Muhammad Talha

Investigation of macro and micro-nutrients in selected medicinal plants

Department of Chemistry, Government Degree College, Ara Khel FR, Kohat KPK, Pakistan. Riyadh Community College, King Saud University, Saudi Arabia. Department of Chemistry, Kohat University of Science and Technology, Kohat-26000, KPK, Pakistan. College of Science Research Centre, King Saud University, P. O. Box 2455, Riyadh 11451, Saudi Arabia. Department of Chemical Engineering, College of Engineering King Saud University Riyadh Saudi Arabia.

Photodynamic Effect of Ni Nanotubes on an HeLa Cell Line.

Nickel nanomaterials are promising in the biomedical field, especially in cancer diagnostics and targeted therapy, due to their distinctive chemical and physical properties. In this experiment, the toxicity of nickel nanotubes (Ni NTs) were tested in an in vitro cervical cancer model (HeLa cell line) to optimize the parameters of photodynamic therapy (PDT) for their greatest effectiveness. Ni NTs were synthesized by electrodeposition. Morphological analysis and magnetic behavior were examined using a Scanning electron microscope (SEM), an energy dispersive X-ray analysis (EDAX) and a vibrating sample magnetometer (VSM) analysis. Phototoxic and cytotoxic effects of nanomaterials were studied using the Ni NTs alone as well as in conjugation with aminolevulinic acid (5-ALA); this was performed both in the dark and under laser exposure. Toxic effects on the HeLa cell model were evaluated by a neutral red assay (NRA) and by detection of intracellular reactive oxygen species (ROS) production. Furthermore, 10–200 nM of Ni NTs was prepared in solution form and applied to HeLa cells in 96-well plates. Maximum toxicity of Ni NTs complexed with 5-ALA was observed at 100 J/cm2 and 200 nM. Up to 65–68% loss in cell viability was observed. Statistical analysis was performed on the experimental results to confirm the worth and clarity of results, with p-values = 0.003 and 0.000, respectively. Current results pave the way for a more rational strategy to overcome the problem of drug bioavailability in nanoparticulate targeted cancer therapy, which plays a dynamic role in clinical practice.

Phytochemical analysis and biological activities of selected medicinal plants

Department of Community Health Sciences, College of Applied Medical Science, King Saud University, Riyadh 11433, Saudi Arabia. Department of Chemistry, Kohat University of Science and Technology KUST KPK Pakistan. Department of Chemistry, Islamia College University Peshawar, KPK, Pakistan. Department of Chemistry, College of Science, King Saud University, Riyadh 11451, Saudi Arabia. Department of Chemistry Government Degree College Ara Khel Jawaki FR Kohat KPK, Pakistan. Department of Chemical Engineering, College of Engineering, King Saud University, P. O. Box 800, Riyadh 11421, Kingdom of Saudi Arabia. College of Science Research Centre, King Saud University, P. O. Box 2455, Riyadh 11451, Saudi Arabia.

A Practical Approach: Design and Implementation of a Healthcare Software for Screening of Dysphonic Patients

Risk management in the development of medical software and devices is one of the most crucial processes in ensuring accurate diagnoses and treatment of disease. The consequences of wrong decisions that happen in our daily life might be unembellished. However, wrong decisions in healthcare based on unreliable evidence due to erroneous software could result in loss of life. Dysphonic patients suffering from various vocal fold disorders might have a threat of life due to inaccurate diagnosis. Some voice disorders, such as keratosis, are precancerous, and can become cancerous in cases that involve inaccurate diagnosis due to software failure. The objective of this paper is to design and implement a healthcare software for the detection of voice disorders in nonperiodic speech signals. Occurrences of potential risks during the design and development of the proposed software are taken into account to avoid failure. The software is implemented by applying the local binary pattern (LBP) operator on the textures of nonperiodic signals. The textures are obtained through the recurrence plot. The LBP operator computes the histograms for normal persons and dysphonic patients, and these histograms are used with the support vector machine for the automatic classification of dysphonic patients. The software is evaluated and tested by using the Massachusetts Eye and Ear Infirmary voice disorder database. The success rate of the proposed healthcare system is 97.73% ± 1.2, and the area under the receiver operating characteristic curve is 0.98 ± 0. The performance of the proposed healthcare system is much better than the existing commercial software used for screening dysphonic patients.

Ion Exchange Kinetics of Heavy Metal Ions on Organic–Inorganic Composite Cation Exchanger Poly-o-toluidine Zr(IV) Tungstate

To study the ion exchange kinetics of heavy metal ions on the organic–inorganic composite cation exchanger poly-o-toluidine Zr(IV) tungstate, Nernst–Planck was computer simulated. Simulated numerical results for counter ions (Cu, Zn, Cd and Pb) of equal valence and four different ionic mobilities are presented to understand the ionic diffusion process. These results are based on the fractional attainment of equilibrium U(τ), of the counter ions under study. The forward (M2+–H+) and reverse (H+–M2+) ion exchange processes are justified as the particle diffusion phenomenon. The self-diffusion coefficient (Do), energy of activation (Ea), and entropy of activation (∆S*) have also been estimated to understand the ion exchange process occurring over the surface of this cation exchanger and indicated that the ion exchange process is feasible and spontaneous. It is concluded that the difference in activation energies and entropy of activation may facilitate the separation of metal ions. The regeneration capability of this cation exchanger was also explained.

Evaluation of the chemical composition and element analysis of Urtica dioca

1 Department of Chemistry, College of Science, King Saud University, Riyadh 11451, Saudi Arabia. 2 Department of Chemistry, Gomal University, Dera Ismail Khan, Pakistan. 3 Diabetis and Nutritional Sciences Division, King’s College London. 4 Department of Community Health Sciences, College of Applied Medical Science, King Saud University, Riyadh 11433, Saudi Arabia. 5 Department of Chemistry, GDC Ara Khel Jawaki FR Kohat KPK, Pakistan. 6 Department of Chemical Engineering, College of Engineering, King Saud University, P. O. Box 800, Riyadh 11421, Kingdom of Saudi Arabia. 7 College of Science Research Centre, King Saud University, P. O. Box 2455, Riyadh 11451, Saudi Arabia. 8 Department of Chemistry, Kohat University of Science and Technology, KPK Pakistan.

Big Data Processing using Internet of Software Defined Things in Smart Cities

Software Defined Networks (SDN) has been attracting researchers, scientist, and technology experts from both academia and industry to enhance the current ICT stakes and networking paradigm. The beauty of SDN is the division of Control and Data planes and make it easy for the engineers to modify the networking protocols without visiting onsite devices. Similarly, smart cities concept has been coined recently, where a plethora of smart devices will be connected and providing tons of services to the citizens, officials, and governmental departments. The Internet of Things (IoT) plays a vital role in guaranteeing such services. Few efforts have been made to merge SDN and IoT with the sole purpose of efficient Data retrieval and achieve remotely configurable networks. In this paper, we explicitly define the Internet of Software Defined Things architecture and bring it to Smart Cities as a use-case. Our 3-tier architecture consists of Data Collection, Data Management, and Application levels that are further connected via two intermediate levels working on SDN principles. Followed by the potentials of SDN and IoT for Smart Cities, we evaluated our proposed architecture using Spark and GraphX with Hadoop Ecosystem and the results shows that efficient transfer of Data over SDN for real-time processing is achieved.

Multicriteria-Based Location Privacy Preservation in Vehicular Ad Hoc Networks

Vehicular ad hoc networks (VANETs) are the preferable choice for Intelligent Transportation Systems (ITS) because of its prevailing significance in both safety and nonsafety applications. Information dissemination in a multihop fashion along with privacy preservation of source node is a serious but challenging issue. We have used the idea of the phantom node as the next forwarder for data dissemination. The phantom node (vehicle) hides the identity of actual source node thus preserving the location privacy. The selection of the phantom node among the set of alternatives’ candidate vehicles is considered as a multicriteria-based problem. The phantom node selection problem is solved by using an analytical network process (ANP) by considering different traffic scenarios. The selection is based on different parameters which are distance, speed, trust, acceleration, and direction. The best alternative (target phantom vehicle) is selected through an ANP where all the alternatives are ranked from best to worst. The vehicle having maximum weight is considered to be the best choice as a phantom node. In order to check the stability of the alternatives’ ranking, sensitivity analysis is performed by taking into account different traffic scenarios and interest level of candidate vehicles.