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Railway projects are incredibly costly due to their complex nature. This study performs risk analysis and management of Pakistan railways ML-1 project expansion and upgradation that will be undertaken at US$6.8 billion under the China-Pakistan Economic Corridor (CPEC). The risks were identified based on an extensive literature review and their relevance to the CPEC. We employed fuzzy set theory (integrated with the risk severity index) to obtain the most severe risks. The novelty of this study is the technique employed to analyse and rank the risk, also there are no previous studies conducted that emphasized the construction risk of railway projects in Pakistan. The study is useful for all stakeholders of the project, as it can plan for them to tackle these risks and implement ML-1 successfully.

Image segmentation and identification are crucial to modern medical image processing techniques. This research provides a novel and effective method for identifying and segmenting liver tumors from public CT images. Our approach leverages the hybrid ResUNet model, a combination of both the ResNet and UNet models developed by the Monai and PyTorch frameworks. The ResNet deep dense network architecture is implemented on public CT scans using the MSD Task03 Liver dataset. The novelty of our method lies in several key aspects. First, we introduce innovative enhancements to the ResUNet architecture, optimizing its performance, especially for liver tumor segmentation tasks. Additionally, by harassing the capabilities of Monai, we streamline the implementation process, eliminating the need for manual script writing and enabling faster, more efficient model development and optimization. The process of preparing images for analysis by a deep neural network involves several steps: data augmentation, a Hounsfield windowing unit, and image normalization. ResUNet network performance is measured by using the DC metric Dice coefficient. This approach, which utilizes residual connections, has proven to be more reliable than other existing techniques. This approach achieved DC values of 0.98% for detecting liver tumors and 0.87% for segmentation. Both qualitative and quantitative evaluations show promising results regarding model precision and accuracy. The implications of this research are that it could be used to increase the precision and accuracy of liver tumor detection and liver segmentation, reflecting the potential of the proposed method. This could help in the early diagnosis and treatment of liver cancer, which can ultimately improve patient prognosis.

Climate change and salt-affected soils detrimentally affect crop production in arid regions. Reclaiming these soils for crops and carbon sequestration can mitigate climate change and enhance food security. A laboratory-scale experiment was conducted on a wheat-maize crop rotation system for three consecutive years to check the effectiveness of organic amendments in reclaiming marginally salt-affected soils, improving soil health, sequestering carbon, and improving food grain production. This study included five treatments namely control (T1), gypsum alone at 100% gypsum requirements (G100), and its combinations with different organic amendments and 50% gypsum requirements (farm manure (FYM+G50), poultry manure (PM+G50), and green manure (GM+G50)) were used. Results indicated that sandy clay loam textured soil showed highest potential for its properties improvement after 45 days, i.e., EC decreased up to 3.9 dS m−1, pH 7.9 and, SOC increase up to 0.25%. After the fallow period, three consecutive years of crop production study indicated up to 39 and 70% increase in wheat and maize yields, respectively, compared to inorganic fertilizer alone. Maximum soil aggregation was noted in treatment with gypsum and farmyard manure application in loam soils (50%). The maximum soil organic carbon accumulation over the whole experiment was recorded in farmyard manure application in combination with gypsum (0.44 g kg−1) in both loam and sandy clay loam soil, while 0.31 g kg−1 in the clay loam soil. Based on the results, it was concluded that reclaiming marginally salt-affected soils enhances food crop production and incorporating manures improves soil through aggregation and carbon sequestration, mitigating climate change. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to investigate the status of antimicrobial‐resistant strains of Staphylococcus aureus in Pakistan, their association in terms of co‐occurrence with the biofilm‐forming genes, resistance profiling and associated discrepancies in diagnostic methods. Methodology: A total of 384 milk samples from bovine was collected by using convenient sampling technique and were initially screened for subclinical mastitis, further preceded by isolation and confirmation of S. aureus. The S. aureus isolates were subjected to evaluation of antimicrobial resistance by phenotypic identification using Kirby–Bauer disc diffusion method, while the genotypic estimation was done by polymerase chain reaction to declare isolates as methicillin, beta‐lactam, vancomycin, tetracycline, and aminoglycoside resistant S. aureus (MRSA, BRSA, VRSA, TRSA, and ARSA), respectively. Results: The current study revealed an overall prevalence of subclinical mastitis and S. aureus to be 59.11% and 46.69%, respectively. On a phenotypic basis, the prevalence of MRSA, BRSA, VRSA, TRSA, and ARSA was found to be 44.33%, 58.49%, 20.75%, 35.84%, and 30.18%, respectively. The results of PCR analysis showed that 46.80% of the tested isolates were declared as MRSA, 37.09% as BRSA, and 36.36% as VRSA, while the occurrence of TRSA and ARSA was observed in 26.31% and 18.75%, respectively. The current study also reported the existence of biofilm‐producing genes (icaA and icaD) in 49.06% and 40.57% isolates, respectively. Lastly, this study also reported a high incidence of discrepancies for both genotypic and phenotypic identification methods of resistance evaluation, with the highest discrepancy ratio for the accA‐aphD gene, followed by tetK, vanB, blaZ, and mecA genes. Conclusion: The study concluded that different antibiotic resistance strains of S. aureus are prevalent in study districts with high potential to transmit between human populations. The study also determined that there are multiple resistance determinants and mechanisms that are responsible for the silencing and expression of antibiotic resistance genes. [ABSTRACT FROM AUTHOR]

In this article, a fuel tank is coupled with gyrostat in a moving spacecraft to discuss its dynamical behaviour and bringing stability in velocity vectors. Parametric study is performed using Hopf bifurcation to find the bifurcation parameter for a considered mechanical model. Furthermore, a region is constructed in which negligible limit cycles appear around unstable spirals for angular momentum greater than bifurcation point. Based on local dynamical analysis, trajectories of angular velocities are observed with respect to damping constant, which is formulated in the form of bifurcation parameter. Moreover, a controller is designed in this article for considered dynamical system by achieving global stability, with the help of Lyapunov theory, into the spacecraft coupled with filled fuel tank, and their results are compared with effective spacecraft control strategies to observe the effectiveness of our proposed control technique. Finally, in presented research, numerical simulations are performed using MATLAB for validation of analytical results, which the authors have achieved for Hopf bifurcation and designed controller.