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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]

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.

School mapping being a form of local planning is dealt as a local subject but has national and international impacts. This is a dynamic process which initiates with detailed diagnoses of the local situation, and on the basis of national objectives and international norms, provides for future educational needs at the local level and to indicates the obligatory measure required to achieve these needs. Ironically, local and national planners in Kyhber Pakhtunkhwa and Pakistan still show reluctance in using School Mapping Techniques. As a result the resources are misused, supervision becomes difficult and ghost and un-operational schools are not uncommon. This qualitative study focuses to address the customary conditions of school mapping in twenty four districts of Khyber Pakhtunkhwa for diagnosis of the major factors that make the educational planners reluctant and in addition to determine the causes of not realizing its importance in Educational Management Information System (EMIS). This makes the study unique as no such effort has ever made before in the area to probe the matter and suggest remedies. Data were collected by means of interview schedule with dealing EMIS managers at provincial level of Khyber Pakhtunkhwa Province and Executive District Officers of Peshawar, Nowshera, Mardan, Kohat, Karak, Charsadda, Abbottabad and Mansehra districts while from the rest of sixteen districts telephonic conversation was focused as a major tool for collecting data. The results show that respondents both at Provincial and District level are well aware of the importance of school mapping but were reluctant to implement it practically due to very minor or no reasons.

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]

Metal-oxide-based gas sensors are extensively utilized across various domains due to their cost-effectiveness, facile fabrication, and compatibility with microelectronic technologies. The copper (Cu)-based multifunctional polymer-enhanced sensor (CuMPES) represents a notably tailored design for non-invasive environmental monitoring, particularly for detecting diverse gases with a low concentration. In this investigation, the Cu-CuO/PEDOT nanocomposite was synthesized via a straightforward chemical oxidation and vapor-phase polymerization. Comprehensive characterizations employing X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM), X-ray diffraction (XRD), and micro Raman elucidated the composition, morphology, and crystal structure of this nanocomposite. Gas-sensing assessments of this CuMPES based on Cu-CuO/PEDOT revealed that the response current of the microneedle-type CuMPES surpassed that of the pure Cu microsensor by nearly threefold. The electrical conductivity and surface reactivity are enhanced by poly (3,4-ethylenedioxythiophene) (PEDOT) polymerized on the CuO-coated surface, resulting in an enhanced sensor performance with an ultra-fast response/recovery of 0.3/0.5 s. [ABSTRACT FROM AUTHOR]

Organophosphates are toxic compounds commonly used in agriculture, industry and warfare, making their detection a critical issue for public health and safety. Gold nanoparticles have emerged as a promising tool for the detection of organophosphates due to their unique optical properties and surface chemistry. This review discusses the various methods for synthesizing gold nanoparticles and their functionalization for improved organophosphate detection. The sensitivity and selectivity of the detection method are also discussed, as well as its potential applications in environmental monitoring, food safety, clinical diagnosis and industrial applications. The use of gold nanoparticle-based detection methods for organophosphates has the potential to provide a rapid, sensitive and reliable tool for the detection and monitoring of these toxic compounds in various fields. [ABSTRACT FROM AUTHOR]