Effect of sediment load boundary conditions in predicting sediment Delta of Tarbela Reservoir in Pakistan

Setting precise sediment load boundary conditions plays a central role in robust modeling of sedimentation in reservoirs. In the presented study, we modeled sediment transport in Tarbela Reservoir using sediment rating curves (SRC) and wavelet artificial neural networks (WA-ANNs) for setting sediment load boundary conditions in the HEC-RAS 1D numerical model. The reconstruction performance of SRC for finding the missing sediment sampling data was at R-2 = 0.655 and NSE = 0.635. The same performance using WA-ANNs was at R-2 = 0.771 and NSE = 0.771. As the WA-ANNs have better ability to model non-linear sediment transport behavior in the Upper Indus River, the reconstructed missing suspended sediment load data were more accurate. Therefore, using more accurately-reconstructed sediment load boundary conditions in HEC-RAS, the model was better morphodynamically calibrated with R-2 = 0.980 and NSE = 0.979. Using SRC-based sediment load boundary conditions, the HEC-RAS model was calibrated with R-2 = 0.959 and NSE = 0.943. Both models validated the delta movement in the Tarbela Reservoir with R-2 = 0.968, NSE = 0.959 and R-2 = 0.950, NSE = 0.893 using WA-ANN and SRC estimates, respectively. Unlike SRC, WA-ANN-based boundary conditions provided stable simulations in HEC-RAS. In addition, WA-ANN-predicted sediment load also suggested a decrease in supply of sediment significantly to the Tarbela Reservoir in the future due to intra-annual shifting of flows from summer to pre- and post-winter. Therefore, our future predictions also suggested the stability of the sediment delta. As the WA-ANN-based sediment load boundary conditions precisely represented the physics of sediment transport, the modeling concept could very likely be used to study bed level changes in reservoirs/rivers elsewhere in the world

Carbohydrate mediated drug delivery: Synthesis and characterization of new lipid-conjugates

AbstractA new synthetic methodology for cationic glycolipids using p-aminophenyl-α-d-mannopyranoside (PAPM), p-aminophenyl-α-d-galactopyranoside (PAPG) was developed. PAPM-lipids and PAPG-lipids conjugates were also synthesized for targeting drugs to receptors. A binding inhibition study of synthesized p-(dimethylamino butylamido) phenyl-α-d-mannopyranoside (1a) with Concanavalin A was performed using invertase enzyme. In addition, transfection of pSV-β-gal reporter gene with was investigated in A549 cells

Green Nano-synthesis: Salix alba Bark-Derived Zinc Oxide Nanoparticle and their nematicidal Efficacy against root knot nematode Meloidogyne incognita

Background: Plant parasitic nematodes (PPNs) are considered major agriculture pests, causing significant damage to crops by directly targeting the plant root system to prevent water and nutrient uptake. One of its major species, Meloidogyne incognita, is considered a serious threat to agriculture crop production worldwide. The current study was intended to evaluate the potential of Nanoparticles synthesized from Salix alba bark extract as nematicidal agent.Methods: Phytochemical analyses of Salix alba bark extract were conducted, and nanoparticles of the same extract were synthesized and characterized using UV-vis spectroscopy, XRD (X-Ray Diffraction), SEM (Scanning Electron Microscopy) and EDX (Energy Dispersive X-ray Spectroscopy) techniques. Results: The qualitative phytochemical analysis of Salix alba bark extract revealed the presence of phenolics, flavonoids, reducing sugars, and saponins. When applied on juveniles of the plant parasitic nematode Meloidogyne incognita, the nanoparticles demonstrated a dose and time-dependent impact. After 24 hours, the highest concentration (1000 µg/ml) of nanoparticles exhibited the greatest mortality, reaching 82.2%, while the lowest concentration resulted in a mortality rate of 34.5%. Similarly, at the 48-hour mark, the highest mortality (92.2%) was observed with 1000 µg/ml of nanoparticles, whereas the lowest concentration yielded a mortality rate of 54.5%. Extending the observation period to 72 hours, the mortality rate peaked at 98.33% with the highest nanoparticle concentration (1000 µg/ml), and the lowest mortality rate was recorded at the lowest dose, amounting to 72.5%. These results underscore the dose and time-dependent efficacy of Salix alba bark-derived nanoparticles against Meloidogyne incognita. Conclusion: Our findings suggest that zinc oxide nanoparticles synthesized from Salix alba bark can be an effective agent against plant parasitic nematode Meloidogyne incognita. Further experiments are recommended to study the impact of these nanoparticles on other biotic stresses

The Effectiveness of the ‘Extended Sick Neonatal Score in Predicting Mortality in a ResourceConstrained Neonatal Care Uni

Objectives: To determine the diagnostic accuracy of the extended sick neonatal score (ESNS) in neonates admitted in a resource-limited neonatal intensive care unit (NICU) at Peshawar. Study Design: Cross-sectional analytical study Place and Duration of Study: Neonatal Intensive Care Unit, CMH Peshawar Pakistan, from Mar to May 2020. Methodology: Primary data was collected from 60 neonates admitted to NICU after taking consent from the parents. The receiver operating characteristic curve (ROC) was plotted to determine the clinical score (ESNS) cut-off value in predicting mortality. Result: The sensitivity and specificity of the Extended sick neonatal score to predict mortality among neonates was 93.3% and 97%, respectively, for a cut-off of 12.5. The area under the ROC curve was 0.990 (95% CI: 0.971–1.000). This was statistically significant with a p-value of <0.001 Conclusion: Extended Sick Neonatal score is an important tool that helps predict the risk of mortality of a neonate without the help of any invasive diagnostic procedure, thus enhancing the prioritization of health care to the most deserving neonates

Financial and social efficiency of microcredit programs of partner organizations of Pakistan Poverty Alleviation Fund.

This paper examines the financial and social efficiency of the microcredit programs offered by the Pakistan Poverty Alleviation Fund partner organizations. Panel data concerning variables of interest are collected from Pakistan Microfinance Network, covering a minimum of 14 partner organizations (in 2005) to a maximum of 35 partner organizations (in 2014). The data is analyzed using the Data Envelopment Analysis, assuming both constant and variable returns to scale scenarios and the operational scale of the partner organizations. Trends in average efficiency scores have been analyzed to assess the mission drift of the partner organizations. Results reveal that managerial inefficiency is more pronounced than the sub-optimal production scale in all three scenarios under consideration. Moreover, trends in the efficiency scores indicated a slight mission drift of the microfinance providers. About 77.5% of the partner organizations were financially sustainable over the entire study period. The study recommends providing objective-oriented training, workshops, and seminars for managing microfinance providers

A Quality of Service-Aware Secured Communication Scheme for Internet of Things-Based Networks

The Internet of Things (IoT) is an emerging technology that aims to enable the interconnection of a large number of smart devices and heterogeneous networks. Ad hoc networks play an important role in the designing of IoT-enabled platforms due to their efficient, flexible, low-cost and dynamic infrastructures. These networks utilize the available resources efficiently to maintain the Quality of Service (QoS) in a multi-hop communication. However, in a multi-hop communication, the relay nodes can be malicious, thus requiring a secured and reliable data transmission. In this paper, we propose a QoS-aware secured communication scheme for IoT-based networks (QoS-IoT). In QoS-IoT, a Sybil attack detection mechanism is used for the identification of Sybil nodes and their forged identities in multi-hop communication. After Sybil nodes detection, an optimal contention window (CW) is selected for QoS provisioning, that is, to achieve per-flow fairness and efficient utilization of the available bandwidth. In a multi-hop communication, the medium access control (MAC) layer protocols do not perform well in terms of fairness and throughput, especially when the nodes generate a large amount of data. It is because the MAC layer has no capability of providing QoS to prioritized or forwarding flows. We evaluate the performance of QoS-IoT in terms of Sybil attack detection, fairness, throughput and buffer utilization. The simulation results show that the proposed scheme outperforms the existing schemes and significantly enhances the performance of the network with a large volume of data. Moreover, the proposed scheme is resilient against Sybil attack