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| 1 | Impact of land uses on water quality in Malaysia: a review显示文摘Land use changes in urbanization,industrialization,and agricultural processes will continue to have negative impacts on water quality at all scales.The impact of land use changes on water quality is generally studied by analyzing the relationships between land use and water quality indicators.Therefore,the purpose of this research was to review and analyze the main relationships between land use and water quality,as well as to visualize the major sources and processes of water quality pollution in Malaysia.To achieve our goal,we evaluated the significance of both land use and water quality attributes used in the past studies and correlated them to understand their relationship from another angle of view.The results revealed that 87%of the reviewed studies indicated urban land use as a major source of water pollution,while 82%indicated agricultural land use,77%indicated forest land use,and 44%indicated other land uses.However,the results of correlation analysis showed that agricultural and forest-related activities more affected water quality through their significant positive correlation with physical and chemical indicators of water quality,while urban development activities had a greater impact on water quality through altering hydrological processes such as runoff and erosion.These findings would provide decision-makers with useful information for managing water pollution processes rather than sources only. | Moriken Camara Nor Rohaizah Jamil Ahmad Fikri Bin Abdullah | 2019 | Ecological Processes2019，8，1： | 8 |
| 2 | Molecular hallmarks of long non-coding RNAs in aging and its significant effect on aging-associated diseases显示文摘Aging is linked to the deterioration of many physical and cognitive abilities and is the leading risk factor for Alzheimer’s disease. The growing aging population is a significant healthcare problem globally that researchers must investigate to better understand the underlying aging processes. Advances in microarrays and sequencing techniques have resulted in deeper analyses of diverse essential genomes(e.g., mouse, human, and rat) and their corresponding cell types, their organ-specific transcriptomes, and the tissue involved in aging. Traditional gene controllers such as DNA-and RNA-binding proteins significantly influence such programs, causing the need to sort out long non-coding RNAs, a new class of powerful gene regulatory elements. However, their functional significance in the aging process and senescence has yet to be investigated and identified. Several recent researchers have associated the initiation and development of senescence and aging in mammals with several well-reported and novel long non-coding RNAs. In this review article, we identified and analyzed the evolving functions of long non-coding RNAs in cellular processes, including cellular senescence, aging, and age-related pathogenesis, which are the major hallmarks of long non-coding RNAs in aging. | Syed Aoun Mehmood Sherazi Asim Abbasi Abdullah Jamil Mohammad Uzair Ayesha Ikram Shanzay Qamar Adediji Ayomide Olamide Muhammad Arshad Peter J.Fried Milos Ljubisavljevic Ran Wang Shahid Bashir | 2023 | Neural Regeneration Research2023，18，5： | 2 |
| 3 | Segmentation of natural images using an improved thresholding-based technique 显示文摘 | Abdullah SLS Hambali HA Jamil N | 2012 | Procedia Engineering2012，41，： | 1 |
| 4 | Effects of Rice Husk Filler on the Mechanical and Thermal Properties of Liquid Natural Rubber Compatibilized High-density Polyethylene/Natural Rubber Blends显示文摘 | Jamil M Ahmad l Abdullah I | 2006 | Journal of Polymer Research2006，13，4： | 1 |
| 5 | EfficientNet-Based Robust Recognition of Peach Plant Diseases in Field Images显示文摘Plant diseases are a major cause of degraded fruit quality andyield losses. These losses can be significantly reduced with early detection ofdiseases to ensure their timely treatment, particularly in developing countries.In this regard, an expert system based on deep learning model where the expertknowledge, particularly the one acquired by plant pathologist, is recursivelylearned by the system and is applied using a smart phone application for use inthe target field environment, is being proposed. In this paper, a robust diseasedetection method is developed based on convolutional neural network (CNN),where its powerful features extraction capabilities are leveraged to detectdiseases in images of fruits and leaves. The features extraction pipelines ofseveral state-of-the-art pretrained networks are fine-tuned to achieve optimaldetection performance. A novel dataset is collected from peach orchards andextensively augmented using both label-preserving and non-label-preservingtransformations. The augmented dataset is used to study the effects of finetuning the pretrained networks’ feature extraction pipeline as opposed tokeeping the network parameters unchanged. The CNN models, particularlyEfficientNet exhibited superior performance on the target dataset once theirfeature extraction pipelines are fine-tuned. The optimal model is able toachieve 96.6% average accuracy, 90% sensitivity and precision, and 98%specificity on the test set of images. | Haleem Farman Jamil Ahmad Bilal Jan Yasir Shahzad Muhammad Abdullah Atta Ullah | 2022 | Computers, Materials & Continua2022，，4： | 0 |
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