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Objective: To find out the incidence, characteristics and laboratory parameters of epistaxis in children with β-thalassemia major visiting a tertiary healthcare facility of South Punjab, Pakistan. Study Design: Retrospective study. Setting: Department of Hematological Diseases, Thalassemia and Bone Marrow Transplantation Centre, and Department of Biochemistry, Bahawal Victoria Hospital, Quaid e Azam Medical College, Bahawalpur, Pakistan. Period: January 2021 to November 2022. Material & Methods: The hospital record of children of both genders aged from 2 to 18 years of age with blood transfusion dependent β-thalassemia was analyzed. Children reporting at least 1 episode of epistaxis in the preceding period were included in the final analysis to find out the incidence, characteristics and laboratory findings of children presenting with of epistaxis. Results: Out of 3772 children with β-thalassemia major, 85 reported at least 1 episode of epistaxis showing the incidence of epistaxis as 22.5/1,000 cases of β-thalassemia major. The mean age of the children at the time of enrollment and at the time of diagnosis of thalassemia was 9.93±3.48 years and 1.23±1.26 years respectively. The mean monthly frequency of blood transfusion was 1.71±0.75 blood transfusions per month. The mean monthly epistaxis frequency was reported to be 2.35±1.71 while 59 (69.4%) children had 2 or more than 2 monthly episodes of epistaxis. The mean serum ferritin level was noted to be 4058±2173 ng/ml. Ultrasonography findings revealed mean spleen size to be 9.25±5.80 cm. Conclusion: The incidence of epistaxis episodes among children with β-thalassemia was very high. Chronic iron-overload seemed to be common abnormality among children with β-thalassemia that should be addressed to potentially reduce the risk of epistaxis among these children. [ABSTRACT FROM AUTHOR]

This study aims to the evaluation of an extensively used decision support tool "Statistical Down Scaling Model" (SDSM) for assessment of future variation in Precipitation (PPT), Temperature maximum (Tmax) and Temperature minimum (Tmin) of Jhelum River's Drainage Area (JRDA), Pakistan. The current framework considered the partial correlation percentage (PRP) within 46.50%, 46.06%, 35.96%, and 21.97% to evaluate the effective predictors or the predictands. The R2 values for both SDSM-M and SDSM-A models were calculated in scenarios 2.6, 4.5, and 8.5 RCPs under CIMP5 (CanESM-2). The R2 precipitation values under all scenarios ranged between 82%-88% in SDSM-M. Whereas, R2 for Tmin and Tmax was between 69%-71% and 68%-74%, respectively. For the SDSM-A model, precipitation ranged between 76.5%-80% for all scenarios, while Tmin and Tmax were found to be lying between 85%-92% and 89%-96%, respectively. Both models reflected seasonal and annual projected precipitation under RCPs 2.6, 4.5, and 8.5 from 13%-68%, 25%-69%, and 13%-71% in the 2020s-2080s, respectively. Tmin in annual models under RCP 2.6 decreased from -0.91 °C to -1.89 °C, -0.20 °C to -1.46 °C and -0.87 °C to -1.90 °C.The temperature under RCPs 2.6, 4.5, and 8.5 expressed a rise during the period 2020s-2080s from 0.04 °C to 3.75 °C, 1.02 °C to 2.62 °C, and 1.03 °C to 2.60 °C for the monthly model. Furthermore, an increasing trend was observed for Tmax from 0.01 °C to 4.18 °C, 0.01 °C to 4.49 °C and 0.12 °C to 3.90 °C in the period 2020s-2080s under RCPs 2.6, 4.5, and 8.5. The results revealed that the region will be generally warmer and wetter compared to the historical record. SDSM-A exhibited normal variation for the observed data compared to SDSM-M. It was concluded that the SDSM-A provided good results for average seasonal and annual temperatures (Tmax and Tmin). The results predicted the occurrence of more extreme events in JRDA during the 21st century. This study will be useful for water resources under different climatic conditions. [ABSTRACT FROM AUTHOR]

The present study aimed to determine the impact of climate variability on rice crops in terms of sowing and harvesting dates and crop period. The identification of sowing and harvesting dates were spotted by mask identification, variations in land surface temperature (LST) on a temporal scale in the respective months, and a field-level social inquiry. The study was conducted during a time period (1994–2017), in which geo-referenced crop samples, farmer's perception survey data, Landsat satellite images, and climate data of district Larkana were used. The analysis of satellite imageries revealed that on 20 June 1994, the rice was transplanted on 14.7% of the area of the region while it was only 7.1% of the area in 2017. Similarly, the area under rice crop in the first week of July 1994 was 18.3% compared to 8.15% during the same period in 2017. However, in the first week of October 2017, the rice crop was standing on 46.8% of the area while it was on 34.6% of the area during the year 1994 on the same date. This LST variation depicts a delay in the sowing and harvesting of the rice crop. This changing pattern is further confirmed through mean LST. Mean LST (°C) has been increasing in the sowing period of rice crop from 31.9 °C in June 1994 to 35.8 °C in June 2017, and from 32.8 °C in July 1994 to 36.8 °C in July 2017. Furthermore, the LST decreased during the harvesting period of rice crop from 31 °C in October 1994 to 28.6 °C in October 2017. The present study quantifies a delay of 15–30 days in sowing and harvesting dates of the rice crop in the district due to climate variability. [ABSTRACT FROM AUTHOR]

The optimal management of hydropower resources is highly dependent on accurate and reliable hydrological runoff forecasting. The development of a suitable runoff-forecasting model is a challenging task due to the complex and nonlinear nature of runoff. To meet the challenge, this study proposed a three-stage novel hybrid model namely IVG (ICEEMDAN-VMD-GRU), by coupling gated recurrent unit (GRU) with a two-stage signal decomposition methodology, combining improved complete ensemble empirical decomposition with additive noise (ICEEMDAN) and variational mode decomposition (VMD), to forecast the monthly runoff of SWAT river, Pakistan. ICEEMDAN decomposed the runoff time series into subcomponents, and VMD performed further decomposition of the high-frequency component obtained by ICEEMDAN decomposition. Afterward, the GRU network was employed to the decomposed subcomponents for forecasting purposes. The performance of the IVG model was compared with other hybrid models including, ICEEMDAN-VMD-SVM (support vector machine), ICEEMDANGRU, VMD-GRU, ICEEMDAN-SVM, VMD-SVM; and standalone models including GRU and SVM by utilizing statistical indices. Experimental results proved that the IVG model outperformed other models in terms of accuracy and error reduction, which indicates the feasibility of the IVG model to analyze the nonlinear features of runoff time series and for runoff forecasting with applicability for future planning and management of water resources. [ABSTRACT FROM AUTHOR]