The goal of this study is to identify the factors that influence hospital stay length and in-hospital death due to COVID-19 infection.Methods: This cross-sectional study was conducted from August to October 2020 and included 630 patients with a confirmed diagnosis of COVID-19 infection. Using odds ratios (OR) and 95% confidence intervals (CI), a multivariable logistic regression model was used to assess the variables that are linked to longer hospital stays and in-hospital deaths.Results: Most patients were male (64.3%), and most were older than 40 years (81.4%). The mean length of hospital stay (LoHS) was 10.4± 11.6 days. The overall death rate among these COVID-19 cases was 14.3%. Non-survivors were older, had more comorbidities, had prolonged LoHS with increased ICU admission rates and mechanical ventilation usage, and had a more severe condition than survivors. ICU admission, low serum albumin, and elevated LDH levels were associated with longer LoHS, while ICU admission, DM, and respiratory diseases as comorbidities, total leukocytic count, and serum albumin were predictors of mortality.Conclusion: Longer LoHS due to COVID-19 infection was linked to ICU admission, low serum albumin, and elevated LDH levels, while the independent predictors of in-hospital death were ICU admission, DM, and respiratory diseases as comorbidities, total leukocytic count, and serum albumin.Keywords: COVID-19, Saudi Arabia, hospital stay, Al-Ahs

DataSheet_1_Foliar spray of silica improved water stress tolerance in rice (Oryza sativa L.) cultivars.pdf

Rice (Oryza sativa L.) is a major cereal crop and a staple food across the world, mainly in developing countries. Drought is one of the most important limiting factors for rice production, which negatively affects food security worldwide. Silica enhances antioxidant activity and reduces oxidative damage in plants. The current study evaluated the efficiency of foliar spray of silica in alleviating water stress of three rice cultivars (Giza178, Sakha102, and Sakha107). The seedlings of the three cultivars were foliar sprayed with 200 or 400 mg l-1 silica under well-watered [80% water holding capacity (WHC)] and drought-stressed (40% WHC)] conditions for two summer seasons of 2019 and 2020. The obtained results demonstrated that drought stress caused significant decreases in growth, yield, and physiological parameters but increases in biochemical parameters (except proline) of leaves in all rice cultivars compared to well-irrigated plants (control). The roots of drought-stressed seedlings exhibited smaller diameters, fewer numbers, and narrower areas of xylem vessels compared to those well-watered. Regardless of its concentration, the application of silica was found to increase the contents of photosynthetic pigments and proline. Water relation also increased in seedlings of the three tested rice cultivars that were treated with silica in comparison to their corresponding control cultivars when no silica was sprayed. Foliar application of 400 mg l-1 silica improved the physiological and biochemical parameters and plant growth. Overall, foliar application of silica proved to be beneficial for mitigating drought stress in the tested rice cultivars, among which Giza178 was the most drought-tolerant cultivar. The integration of silica in breeding programs is recommended to improve the quality of yield and to provide drought-tolerant rice cultivars under drought-stress conditions.</p