Application of soft computing models with input vectors of snow cover area in addition to hydro-climatic data to predict the sediment loads

The accurate estimate of sediment load is important for management of the river ecosystem, designing of water infrastructures, and planning of reservoir operations. The direct measurement of sediment is the most credible method to estimate the sediments. However, this requires a lot of time and resources. Because of these two constraints, most often, it is not possible to continuously measure the daily sediments for most of the gauging sites. Nowadays, data-based sediment prediction models are famous for bridging the data gaps in the estimation of sediment loads. In data-driven sediment predictions models, the selection of input vectors is critical in determining the best structure of models for the accurate estimation of sediment yields. In this study, time series inputs of snow cover area, basin effective rainfall, mean basin average temperature, and mean basin evapotranspiration in addition to the flows were assessed for the prediction of sediment loads. The input vectors were assessed with artificial neural network (ANN), adaptive neuro-fuzzy logic inference system with grid partition (ANFIS-GP), adaptive neuro-fuzzy logic inference system with subtractive clustering (ANFIS-SC), adaptive neuro-fuzzy logic inference system with fuzzy c-means clustering (ANFIS-FCM), multiple adaptive regression splines (MARS), and sediment rating curve (SRC) models for the Gilgit River, the tributary of the Indus River in Pakistan. The comparison of different input vectors showed improvements in the prediction of sediments by using the snow cover area in addition to flows, effective rainfall, temperature, and evapotranspiration. Overall, the ANN model performed better than all other models. However, as regards sediment load peak time series, the sediment loads predicted using the ANN, ANFIS-FCM, and MARS models were found to be closer to the measured sediment loads. The ANFIS-FCM performed better in the estimation of peak sediment yields with a relative accuracy of 81.31% in comparison to the ANN and MARS models with 80.17% and 80.16% of relative accuracies, respectively. The developed multiple linear regression equation of all models show an R$^{2}$ value of 0.85 and 0.74 during the training and testing period, respectively

Comparative assessment of spatial variability and trends of flows and sediments under the impact of climate change in the upper Indus basin

Extensive research of the variability of flows under the impact of climate change has been conducted for the Upper Indus Basin (UIB). However, limited literature is available on the spatial distribution and trends of suspended sediment concentrations (SSC) in the sub-basins of UIB. This study covers the comparative assessment of flows and SSC trends measured at 13 stations in the UIB along with the variability of precipitation and temperatures possibly due to climate change for the past three decades. In the course of this period, the country’s largest reservoir, Tarbela, on the Indus River was depleted rapidly due to heavy sediment influx from the UIB. Sediment management of existing storage and future planned hydraulic structures (to tap 30,000 MW in the region) depends on the correct assessment of SSC, their variation patterns, and trends. In this study, the SSC trends are determined along with trends of discharges, precipitation, and temperatures using the non-parametric Mann–Kendall test and Sen’s slope estimator. The results reveal that the annual flows and SSC are in a balanced state for the Indus River at Besham Qila, whereas the SSC are significantly reduced ranging from 18.56%–28.20% per decade in the rivers of Gilgit at Alam Bridge, Indus at Kachura, and Brandu at Daggar. The SSC significantly increase ranging from 20.08%–40.72% per decade in the winter together with a significant increase of average air temperature. During summers, the SSC are decreased significantly ranging from 18.63%–27.79% per decade along with flows in the Hindukush and Western–Karakorum regions, which is partly due to the Karakorum climate anomaly, and in rainfall-dominated basins due to rainfall reduction. In Himalayan regions, the SSC are generally increased slightly during summers. These findings will be helpful for understanding the sediment trends associated with flow, precipitation, and temperature variations, and may be used for the operational management of current reservoirs and the design of several hydroelectric power plants that are planned for construction in the UIB

Need for recovery amongst emergency physicians in the UK and Ireland: A cross-sectional survey

OBJECTIVES: To determine the need for recovery (NFR) among emergency physicians and to identify demographic and occupational characteristics associated with higher NFR scores. DESIGN: Cross-sectional electronic survey. SETTING: Emergency departments (EDs) (n=112) in the UK and Ireland. PARTICIPANTS: Emergency physicians, defined as any registered physician working principally within the ED, responding between June and July 2019. MAIN OUTCOME MEASURE: NFR Scale, an 11-item self-administered questionnaire that assesses how work demands affect intershift recovery. RESULTS: The median NFR Score for all 4247 eligible, consented participants with a valid NFR Score was 70.0 (95% CI: 65.5 to 74.5), with an IQR of 45.5-90.0. A linear regression model indicated statistically significant associations between gender, health conditions, type of ED, clinical grade, access to annual and study leave, and time spent working out-of-hours. Groups including male physicians, consultants, general practitioners (GPs) within the ED, those working in paediatric EDs and those with no long-term health condition or disability had a lower NFR Score. After adjusting for these characteristics, the NFR Score increased by 3.7 (95% CI: 0.3 to 7.1) and 6.43 (95% CI: 2.0 to 10.8) for those with difficulty accessing annual and study leave, respectively. Increased percentage of out-of-hours work increased NFR Score almost linearly: 26%-50% out-of-hours work=5.7 (95% CI: 3.1 to 8.4); 51%-75% out-of-hours work=10.3 (95% CI: 7.6 to 13.0); 76%-100% out-of-hours work=14.5 (95% CI: 11.0 to 17.9). CONCLUSION: Higher NFR scores were observed among emergency physicians than reported in any other profession or population to date. While out-of-hours working is unavoidable, the linear relationship observed suggests that any reduction may result in NFR improvement. Evidence-based strategies to improve well-being such as proportional out-of-hours working and improved access to annual and study leave should be carefully considered and implemented where feasible

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Not AvailableIn the present work, the salinity tolerance level of Indian major carp, Catla catla, genetically improved Labeo rohita (Jayanti rohu) and Cirrhinus mrigala were ascertained in terms of weight gain and mortality by exposing the fishes gradually to different levels of salinities for 45 days. Overall analysis of the result showed that, the severity of impact of increasing salinity was significantly higher (P<0.05) in Catla compared to other two species (Jayanti rohu and Mrigal). In case of C. catla significant decrease (P<0.05) in weight gain was noted from 1 ppt onwards, whereas in case of L. rohita the decrease in weight gain was found significant (P<0.05) from 3 ppt onwards and in case of C. mrigala the growth retardation was noticed from 4 ppt onwards compared to control. In case of Catla, mortality started at salinity above 5 ppt, and reached to 100% at salinity level of 8 ppt , whereas, Jayanti rohu showed no mortality up to 6 ppt salinity, though the survivability got reduced to 40% in salinity of 8 ppt. Interestingly, in case of Mrigal no mortality were recorded at salinity level up to 8 ppt on 30 days post experiment. The result obtained in the present study had given an account of the level of salinity tolerance in Indian major carps.Not Availabl

Atlanto-occipital fusion: An osteological study with clinical implications

Background: Atlanto-occipital fusion may be symptomatic or asymptomatic in nature. The anomaly may be incidentally detected at autopsies or during routine cadaveric dissections. The fusion of the atlas with occipital bone may result in the compression of vertebral artery and first cervical nerve. Methods: A total of 55 dried occipital bones in the Department of Anatomy, Universiti Kebangsaan Malaysia (UKM) and Department of Anatomy, Universiti Malaya (UM) were included in the study. The presence of atlanto-occipital fusion was closely observed and morphometric measurements were taken. Results: Out of 55 dried occipital bones studied, we observed atlanto-occiptalization in two bones (3.63 %). A total of 53 occipital bones (96.37 %) did not exhibit any anomalous fusions. Out of the two anomalous atlanto-occiptal fusions, one was complete while the other had unilateral right-sided fusion of the atlas with the occipital bone. Conclusion: Atlanto-occipitalization may result in the compression of vertebral artery thereby influencing the blood flow to the brain. Atlanto-occipitalization may also result in compression of the first cervical nerve. The action of the postural muscles on the extensor surface may be affected as a result of this anomaly. The present article discusses the clinical implications of atlanto-occipitalization, which may be beneficial for neurosurgeons, neurologists and radiologists in day-to-day clinical practice (Fig. 3, Ref. 17). Full Text in free PDF www.bmj.sk

Isolation and purlfkation of B-lactemase from proteus mairbilis local isolates 4TF and 20TF

Proteus mirabilis ? -lactamase of local isolates number 4TF represent karkh side and 20TF represent rusafa side of Baghdad were extracted and purified 23.17, 25.23 fold with yield of 36.66 %, 37.5% and specific activity 11.8, 12.6 of unit/ mg protein by DEAE –cellulose and Sepharose 4B (respectively ).Molecular weight of both enzyme was about 35500 Dalton determined by gel filtration. The study indicated that the isoelectric point of purified ? -lactamase that extracted from isolate number 4TF and 20TF was 5.4