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

The anti-adhesive effect of curcumin on Candida albicans biofilms on denture materials

The use of natural compounds as an alternative source of antimicrobials has become a necessity given the growing concern over global antimicrobial resistance. Polyphenols, found in various edible plants, offers one potential solution to this. We aimed to investigate the possibility of using curcumin within the context of oral health as a way of inhibiting and preventing the harmful development of Candida albicans biofilms. We undertook a series of adsorption experiments with varying concentrations of curcumin, showing that 50 ug/ml could prevent adhesion. This effect could be further synergised by the curcumin pretreatment of yeast cells to obtain significantly greater inhibition (>90, p<0.001). Investigation of the biological impact of curcumin showed that it preferentially affected immature morphological forms (yeast and germlings), and actively promoted aggregation of the cells. Transcriptional analyses showed that key adhesins were down-regulated (ALS1 and ALS3), whereas aggregation related genes (ALS5 and AAF1) were up-regulated. Collectively, these data demonstrated that curcumin elicits anti-adhesive effects and that induces transcription of genes integrally involved in the processes related to biofilm formation. Curcumin and associated polyphenols therefore have the capacity to be developed for use in oral healthcare to augment existing preventative strategies for candidal biofilms on the denture surface

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

Influence of anodizing process on fatigue life of a machined aluminium alloy

In order to investigate the coupled effects of machining and anodizing processes on fatigue life of alloy 7010-T7451, a series of rotating bending fatigue tests were conducted at 60Hz. In the as machined condition, test results showed that fatigue life is surface roughness dependent and that fatigue life decreases with an increase in surface roughness and this effect is found to be more pronounced in high cycle fatigue where major portion of fatigue life is consumed in nucleating the cracks. Effects of pretreatments, like degreasing and pickling employed prior to anodizing, on fatigue life of the given alloy were also studied. Results demonstrated that degreasing showed no change in fatigue life while pickling had negative impact on fatigue life of specimens. The small decrease in fatigue life of anodized specimens as compare to pickled specimens is attributed to brittle and microcracking of the coating. Scanning electron microscopic (SEM) examination revealed multi-site crack initiation for the pickled and anodized specimens. SEM examination showed that pickling solution attacked the grain boundaries and intermetallic inclusions present on the surface resulting in pits formation. These pits are of primary concern with respect to accelerated fatigue crack nucleation and subsequent anodized coating formation

Visualisation of heterogeneous data with simultaneous feature saliency using Generalised Generative Topographic Mapping

Most machine-learning algorithms are designed for datasets with features of a single type whereas very little attention has been given to datasets with mixed-type features. We recently proposed a model to handle mixed types with a probabilistic latent variable formalism. This proposed model describes the data by type-specific distributions that are conditionally independent given the latent space and is called generalised generative topographic mapping (GGTM). It has often been observed that visualisations of high-dimensional datasets can be poor in the presence of noisy features. In this paper we therefore propose to extend the GGTM to estimate feature saliency values (GGTMFS) as an integrated part of the parameter learning process with an expectation-maximisation (EM) algorithm. The efficacy of the proposed GGTMFS model is demonstrated both for synthetic and real datasets

Client Satisfaction Towards Quality of Health Services: an Assessment at Primary Healthcare of District Gujranwala

This survey designed to evaluate the satisfaction level and the factors that affect the patient satisfaction regarding health care delivery services with the aim to improve the services in the primary health care settings of Gujranwala. A Cross Sectional Study done on randomly selected patients attending the basic health units of Gujranwala, with more than18 years of age. Pretested structured "Liker scale questionnaire" was used for data collection. Out of total respondents, 62 (41.3%) clients were satisfied with the services provided by the basic health units of Gujranwala. The factors identified to determine patient satisfaction were accessibility of services, behavior of staff, health education, level of cleanliness, drug availability and miscellaneous services. Not a single ranked area of satisfaction noticed. Client\u27s occupation and income had significant relationship with the patient satisfaction level. Gender, age, and education of clients were not contributing factors; they not affect the client satisfaction level.Less than half clients were satisfied with the services provided by the basic health units. Management of health facilities needs to improve the services

EVALUATION OF EFFICACY AND SAFETY OF NIGELLA SATIVA OIL SUPPLEMENTATION IN PATIENTS OF CHRONIC KIDNEY DISEASE

ABSTRACTObjective: To evaluate efficacy and safety of add-on therapy of Nigella sativa oil in patients of stage 3 and 4 of chronic kidney disease (CKD).Materials and Methods: The study was conducted in a tertiary care center of north India in stage 3 and 4 patients of CKD. It was a prospective,comparative, and open label study. Patients were randomly divided into two interventional groups. Group I (Control) received conservativemanagement of CKD while Group II (Test) received conservative management along with N. sativa oil (2.5 mL, per orally, once daily) for 12 weeks.Hemogram and renal function tests were done, and adverse events were recorded at 0, 6, and 12 weeks of treatment.Results: After 12 weeks of treatment, there was a progressive improvement in clinical features and biochemical parameters in both the groups, but itwas more marked in the test group compared to control group. Both groups showed gradual improvement in the biochemical parameters as comparedto their pre-treated values which were more marked in N. sativa oil supplemented group. There was a reduction in blood glucose, blood urea, serumcreatinine, and 24-hr total urine protein. There was an increase in hemoglobin, 24-hr total urine volume, and glomerular filtration rate.Conclusion: N. sativa oil supplementation along with conservative management is efficacious and safe in averting the progression of disease in stage 3and 4 patients of CKD.Keywords: Chronic kidney disease, Nigella sativa oil, End-stage renal disease, Glomerular filtration rate

Estimation of lightning impulse insulation strength of two seriesdielectrics using the least square technique

In this paper, the least square (LS) estimation technique was used to estimate the total critical flashover (CFO) for combinations of two insulating materials from the experimental data obtained. This method had acceptable accuracy when applied to the total population of the two-component combinations but lost some accuracy for some of the sub-sets of the two material

Human-computer interaction of single/three phase transformer designand performance

This paper presents a menu-driven, easy-to-use computer package which has been tailored at this stage to assist: (1) young electrical engineers in industry to visualize and enhance the practical use of theoretical and analytical brief notes learned in typical energy conversion courses taken at the undergraduate level, and enable them to have confidence, industry know-how process and sufficient design and performance evaluation skills on the different types of transformers; and (2) in teaching electrical machines laboratory skills to power engineering students by an interactive step-by-step approach. All experiments performed on transformers can be handled by the software to illustrate transformer design and performance details. The scope of this package is to present transformer performance in an interactive logical design procedure and to calculate core/yoke/sheets dimensions, low and high voltage winding's number of turns/layers, axial length and other related dimension

Clinical evaluation of efficacy and safety of α-keto analogs of essential amino acids supplementation in patients of chronic kidney disease

Background: The objective was to evaluate the efficacy and safety of α-keto analogs of essential amino acids (KAA) as a supplement in chronic kidney disease (CKD).Methods: A prospective comparative study was conducted in patients of CKD of a tertiary care center of North India. Patients were randomly divided into two interventional groups. Group I (control) was advised conservative management and placebo while Group II (KAA) given conservative management along with KAA (600 mg, thrice daily) for 12 weeks. Hemogram, renal function tests, lipid profiles were done, and adverse effects were recorded at 0, 4, 8, and 12 weeks of treatment.Results: There was progressive improvement in clinical features in both groups after 12 weeks of treatment, but KAA group showed more marked improvement as compared with the control group. Both groups showed gradual improvement in the biochemical parameters as compared to their pre-treated values, which was more marked in KAA supplemented group. There was a reduction in blood glucose, blood urea, serum creatinine, and 24 h total urine protein. There was an increase in hemoglobin, 24 h total urine volume and glomerular filtration rate. KAA group showed significant (p<0.05) improvement in lipid profiles as compared with the control group. There was no statistical difference in two groups with respect to side-effects (p>0.05).Conclusion: KAA supplementation along with conservative management is efficacious and safe in preventing the progression of disease in patients of CKD