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Fibre reinforcement strategies for enhancing ductile behaviour in concrete elements
Full text linkSteel is costly and detrimental to the environment when used as a reinforcement. Another technique for reinforcing concrete is fibre reinforcement. Fibre is a small amount of reinforcing material with specific properties. Fibre-reinforced concrete has several uses and is available in several shapes. Cellulose fibre, glass fibre, steel wire fibre and steel raw material have the following percentages: 0.5%, 0.7%, and 1%; 0.3%, 0.6%, and 1%; and 0.5%, 1%, and 1.5%, respectively. Specific percentages of different fibres, ranging from 0.3% to 1.5%, are employed in this study to assess the ductile behaviour of concrete since the primary objective of utilising these fibres is to enhance the ductile qualities of concrete. The fibre-added specimens are subjected to four distinct kinds of tests. It has been demonstrated that concrete’s flexural strength, split cylinder strength, and double punching strength have increased by up to 28%, 60%, and 93%, respectively, compared to the control mix concrete. Steel and raw material fibre exhibited no detrimental impacts on compression at certain percentages; however, glass fibre and cellulose fibre reinforcements had detrimental effects, reducing the compressive strength by up to 33.5% and 49.3%, respectively
Investigating socioeconomic development in the absence of local government in Gilgit Baltistan, Pakistan
Full text linkThis paper examines the extent to which local governance serves as a foundation for socio-economic development at the grassroots level. Local government is pivotal in fostering citizen participation in decision-making processes, promoting community development, enhancing inclusivity, and implementing welfare initiatives. The Gilgit-Baltistan Governance Order 2018 marked a significant legal and political milestone, laying the groundwork for decentralized governance. This study explores the socio-economic development of Gilgit-Baltistan in the absence of a functioning local government system. Data was collected through interviews with key stakeholders, including bureaucrats, Members of the Legislative Assembly (MLAs), and local NGOs. The findings reveal that bureaucratic inertia and a lack of political will among leadership have hindered the establishment of a “democratic nursery” in the region. Participants strongly recommend reinstating local governments and delegating powers to these bodies to enhance socio-economic development, enforcing zoning regulations to prevent unregulated development, and preserving green spaces to maintain ecological balance through checks and balances
Governance and power dynamics in the Princely States of the Northwest Frontier, Pakistan: a historical overview
Full text linkThis research study focuses on the political, administrative, and judicial history of the former princely states during British rule, which were annexed to Pakistan after 1947 as special autonomous territories administered under federal-cum-provincial jurisdiction as the Provincially Administered Tribal Areas (PATA) after 1969. This study covers the princely state\u27s accession to Pakistan, its constitutional and political development during the British occupation, and its constitutional status under the 1956 and 1962 constitutions of Pakistan. Moreover, this study analyses the strategic importance of princely states to British India and of PATA to Pakistan, as well as the reasons for the comparatively longer survival of princely states, and the integration of princely states into Pakistan in 1947 as PATA. The study has thoroughly analysed the governance systems of the princely states and identified the gaps during the princely rule and after they were formally annexed to Pakistan’s mainstream as special regions. The findings reveal that the British and Pakistan have used these areas for strategic purposes, and the democratic setup was not intentionally extended to these regions. The areas still need special attention for the provision of basic infrastructure, improvement of the governance structure and measures for economic development
Investigation and classification of bone fracture using a deep learning model
Full text linkBone fractures represent a large percentage of medical cases worldwide, requiring accurate and precise detection to improve patient results. The current work, therefore, suggests a new deep learning model for detecting and classifying bone fractures from medical images that addresses the limitations of traditional diagnostic methods. Leveraging the power of Convolutional Neural Networks (CNNs), the model learns imaging data, identifies subtle fracture features, and labels them with high accuracy into the pre-existing categories. They trained their model on a comprehensive dataset comprising numerous triaged and undistributable fractures, which was coupled with data augmentation to improve the model’s robustness to variation in clinical presentation. Systematic regularisation strategies applied throughout the training prevented overfitting and improved model generalizability. Preliminary results indicate strong levels of accuracy, suggesting that the model can potentially complement or replace traditional diagnostic pathways. Implementing advanced AI-based systems into clinical workflows may transform radiology by speeding up diagnostic workflows and improving uniformity for identifying fractures. This research represents progress in the science behind automated fracture diagnosis techniques and the importance of artificial intelligence in healthcare, currently in implementing solutions to complex diagnostic challenges and improvements in related patient care outcomes
AI-based skin cancer detection algorithms: opportunities, challenges and a way forward
Full text linkSkin cancer is a significant global health concern. Early and accurate detection is crucial for enhancing patient outcomes. This study conducts an in-depth literature review to identify commonly used Convolutional Neural Network (CNN) variants, datasets, and key evaluation metrics to assess their performance in classifying benign and malignant skin lesions. Widely used CNN architectures, including ResNet, EfficientNet, DenseNet, AlexNet, VGG, GoogleNet, LeNet-5, Xception, and MobileNet were implemented. A comparative analysis is conducted based on metrics such as accuracy, precision, sensitivity, recall, and F1-score, highlighting the strengths and limitations of each algorithm. The results show that VGG-16 outperforms other models with an accuracy of 97%, followed by VGG-19 and Mobilenet-v2 with 88%. Lastly, this paper highlights the trade-offs between various metrics, providing critical insights for deploying AI-based skin cancer detection algorithms in clinical practice
Enhancing thermal stability and viscosity of cellulose ether using propylene carbonate as a transesterification agent for oilfield applications
Full text linkThis study presents the utilisation of Propylene Carbonate (PC), along with an alkali-based solution, to modify the Hydroxyethyl Methyl Cellulose (HEMC) polymer to mitigate the thermal degradation of cellulose ether. The experimental results from FTIR and XRD analysis confirmed the addition of a new function group to the HEMC backbone and the formation of a new organic carbonate-based cellulose ether. Shear viscosity experiments were conducted at concentrations of 0.50-wt.% to 2-wt.% at ambient and elevated temperatures ranging from 80°C-110°C using a rheometer. All polymeric solutions exhibited shear-thinning behaviour, and the viscosity of polymeric solutions was enhanced by increasing the concentration of modified HEMC solutions. The modified HEMC solutions exhibited higher viscosity at 1000 s-1 shear rate at 110ºC compared to the native HEMC solutions, confirming the enhanced thermal stability of the PC-based modified HEMC solution. Alkali-based modified HEMC solution exhibited low shear viscosity at ambient temperature. The alkali-based polymeric solution’s viscosity was increased by 48% at a high shear rate at 110ºC. In conclusion, 0.50-wt.% and 01-wt.% concentration of alkali-based PC-modified HEMC solution proved efficient in maintaining viscosity under ambient conditions, increasing solubility and exhibiting improved thermal stability at geothermal conditions for oil field applications
Indo-Pak conflict in South Asia: dynamics of Kashmir issue and the way forward for peace
Full text linkIndia and Pakistan have experienced various military conflicts since their inception in 1947. The Kashmir issue is one of the most pertinent causes of conflict between both nations as they have gone to war in 1948, 1965 and 1999 on the issue of Kashmir. This matter was also brought to the United Nations Security Council for resolution. However, India has categorically refused to seek any international mediation over this issue by terming it as an internal issue of India. Both countries officially joined the nuclear club in May 1998, which posed a severe threat to the security of the South Asian region as it enabled them to use the nuclear option in future. After acquiring atomic status, both countries came close to war in 2001 when armies were deployed on forward positions on international borders and in 2019 when Pakistan shot down the Indian Air Force fighter jet in the Azad Jammu and Kashmir. Since 2019, especially after India revoked Article 370, relations between the two countries have been dismal. The paper contemplates the background of this conflict and the resultant wars between India and Pakistan and presents confidence-building measures for the pursuit of peace-making in South Asia
Tribal politics, Mughal mansab and the sons of Khushal Khan Khattak (1667-1674)
Full text linkKhushal Khattak, the 17th-century poet, warrior and tribal chief, was a Mughal mansabdar from 1641 to 1664. Like his forefathers, he served the Mughals with loyalty. His fortune changed after his arrest by Aurangzeb (1658-1707), and his perception transformed vis-à-vis the Mughals. At the time of his release in 1668, a tribal uprising engulfed the Pakhtun borderland areas. The Yusufzais’ uprising in the plain and hilly terrain of the Malakand region, coupled with Aimal Khan and Darya Khan’s forays, had blocked the route of Khyber, which halted swift transportation for the Mughals. Although Khushal himself did not accept any Mughal slot after his release, his two sons, Afzal Khan and Behram Khan, fought against each other to get the mansab from the Mughals. This phase of Khushal’s life was full of miseries. What role did Khushal play during this period? Why has his once dominating role and influence been diminished? Why did he fail to control or bring reconciliation between his sons? These questions are explored to grasp his position in that intra-family and inter-tribal power struggle. An attempt has been made to find out the role and position of other tribes during the second half of the 17th century
A comparative analysis and prediction of the economic growth of Pakistan using machine learning models
Full text linkThis article investigates a comparative analysis of machine learning models for Pakistan\u27s Gross Domestic Product (GDP), an important indicator of the nation\u27s economic development. GDP is crucial to assess well-versed decisions. Since machine learning techniques are more sophisticated, much interest has been developed in predicting GDP to handle complex data patterns and enhance prediction accuracy. In this study, we evaluated the performance of a variety of machine learning algorithms like Auto-Regressive Integrated Moving Average (ARIMA), double exponential smoothing, Multilayer Perceptron (MLP), Neural Network Auto-Regressive (NNAR), and hybrid machine learning models on data from 1960 to 2022. The MLP used in Artificial Neural Networks (ANNs) outperforms based on the outcomes. This comparative analysis provides insights into the most suitable model for accurate prediction of Pakistani GDP for the years 2023 to 2032. This article provides a detailed analysis of various machine learning models used to predict Pakistan\u27s GDP accurately. GDP prediction is an essential indicator of a nation\u27s economic development and is crucial in making informed decisions. With the advancements in machine learning techniques, there has been a growing interest in predicting GDP due to their efficiency in handling complex data patterns and improving prediction accuracy.
Investigations of carbon and particulate matter emissions of diesel engine using tertiary fuel
Full text linkThe development of modern world reveals that the world is facing an energy crisis due to the depletion of fossil fuel reserves. Biodiesel is renewable bioenergy made from vegetable oils, microalgae oil, and animal fats. The study involved adding 3,000 parts per million (ppm) of clove oil as an additive to the biodiesel. An endurance test was then conducted on a Compression Ignition (CI) engine for a duration of 100 hours, using three different fuel samples: pure diesel fuel (D100), a blend of 30% biodiesel and 70% diesel fuel (B30), and a blend of biodiesel with 3,000 ppm of clove oil (3000 ppm). The study analysed the effects of the fuel samples on carbon emissions from a CI engine. The results show that carbon monoxide (1.69%) is reduced in B30 and (7.49%) is reduced in CL3000 ppm. Carbon dioxide (7.97%) in B30 and 12.59% in CL3000 ppm are also reduced. Further particulate diesel engine emissions using biodiesel and clove oil-blend fuel samples were investigated. It was found that PM emissions were reduced when using clove oil-blend fuel