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Land Use/Land Cover (LU/LC) change is among the dominant driving factors that directly influence water balance by transforming hydrological responses. Consequently, a thorough comprehension of its impacts is imperative for sustainable water resource planning and development, notably in developing worlds such as Pakistan, where agriculture is a major livelihood. This research intends to assess the continuing changes in LU/LC and evaluate their probable repercussions on the hydrological regime of the Potohar Plateau. The maximum likelihood classification (MLC) algorithm for land use classification of the high-resolution satellite imageries, the Cellular-Automata Markov Chain Model (CA-MCM) for the projection of LU/LC maps, and the Soil and Water Assessment Tool (SWAT) in tandem with SWAT-CUP for hydrological modeling were employed in this research. The high-resolution climatic dataset (10 × 10 km) was used in SWAT. The LU/LC analysis revealed a continual propagation of agricultural and built-up lands at the detriment of forest and barren land during the last three decades, which is anticipated to continue in the future, too. Hydrological model calibrations and validations were performed on multi-basins, and the performance was evaluated using different statistical coefficients, e.g., the coefficient of determination (R2), Nash–Sutcliffe Efficiency (NSE), Kling–Gupta Efficiency (KGE), and Percent Bias (PBIAS). The results yielded that the model performed very well and demonstrated the model's robustness in reproducing the flow regime. The water balance study revealed that the anticipated LU/LC changes are projected to decrease the mean annual surface runoff, water yield, and streamflow due to an increase in percolation, lateral flow, sub-surface flow, and evapotranspiration. More significant variations of the water balance components were observed at the sub-basin level, owing to the heterogeneous spatial distribution of LU/LC, than at the basin level. The outcome of this study will provide pragmatic details to legislative bodies to develop land and water management ameliorative strategies to harness hydrological changes sustainably. [ABSTRACT FROM AUTHOR]

Wheat yellow/stripe rust pathogen Puccinia striiformis is highly diverse and recombinant in the north of Pakistan in the Himalayan region. However, little is known about the role of this diversity in disease epidemics in areas where wheat yellow rust is an important disease in both irrigated and rain-fed wheat (i.e., in the plains of Pakistan). We explored the population diversity in P. striiformis during the rust epidemics of 2013 in the major wheat-growing regions of Pakistan (the Himalayan region, central Khyber Pakhtunkhwa [KP], southern KP, central and northern Punjab). Disease severities among commonly grown cultivars ranged from 5% to 100%. Microsatellite genotyping with 16 simple sequence repeat (SSR) markers revealed a high diversity among 266 isolates collected during the season, with the Simpson diversity index (Simpson 1949) ranging from 0.870 (Himalayan) to 0.955 (southern KP). The recombination signature was stronger in the Himalayan population and central KP compared with wheat-growing regions of Punjab and southern KP. The overall diversity was higher in Pakistan relative to the clonal populations present in Europe, Australia, and the Americas. Analyses of population subdivision revealed no clear evidence of spatial structure for samples from Pakistan, with a maximum fixation index (FST) value of only 0.10. The lack of clear population subdivision could be attributed to migration of pathogen. In turn, the high diversity of P. striiformis in Pakistan represents a potential threat to wheat production in the region and worldwide, as a possible source to found clonal populations in diverse wheat-growing areas. [ABSTRACT FROM AUTHOR]

The stock market is one of the imperative indicators of the economy. This study strived to explore the impact of five macroeconomic variables on General Index in the long run and short run. In order to investigate the long run and short run relationships Johansen cointegation technique and VECM was applied. This study used monthly data from November 1991 to June 2008 for analysing General Index. The study revealed that consumer price index, and real effective exchange rate, and industrial production index had a positive impact on stock prices in Pakistan while money supply and three month treasury bills rate affected stock prices negatively in the long run. The VECM demonstrated that it took more than eight months to eliminate the disequilibrium. The variance decompositions exposed that consumer price index and money supply showed greater forecast error than real effective exchange rate, industrial production index, and three month treasury bills rate for General Index. [ABSTRACT FROM AUTHOR]

Biased distribution of hydro-climate stations in high elevations are major obstacles for reliable appraisal of the hydro-climatic regime of the Chitral Basin located in the extreme north of Pakistan. We modeled this regime in the ARC-SWAT hydrological model forced with the latest gridded reanalysis ERA5 Land dataset, bias-corrected against a good quality reference dataset. The performance of the gridded dataset was cross-validated by comparing the model flow simulation against the observed flows. The ERA5 Land overall provided reasonably good estimates. The calibrated model on the daily time scale was able to provide excellent values of the employed statistical measures (NSE, KGE, PBIAS, RMSE and MAE). For a future climate change analysis, climate series was devised using two future projection scenarios (RCP4.5 and RCP8.5) using the best performing GCM (MIROC5_rlilp1) out of five investigated GCMs. The results of the climate change analysis reveal increment in the average temperature up to +3.73 °C and +5.62 °C for RCP4.5 and RCP8.5, respectively, while the analysis of precipitation suggests an annual decrease up to −16% and −35% against RCP4.5 and RCP8.5, respectively, by the end of century. A future simulated flow analysis showed an increment of +0.25 % and decrease of −6.82% for RCP4.5 and RCP8.5, respectively. Further analysis of climate suggests seasonal deflections especially in precipitation and flow regimes. A notable climb in flow quantities was observed during spring season (MAM) in spite of the major reduction in precipitation amounts for that season. This implicitly supports a high rate of glacial/snow melt especially in the spring season during that period. Frequent droughts and floods are also projected by examining flow durations at each interval of the 21st century. [ABSTRACT FROM AUTHOR]

The basic objective of the irrigation reforms, i.e., participatory irrigation management in Pakistan, was a better economic and financial management of irrigation service delivery, equity in water distribution, and better environmental outcome. The aim of this study was to assess the optimism with the reforms package that has actually delivered expected outcomes. For this purpose, this study used a cross-sectional dataset of 567 farmers in five selected Area Water Boards (AWBs) of Punjab and Sindh provinces of Pakistan. Important institutional features including compliance, adaptiveness, clarity of objectives, good interaction, and appropriate scale, were modeled through structural equation modeling on the overall performance assessment of water use associations from a farmer's perspective. Results suggested that clear objectives, adaptiveness, scale, and compliance show a strong relationship with an overall assessment of performance. While good interaction has not impacted significantly with an overall performance assessment. The impact of institutional feature on the overall performance assessment depends on the nature of performance considered, e.g., drivers of the economic performance of a farmer organization may not be the same as the drivers of its environmental performance. Besides offering insights on specific drivers that matter for a particular dimension of the institutional performance of farmer organizations, the study suggests that participatory irrigation management institutions are still in infancy even after decades of their introduction, and just creating institutions is neither mandatory nor sufficient. Furthermore, the institutional designs are considered critical for the success of participatory institutions. Therefore, there is a need to consider the conformity of the strategies with the existing norms and compliance to the on-going procedures. [ABSTRACT FROM AUTHOR]

A study was conducted under the laboratory conditions in the Department of Zoology, Wildlife and Fisheries, University of Agriculture, Faisalabad, Pakistan during 2014 to investigate the effect of supplementation of lysine on nutrient digestibility in the juveniles of Labeo rohita. Seven experimental diets were formulated by supplementing 0, 0.5, 1, 1.5, 2, 2.5 and 3% lysine and designated as D1, D2, D3, D4, D5, D6 and D7, respectively. To test each diet, two replicates with 20 fish each (average weight 3.526±0.056g) were assigned. The experiment was performed within the time duration of 60 days. Water quality parameters like dissolved oxygen (5.8-7.3 mg/L), temperature (24.9-28.7°C) and pH (7.4-8.6) were maintained throughout this period. Results showed that lysine supplementation in fish diet increased the digestibility of crude protein and dry matter. Maximum digestibility of crude protein and dry matter was observed at lysine level of 1.5 and 2.5%, respectively. However, it was observed that digestibility of crude fat decreased in response to lysine supplementation. In conclusion, it was found that lysine supplementation improved the nutrient digestibility performance of juveniles of L. rohita. [ABSTRACT FROM AUTHOR]

Maize is a globally significant food crop but its future sustainability under rainfed conditions is at risk due to climate change and increased climate uncertainty. In Pakistan most maize is rainfed but there is increasing interest in the role of supplemental irrigation to reduce the vulnerability of crop yields to future drought and climate risks. Using a crop model (DSSAT CERES-Maize) with downscaled data from a weather generator (LARS-WG) and for five selected GCMs, two RCPs (4.5 and 8.5) and two time slices (2050s and 2080s), this study assessed the impacts of climate change and climate variability on rainfed maize grown in the Pothwar region of Pakistan, and the extent to which irrigation could offset future yield reductions. Model simulations were calibrated and validated using experimental data from 2021 and 2022. The outputs showed that on average the yield of maize could be increased by 55% with a single irrigation of 60 mm during the reproductive stage. For the baseline (1991–2020) the average rainfed yield was 3370 kg/ha. The climate change scenarios for the 2050s indicated a −13.5% and −5.8% decline in rainfed yield under RCP4.5 and RCP8.5, respectively. Irrigation applications (between 162 mm and 180 mm) increased grain yields by 5615 kg/ha and 5732 kg/ha, respectively. For the 2080s scenarios there was a projected decrease in yield by - 9.3% and - 39.7% under RCP4.5 and RCP8.5, respectively. Modelling also confirmed significant reductions in maize biomass production which would negatively impact on feedstocks for both livestock and renewable energy generation. • Supplemental irrigation can increase maize yields by up to 55% in the Pothwar region. • Climate change will increase dependence on supplemental irrigation to ensure future maize production is sustainable. • Policy reforms to support improved irrigation management are needed to avoid significant economic losses. [ABSTRACT FROM AUTHOR]

This paper illustrates the importance of monitoring health facility-level information to monitor changes in maternal mortality risks. The annual facility-level maternal mortality ratios (MMRs), complications to live births ratios and case fatality ratios (CFRs) were computed from data recorded during 2007 and 2009 in 31 upgraded public sector health facilities across Pakistan. The facility-level MMR declined by about 18%; both the number of Caesarean sections and the episodes of complications as a percentage of live births increased; and CFR based on Caesarean sections and episodes of complications declined by 29% and 37%, respectively. The observed increases in the proportion of women with complications among those who come to these facilities point to a reduction in the delay in reaching facilities (first and second delays; Thaddeus & Maine, 1994); the decrease in CFRs points to improvements in treating obstetric complications and a reduction in the delay in receiving treatment once at facilities (the third delay). These findings point to a decline in maternal mortality risks among communities served by these facilities. A system of woman-level data collection instituted at health facilities with comprehensive emergency obstetric care is essential to monitor changes in the effects of any reduction in the three delays and any improvement in quality of care or the effectiveness of treating pregnancy-related complications among women reaching these facilities. Such a system of information gathering at these health facilities would also help policymakers and programme mangers to measure and improve the effectiveness of safe-motherhood initiatives and to monitor progress being made toward achieving the fifth Millennium Development Goal. [ABSTRACT FROM PUBLISHER]

• Manual identification of different fish species is a difficult task. • We proposed a framework based on the CNN for fish species identification. • The proposed CNN architecture contains 32 deep layers. • We developed a data set termed as Fish-Pak from the tropical area of Pakistan. • The proposed CNN architecture is compared with state of the art CNN models. Morphological based fish species identification is an erroneous and time-consuming process. There are numerous fish species and due to their close resemblance with each other, it is difficult to classify them by external characters. Recently, computer vision and deep learning-based identification of different animal species is being widely used by the researchers. Convolutional Neural Network (CNN) is one of the most analytically powerful tools in deep learning architecture for the image classification based on visual features. This work aims to propose a deep learning framework based on the CNN method for fish species identification. The proposed CNN architecture contains 32 deep layers that are considerably deep to derive valuable and discriminating features from the image. The deep supervision is inflicted on the VGGNet architecture to increase the classification performance by instantly adding four convolutional layers to the training of each level in the network. To test the performance of proposed 32-Layer CNN architecture, we developed a dataset termed as Fish-Pak and is publicly available at Mendeley data (Fish-Pak: https://doi.org/10.17632/n3ydw29sbz.3#folder-6b024354-bae3-460a-a758-352685ba0e38). Fish-Pak contains 915 images with six distinct classes; Ctenopharyngodon idella (Grass carp), Cyprinus carpio (Common carp), Cirrhinus mrigala (Mori), Labeo rohita (Rohu), Hypophthalmichthys molitrix (Silver carp), and Catla catla (Thala) and three different image views (head region, body shape, and scale). To ensure the superior performance of proposed CNN architecture, we have carried out the experimental comparison with other deep learning frameworks involving VGG-16 for transfer learning, one block VGG, two block VGG, three block VGG, LeNet-5, AlexNet, GoogleNet, and ResNet-50 on the Fish-Pak data set. Comprehensive empirical analyses reveal that the proposed method achieves state of the art performance and outperforms existing methods. [ABSTRACT FROM AUTHOR]

Wheat powdery mildew possesses a significant threat to wheat crops not only on a global scale but also in the northern region of Pakistan. Recognizing the need for effective measures, the exploration and utilization of exotic germplasm take on critical importance. To address this, a series of trials were made to investigate the response of 30 European (EU) lines, in addition to the local checks (Siran, Atta-Habib (AH) and Ghanimat-e-IBGE) against wheat powdery mildew at the Himalayan region of Pakistan. The study involved field testing from 2018 to 2022 across multiple locations, resulting in 38 different environments (location × year). In addition to field evaluations, molecular genotyping was also performed. The disease was absent on the tested lines during 2018, 2019, and 2020 whereas it ranged from 0 to 100% at Chitral location during 2021, where 100% was observed only for one EU wheat line "Matrix." The disease prevailed only at Gilgit location (0-60% for EU wheat line "F236") and at Nagar location (0-10% for EU wheat lines Substance and Nelson) during the disease season of 2022. Most of the EU wheat lines showed very low ACI values, due to an overall low disease pressure. Matrix showed the maximum ACI (1.54) followed by Ritter (1.25) and Bli_autrichion (0.87), whereas the minimum (0.1) was for Substance, JB_Asano, and KWS_Loft followed by Canon (0.19), all exhibiting partial resistance. The molecular marker-based screening revealed that Pm38 was the most prevalent and detected in 100% of wheat lines followed by Pm39 (60%) and Pm8 (30%). Six wheat lines (20%) possessed all three Pm genes (Pm8, Pm38, and Pm39) concurrently. The variability observed in this study can be utilized in future breeding efforts aimed at developing resistant wheat varieties., (© 2023. The Author(s), under exclusive licence to Institute of Plant Genetics Polish Academy of Sciences.)

Background: Urethral stricture disease has significant economic impact throughout world. The bulbar urethra is the commonest site for urethral strictures (Approx 50%) followed by penile urethra in most of the published literature. In developing countries trauma (road traffic accident and iatrogenic) is the leading cause of urethral stricture disease. Younger patients have usually idiopathic type as compare to old age group, which present more frequently with iatrogenic and trauma related urethral strictures., Methods: This Qausi Experimental study was conducted from May2012-June2016 of duration at Liaquat National Hospital Karachi. All the patients diagnosed with short urethral strictures related to bulbar urethra were included in this study. All the patients underwent non transecting bulbar urethroplasty. All patients were assessed preoperatively, peri-operatively and postoperatively and on follow-up visits as; on 2nd, 8th and 24th week. All the data regarding outcome was recorded on the Performa and analyzed on SPSS V20., Results: Total of 179patients were included, mean age was 38±SD15.3years (range 20- 65years). Anatomically bulbar urethra was affected in 52% of the cases followed by bulbopenile, bulbomembranous region. Etiologically idiopathic type was found in 40% cases, while trauma 21%, iatrogenic injury 26% and UTI 13% were also reasons. Stricture length was mean1.1±SD 1.4 cm (range 0.5-2.5cm). Preoperative Uroflowmetry revealed mean Qmax of 10.5±SD 5.3 ml/sec. Mean operative time was 35±SD 4.6 minutes, 7 patients had conversion to other procedures (3.91%), Postoperative complications were minimal. Mean follow up was 12±SD 21 months (range 6 months to 3 years). On initial follow up at 8th week and 24th week, Qmax was significantly improved. Only 3 patients required DVIU after the 24th week. Initial success rate after 24th week was 98.3% and eventually 100% at the long-term follow-up., Conclusions: non-transecting anastomotic bulbar urethroplasty (NTABU) is a new standard of care for the short bulbar urethral stricture up to 2.5cm. Idiopathic aetiology, iatrogenic and posttraumatic urethral strictures in selective patients can safely be operated with this technique.