Browsing by Author "Ali, Amjad"

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    Artificial intelligence and bio-inspired soft computing-based maximum power plant tracking for a solar photovoltaic system under non-uniform solar irradiance shading conditions - a review
    (MDPI, 2021-09-23) Ali, Amjad; Irshad, Kashif; Khan, Mohammad Farhan; Hossain, Md Moinul; Al-Duais, Ibrahim N. A.; Malik, Muhammad Zeeshan
    Substantial progress in solar photovoltaic (SPV) dissemination in grid-connected and standalone power generation systems has been witnessed during the last two decades. However, weather intermittency has a non-linear characteristic impact on solar photovoltaic output, which can cause considerable loss in the system’s overall output. To overcome these inevitable losses and optimize the SPV output, maximum power point tracking (MPPT) is mounted in the middle of the power electronics converters and SPV to achieve the maximum output with better precision from the SPV system under intermittent weather conditions. As MPPT is considered an essential part of the SPV system, up to now, many researchers have developed numerous MPPT techniques, each with unique features. A Google Scholar survey from 2015–2021 was performed to scrutinize the number of published review papers in this area. An online search established that on different MPPT techniques, overall, 100 review articles were published; out of these 100, seven reviews on conventional MPPT techniques under shading or partial shading and only four under non-uniform solar irradiance are published. Unfortunately, no dedicated review article has explicitly focused on soft computing MPPT (SC-MPPT) techniques. Therefore, a comprehensive review of articles on SC-MPPT techniques is desirable, in which almost all the familiar SC-MPPT techniques have to be summarized in one piece. This review article concentrates explicitly on soft computing-based MPPT techniques under non-uniform irradiance conditions along with their operating principles, block/flow diagram. It will not only be helpful for academics and researchers to provide a future direction in SC-MPPT optimization research, but also help the field engineers to select the appropriate SC-MPPT for SPV according to system design and environmental conditions.
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    Solidago canadensis modifies microbial community and soil physicochemical properties through litter leachates and root exudates
    (Oxford University Press (OUP), 2025-04) Bo, Yanwen; Liao, Yali; Pawlett, Mark; Akbar, Rasheed; Girkin, Nickolas T.; Sun, Jianfan; Ali, Amjad; Ahmad, Naushad; Liu, Wei; Wang, Xiaoyan; Du, Daolin
    Invasive plant inputs alter soil microbial communities via chemical compounds in litter, root exudates, and leachate, impacting a range of soil processes, but precise effects are poorly understood. We examined Solidago canadensis, a common invasive species in China, and its litter effects on soil microbial communities under natural conditions. Experimental treatments included S. canadensis seedling density (1 and 2 plants/pot) and quantity of litter (10 and 20 g/pot), with control groups that contained no plants or litter. After 120 days, soil samples were analyzed for physico-chemical properties, GC-MS chemical composition, and bacterial community composition using high-throughput sequencing. Results showed that S. canadensis seedlings and litter inputs increased soil pH, organic matter (SOM), and nitrogen (TN), while phosphorus and potassium remained unchanged. We identified 66 chemical compounds, predominantly ketones, alcohol, aldehyde, hydrocarbon, ester, acid, terpenoids, and alkaloids, associated with the presence of the invasive species, alongside shifts in dominant bacterial genera including Sphingomonas, Acidobacteriales, and Gemmatimonas. Rarer genera under the invasive treatment species, such as Candidatus, Rhodoplanes and Novosphingobium, correlated positively with soil TN, pH, and SOM. Collectively, our results demonstrate how the increased presence of allelochemicals from S. canadensis litter significantly impact soil properties and bacterial communities, and may therefore have implications for ecosystem dynamics.