Cancer remains a second leading cause of deaths and major public health problem. It occurs due to extensive DNA damage caused by ultraviolet radiations, ionizing radiations, environmental agents, ...therapeutic agents, etc. Among all cancers, the most frequently diagnosed cancers are lung (12.7%), breast (10.9%), colorectal (9.7%), and gastric cancer (7.81%). Natural compounds are most favorable against cancer on the count of their anti-cancerous ability, easy to avail and efficient. Among natural compounds, polyphenols (flavonoids, catechin, hesperetin, flavones, quercetin, phenolic acids, ellagic acid, lignans, stilbenes, etc.) represent a large and diverse group used in the prevention and treatment of cancer. Natural flavonoids are derived from different plant sources and from various medicinal plants including Petroselinum crispum, Apium graveolens, Flemingia vestita, Phyllanthus emblica, etc. Natural flavonoids possess antioxidant, anti-inflammation, as well as anti-cancerous activities through multiple pathways, they induce apoptosis in breast, colorectal, and prostate cancers, lower the nucleoside diphosphate kinase-B activity in lung, bladder and colon cancers, inhibit cell-proliferation and cell cycle arrest by suppressing the NF-kB pathway in various cancers, etc. The current review summarized the anticancer activities of natural polyphenols and their mechanisms of action.
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DOBA, IJS, IZUM, KILJ, NUK, OILJ, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK, VSZLJ
Heavy metal exist naturally in environment, but due to human and some natural activities they have been entered to water bodies, air and soil and have become one of the major global issue. They are ...equally toxic to both plants and animals as most of them have no role inside the bodies of plants and humans. After entry to the body most of them accumulate there for longer period of time producing various complications like in plants it can damage organs like root, leaves, and components of cells or even interfere with important biochemical process such as photosynthesis, absorption of minerals. Similarly in animals they can damage body basic organs like kidney, liver also cause serious diseases like cancer. The disorders produced by these heavy metals largely depend upon their dose, time of exposure and level of concentration. Heavy metals toxicity has become a serious problem due to their hazardous nature, bioaccumulation and non-biodegradable nature. Living things have been exposed to these heavy metals by various sources but water particularly drinking water is a prominent source. Extensive work has been carried out to remove these metals from water. But the conventional methods have various drawbacks like, not economical, have some impact on environment. Magnetic iron oxide nanoparticles have emerged an ultimate choice of water cleaning adsorbent. It has lot of qualities like, ecofriendly, cost effective, easy use, regeneration and surface modification.
•Toxicity of heavy metals in plants and animals•Toxicity of heavy metals in humans•Synthesis and applications of iron oxide NPs•Removal of heavy metals by magnetic iron oxide NPs
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
It is well trusted that the physical believe subject to non-Newtonian fluid models in a magnetized frame always yield the complex mathematical equations and an exact solution in this direction seems ...impossible. Therefore, it remains challenging task for the researchers to report acceptable solutions. The current pagination contains a systemic remedy in this direction. To be more specific, the Carreau fluid flow towards flat surface is considered along with an externally applied magnetic field. The flow regime is manifested with pertinent physical believes namely, the heat source/sink and chemical reaction. The flow field is additionally supported with both the velocity and thermal slip effects. The Lie group of transformations is proposed for the present problem by means of group theoretic approach. The symmetry generator is constructed against developed Lie group of transformations. The characteristic equation subject to symmetry generator gives suitable set of variables. Such set of variables are used to step down the flow narrating differential equations in terms of an independent variables. Further, the reduced system is solved by numerical algorithm and the observations are offered by way of graphs. It is observed that the Carreau fluid velocity is suppressed for the case of magnetized flow field as compared to non-magnetized Carreau flow field. Further, the temperature of flow regime is higher in strength when the heat source is present. Finally, the results are validated by constructing comparison with an existing work.
•Two layer liquids subject to Carreau model are considered.•Mathematical model is proposed for two layer flow fields.•Order reduction application of Lie symmetry is debated.•Compatibility of problem is justified by graphical and tabular trends.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
In recent years, metal and metal oxide modified mesoporous materials have attracted great attention in science and technology due to their remarkable properties, such as mesoscopic bulky shape, large ...surface area, and interconnected porous structures enabling them to be one of the most exciting materials for biomedical and photocatalytic applications. In this paper, we used a hydrothermal technique to investigate new multifunctional nanostructural material i.e. CuO-MCM-41. The obtained nanocomposites were characterized using XRD, FTIR, UV, SEM, HRTEM, EDX and BET analyses. The as synthesized nanomaterials were screened for the photocatalytic degradation of methylene blue (MB) under visible light irradiation. In the presence of CuO-MCM-41 photocatalyst, 97% MB was degraded only in 30 min of irradiation. The CuO-MCM-41 is an efficient antibacterial agent with effective light inhibition activity against E. coli, S. aureus, S. typhimurium, K. pneumoniae, and B. subtilis. The production of reactive oxygen species (ROS) was also analysed. Furthermore, the nanomaterial is also an efficient DPPH stabilizing agent. The hydrothermally prepared CuO-MCM-41 nanocomposite may be a promising material for removing hazardous organic compounds and microorganisms.
Hydrothermal synthesis of CuO/MCM-41 nanocomposite. Display omitted
•Synthesis of new active CuO/MCM-41 nanocomposite.•Novel chemical hydrothermal protocol was applied.•CuO/MCM-41 nanocomposite was applied for the photodegradation of methylene blue dye.•Detail mechanism was studied.•CuO/MCM-41nanocomposite has significant antibacterial activity and DPPH scavenging activity.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Microcalcification clusters in mammograms are one of the major signs of breast cancer. However, the detection of microcalcifications from mammograms is a challenging task for radiologists due to ...their tiny size and scattered location inside a denser breast composition. Automatic CAD systems need to predict breast cancer at the early stages to support clinical work. The intercluster gap, noise between individual MCs, and individual object’s location can affect the classification performance, which may reduce the true-positive rate. In this study, we propose a computer-vision-based FC-DSCNN CAD system for the detection of microcalcification clusters from mammograms and classification into malignant and benign classes. The computer vision method automatically controls the noise and background color contrast and directly detects the MC object from mammograms, which increases the classification performance of the neural network. The breast cancer classification framework has four steps: image preprocessing and augmentation, RGB to grayscale channel transformation, microcalcification region segmentation, and MC ROI classification using FC-DSCNN to predict malignant and benign cases. The proposed method was evaluated on 3568 DDSM and 2885 PINUM mammogram images with automatic feature extraction, obtaining a score of 0.97 with a 2.35 and 0.99 true-positive ratio with 2.45 false positives per image, respectively. Experimental results demonstrated that the performance of the proposed method remains higher than the traditional and previous approaches.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Hybrid nanofluids are introduced as heat transfer fluids with greater surface stability, diffusion and dispersion capabilities compared to traditional nanofluids. In this work, flow, convective heat ...transport and volumetric entropy generation in Powell–Eyring hybrid nanofluid are investigated. Hybrid nanofluid occupies the space over the uniform horizontal porous stretching surface with velocity slip at the interface. Effect of viscous dissipation and linear thermal radiation are also included in the simplified model. Mathematical equations for conservation of mass, momentum, energy and entropy are simplified under assumptions of boundary layer flow of Powell–Eyring hybrid nanofluid. Similarity solutions are obtained by transformation of governing partial differential equations to ordinary differential equations, using similarity variables. Keller box finite difference scheme is then adopted to find the approximate solutions of reduced ordinary differential equations. Numerical computations are performed for alumina–copper water (
Al
2
O
3
–
Cu
/
H
2
O
) hybrid nanofluid and conventional copper water (
Cu
–
H
2
O
) nanofluid. Graphs are produced for velocity, temperature and entropy profiles to study the effect of governing parameters. Skin friction factor and the local Nusselt number are also calculated at the boundary. The notable findings indicate that the hybrid Powell–Eyring nanofluid is better thermal conductor when compared with the conventional nanofluid. The rate of heat transfer at the boundary is greatest for smallest value of the shape factor parameter. The increase in Reynolds number and Brinkman number increases the overall entropy of the system.
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DOBA, EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, IZUM, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UILJ, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
•Magnetized ferric oxide–water nanofluid in a fillet cavity is formulated mathematically.•Magnetized ferrofluid around rotating heated cylinder is carried with Entropy generation.•Flow field in ...inspected by using Galerkin Finite Element Method.•A grid independence and code validation are also reported.
The present work contains numerical analysis on the magnetized ferric oxide–water nanofluid in a fillet square cavity. The magnetized ferrofluid flow around a rotating heated cylinder is manifested with entropy generation. The governing equations in conjunction with various non-dimensional physical parameters are simulated via Galerkin’s Finite Element Method (GFEM). The discrete system of non-linear algebraic equations is treated by adopting the Newton method coupled with a direct solver PARDISO. A space involving the quadratic polynomials (P2) has been selected to compute the approximations for the velocity profile while the pressure and temperature profiles are approximated by linear (P1) finite element space of functions. The effects of the pertinent parameters have been examined for Hartmann number 0≤Ha≤100, angular velocity 0≤ω≤4 and volume fraction 0≤ϕ≤0.06. A grid independence and code validation studies are also performed. Computational outcomes are represented through streamlines, isotherms and line graphs of other quantities of interest. It is deducted that the fluid move over the cylinder as the cylinder rotates clockwise. Furthermore, increasing the volume fraction of ferro-particles and their angular velocity raises the Nuavg and lowers both viscous and thermal entropy.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Patients with breast cancer are prone to serious health-related complications with higher mortality. The primary reason might be a misinterpretation of radiologists in recognizing suspicious lesions ...due to technical issues in imaging qualities and heterogeneous breast densities which increases the false-(positive and negative) ratio. Early intervention is significant in establishing an up-to-date prognosis process which can successfully mitigate complications of disease with higher recovery. The manual screening of breast abnormalities through traditional machine learning schemes misinterpret the inconsistent feature-extraction process which poses a problem, i.e., patients being called-back for biopsies to eliminates the suspicions. However, several deep learning-based methods have been developed for reliable breast cancer prognosis and classification but very few of them provided a comprehensive overview of lesions segmentation. This research focusses on providing benefits and risks of breast multi-imaging modalities, segmentation schemes, feature extraction, classification of breast abnormalities through state-of-the-art deep learning approaches. This research also explores various well-known databases using "Breast Cancer" keyword to present a comprehensive survey on existing diagnostic schemes to open-up new research challenges for radiologists and researchers to intervene as early as possible to develop an efficient and reliable breast cancer prognosis system using prominent deep learning schemes.
•Vegetables irrigated with waste water were found more enriched with heavy metals than vegetables irrigated with ground water.•Green vegetables were found more prone to heavy metals DIM and HRI were ...higher for crops treated with waste water.•Heavy metals higher in wastewater resulted in higher concentration in crops irrigated with wastewater.
The use of wastewater for irrigation is a common practice in the developing world. It is a major route of heavy metal contamination in vegetables. The groundwater, an alternative source for irrigation, is under threat of heavy metal contamination due to long-term use of wastewater. The present study investigated heavy metals contamination from irrigation with wastewater compared to groundwater in District Sahiwal situated in the vicinity of Lahore, Pakistan. Irrigated water, soil and vegetables were analyzed for Iron, Nickel, Lead, copper, Cadmium, Manganese and Zinc; Metal transfer factor (MTF); daily intake of metals (DIM) and health risk index (HRI) were calculated. Manganese (Mn) and Cd in wastewater irrigated soil, Pb, Cd, Mn and Fe in wastewater-irrigated vegetables and Pb, Mn and Fe in groundwater-irrigated vegetables exceeded the permissible limits (WHO, 1996), particularly in Mustard and Spinach. Generally, MTF was higher in wastewater than groundwater-irrigated vegetables, particularly with Fe followed by Ni. HRI was higher for wastewater-irrigated than groundwater-irrigated vegetables. Wastewater-irrigated Mustard and Spinach showed a HRI > 1 only for Mn. Quality control mechanisms need to be applied for long-term use of groundwater. Also, treatment of wastewater prior to application to plants must be considered to save crops from contamination.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Objective characterization of affective states during music clip watching could lead to disruptive new technologies, such as affective brain–computer interfaces, neuromarketing tools, and affective ...video tagging systems, to name a few. To date, the majority of existing systems have been developed based on analyzing electroencephalography (EEG) patterns in specific brain regions. With music videos, however, a complex interplay of information transfer exists between various brain regions. In this paper, we propose the use of EEG graph-theoretic analysis to characterize three emotional ratings: valence, arousal, and dominance, as well as the “liking” subjective rating. For characterization, graph-theoretic features were used to classify emotional states through support vector machine (SVM) and relevance vector machine (RVM) classifiers. Moreover, fusion schemes at feature and decision levels were also used to improve classification performance. In general, our study shows that the EEG graph-theoretic features are better suited for emotion classification than traditionally used EEG features such as, spectral power features (SPF) and asymmetry index (AI) features. The percentage increase in classification performance, represented by F1-scores, obtained using the proposed methodologies relative to the traditionally used SPF and AI features ranged from: Valence (7–9%), Arousal (3–8%), Dominance (5–6%) and Liking (4–7%). These findings suggest that an EEG graph-theoretical approach along with a robust classifier can better characterize human affective states evoked during music clip watching.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
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