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3,107 results on '"Murtaza, Ghulam"'

3. Particulate and gaseous air pollutants exceed WHO guideline values and have the potential to damage human health in Faisalabad, Metropolitan, Pakistan.

Author

Zeeshan, Nukshab, Murtaza, Ghulam, Ahmad, Hamaad, Awan, Abdul, Shahbaz, Muhammad, and Freer-Smith, Peter

Subjects
Air quality index, CO, Heavy metals, Human health, NO2, Particulates, SO2, Pakistan, Humans, Air Pollutants, Environmental Monitoring, Particulate Matter, Air Pollution, Seasons, World Health Organization, Sulfur Dioxide, Cities, Nitrogen Dioxide, Environmental Exposure, Carbon Monoxide
Abstract

First-ever measurements of particulate matter (PM2.5, PM10, and TSP) along with gaseous pollutants (CO, NO2, and SO2) were performed from June 2019 to April 2020 in Faisalabad, Metropolitan, Pakistan, to assess their seasonal variations; Summer 2019, Autumn 2019, Winter 2019-2020, and Spring 2020. Pollutant measurements were carried out at 30 locations with a 3-km grid distance from the Sitara Chemical Industry in District Faisalabad to Bhianwala, Sargodha Road, Tehsil Lalian, District Chiniot. ArcGIS 10.8 was used to interpolate pollutant concentrations using the inverse distance weightage method. PM2.5, PM10, and TSP concentrations were highest in summer, and lowest in autumn or winter. CO, NO2, and SO2 concentrations were highest in summer or spring and lowest in winter. Seasonal average NO2 and SO2 concentrations exceeded WHO annual air quality guide values. For all 4 seasons, some sites had better air quality than others. Even in these cleaner sites air quality index (AQI) was unhealthy for sensitive groups and the less good sites showed Very critical AQI (> 500). Dust-bound carbon and sulfur contents were higher in spring (64 mg g-1) and summer (1.17 mg g-1) and lower in autumn (55 mg g-1) and winter (1.08 mg g-1). Venous blood analysis of 20 individuals showed cadmium and lead concentrations higher than WHO permissible limits. Those individuals exposed to direct roadside pollution for longer periods because of their occupation tended to show higher Pb and Cd blood concentrations. It is concluded that air quality along the roadside is extremely poor and potentially damaging to the health of exposed workers.

Published
2024

34. Efficient room-temperature molecular single-photon sources for quantum key distribution

Author

Murtaza, Ghulam, Colautti, Maja, Hilke, Michael, Lombardi, Pietro, Cataliotti, Francesco Saverio, Zavatta, Alessandro, Bacco, Davide, and Toninelli, Costanza

Subjects
Quantum Physics
Abstract

Quantum Key Distribution (QKD) allows the distribution of cryptographic keys between multiple users in an information-theoretic secure way, exploiting quantum physics. While current QKD systems are mainly based on attenuated laser pulses, deterministic single-photon sources could give concrete advantages in terms of secret key rate (SKR) and security owing to the negligible probability of multi-photon events. Here, we introduce and demonstrate a proof-of-concept QKD system exploiting a molecule-based single-photon source operating at room temperature and emitting at 785nm. With an estimated SKR of 0.5 Mbps, our solution paves the way for room-temperature single-photon sources for quantum communication protocols., Comment: 15 pages 5 figures

Published
2022
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48. Morphological and molecular characterization of variation in common bean (Phaseolus vulgaris L.) germplasm from Azad Jammu and Kashmir, Pakistan

Author

Nasar, Sidra, Ostevik, Kate, Murtaza, Ghulam, and Rausher, Mark D

Subjects
Agricultural, Veterinary and Food Sciences, Biological Sciences, Genetics, Plant Biology, Agriculture, Land and Farm Management, Horticultural Production, Genetic Variation, Microsatellite Repeats, Pakistan, Phaseolus, Phenotype, Plant Breeding, General Science & Technology
Abstract

Phaseolus vulgaris, an essential food and source of protein, is cultivated across the world. This study was carried out to investigate the diversity and population structure of 34 P. vulgaris landrace accessions collected from the Azad Jammu and Kashmir (AJ&K) regions of Pakistan. The samples were analyzed both morphologically and using genetic variation identified through RNA sequencing. Our results indicated that most genetic variation occurs among local accessions, with little genetic variation occurring between geographical regions. In addition, the accessions fell into two major genetic groups. Morphological analysis revealed that these two genetic groups differ in a number of quantitative traits, including seed length, seed width, and seed weight. One accession, DUD-11, appears to be a mixture of the two major groups genetically as well as morphologically. Among the other accessions, DUD-8, RWK-2, and NGD-1 depicted particularly high seed weight along with higher seed length, seed width, and seed yield per plant. We suggest focusing on these accessions in future breeding programs. More generally, our results provide baseline data that will be useful for crop improvement and effective cultivation practices in Pakistan.

Published
2022

49. Indistinguishable photons on demand from an organic dye molecule

Author

Lombardi, Pietro, Colautti, Maja, Duquennoy, Rocco, Murtaza, Ghulam, Majumder, Prosenjit, and Toninelli, Costanza

Subjects
Quantum Physics, Physics - Optics
Abstract

Single molecules in solid-state matrices have been proposed as sources of single-photon Fock states back 20 years ago. Their success in quantum optics and in many other research fields stems from the simple recipes used in the preparation of samples, with hundreds of nominally identical and isolated molecules. Main challenges as of today for their application in photonic quantum technologies are the optimization of light extraction and the on-demand emission of indistinguishable photons. We here present Hong-Ou-Mandel experiments with photons emitted by a single molecule of dibenzoterrylene in an anthracene nanocrystal at 3 K, under continuous wave and also pulsed excitation. A detailed theoretical model is applied, which relies on independent measurements for most experimental parameters, hence allowing for an analysis of the different contributions to the two-photon interference visibility, from residual dephasing to spectral filtering.

Published
2021

50. SimpleChrome: Encoding of Combinatorial Effects for Predicting Gene Expression

Author

Cheng, Wei, Murtaza, Ghulam, and Wang, Aaron

Subjects
Quantitative Biology - Genomics, Computer Science - Machine Learning
Abstract

Due to recent breakthroughs in state-of-the-art DNA sequencing technology, genomics data sets have become ubiquitous. The emergence of large-scale data sets provides great opportunities for better understanding of genomics, especially gene regulation. Although each cell in the human body contains the same set of DNA information, gene expression controls the functions of these cells by either turning genes on or off, known as gene expression levels. There are two important factors that control the expression level of each gene: (1) Gene regulation such as histone modifications can directly regulate gene expression. (2) Neighboring genes that are functionally related to or interact with each other that can also affect gene expression level. Previous efforts have tried to address the former using Attention-based model. However, addressing the second problem requires the incorporation of all potentially related gene information into the model. Though modern machine learning and deep learning models have been able to capture gene expression signals when applied to moderately sized data, they have struggled to recover the underlying signals of the data due to the nature of the data's higher dimensionality. To remedy this issue, we present SimpleChrome, a deep learning model that learns the latent histone modification representations of genes. The features learned from the model allow us to better understand the combinatorial effects of cross-gene interactions and direct gene regulation on the target gene expression. The results of this paper show outstanding improvements on the predictive capabilities of downstream models and greatly relaxes the need for a large data set to learn a robust, generalized neural network. These results have immediate downstream effects in epigenomics research and drug development.

Published
2020

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