Ali Raza

Shenzhen University

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i-10 index

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Co-Authors

Muhammad Bilal Hafeez

Northwest A&F University

Noreen Zahra

University of Agriculture Faisalabad

Xiling Zou

Oil Crops Research Institute

Sidra Charagh

China National Rice Research Institute

Rajeev K. Varshney

Murdoch University

Yan Lv

Yunnan University

Yong Cheng

Peking University People's Hospital

Wei Su

Xinxiang Medical University

Kanval Shaukat

University of Balochistan

Xiaoyu Ding

Chinese Academy of Fishery Sciences

Cooperative Institutions

University of Oxford

623

Johns Hopkins Hospital

353

All India Institute of Medical Sciences Rishikesh

307

All India Institute of Medical Sciences Raipur

306

University of Agriculture Faisalabad

259

Inserm

223

University of Faisalabad

151

Assistance Publique – Hôpitaux de Paris

134

Government College University, Faisalabad

109

Prince Charles Hospital

107

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Determination of florfenicol by Raman spectroscopy with principal component analysis (PCA) and partial least squares regression (PLSR)

Analytical Letters (2023)

Zain Ali Haq Nawaz Muhammad Irfan Majeed Nosheen Rashid Mashkoor Mohsin

Raman spectroscopy is an important analytical technique because of its use for the quantification of different antibiotics used for the treatment of different diseases. Florfenicol is considered a broad-spectrum antibiotic drug that is used for bacterial infection and livestock species, including porcine, bovine, and chicken. In the current study, the qualitative and quantitative evolution of different concentrations of florfenicol drug along with a number of excipients has been done by using Raman spectroscopy. Some major Raman peaks such as 379 cm−1, 478 cm−1, 878 cm−1, 918 cm−1, 1341 cm−1 and 1457 cm−1 are related to the excipient and 630 cm−1, 769 cm−1, 973 cm−1, 1142 cm−1 and 1681 cm−1 are related to the API concentrations and their intensities are increased and decreased with different concentration of excipient and API. The determination of Raman spectral data set of different concentrations of florfenicol drug has been done by using principal component analysis and partial least square regression model. The results of this study can lead to establishing an effective and reliable method to verify florfenicol contents in pharmaceutical samples which may be employed on an industrial scale.

Florfenicol

Principal component regression

Excipient

Chemometrics

10.1080/00032719.2023.2192942

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Citations (6)

A manipulative interplay between positive and negative regulators of phytohormones: A way forward for improving drought tolerance in plants

Physiologia Plantarum (2021)

Muhammad Salman Mubarik Sultan Habibullah Khan Muhammad Sajjad Ali Raza Muhammad Bilal Hafeez

Among different abiotic stresses, drought stress is the leading cause of impaired plant growth and low productivity worldwide. It is therefore essential to understand the process of drought tolerance in plants and thus to enhance drought resistance. Accumulating evidence indicates that phytohormones are essential signaling molecules that regulate diverse processes of plant growth and development under drought stress. Plants can often respond to drought stress through a cascade of phytohormones signaling as a means of plant growth regulation. Understanding biosynthesis pathways and regulatory crosstalk involved in these vital compounds could pave the way for improving plant drought tolerance while maintaining overall plant health. In recent years, the identification of phytohormones related key regulatory genes and their manipulation through state-of-the-art genome engineering tools have helped to improve drought tolerance plants. To date, several genes linked to phytohormones signaling networks, biosynthesis, and metabolism have been described as a promising contender for engineering drought tolerance. Recent advances in functional genomics have shown that enhanced expression of positive regulators involved in hormone biosynthesis could better equip plants against drought stress. Similarly, knocking down negative regulators of phytohormone biosynthesis can also be very effective to negate the negative effects of drought on plants. This review explained how manipulating positive and negative regulators of phytohormone signaling could be improvised to develop future crop varieties exhibiting higher drought tolerance. In addition, we also discuss the role of a promising genome editing tool, CRISPR/Cas9, on phytohormone mediated plant growth regulation for tackling drought stress.

Crosstalk

Drought Tolerance

Crop Productivity

Drought stress

10.1111/ppl.13325

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Citations (89)

Seed priming with zinc ion on growth performance and nutrient acquisition of maize in aridisols

Pakistan Journal of Botany (2023)

Ali Raza Mukkram Ali Tahir Noor-us- Sabah Sabir Hussain Shah Ghulam Sarwar

Priming (agriculture)

10.30848/pjb2023-4(26)

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Citations (2)

BZR proteins: identification, evolutionary and expression analysis under various exogenous growth regulators in plants

Molecular Biology Reports (2022)

Uzair Ullah Abdullah Shalmani Mohammad Ilyas Ali Raza Sheraz Ahmad

10.1007/s11033-022-07814-2

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Citations (10)

Role of Aminolevulinic Acid in Mediating Salinity Stress Tolerance in Sunflower (Helianthus annuus L.)

Journal of soil science and plant nutrition (2023)

Irfana Lalarukh Noreen Zahra Aleena Shahzadi Muhammad Bilal Hafeez Sehar Shaheen

Helianthus annuus

Helianthus

Dry weight

10.1007/s42729-023-01406-0

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Citations (7)

Week Ahead Electricity Power and Price Forecasting Using Improved DenseNet-121 Method

Computers, materials & continua/Computers, materials & continua (Print) (2022)

Muhammad Irfan Ali Raza Faisal Althobiani Nasir Ayub Muhammad Idrees

In the Smart Grid (SG) residential environment, consumers change their power consumption routine according to the price and incentives announced by the utility, which causes the prices to deviate from the initial pattern. Thereby, electricity demand and price forecasting play a significant role and can help in terms of reliability and sustainability. Due to the massive amount of data, big data analytics for forecasting becomes a hot topic in the SG domain. In this paper, the changing and non-linearity of consumer consumption pattern complex data is taken as input. To minimize the computational cost and complexity of the data, the average of the feature engineering approaches includes: Recursive Feature Eliminator (RFE), Extreme Gradient Boosting (XGboost), Random Forest (RF), and are upgraded to extract the most relevant and significant features. To this end, we have proposed the DensetNet-121 network and Support Vector Machine (SVM) ensemble with Aquila Optimizer (AO) to ensure adaptability and handle the complexity of data in the classification. Further, the AO method helps to tune the parameters of DensNet (121 layers) and SVM, which achieves less training loss, computational time, minimized overfitting problems and more training/test accuracy. Performance evaluation metrics and statistical analysis validate the proposed model results are better than the benchmark schemes. Our proposed method has achieved a minimal value of the Mean Average Percentage Error (MAPE) rate i.e., 8% by DenseNet-AO and 6% by SVM-AO and the maximum accurateness rate of 92% and 95%, respectively.

Overfitting

Benchmark (surveying)

Adaptability

10.32604/cmc.2022.025863

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Citations (10)

Effect of copper nanoparticles on growth parameters of maize seedlings

International Journal of Nanotechnology (2022)

Abdur Rehman Helena A. L. Oliveira Abdul Mateen Adnan Arshad Ali Raza

10.1504/ijnt.2022.10050410

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Citations (0)

Using Anomaly Detection to Detect Poisoning Attacks in Federated Learning Applications

arXiv (Cornell University) (2022)

Ali Raza Shujun Li Kim Phuc Tran Ludovic Koehl

Adversarial attacks such as poisoning attacks have attracted the attention of many machine learning researchers. Traditionally, poisoning attacks attempt to inject adversarial training data in order to manipulate the trained model. In federated learning (FL), data poisoning attacks can be generalized to model poisoning attacks, which cannot be detected by simpler methods due to the lack of access to local training data by the detector. State-of-the-art poisoning attack detection methods for FL have various weaknesses, e.g., the number of attackers has to be known or not high enough, working with i.i.d. data only, and high computational complexity. To overcome above weaknesses, we propose a novel framework for detecting poisoning attacks in FL, which employs a reference model based on a public dataset and an auditor model to detect malicious updates. We implemented a detector based on the proposed framework and using a one-class support vector machine (OC-SVM), which reaches the lowest possible computational complexity O(K) where K is the number of clients. We evaluated our detector's performance against state-of-the-art (SOTA) poisoning attacks for two typical applications of FL: electrocardiograph (ECG) classification and human activity recognition (HAR). Our experimental results validated the performance of our detector over other SOTA detection methods.

Anomaly (physics)

10.48550/arxiv.2207.08486

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Citations (0)

THE JOURNAL OF MICROBIOLOGY AND MOLECULAR GENETICS (2022)

Ali Raza Muhammad Hairs Aamir Riaz Rumesha Rafiq Memoona Basharat

Agriculture is crucial for all of humanity and will continue to play a significant role in ensuring the continued food security of the world's expanding population. There are several illnesses that may affect plants, especially crop plants, which can result in significant reductions in production. Plants, and especially crop plants, are particularly susceptible to these diseases. The lessons learned from history show that illnesses of this kind not only harmed agricultural output but also had a negative impact on the economy. The majority of the losses may be attributed to fungal infections. Such fungal infections are imposing a continousthreat to the sustainability of plants gobally. These phytopathogens show great persistance in causing plant diseases and quality degradation. Pathogenic fungi employ a variety of techniques to colonies plants and infect them with illness. Necrotrophic fungi destroy their hosts and consume their remains, whereas other fungi invade live cells (biotrophs). Pathogenic growth is strictly controlled, and specific infection components are created, for the full invasion of vegetative organs. Fungal infections use a wide range of virulence determinants to further colonies hosts and spread illness. The roles that virulence variables play vary depending on the infection approach. Necrotrophic pathogens produce poisons that damage plant tissue, although most pathogens obstruct the main plant defense. Contrarily, biotrophs use effector chemicals to prevent plant cell damage and change the metabolism of plants in the pathogen's benefit.

10.52700/jmmg.v3i3.73

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Citations (1)

Role of foliar spray of plant growth regulators in improving photosynthetic pigments and metabolites in Plantago ovata (Psyllium) under salt stress–A field appraisal

Biocell (2023)

Abdul Samad Kanval Shaukat MAHMOOD-UR-REHMAN ANSARI Mereen Nizar Noreen Zahra

Salinity is one of the major abiotic factors that limit the growth and productivity of plants. Foliar application of plant growth regulators (PGRs) may help plants ameliorate the negative impacts of salinity. Thus, a field experiment was conducted at the Botanical Garden University of Balochistan, Quetta, to explore the potential role of PGRs, i.e., moringa leaf extract (MLE; 10%), proline (PRO; 1 µM), salicylic acid (SA; 250 µM), and thiourea (TU; 10 mM) in ameliorating the impacts of salinity (120 mM) on Plantago ovata, an important medicinal plant. Salinity hampered plant photosynthetic pigments and metabolites but elevated oxidative parameters. However, foliar application of PGRs enhanced photosynthetic pigments, including Chl b (21.11%), carotenoids (57.87%) except Chl a, activated the defense mechanisms by restoring and enhancing the metabolites, i.e., soluble sugars (49.68%), soluble phenolics (33.34%), and proline (31.47%), significantly under salinity stress. Furthermore, foliar supplementation of PGRs under salt stress led to a decrease of about 43.02% and 43.27% in hydrogen peroxide and malondialdehyde content, respectively. Thus, PGRs can be recommended for improved photosynthetic efficiency and metabolite content that can help to get better yield under salt stress, with the best and most effective treatments being those of PRO and MLE to predominately ameliorate the harsh impacts of salinity.

Plantago ovata

Biological pigment

Photosynthetic pigment

Photosynthetic efficiency

Plantago

10.32604/biocell.2023.023704

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Citations (8)