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Asynchronous interconnection is essential for integrating AC networks operating at different frequencies, typically 50 Hz and 60 Hz. This need arises from distributed power generation methods, including offshore renewable sources and diverse regional grid configurations. Advanced strategies are required to overcome these frequency differences and ensure uninterrupted power transfer. High-Voltage Direct Current (HVDC) transmission systems facilitate efficient power exchange, enhancing grid reliability and stability. This study focuses on optimizing the Proportional-plus-Integral (PI) controller parameters within a 20 MVA Voltage Source Converters (VSC)-based HVDC system to enable asynchronous interconnection between offshore and onshore AC networks. The offshore VSC regulates active and reactive power, while the onshore VSC controls DC voltage and reactive power. A vector control approach with symmetric optimum PI tuning is proposed for a comprehensive performance assessment of the VSC-based HVDC transmission system. The effectiveness of the tuned PI controller parameters is evaluated through four test cases using MATLAB/Simulink for offline simulation and Typhoon HIL604 for real-time validation. These cases involve abrupt changes in reference active and reactive power for the offshore VSC; and in reference reactive power and DC voltage for the onshore VSC. Results demonstrate rapid and satisfactory dynamic performance across all test cases, as evidenced by offline simulations and real-time validation. The validation highlights the effectiveness of the proposed control design with symmetric optimum PI tuning, confirming its ability to enhance the overall performance of the HVDC transmission system for efficient asynchronous interconnection.

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India is one of the highly developing countries in the world and it has the second-largest agricultural source of income, which covers 61% of the entire income of the country. The most valuable income group, by giving the appropriate training in this technology, will make their entire country to become one of the most highly developing counties in the world. In recent years, many developing, developed, and underdeveloped countries face shortages of fish, fruits, and vegetables due to natural disasters like earthquakes, tsunami, and any other unexpected events. Now the main issue of this paper is to preserve the food products from post-harvest to consumer-level, which cover 60% of losses due to the unavailability of preservative methods. This paper mainly focused on the conventional methods to advanced solar drying technologies for perseverating fish, fruits, and vegetables and also it discusses the technology used for drying the yield range of fish like Atheriniformes, Catfish, Chilwa, etc. Fruits like banana, mango, and papaya, and vegetables like bitter gourd, cabbage, and cocoa beans have been reviewed and also discussed some problems along with their solutions in concern with food products drying, thereby the selection of dryer for drying products will be made easy by this review article. On the whole, this investigation would help researchers in fish drying to choose the better drying methods for acquiring better results for particular fish, fruits, and vegetables that enable any entrepreneur to select the appropriate method reducing the cost and time.

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The scarcity of clean and safe water is one of the most perilous glitches faced by the world. The pure drinking water resources across the world are depleting progressively due to rapid industrialization and growth in population. The conceivable solution for this problem is converting the available seawater into pure drinking water through several techniques of desalination. In the stream of desalination, many prodigious endeavours are in evolution to increase the reliability of the process by cutting down the principal and maintenance costs. Among several desalination approaches, low-temperature thermal desalination (LTTD) is an intriguing and advancing trend in the desalination process by using low temperatures and pressures in a range similar to ambient temperatures and vacuum pressures. The LTTD technique is operated by taking the energy input from waste heat, thermoclines and renewable energy sources. However, the operating temperatures of the LTTD system are less than 50 °C. The development of this particular LTTD process driven by renewable energy sources has gone through various stages, based on the water-energy demands, environmental concerns and technological progressions. In this article, the historical developments of the LTTD process using several renewable and non-renewable energy sources have been reviewed. Finally, some future recommendations for further developments in this approach are discussed. This article paves the path for the researchers working in desalination to choose an appropriate LTTD approach that is more viable and sustainable than the conventional desalination systems.

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The objective of this research is to reduce the emission and improve the performance of diesel engine when they operate with distilled tire pyrolysis oil blends (DTPO30). Utilization of tire oil on diesel engine has been an active research field for the last two decades. But, it is still challengeable due to their high emissions. To overcome this, the present study has been attempted to analyze the influence of hybrid silicon oxide (SiO2) and cerium oxide (CeO2) nanoparticles in tire oil blends. The SiO2 and CeO2 are considered in hybrid nature with proportions of 20 mg/L (sum 40 mg/L), 50 mg/L, and 70 mg/L each. The nanoparticles mixed fuel blends were prepared using an ultrasonication technique. The experiments were conducted with a water-cooled engine with a constant speed of 1500 rpm, a compression ratio of 17.5, and an injection timing of 23° BTDC. The FTIR spectra indicated that all the samples were identified with alkanes and alkenes like diesel. But, DTPO30 + 70 found with many peaks in bending mode, which indicates the changes in chemical functional groups. From the engine testing, the brake thermal efficiency was improved by about 2% and brake specific fuel consumption was reduced up to 0.03 kg/kW h with DTPO30 + 70 (SiO2 + CeO2) than DTPO30. The cylinder pressure and heat release rate were reduced with hybrid nanoparticles blended fuel than with that of individually mixed fuel. Also, the emissions such as NOx, CO, UBHC, and soot were reduced with hybrid nanoparticles, up to 4.8%, 13.5%, 27%, and 10% respectively. The hybrid nature of SiO2 + CeO2 has the potential to adhere to the soot particles around their surface which leads to reducing the duration of suspension in the atmosphere.

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In the pursuit of constructing a sustainable world for all through the instrumental seventeen Sustainable Development Goals, the COVID-19 pandemic emerged and affected the efforts concentrated on these goals. Therefore, there is a pressing need to analyze the extent of the impact that unfolded from the pandemic on each Sustainable Development Goal and further to direct the post-pandemic situation to accelerate the progress in every goal. Besides, there exists a knowledge gap in understanding the Sustainable Development Goals and its interaction with each goal through synergic and trade-off effects. To address the aforementioned imperative problems, this study is formulated to perform an impact assessment as well as to provide direction in the post-pandemic environment to effectively progress towards the Sustainable Development Goals by using a hybrid qualitative and quantitative framework. A detailed investigation is carried out to examine the pandemic impacts in every goal, and a quantified impact analysis is performed in terms of the targets of the Sustainable Development Goals with the aid of ranking methodology. The results indicate that SDG 1 and SDG 8 are the most impacted goal. To provide deeper perspectives into the Sustainable Development Goals, a critical analysis of the targets and indicators is performed to characterize the goals from their elemental point of view, such as nature of goals, depending factors, locus of the goal, and Sustainable Development Goal interactions. Further, a novel parameter, the degree of randomness, is proposed whose application in environmental research is immense. The impact on each goal and impact interaction between all the SDGs are also mapped, through which the dynamics of Sustainable Development Goal interactions is elaborated. In context with the post-pandemic scenario, the strategies to achieve the Sustainable Development Goals with environmental focus are presented with prioritization factor that supports quick recovery. The introduced prioritization factor is formulated by employing a multi-criteria analysis methodology. In addition, the fundamental elements of SDGs are built upon one another to frame an optimized and effective approach to achieving the SDGs in the post-pandemic environment. Despite the strategies, a conceptual framework to align the business practices with the SDGs is propounded. This study deep down would provide a unique perspective to the research community and would impart deeper knowledge in connection with sustainability, while the solutions framed would steer the policy and decision-makers.

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The proposed research study aims to improve the productivity of solar still (SS) by using low-cost and eco-friendly materials. The aforementioned objective was achieved by enhancing the evaporation rate of seawater in the absorber basin and the condensation rate over the glass cover of the solar still. In this study, the low-cost and eco-friendly materials used for enhancing the evaporation rate in the solar still were molasses powder (MP), sawdust (SD) and rice husk (RH). In addition to these materials, bamboo straw (BS), banana leaf stem (BL) and rice straw (RS) were used as absorbing materials over the glass cover for enhancing the condensation rate. The experiments were carried out under similar meteorological conditions, and the results of the modified solar still were compared with the conventional solar still (CSS). The productivities of CSS, SSMP, SSRH, SSSD, SSBS, SSBL and SSRS were about 2250 mL/m2, 2383 mL/m2, 2467 mL/m2, 3033 mL/m2, 2700 mL/m2, 2683 mL/m2 and 3367 mL/m2, respectively. The results of the experimental investigation highlighted that the SSSD had a comparatively better evaporation rate and 34.81% higher yield than CSS. Besides, SSRS had a comparatively better condensation rate and a 51.88% higher yield than CSS. Furthermore, the combination of sawdust (SD) and rice straw (RS) was investigated for the combined enhancement of evaporation and condensation. The solar still with sawdust and rice straw (SSSDRS) showed a 62.88% improvement in productivity with 3633 mL/m2 when compared to CSS. Also, the economic analysis showed that the cost per litre (CPL) of freshwater obtained from SSSDRS was about ₹ 1.9 ($ 0.025) with a payback period of 4.4 months which was the least when compared to all the considered cases.

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OBJECTIVES: Widespread acceptance of the COVID-19 vaccine will be the next important step in fighting the novel coronavirus disease. Though the Pakistani government has successfully implemented robust policies to overcome the COVID-19 pandemic; however, studies assessing public intention to get COVID-19 vaccination (IGCV) are limited. The aim of this study is to deal with this literature gap and has also expanded the conceptual framework of planned behaviour theory. We have introduced three new considerations (risk perceptions of the pandemic, perceived benefits of the vaccine, and unavailability of vaccine) to have a better understanding of the influencing factors that encourage or discourage public IGCV. METHODS: Results are based on a sample collected from 754 households using an inclusive questionnaire survey. Hypotheses are tested by utilizing the structural equation modelling approach. RESULTS: The results disclose that the intention factors, that is, attitude, risk perceptions of the pandemic, and perceived benefits of the vaccine, impart positive effects on public IGCV. In contrast, the cost of the vaccine and the unavailability of the vaccine have negative effects. Notably, environmental concern has an insignificant effect. CONCLUSIONS: Research findings emphasize the importance of publicizing the devastating impacts of COVID-19 on society and the environment, ensuring vaccination availability at an accessible price while simultaneously improving public healthcare practices.

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Face masks are considered an effective intervention in controlling the spread of airborne viruses, as evidenced by the 2009's H1N1 swine flu and 2003's severe acute respiratory syndrome (SARS) outbreaks. However, research aiming to examine public willingness to wear (WTW) face masks in Pakistan are scarce. The current research aims to overcome this research void and contributes by expanding the theoretical mechanism of theory of planned behavior (TPB) to include three novel dimensions (risk perceptions of the pandemic, perceived benefits of face masks, and unavailability of face masks) to comprehensively analyze the factors that motivate people to, or inhibit people from, wearing face masks. The study is based on an inclusive questionnaire survey of a sample of 738 respondents in the provincial capitals of Pakistan, namely, Lahore, Peshawar, Karachi, Gilgit, and Quetta. Structural equation modeling (SEM) is used to analyze the proposed hypotheses. The results show that attitude, social norms, risk perceptions of the pandemic, and perceived benefits of face masks are the major influencing factors that positively affect public WTW face masks, whereas the cost of face masks and unavailability of face masks tend to have opposite effects. The results emphasize the need to enhance risk perceptions by publicizing the deadly effects of COVID-19 on the environment and society, ensure the availability of face masks at an affordable price, and make integrated and coherent efforts to highlight the benefits that face masks offer.

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Parameters for defining photovoltaic models using measured voltage-current​ characteristics are essential for simulation, control, and evaluation of photovoltaic-based systems. This paper proposes an enhanced chaotic JAYA algorithm to classify the parameters of various photovoltaic models, such as the single-diode and double-diode models, accurately and reliably. The proposed algorithm introduces a self-adaptive weight to regulate the trend to reach the optimal solution and avoid the worst solution in various phases of the search space. The self-adaptive weight capability also allows the proposed technique to reach the best solution at the earliest phase, and later, the local search process starts, which also increase the ability to explore. A three different chaotic process, including sine, logistics and tent map, is proposed to optimize the consistency of each generation's best solution. The proposed algorithm and its variants proposed are used to solve the parameter estimation problem of various PV models. To show the proficiency of the suggested algorithm and its variants, an extensive simulation is carried out using MATLAB/Simulink software. Two statistical tests are conducted and compared with the latest techniques for validating the performance of the suggested algorithm and its variants. Comprehensive analysis and experimental results display that the suggested algorithm can achieve highly competitive efficiency in terms of accuracy and reliability compared to other algorithms in the literature. This research will be backed up with extra online service and guidance for the paper's source code at https://premkumarmanoharan.wixsite.com/mysite.

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The COVID-19 pandemic affects all of society and hinders day-to-day activities from a straightforward perspective. The pandemic has an influential impact on almost everything and the characteristics of the pandemic remain unclear. This ultimately leads to ineffective strategic planning to manage the pandemic. This study aims to elucidate the typical pandemic characteristics in line with various temporal phases and its associated measures that proved effective in controlling the pandemic. Besides, an insight into diverse country's approaches towards pandemic and their consequences is provided in brief. Understanding the role of technologies in supporting humanity gives new perspectives to effectively manage the pandemic. Such role of technologies is expressed from the viewpoint of seamless connectivity, rapid communication, mobility, technological influence in healthcare, digitalization influence, surveillance and security, Artificial Intelligence (AI), and Internet of Things (IoT). Furthermore, some insightful scenarios are framed where the full-fledged implementation of technologies is assumed, and the reflected pandemic impacts in such scenarios are analyzed. The framed scenarios revolve around the digitalized energy sector, an enhanced supply chain system with effective customer-retailer relationships to support the city during the pandemic scenario, and an advanced tracking system for containing virus spread. The study is further extended to frame revitalization strategies to highlight the expertise where significant attention needs to be provided in the post-pandemic period as well as to nurture sustainable development. Finally, the current pandemic scenario is analyzed in terms of occurred changes and is mapped into SWOT factors. Using Fuzzy Technique for Order of Preference by Similarity to Ideal Solution based Multi-Criteria Decision Analysis, these SWOT factors are analyzed to determine where prioritized efforts are needed to focus so as to traverse towards sustainable cities. The results indicate that the enhanced crisis management ability and situational need to restructure the economic model emerges to be the most-significant SWOT factor that can ultimately support humanity for making the cities sustainable.