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- Anwar, Hamid, et al.
(author)
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Intercomparison of deep learning models in predicting streamflow patterns: insight from CMIP6
- 2024
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In: Scientific Reports. - : Springer Nature. - 2045-2322. ; 14
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Journal article (peer-reviewed)abstract
- This research was carried out to predict daily streamflow for the Swat River Basin, Pakistan through four deep learning (DL) models: Feed Forward Artificial Neural Networks (FFANN), Seasonal Artificial Neural Networks (SANN), Time Lag Artificial Neural Networks (TLANN) and Long Short-Term Memory (LSTM) under two Shared Socioeconomic Pathways (SSPs) 585 and 245. Taylor Diagram, Random Forest, and Gradient Boosting techniques were used to select the best combination of General Circulation Models (GCMs) for Multi-Model Ensemble (MME) computation. MME was computed via the Random Forest technique for Maximum Temperature (Tmax), Minimum Temperature (Tmin), and precipitation for the aforementioned three techniques. The best MME for Tmax, Tmin, and precipitation was rendered by Compromise Programming. The DL models were trained and tested using observed precipitation and temperature as independent variables and discharge as dependent variables. The results of deep learning models were evaluated using statistical performance indicators such as root mean square error (RMSE), mean square error (MSE), mean absolute error (MAE), and coefficient of determination (R2). The TLANN demonstrated superior performance compared to the other models based on RMSE, MSE, MAE, and R2 during training (65.25 m3/s, 4256.97 m3/s, 46.793 m3/s and 0.7978) and testing (72.06 m3/s, 5192.95 m3/s, 51.363 m3/s and 0.7443) respectively. Subsequently, TLANN was utilized to make predictions based on MME of SSP245 and SSP585 scenarios for future streamflow until the year 2100. These results can be used for planning, management, and policy-making regarding water resources projects in the study area.
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| 3. |
- Shuaib, YA, et al.
(author)
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Smear Microscopy for Diagnosis of Pulmonary Tuberculosis in Eastern Sudan
- 2018
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In: Tuberculosis research and treatment. - : Hindawi Limited. - 2090-150X .- 2090-1518. ; 2018, s. 8038137-
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Journal article (peer-reviewed)abstract
- Background. In Sudan, tuberculosis diagnosis largely relies on clinical symptoms and smear microscopy as in many other low- and middle-income countries. The aim of this study was to investigate the positive predictive value of a positive sputum smear in patients investigated for pulmonary tuberculosis in Eastern Sudan. Methods. Two sputum samples from patients presenting with symptoms suggestive of tuberculosis were investigated using direct Ziehl-Neelsen (ZN) staining and light microscopy between June to October 2014 and January to July 2016. If one of the samples was smear positive, both samples were pooled, stored at −20°C, and sent to the National Reference Laboratory (NRL), Germany. Following decontamination, samples underwent repeat microscopy and culture. Culture negative/contaminated samples were investigated using polymerase chain reaction (PCR). Results. A total of 383 samples were investigated. Repeat microscopy categorized 123 (32.1%) as negative, among which 31 were culture positive. This increased to 80 when PCR and culture results were considered together. A total of 196 samples were culture positive, of which 171 (87.3%), 14 (7.1%), and 11 (5.6%) were M. tuberculosis, M. intracellulare, and mixed species. Overall, 15.6% (57/365) of the samples had no evidence of M. tuberculosis, resulting in a positive predictive value of 84.4%. Conclusions. There was a discordance between the results of smear microscopy performed at local laboratories in the Sudan and at the NRL, Germany; besides, a considerable number of samples had no evidence of M. tuberculosis. Improved quality control for smear microscopy and more specific diagnostics are crucial to avoid possible overtreatment.
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| 6. |
- Bravo, L, et al.
(author)
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- 2021
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swepub:Mat__t
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| 7. |
- Tabiri, S, et al.
(author)
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- 2021
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swepub:Mat__t
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