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Article ; Online: WITHDRAWN: Original Antigenic Sin in COVID-19: Hoskins Effect and Vaccine

Khan, Mudassir / Manzoor, Sobia / Ullah, Najeeb / Khan, Dilawar

2022

Language	English
Publishing date	2022-03-17
Publishing country	United Arab Emirates
Document type	Journal Article
ZDB-ID	2234298-9
ISSN	2212-3989 ; 1871-5265
ISSN (online)	2212-3989
ISSN	1871-5265
DOI	10.2174/1871526522666220317154549
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Article ; Online: Assessment of heavy metal distribution and bioaccumulation in soil and plants near coal mining areas: implications for environmental pollution and health risks.

Akbar, Waqas Ali / Rahim, Hafeez Ur / Irfan, Muhammad / Sehrish, Adiba Khan / Mudassir, Muhammad

Environmental monitoring and assessment

2023 Volume 196, Issue 1, Page(s) 97

Abstract: Monitoring heavy metals (HMs) across source distance and depth distribution near coal mining sites is essential for preventing environmental pollution and health risks. This study investigated the distribution of selected HMs, cadmium ( ... ...

Abstract	Monitoring heavy metals (HMs) across source distance and depth distribution near coal mining sites is essential for preventing environmental pollution and health risks. This study investigated the distribution of selected HMs, cadmium (Cd
MeSH term(s)	Bioaccumulation ; Coal Mining ; Cadmium ; Copper ; Carbon ; Lead ; Soil ; Environmental Monitoring ; Environmental Pollution ; Metals, Heavy
Chemical Substances	Cadmium (00BH33GNGH) ; Copper (789U1901C5) ; Carbon (7440-44-0) ; Lead (2P299V784P) ; Soil ; Metals, Heavy
Language	English
Publishing date	2023-12-28
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	782621-7
ISSN	1573-2959 ; 0167-6369
ISSN (online)	1573-2959
ISSN	0167-6369
DOI	10.1007/s10661-023-12258-7
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Article ; Online: Retraction Note: pH-responsive CAP-co-poly(methacrylic acid)-based hydrogel as an efficient platform for controlled gastrointestinal delivery: fabrication, characterization, in vitro and in vivo toxicity evaluation.

Shah, Syed Ahmed / Sohail, Muhammad / Minhas, Muhammad Usman / Nisar-Ur-Rehman / Khan, Shahzeb / Hussain, Zahid / Mudassir / Mahmood, Arshad / Kousar, Mubeen / Mahmood, Asif

Drug delivery and translational research

2024

Language	English
Publishing date	2024-04-11
Publishing country	United States
Document type	Retraction of Publication
ZDB-ID	2590155-2
ISSN	2190-3948 ; 2190-393X
ISSN (online)	2190-3948
ISSN	2190-393X
DOI	10.1007/s13346-024-01600-2
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Article ; Online: A featureless approach for object detection and tracking in dynamic environments.

Zohaib, Mohammad / Ahsan, Muhammad / Khan, Mudassir / Iqbal, Jamshed

PloS one

2023 Volume 18, Issue 1, Page(s) e0280476

Abstract: One of the challenging problems in mobile robotics is mapping a dynamic environment for navigating robots. In order to disambiguate multiple moving obstacles, state-of-art techniques often solve some form of dynamic SLAM (Simultaneous Localization and ... ...

Abstract	One of the challenging problems in mobile robotics is mapping a dynamic environment for navigating robots. In order to disambiguate multiple moving obstacles, state-of-art techniques often solve some form of dynamic SLAM (Simultaneous Localization and Mapping) problem. Unfortunately, their higher computational complexity press the need for simpler and more efficient approaches suitable for real-time embedded systems. In this paper, we present a ROS-based efficient algorithm for constructing dynamic maps, which exploits the spatial-temporal locality for detecting and tracking moving objects without relying on prior knowledge of their geometrical features. A two-prong contribution of this work is as follows: first, an efficient scheme for decoding sensory data into an estimated time-varying object boundary that ultimately decides its orientation and trajectory based on the iteratively updated robot Field of View (FoV); second, lower time-complexity of updating the dynamic environment through manipulating spatial-temporal locality available in the object motion profile. Unlike existing approaches, the snapshots of the environment remain constant in the number of moving objects. We validate the efficacy of our algorithm on both V-Rep simulations and real-life experiments with a wide array of dynamic environments. We show that the algorithm accurately detects and tracks objects with a high probability as long as sensor noise is low and the speed of moving objects remains within acceptable limits.
MeSH term(s)	Artificial Intelligence ; Robotics/methods ; Algorithms ; Motion
Language	English
Publishing date	2023-01-17
Publishing country	United States
Document type	Journal Article
ZDB-ID	2267670-3
ISSN	1932-6203 ; 1932-6203
ISSN (online)	1932-6203
ISSN	1932-6203
DOI	10.1371/journal.pone.0280476
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Article: Petechiae Over Face: A Case of Rumpel-Leede Phenomenon.

Khan, Hania Qamar / Adil, Mohammad / Amin, Syed Suhail / Mudassir, Mohammad

Indian dermatology online journal

2020 Volume 11, Issue 4, Page(s) 658–659

Keywords	covid19
Language	English
Publishing date	2020-01-24
Publishing country	India
Document type	Journal Article
ZDB-ID	2585814-2
ISSN	2249-5673 ; 2229-5178
ISSN (online)	2249-5673
ISSN	2229-5178
DOI	10.4103/idoj.IDOJ_441_19
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Article: An automatic diagnostic model for the detection and classification of cardiovascular diseases based on swarm intelligence technique.

Venkatesh, C / V S Prasad, B V / Khan, Mudassir / Babu, J Chinna / Dasu, M Venkata

Heliyon

2024 Volume 10, Issue 3, Page(s) e25574

Abstract: Globally, cardiovascular diseases (CVDs) rank among the leading causes of mortality. One out of every three deaths is attributed to cardiovascular disease, according to new World Heart Federation research. Cardiovascular disease can be caused by a number ...

Abstract	Globally, cardiovascular diseases (CVDs) rank among the leading causes of mortality. One out of every three deaths is attributed to cardiovascular disease, according to new World Heart Federation research. Cardiovascular disease can be caused by a number of factors, including stress, alcohol, smoking, a poor diet, inactivity, and other medical disorders like high blood pressure or diabetes. In contrast, for the vast majority of heart disorders, early diagnosis of associated ailments results in permanent recovery. Using newly developed data analysis technology, examining a patient's medical record could aid in the early detection of cardiovascular disease. Recent work has employed machine learning algorithms to predict cardiovascular illness on clinical datasets. However, because of their enormous dimension and class imbalance, clinical datasets present serious issues. An inventive model is offered in this work for addressing these problems. An efficient decision support system, also known as an assistive system, is proposed in this paper for the diagnosis and classification of cardiovascular disorders. It makes use of an optimisation technique and a deep learning classifier. The efficacy of traditional techniques for predicting cardiovascular disease using medical data is anticipated to advance with the combination of the two methodologies. Deep learning systems can reduce mortality rates by predicting cardiovascular illness based on clinical data and the patient's severity level. For an adequate sample size of synthesized samples, the optimisation process chooses the right parameters to yield the best prediction from an enhanced classifier. The 99.58% accuracy was obtained by the proposed method. Also, PSNR, sensitivity, specificity, and other metrics were calculated in this work and compared with systems that are currently in use.
Language	English
Publishing date	2024-02-05
Publishing country	England
Document type	Journal Article
ZDB-ID	2835763-2
ISSN	2405-8440
ISSN	2405-8440
DOI	10.1016/j.heliyon.2024.e25574
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Article ; Online: Plant-Based Nutraceutical Formulation Modulates the Human Gut Microbiota and Ferulic Acid Esterase Activity During In Vitro Fermentation.

Kunnummal, Saarika Pothuvan / Sori, Nidhi / Khan, Mudassir Azeez / Khan, Mahejibin

Current microbiology

2023 Volume 81, Issue 1, Page(s) 3

Abstract: Oxidative stress is an imbalance between free reactive oxygen species and antioxidant defences leading to neurological and other chronic disorders. The interaction between food and gut microbiota and their metabolites significantly reduces oxidative ... ...

Abstract	Oxidative stress is an imbalance between free reactive oxygen species and antioxidant defences leading to neurological and other chronic disorders. The interaction between food and gut microbiota and their metabolites significantly reduces oxidative stress and influences host physiology and metabolism. This process mainly involves enzymes that hydrolyse complex polysaccharides and produce metabolites. Ferulic acid esterases (FAE) one of the most important enzymes of the gut microbiome, release ferulic acid from feruloylated sugar ester conjugates, that occur naturally in grains, fruits, and vegetables. FA is crucial in combating oxidative stress resulted from free radical formation. This study investigated the effect of two plant-based nutraceutical formulations, cereal-millet-based (PC1) and fruit-vegetable-based (PC2), on gut microbiota and the production of FAE, short chain fatty acids (SCFA) and other small metabolites in in vitro fermentation using human faecal samples. After in vitro fermentation, both nutraceutical formulations increased the abundance of Bifidobacterium, Lactobacillus, Prevotella, Feacalibacteria, and Clostridium leptum. Furthermore, they induced the production of FAE, xylanase and pectinase enzymes, SCFA and other small metabolites, resulting in increased antioxidation activity of the fermentate. PC1 stimulated FAE and xylanase production more effectively. These results demonstrated a positive correlation between the feruloylated nutraceutical formulation and the production of FAE and other accessory enzymes, suggesting that PC1 and PC2 stimulate the proliferation of the FAE-producing microbial consortium of the gut microbiome and therefore, increase FA and SCFA concentration. From this study it is evident that FA-rich plant-based formulation can be used as a prophylactic nutraceutical supplement to alleviate oxidative stress by modulating the gut microbiota.
MeSH term(s)	Humans ; Fermentation ; Gastrointestinal Microbiome ; Fatty Acids, Volatile/metabolism ; Dietary Supplements ; Feces/microbiology
Chemical Substances	ferulic acid (AVM951ZWST) ; feruloyl esterase (EC 3.1.1.73) ; Fatty Acids, Volatile
Language	English
Publishing date	2023-11-08
Publishing country	United States
Document type	Journal Article
ZDB-ID	134238-1
ISSN	1432-0991 ; 0343-8651
ISSN (online)	1432-0991
ISSN	0343-8651
DOI	10.1007/s00284-023-03518-3
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Article ; Online: Machine learning-based assessment and simulation of land use modification effects on seasonal and annual land surface temperature variations

Mudassir Khan / Muhammad Qasim / Adnan Ahmad Tahir / Abida Farooqi

Heliyon, Vol 9, Iss 12, Pp e23043- (2023)

2023

Abstract: Rapid urban sprawl adversely impacts the local climate and the ecosystem components. Islamabad, one of South Asia's green and environment-friendly capitals, has experienced major Land Use Land Cover (LULC) changes over the past three decades consequently, ...

Abstract	Rapid urban sprawl adversely impacts the local climate and the ecosystem components. Islamabad, one of South Asia's green and environment-friendly capitals, has experienced major Land Use Land Cover (LULC) changes over the past three decades consequently, elevating the seasonal and annual Land Surface Temperature (LST) in planned and unplanned urban areas. The focus of this study was to quantify the fluctuations in LULC and LST in planned and unplanned urban areas using Landsat data and Machine Learning algorithms involving the Support Vector Machine (SVM) over the 1990–2020 data period. Moreover, hybrid Cellular Automata-Markov (CA-Markov) and Artificial Neural Network (ANN) models were employed to project the future changes in LULC and annual LST, respectively, for the years 2035 and 2050. The findings of the study reveal a distinct difference in seasonal and annual LST in planned and unplanned areas. Results showed an increase of ∼22 % in the built-up area but vegetation and bare soil decreased by ∼10 % and ∼12 %, respectively. Built-up land showed a maximum annual mean LST followed by bare-soil and vegetative surfaces. Seasonal analysis showed that summer months experience the highest LST, followed by spring, autumn and winter. Future projections revealed that the built-up areas (∼27 % in 2020) are likely to increase to ∼37 % and ∼50 %, and the areas under the highest annual mean LST class i.e., ≥28 °C are likely to increase to ∼19 % and ∼21 % in planned, and ∼38 % and ∼42 % in unplanned urban areas for the years 2035 and 2050, respectively. Planned areas have better temperature control with urban green spaces, and controlled infrastructure. The Capital Development Authority of Islamabad may be advised to control the expansion of built-up areas, grow urban forests, and thus mitigate the possible Urban Heat Island (UHI) effect.
Keywords	Urbanization ; Cellular automata-markov ; Artificial neural network ; Urban heat island ; Machine learning ; Urban forest ; Science (General) ; Q1-390 ; Social sciences (General) ; H1-99
Subject code	910
Language	English
Publishing date	2023-12-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Spatial and temporal analyses of land use changes with special focus on seasonal variation in snow cover in District Chitral; a Hindu Kush mountain region of Pakistan

Qasim, Muhammad / Khan, Mudassir / Rashid, Wajid

Remote Sensing Applications: Society and Environment. 2023 Jan., v. 29 p.100902-

2023

Abstract: Snow and glacier changes and increase in temperature due to climate change in Hindu Kush Himalayas (HKH) and its impacts are important for water resource management in the world and specifically for Pakistan, which is a water-stressed country. Being a ... ...

Abstract	Snow and glacier changes and increase in temperature due to climate change in Hindu Kush Himalayas (HKH) and its impacts are important for water resource management in the world and specifically for Pakistan, which is a water-stressed country. Being a mountainous region, the people living in HKH are highly susceptible to the adverse impacts induced by climate change. This paper therefore mainly focused on monitoring snow cover changes in district Chitral using USGS satellite images (Landsat5-TM, Landsat7-ETM+, and Landsat8-OLI) for the years 2000, 2004, 2008, 2012, and 2016. The maximum likelihood method was used for Land Use Land Cover (LULC) classification. For a better understanding of the pattern of seasonal variation in snow cover over time, the total study period was distributed in four quadrennials, and the dataset for each period was taken only for early winter (Oct-Nov). A marked increase (266.7%) in the built-up area and 135.9 km² of agriculture expansion in this remote and mountainous area is quite significant. Results of the current study showed that in the year 2000, more than half (51.6%) of the total land of District Chitral was covered with snow in early winter, but it drastically decreased to only 6.8% in the year 2008. During the first two quadrennials, 44.7% (5694.6 km²) of glaciated area exposed the barren rocks, while the overall changes in snow-cover areas are approximately 43.3% (5514.6 km²). The most significant impact of melting snow and glaciers is Glacial Lakes Outburst Floods (GLOFs). GLOFs may cause human deaths and injuries, while these are also a threat to agricultural land, forest, and residential areas. Based on the current study, it is recommended to enhance institutional capacity in the country to face different environmental hazards, including early warning systems on the local scale. Keeping in view the water stress and based agriculture-based economy of Pakistan, proper analysis and monitoring of snow should be carried out for the sack of water availability, drought or floods, and other environmental vulnerabilities.
Keywords	agricultural land ; climate change ; data collection ; drought ; environment ; forests ; glaciers ; humans ; land use ; land use and land cover maps ; mountains ; people ; satellites ; seasonal variation ; snow ; snowpack ; statistical analysis ; temperature ; water management ; water stress ; winter ; Himalayan region ; Pakistan ; Snow cover ; River flow ; Communities vulnerability ; Chitral
Language	English
Dates of publication	2023-01
Publishing place	Elsevier B.V.
Document type	Article ; Online
ISSN	2352-9385
DOI	10.1016/j.rsase.2022.100902
Database	NAL-Catalogue (AGRICOLA)

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Article: Machine learning-based assessment and simulation of land use modification effects on seasonal and annual land surface temperature variations.

Khan, Mudassir / Qasim, Muhammad / Tahir, Adnan Ahmad / Farooqi, Abida

Heliyon

2023 Volume 9, Issue 12, Page(s) e23043

Abstract	Rapid urban sprawl adversely impacts the local climate and the ecosystem components. Islamabad, one of South Asia's green and environment-friendly capitals, has experienced major Land Use Land Cover (LULC) changes over the past three decades consequently, elevating the seasonal and annual Land Surface Temperature (LST) in planned and unplanned urban areas. The focus of this study was to quantify the fluctuations in LULC and LST in planned and unplanned urban areas using Landsat data and Machine Learning algorithms involving the Support Vector Machine (SVM) over the 1990-2020 data period. Moreover, hybrid Cellular Automata-Markov (CA-Markov) and Artificial Neural Network (ANN) models were employed to project the future changes in LULC and annual LST, respectively, for the years 2035 and 2050. The findings of the study reveal a distinct difference in seasonal and annual LST in planned and unplanned areas. Results showed an increase of ∼22 % in the built-up area but vegetation and bare soil decreased by ∼10 % and ∼12 %, respectively. Built-up land showed a maximum annual mean LST followed by bare-soil and vegetative surfaces. Seasonal analysis showed that summer months experience the highest LST, followed by spring, autumn and winter. Future projections revealed that the built-up areas (∼27 % in 2020) are likely to increase to ∼37 % and ∼50 %, and the areas under the highest annual mean LST class i.e., ≥28 °C are likely to increase to ∼19 % and ∼21 % in planned, and ∼38 % and ∼42 % in unplanned urban areas for the years 2035 and 2050, respectively. Planned areas have better temperature control with urban green spaces, and controlled infrastructure. The Capital Development Authority of Islamabad may be advised to control the expansion of built-up areas, grow urban forests, and thus mitigate the possible Urban Heat Island (UHI) effect.
Language	English
Publishing date	2023-11-29
Publishing country	England
Document type	Journal Article
ZDB-ID	2835763-2
ISSN	2405-8440
ISSN	2405-8440
DOI	10.1016/j.heliyon.2023.e23043
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