| 1. |
- Ademuyiwa, Adesoji O., et al.
(författare)
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Determinants of morbidity and mortality following emergency abdominal surgery in children in low-income and middle-income countries
- 2016
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Ingår i: BMJ Global Health. - : BMJ Publishing Group Ltd. - 2059-7908. ; 1:4
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Tidskriftsartikel (refereegranskat)abstract
- Background: Child health is a key priority on the global health agenda, yet the provision of essential and emergency surgery in children is patchy in resource-poor regions. This study was aimed to determine the mortality risk for emergency abdominal paediatric surgery in low-income countries globally.Methods: Multicentre, international, prospective, cohort study. Self-selected surgical units performing emergency abdominal surgery submitted prespecified data for consecutive children aged <16 years during a 2-week period between July and December 2014. The United Nation's Human Development Index (HDI) was used to stratify countries. The main outcome measure was 30-day postoperative mortality, analysed by multilevel logistic regression.Results: This study included 1409 patients from 253 centres in 43 countries; 282 children were under 2 years of age. Among them, 265 (18.8%) were from low-HDI, 450 (31.9%) from middle-HDI and 694 (49.3%) from high-HDI countries. The most common operations performed were appendectomy, small bowel resection, pyloromyotomy and correction of intussusception. After adjustment for patient and hospital risk factors, child mortality at 30 days was significantly higher in low-HDI (adjusted OR 7.14 (95% CI 2.52 to 20.23), p<0.001) and middle-HDI (4.42 (1.44 to 13.56), p=0.009) countries compared with high-HDI countries, translating to 40 excess deaths per 1000 procedures performed.Conclusions: Adjusted mortality in children following emergency abdominal surgery may be as high as 7 times greater in low-HDI and middle-HDI countries compared with high-HDI countries. Effective provision of emergency essential surgery should be a key priority for global child health agendas.
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| 2. |
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| 3. |
- Thomas, HS, et al.
(författare)
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- 2019
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swepub:Mat__t
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| 4. |
- Alvarez, E. M., et al.
(författare)
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The global burden of adolescent and young adult cancer in 2019: a systematic analysis for the Global Burden of Disease Study 2019
- 2022
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Ingår i: Lancet Oncology. - : Elsevier BV. - 1470-2045. ; 23:1, s. 27-52
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Tidskriftsartikel (refereegranskat)abstract
- Background In estimating the global burden of cancer, adolescents and young adults with cancer are often overlooked, despite being a distinct subgroup with unique epidemiology, clinical care needs, and societal impact. Comprehensive estimates of the global cancer burden in adolescents and young adults (aged 15-39 years) are lacking. To address this gap, we analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, with a focus on the outcome of disability-adjusted life-years (DALYs), to inform global cancer control measures in adolescents and young adults. Methods Using the GBD 2019 methodology, international mortality data were collected from vital registration systems, verbal autopsies, and population-based cancer registry inputs modelled with mortality-to-incidence ratios (MIRs). Incidence was computed with mortality estimates and corresponding MIRs. Prevalence estimates were calculated using modelled survival and multiplied by disability weights to obtain years lived with disability (YLDs). Years of life lost (YLLs) were calculated as age-specific cancer deaths multiplied by the standard life expectancy at the age of death. The main outcome was DALYs (the sum of YLLs and YLDs). Estimates were presented globally and by Socio-demographic Index (SDI) quintiles (countries ranked and divided into five equal SDI groups), and all estimates were presented with corresponding 95% uncertainty intervals (UIs). For this analysis, we used the age range of 15-39 years to define adolescents and young adults. Findings There were 1.19 million (95% UI 1.11-1.28) incident cancer cases and 396 000 (370 000-425 000) deaths due to cancer among people aged 15-39 years worldwide in 2019. The highest age-standardised incidence rates occurred in high SDI (59.6 [54.5-65.7] per 100 000 person-years) and high-middle SDI countries (53.2 [48.8-57.9] per 100 000 person-years), while the highest age-standardised mortality rates were in low-middle SDI (14.2 [12.9-15.6] per 100 000 person-years) and middle SDI (13.6 [12.6-14.8] per 100 000 person-years) countries. In 2019, adolescent and young adult cancers contributed 23.5 million (21.9-25.2) DALYs to the global burden of disease, of which 2.7% (1.9-3.6) came from YLDs and 97.3% (96.4-98.1) from YLLs. Cancer was the fourth leading cause of death and tenth leading cause of DALYs in adolescents and young adults globally. Interpretation Adolescent and young adult cancers contributed substantially to the overall adolescent and young adult disease burden globally in 2019. These results provide new insights into the distribution and magnitude of the adolescent and young adult cancer burden around the world. With notable differences observed across SDI settings, these estimates can inform global and country-level cancer control efforts. Copyright (C) 2021 The Author(s). Published by Elsevier Ltd.
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| 5. |
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| 6. |
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| 7. |
- Tao, Hai, et al.
(författare)
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Energy and cost management of different mixing ratios and morphologies on mono and hybrid nanofluids in collector technologies
- 2023
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Ingår i: Engineering Applications of Computational Fluid Mechanics. - : Taylor & Francis. - 1994-2060 .- 1997-003X. ; 17:1
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Tidskriftsartikel (refereegranskat)abstract
- The flat-plate solar collector (FPSC) three-dimensional (3D) model was used to numerically evaluate the energy and economic estimates. A laminar flow with 500 ≤ Re ≤ 1900, an inlet temperature of 293 K, and a solar flux of 1000 W/m2 were assumed the operating conditions. Two mono nanofluids, CuO-DW and Cu-DW, were tested with different shapes (Spherical, Cylindrical, Platelets, and Blades) and different volume fractions. Additionally, hybrid nanocomposites from CuO@Cu/DW with different shapes (Spherical, Cylindrical, Platelets and Blades), different mixing ratios (60% + 40%, 50% + 50% and 40% + 60%) and different volume fractions (1 volume%, 2 volume%, 3 volume% and 4 volume%) were compared with mono nanofluids. At 1 volume% and Re = 1900, CuO-Platelets demonstrated the highest pressure drop (33.312 Pa). CuO-Platelets achieved the higher thermal enhancement with (8.761%) at 1 vol.% and Re = 1900. CuO-Platelets reduced the size of the solar collector by 25.60%. Meanwhile, CuO@Cu-Spherical (40:60) needed a larger collector size with 16.69% at 4 vol.% and Re = 1900. CuO-Platelets with 967.61, CuO – Cylindrical with 976.76, Cu Platelets with 983.84, and Cu-Cylindrical with 992.92 presented the lowest total cost. Meanwhile, the total cost of CuO – Cu – Platelets with 60:40, 50:50, and 40:60 was 994.82, 996.18, and 997.70, respectively.
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| 8. |
- Bravo, L, et al.
(författare)
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- 2021
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swepub:Mat__t
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| 9. |
- Tabiri, S, et al.
(författare)
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- 2021
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swepub:Mat__t
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| 10. |
- Alawsi, Mustafa A., et al.
(författare)
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Tuning ANN Hyperparameters by CPSOCGSA, MPA, and SMA for Short-Term SPI Drought Forecasting
- 2022
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Ingår i: Atmosphere. - : MDPI. - 2073-4433. ; 13:19
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Tidskriftsartikel (refereegranskat)abstract
- Modelling drought is vital to water resources management, particularly in arid areas, to reduce its effects. Drought severity and frequency are significantly influenced by climate change. In this study, a novel hybrid methodology was built, data preprocessing and artificial neural network (ANN) combined with the constriction coefficient-based particle swarm optimisation and chaotic gravitational search algorithm (CPSOCGSA), to forecast standard precipitation index (SPI) based on climatic factors. Additionally, the marine predators algorithm (MPA) and the slime mould algorithm (SMA) were used to validate the performance of the CPSOCGSA algorithm. Climatic factors data from 1990 to 2020 were employed to create and evaluate the SPI 1, SPI 3, and SPI 6 models for Al-Kut City, Iraq. The results indicated that data preprocessing methods improve data quality and find the best predictors scenario. The performance of CPSOCGSA-ANN is better than MPA-ANN and SMA-ANN algorithms based on various statistical criteria (i.e., R2, MAE, and RMSE). The proposed methodology yield R2 = 0.93, 0.93, and 0.88 for SPI 1, SPI 3, and SPI 6, respectively.
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| 11. |
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| 12. |
- Ghazy, Ramy Mohamed, et al.
(författare)
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Acceptance of COVID-19 Vaccine Booster Doses Using the Health Belief Model : A Cross-Sectional Study in Low-Middle- and High-Income Countries of the East Mediterranean Region
- 2022
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Ingår i: International Journal of Environmental Research and Public Health. - : MDPI AG. - 1661-7827 .- 1660-4601. ; 19:19
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Tidskriftsartikel (refereegranskat)abstract
- Coronavirus disease (COVID-19) booster doses decrease infection transmission and disease severity. This study aimed to assess the acceptance of COVID-19 vaccine booster doses in low, middle, and high-income countries of the East Mediterranean Region (EMR) and its determinants using the health belief model (HBM). In addition, we aimed to identify the causes of booster dose rejection and the main source of information about vaccination. Using the snowball and convince sampling technique, a bilingual, self-administered, anonymous questionnaire was used to collect the data from 14 EMR countries through different social media platforms. Logistic regression analysis was used to estimate the key determinants that predict vaccination acceptance among respondents. Overall, 2327 participants responded to the questionnaire. In total, 1468 received compulsory doses of vaccination. Of them, 739 (50.3%) received booster doses and 387 (26.4%) were willing to get the COVID-19 vaccine booster doses. Vaccine booster dose acceptance rates in low, middle, and high-income countries were 73.4%, 67.9%, and 83.0%, respectively (p < 0.001). Participants who reported reliance on information about the COVID-19 vaccination from the Ministry of Health websites were more willing to accept booster doses (79.3% vs. 66.6%, p < 0.001). The leading causes behind booster dose rejection were the beliefs that booster doses have no benefit (48.35%) and have severe side effects (25.6%). Determinants of booster dose acceptance were age (odds ratio (OR) = 1.02, 95% confidence interval (CI): 1.01–1.03, p = 0.002), information provided by the Ministry of Health (OR = 3.40, 95% CI: 1.79–6.49, p = 0.015), perceived susceptibility to COVID-19 infection (OR = 1.88, 95% CI: 1.21–2.93, p = 0.005), perceived severity of COVID-19 (OR = 2.08, 95% CI: 137–3.16, p = 0.001), and perceived risk of side effects (OR = 0.25, 95% CI: 0.19–0.34, p < 0.001). Booster dose acceptance in EMR is relatively high. Interventions based on HBM may provide useful directions for policymakers to enhance the population’s acceptance of booster vaccination.
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| 13. |
- Khatri, C, et al.
(författare)
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Outcomes after perioperative SARS-CoV-2 infection in patients with proximal femoral fractures: an international cohort study
- 2021
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Ingår i: BMJ open. - : BMJ. - 2044-6055. ; 11:11, s. e050830-
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Tidskriftsartikel (refereegranskat)abstract
- Studies have demonstrated high rates of mortality in people with proximal femoral fracture and SARS-CoV-2, but there is limited published data on the factors that influence mortality for clinicians to make informed treatment decisions. This study aims to report the 30-day mortality associated with perioperative infection of patients undergoing surgery for proximal femoral fractures and to examine the factors that influence mortality in a multivariate analysis.SettingProspective, international, multicentre, observational cohort study.ParticipantsPatients undergoing any operation for a proximal femoral fracture from 1 February to 30 April 2020 and with perioperative SARS-CoV-2 infection (either 7 days prior or 30-day postoperative).Primary outcome30-day mortality. Multivariate modelling was performed to identify factors associated with 30-day mortality.ResultsThis study reports included 1063 patients from 174 hospitals in 19 countries. Overall 30-day mortality was 29.4% (313/1063). In an adjusted model, 30-day mortality was associated with male gender (OR 2.29, 95% CI 1.68 to 3.13, p<0.001), age >80 years (OR 1.60, 95% CI 1.1 to 2.31, p=0.013), preoperative diagnosis of dementia (OR 1.57, 95% CI 1.15 to 2.16, p=0.005), kidney disease (OR 1.73, 95% CI 1.18 to 2.55, p=0.005) and congestive heart failure (OR 1.62, 95% CI 1.06 to 2.48, p=0.025). Mortality at 30 days was lower in patients with a preoperative diagnosis of SARS-CoV-2 (OR 0.6, 95% CI 0.6 (0.42 to 0.85), p=0.004). There was no difference in mortality in patients with an increase to delay in surgery (p=0.220) or type of anaesthetic given (p=0.787).ConclusionsPatients undergoing surgery for a proximal femoral fracture with a perioperative infection of SARS-CoV-2 have a high rate of mortality. This study would support the need for providing these patients with individualised medical and anaesthetic care, including medical optimisation before theatre. Careful preoperative counselling is needed for those with a proximal femoral fracture and SARS-CoV-2, especially those in the highest risk groups.Trial registration numberNCT04323644
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| 14. |
- Khudhair, Zahraa S., et al.
(författare)
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A CPSOCGSA-tuned neural processor for forecasting river water salinity: Euphrates river, Iraq
- 2022
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Ingår i: Cogent Engineering. - : Taylor & Francis Group. - 2331-1916. ; 9:1
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Tidskriftsartikel (refereegranskat)abstract
- Salinity is a classic problem in water quality management since it is directly associated with low water quality indices. Debate continues about selecting the best model for water quality forecasting, it remains a major challenge and causes much uncertainty. Accordingly, identifying the optimal modelling that can capture the salinity behaviour is becoming a common trend in recent water quality research. This study applies novel combined techniques, including data pre-processing and artificial neural network (ANN) optimised with constriction coefficient-based particle swarm optimisation and chaotic gravitational search algorithm (CPSOCGSA) to forecast monthly salinity data. Historical monthly total dissolved solids (TDS) and electrical conductivity (EC) data of the Euphrates River at Al-Musayyab, Babylon, and climatic factors from 2010 to 2019 were used to build and validate the methodology. Additionally, for more validation, the CPSOCGSA-ANN was compared with the slime mould algorithm (SMA-ANN), particle swarm optimisation (PSO-ANN) and multi-verse optimiser (MVO-ANN). The results reveal that the pre-processing data approaches improved data quality and selected the best predictors’ scenario. The CPSOCGSA-ANN algorithm is the best based on several statistical criteria. The proposed methodology accurately simulated the TDS and EC time series based on R2 = 0.99 and 0.97, respectively, and SI = 0.003 for both parameters.
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| 15. |
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| 16. |
- Micah, Angela E., et al.
(författare)
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Tracking development assistance for health and for COVID-19 : a review of development assistance, government, out-of-pocket, and other private spending on health for 204 countries and territories, 1990-2050
- 2021
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Ingår i: The Lancet. - : Elsevier. - 0140-6736 .- 1474-547X. ; 398:10308, s. 1317-1343
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Forskningsöversikt (refereegranskat)abstract
- Background The rapid spread of COVID-19 renewed the focus on how health systems across the globe are financed, especially during public health emergencies. Development assistance is an important source of health financing in many low-income countries, yet little is known about how much of this funding was disbursed for COVID-19. We aimed to put development assistance for health for COVID-19 in the context of broader trends in global health financing, and to estimate total health spending from 1995 to 2050 and development assistance for COVID-19 in 2020. Methods We estimated domestic health spending and development assistance for health to generate total health-sector spending estimates for 204 countries and territories. We leveraged data from the WHO Global Health Expenditure Database to produce estimates of domestic health spending. To generate estimates for development assistance for health, we relied on project-level disbursement data from the major international development agencies' online databases and annual financial statements and reports for information on income sources. To adjust our estimates for 2020 to include disbursements related to COVID-19, we extracted project data on commitments and disbursements from a broader set of databases (because not all of the data sources used to estimate the historical series extend to 2020), including the UN Office of Humanitarian Assistance Financial Tracking Service and the International Aid Transparency Initiative. We reported all the historic and future spending estimates in inflation-adjusted 2020 US$, 2020 US$ per capita, purchasing-power parity-adjusted US$ per capita, and as a proportion of gross domestic product. We used various models to generate future health spending to 2050. Findings In 2019, health spending globally reached $8. 8 trillion (95% uncertainty interval [UI] 8.7-8.8) or $1132 (1119-1143) per person. Spending on health varied within and across income groups and geographical regions. Of this total, $40.4 billion (0.5%, 95% UI 0.5-0.5) was development assistance for health provided to low-income and middle-income countries, which made up 24.6% (UI 24.0-25.1) of total spending in low-income countries. We estimate that $54.8 billion in development assistance for health was disbursed in 2020. Of this, $13.7 billion was targeted toward the COVID-19 health response. $12.3 billion was newly committed and $1.4 billion was repurposed from existing health projects. $3.1 billion (22.4%) of the funds focused on country-level coordination and $2.4 billion (17.9%) was for supply chain and logistics. Only $714.4 million (7.7%) of COVID-19 development assistance for health went to Latin America, despite this region reporting 34.3% of total recorded COVID-19 deaths in low-income or middle-income countries in 2020. Spending on health is expected to rise to $1519 (1448-1591) per person in 2050, although spending across countries is expected to remain varied. Interpretation Global health spending is expected to continue to grow, but remain unequally distributed between countries. We estimate that development organisations substantially increased the amount of development assistance for health provided in 2020. Continued efforts are needed to raise sufficient resources to mitigate the pandemic for the most vulnerable, and to help curtail the pandemic for all. Copyright (C) 2021 The Author(s). Published by Elsevier Ltd.
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| 17. |
- Mohammed, Sarah J., et al.
(författare)
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Application of Metaheuristic Algorithms and ANN Model for Univariate Water Level Forecasting
- 2023
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Ingår i: Advances in Civil Engineering / Hindawi. - : Hindawi Publishing Corporation. - 1687-8086 .- 1687-8094.
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Tidskriftsartikel (refereegranskat)abstract
- With the rapid development of machine learning (ML) models, the artificial neural network (ANN) is being increasingly applied for forecasting hydrological processes. However, researchers have not treated hybrid ML models in much detail. To address these issues, this study herein suggests a novel methodology to forecast the monthly water level (WL) based on multiple lags of the Tigris River in Al-Kut, Iraq, over ten years. The methodology includes preprocessing data methods, and the ANN model optimises with a marine predator algorithm (MPA). In the optimisation procedure, to decrease uncertainty and expand the predicting range, the slime mould algorithm (SMA-ANN), constriction coefficient-based particle swarm optimisation and chaotic gravitational search algorithms (CPSOCGSA-ANN), and particle swarm optimisation (PSO-ANN) are applied to compare and validate the MPA-ANN model performance. Analysis of results revealed that the data pretreatment methods improved the original data quality and selected the ideal predictors’ scenario by singular spectrum analysis and mutual information methods, respectively. For example, the correlation coefficient of the first lag improved from 0.648 to 0.938. Depending on various evaluation metrics, MPA-ANN tends to forecast WL better than SMA-ANN, PSO-ANN, and CPSOCGSA-ANN algorithms with coefficients of determination of 0.94, 0.81, 0.85, and 0.90, respectively. Evidence shows that the proposed methodology yields excellent results, with a scatter index equal to 0.002. The research outcomes represent an additional step towards evolving various hybrid ML techniques, which are valuable to practitioners wishing to forecast WL data and the management of water resources in light of environmental shifts.
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| 18. |
- Mohammed, Sarah J., et al.
(författare)
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Hybrid Technique to Improve the River Water Level Forecasting Using Artificial Neural Network-Based Marine Predators Algorithm
- 2022
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Ingår i: Advances in Civil Engineering / Hindawi. - : Hindawi Publishing Corporation. - 1687-8086 .- 1687-8094. ; 2022
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Tidskriftsartikel (refereegranskat)abstract
- Water level (WL) forecasting has become a difficult undertaking due to spatiotemporal fluctuations in climatic factors and complex physical processes. This paper proposes a novel hybrid machine learning model based on an artificial neural network (ANN) and the Marine Predators algorithm (MPA) for modeling monthly water levels of the Tigris River in Al-Kut, Iraq. Data preprocessing techniques are employed to enhance data quality and determine the optimal input model. Historical data for water level and climatic factors data are utilized from 2011 to 2020 to build and assess the model. MPA-ANN algorithm’s performance is compared with recent constriction coefficient-based particle swarm optimization and chaotic gravitational search algorithm (CPSOCGSA-ANN) and slime mold algorithm (SMA-ANN) to reduce uncertainty and raise the prediction range. The finding demonstrated that singular spectrum analysis is a highly effective method to denoise time series. MPA-ANN outperformed CPSOCGSA-ANN and SMA-ANN algorithms based on different statistical criteria. The suggested novel methodology offers good results with scatter index (SI) = 0.0009 and coefficient of determination (R2 = 0.98).
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| 19. |
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| 20. |
- Swed, Sarya, et al.
(författare)
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Parents' acceptance to vaccinate children against COVID-19 : A Syrian online survey
- 2022
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Ingår i: Frontiers In Public Health. - : Frontiers Media SA. - 2296-2565. ; 10
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Tidskriftsartikel (refereegranskat)abstract
- After the widespread of COVID-19 virus worldwide, vaccination targeted reducing spread of cases and mortality rates. However, vaccination hesitancy was observed among the communities worldwide. Vaccination hesitancy involved parents regarding the decision of vaccinating their children- After obtaining ethical approval, an online cross-sectional study was conducted from 1 March to 22 April 2021 to evaluate the parents' acceptance of vaccinating their children against the COVID-19 virus in Syria. Data were analyzed using descriptive and multivariate logistic regression analysis in IBM, SPSS V. 28.0 package program (IBM Corporation, Armonk, NY, USA). Among 283 participants, 105 participants agreed to vaccinate their children, and 178 were not. A significant correlation between age and vaccine willingness was found (P-value < 0.0001*), especially in the age group between 18 and 30 years old (45.2%). Parents who accepted vaccinating themselves were more willing to vaccinate their children (34.6%). According to our results, there is a greater need to enhance awareness and knowledge programs about the vaccine's effectiveness and encourage parents to accept giving the vaccine to their children.
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| 21. |
- Tran, K. B., et al.
(författare)
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The global burden of cancer attributable to risk factors, 2010-19: a systematic analysis for the Global Burden of Disease Study 2019
- 2022
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Ingår i: Lancet. - 0140-6736. ; 400:10352, s. 563-591
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Tidskriftsartikel (refereegranskat)abstract
- Background Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. Methods The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk-outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. Findings Globally, in 2019, the risk factors included in this analysis accounted for 4.45 million (95% uncertainty interval 4.01-4.94) deaths and 105 million (95.0-116) DALYs for both sexes combined, representing 44.4% (41.3-48.4) of all cancer deaths and 42.0% (39.1-45.6) of all DALYs. There were 2.88 million (2.60-3.18) risk-attributable cancer deaths in males (50.6% [47.8-54.1] of all male cancer deaths) and 1.58 million (1.36-1.84) risk-attributable cancer deaths in females (36.3% [32.5-41.3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20.4% (12.6-28.4) and DALYs by 16.8% (8.8-25.0), with the greatest percentage increase in metabolic risks (34.7% [27.9-42.8] and 33.3% [25.8-42.0]). Interpretation The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.
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| 22. |
- Zubaidi, Salah L., et al.
(författare)
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Assessing the Benefits of Nature-Inspired Algorithms for the Parameterization of ANN in the Prediction of Water Demand
- 2023
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Ingår i: Journal of water resources planning and management. - : American Society of Civil Engineers (ASCE). - 0733-9496 .- 1943-5452. ; 149:1
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Tidskriftsartikel (refereegranskat)abstract
- Accurate forecasting techniques for a stochastic pattern of water demand are essential for any city that faces high variability in climate factors and a shortage of water resources. This study was the first research to assess the impact of climatic factors on urban water demand in Iraq, which is one of the hottest countries in the world. We developed a novel forecasting methodology that includes data preprocessing and an artificial neural network (ANN) model, which we integrated with a recent nature-inspired metaheuristic algorithm [marine predators algorithm (MPA)]. The MPA-ANN algorithm was compared with four nature-inspired metaheuristic algorithms. Nine climatic factors were examined with different scenarios to simulate the monthly stochastic urban water demand over 11 years for Baghdad City, Iraq. The results revealed that (1) precipitation, solar radiation, and dew point temperature are the most relevant factors; (2) the ANN model becomes more accurate when it is used in combination with the MPA; and (3) this methodology can accurately forecast water demand considering the variability in climatic factors. These findings are of considerable significance to water utilities in planning, reviewing, and comparing the availability of freshwater resources and increasing water requests (i.e., adaptation variability of climatic factors).
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| 23. |
- Abdeljaber, Osama, et al.
(författare)
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A novel video-vibration monitoring system for walking pattern identification on floors
- 2020
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Ingår i: Advances in Engineering Software. - : Elsevier. - 0965-9978 .- 1873-5339. ; 139
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Tidskriftsartikel (refereegranskat)abstract
- Walking-induced loads on office floors can generate unwanted vibrations. The current multi-person loading models are limited since they do not take into account nondeterministic factors such as pacing rates, walking paths, obstacles in walking paths, busyness of floors, stride lengths, and interactions among the occupants. This study proposes a novel video-vibration monitoring system to investigate the complex human walking patterns on floors. The system is capable of capturing occupant movements on the floor with cameras, and extracting walking trajectories using image processing techniques. To demonstrate its capabilities, the system was installed on a real office floor and resulting trajectories were statistically analyzed to identify the actual walking patterns, paths, pacing rates, and busyness of the floor with respect to time. The correlation between the vibration levels measured by the wireless sensors and the trajectories extracted from the video recordings were also investigated. The results showed that the proposed video-vibration monitoring system has strong potential to be used in training data-driven crowd models, which can be used in future studies to generate realistic multi-person loading scenarios.
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| 24. |
- Acero, F., et al.
(författare)
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Prospects for Cherenkov Telescope Array Observations of the Young Supernova Remnant RX J1713.7-3946
- 2017
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Ingår i: Astrophysical Journal. - : Institute of Physics Publishing (IOPP). - 0004-637X .- 1538-4357. ; 840:2
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Tidskriftsartikel (refereegranskat)abstract
- We perform simulations for future Cherenkov Telescope Array (CTA) observations of RX J1713.7-3946, a young supernova remnant (SNR) and one of the brightest sources ever discovered in very high energy (VHE) gamma rays. Special attention is paid to exploring possible spatial (anti) correlations of gamma rays with emission at other wavelengths, in particular X-rays and CO/H I emission. We present a series of simulated images of RX J1713.7-3946 for CTA based on a set of observationally motivated models for the gamma-ray emission. In these models, VHE gamma rays produced by high-energy electrons are assumed to trace the nonthermal X-ray emission observed by XMM-Newton, whereas those originating from relativistic protons delineate the local gas distributions. The local atomic and molecular gas distributions are deduced by the NANTEN team from CO and H I observations. Our primary goal is to show how one can distinguish the emission mechanism(s) of the gamma rays (i.e., hadronic versus leptonic, or a mixture of the two) through information provided by their spatial distribution, spectra, and time variation. This work is the first attempt to quantitatively evaluate the capabilities of CTA to achieve various proposed scientific goals by observing this important cosmic particle accelerator.
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| 25. |
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| 26. |
- Ahmed, Sirwan Khalid, et al.
(författare)
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Knowledge, Attitude and Worry in the Kurdistan Region of Iraq during the Mpox (Monkeypox) Outbreak in 2022 : An Online Cross-Sectional Study
- 2023
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Ingår i: Vaccines. - : MDPI AG. - 2076-393X. ; 11:3
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Tidskriftsartikel (refereegranskat)abstract
- The rapid spread of monkeypox (mpox) has been declared as a public health emergency of international concern (PHEIC). The present study aimed to assess the knowledge, attitude, and worry levels of the general population in the Kurdistan region of Iraq regarding the ongoing mpox multi-country outbreak. An online cross-sectional survey was conducted between 27–30 July 2022, using a convenience sampling method. The questionnaire was adapted from previous studies addressing the same topic. The independent Student’s t-test, one-way ANOVA, and logistic regression were used to assess possible factors associated with knowledge, attitude, and worry toward mpox. A total of 510 respondents were included in the final analysis. The participants showed a moderate level of mpox knowledge, a neutral attitude towards mpox, and a relatively moderate worry level. The logistic regression analysis showed that age, gender, marital status, religion, level of education, and place of residence were associated with mpox knowledge; however, the significant variables in the multivariate regression analysis were gender, religion, level of education, and residential area. Gender and residential area were associated with attitudes toward mpox; however, the significant variables in the multivariate regression analysis were gender and residential areas. The worry toward mpox was influenced by gender, marital status, religion, and place of residence, yet the significant variables in the multivariate regression analysis were gender, religion, educational level, and residential area. In conclusion, the Kurdish population had moderate knowledge, a neutral attitude, and a moderate level of worry about mpox. Considering the continuous rapid rise in mpox cases in several countries, and its possible risk as pandemic amid the ongoing COVID-19 pandemic, proactive control measures, adequate disease prevention strategies, and preparedness plans need to be formulated and immediately implemented to tackle the appearance of fears among people, and to safeguard the mental health of the public.
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| 27. |
- Al-Zubaidy, Hussein Mohammed, et al.
(författare)
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Performance of in-network processing for visual analysis in wireless sensor networks
- 2015
-
Ingår i: Proceedings of 2015 14th IFIP Networking Conference, IFIP Networking 2015. - : IEEE conference proceedings. - 9783901882685
-
Konferensbidrag (refereegranskat)abstract
- Nodes in a sensor network are traditionally used for sensing and data forwarding. However, with the increase of their computational capability, they can be used for in-network data processing, leading to a potential increase of the quality of the networked applications as well as the network lifetime. Visual analysis in sensor networks is a prominent example where the processing power of the network nodes needs to be leveraged to meet the frame rate and the processing delay requirements of common visual analysis applications. The modeling of the end-to-end performance for such networks is, however, challenging, because in-network processing violates the flow conservation law, which is the basis for most queuing analysis. In this work we propose to solve this methodological challenge through appropriately scaling the arrival and the service processes, and we develop probabilistic performance bounds using stochastic network calculus. We use the developed model to determine the main performance bottlenecks of networked visual processing. Our numerical results show that an end-to-end delay of 2-3 frame length is obtained with violation probability in the order of 10-6. Simulation shows that the obtained bounds overestimates the end-to-end delay by no more than 10%.
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| 28. |
- Alabbasi, Sateh, et al.
(författare)
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A numerical and experimental investigation of a special type of floating-slab tracks
- 2020
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Ingår i: Engineering structures. - : Elsevier. - 0141-0296 .- 1873-7323. ; 215, s. 1-16
-
Tidskriftsartikel (refereegranskat)abstract
- Floating-Slab Tracks (FST) are predominantly used for mitigating railway-induced vibrations where the concrete slab is mounted on soft resilient bearings to provide vibration isolation. This paper presents a research study on the dynamic behavior of a special type of FST used in the recently built subway system in Doha, Qatar. The special FST has a continuous concrete slab with periodic grooves. Therefore, the track can be modeled as a periodic structure with a slab unit having two elements with different cross-sections. Extensive numerical and experimental investigations were conducted on a multi-unit full-scale mockup track representing the special FST. A fast running model based on the Dynamic Stiffness Method was developed and examined, in an initial numerical exercise, against a detailed Finite Element model for a track with a finite length. In the experimental campaign, a test was performed with an impact hammer to identify the actual vibration response of the mockup track. Results from the experimental investigations were then used for model updating of the fast running model. The model updating process was carried out according to an automated hybrid optimization approach that combines genetic algorithms with a local search method. Finally, the updated model was extended to an infinite model to investigate the influence of varying grooves thickness on the dynamic behavior of the special track with infinite length for both bending and torsion scenarios. The investigations suggested that reducing the thickness below 50% of the full thickness of the slab significantly affects the dynamic behavior of the special FST.
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| 29. |
- Alawi, Omer A., et al.
(författare)
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Heat transfer and hydrodynamic properties using different metal-oxide nanostructures in horizontal concentric annular tube : An optimization study
- 2021
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Ingår i: Nanomaterials. - : MDPI AG. - 2079-4991. ; 11:8
-
Tidskriftsartikel (refereegranskat)abstract
- Numerical studies were performed to estimate the heat transfer and hydrodynamic properties of a forced convection turbulent flow using three-dimensional horizontal concentric annuli. This paper applied the standard k–ε turbulence model for the flow range 1 × 104 ≤ Re ≥ 24 × 103. A wide range of parameters like different nanomaterials (Al2O3, CuO, SiO2 and ZnO), different particle nanoshapes (spherical, cylindrical, blades, platelets and bricks), different heat flux ratio (HFR) (0, 0.5, 1 and 2) and different aspect ratios (AR) (1.5, 2, 2.5 and 3) were examined. Also, the effect of inner cylinder rotation was discussed. An experiment was conducted out using a field-emission scanning electron microscope (FE-SEM) to characterize metallic oxides in spherical morphologies. Nano-platelet particles showed the best enhancements in heat transfer properties, followed by nano-cylinders, nano-bricks, nano-blades, and nano-spheres. The maximum heat transfer enhancement was found in SiO2, followed by ZnO, CuO, and Al2O3, in that order. Meanwhile, the effect of the HFR parameter was insignificant. At Re = 24,000, the inner wall rotation enhanced the heat transfer about 47.94%, 43.03%, 42.06% and 39.79% for SiO2, ZnO, CuO and Al2O3, respectively. Moreover, the AR of 2.5 presented the higher heat transfer improvement followed by 3, 2, and 1.5.
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| 30. |
- Athab, Zahraa H., et al.
(författare)
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Comparison activity of pure and chromium-doped nickel oxide nanoparticles for the selective removal of dyes from water
- 2024
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Ingår i: Scientific Reports. - : Springer Nature. - 2045-2322. ; 14:1
-
Tidskriftsartikel (refereegranskat)abstract
- The current study involves a synthesis of a composite of nickel oxide nanoparticles (NiONPs) with a chromium dopant to yield (Cr/NiONPs). Synthesis of nickel oxide was performed by the co-precipitation method. The synthesis of the composite was conducted by the impregnation method. FTIR, EDX, SEM, and XRD were used to characterize the synthesized materials. The synthesised materials’ point zero charges (PZC) were performed using the potentiometric titration method. The obtained results show that the PZC for neat nickel oxide was around 5, and it was around 8 for Cr/NiONPs. The adsorption action of the prepared materials was examined by applying them to remove Reactive Red 2 (RR2) and Crystal Violate (CV) dyes from solutions. The outcomes demonstrated that Cr/NiONPs were stronger in the removal of dyes than NiONPs. Cr/NiONPs achieved 99.9% removal of dyes after 1 h. Adsorption isotherms involving Freundlich and Langmuir adsorption isotherms were also conducted, and the outcomes indicated that the most accurate representation of the adsorption data was offered by Langmuir adsorption isotherms. Additionally, it was discovered that the adsorption characteristics of the NiONPs and Cr/NiONPs correspond well with the pseudo-second-order kinetic model. Each of the NiONPs and Cr/NiONPs was reused five times, and the results display that the effectiveness of the removal of RR2 dye slightly declined with the increase in reuse cycles; it lost only 5% of its original efficiency after the 5 cycles. Generally, Cr/NiONPs showed better reusability than NiONPs under the same conditions.
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| 31. |
- Avci, Onur, et al.
(författare)
-
A New Benchmark Problem for Structural Damage Detection : Bolt Loosening Tests on a Large-Scale Laboratory Structure
- 2022
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Ingår i: Dynamics of Civil Structures, Volume 2. - Cham : Springer. - 9783030771423 - 9783030771430 ; , s. 15-22
-
Konferensbidrag (refereegranskat)abstract
- Monitoring the structural performance of engineering structures has always been pertinent for maintaining structural health and assessing the life cycle of structures. Structural Health Monitoring (SHM) and Structural Damage Detection (SDD) fields have been topics of ongoing research over the years to explore and verify different monitoring techniques and damage detection and localization procedures. In an attempt to compare performances of different methods, benchmark datasets are valuable resources since the data is made available to researchers enabling side-by-side comparisons. This paper presents a new experimental benchmark dataset generated from tests on a large-scale laboratory structure. The primary goal of the authors was to explore brand-new damage detection and quantification methodologies for efficient monitoring of structures. For this purpose, a large-scale steel grid structure with footprint dimensions of 4.2 m × 4.2 m was constructed in laboratory environment and it has been used as a test bed by the authors. The structural members of the structure are all IPE120 hot-rolled steel cross sections. The simulation of structural damage was simply loosening the bolts at one of the beam-to-girder connections, which is a slight change of rotational stiffness at the joint of the steel grid structure. The authors shared the dataset for 1 undamaged and 30 damaged conditions and published it on a public website as a new benchmark problem for structural damage detection at http://www.structuralvibration.com/benchmark/ so that other researchers can use the data and test algorithms. The authors also shared one of the damage detection tools they used, One-Dimensional Convolutional Neural Networks (1D-CNNs). The application codes, configuration files, and accompanied components of the 1D-CNNs package are available for viewers at http://www.structuralvibration.com/cnns/. © 2022, The Society for Experimental Mechanics, Inc.
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| 32. |
- Avci, Onur, et al.
(författare)
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A review of vibration-based damage detection in civil structures : from traditional methods to Machine Learning and Deep Learning applications
- 2021
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Ingår i: Mechanical systems and signal processing. - : Elsevier. - 0888-3270 .- 1096-1216. ; 147
-
Tidskriftsartikel (refereegranskat)abstract
- Monitoring structural damage is extremely important for sustaining and preserving the service life of civil structures. While successful monitoring provides resolute and staunch information on the health, serviceability, integrity and safety of structures; maintaining continuous performance of a structure depends highly on monitoring the occurrence, formation and propagation of damage. Damage may accumulate on structures due to different environmental and human-induced factors. Numerous monitoring and detection approaches have been developed to provide practical means for early warning against structural damage or any type of anomaly. Considerable effort has been put into vibration-based methods, which utilize the vibration response of the monitored structure to assess its condition and identify structural damage. Meanwhile, with emerging computing power and sensing technology in the last decade, Machine Learning (ML) and especially Deep Learning (DL) algorithms have become more feasible and extensively used in vibration-based structural damage detection with elegant performance and often with rigorous accuracy. While there have been multiple review studies published on vibration-based structural damage detection, there has not been a study where the transition from traditional methods to ML and DL methods are described and discussed. This paper aims to fulfill this gap by presenting the highlights of the traditional methods and provide a comprehensive review of the most recent applications of ML and DL algorithms utilized for vibration-based structural damage detection in civil structures.
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| 33. |
- Avci, Onur, et al.
(författare)
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Operational modal analysis and finite element model updating of a 230 m tall tower
- 2022
-
Ingår i: Structure. - : Elsevier. - 2352-0124. ; 37, s. 154-167
-
Tidskriftsartikel (refereegranskat)abstract
- Dynamic response levels are critical for tall and slender civil structures. Studying the dynamic behavior of large civil structures with finite element modeling techniques requires detailed and accurate modeling of structural geometry, material properties, member fixities, connection types, and accompanying assumptions. Still, the finite element model results are approximations that could be away from representing the actual structural behavior. Structures are dynamically tested at their operational conditions to validate the finite element model results. This paper presents Operational Modal Analysis (OMA) and finite element model updating of a tall structure located in the West Bay area of Doha (Qatar). The structure is a reinforced concrete building with shear wall cores situated towards the center of the building plan, which was constructed between 2012 and 2016. With 53 stories above the ground and two stories below ground, the 230 m (755 ft) tall building is being used for residential and hotel purposes. For the finite element model updating and calibration tasks presented in this paper, the authors intentionally introduced drastic model changes for the first two model updates so that the results from the first two attempts guide how to proceed with a more reasonable update for the third calibration of the finite element model. While this is a non-standard technique that represents a specific condition where the initial attempts on the finite element model are very crude approximations, it is a systematized demonstration of how to operate when the structural parameters are sparse or uncertain for modeling purposes. While in theory, the finite element model updates can always be fine-tuned in a way to further decrease the error between the measured and predicted OMA results, in this paper, the authors predominantly focused on the presentation of three finite element model updates to demonstrate the way they have improved the modal assurance criteria plots and lowered the average absolute errors by visiting two drastic and then one moderate finite element model updates. The material presented here in this paper is arguably the first published work on large-scale dynamic testing of a civil structure in the State of Qatar. © 2021 Institution of Structural Engineers
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| 34. |
- Avci, Onur, et al.
(författare)
-
Operational Modal Analysis and Finite Element Model Updating of a 53-Story Building
- 2022
-
Ingår i: Dynamics of Civil Structures, Volume 2. - Cham : Springer. - 9783030771430 - 9783030771423 ; , s. 83-91
-
Konferensbidrag (refereegranskat)abstract
- This paper presents Operational Modal Analysis (OMA) and Finite Element (FE) model updating of a tall structure. Located in the West Bay area of Doha (Qatar), the structure was constructed between 2012 and 2016. It is a reinforced concrete building with shear wall cores located towards the center of the building plan. With 53 stories above the ground and 2 stories below ground, the 230 m (755 ft) tall building is being used for residential and hotel purposes. The material presented here is arguably the first published work on large-scale dynamic testing of a civil structure in Qatar. The wireless sensors used for testing are state-of-the-art equipment that can capture very low frequencies, something that cannot be accomplished with most of the conventional accelerometers available in the market. © 2022, The Society for Experimental Mechanics, Inc.
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| 35. |
- Avci, Onur, et al.
(författare)
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Wireless and real-time structural damage detection : a novel decentralized method for wireless sensor networks
- 2018
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Ingår i: Journal of Sound and Vibration. - : Elsevier. - 0022-460X .- 1095-8568. ; 424, s. 158-172
-
Tidskriftsartikel (refereegranskat)abstract
- Being an alternative to conventional wired sensors, wireless sensor networks (WSNs) are extensively used in Structural Health Monitoring (SHM) applications. Most of the Structural Damage Detection (SDD) approaches available in the SHM literature are centralized as they require transferring data from all sensors within the network to a single processing unit to evaluate the structural condition. These methods are found predominantly feasible for wired SHM systems; however, transmission and synchronization of huge data sets in WSNs has been found to be arduous. As such, the application of centralized methods with WSNs has been a challenge for engineers. In this paper, the authors are presenting a novel application of 1D Convolutional Neural Networks (1D CNNs) on WSNs for SDD purposes. The SDD is successfully performed completely wireless and real-time under ambient conditions. As a result of this, a decentralized damage detection method suitable for wireless SHM systems is proposed. The proposed method is based on 1D CNNs and it involves training an individual 1D CNN for each wireless sensor in the network in a format where each CNN is assigned to process the locally-available data only, eliminating the need for data transmission and synchronization. The proposed damage detection method operates directly on the raw ambient vibration condition signals without any filtering or preprocessing. Moreover, the proposed approach requires minimal computational time and power since 1D CNNs merge both feature extraction and classification tasks into a single learning block. This ability is prevailingly cost-effective and evidently practical in WSNs considering the hardware systems have been occasionally reported to suffer from limited power supply in these networks. To display the capability and verify the success of the proposed method, large-scale experiments conducted on a laboratory structure equipped with a state-of-the-art WSN are reported.
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| 36. |
- Bashir, Muwada Bashir Awad, et al.
(författare)
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Predictors and correlates of examination anxiety and depression among high school students taking the Sudanese national board examination in Khartoum state, Sudan: a cross-sectional study
- 2019
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Ingår i: Pan African Medical Journal. - : Pan African Medical Journal. - 1937-8688. ; 33
-
Tidskriftsartikel (refereegranskat)abstract
- Introduction: test anxiety and depression are of the major challenges experienced in students' life, considering the inverse associations they have on their mental wellbeing and academic performance. Evidence from Sudan have reported high figures of adolescent's mental health problems of depression and anxiety. However, studies investigating its association with academic exam stress are lacking. We investigated the prevalence of exam anxiety and depression severity among student setting for Sudan national boarding examination, aiming at identifying possible predictors related to student's socio-demographic and academic status and measuring correlation between exam anxiety and depression severity status among students. Methods: using cross-sectional design, data obtained using standardized west side anxiety scale for measuring test anxiety; and patient's health questionnaire (PHQ9) of nine items for measuring depression was presented in percentages. Association with sociodemographic and academic factors was measured using logisticregression models. Analysis was run at 0.05 level of significance. Results: depression and exam anxiety were found to be highly correlated. The highest fractions of students are those with high levels of test anxiety and moderate to severe depression. Gender, maternal level of education, previous exam experience and academic performance are significant predictor for student's exam anxiety status. Conclusion: high figures of exam anxiety and depression are there among Sudanese students setting for their third years boarding exam. Males, low academic performance and maternal low education are risk factors. school mental health services and programs addressing such group of students are highly demanded in line with more elaborative research efforts in this arena.
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| 37. |
- Braik, Malik, et al.
(författare)
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Adaptive dynamic elite opposition-based Ali Baba and the forty thieves algorithm for high-dimensional feature selection
- 2024
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Ingår i: Cluster Computing. - : SPRINGER. - 1386-7857 .- 1573-7543.
-
Tidskriftsartikel (refereegranskat)abstract
- High-dimensional Feature Selection Problems (HFSPs) have grown in popularity but remain challenging. When faced with such complex situations, the majority of currently employed Feature Selection (FS) methods for these problems drastically underperform in terms of effectiveness. To address HFSPs, a new Binary variant of the Ali Baba and the Forty Thieves (BAFT) algorithm known as binary adaptive elite opposition-based AFT (BAEOAFT), incorporating historical information and dimensional mutation is presented. The entire population is dynamically separated into two subpopulations in order to maintain population variety, and information and knowledge about individuals are extracted to offer adaptive and dynamic strategies in both subpopulations. Based on the individuals' history knowledge, Adaptive Tracking Distance (ATD) and Adaptive Perceptive Possibility (APP) schemes are presented for the exploration and exploitation subpopulations. A dynamic dimension mutation technique is used in the exploration subpopulation to enhance BAEOAFT's capacity in solving HFSPs. Meanwhile, the exploratory subpopulation uses Dlite Dynamic opposite Learning (EDL) to promote individual variety. Even if the exploitation group prematurely converges, the exploration subpopulation's variety can still be preserved. The proposed BAEOAFT-based FS technique was assessed by utilizing the k-nearest neighbor classifier on 20 HFSPs obtained from the UCI repository. The developed BAEOAFT achieved classification accuracy rates greater than those of its competitors and the conventional BAFT in more than 90% of the applied datasets. Additionally, BAEOAFT outperformed its rivals in terms of reduction rates while selecting the fewest number of features.
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| 38. |
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| 39. |
- El Jery, Atef, et al.
(författare)
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Optimization of oil industry wastewater treatment system and proposing empirical correlations for chemical oxygen demand removal using electrocoagulation and predicting the system’s performance by artificial neural network
- 2023
-
Ingår i: PeerJ. - : PeerJ Inc.. - 2167-8359. ; 11
-
Tidskriftsartikel (refereegranskat)abstract
- The alarming pace of environmental degradation necessitates the treatment of wastewater from the oil industry in order to ensure the long-term sustainability of human civilization. Electrocoagulation has emerged as a promising method for optimizing the removal of chemical oxygen demand (COD) from wastewater obtained from oil refineries. Therefore, in this study, electrocoagulation was experimentally investigated, and a single-factorial approach was employed to identify the optimal conditions, taking into account various parameters such as current density, pH, COD concentration, electrode surface area, and NaCl concentration. The experimental findings revealed that the most favorable conditions for COD removal were determined to be 24 mA/cm2 for current density, pH 8, a COD concentration of 500 mg/l, an electrode surface area of 25.26 cm2, and a NaCl concentration of 0.5 g/l. Correlation equations were proposed to describe the relationship between COD removal and the aforementioned parameters, and double-factorial models were examined to analyze the impact of COD removal over time. The most favorable outcomes were observed after a reaction time of 20 min. Furthermore, an artificial neural network model was developed based on the experimental data to predict COD removal from wastewater generated by the oil industry. The model exhibited a mean absolute error (MAE) of 1.12% and a coefficient of determination (R2) of 0.99, indicating its high accuracy. These findings suggest that machine learning-based models have the potential to effectively predict COD removal and may even serve as viable alternatives to traditional experimental and numerical techniques.
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| 40. |
- Ghareeb, Waleed M., et al.
(författare)
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Deep Neural Network for the Prediction of KRAS Genotype in Rectal Cancer
- 2022
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Ingår i: Journal of the American College of Surgeons. - 1879-1190. ; 235:3, s. 482-493
-
Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: KRAS mutation can alter the treatment plan after resection of colorectal cancer. Despite its importance, the KRAS status of several patients remains unchecked because of the high cost and limited resources. This study developed a deep neural network (DNN) to predict the KRAS genotype using hematoxylin and eosin (H&E)-stained histopathological images. STUDY DESIGN: Three DNNs were created (KRAS_Mob, KRAS_Shuff, and KRAS_Ince) using the structural backbone of the MobileNet, ShuffleNet, and Inception networks, respectively. The Cancer Genome Atlas was screened to extract 49,684 image tiles that were used for deep learning and internal validation. An independent cohort of 43,032 image tiles was used for external validation. The performance was compared with humans, and a virtual cost-saving analysis was done. RESULTS: The KRAS_Mob network (area under the receiver operating curve [AUC] 0.8, 95% CI 0.71 to 0.89) was the best-performing model for predicting the KRAS genotype, followed by the KRAS_Shuff (AUC 0.73, 95% CI 0.62 to 0.84) and KRAS_Ince (AUC 0.71, 95% CI 0.6 to 0.82) networks. Combing the KRAS_Mob and KRAS_Shuff networks as a double prediction approach showed improved performance. KRAS_Mob network accuracy surpassed that of two independent pathologists (AUC 0.79 [95% CI 0.64 to 0.93], 0.51 [95% CI 0.34 to 0.69], and 0.51 (95% CI 0.34 to 0.69]; p < 0.001 for all comparisons). CONCLUSION: The DNN has the potential to predict the KRAS genotype directly from H&E-stained histopathological slide images. As an algorithmic screening method to prioritize patients for laboratory confirmation, such a model might possibly reduce the number of patients screened, resulting in significant test-related time and economic savings.
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| 41. |
- Hilo, Salam J., et al.
(författare)
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Structural Performance of Internally Stiffened Double-Skinned Profiled Composite Walls with Openings
- 2023
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Ingår i: Buildings. - 2075-5309. ; 13:6
-
Tidskriftsartikel (refereegranskat)abstract
- The double-skin profiled composite wall (DSPCW) system, filled with concrete material, is favorable in modern structures due to its high strength and ductility. Openings may be required within this composite wall (DSPCW) for various reasons, similar to a conventional bearing wall, which can lead to a reduction in bearing capacity. Therefore, to avoid changes in the geometry, materials, and thickness of this DSPCW wall, a new internally stiffening concept has been suggested by providing embedded cold-formed steel tube (CFST) columns. For this purpose, two full-scale DSPCW specimens were tested under static axial load, one of which was fabricated with a large opening size and stiffened with two octagonal CFST columns, while the other was designed without an opening and served as a control wall specimen. The results showed that the stiffened DSPCW with an opening achieved a slightly lower ultimate bearing strength (-9.4%) than the control wall specimen, with no reduction in the ductility behavior. Furthermore, several finite element models of DSPCW have been analyzed and designed to investigate additional parameters that were not experimentally tested, including the effects of the embedded CFST column's shape and different types of internal stiffeners longitudinally provided inside these columns. The numerical investigation confirmed that the embedded CFST column with an octagonal cross-section was more efficient compared to the hexagonal and rectangular shapes by about 11% and 18.4%, respectively. Furthermore, using internal steel stiffeners for embedded tubes with a T-shape improved the axial bearing capacity of the DSPCW with an opening slightly higher than the corresponding stiffened walls with other investigated stiffener shapes (V-shaped, U-shaped, and L-shaped).
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| 42. |
- Homod, R. Z., et al.
(författare)
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Crude oil production prediction based on an intelligent hybrid modelling structure generated by using the clustering algorithm in big data
- 2023
-
Ingår i: Geoenergy Science and Engineering. - : Elsevier. - 2949-8910. ; 225
-
Tidskriftsartikel (refereegranskat)abstract
- Since the behavior of a complex dynamic system for a large oil field in Iraq is significantly influenced by many nonlinearities, its dependent parameters exhibit non-stationary with a very high delay time. Developing white-box modelling approaches for such dynamic oil well production cannot handle these large data sets with all dependent dimensions and their non-linear effects. Therefore, this study adopts the hybrid model that combines white-box and black-box to address such problems because the model outputs require various variable types to achieve optimal fitness to measured values. The hybrid model structure needs to evolve with changes in the physical parameters (white-box part) and Neural Networks' Weights (black-box part). The model structure of the proposed hybrid network relied on converting fuzzy rules in a Takagi–Sugeno–Kang Fuzzy System (TSK-FS) into a multilayer perceptron network (MLP). The hybrid parameters are formulated concerning six-dimensional dependent variables to describe them in matrix form or layer and by which can quantify total model outputs. After mapping categorical variables to tuples of MLP, the Gauss-Newton regression (GNR) provides an optimal update of the hybrid parameters to get the best fitting of the model outputs with the target of the dataset. The clustering technique and GNR promote predictive performance due to reducing uncertainties in the hybrid parameters. Due to time being the most effective of the independent variables for predicting oil production, datasets are classified into different clusters based on time. The actual field dataset for training and validation is collected from Zubair Oil Field (9 oil wells), which is implemented to build the proposed model. The results of the hybrid model indicate that the development of the proposed structure has achieved the high capability to represent such big data which is the most imperative feature of the proposed model. Furthermore, obtained results show its accuracy far outpacing competitors and achieving a significant improvement in predictive performance.
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| 43. |
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| 44. |
- Hussein,, Jelili Babatunde, et al.
(författare)
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Effect of hybrid solar drying method on the Functional and sensory properties of tomato
- 2016
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Ingår i: American Journal of Food Science and Technology. - 2333-4827 .- 2333-4835. ; 4:5, s. 141-148
-
Tidskriftsartikel (refereegranskat)abstract
- A hybrid solar dryer, direct solar energy dryer and open sun drying under the climatic conditions of Yola, Nigeria was used to dry tomato slices. The effect of these drying methods on the functional and sensory quality of the dried tomatoes was examined. The functional properties of the dried tomatoes slices were significantly different (p<0.05). In open sun dried tomatoes, the bulk density ranged from 0.56 – 0.62 g/ml, water absorption index (WAI) 436.33 – 475.67 gH2O/sample, water solubility index (WSI) 6.00 – 14.00, specific volume 1.61 – 1.78 ml/g and wettability 10.33 – 13.33 s for 4 – 8 mm thick tomato samples. For solar dried tomatoes, the bulk density ranged from 0.52 – 0.57 g/ml, the WAI ranged from 412.00 – 454.00 gH2O/sample, the water solubility index (WSI) range was 12.33 – 16.67, specific volume range was 1.73 – 1.90 ml/g and wettability ranged from 5.85 – 10.63 s for 4 – 8 mm thick tomato samples. For the hybrid dried tomatoes, the bulk density ranged from 0.50 – 0.54 g/ml, the WAI values ranged from 386.00 – 436.00 gH2O/sample, the WSI 14.67 – 18.00, specific volume range was 1.84 – 1.99 ml/g and wettability 5.80 – 8.44 s for 4 – 8 mm thick tomato sample. The organoleptic properties showed that the tomatoes dried by hybrid drying method was superior in terms of acceptability test than those dried using direct solar energy and a photovoltaic (PV) solar panel tomato products. Conclusively, good quality shelf stable dried tomato slices could be produced using hybrid drying method.
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| 45. |
- Hussein, Wafaa Mohamed, et al.
(författare)
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A review of the infection-associated cancers in North African countries
- 2016
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Ingår i: Infectious Agents and Cancer. - : Springer Science and Business Media LLC. - 1750-9378. ; 11:1
-
Forskningsöversikt (refereegranskat)abstract
- Cancer is typically classified as a leading non-communicable disease; however, infectious agents, such as Helicobacter pylori (H. pylori), hepatitis B virus (HBV), hepatitis C virus (HCV) and human papilloma virus (HPV), contribute significantly to the pathogenesis of various cancers. Less developed countries, including countries of the North African (NA) region, endure the highest burden of infection-related cancers. The five most common infection-associated cancers in NA in order of incidence are bladder cancer, cervical cancer, liver cancer, stomach cancer, and nasopharyngeal carcinoma. This review aims to outline the epidemiologic pattern of infection-associated cancers in five NA countries (namely: Morocco, Algeria, Tunisia, Libya and Egypt) highlighting the similarities and differences across the region. The present study employed an initial literature review of peer-reviewed articles selected from PubMed, ScienceDirect and World Health Organization (WHO) databases based on key word searches without restriction on publication dates. Original research articles and reports written in French, as well as data from institutional reports and regional meeting abstracts were also included in this extensive review. Egypt, Libya, Tunisia, Algeria and Morocco were selected to be the focus of this review.
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| 46. |
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| 47. |
- Ikuta, K. S., et al.
(författare)
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Global mortality associated with 33 bacterial pathogens in 2019: a systematic analysis for the Global Burden of Disease Study 2019
- 2022
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Ingår i: Lancet. - : Elsevier BV. - 0140-6736. ; 400:10369, s. 2221-2248
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Tidskriftsartikel (refereegranskat)abstract
- Background Reducing the burden of death due to infection is an urgent global public health priority. Previous studies have estimated the number of deaths associated with drug-resistant infections and sepsis and found that infections remain a leading cause of death globally. Understanding the global burden of common bacterial pathogens (both susceptible and resistant to antimicrobials) is essential to identify the greatest threats to public health. To our knowledge, this is the first study to present global comprehensive estimates of deaths associated with 33 bacterial pathogens across 11 major infectious syndromes. Methods We estimated deaths associated with 33 bacterial genera or species across 11 infectious syndromes in 2019 using methods from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, in addition to a subset of the input data described in the Global Burden of Antimicrobial Resistance 2019 study. This study included 343 million individual records or isolates covering 11 361 study-location-years. We used three modelling steps to estimate the number of deaths associated with each pathogen: deaths in which infection had a role, the fraction of deaths due to infection that are attributable to a given infectious syndrome, and the fraction of deaths due to an infectious syndrome that are attributable to a given pathogen. Estimates were produced for all ages and for males and females across 204 countries and territories in 2019. 95% uncertainty intervals (UIs) were calculated for final estimates of deaths and infections associated with the 33 bacterial pathogens following standard GBD methods by taking the 2.5th and 97.5th percentiles across 1000 posterior draws for each quantity of interest. Findings From an estimated 13.7 million (95% UI 10.9-17.1) infection-related deaths in 2019, there were 7.7 million deaths (5.7-10.2) associated with the 33 bacterial pathogens (both resistant and susceptible to antimicrobials) across the 11 infectious syndromes estimated in this study. We estimated deaths associated with the 33 bacterial pathogens to comprise 13.6% (10.2-18.1) of all global deaths and 56.2% (52.1-60.1) of all sepsis-related deaths in 2019. Five leading pathogens-Staphylococcus aureus, Escherichia coli, Streptococcus pneumoniae, Klebsiella pneumoniae, and Pseudomonas aeruginosa-were responsible for 54.9% (52.9-56.9) of deaths among the investigated bacteria. The deadliest infectious syndromes and pathogens varied by location and age. The age-standardised mortality rate associated with these bacterial pathogens was highest in the sub-Saharan Africa super-region, with 230 deaths (185-285) per 100 000 population, and lowest in the high-income super-region, with 52.2 deaths (37.4-71.5) per 100 000 population. S aureus was the leading bacterial cause of death in 135 countries and was also associated with the most deaths in individuals older than 15 years, globally. Among children younger than 5 years, S pneumoniae was the pathogen associated with the most deaths. In 2019, more than 6 million deaths occurred as a result of three bacterial infectious syndromes, with lower respiratory infections and bloodstream infections each causing more than 2 million deaths and peritoneal and intra-abdominal infections causing more than 1 million deaths. Interpretation The 33 bacterial pathogens that we investigated in this study are a substantial source of health loss globally, with considerable variation in their distribution across infectious syndromes and locations. Compared with GBD Level 3 underlying causes of death, deaths associated with these bacteria would rank as the second leading cause of death globally in 2019; hence, they should be considered an urgent priority for intervention within the global health community. Strategies to address the burden of bacterial infections include infection prevention, optimised use of antibiotics, improved capacity for microbiological analysis, vaccine development, and improved and more pervasive use of available vaccines. These estimates can be used to help set priorities for vaccine need, demand, and development. Copyright (c) 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.
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| 48. |
- Ishigaki, Kazuyoshi, et al.
(författare)
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Multi-ancestry genome-wide association analyses identify novel genetic mechanisms in rheumatoid arthritis
- 2022
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Ingår i: Nature Genetics. - : Springer Nature. - 1061-4036 .- 1546-1718. ; 54:11, s. 1640-1651
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Tidskriftsartikel (refereegranskat)abstract
- Rheumatoid arthritis (RA) is a highly heritable complex disease with unknown etiology. Multi-ancestry genetic research of RA promises to improve power to detect genetic signals, fine-mapping resolution and performances of polygenic risk scores (PRS). Here, we present a large-scale genome-wide association study (GWAS) of RA, which includes 276,020 samples from five ancestral groups. We conducted a multi-ancestry meta-analysis and identified 124 loci (P < 5 × 10−8), of which 34 are novel. Candidate genes at the novel loci suggest essential roles of the immune system (for example, TNIP2 and TNFRSF11A) and joint tissues (for example, WISP1) in RA etiology. Multi-ancestry fine-mapping identified putatively causal variants with biological insights (for example, LEF1). Moreover, PRS based on multi-ancestry GWAS outperformed PRS based on single-ancestry GWAS and had comparable performance between populations of European and East Asian ancestries. Our study provides several insights into the etiology of RA and improves the genetic predictability of RA.
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| 49. |
- Kareem, Baydaa Abdul, et al.
(författare)
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Applicability of ANN Model and CPSOCGSA Algorithm forMulti-Time Step Ahead River Streamflow Forecasting
- 2022
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Ingår i: Hydrology. - : MDPI. - 2306-5338. ; 9:10
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Tidskriftsartikel (refereegranskat)abstract
- Accurate streamflow prediction is significant when developing water resource management and planning, forecasting floods, and mitigating flood damage. This research developed a novel methodology that involves data pre-processing and an artificial neural network (ANN) optimised with the coefficient-based particle swarm optimisation and chaotic gravitational search algorithm (CPSOCGSA-ANN) to forecast the monthly water streamflow. The monthly streamflow data of the Tigris River at Amarah City, Iraq, from 2010 to 2020, were used to build and evaluate the suggested methodology. The performance of CPSOCGSA was compared with the slim mold algorithm (SMA) and marine predator algorithm (MPA). The principal findings of this research are that data pre-processing effectively improves the data quality and determines the optimum predictor scenario. The hybrid CPSOCGSA-ANN outperformed both the SMA-ANN and MPA-ANN algorithms. The suggested methodology offered accurate results with a coefficient of determination of 0.91, and 100% of the data were scattered between the agreement limits of the Bland–Altman diagram. The research results represent a further step toward developing hybrid models in hydrology applications.
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| 50. |
- Kassimu, Kamaka, et al.
(författare)
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Safety and Tolerability of an Antimalarial Herbal Remedy in Healthy Volunteers : An Open-Label, Single-Arm, Dose-Escalation Study on Maytenus senegalensis in Tanzania
- 2022
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Ingår i: Tropical Medicine and Infectious Disease. - : MDPI. - 2414-6366. ; 7:12
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Tidskriftsartikel (refereegranskat)abstract
- Background: Though Maytenus senegalensis is one of the medicinal plants widely used in traditional medicine to treat infectious and inflammatory diseases in Africa, there is a lack of safety data regarding its use. Therefore, the study aimed to asselss the safety and tolerability of the antimalarial herbal remedy M. senegalensis. Material and Methods: The study design was an open-label, single-arm, dose-escalation. Twelve eligible male healthy Tanzanians aged 18 to 45 years were enrolled in four study dose groups. Volunteers' safety and tolerability post-investigational-product administration were monitored on days 0 to 7,14, and 56. Results: There were no deaths or serious adverse events in any of the study groups, nor any adverse events that resulted in premature discontinuation. The significant mean changes observed in WBC (p = 0.003), Neutrophils (p = 0.02), Lymphocytes (p = 0.001), Eosinophils (p = 0.009), Alanine aminotransferase (p = 0.002), Creatinine (p = 0.03) and Total bilirubin (p = 0.004) laboratory parameters were not associated with any signs of toxicity or clinical symptoms. Conclusions: M. senegalensis was demonstrated to be safe and tolerable when administered at a dose of 800 mg every eight hours a day for four days. This study design may be adapted to evaluate other herbal remedies.
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