The Construction and demolition (C and D) waste generation is a critical issue for the construction industry, which negatively affects the economy, environment, and society. This study estimates the ...penalty-cost based on the produced C&D wastes in steel and concrete skeleton projects. Field survey and the BOQ data were collected from five concrete and four steel skeleton projects. The difference of materials used and wastes generated between concrete and steel skeleton projects were evaluated statistically (ANOVA and Welch and Brown-Forsythe). A financial analysis was implemented for estimating the penalty cost. The study outcomes demonstrate that the amount of waste that construction managers estimated is significantly lower than the actual amount generated. Furthermore, 0.055% of the total project cost of a penalty was estimated based on the waste produced at construction sites. In the end, the estimated penalty was validated by comparing it with the six recent completed projects. The penalty calculated in this study could save the project cost and reduce the C&D waste. As a result, imposing the estimated cost as a penalty would force construction managers to think thoroughly about the generated C&D waste problems. This study also has a novelty and will add to the body of knowledge by using penalty-cost quantification model to save project-cost of construction material-based-waste, and it can be further explored by adopting more quality data and engaging different construction materials.
Prediction of an extreme seismic event in any area has been a perplexing study area. Baluchistan is the largest province of Pakistan, and the whole province lies in a seismically active region which ...makes it vulnerable to earthquakes. In the current study, different aspects of seismology of Baluchistan, for instance, frequency content, recurrence time, Gutenberg-Richter law, seismic energy release, seismic rate changes, and other seismic features, are calculated. Furthermore, the Maximum Relevance and Minimum Redundancy (mRMR) principle is used to select the appropriate features. In order to predict the occurrence of future earthquakes, a Support Vector Regressor (SVR) and Hybrid Neural Network (HNN) centered prediction model (SVR-HNN) is formulated. An Enhanced Particle Swarm Optimization (EPSO) algorithm is incorporated in HNN for weight optimization at each layer. After testing the stability performance, the proposed model with systematically selected seismic features is applied for earthquake prediction along the Chaman fault in Baluchistan province. The accuracy of the prediction model is evaluated by computing prominent performance measures. The sensitivity and specificity for the earthquake prediction for the studied region were found to be 68.3% and 87.4%, respectively, with an accuracy of 81.2%. The accuracy of the prediction model is evaluated by computing prominent performance measures. The results of the study revealed a close relationship with the existing historical earthquake data as per the evaluation indices and can be considered acceptable. The proposed methodology can be equally useful for other areas for the prediction of a scenario earthquake. The results of the proposed methodology can help the decision and policymakers to plan cities and houses such that the damage can be minimized. Moreover, the decision-makers and future researchers can propose proper disaster mitigation strategies for averting the damage of future earthquakes.
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In this study, we elucidated the effect of sewage drain on groundwater contamination as including different contaminants, microbes, and pathogens, which deteriorating the groundwater ...by poor infiltration and seepage. This is getting severer in developing countries like India, Bangladesh, and Pakistan, where unprocessed effluent is discharged into the water bodies. This study was planned to elucidate the effect of sewage drain (based on distance 0–5, 5–10, 15–20, 20–25 m) from two different sewage drains to explain the different physiochemical, and biological parameters including total soluble solids (TSS), chloride, total dissolved solids (TDS), calcium, total hardness, magnesium, nitrate, chemical oxygen demand (COD), dissolved oxygen (D.O.), and biological oxygen demand (BOD). Drainage channel number-1 results showed that E. coli (positive), coliform count (22.75–48.66 /100 mL), and BOD (8–25.75 mgL−1) remained above the permissible limit of the World Health Organization (WHO). Besides, drainage channel number 2 results exposed that E. coli (positive), coliform count (17.7–47 /100 mL), and BOD (6.25–21.5 mg/ L) was not within the permissible limit of WHO. The presence of COVID-19 in the stool has been significantly reported in the literature. The presence of stool in sewage drain leading to groundwater contamination can be an emerging threat to water pollution and could lead to the spread of COVID-19. This study helps to minimize this threat with the help of corporate social responsibility (CSR). Because organizational responsibility towards its society is one of the critical factors to contain numerous issues related to the society.
Accurate building models are widely used in the construction industry in the digital era. UAV cameras combined with image-based reconstruction provide a low-cost technology for building modeling. ...Most existing reconstruction methods operate on point clouds, while massive points reduce computational efficiency, and the accumulated error of point position often distorts building edges. This paper introduces an innovative 3D reconstruction method, Edge3D, that recovers building edges in the form of 3D lines. It employs geometry constraints and progressive screening technology to improve the robustness and precision of line segment matching. An innovative bundle adjustment strategy based on endpoints is designed to reduce the global reprojection error. Edges were tested on challenging real-world image sets, and matching precisions of 96% and 94% were achieved on the two image sets, respectively, with good reconstruction results. The proposed approach reconstructs building edges using a small number of lines instead of massive points, which contributes to the rapid reconstruction of building contour construction and obtaining accurate models, serving as an important foundation for the promotion of construction advancement.
Historic buildings are considered assets for generations. The use of 3D interactive models is an excellent way to document such historic cultural heritage. Such buildings include socio-religious ...buildings, such as shrines and religious monuments. Digital technologies such as photogrammetry and laser scanning play a pivotal role in monitoring and safeguarding precious shrine cultural heritage. These advanced techniques allow the capture of details and accurate 3D representations of cultural artifacts, architectural structures, and even entire shrines. This study deals with research related to the conservation of the selected historic shrine of Shah Yousaf Gardez. A laser scanner methodology was used to produce a high-level detail interactive model translated into a heritage building information modeling (HBIM) prototype. This HBIM model has been designed to maintain the historical details of the shrine, especially geometric features, artwork present on the surface, and condition of structural as well as non-structural components. Data analysis of defects in structural and non-structural components was also analyzed in the study. This study was conducted fort the first time for a shrine case study. It will not only help to document and preserve historic buildings and cultural heritage but also monitor potential degradation or damage over time. Using this technology, scheduled conservation and restoration efforts ensuring the long-term preservation of these invaluable treasures can be adopted.
Sorting cells is an essential primary step in many biological and clinical applications such as high-throughput drug screening, cancer research and cell transplantation. Cell sorting based on their ...mechanical properties has long been considered as a promising label-free biomarker that could revolutionize the isolation of cells from heterogeneous populations. Recent advances in microfluidic image-based cell analysis combined with subsequent label-free sorting by on-chip actuators demonstrated the possibility of sorting cells based on their physical properties. However, the high purity of sorting is achieved at the expense of a sorting rate that lags behind the analysis throughput. Furthermore, stable and reliable system operation is an important feature in enabling the sorting of small cell fractions from a concentrated heterogeneous population. Here, we present a label-free cell sorting method, based on the use of focused travelling surface acoustic wave (FTSAW) in combination with real-time deformability cytometry (RT-DC). We demonstrate the flexibility and applicability of the method by sorting distinct blood cell types, cell lines and particles based on different physical parameters. Finally, we present a new strategy to sort cells based on their mechanical properties. Our system enables the sorting of up to 400 particles per s. Sorting is therefore possible at high cell concentrations (up to 36 million per ml) while retaining high purity (>92%) for cells with diverse sizes and mechanical properties moving in a highly viscous buffer. Sorting of small cell fraction from a heterogeneous population prepared by processing of small sample volume (10 μl) is also possible and here demonstrated by the 667-fold enrichment of white blood cells (WBCs) from raw diluted whole blood in a continuous 10-hour sorting experiment. The real-time analysis of multiple parameters together with the high sensitivity and high-throughput of our method thus enables new biological and therapeutic applications in the future.
This paper examines how the latest mega plan and the Belt and Road Initiative (BRI) will impact the geopolitics of energy and infrastructural development. With a massive change in the supply and ...demand of global energy and its infrastructure, the transition of international energy order is in the making. While the US is going towards a more isolationist path from its traditional superpower role, there are rising economies such as China, India, Japan, and Russia which are undoubtedly playing a vital role in the geopolitical stage and the other development endeavors. Several regions such as Central Asia, the Arctic, Eastern Mediterranean, and the South China Sea are offering substantial natural gas and oil reserves and drawing global attention to develop energy cooperation. This situation is profoundly influencing the transition of energy order. In this transition, BRI is supposed to play an important role. As a mega development strategy with a robust geostrategic dimension, it purposes to advocate interconnectivity collaboration in framework, exchange, and advancement among the partaking nations. This super arrangement offers a lot of ventures, foundation developments, and modern reconciliation in the energy sector. The country is trying to establish a multilateral platform for endorsing and shielding energy cooperation under BRI. This paper, therefore, attempts to observe how this mega plan will contribute to reshaping the existing energy order as well as the geopolitics of energy with motivation on multifaceted energy collaboration.
The present investigation aims to propose a numerical model for assessing the complex damaging response of glass fiber-reinforced polymer- (GFRP-) reinforced concrete columns having hybrid fibers and ...confined with GFRP spirals (GFHF columns) under concentric and eccentric compression. Fiber-reinforced concrete (FRC) consists of polyvinyl alcohol fibers (PVA) and polypropylene fibers (PF). A total of six GFHF circular columns were constructed having a circular cross section of 250 mm and a height of 1200 mm. A commercial package ABAQUS was used for the finite element analysis (FEA) of the GFHF columns by using a modified concrete damage plastic (CDP) model for hybrid fiber-reinforced concrete (HFRC). The damaging response of GFRP bars was defined using a linear elastic model. The results depicted that the failure of GFHF columns occurred either in the upper or in the lower half portion with the rupture of GFRP longitudinal bars and GFRP spirals. The decrease in the pitch of GFRP spirals led to an improvement in the axial strength (AS) of GFHF columns. The eccentric loading caused a significant reduction in the AS of columns. The comparative study solidly substantiates the validity and applicability of the newly developed FEA models for capturing the AS of GFHF columns by considering the axial involvement of longitudinal GFRP bars and the confinement effect of transverse GFRP spirals. So, the suggested numerical model having a complex system of equations for HFRC can be used for the accurate analysis of HFRC members.
Disaster is a state of serious disruptions in the functionality of any society or county. Disasters pose serious economic or environmental impacts that surpass the capacity of the affected country or ...society to compete with the use of their assets. Recently, Pakistan significantly prone to health disasters due to COVID-19 among developing South Asian countries. The long-term impact of health disasters and other natural hazards put additional pressure mostly on the government's economic policy. It forces the government to follow a constructive approach like a disaster relief-based approach rather than a conventional mitigation management formation to reduce the impact of disaster risk. This study elaborates on the main issues associated with disaster preparedness as well as recovery of the economy and businesses of the country. For Scientific risk performance analysis, open-source data from the National Institute of Disaster Management (NDMA) has been utilized to study the current situation of COVID-19 in Pakistan. Results show Pakistan has been facing a highly vulnerable situation as more than three hundred and fifty thousand confirmed cases have been reported. Poor health and technical management facilities have been exposed against COVID-19 as Pakistan has a low heath budget because of its declining GDP growth rate in the world. This research will help in disaster preparedness and the development of a disaster risk management framework while designing strategies to deal with such pandemics in the future.
Rockburst is a complex phenomenon of dynamic instability in the underground excavation of rock. Owing to the complex and unclear rockburst mechanism, it is difficult to accurately predict and ...reasonably assess the rockburst potential. With the increasing availability of case histories from rock engineering and the advancement of data science, the data mining algorithms provide a good way to predict complex phenomena, like rockburst potential. This paper investigates the potential of J48 and random tree algorithms to predict the rockburst classification ranks using 165 cases, with four parameters, namely maximum tangential stress of surrounding rock, uniaxial compressive strength, uniaxial tensile strength, and strain energy storage index. A comparison of developed models’ performances reveals that the random tree gives more reliable predictions than J48 and other empirical models (Russenes criterion, rock brittleness coefficient criterion, and artificial neural networks). Similar comparisons with convolutional neural network resulted at par performance in modeling the rockburst hazard data.
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