1,722,240 research outputs found
Sustainable Manufacturing through Digital Multi-Material 3D Printing
Full text linkThe utilisation of three-dimensional (3D) printing has become a well-established method for fabricating structural components across various materials such as polymers, metals and ceramics. Within this domain, multi-material 3D printing emerges as a pivotal advancement, offering prospects for rapid manufacturing, customised design, and structural innovation. Particularly, the incorporation of recycled materials into multi-material printing holds promise for promoting sustainability and recyclability in manufacturing processes. By leveraging multi-material printing techniques and incorporating recycled materials, this study aims to advance the sustainability agenda within manufacturing practices while concurrently exploring avenues to enhance material performance for practical engineering applications. This study focuses on the multi-material printing of pure polylactic acid (PLA) alongside recycled polylactic acid (rPLA), employing fused deposition modelling (FDM) as a cost-effective 3D printing technique. The research aims to identify the optimal composition for achieving desired material properties by exploring different percentages and layer placements of recycled material in combination with pure PLA. Detailed analysis of the mechanical properties of these 3D printed components was conducted, with the experimental results further validated through analysis of variance. The results of this study emphasis the mechanical advantages associated with the utilisation of multi-material 3D printing techniques. Moreover, the incorporation of both PLA and rPLA materials highlights the potential sustainability benefits inherent in these approaches
Analysis of photovoltaic panels performance and power output forecasting based on optimized deep learning technique / Muhammad Naveed Akhter
No full textAlternative renewable energy sources have a significant contribution to meet the world’s energy demand due to population climax and reduce global warming. Solar energy is a major alternative energy source to generate electricity through photovoltaic (PV) systems. However, the generated PV power is susceptible to unpredictable climate and seasonal factors, which cause an unfavorable effect on the stability, reliability, and operation of the grid. Therefore, proper monitoring of the PV system and accurate forecasting of PV power output is required to ensure the stability and reliability of the grid. The purpose of monitoring the PV systems is to keep the PV system in continuous functional status with improved performance. In the first part of this work, the performance of three grid-connected photovoltaic systems installed at the rooftop of the engineering tower building, University of Malaya, Kuala Lumpur, Malaysia, is evaluated. The grid-connected PV systems are based on poly-crystalline (p-si), mono-crystalline (m-si), and a-si (amorphous silicon (a-si)) technologies. The performance is evaluated on monthly and annual data monitored from January 2016 to December 2019. A comprehensive analysis is conducted on eleven performance parameters: performance ratio, capacity factor, array yield, final yield, PV array efficiency, PV system efficiency, inverter efficiency, AC energy, array losses, system, and the overall losses. Secondly, an hour ahead forecasting of solar power output is performed on an annual basis for the aforesaid three PV systems over the same period (2016-2019), based on forecasting accuracy measurement parameters such as RMSE, MSE, MAE, r and R2. A deep learning method (RNN-LSTM) is proposed and compared with regression (GPR, GPR (PCA)), machine learning (SVR, SVR (PCA), ANN), and hybrid methods (ANFIS (GP), ANFIS(SC), ANFIS(FCM)) for an hour ahead forecasting of PV power output on an annual basis for the whole period. Moreover, Salp Swarm Algorithm (SSA) is used to tune the hyperparameters of the developed deep learning method on an annual basis over four years to enhance its forecasting accuracy and is compared with RNN-LSTM, GA-RNN-LSTM, and PSO-RNN-LSTM. Performance analysis findings show that p-si PV system performs better with a higher annual average (array yield (1309.7 h), array efficiency (12.17 %), and system efficiency (11.33 %)) accompanied by less degradation in almost all performance parameters compared to a-si and m-si PV systems. Moreover, the composite PV system has the potential to avoid 28143.7 kg of CO2 emissions in four years. The forecasting results show that the proposed deep learning technique (RNN-LSTM) has presented lower (RMSE, MSE) and higher (r and R2) compared to other techniques. Moreover, the proposed hybrid method (SSA-RNN-LSTM) is found (19.14% and 21.57%), (15.4% and10.81%) and (22.9% and 25.2%) better in terms of (RMSE and MAE) than developed (RNN-LSTM) for p-si, m-si and a-si PV systems respectively. Furthermore, the proposed hybrid method (SSA-RNN-LSTM) has shown higher R2 and maximum convergence speed compared to GA-RNN-LSTM and PSO-RNN-LSTM. In addition, the proposed deep learning and hybrid models (SSA-RNN-LSTM) are found to be robust and flexible in the prediction of power output for three different PV systems over four years duration
Chemical composition and biological activities of the essential oil of Skimmia laureola leaves
Full text linkThe composition of the essential oil from leaves of Skimmia laureola was determined by GC and GC-MS. Twenty-eight components were identified, accounting for 93.9% of the total oil. The oil is mainly composed of monoterpenes (93.5%), of which monoterpene hydrocarbons and oxygenated monoterpenes represent 11.0% and 82.5%, respectively. Sesquiterpenes constitute only 0.3% of the total oil. Linalyl acetate is the main component (50.5%), with linalool (13.1%), geranyl acetate (8.5%) and cis-p-menth-2-en-1-ol (6.2%) as other principal constituents. The essential oil showed a significant antispasmodic activity, in a dose range of 0.03-10 mg/mL. The essential oil also possesses antibacterial and antifungal activities against some pathogenic strains. The phytotoxic and cytotoxic activities were also assessed
EFFECT OF ANTIPLATELET AGENTS ON VIABILITY OF AV FISTULA
No full text*Dr. Syed Muhammad Naveed Zafar Zaidi, Dr. Rao Muhammad Shargeel, Dr. Rafia and Dr. Rizwan Rashi
Construction Development and Consequences of Job Satisfaction : Banking Sector of Pakistan
No full textTitle: Construction, Development and Consequences of Job Satisfaction in Banking Sector of PakistanLevel: Second CycleAuthor: Muhammad Naveed Iqbal and Sidra RizviSupervisor: Dr. Maria Fregidou-MalamaDate: 2012, February.Purpose: This study investigates job satisfaction concepts by considering jobs satisfaction factors, leader/manager’s behavior and effects of job satisfaction in the form of organizational efficiency and individual efficiency. It studies the construction, development and consequences of job satisfaction.Design/methodology: The data is collected from commercial bank in Pakistan through a survey by using two different questionnaires, one for employees and one for managers. SPSS technique was used for data analysis.Result & Conclusion: The job satisfaction factors and manager behavior are the input in construction and development of employees’ job satisfaction. Six factors: (promotion, pay, benefit, rewards coworkers and job responsibilities) and managerial style: (middle to the road managerial style) are the most important basis to build the satisfaction level of the employees. Satisfaction/dissatisfaction of an employee affects the organizational efficiency as well as individual efficiency.Contribution: This research helps researchers to use the created model for further extensive research on job satisfaction. It helps the organizations to assess the status of their employee in regard of job satisfaction. Managers can manage polices related to factors and design training accordingly for the desired leadership behavior according to employees preference.Further Suggestion: This research is done in one department of commercial bank in Pakistan. Increase in sample size could produce comprehensive results. National culture effect is ignored in this research that helps to look on different consequences of job satisfaction assessment according to country’s culture. More service sectors such as hospital, insurance, telecommunication etc. should be considered to get more general results.Originality: This research presents construction, development of employee job satisfaction through factors and manager/leader behavior and its results in the form of consequences of satisfaction or dissatisfaction.Keywords: Job Satisfaction, Employees, Job Satisfaction Factors, Manager/Leade
COMPARATIVE ANALYSIS OF DEPRESSION AND ANXIETY AMONG MEDICAL STUDENTS OF PUBLIC AND PRIVATE SECTOR MEDICAL COLLEGES.
No full text*Dr. Asfa Batool, Dr. Rao Muhammad Shargeel and Dr. Syed Muhammad Naveed Zafar Zaid
COMPARATIVE ANALYSIS OF DEPRESSION AND ANXIETY AMONG MEDICAL STUDENTS OF PUBLIC AND PRIVATE SECTOR MEDICAL COLLEGES
No full text*Dr. Rizwan Rashid, Dr. Rao Muhammad Shargeel and Dr. Syed Muhammad Naveed Zafar Zaid
Antinociceptive and anti-inflammatory potential of Rhododendron arboreum bark
No full textRhododendron arboreum Smith. (Ericaceae), an evergreen small tree, is one of the 1000 species that belongs to genus Rhododendron distributed worldwide. In folk medicine, as various parts of this plant exhibit medicinal properties, it is used in the treatment of different ailments.The present study was designed to evaluate the potential anti-inflammatory and antinociceptive effects of methanolic extract of R. arboreum bark, followed by activity-guided fractionation of n-hexane, n-butanol, chloroform, ethyl acetate and aqueous fractions.The ethyl acetate fraction (200 mg/kg i.p.) showed the maximum analgesic effect (82%) in acetic acid-induced writhing, followed, to a less extent, by crude extract and chloroform fraction both at a dose of 200 mg/kg i.p. (65.09% and 67.89%, respectively). In carrageenan-induced mouse paw oedema, the crude extract and its related fractions displayed in a dose-dependent manner (50-200 mg/kg i.p.) an anti-inflammatory activity for all time-courses (1-5 hrs). For the active extract/fractions (200 mg/kg i.p.), the maximum effect was observed 5 h after carrageenan injection. These evidences were also supported by in vitro lipoxygenase inhibitory properties. In conclusion, R. arboreum crude methanolic extract and its fractions exhibited anti-inflammatory and antinociceptive effects. For these reasons, this plant could be a promising source of new compounds for the management of pain and inflammatory diseases
Generation and analysis of expressed sequence tags from roots cDNA library of cotton (Gossypium arboreum)
No full textEnhancing Sustainability and Functionality with Recycled Materials in Multi-Material Additive Manufacturing
Full text linkThis study presents a novel multi‐material additive manufacturing (MMAM) strategy by combining virgin polylactic acid (vPLA) with recycled polylactic acid (rPLA) in a layered configuration to improve both performance and sustainability. Specimens were produced using fused deposition modelling (FDM) with various vPLA: rPLA ratios (33:67, 50:50, and 67:33) and two distinct layering approaches: one with vPLA forming the external layers and rPLA as the core, and a second using the reversed arrangement. Mechanical testing revealed that when vPLA is used as the exterior, printed components exhibit tensile strength and elongation improvements of 10–25% over conventional single‐material prints, while the tensile modulus is largely influenced by the distribution of the two materials. Thermal analysis shows that both vPLA and rPLA begin to degrade at approximately 330°C; however, rPLA demonstrates a higher end‐of‐degradation temperature (461.7°C) and increased residue at elevated temperatures, suggesting improved thermal stability due to enhanced crystallinity. Full‐field strain mapping, corroborated by digital microscopy (DM) and scanning electron microscopy (SEM), revealed that vPLA‐rich regions display more uniform interlayer adhesion with minimal voids or microcracks, whereas rPLA‐dominated areas exhibit greater porosity and a higher propensity for brittle failure. These findings highlight the role of optimal material placement in mitigating the inherent deficiencies of recycled polymers. The integrated approach of combining microstructural assessments with full‐field strain mapping provides a comprehensive view of interlayer bonding and underlying failure mechanisms. Statistical analysis using analysis of variance (ANOVA) confirmed that both layer placement and material ratio have a significant influence on performance, with high effect sizes highlighting the sensitivity of mechanical properties to these parameters. In addition to demonstrating improvements in mechanical and thermal properties, this work addresses a significant gap in the literature by evaluating the combined effect of vPLA and rPLA in a multi-material configuration. The results emphasise that strategic material distribution can effectively counteract some of the limitations typically associated with recycled polymers, while also contributing to reduced dependence on virgin materials. These outcomes support broader sustainability objectives by enhancing energy efficiency and promoting a circular economy within additive manufacturing (AM). Overall, the study establishes a robust foundation for industrial-scale implementations, paving the way for future innovations in eco-efficient FDM processes
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