Displaying publications 1 - 20 of 27 in total

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  1. Natural language processing for analyzing online customer reviews: a survey, taxonomy, and open research challenges
    Malik N, Bilal M
    PeerJ Comput Sci, 2024;10:e2203.
    PMID: 39145232 DOI: 10.7717/peerj-cs.2203
    In recent years, e-commerce platforms have become popular and transformed the way people buy and sell goods. People are rapidly adopting Internet shopping due to the convenience of purchasing from the comfort of their homes. Online review sites allow customers to share their thoughts on products and services. Customers and businesses increasingly rely on online reviews to assess and improve the quality of products. Existing literature uses natural language processing (NLP) to analyze customer reviews for different applications. Due to the growing importance of NLP for online customer reviews, this study attempts to provide a taxonomy of NLP applications based on existing literature. This study also examined emerging methods, data sources, and research challenges by reviewing 154 publications from 2013 to 2023 that explore state-of-the-art approaches for diverse applications. Based on existing research, the taxonomy of applications divides literature into five categories: sentiment analysis and opinion mining, review analysis and management, customer experience and satisfaction, user profiling, and marketing and reputation management. It is interesting to note that the majority of existing research relies on Amazon user reviews. Additionally, recent research has encouraged the use of advanced techniques like bidirectional encoder representations from transformers (BERT), long short-term memory (LSTM), and ensemble classifiers. The rising number of articles published each year indicates increasing interest of researchers and continued growth. This survey also addresses open issues, providing future directions in analyzing online customer reviews.
  2. Biocatalytic remediation of pharmaceutically active micropollutants for environmental sustainability
    Bilal M, Lam SS, Iqbal HMN
    Environ Pollut, 2022 Jan 15;293:118582.
    PMID: 34856243 DOI: 10.1016/j.envpol.2021.118582
    The discharge of an alarming number of recalcitrant pollutants from various industrial activities presents a serious threat to environmental sustainability and ecological integrity. Bioremediation has gained immense interest around the world due to its environmentally friendly and cost-effective nature. In contrast to physical and chemical methods, the use of microbial enzymes, particularly immobilized biocatalysts, has been demonstrated as a versatile approach for the sustainable mitigation of environmental pollution. Considerable attention is now devoted to developing novel enzyme engineering approaches and state-of-the-art bioreactor design for ameliorating the overall bio-catalysis and biodegradation performance of enzymes. This review discusses the contemporary and state of the art technical and scientific progress regarding applying oxidoreductase enzyme-based biocatalytic systems to remediate a vast number of pharmaceutically active compounds from water and wastewater bodies. A comprehensive insight into enzyme immobilization, the role of mediators, bioreactors designing, and transformation products of pharmaceuticals and their associated toxicity is provided. Additional studies are necessary to elucidate enzymatic degradation mechanisms, monitor the toxicity levels of the resulting degraded metabolites and optimize the entire bio-treatment strategy for technical and economical affordability.
  3. Time-domain reconstruction using sensitivity coefficients for limited view ultrawide band tomography
    Abdullah MZ, Yin W, Bilal M, Armitage DW, Mackin R, Peyton AJ
    Rev Sci Instrum, 2007 Aug;78(8):084703.
    PMID: 17764343
    This article addresses time-domain ultrawide band (UWB) electromagnetic tomography for reconstructing the unknown spatial characteristic of an object from observations of the arrivals of short electromagnetic (EM) pulses. Here, the determination of the first peak arrival of the EM traces constitutes the forward problem, and the inverse problem aims to reconstruct the EM property distribution of the media. In this article, the finite-difference time-domain method implementing a perfectly matched layer is used to solve the forward problem from which the system sensitivity maps are determined. Image reconstruction is based on the combination of a linearized update and regularized Landweber minimization algorithm. Experimental data from a laboratory UWB system using targets of different contrasts, sizes, and shapes in an aqueous media are presented. The results show that this technique can accurately detect and locate unknown targets in spite of the presence of significant levels of noise in the data.
  4. Fulltext The non-Newtonian maxwell nanofluid flow between two parallel rotating disks under the effects of magnetic field
    Ahmadian A, Bilal M, Khan MA, Asjad MI
    Sci Rep, 2020 Oct 13;10(1):17088.
    PMID: 33051520 DOI: 10.1038/s41598-020-74096-8
    The main feature of the present numerical model is to explore the behavior of Maxwell nanoliquid moving within two horizontal rotating disks. The disks are stretchable and subjected to a magnetic field in axial direction. The time dependent characteristics of thermal conductivity have been considered to scrutinize the heat transfer phenomena. The thermophoresis and Brownian motion features of nanoliquid are studied with Buongiorno model. The lower and upper disk's rotation for both the cases, same direction as well as opposite direction of rotation is investigated. The subsequent arrangement of the three dimensional Navier Stoke's equations along with energy, mass and Maxwell equations are diminished to a dimensionless system of equations through the Von Karman's similarity framework. The comparative numerical arrangement of modeled equations is further set up by built-in numerical scheme "boundary value solver" (Bvp4c) and Runge Kutta fourth order method (RK4). The various physical constraints, such as Prandtl number, thermal conductivity, magnetic field, thermal radiation, time relaxation, Brownian motion and thermophoresis parameters and their impact are presented and discussed briefly for velocity, temperature, concentration and magnetic strength profiles. In the present analysis, some vital characteristics such as Nusselt and Sherwood numbers are considered for physical and numerical investigation. The outcomes concluded that the disk stretching action opposing the flow behavior. With the increases of magnetic field parameter [Formula: see text] the fluid velocity decreases, while improving its temperature. We show a good agreement of the present work by comparing with those published in literature.
  5. Fulltext Numerical analysis of thermal conductive hybrid nanofluid flow over the surface of a wavy spinning disk
    Ahmadian A, Bilal M, Khan MA, Asjad MI
    Sci Rep, 2020 Nov 02;10(1):18776.
    PMID: 33139760 DOI: 10.1038/s41598-020-75905-w
    A three dimensional (3D) numerical solution of unsteady, Ag-MgO hybrid nanoliquid flow with heat and mass transmission caused by upward/downward moving of wavy spinning disk has been scrutinized. The magnetic field has been also considered. The hybrid nanoliquid has been synthesized in the presence of Ag-MgO nanoparticles. The purpose of the study is to improve the rate of thermal energy transmission for several industrial purposes. The wavy rotating surface increases the heat transmission rate up to 15%, comparatively to the flat surface. The subsequent arrangement of modeled equations is diminished into dimensionless differential equation. The obtained system of equations is further analytically expounded via Homotopy analysis method HAM and the numerical Parametric continuation method (PCM) method has been used for the comparison of the outcomes. The results are graphically presented and discussed. It has been presumed that the geometry of spinning disk positively affects the velocity and thermal energy transmission. The addition of hybrid nanoparticles (silver and magnesium-oxide) significantly improved thermal property of carrier fluid. It uses is more efficacious to overcome low energy transmission. Such as, it provides improvement in thermal performance of carrier fluid, which play important role in power generation, hyperthermia, micro fabrication, air conditioning and metallurgical field.
  6. Fulltext Improved Reconstruction of MR Scanned Images by Using a Dictionary Learning Scheme
    Ikram S, Shah JA, Zubair S, Qureshi IM, Bilal M
    Sensors (Basel), 2019 Apr 23;19(8).
    PMID: 31018597 DOI: 10.3390/s19081918
    The application of compressed sensing (CS) to biomedical imaging is sensational since it permits a rationally accurate reconstruction of images by exploiting the image sparsity. The quality of CS reconstruction methods largely depends on the use of various sparsifying transforms, such as wavelets, curvelets or total variation (TV), to recover MR images. As per recently developed mathematical concepts of CS, the biomedical images with sparse representation can be recovered from randomly undersampled data, provided that an appropriate nonlinear recovery method is used. Due to high under-sampling, the reconstructed images have noise like artifacts because of aliasing. Reconstruction of images from CS involves two steps, one for dictionary learning and the other for sparse coding. In this novel framework, we choose Simultaneous code word optimization (SimCO) patch-based dictionary learning that updates the atoms simultaneously, whereas Focal underdetermined system solver (FOCUSS) is used for sparse representation because of a soft constraint on sparsity of an image. Combining SimCO and FOCUSS, we propose a new scheme called SiFo. Our proposed alternating reconstruction scheme learns the dictionary, uses it to eliminate aliasing and noise in one stage, and afterwards restores and fills in the k-space data in the second stage. Experiments were performed using different sampling schemes with noisy and noiseless cases of both phantom and real brain images. Based on various performance parameters, it has been shown that our designed technique outperforms the conventional techniques, like K-SVD with OMP, used in dictionary learning based MRI (DLMRI) reconstruction.
  7. Fulltext Respiratory Motion Correction for Compressively Sampled Free Breathing Cardiac MRI Using Smoothl1-Norm Approximation
    Bilal M, Shah JA, Qureshi IM, Kadir K
    Int J Biomed Imaging, 2018;2018:7803067.
    PMID: 29610569 DOI: 10.1155/2018/7803067
    Transformed domain sparsity of Magnetic Resonance Imaging (MRI) has recently been used to reduce the acquisition time in conjunction with compressed sensing (CS) theory. Respiratory motion during MR scan results in strong blurring and ghosting artifacts in recovered MR images. To improve the quality of the recovered images, motion needs to be estimated and corrected. In this article, a two-step approach is proposed for the recovery of cardiac MR images in the presence of free breathing motion. In the first step, compressively sampled MR images are recovered by solving an optimization problem using gradient descent algorithm. TheL1-norm based regularizer, used in optimization problem, is approximated by a hyperbolic tangent function. In the second step, a block matching algorithm, known as Adaptive Rood Pattern Search (ARPS), is exploited to estimate and correct respiratory motion among the recovered images. The framework is tested for free breathing simulated andin vivo2D cardiac cine MRI data. Simulation results show improved structural similarity index (SSIM), peak signal-to-noise ratio (PSNR), and mean square error (MSE) with different acceleration factors for the proposed method. Experimental results also provide a comparison betweenk-tFOCUSS with MEMC and the proposed method.
  8. Social Profiling: A Review, Taxonomy, and Challenges
    Bilal M, Gani A, Lali MIU, Marjani M, Malik N
    Cyberpsychol Behav Soc Netw, 2019 Jul;22(7):433-450.
    PMID: 31074639 DOI: 10.1089/cyber.2018.0670
    Social media has taken an important place in the routine life of people. Every single second, users from all over the world are sharing interests, emotions, and other useful information that leads to the generation of huge volumes of user-generated data. Profiling users by extracting attribute information from social media data has been gaining importance with the increasing user-generated content over social media platforms. Meeting the user's satisfaction level for information collection is becoming more challenging and difficult. This is because of too much noise generated, which affects the process of information collection due to explosively increasing online data. Social profiling is an emerging approach to overcome the challenges faced in meeting user's demands by introducing the concept of personalized search while keeping in consideration user profiles generated using social network data. This study reviews and classifies research inferring users social profile attributes from social media data as individual and group profiling. The existing techniques along with utilized data sources, the limitations, and challenges are highlighted. The prominent approaches adopted include Machine Learning, Ontology, and Fuzzy logic. Social media data from Twitter and Facebook have been used by most of the studies to infer the social attributes of users. The studies show that user social attributes, including age, gender, home location, wellness, emotion, opinion, relation, influence, and so on, still need to be explored. This review gives researchers insights of the current state of literature and challenges for inferring user profile attributes using social media data.
  9. Biodegradation mechanism of chlorpyrifos by halophilic bacterium Hortaea sp. B15
    Hadibarata T, Kristanti RA, Bilal M, Yilmaz M, Sathishkumar P
    Chemosphere, 2023 Jan;312(Pt 1):137260.
    PMID: 36400190 DOI: 10.1016/j.chemosphere.2022.137260
    For decades, most of the developing nations have relied on chlorpyrifos for insecticidal activity in the agriculture sector. It is a common chlorinated organophosphorus pesticide that has been widely used to control insects to protect plants. This study aimed to investigate the effects of environmental characteristics such as salinity, pH, temperature, and surfactant on Hortaea sp. B15 mediated degradation of chlorpyrifos as well as enzyme activity and metabolic pathway. The highest bacterial growth (4.6 × 1016 CFU/mL) was achieved after 20 h of incubation in a 100 mg/L chlorpyrifos amended culture. The fit model and feasible way to express the chlorpyrifos biodegradation kinetics in normal condition and optimized was a first-order rate equation, with an R2 value of 0.95-0.98. The optimum pH for chlorpyrifos biodegradation was pH 9, which resulted in a high removal rate (91.1%) and a maximum total count of 3.8 × 1016 CFU/mL. Increasing the temperature over 40 °C may inhibit microbial development and biodegradation. There was no significant effect of culture salinity on degradation and bacterial growth. In the presence of non-ionic surfactant Tween 80, the maximum chlorpyrifos degradation (89.5%) and bacterial growth (3.8 × 1016 CFU/mL) was achieved. Metabolites such as 3,5,6-trichloropyridin-2-ol and 2-pyridinol were identified in the Hortaea sp. B15 mediated degradation of chlorpyrifos. According to the findings, Hortaea sp. B15 should be recommended for use in the investigation of in situ biodegradation of pesticides.
  10. Multi-Objective Task-Aware Offloading and Scheduling Framework for Internet of Things Logistics
    Umer A, Ali M, Jehangiri AI, Bilal M, Shuja J
    Sensors (Basel), 2024 Apr 09;24(8).
    PMID: 38675998 DOI: 10.3390/s24082381
    IoT-based smart transportation monitors vehicles, cargo, and driver statuses for safe movement. Due to the limited computational capabilities of the sensors, the IoT devices require powerful remote servers to execute their tasks, and this phenomenon is called task offloading. Researchers have developed efficient task offloading and scheduling mechanisms for IoT devices to reduce energy consumption and response time. However, most research has not considered fault-tolerance-based job allocation for IoT logistics trucks, task and data-aware scheduling, priority-based task offloading, or multiple-parameter-based fog node selection. To overcome the limitations, we proposed a Multi-Objective Task-Aware Offloading and Scheduling Framework for IoT Logistics (MT-OSF). The proposed model prioritizes the tasks into delay-sensitive and computation-intensive tasks using a priority-based offloader and forwards the two lists to the Task-Aware Scheduler (TAS) for further processing on fog and cloud nodes. The Task-Aware Scheduler (TAS) uses a multi-criterion decision-making process, i.e., the analytical hierarchy process (AHP), to calculate the fog nodes' priority for task allocation and scheduling. The AHP decides the fog nodes' priority based on node energy, bandwidth, RAM, and MIPS power. Similarly, the TAS also calculates the shortest distance between the IoT-enabled vehicle and the fog node to which the IoT tasks are assigned for execution. A task-aware scheduler schedules delay-sensitive tasks on nearby fog nodes while allocating computation-intensive tasks to cloud data centers using the FCFS algorithm. Fault-tolerant manager is used to check task failure; if any task fails, the proposed system re-executes the tasks, and if any fog node fails, the proposed system allocates the tasks to another fog node to reduce the task failure ratio. The proposed model is simulated in iFogSim2 and demonstrates a 7% reduction in response time, 16% reduction in energy consumption, and 22% reduction in task failure ratio in comparison to Ant Colony Optimization and Round Robin.
  11. Sustainable Hydrates for Enhanced Carbon Dioxide Capture from an Integrated Gasification Combined Cycle in a Fixed Bed Reactor
    Abu Hassan MH, Sher F, Fareed B, Ali U, Zafar A, Bilal M, et al.
    Ind Eng Chem Res, 2021 Aug 04;60(30):11346-11356.
    PMID: 34475634 DOI: 10.1021/acs.iecr.1c01174
    An increase in temperature of up to 2 °C occurs when the amount of CO2 reaches a range of 450 ppm. The permanent use of mineral oil is closely related to CO2 emissions. Maintaining the sustainability of fossil fuels and eliminating and reducing CO2 emissions is possible through carbon capture and storage (CCS) processes. One of the best ways to maintain CCS is hydrate-based gas separation. Selected type T1-5 (0.01 mol % sodium dodecyl sulphate (SDS) + 5.60 mol % tetrahydrofuran (THF), with the help of this silica gel promotion was strongly stimulated. A pressure of 36.5 bar of CO2 is needed in H2O to investigate the CO2 hydrate formation. Therefore, ethylene glycol monoethyl ether (EGME at 0.10 mol %) along with SDS (0.01 mol %) labeled as T1A-2 was used as an alternative to THF at the comparable working parameters in which CO2 uptake of 5.45 mmol of CO2/g of H2O was obtained. Additionally, it was found that with an increase in tetra-n-butyl ammonium bromide (TBAB) supplementation of CO2, the hydrate and operating capacity of the process increased. When the bed height was reduced from 3 cm to 2 cm with 0.1 mol % TBAB and 0.01% SDS (labelled as T3-2) in fixed bed reactor (FBR), the outcomes demonstrated a slight expansion in gas supply to 1.54 mmol of CO2/g of H2O at working states of 283 K and 70 bar. The gas selectivity experiment by using the high-pressure volume analysis through hydrate formation was performed in which the highest CO2 uptake for the employment of silica contacts with water in fuel gas mixture was observed in the non-IGCC conditions. Thus, two types of reactor configurations are being proposed for changing the process from batch to continuous with the employment of macroporous silica contacts with new consolidated promoters to improve the formation of CO2 hydrate in the IGCC conditions. Later, much work should be possible on this with an assortment of promoters and specific performance parameters. It was reported in previous work that the repeatability of equilibrium moisture content and gas uptake attained for the sample prepared by the highest rates of stirring was the greatest with the CIs of ±0.34 wt % and ±0.19 mmol of CO2/g of H2O respectively. This was due to the amount of water occluded inside silica gel pores was not an issue or in other words, vigorous stirring increased the spreadability. The variation of pore size to improve the process can be considered for future work.
  12. Fulltext Reduction of Motion Artifacts in the Recovery of Undersampled DCE MR Images Using Data Binning and L+S Decomposition
    Bilal M, Anis H, Khan N, Qureshi I, Shah J, Kadir KA
    Biomed Res Int, 2019;2019:6139785.
    PMID: 31119178 DOI: 10.1155/2019/6139785
    Background: Motion is a major source of blurring and ghosting in recovered MR images. It is more challenging in Dynamic Contrast Enhancement (DCE) MRI because motion effects and rapid intensity changes in contrast agent are difficult to distinguish from each other.

    Material and Methods: In this study, we have introduced a new technique to reduce the motion artifacts, based on data binning and low rank plus sparse (L+S) reconstruction method for DCE MRI. For Data binning, radial k-space data is acquired continuously using the golden-angle radial sampling pattern and grouped into various motion states or bins. The respiratory signal for binning is extracted directly from radially acquired k-space data. A compressed sensing- (CS-) based L+S matrix decomposition model is then used to reconstruct motion sorted DCE MR images. Undersampled free breathing 3D liver and abdominal DCE MR data sets are used to validate the proposed technique.

    Results: The performance of the technique is compared with conventional L+S decomposition qualitatively along with the image sharpness and structural similarity index. Recovered images are visually sharper and have better similarity with reference images.

    Conclusion: L+S decomposition provides improved MR images with data binning as preprocessing step in free breathing scenario. Data binning resolves the respiratory motion by dividing different respiratory positions in multiple bins. It also differentiates the respiratory motion and contrast agent (CA) variations. MR images recovered for each bin are better as compared to the method without data binning.

  13. Fulltext Total Synthesis of Terpenes and Their Biological Significance: A Critical Review
    Kanwal A, Bilal M, Rasool N, Zubair M, Shah SAA, Zakaria ZA
    Pharmaceuticals (Basel), 2022 Nov 11;15(11).
    PMID: 36422521 DOI: 10.3390/ph15111392
    Terpenes are a group of natural products made up of molecules with the formula (C5H8)n that are typically found in plants. They are widely employed in the medicinal, flavor, and fragrance industries. The total synthesis of terpenes as well as their origin and biological potential are discussed in this review.
  14. Evaluating the dynamic response and phase angle behavior of SBS-modified asphalt mixtures for enhanced pavement performance
    Khan I, Bilal M, Khaliq W, Khan N, Khahro SH, Memon ZA, et al.
    Sci Rep, 2024 Nov 27;14(1):29480.
    PMID: 39604467 DOI: 10.1038/s41598-024-79869-z
    Bitumen exhibits viscoelastic properties, showcasing both viscous and elastic behaviors, which are characterized by the phase angle and dynamic modulus. Issues like early fatigue fractures, rutting, and permanent deformations in bituminous asphalt pavements arise due to moisture susceptibility, high-temperature deformation, low-temperature cracking, and overloading. These distresses result in potholes, alligator cracks, and specific deformations that lead to early pavement failure, increasing rehabilitation and maintenance costs. To address these issues, this study examines the dynamic modulus and phase angle behavior of Styrene Butadiene Styrene (SBS) modified and unmodified asphalt mixtures. SBS was incorporated in various proportions, ranging from 2 to 7% by the weight of bitumen. The asphalt mixture performance tester (AMPT) was utilized to measure the dynamic modulus at temperatures of 4.4, 21.1, 37.8, and 54.4 °C, and frequencies of 0.1, 0.5, 1, 5, 10, and 25 Hz. The study found significant correlations between dynamic modulus, temperature, loading frequency, and SBS content. Additionally, Multi Expression Programming (MEPX) and regression modeling were employed to estimate the dynamic modulus of SBS-modified HMA. Results indicated that increasing SBS content up to 7% decreased penetration and ductility values by up to 46% and 56%, respectively, while raising the softening point by 63% due to increased stiffness. The blend with 6% SBS by weight of bitumen exhibited superior performance compared to other mixtures. Phase angle initially increased with rising temperature, peaking at 37.8 °C at lower frequencies, and continued to increase at higher frequencies. Isothermal and isochronal plots showed that the 0% SBS mix had a higher phase angle due to increased bitumen content. Overall, the HMA mix with 6% SBS provided the best outcomes.
  15. N-([1,1'-biaryl]-4-yl)-1-naphthamide-based scaffolds synthesis, their cheminformatics analyses, and screening as bacterial biofilm inhibitor
    Ejaz S, Zubair M, Rasool N, Ahmed F, Bilal M, Ahmad G, et al.
    J Basic Microbiol, 2021 Nov 01.
    PMID: 34724237 DOI: 10.1002/jobm.202100288
    Naphthamides have pharmacological potential as they express strong activities against microorganisms. The commercially available naphthoyl chloride and 4-bromoaniline were condensed in dry dichloromethane (DCM) in the presence of Et3 N to form N-(4-bromophenyl)-1-naphthamide (86%) (3). Using a Pd(0) catalyzed Suzuki-Miyaura Cross-Coupling reaction of (3) and various boronic acids, a series of N-([1,1'-biaryl]-4-yl)-1-naphthamide derivatives (4a-h) were synthesized in moderate to good yields. The synthesized derivatives were evaluated for cytotoxicity haemolytic assay and biofilm inhibition activity through in silico and in vitro studies. Molecular docking, ADME (absorption, distribution, metabolism, and excretion), toxicity risk, and other cheminformatics predict synthesized molecules as biologically active moieties, further validated through in vitro studies in which compounds (4c) and (4f) showed significant haemolytic activity whereas (4e) exhibited an efficient biofilm inhibition activity against Gram-negative bacteria Escherichia coli and Gram-positive bacteria Bacillus subtilis. When forming biofilms, bacteria become resistant to various antimicrobial treatments. Currently, research is focused on the development of agents that inhibit biofilm formation, thus the present work is valuable for preventing future drug resistance.
  16. Roles of clock genes in the pathogenesis of Parkinson's disease
    Shkodina AD, Tan SC, Hasan MM, Abdelgawad M, Chopra H, Bilal M, et al.
    Ageing Res Rev, 2022 02;74:101554.
    PMID: 34973458 DOI: 10.1016/j.arr.2021.101554
    Parkinson's disease (PD) is a common motor disorder that has become increasingly prevalent in the ageing population. Recent works have suggested that circadian rhythms disruption is a common event in PD patients. Clock genes regulate the circadian rhythm of biological processes in eukaryotic organisms, but their roles in PD remain unclear. Despite this, several lines of evidence point to the possibility that clock genes may have a significant impact on the development and progression of the disease. This review aims to consolidate recent understanding of the roles of clock genes in PD. We first summarized the findings of clock gene expression and epigenetic analyses in PD patients and animal models. We also discussed the potential contributory role of clock gene variants in the development of PD and/or its symptoms. We further reviewed the mechanisms by which clock genes affect mitochondrial dynamics as well as the rhythmic synthesis and secretion of endocrine hormones, the impairment of which may contribute to the development of PD. Finally, we discussed the limitations of the currently available studies, and suggested future potential studies to deepen our understanding of the roles of clock genes in PD pathogenesis.
  17. Metal-Organic Framework-Based Composites for the Detection and Monitoring of Pharmaceutical Compounds in Biological and Environmental Matrices
    Rizwan M, Selvanathan V, Rasool A, Qureshi MAUR, Iqbal DN, Kanwal Q, et al.
    Water Air Soil Pollut, 2022;233(12):493.
    PMID: 36466935 DOI: 10.1007/s11270-022-05904-2
    The production of synthetic drugs is considered a huge milestone in the healthcare sector, transforming the overall health, aging, and lifestyle of the general population. Due to the surge in production and consumption, pharmaceutical drugs have emerged as potential environmental pollutants that are toxic with low biodegradability. Traditional chromatographic techniques in practice are time-consuming and expensive, despite good precision. Alternatively, electroanalytical techniques are recently identified to be selective, rapid, sensitive, and easier for drug detection. Metal-organic frameworks (MOFs) are known for their intrinsic porous nature, high surface area, and diversity in structural design that provides credible drug-sensing capacities. Long-term reusability and maintaining chemo-structural integrity are major challenges that are countered by ligand-metal combinations, optimization of synthetic conditions, functionalization, and direct MOFs growth over the electrode surface. Moreover, chemical instability and lower conductivities limited the mass commercialization of MOF-based materials in the fields of biosensing, imaging, drug release, therapeutics, and clinical diagnostics. This review is dedicated to analyzing the various combinations of MOFs used for electrochemical detection of pharmaceutical drugs, comprising antibiotics, analgesics, anticancer, antituberculosis, and veterinary drugs. Furthermore, the relationship between the composition, morphology and structural properties of MOFs with their detection capabilities for each drug species is elucidated.
  18. Tricks and tracks in waste management with a special focus on municipal landfill leachate: Leads and obstacles
    Mohanty SS, Vyas S, Koul Y, Prajapati P, Varjani S, Chang JS, et al.
    Sci Total Environ, 2023 Feb 20;860:160377.
    PMID: 36414054 DOI: 10.1016/j.scitotenv.2022.160377
    Landfilling is the most widely used disposal method for municipal solid waste around the world. The main disadvantage of this strategy is formation of leachate, among other aspects. Landfill leachate contains highly toxic and bio-refractory substances that are detrimental to the environment and human health. Hence, the risk(s) of discharging potentially harmful landfill leachate into the environment need to be assessed and measured in order to make effective choices about landfill leachate management and treatment. In view of this, the present review aims to investigate (a) how landfill leachate is perceived as an emerging concern, and (b) the stakeholders' mid- to long-term policy priorities for implementing technological and integrative solutions to reduce the harmful effects of landfill leachate. Because traditional methods alone have been reported ineffective, and in response to emerging contaminants and stringent regulations, new effective and integrated leachate treatments have been developed. This study gives a forward-thinking of the accomplishments and challenges in landfill leachate treatment during the last decade. It also provides a comprehensive compilation of the formation and characterization of landfill leachate, the geo-environmental challenges that it raises, as well as the resource recovery and industrial linkage associated with it in order to provide an insight into its sustainable management.
  19. Fulltext Synthesis of 1-(4-Bromobenzoyl)-1,3-dicyclohexylurea and Its Arylation via Readily Available Palladium Catalyst-Their Electronic, Spectroscopic, and Nonlinear Optical Studies via a Computational Approach
    Maqbool T, Younas H, Bilal M, Rasool N, Bajaber MA, Mubarik A, et al.
    ACS Omega, 2023 Aug 22;8(33):30306-30314.
    PMID: 37636953 DOI: 10.1021/acsomega.3c03183
    In this study, we reported the synthesis of 1-(4-bromobenzoyl)-1,3-dicyclohexylurea by the reaction of DCC (N,N'-dicyclohexylcarbodiimide) with 4-bromobenzoic acid. Subsequently, we further synthesized a new series of 1-(4-arylbenzoyl)-1,3-dicyclohexylurea (5a-g) derivatives using a Suzuki cross-coupling reaction between 1-(4-bromobenzoyl)-1,3-dicyclohexylurea (3) and various aryl/heteroaryl boronic acids (4). Thus, density functional theory (DFT) calculations have been performed to examine the electronic structure of the synthesized compounds (3, 5a-g) and to calculate their spectroscopic data. Moreover, optimized geometries and thermodynamic properties, such as frontier molecular orbitals (HOMO, LUMO), molecular electrostatic potential surfaces, and reactivity descriptors, were also calculated at the PBE0-D3BJ/def2-TZVP/SMD1,4-dioxane level of theory to validate the structures of the synthesized compounds.
  20. Fulltext The impact of PEG-induced drought stress on seed germination and seedling growth of different bread wheat (Triticum aestivum L.) genotypes
    Mahpara S, Zainab A, Ullah R, Kausar S, Bilal M, Latif MI, et al.
    PLoS One, 2022;17(2):e0262937.
    PMID: 35148345 DOI: 10.1371/journal.pone.0262937
    Wheat is an important crop, used as staple food in numerous countries around the world. However, wheat productivity is low in the developing world due to several biotic and abiotic stresses, particularly drought stress. Non-availability of drought-tolerant wheat genotypes at different growth stages is the major constraint in improving wheat productivity in the developing world. Therefore, screening/developing drought-tolerant genotypes at different growth stages could improve the productivity of wheat. This study assessed seed germination and seedling growth of eight wheat genotypes under polyethylene glycol (PEG)-induced stress. Two PEG-induced osmotic potentials (i.e., -0.6 and -1.2 MPa) were included in the study along with control (0 MPa). Wheat genotypes included in the study were 'KLR-16', 'B6', 'J10', '716', 'A12', 'Seher', 'KTDH-16', and 'J4'. Data relating to seed germination percentage, root and shoot length, fresh and dry weight of roots and shoot, root/shoot length ratio and chlorophyll content were recorded. The studied parameters were significantly altered by individual and interactive effects of genotypes and PEG-induced osmotic potentials. Seed germination and growth parameters were reduced by osmotic potentials; however, huge differences were noted among genotypes. A reduction of 32.83 to 53.50% was recorded in seed germination, 24.611 to 47.75% in root length, 37.83 to 53.72% in shoot length, and 53.35 to 65.16% in root fresh weight. The genotypes, 'J4', 'KLR-16' and 'KTDH-16', particularly 'J4' better tolerated increasing osmotic potentials compared to the rest of the genotypes included in the study. Principal component analysis segregated these genotypes from the rest of the genotypes included in the study indicated that these can be used in the future studies to improve the drought tolerance of wheat crop. The genotype 'J4' can be used as a breeding material to develop drought resistant wheat genotypes.
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