Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
3,361
result(s) for
"Anwar, Muhammad"
Sort by:
Mitigation of Salinity-Induced Oxidative Damage, Growth, and Yield Reduction in Fine Rice by Sugarcane Press Mud Application
Salinity stress is one of the major global problems that negatively affect crop growth and productivity. Therefore, ecofriendly and sustainable strategies for mitigating salinity stress in agricultural production and global food security are highly demandable. Sugarcane press mud (PM) is an excellent source of the organic amendment, and the role of PM in mitigating salinity stress is not well understood. Therefore, this study was aimed to investigate how the PM mitigates salinity stress through the regulation of rice growth, yield, physiological properties, and antioxidant enzyme activities in fine rice grown under different salinity stress conditions. In this study, different levels of salinity (6 and 12 dS m –1 ) with or without different levels of 3, 6, and 9% of SPM, respectively were tested. Salinity stress significantly increased malondialdehyde (MDA, 38%), hydrogen peroxide (H 2 O 2 , 74.39%), Na + (61.5%), electrolyte leakage (40.32%), decreased chlorophyll content (32.64%), leaf water content (107.77%), total soluble protein (TSP, 72.28%), and free amino acids (FAA, 75.27%). However, these negative effects of salinity stress were reversed mainly in rice plants after PM application. PM application (9%) remained the most effective and significantly increased growth, yield, TSP, FAA, accumulation of soluble sugars, proline, K + , and activity of antioxidant enzymes, namely, ascorbate peroxidase (APX), catalase (CAT), and peroxidase (POD). Thus, these findings suggest a PM-mediated eco-friendly strategy for salinity alleviation in agricultural soil could be useful for plant growth and productivity in saline soils.
Journal Article
Medical Image Analysis using Convolutional Neural Networks: A Review
The science of solving clinical problems by analyzing images generated in clinical practice is known as medical image analysis. The aim is to extract information in an affective and efficient manner for improved clinical diagnosis. The recent advances in the field of biomedical engineering have made medical image analysis one of the top research and development area. One of the reasons for this advancement is the application of machine learning techniques for the analysis of medical images. Deep learning is successfully used as a tool for machine learning, where a neural network is capable of automatically learning features. This is in contrast to those methods where traditionally hand crafted features are used. The selection and calculation of these features is a challenging task. Among deep learning techniques, deep convolutional networks are actively used for the purpose of medical image analysis. This includes application areas such as segmentation, abnormality detection, disease classification, computer aided diagnosis and retrieval. In this study, a comprehensive review of the current state-of-the-art in medical image analysis using deep convolutional networks is presented. The challenges and potential of these techniques are also highlighted.
Journal Article
Growth and nutrient removal efficiency of duckweed (lemna minor) from synthetic and dumpsite leachate under artificial and natural conditions
Sustainable management of leachate produced from the dumpsite is one of the major concerns in developing countries Aquatic plants such as duckweed have the potential to remove pollutants from wastewater which can also be cost-effective and feasible options for leachate treatment. Therefore, the objective of our present study was to examine the growth and nutrient removal efficiency of duckweed (Lemna minor) on leachate. Three tests were performed each by growing lemna minor on synthetic leachate under controlled conditions and on dumpsite leachate under natural conditions. During each test, duckweed was grown in 300 ml plastic containers with a surface area of 25.8 cm2. About 60 mg of fresh mass of duckweed was grown on 250 ml leachate at an internal depth of 9.5 cm. Results revealed that, in comparison to synthetic leachate, duckweed removed Chemical Oxygen Demand (COD), nitrogen (N), and phosphorous (P) more efficiently from dumpsite leachate under natural climatic conditions. However, the amounts of N and P absorbed into duckweed body mass were about 16% and 35% respectively more at synthetic leachate under controlled conditions. Maximum growth rate of duckweed (7.03 g m-2 day-1) was also observed for synthetic leachate in comparison to the growth rate of 4.87 g m-2 day-1 at dumpsite leachate. Results of this study provide a useful interpretation of duckweed growth and nutrient removal dynamics from leachate under natural and laboratory conditions.
Journal Article
Synthesis, characterization and heavy metal removal efficiency of nickel ferrite nanoparticles (NFN’s)
The heavy metals, such as Cr(VI), Pb(II) and Cd(II), in aqueous solutions are toxic even at trace levels and have caused adverse health impacts on human beings. Hence the removal of these heavy metals from the aqueous environment is important to protect biodiversity, hydrosphere ecosystems, and human beings. In this study, magnetic Nickel-Ferrite Nanoparticles (NFNs) were synthesized by co-precipitation method and characterized using X-Ray Diffraction (XRD), Energy Dispersive Spectroscopy (EDS) and Field Emission Scanning Electronic Microscopy (FE-SEM) techniques in order to confirm the crystalline structure, composition and morphology of the NFN’s, these were then used as adsorbent for the removal of Cr(VI), Pb(II) and Cd(II) from wastewater. The adsorption parameters under study were pH, dose and contact time. The values for optimum removal through batch-adsorption were investigated at different parameters (pH 3–7, dose: 10, 20, 30, 40 and 50 mg and contact time: 30, 60, 90, and 120 min). Removal efficiencies of Cr(VI), Pb(II) and Cd(II) were obtained 89%, 79% and 87% respectively under optimal conditions. It was found that the kinetics followed the pseudo second order model for the removal of heavy metals using Nickel ferrite nanoparticles.
Journal Article
Colorectal Cancer and Alcohol Consumption—Populations to Molecules
Colorectal cancer (CRC) is a major cause of morbidity and mortality, being the third most common cancer diagnosed in both men and women in the world. Several environmental and habitual factors have been associated with the CRC risk. Alcohol intake, a common and rising habit of modern society, is one of the major risk factors for development of CRC. Here, we will summarize the evidence linking alcohol with colon carcinogenesis and possible underlying mechanisms. Some epidemiologic studies suggest that even moderate drinking increases the CRC risk. Metabolism of alcohol involves ethanol conversion to its metabolites that could exert carcinogenic effects in the colon. Production of ethanol metabolites can be affected by the colon microbiota, another recently recognized mediating factor to colon carcinogenesis. The generation of acetaldehyde and alcohol’s other metabolites leads to activation of cancer promoting cascades, such as DNA-adduct formation, oxidative stress and lipid peroxidation, epigenetic alterations, epithelial barrier dysfunction, and immune modulatory effects. Not only does alcohol induce its toxic effect through carcinogenic metabolites, but alcoholics themselves are predisposed to a poor diet, low in folate and fiber, and circadian disruption, which could further augment alcohol-induced colon carcinogenesis.
Journal Article
The Role of Government Support in Sustainable Competitive Position and Firm Performance
Achievement of sustainable competitive position and superior performance is the first priority of business organizations. However, small firms, due to fairly known reasons; lack of resources, financial capabilities and lack of managerial skills are often unable to succeed in their mission. Hence, they often look for less risky and convenience sources to compete in the market. A variety of factors has been tested towards a firm competitive position and performance but the role of government support in this perspective has received minor attention. The present study examines the influence of government financial support and nonfinancial support on firm performance with mediating role of the sustainable competitive position. Hypotheses were tested using structural equation modeling in Analysis Moment of Structure (AMOS) on a data set of 326 Pakistani Small and Medium Size Enterprises (SMEs). The results indicate that government financial and nonfinancial support have a significant influence on sustainable competitive position and firm performance. Additionally, a sustainable competitive position partially mediates the relationship between government support and firm performance. Government bodies and policy makers are advised to provide financial and nonfinancial support to SMEs which in turn can upsurge economic growth and sustainability.
Journal Article
An empirical study on quality of life and related factors of Pakistani breast cancer survivors
A comprehensive understanding of the quality of life (QoL) is essential to establish long-term survivor care plans. The present study was aimed at the assessment of QoL of BC survivors with special emphasis on post-treatment physical, emotional, social, and spiritual challenges. We have assessed the QoL of 250 female BC survivors of all age groups through demographic factors. Volunteer BC survivors were registered in the present study who had got treatment from the Institute of Nuclear Medicine and Oncology (INMOL) hospital and Mayo hospital Lahore. An informed consent form was signed by each participant. The physical, psychological, and spiritual well-being was evaluated by a questionnaire filled with the help of respondents. The average age of BC survivors was 52 ± 7.8 years. Most of them (83%) complained of fatigue during daily life activities, 75.1% body pain or headache, 77.1% had problems with appetite, 63.2% reported weight loss, 77.1% had sleep problems, and 90.5% were feeling general weakness. Only 16.2% were satisfied with their physical health and 2% were not satisfied with their medication. Psychologically, 74.4% were feeling different levels of anxiety, only 10% of them were hoping to achieve a desired life. Age group 21 to 40 years reported better physical health, those with 40–50 years of age and family history of BC have shown better mental strength. The physical and psychological health of survivors from rural areas was comparatively better than those from urban areas. The BC survivor women have to face several physical, psychological and social challenges. The majorities of them complain of anxiety, body pain, fatigue, sleep problems, general weakness, and fear about the future. Our findings suggest the need for psychological support, physical activity a comprehensive post-diagnosis and post-treatment physical and mental health assistance plan for all BC survivors.
Implications for Cancer Survivors
. Survivors of breast cancer experience various challenges including anxiety, sleep problems, body pain, fatigue, and fear about the future. The psychological, physical and social factors make a great difference in their quality of life.
Journal Article
BI-SENT: bilingual aspect-based sentiment analysis of COVID-19 Tweets in Urdu language
The COVID-19 pandemic resulted in over 600 million cases worldwide, and significantly impacted both physical and mental health, fostering widespread anxiety and fear. Consequently, the extensive use of online social networks to express emotions made sentiment analysis a crucial tool for understanding public sentiment. Traditionally, sentiment analysis in the Urdu language has focused on sentence-level analysis. However, aspect-level sentiment analysis is increasingly important and remains underexplored due to the challenges of the costly and time-consuming manual dataset annotation process. This study presents an innovative bilingual aspect-based sentiment analysis for Urdu and Roman Urdu using unsupervised methods. For Urdu, a syntactic rule-based approach achieves an accuracy of 83% in extracting aspect terms, marking a 5% improvement in F1-score over existing methods. For Roman Urdu, the study employs collocation patterns and topic modeling to identify and categorize key aspects, resulting in a perplexity score of –7 and a coherence score of 41. The results not only demonstrate the semantic coherence of the identified categories but also represent a significant advancement in aspect-level sentiment analysis by eliminating the need for manual annotation. This study offers new insights into the sentiments expressed during the pandemic, providing valuable feedback for policymakers and health organizations.
Journal Article