| 1. |
- Khan, M., et al.
(författare)
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Monitoring and assessment of heavy metal contamination in surface water of selected rivers
- 2023
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Ingår i: Geocarto International. - : Taylor & Francis. - 1010-6049 .- 1752-0762. ; 38:1
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Tidskriftsartikel (refereegranskat)abstract
- The current research aimed to monitor and assess the heavy metal contamination in the surface water of 53 sampling sites along the selected rivers using principal component analysis and cluster analysis. For this purpose, both physiochemical parameters such as the temperature (T), the potential of hydrogen (pH), total dissolved solids (TDS) and electroconductivity (EC), and heavy metals such as iron (Fe), chromium (Cr), nickel (Ni), cadmium (Cd), lead (Pb) and arsenic (As) are analyzed as potential water contaminants. The average values of pH, TDS, EC and T are found at 7.75, 70.89 mg/L, 139.11 µs/cm and 20.29 °C, respectively, and heavy metals including Cr, Ni, Cd, Pb, As and Fe are observed at 0.04, 0.04, 0.04, 0.03, 0.001 and 0.04 mg/L, respectively. Moreover, it is found that in both rivers hazardous metals, including Cr (100%), Cd (92.30%), Pb (100%), Ni (100%) and Fe (91%), exceed the permissible limits of the WHO.
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| 2. |
- Murtaza, S., et al.
(författare)
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Effect of exogenous administration of oxytocin on postpartum follicular dynamics, oestrous rate and ovulation in Nili-Ravi buffaloes
- 2021
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Ingår i: Reproduction in domestic animals. - : John Wiley & Sons. - 0936-6768 .- 1439-0531. ; 56:11, s. 1369-1376
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Tidskriftsartikel (refereegranskat)abstract
- Based on different surveys, dairy farmers are concerned about extensive use of exogenous oxytocin in buffaloes, which is being held responsible for reproductive problems including irregular oestrous cycle and delayed ovulation. For these concerns, effects of oxytocin injection on postpartum follicular dynamics, postpartum oestrous interval (PEI), oestrous length, the interval from onset of ostrus to ovulation and blood progesterone (P4) were studied in Nili-Ravi buffaloes. For this purpose, 23 animals within 1 week after calving were randomly divided into three groups: without oxytocin (CON; n = 7), 10 i.u. oxytocin (LOW; n = 8), 30 i.u. oxytocin – (HIGH; n = 8) and used to record the PEI for the study period of 154 days. At subsequent estrus, three buffaloes from each group (not served) were selected randomly to monitor two cycles for 6 weeks. Transrectal ultrasonography was performed to evaluate follicular and corpus luteum (CL) development, and blood sampling was done for progesterone (P4) analysis. These results revealed that postpartum oestrous interval (PEI) decreased significantly in oxytocin-treated groups. The number of small, medium and total follicles on the left ovary was significantly higher in the HIGH group. However, an overall number of small and total follicles on both right and left ovaries was significantly higher in CON and HIGH groups. On the other hand, there was no difference in the number of follicles on the right ovary among all treatment groups. The same was true for the size of pre-ovulatory follicles, CL, P4 concentrations and oestrous cycle length. The intervals from onset of estrus to ovulation and from standing estrus to ovulation were increased considerably in the HIGH group. It is concluded that exogenous oxytocin administration resulted in the shortening of PEI but triggered a delay in ovulation. Moreover, a higher dose of oxytocin could stimulate the growth of small, medium, and total follicles in postpartum Nili-Ravi buffaloes.
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| 3. |
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| 4. |
- Niaz, R., et al.
(författare)
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Proposing a new framework for analyzing the severity of meteorological drought
- 2023
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Ingår i: Geocarto International. - : Taylor & Francis. - 1010-6049 .- 1752-0762. ; 38:1
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Tidskriftsartikel (refereegranskat)abstract
- The quantitative description of meteorological drought from various geographical locations and indicators is crucial for early drought warning to avoid its negative impacts. Therefore, the current study proposes a new framework to comprehensively accumulate spatial and temporal information for meteorological drought from various stations and drought indicators (indices). The proposed framework is based on two major components such as the Monthly-based Monte Carlo Feature Selection (MMCFS,) and Monthly-based Joint Index Weights (MJIW). Besides, three commonly used SDI are jointly assessed to quantify drought for selected geographical locations. Moreover, the current study uses the monthly data from six meteorological stations in the northern region for 47 years (1971-2017) for calculating SDI values. The outcomes of the current research explicitly accumulate regional spatiotemporal information for meteorological drought. In addition, results may serve as an early warning to the effective management of water resources to avoid negative drought impacts in Pakistan.
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| 5. |
- Noreen, Khadija, et al.
(författare)
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Algorithms to obtain generalized neighbor designs in minimal circular blocks
- 2022
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Ingår i: Communications in statistics. Simulation and computation. - : Taylor & Francis. - 0361-0918 .- 1532-4141.
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Tidskriftsartikel (refereegranskat)abstract
- The experiments where response of a treatment (direct effect) is affected by the treatment(s) applied in neighboring units, neighbor designs are used to balance the neighbor effects. Being the economical, minimal neighbor designs are preferred by the experimenters. Minimal circular neighbor designs could not be constructed for almost every case of v even, where v is number of treatments. For v even, minimal circular generalized neighbor designs are preferred. In this article, algorithms are developed to obtain minimal circular generalized neighbor designs in which (a) v/2 of the unordered pairs, and (b) 3v/2 of the unordered pairs, do not appear as neighbor whereas the remaining ones appear once. These algorithms are also coded with R-language.
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| 6. |
- Noreen, K., et al.
(författare)
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Some new constructions of minimal efficient circular nearly strongly balanced neighbor designs
- 2023
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Ingår i: Journal of King Saud University - Science. - : Elsevier. - 1018-3647. ; 35:6
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Tidskriftsartikel (refereegranskat)abstract
- Neighbor designs are popular to control neighbor effects. Among neighbor designs, strongly balanced neighbor designs are important to estimate treatment effects and neighbor effects independently. Minimal circular strongly balanced neighbor designs (MCSBNDs) can be obtained only for odd v (number of treatments). For v even, minimal circular nearly strongly balanced neighbor designs are used which satisfied all conditions of MCSBNDs except that the treatment labeled as (v − 1) does not appear as its own neighbor. These designs can be converted directly in some other useful classes of neighbor designs. These designs are efficient to minimize the bias due to the neighbor effects.
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| 7. |
- Omer, Talha, et al.
(författare)
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Improved Breitung and Roling estimator for mixed-frequency models with application to forecasting inflation rates
- 2024
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Ingår i: Statistical papers. - : Springer. - 0932-5026 .- 1613-9798.
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Tidskriftsartikel (refereegranskat)abstract
- Instead of applying the commonly used parametric Almon or Beta lag distribution of MIDAS, Breitung and Roling (J Forecast 34:588–603, 2015) suggested a nonparametric smoothed least-squares shrinkage estimator (henceforth SLS1) for estimating mixed-frequency models. This SLS1 approach ensures a flexible smooth trending lag distribution. However, even if the biasing parameter in SLS1 solves the overparameterization problem, the cost is a decreased goodness-of-fit. Therefore, we suggest a modification of this shrinkage regression into a two-parameter smoothed least-squares estimator (SLS2). This estimator solves the overparameterization problem, and it has superior properties since it ensures that the orthogonality assumption between residuals and the predicted dependent variable holds, which leads to an increased goodness-of-fit. Our theoretical comparisons, supported by simulations, demonstrate that the increase in goodness-of-fit of the proposed two-parameter estimator also leads to a decrease in the mean square error of SLS2, compared to that of SLS1 . Empirical results, where the inflation rate is forecasted based on the oil returns, demonstrate that our proposed SLS2 estimator for mixed-frequency models provides better estimates in terms of decreased MSE and improved R2, which in turn leads to better forecasts.
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| 8. |
- Omer, Talha, et al.
(författare)
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Improved estimators for the zero-inflated Poisson regression model in the presence of multicollinearity : simulation and application of maternal death data
- 2021
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Ingår i: Communications in Statistics Case Studies Data Analysis and Applications. - : Taylor & Francis. - 2373-7484. ; 7:3, s. 394-412
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Tidskriftsartikel (refereegranskat)abstract
- In this article, we propose Liu-type shrinkage estimators for the zero-inflated Poisson regression (ZIPR) model in the presence of multicollinearity. Our new approach is a remedy to the problem of inflated variances for the ML estimation technique—which is a standard approach to estimate these types of count data models. When the data are in the form of non-negative integers with a surplus of zeros it induces overdispersion in the dependent variable. Considerable multicollinearity is frequently observed, but usually disregarded, for these types of data sets. Based on a Monte Carlo study we illustrate that our proposed estimators exhibit better MSE and MAE than the usual ML estimator and some other Liu estimators in the presence of multicollinearity. To demonstrate the advantages and the empirical relevance of our improved estimators, maternal death data are analyzed and the results illustrate similar benefits as is demonstrated in our simulation study.
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| 9. |
- Omer, Talha, et al.
(författare)
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Optimization of Monitoring Network to the Rainfall Distribution by Using Stochastic Search Algorithms : Lesson from Pakistan
- 2022
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Ingår i: Tellus. Series A, Dynamic meteorology and oceanography. - : Stockholm University Press. - 0280-6495 .- 1600-0870. ; 74:1, s. 333-345
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Tidskriftsartikel (refereegranskat)abstract
- Agricultural production is greatly influenced by environmental parameters such as temperature, rainfall, humidity, and wind speed. The accurate information about environmental parameters plays a vital and useful role when making policies for the agriculture sector as well as for other sectors. Pakistan meteorological department observed these environmental parameters at more than 90 stations. The allocation of these monitoring stations is not made systematically correct. This leads to inaccurate predictions for unobserved locations. The study aims to propose a monitoring network by which these prediction errors of the environmental parameters can be minimized. The well-known prediction techniques named, model-based ordinary kriging and model-based universal kriging (UK) with the known Matheron variogram model are used for prediction purposes. We investigate the monitoring network of Pakistan for rainfall and focus on both the optimal deletion/addition of monitoring stations from/to this network. The two stochastic search algorithms, spatial simulated annealing, and genetic algorithm are used for optimization purposes. Furthermore, the minimization of the Average Kriging Variance (AKV) is taken as the interpolation accuracy measure. The spatial simulated annealing exhibits a lower AKV as compared to the Genetic algorithm when adding/removing the optimal/redundant locations from the monitoring network.
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| 10. |
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