Search

The application of graph theory in the study of molecular physical and chemical properties involves theoretical mathematical chemistry. Atoms, represented by vertices, and edges, represented by bonds between them, are detailed in simple graphs called chemical graphs. The mathematical derivation of the numerical value of a graph is called the molecular descriptor of the graph. Any connected graph wherein no edge is contained in exclusive of a single cycle is called a cactus graph. In the research in this article, expressions for various molecular descriptors of line graph of the graph obtained by the rooted product of the cycle and path graphs are constructed. This article obtained the calculation of molecular descriptors for line graphs of chain ortho cactus and chain para cactus graphs. To predict the biological activity of a compound, the generalized Zagreb index, the first Zagreb index M 1 G , the second Zagreb index M 2 G , the F-index, the general Randic index, the symmetric division, the atom bond connectivity (ABC), and the geometric arithmetic (GA) descriptors are created. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the behavior of anisotropic compact stars in generalized modified gravity, namely f (R , ϕ , X) gravity, where R represents the Ricci scalar, ϕ is the scalar potential function and X is a kinetic term of ϕ. We consider the spherically symmetric spacetime to analyze the feasible exposure of compact stars. We observe the behavior of anisotropic compact stars which includes Her X1, SAX J 1808.4-3658 and 4U 1820-30. From the graphical evaluation of energy density, tangential pressure, radial pressure, equilibrium conditions, energy conditions, mass–radius relationship, compactness and stability analysis of compact stars, it is concluded that the behavior of candidates of compact stars is regular in f (R , ϕ , X) gravity for the considered parameter. [ABSTRACT FROM AUTHOR]

• Substrates inoculated with bacterial and fungal strains had highest germination percentage and earliest mean germination. • Trichoderma spp. (108 CFU mL−1) inoculated substrate produced uniform healthy marigold seedlings. • Enterobacter MN-17 (107 CFU mL−1) inoculated substrate resulted in uniform seed germination of zinnia. • Physico-chemical attributes of PGPR inoculated substrates were within recommended levels. Nursery raising of ornamental flowering annuals using soilless substrates is becoming a lucrative industry worldwide. Pakistan, being an agricultural country, still doesn't have its own cheaper and sustainable soilless substrates for high quality nursery production. Therefore, a study was conducted at University of Agriculture, Faisalabad, Pakistan and Purdue University, West Lafayette, IN, USA, for development and evaluation of a cheaper, sustainable, and easily available soilless substrate using agricultural by-products along with its value addition by inoculating it with plant growth promoting rhizobacteria. For this purpose, coco-coir, rice hulls ash and composted sugarcane pressmud were combined in ratio of 1:1:1; v/v/v and were inoculated with Bacillus (MN-54), Enterobacter (MN-17) and Trichoderma species in 108 CFU mL−1 and 107 CFU mL−1 solutions. These inoculated treatments along with uninoculated treatment, a negative control (sand: silt; 1:1, v/v) were evaluated for their physico-chemical and nursery raising aspects for 'Inca' marigold and 'Giant Dahlia Flowered' zinnia. The study revealed that Enterobacter MN-17 (107 CFU mL−1) inoculated substrate had highest water holding capacity (72.9 %), total porosity (81.04 %) and organic matter contents (92.9 %). Whereas, Trichoderma spp. (108 CFU mL−1) inoculated substrate had better electrical conductivity (1.59 dS m−1) and pH (5.64) and resulted in highest final germination percentage (93.6 %), with greatest seedling vigor index (2195), seedling shoot length (10.2 cm), root length (12.5 cm) and leaf total chlorophyll contents (57.4 SPAD) in marigold. However, in zinnia, Enterobacter MN-17 (107 CFU mL−1) inoculated substrate resulted in highest germination percentage (98.3 %), greatest seedling vigor index (3302), seedling root length (15.8 cm) and leaf total chlorophyll contents (55.8 SPAD), whereas same strain with 108 CFU mL−1 took shortest time for mean germination (3.8 days). In conclusion, substrate enriched with Enterobacter MN-17 (107 CFU mL−1) or Trichoderma spp. (108 CFU mL−1) may be used to produce high quality ornamental flowering annuals nursery. [ABSTRACT FROM AUTHOR]

In this research paper, an innovative bio-inspired algorithm based on evolutionary cubic splines method (CSM) has been utilized to estimate the numerical results of nonlinear ordinary differential equation Painlevé-I. The computational mechanism is used to support the proposed technique CSM and optimize the obtained results with global search technique genetic algorithms (GAs) hybridized with sequential quadratic programming (SQP) for quick refinement. Painlevé-I is solved by the proposed technique CSM-GASQP. In this process, variation of splines is implemented for various scenarios. The CSM-GASQP produces an interpolated function that is continuous upto its second derivative. Also, splines proved to be stable than a single polynomial fitted to all points, and reduce wiggles between the tabulated points. This method provides a reliable and excellent procedure for adaptation of unknown coefficients of splines by searching globally exploiting the performance of GA-SQP algorithms. The convergence, exactness and accuracy of the proposed scheme are examined through the statistical analysis for the several independent runs. [ABSTRACT FROM AUTHOR]

In view of the successful applications of graph theory, relationships between the biological activity and chemical structure have been developed. One of the popular topics in graph theory is problems relating to topological indices. Degree-based topological indices, distance-based topological indices, and counting-related topological indices are various types of topological indices. Physiochemical properties such as boiling point and stability of chemical compounds are correlated by these topological indices. A topological index of a graph is a numerical quantity obtained from the graph mathematically. A cactus graph is a connected graph in which no edge lies in more than one cycle. In this study, we have derived certain degree-based topological indices for some families of graphs consisting of graph obtained by the rooted product of paths and cycles and two types of cactus graph (paracactus and orthocactus) with the help of the generalized Zagreb index. [ABSTRACT FROM AUTHOR]

In the recent advancement in growing nano-technology, the dynamic scientists have shown their interest toward the thermal aspects of nanoparticles due to their prestigious industrial, engineering, medical and modern sciences applications. The current exertion discloses unsteady three-dimensional chemically reactive couple stress nanofluid flow induced by bidirectional oscillatory stretching surface. The heat transfer analysis is explored by utilizing heat generation/absorption and thermal radiation features. Additionally, the mixed convection and magnetic effects are also encountered as novelty. The flow has been generated by bidirectional periodically accelerated surface. Apposite transformations are engaged to reduce formulated nonlinear problem into dimensionless form, and then analytic series solution is computed via homotopic technique. The physical aspect of involved flow parameters is graphically entertained. A complete graphical investigation for profiles of dimensionless velocities, temperature, concentration and skin friction coefficients is deliberated for various prominent flow parameters. Furthermore, the numerical calculations for local Nusselt and Sherwood numbers are presented and discussed. The results perceived that amplitude of oscillation increases in both components of velocities and skin friction coefficients for higher couple stress parameter. It is further reported that temperature distribution enhanced for higher values of Brownian motion parameter, thermophoresis constant and radiation parameter. Moreover, the concentration distribution decreases for enhancement of Brownian motion parameter and chemical reaction parameter. [ABSTRACT FROM AUTHOR]

A novel design of stochastic numerical computing method is introduced for computational fluid dynamics problem governed with nonlinear thin film flow (TFF) system by exploiting the competency of polynomial splines for discretization and optimization with evolutionary computing aided with brilliance of local search. The TFF model of second grade fluid is represented with nonlinear second-order differential system. The aim of the present work is to exploit the cubic spline approach (CSA) to transform the differential equations for TFF model into an equivalent set of nonlinear equations. The approximation in mean squared error sense is introduced for the formulation of cost function for solving the nonlinear system of equations representing TFF model. The optimization of the decision variables of the cost function is carried out with global search efficacy of evolution by genetic algorithms (GAs) integrated with sequential quadratic programming (SQP) for speedy adjustments. The designed spline–evolutionary computing paradigm, CSA–GA–SQP, is evaluated for different scenarios of TFF model by variation of second grade and magnetic parameters, as well as variation in the length of splines. Results endorsed the worth of CSA–GA–SQP solver as an efficient alternative, reliable, stable, and accurate framework for the variants of nonlinear TFF systems on the basis of multiple autonomous executions. The design computing spline paradigm CSA–GA–SQP is a promising alternative numerical solver to be implemented for the solution of stiff nonlinear systems representing the complex scenarios of computational fluid dynamics problems. [ABSTRACT FROM AUTHOR]

The aim of study is to investigate the mass and heat transfer phenomena in hybrid hydro-nanofluidic system involving Al 2 O 3 –Cu–H 2 O over the rotating disk in porous medium with viscous dissolution and Joule heating through the stochastic solver by way of Levenberg-Marquardt backpropagation neural networks. The mathematical model in system of PDEs describes the physical phenomena of the hybrid hydro-nanofluid flow problem are converted into set of ODEs by means of scaling group transformations. The datasets are constructed by utilizing the power of explicit Runge-Kutta numerical method that help to the develop a continuous neural networks mapping. The validation, training and testing processes are utilized to learn the neural network mapping to estimate the solution of various scenarios with cases that are constructed by varying different values of physical constraints such as porosity factor, inertia coefficient, Prandtl number, Brinkman number, radiation parameter, mgnetic parameter, concentration of nanoparticles on the velocities and temperature profiles. Determination, convergence, verification and stability of Levenberg-Marquardt backpropogation neural network mappings are validated on the assessment of achieved accuracy through regression based statistical analysis, mean squared error and error histograms for hybrid hydro-nanofluidic model. • Neuro-intelligent mappings computing for viscous dissolution and Joule heating. • A computing backpropagation networks was found working for hydro-nanofluidic system. • Designed technique is implemented to measure the dynamics of different scenarios. • Study the dynamics of velocities and temperature profiles. • Determination and stability of scheme are validated on rigorous analysis. [ABSTRACT FROM AUTHOR]

The contribution of amino acids (AAs) to soil nitrogen (N) fluxes is higher than previously thought. The fact that AA uptake is pivotal for N nutrition in boreal ecosystems highlights plant AA transporters as key components of the N cycle. At the same time, very little is known about AA transport and respective transporters in trees. Tree genomes may contain 13 or more genes encoding the lysine histidine transporter (LHT) family proteins, and this complicates the study of their significance for tree N-use efficiency. With the strategy of obtaining a tool to study N-use efficiency, our aim was to identify and characterize a relevant AA transporter in hybrid aspen (Populus tremula L. x tremuloides Michx.). We identified PtrLHT1.2, the closest homolog of Arabidopsis thaliana (L.) Heynh AtLHT1, which is expressed in leaves, stems and roots. Complementation of a yeast AA uptake mutant verified the function of PtrLHT1.2 as an AA transporter. Furthermore, PtrLHT1.2 was able to fully complement the phenotypes of the Arabidopsis AA uptake mutant lht1 aap5 , including early leaf senescence-like phenotype, reduced growth, decreased plant N levels and reduced root AA uptake. Amino acid uptake studies finally showed that PtrLHT1.2 is a high affinity transporter for neutral and acidic AAs. Thus, we identified a functional AtLHT1 homolog in hybrid aspen, which harbors the potential to enhance overall plant N levels and hence increase biomass production. This finding provides a valuable tool for N nutrition studies in trees and opens new avenues to optimizing tree N-use efficiency. [ABSTRACT FROM AUTHOR]

The growing interest in emerging nanotechnologies has led the scientists towards to investigate the interaction of nanoparticles with fluids. Current continuation endeavors the rheological analysis for the Oldroyd-B nanomaterial across periodically accelerated and heated surface. The interesting features of thermophoresis and Brownian motions are presented by following famous Buongiorno nanofluid model. Further, Cattaneo–Christov heat and mass flux expressions are exploited to determine the characteristics of thermal and mass diffusions. As a novelty, the variable thermal conductivity and heat absorption/generation consequences are also utilizing the energy equation. The flow model has been developed by using concerning boundary layer equations which are converted into dimensionless forms by using appropriate variables. The analytical solution of such transmuted equations is computed by using homotopy analytic method. Various physical parameters of interest are scrutinized through various graphs. The observations from analysis convey a declining change in nanofluid concentration and temperature with variation of thermal and solutal relaxation parameters, respectively. Moreover, thermophoresis parameter causes an enhancement of concentration profile while a retarded concentration profile results with increment of Schmidt number. The obtained theoretical results reflect significant applications in cooling and heating systems, thermal sciences, manufacturing processes, extrusion systems, enhancement of transport of energy and heat resources. [ABSTRACT FROM AUTHOR]

Motivated by the significant role of nanofluid in pollution cleaning and energy recovery, we decided to explore the unsteady three-dimensional rotating flow of nanofluid driven by the movement of a flat surface with the potencies of prescribed heat distributions. The modeling of the physical model is completed with the help of Buongiorno nanofluid model. Suitable arrangement of similarity variables is implemented to transform the model equations into strongly nonlinear ordinary differential equations. Numerical inspection of the model is made by employing Keller–Box algorithm. Influences of involved parameters on the distributions of heat and mass are discussed graphically, while the potencies of influential parameters on reduced Nusselt and reduced Sherwood numbers are physically discussed through tabular arrangements. It is deduced that increasing the values of Prandtl factor and heat controlling indices diminishes the temperature and concentration distributions, whereas intensification in the amount of rotation factor enhances the temperature as well as concentration distribution. Moreover, negative trends in the amounts of reduced Nusselt and Sherwood numbers are achieved with the escalations in the values of rotation and thermophoresis factors, whereas opposite trend is achieved with the intensification in the choice of Prandtl factor. [ABSTRACT FROM AUTHOR]

developments in nanotechnology have attracted the attention of scientists towards the interaction of nanoparticles due to their fascinating applications in thermal engineering and solar energy systems. Convinced by such motivating applications, the current research project addresses the utilization of nanoparticles in the unsteady three‐dimensional chemically reactive flow of an Oldroyd‐B fluid induced by a bidirectional oscillatory stretching surface. The effects of mixed convection are also considered here. The prime features of the nanofluid namely thermophoresis and Brownian motion characteristics are explored by introducing the famous Buongiorno's nanofluid model. The relevant equations for the formulated theoretical model have been reduced by the appropriate transformations for which the analytic solution is deliberated via the homotopic technique. Later on, a complete graphical analysis for distinct flow parameters is deliberated for dimensionless velocities, concentration, and temperature distributions with the relevant physical implications. Moreover, stimulating physical quantities like local Nusselt and Sherwood numbers are numerically calculated and discussed. The study emphasizes that decreasing variation in both components of velocities has been reported with an increment of relaxation time, while the impact of the retardation time constant is quite opposite. It is further claimed that the velocity distribution has an increasing tendency in the horizontal direction for a higher buoyancy ratio and mixed convection parameters. Moreover, an increment in thermophoresis parameter enhances both temperature and concentration distributions. [ABSTRACT FROM AUTHOR]

In this study, unsteady bidirectional stretched flow and heat transport of a Cu–water nanomaterial in the presence of a magnetic environment embedded in a porous medium occupying boundary‐layer region is investigated. Moreover, heat transport investigation is conceded out by simultaneous heat sources, namely, prescribed surface temperature and prescribed heat flux. The considered problem is converted into a set of four coupled differential equations with the help of a suitable combination of variables. The Keller–Box method is then implemented to get the numerical solution for velocity components and temperature distributions. Nanomaterial volume fraction ψ impact on the velocity components and temperature distributions are studied. Through reduced skin friction coefficients and Nusselt numbers, it is detected that the heat transport capacity of nanomaterial is better than that of the base fluid. An exponentially decaying behavior of velocity components and temperature distributions is observed at far‐field for various amounts of involved flow parameters. [ABSTRACT FROM AUTHOR]

This study aims to investigate an Nflationary phase diagram with a multifield polynomial potential. The gradual vanishing of the inflationary phase during slow roll phase of the Nflation model has been demonstrated for a large number of fields in the case when there are voluminous N phase transitions occurring in it. A phase diagram for Nflation model illustrates its phase transitions for a multifield potential Λ j 4 ϕ j μ j p . We use Marčenko–Pastur law to find likely distribution of different mass-scales of the fields. Further, the study for the conditions of entropy is carried out in the form of a bound that conforms to the number of e-folds 𝒩 and the number of fields N. These drive Nflationary phase and are mostly responsible for the phenomena taking place in it. We investigate in addition, that all the de Sitter entropy in the neighborhood of the critical point is concentrated around it and is largely condensed in the number of fields N for the selected potential. [ABSTRACT FROM AUTHOR]

In this study, bio-inspired computational techniques have been exploited to get the numerical solution of a nonlinear two-point boundary value problem arising in the modelling of the corneal shape. The computational process of modelling and optimization makes enormously straightforward to obtain accurate approximate solutions of the corneal shape models through artificial neural networks, pattern search (PS), genetic algorithms (GAs), simulated annealing (SA), active-set technique (AST), interior-point technique, sequential quadratic programming and their hybrid forms based on GA–AST, PS–AST and SA–AST. Numerical results show that the designed solvers provide a reasonable precision and efficiency with minimal computational cost. The efficacy of the proposed computing strategies is also investigated through a descriptive statistical analysis by means of histogram illustrations, probability plots and one-way analysis of variance. [ABSTRACT FROM AUTHOR]

In this paper, the structural, elastic, and electronic properties of RIn3 and RSn3 (R = Sm, Eu, Gd) compounds have been investigated using the full potential linearized augmented plane wave plus local orbital method within the density functional theory. The structural properties are investigated using the LDA, GGA, and the band correlated LDA+U and GGA+U schemes. The lattice parameters are in good agreement with the available experimental results and the divalent state of Eu is also verified. The spin-orbit coupling is included in order to predict the correct electronic properties and splitting of 4f states of the rare earth elements is also incorporated. We calculated Bulk modulus, shear modulus, Young's modulus, anisotropic ratio, Kleinman parameters, Poisson's ratio, Lame's co-efficient, sound velocities for shear and longitudinal waves, and Debye temperature. We also predict the Cauchy pressure and B/G ratio in order to explore the ductile and brittle behaviors of these compounds. [ABSTRACT FROM AUTHOR]

The porous media transport theories are thoroughly operative to analyse transferral phenomenon in reducing the bio-convective flow instabilities and biological tissues. The present study is designed to investigate the heat transfer phenomena in nanofluidic system involving Cu − H 2 O over the stretched porous media with the strength of stochastic solver via Levenberg-Marquardt backpropagation networks. The mathematical model of physical phenomena is described in PDEs that are reduced to system of ODEs through scaling group transformations. The datasets are determined through explicit Runge-Kutta numerical method and used as a target parameter for the development of continuous neural networks mapping. The training, testing and validation processes are utilized in learning of neural network models based on backpropagation of Levenberg-Marquardt technique to determines the solution of different scenarios constructed on the various values of porosity parameter along with six different cases based on the stretching ratio values. Validation and verification of neural network model to find the solution of nanfluidic problem is endorsed on the assessment of achieved accuracy through mean squared error, error histograms and regression studies. [ABSTRACT FROM AUTHOR]

The main focus of this research is to explore the consequences of motile gyrotactic microorganisms for unsteady Williamson nanofluid induced by bidirectional periodically accelerated surface. The combined features of magnetic and buoyancy forces with association of nanoparticles and swimming microorganisms developed the nanofluid bioconvection. Thermal radiation and heat generation aspects are considered to analyze the heat transportation phenomenon. The consequences of activation energy and chemical reaction are further explored for physical relevance. Appropriate transformations have been employed to transmute the formulated nonlinear equations into dimensionless form, and then analytically elucidated by homotopic technique. The effect of diverse dominant parameters on velocities, concentration, temperature, motile microorganisms as well as skin friction coefficients are deliberated through various graphs while the deviation in local Sherwood, Nusselt and motile density numbers have been deliberated by numerical data in tabular form. It is noticed that both velocity components periodically drop for augmentation in Williamson parameter. Current investigation accentuated that higher reaction rate leads to decay in concentration distribution, but impact of activation energy parameter is rather conflicting. Furthermore, the profile of motile microorganism leads to be intensified for higher magnetic parameter, while opposite trend is perceived for bioconvected Peclet and Lewis numbers. [ABSTRACT FROM AUTHOR]

We investigated changes in plant morphology, anatomy and physiology in a commonly occurring weed, Euphorbia helioscopia L. due to exposure to post‐emergence herbicides. Weed plants were sprayed with one of the following herbicides: pyrimidinyl sulphonylharnstoffe (PS), tribenuron‐methyl (TM), fluroxypyr‐methyl tribenuron‐methyl (FMTM) and bromoxynil (Br). The PS treatment significantly decreased plant height, promoted initiation of side branches and induced a prostrate habit. A specific response of root anatomy to PS and Br treatments was the high proportion of storage parenchyma. The Br‐treated plants showed thickest roots with a significantly large storage parenchyma, not only in the central portion of roots, but also in the cortical parenchyma outside the vascular tissue. A high proportion of xylem in the central portion of roots in the TM or FMTM‐treated plants provides a strong survival response in E. helioscopia. Disintegration of stem cortical parenchyma is the most prominent response of E. helioscopia when treated with a herbicide like PS or FMTM. Survival against these herbicides relates to a complete ring of vascular bundles and intact cortical parenchyma outside the vascular tissue. Increased leaf thickness was recorded in most of the cases except in the FMTM‐treated plants. The PS‐treated plants showed midrib thickness with two distinct vascular bundles. The cortical region, however, was found to be damaged by tissue collapse forming a large lysigenous aerenchyma. Euphorbia helioscopia had altered morphology, anatomy and physiology in response to herbicide application, which changed its growth in the field. To achieve control of this weed species, alternative strategies or higher doses of herbicide should be applied. Further research is required to determine the interaction of surviving weed plants with the crop. [ABSTRACT FROM AUTHOR]

The countless applications of nanofluids in the improvements of nanotechnology, thermal and physical analogies have attracted our attention to frame an unsteady mathematical model for bi-directional flow of a Newtonian nanofluid over a stretching sheet with the potencies of nonzero and zero mass fluxes. Mathematically, this newly presented analysis is more genuine, where the action of a prescribed heat source at a stretching surface is used to control the distribution of heat. Mathematical formulation is carried out using a novel two-phase nanofluid model. Dimensionless forms of governing equations are obtained with the help of a suitable set of variables. The transformed equations are then solved by using an innovative computational technique, namely, Keller–Box approach. Moreover, the convergence of the numerical solution has been discussed via grid-independence tactic. The results for reduced Nusselt and Sherwood numbers have been arranged in the form of a table with CPU run time. Graphical illustrations have been presented for concentration and temperature distributions. It is inspected that escalating amounts of heat distribution indices reduce the mass concentration and the temperature of the nanomaterial. Rate of heat transference is noticed approximately 228.62% higher, while rate of mass transference is observed approximately 16.79% lower when analysis is shifted to zero mass flux environment from nonzero normal mass flux environment. [ABSTRACT FROM AUTHOR]

The objective of the current investigation is to examine the influence of variable viscosity and transverse magnetic field on mixed convection fluid model through stretching sheet based on copper and silver nanoparticles by exploiting the strength of numerical computing via Lobatto IIIA solver. The nonlinear partial differential equations are changed into ordinary differential equations by means of similarity transformations procedure. A renewed finite difference based Lobatto IIIA method is incorporated to solve the fluidic system numerically. Vogel's model is considered to observe the influence of variable viscosity and applied oblique magnetic field with mixed convection along with temperature dependent viscosity. Graphical and numerical illustrations are presented to visualize the behavior of different sundry parameters of interest on velocity and temperature. Outcomes reflect that volumetric fraction of nanoparticles causes to increase the thermal conductivity of the fluid and the temperature enhances due to blade type copper nanoparticles. The convergence analysis on the accuracy to solve the problem is investigated viably though the residual errors with different tolerances to prove the worth of the solver. The temperature of the fluid accelerates due the blade type nanoparticles of copper and skin friction coefficient is reduced due to enhancement of Grashof Number. [ABSTRACT FROM AUTHOR]

Internet of Vehicles (IoV) is a complex system that consists of resource types such as vehicles, humans, and sensors. Although the Internet of Vehicles is complex, it improvises communication among vehicles on the roads. Quality of service (QoS) enabled the cooperative driving system (CDS) based on 5G technology, enabling vehicles to communicate and cooperate to improve road traffic efficiency. Due to the high vehicle density and limited resources (bandwidth) of current network infrastructure, sometimes a better channel that meets the requirements of cooperative driving is not available that causes network congestion, which directly influences the overall QoS of the CDS. To overcome this, we proposed a 5G network-based architecture for CDS that incorporates a D2D technology-based resource allocation scheme. The proposed network architecture and cooperative behavior-based scheme helps in improving QoS for CDS. We implemented our proposed scheme by incorporating the density-based scattered clustering algorithm with noise for vehicular clustering. The proposed scheme's performance shows significant improvement in terms of throughput compared with existing D2D approaches. [ABSTRACT FROM AUTHOR]

Researchers working in the field of unmanned aerial vehicles are observing rapid developments in the field, such as the use of quadrotors to grasp, manipulate, and transport objects. These advancements are made possible through sophisticated control systems, new types of actuation and sensing technologies, and a greater understanding of the aerodynamic effects and gyroscopic moment generated by the rotating blades of the quadrotor involved. Therefore, this research work proposes four novel optimized control laws, i.e., conditioned adaptive barrier-based double integral super twisting sliding mode controller (CABDIST-SMC), BF double integral SMC (BF-DISMC), BF integral SMC, and barrier function-based SMC control laws, for attitude, heading, position, and altitude trajectory tracking of the quadcopter. The non-linear model of the quadcopter is developed using the Lagrange formalism in MATLAB ODE-45 environment, including the gyroscopic moments and aerodynamic effects, and a Lyapunov stability analysis is performed to ensure the asymptotic stability of the system. A 3D-helical complex trajectory is employed to analyze the performance and consistency of the proposed optimized controllers. For performance comparison, the proposed four variants of the SMC are compared with three traditional control strategies, i.e., backstepping SMC, optimized adaptive SMC via particle swarm optimization algorithm, and improved adaptive SMC. These traditional control strategies have also been developed and tested in MATLAB-Simulink. All the controllers are optimized using the improved grey wolf optimization algorithm, and to determine the best control law, six performance indexes, i.e., mean absolute percentage error (MAPE), root mean square error (RMSE), integral square error (ISE), integral absolute error (IAE), integral time absolute error (ITAE), and integral time square error (ITSE) are used. A hardware-in-loop (HIL) test is also performed to validate the performance of the designed novel control law. The C2000 Delfino MCU F28379D launchpad is used for performing the HIL validation test. The simulated results showed that the performance of optimized CABDIST-SMC surpassed all other control laws for altitude, heading, position, and attitude trajectory tracking. It has achieved MAPE of 0.02%, RMSE of 3.9912e−5, ISE of 3.1859e−8, IAE of 7.9823e−4, ITAE of 0.0080, and ITSE of 3.1849e−7 in case of yaw angle control. The proposed control laws have successfully passed the HIL validation test, and real-time implementation of the proposed control laws indicates no significant variations compared to the simulated results. [ABSTRACT FROM AUTHOR]

This study is based on gray-box modeling for the prediction of optimum mass flow rates of inlet streams of a Plate and Fin Heat Exchanger under uncertainty. A first principle model of the Plate and Fin Heat Exchanger was developed in Aspen Exchanger Design and Rating. Genetic algorithm was integrated with the first principle model to achieve the highest possible exit temperature of the cold process stream under uncertainty. A dataset of uncertain process conditions and their corresponding optimum inlet flow rates derived through the first principle-genetic algorithm integration was used to develop an artificial neural networks model. The artificial neural networks model was then integrated with the first principle model by replacing the genetic algorithm to form a novel gray-box framework. The proposed gray box model, i.e., artificial neural networks and first principle integration, achieved a higher effectiveness and higher outlet temperature than those derived through the straight run first principle model. The performance of the gray box framework was also comparable to the first principle integrated genetic algorithm approach and significantly minimized the computation time needed for estimating the optimum process conditions. First principle integrated genetic algorithm approach enhanced the effectiveness of the straight run model by 3.05%. Performance of the proposed gray-box model was comparable to the integrated framework of the genetic algorithm with the first principle model but was significantly faster. The developed artificial neural networks model was employed as a surrogate in Sobol and FAST sensitivity analysis framework to identify the impact of input variables on output variables. The proposed gray box based method enhanced the capability of the plate and fin heat exchanger to recover energy from the process stream and its robustness to cope with uncertainty. The proposed approach is suitable for real-time application and would contribute to laying a foundation for petroleum refinery 4.0. • A Gray-box (GB) modeling framework was developed for the optimization of process conditions of a plate and fin heat exchanger of a tile industry under uncertainty. • The GB framework was based on the integration of first principle (FP) model and Artificial Neural Networks (ANN) model. • The proposed GB approach attained the optimum conditions in a significantly less period of time than the conventional FP-GA framework. [ABSTRACT FROM AUTHOR]

• Citrus reticulata was under environmental stresses. • Micronutrients and melatonin present in high concentration in ecotypes under stress. • Antioxidants were checked. • Effects of antioxidants were checked on photosynthetic pigments. • Melatonin and other antioxidants were alleviated in stress environment. A major commercial fruit in Pakistan, citrus plays an important role in the economy of the country. The current study examined antioxidant responses in citrus plants exposed to various abiotic stresses like industrial pollution, dust pollution, water logging, drought, and salinity, varying in soil properties and agro-climatic conditions, citrus species and cultivars are most susceptible to abiotic stresses in most citrus-producing countries. The effects of abiotic stresses on citrus plants and fruit physiology were studied in six different sites like Thal desert and pollution stressed areas of Faisalabad. A study of the physiological characteristics of various plants has revealed that citrus plants contain more chlorophyll as the concentration of melatonin increases. Integrative elemental and metabolic techniques have been used to study the potential role of melatonin in citrus defense against abiotic stress and to understand the interactions between melatonin and stress-related phytohormones at the elemental and metabolic levels. Citrus plants sensed abiotic stresses based on morphological observations and physiological analysis. Morphological analysis shows that the abiotic stresses adversely affected the leaves, stems and roots. Physiological analysis shows that antioxidant and micronutrients concentrations (boron (B), zinc (Zn), manganese (Mn), iron (Fe), copper (Cu), molybdenum (Mo), chlorine (Cl)) were also adversely effected in citrus plants. Iron concentration was also found higher in healthy plants with a slight difference. Results show that the activity of antioxidants was increased in stressed plants but the activity of melatonin was slightly changed in healthy plants. [ABSTRACT FROM AUTHOR]

• Riparian vegetation and Phyla nodiflora was under industrial pollution stress. • Macronutrients and melatonin present in high concentration in ecotypes under stress. • Antioxidants were checked. • Effects of antioxidants were checked on photosynthetic pigments. • Melatonin and other antioxidants were alleviated in stress environment. This study explores the macro nutritional contents and endogenous melatonin in the structural differences of riparian flora and horticultural ecotype growing in industrially contaminated environments. Water pollution caused by anthropogenic activities poses uncompromising threats to rivers and water sources, resulting in the extinction of many species and the reduction of others to endangered status. Effluents from the industrial hub of Faisalabad are discharged into the Chenab River in Punjab province. As in other parts of the world, effluents from Faisalabad industries pose a great threat to native vegetation in the area. Therefore, this study was designed to verify the presence of industrial pollution. Moreover, the effects of industrial pollution on native vegetation and the survival strategies of adapted species were also assessed. Results showed that several abiotic stresses have been mitigated by endogenous melatonin in herbs and herb-based products. The survival of herbs depends on specific changes to biochemical compounds like melatonin content and vascular structures. Overall, industrial pollution harmed herbs' metabolism and antioxidant activity, although the reactions of specific species to industrial pollution varied. Changes in the concentration of endogenous melatonin metabolism have been identified as promising indicators for industrial pollution biomonitoring. Internal alterations of plants vegetating at various industrially polluted locations contributed significantly to the high level of tolerance of these plants. The typical reaction of all herbs to increased pollution was growth modification in terms of endogenous melatonin content, moisture content, carbohydrates, crude protein, and dry matter. Most of the proximate, melatonin and chlorophyll content were significantly high in indirectly affected vegetation and high in directly affected industrial pollution. Biochemical investigation specifies that in response to industrial pollution four species Calotropis procera, Eclipta alba, Phyla nodiflora (Ornamental plant) and Ranunculus sceleratus increased the primary metabolites like melatonin, carbohydrates, crude protein, crude fibers, and fats. [ABSTRACT FROM AUTHOR]

The present study aims to provide an innovative stochastic numerical solver's application by the use of neural networks with Levenberg-Marquardt backpropagation to examine the dynamics of hydrogen possessions and variable viscosity in the fluidic system of electrically conducting copper and silver nanoparticles with mixed convection. The system of PDEs obtained by mathematical modeling of the physical phenomena are reduced into non-linear ODEs by utilizing suitable transformations. The ODEs dataset is constructed through Adams numerical solver and target parameters for input and output parameter of neural networks. The testing, validation and training processes are exploited in neural network models with learning based on backpropagation of LM method to calculate the solution for different scenarios created on variation of physical parameters of the proposed flow of Reynolds and Vogel models. Validation and verification of neural network model to find the solution of fluid flow problem is endorsed on the assessment of achieved accuracy through mean squared error, error histograms and regression studies. • Novel application of stochastic computing for fluidic system as hydrogen-possessions. • Fluidic model analyzed by exploitation with Levenberg-Marquardt backpropagation. • Dynamics of both Reynold and Vogel models are presented sundry physical parameters. • Validation are endorsed on MSE through histograms and regression analysis. [ABSTRACT FROM AUTHOR]

The present investigation aims to explore the influence of a mixed convection and nonuniform heat source/sink on unsteady flow of a chemically reactive nanofluid driven by a bidirectionally expandable surface. Convective heat transport phenomenon is used to maintain the temperature of the surface. Moreover, zero mass flux is also accounted at the surface such that the fraction of nanomaterial maintains itself on strong retardation. The governing nonlinear set of partial differential equations is transformed into a set of ordinary differential equations via a suitable combination of variables. The Keller‐Box scheme has been incorporated to make a numerical inspection of the transformed problem. The spectacular impacts of the pertinent constraints on thermal and concentration distributions are elucidated through various plots. Graphical outcomes indicate that the thermal state of nanomaterial and nanoparticles concentration are escalated for elevated amounts of Biot number, porosity parameter and nonuniform heat source/sink constraints. Furthermore, it is also seen that escalating amounts of unsteady parameter, temperature controlling indices, Prandtl number, and expansion ratio parameter reduce the thermal and concentration distributions. Numerical results for the rate of heat transference have been reported in tabular form. The grid independence approach is used to verify the convergence of the numerical solution and the CPU run time is also obtained to check the efficiency of the numerical scheme adopted for finding the solution. [ABSTRACT FROM AUTHOR]

The current exploration reveals the unsteady three‐ dimensional flow of Jeffrey nanofluid over a bidirectional oscillatory stretching surface. The Brownian motion and thermophoresis phenomenon has been scrutinized by utilizing Buongiorno's nanofluid model. The heat transfer analysis is carried out in the presence of thermal radiation and heat generation/ absorption features. Furthermore, chemical reaction and magnetic effects are also deliberated. The flow has been generated by a bidirectional periodically accelerated heated surface. The formulated nonlinear problem is condensed into a dimensionless form via apposite transformations, and then analytic series solution is computed via homotopic technique. Comprehensive graphical evaluations for numerous prominent flow constants on associated profiles are performed. In addition, the tabulated numerical calculations for the local Nusselt and Sherwood numbers are also presented. The current analysis reported that both components of velocities have an increasing tendency for higher Deborah number, whereas an adverse influence is observed for the ratio of relaxation and retardation times parameter. Moreover, the concentration profile diminishes for the increasing variation of the chemical reaction parameter. [ABSTRACT FROM AUTHOR]

Various seed conditioning techniques were assessed for uniform germination, seedling vigor, and flower production in zinnia (Zinnia elegans Jacq.). Two initial laboratory experiments evaluated the timing and frequency of seed magnetic stimulation to select the most promising treatments for field production testing and flowering. In the first experiment, a 3% moringa leaf extract (MLE) showed the earliest (2.8 d) and the highest germination rate (90%) with an average root length of 4.2 cm. Hydro-priming resulted in the largest seedling fresh weight (0.8 g), seedling shoot length (5.8 cm), and seedling vigor index (980). The seedling vigor index was determined by multiplying the percent germination with the seedling length (cm). In the second experiment, seeds treated at 25 mT for 5 min. showed the highest (65%) and earliest (3.2 d) germination (T50) although not significantly different from treatments with 50 mT for 5 or 10 min. or 75 mT for 5 min. In field trials, seeds primed with MLE alone or in combination with magnetically treated water (MTW) produced the tallest plants (104 cm) with longer internodes and the largest canopy diameter (42.4 cm). Using MLE along with MTW produced greater plant fresh weight (137 g), more flowers (27.5), and larger flower diameter (9.7 cm) similar to the results of using MTW alone. In summary, seeds primed with MLE in combination with untreated water or MTW resulted in improved plant growth and yield characteristics and may be recommended to commercial growers of zinnia or other annual flowers. [ABSTRACT FROM AUTHOR]

CPEC is a mega investment project, termed as a key to rapid economic growth of Pakistan. It is an economic corridor providing connectivity to China, building around which Pakistan is believed to harness economic dividends as time passes. The project has great strategic significance and it contains enormous economic prospects, thus is vital for both the countries. Though, CPEC is not completed yet, it has already started contributing to Pakistan's economy as investment in energy projects has increased electricity supplies. CPEC has attracting private sector investment in to Pakistan, which as per official estimates, is expected to boost economic growth rate to 5.5 percent in the near future. While CPEC is a game changer for the development, government needs to pay attention to develop human capital (health, education, trainings and skills) and infrastructure (western route) in order to develop lagging regions and to improve the living standard of people living there. [ABSTRACT FROM AUTHOR]

Surface plasmon-polariton (SPPs) at the interface between a nanocomposite material and a medium, in which triple quantum dots (QDs) are uniformely embedded, are theoretically investigated. The absorption and dispersion spectra of SPPs are shown to have interesting behavior in the proposed system. The plasmonic spectra can be efficiently controlled via gate voltages applied in the triple QD as well as the filling ratio of nanoparticles in the composite. Moreover, the effect of incident frequencies on different features of the propagating plasmons is also manipulated. The propagation length and plasmonic depth are measured with different spectroscopic parameters. This study provides more degrees of freedom for generation and control of SPPs in plasmonic geometries containing QDs or nanocomposites or both. The results may find significant applications in atomic spectroscopy, nano-photonics, photovoltaic devices, biosensors and plasmonster technology. [ABSTRACT FROM AUTHOR]

The vehicular ad-hoc networks integrates with long-term evolution (LTE) forming a heterogeneous network, capable of providing seamless connectivity, which meets the communication requirements of intelligent transportation systems. However, heterogeneous network-based applications involve LTE resource (data and spectrum) usage cost and must be taken care while developing such a solution. One of the scenarios is the access of the information to/from remote server over the internet via LTE for road traffic management applications. Although clustering of the vehicle is significant to minimize the data and LTE network usage, however, the problem of non-cooperation of the vehicles in clustering process and within a cluster are major issues in sharing costly data acquired from the internet. Because, who and why one (vehicle) should pay the cost is the big question, proliferating the non-cooperative behavior among the cluster members. To solve these issues, strategic game-theoretic based clustering mechanism named as cooperative interest-aware clustering (CIAC) is developed. The proposed CIAC not only balance the cost of usage by controlling non-cooperative behavior among the vehicles within the cluster but at the same time motivate vehicles to participate in the clustering process to share the data and cost as well. It consists of a cluster head selection process based on the strategic game-theoretic approach and a fair-use policy. The implementation results show superiority in performance of our protocol over the existing approaches. [ABSTRACT FROM AUTHOR]

Inspired by spectacular applications of nonlinear resources in the field of nanotechnology, we formulate a mathematical relation for unsteady radiative flow of a magneto-Carreau nanoliquid as the consequence of a bidirectionally stretchable surface using the Buongiorno model. Practically, this newly mentioned approach is more genuine where we account for the fact that the surface temperature and surface heat flux are adjusted themselves on the boundaries, accordingly. With the utilization of this approach, industrial and engineering quantities of interest are investigated in a more effective manner. A suitable combination of variables is used to alter the partial differential equations into ordinary differential equations and then computationally solved by employing the Keller box method. The great significance of the involved constraints on the Carreau nanomaterial velocity components, temperature, and concentration fields is depicted graphically and elucidated in detail. The foremost outcomes for drag forces, surface temperature gradient, and concentration gradient for the Carreau nanomaterial are anticipated and arranged through tables. For endorsement of the present solution, the attained outcomes are linked with formerly published work in a particular case and found in marvelous agreement. It is observed that an escalating amount of radiative parameter Rd enhances the temperature of the Carreau nanomaterial. Moreover, the amounts of heat and mass fluxes are significantly improved by increasing the temperature of the surface. [ABSTRACT FROM AUTHOR]

Here, we have endeavored the rheological aspects of Oldroyd-B fluid induced by an accelerated and periodically moving sheet. The heat transfer evolution has been characterized with employment of novel Cattaneo-Christov law. Further features of heat transfer are characterized with heat generation/ absorption and thermal conductivity depending upon the temperature. The governing equations have been constituted properly with utilization of associated laws. After truncating the flow problem in dimensionless form, we follow famous analytic procedure, namely, homotopy analysis technique to simulate the solution. The convergence of the solution is established by sketching the h-curves. While assigning suitable constant values to involved physical parameters like Deborah number, thermal relaxation parameter, Prandtl number, and heat source/sink constants, the change in particles movement and heat transfer rate has been examined. It is observed that the velocity profile decreases with increments in Deborah constant, in terms of relaxation time constant. The presence of variable thermal conductivity and heat source parameters enhance the temperature distribution efficiently. Significance of Results: Recently, non-Newtonian fluids have attracted the interest of scientists due to their significant use in various chemical, mechanical, and processing industries. Some essential applications of such materials arise in polymer processing, food industries, paints, petroleum industries, biomedical engineering, and so forth. Besides this, the heat transportation phenomenon in non-Newtonian fluids flow engaged diverse novel applications in area of engineering processes, and also appeared in chemical, mechanical, and processing industries. The present problem may find engineering applications in paper production, glass blowing, polymer solution, and metal extrusion. The proposed results are useful in extrusion system applications, energy production, and manufacturing processes. [ABSTRACT FROM AUTHOR]

Summary: Energy efficiency is a contemporary and challenging issue in geographically distributed data centers. These data centers consume significantly high energy and cast a negative impact on the energy resources and environment. To minimize the energy cost and the environmental impacts, Internet service providers use different approaches such as geographical load balancing (GLB). GLB refers to the placement of data centers in diverse geolocations to exploit variations in electricity prices with the objective to minimize the total energy cost. GLB helps to minimize the overall energy cost, achieve quality of service, and maximize resource utilization in geo‐distributed data centers by employing optimal workload distribution and resource utilization in the real time. In this paper, we summarize various optimization‐based workload distribution strategies and optimization techniques proposed in recent research works based on commonly used optimization factors such as workload type, load balancer, availability of renewable energy, energy storage, and data center server specification in geographically distributed data centers. The survey presents a systemized and a novel taxonomy of workload distribution in data centers. Moreover, we also debate various challenges and open research issues along with their possible solutions. [ABSTRACT FROM AUTHOR]

Soft sensors have been used for estimation of research octane number (RON) of gasoline and to realize stability in process operation. In this study, a novel framework is proposed by incorporating uncertainty analysis in the conventional soft-sensor design for RON prediction. Ensemble learning method, i.e., boosting, and artificial neural networks (ANN) were used to realize highly efficient soft sensor. The individual impact of uncertainty of each process variable on RON was analyzed using Sobol technique and Fourier Amplitude Sensitivity Test (FAST). The accumulative effect of uncertainties on RON was investigated through nonintrusive polynomial chaos expansion (PCE). For realizing reliability in online application of the predictive distribution of RON, control limits were derived using a Just-in-Time method, i.e., k-d tree. The proposed method was validated through process data where the results were found suitable for industrial applications. [ABSTRACT FROM AUTHOR]

Topological indices(TIs) are important numerical number associate with the molecular graph of a chemical structure/compound because due to these parameters, one can guess almost all properties of concerned structure/compound with our performing experiments. In recent years, huge amount work has been done for calculating degreedependent indices for different structures/compouds. In order to compute TIs, one need to do many calculations. Our aim of this paper is to present a simple method to compute degree-dependent TIs. We computed M-polynomials for Block Shift Networks and with the help of this simple algebraic polynomials, we recovered nine important TIs for Block Shift Networks. Our work is important for chemists, physicians and pharmaceutical industry. [ABSTRACT FROM AUTHOR]

Network theory as an important role in the field of electronic and electrical engineering, for example, in signal processing, networking, communication theory, etc. The branch of mathematics known as Graph theory found remarkable applications in this area of study. A topological index (TI) is a real number attached with graph networks and correlates the chemical networks with many physical and chemical properties and chemical reactivity. The Optical Transpose Interconnection System (OTIS) network has received considerable attention in recent years and has a special place among real world architectures for parallel and distributed systems. In this report, we compute redefined first, second and third Zagreb indices of OTIS swapped and OTIS biswapped networks. We also compute some Zagreb polynomials of understudy Networks. [ABSTRACT FROM AUTHOR]

A study was conducted to develop indigenous soilless substrate compositions for improved growth, flower yield, stem quality and vase life of cut antirrhinum. Two experiments comprised of seven substrate compositions with variable ratios of saw dust (SD), peanut hulls (PH) and sugarcane pressmud (a by-product of sugar industry, which is rich in nutrients) or coco-coir (CC), rice hulls (RH) and sugarcane pressmud (PM) were used. Seeds were sown in plastic plug trays containing CC, silt (soil extracted from canal) and PM (1:1:1; v/v/v) substrate for seedling development and transplanted at the two to four leaf stage into lily crates with the treatment substrates. Plants grown in substrates containing SD + PH + PM (experiment I) indicated that plants grown in these soilless compositions died before flowering, while those grown in silt (control) performed best. While in experiment II, the highest quality plants were grown in 50% CC + 40% RH +10% PM. Quality was defined as plants with shortest production time (days), tallest plant height (cm), optimal leaf chlorophyll content (SPAD), highest leaf area (cm²), fresh and dry weight (g), longest vase life (days). Substrates containing CC, RH and PM (50% + 40% + 10%; v/v/v) were superior to substrates of SD, PH and PM. For commercial cut ant [ABSTRACT FROM AUTHOR]

A survey-based study was conducted to analyze the current scenario of substrate usage in local ornamental plants nurseries of Punjab, Pakistan, during 2017, using stratified random sampling technique. Ornamental nurseries of Faisalabad, Lahore, Islamabad, Kasur and Multan were surveyed on a detailed questionnaire, which consisted of comprehensive personal and business information of nurserymen, substrate usage for ornamental plant production and major issues of nursery production business in Punjab, Pakistan. Collected data were coded, decoded and arranged statistically in tabular form, and were analyzed through SPSS (Statistical Package for Social Science) IBM (International Business Machines) version 19. Results demonstrated that majority of local nurserymen were using soil or silt for raising ornamentals. Moreover, major obstacle in nursery production was the unawareness of the nurserymen regarding modern nursery raising techniques and majority (56%) even had no idea about use or significance of soilless substrates. However, a large number (62%) of nurserymen were interested to produce export quality plants, using cheaper local soilless substrates, if available at affordable prices. Only a few nurserymen, who were using modern imported substrates, demanded the tax exemption facility (35%) and reduction of import export barriers (21%), training of labor about modern substrates and nursery raising techniques (21%) and awareness about modern technologies (16%). Ignorance about modern soilless substrates (53%) and high costs of imported soilless substrates (25%) were reported to be the major issues in limited use of soilless substrates. Nurserymen also complained that they were using personal resources only to cope with their nursery issues and no support was available from public or private sector. Nurserymen were purchasing the traditional substrates, viz. silt from other nurserymen (48%), and get some guidance from university experts, floriculture websites or through floriculture department extension agents. Use of garden soil or silt traditionally and unawareness of the modern soilless substrates were reported as major reasons of low quality nursery production and nurserymen were looking for affordable locally developed soilless substrates for better quality ornamental nursery production. [ABSTRACT FROM AUTHOR]

Bibliometrics is a quantitative tool for the analysis of literature published in a scientific field. Using Scopus as the data source, we perform a thorough analysis of scholarly works published in the field of big data from 2008 to 2017. The objective of the work is to find the most cited articles in the given time frame, the citation trends, the authorship trends as well as the trends of research work in the related area. The analysis shows that over 50% of publications do not receive any citations, and the average number of citations per publication is 3.17. It is also observed that single authorship of research publications has declined over the time. The analysis reveals the pioneering role played by the USA in advancing the research in big data, which has lately been taken over by China, and the large-scale usage of big data analytics in various domains of science. [ABSTRACT FROM AUTHOR]

In this study, a stochastic numerical technique is used to investigate the numerical solution of heat transfer temperature distribution system using feed forward artificial neural networks. Mathematical model of fin equation is formulated with the help of artificial neural networks. The effect of the heat on a rectangular fin with thermal conductivity and temperature de-pendent internal heat generation is calculated through neural networks optimization with optimizers like active set technique, interior point technique, pattern search, genetic algorithm and a hybrid approach of pattern search - interior point technique, genetic algorithm - active set technique, genetic algorithm - interior point technique, and genetic algorithm - sequential quadratic programming with different selections of weights. The governing fin equation is transformed into an equivalent non-linear second order ODE. For this transformed ODE model we have performed several simulations to provide the justification of better convergence of results. Moreover, the effectiveness of the designed models is validated through a complete statistical analysis. This study reveals the importance of rectangular fins during the heat transformation through the system. [ABSTRACT FROM AUTHOR]

A study was conducted to develop indigenous soilless substrate compositions for improved growth, flower yield, stem quality and vase life of cut antirrhinum. Two experiments comprised of seven substrate compositions with variable ratios of saw dust (SD), peanut hulls (PH) and sugarcane pressmud (a by-product of sugar industry, which is rich in nutrients) or coco-coir (CC), rice hulls (RH) and sugarcane pressmud (PM) were used. Seeds were sown in plastic plug trays containing CC, silt (soil extracted from canal) and PM (1:1:1; v/v/v) substrate for seedling development and transplanted at the two to four leaf stage into lily crates with the treatment substrates. Plants grown in substrates containing SD + PH + PM (experiment I) indicated that plants grown in these soilless compositions died before flowering, while those grown in silt (control) performed best. While in experiment II, the highest quality plants were grown in 50% CC + 40% RH +10% PM. Quality was defined as plants with shortest production time (days), tallest plant height (cm), optimal leaf chlorophyll content (SPAD), highest leaf area (cm2 ), fresh and dry weight (g), longest vase life (days). Substrates containing CC, RH and PM (50% + 40% + 10%; v/v/v) were superior to substrates of SD, PH and PM. For commercial cut antirrhinum production, substrates with locally available components of CC, RH and RM can be recommended. [ABSTRACT FROM AUTHOR]

Objectives: To find out the frequency of retinopathy in low birth weight infant presenting at tertiary care hospital, Bahawalpur. Study Design: Cross sectional study. Setting: Department of Ophthalmology, Bahawal Victoria Hospital, Bahawalpur. Period: July 2018 to December 2018. Material & Methods: Neonatal eye examination was performed for ROP. Results: Total 78 neonates were recruited for present study and ROP was assessed. Mean gestational age of neonates was 32.54 ± 3.79 weeks. Mean weight was 1445.51 ± 517.373 grams. Out of 78 neonates, ROP was observed in 28 (36%) neonates. ROP was found in 27 (42.19%) neonates of premature group and in 1 (7.14%) neonates of at term group. ROP was found in 1 (3.23%), 5 (29.41%) and 22 (73.33%) neonates respectively in weight group 1500-2500 g, 1000-1500 g and <1000 g group. Male neonates were 35 (44.87%) and female neonates were 43 (55.13%). Development of ROP was not significantly (P = 0.248) associated with gender of the neonates. Statistically significant association between ROP and oxygen supplementation was observed with p value 0.021. Conclusion: Results showed higher association of development of ROP with gestational age. Oxygen supplementation and oxygen concentration was also associated with development of ROP. Findings also showed no effect of gender and duration of hospital stay on ROP. [ABSTRACT FROM AUTHOR]

Real world complex networks are indirect representation of complex systems. They grow over time. These networks are fragmented and raucous in practice. An important concern about complex network is link prediction. Link prediction aims to determine the possibility of probable edges. The link prediction demand is often spotted in social networks for recommending new friends, and, in recommender systems for recommending new items (movies, gadgets etc) based on earlier shopping history. In this work, we propose a new link prediction algorithm namely "Common Neighbor and Centrality based Parameterized Algorithm" (CCPA) to suggest the formation of new links in complex networks. Using AUC (Area Under the receiver operating characteristic Curve) as evaluation criterion, we perform an extensive experimental evaluation of our proposed algorithm on eight real world data sets, and against eight benchmark algorithms. The results validate the improved performance of our proposed algorithm. [ABSTRACT FROM AUTHOR]

The study examined association between perceived parent adolescent conflict and social competence and whether gender of the adolescents moderated impact of parent-adolescent conflicts on their social competence. The sample of 120 college students (60 boys and 60 girls) who were living with both biological parents was recruited from the public colleges of Lahore. The Conflict Behavior Questionnaire and Social Competence Scale for Adolescents were administered to the participants. Results revealed that there was statistically significant difference between the mean scores of adolescent boys and girls on their perceived adolescent conflict with father (t = 9.41, p <.001) and with mother (t = 2.66, p <.012) however boys' conflict with their parents was stronger than that of girls. Interestingly, both boys and girls perceived their relationship with the parent of the opposite sex as more conflicting. Parent-adolescent conflicts negatively predicted social competence and gender moderated the relationship between motheradolescent conflict and social competence of adolescents after statistically controlling for demographic variables i.e., age of adolescents, class and family system, unlike the case of father-adolescents conflict. Furthermore, adolescent girls scored significantly higher on social competence than boys (t =2.45, p < .016). The findings have been discussed in regard to gender roles in the cultural environment/settings of Pakistan where a huge gender disparity exists between the sexes. As a developing country, changing family life-style due to urbanization and spread of education in Pakistan appears to bode well in negotiating gender discrepancies and viewpoints for adaptive parent-adolescent relationship. It can, in turn, boost social competence as well, among adolescents. [ABSTRACT FROM AUTHOR]

This article presents a methodology to solve a one-dimensional steady-state nonlinear reactive transport model (RTM) that is meant for fluid and solute transport model of soft tissues and microvessels. The methodology integrates the artificial neural network (ANN), genetic algorithms (GAs), and pattern search (PS) aided by active-set technique (AST) and interior-point technique (IPT). The RTM is represented with nonlinear second-order system based on the boundary value problem of ordinary differential equation. The ANN modeling is used for governing expression of RTM to form a fitness function in mean square sense, and optimization solvers based on the GA, PS, GA-AST, GA-IPT, PS-AST, PS-IPT are used for viable learning of weights. Proposed techniques are applied to different nonlinear RTMs based on variation in the characteristic reaction rate and half-saturation concentration. The proposed stochastic numerical solutions are compared with state-of-the-art solvers in order to check the accuracy and convergence based on sufficient large multiple runs of the algorithms. [ABSTRACT FROM AUTHOR]

Background: Global Health Estimates 2015 has shown IHD as second leading global cause of death and 3rd leading global cause for DALYs for 2015. The objectives of this study were to determine frequency, distribution and determinants of DM in adult acute coronary syndrome (ACS) population of D.I.Khan Division, Pakistan. Materials & Methods: This cross-sectional study was conducted in Departments of Ophthalmology & Community Medicine, Gomal Medical College, D.I.Khan, from February 1, 2017 to April 30, 2017. 331 cases were selected with margin of error 4.511%, 90%CL and 25% prevalence of DM in 73,438 adults assumed to have IHD. All indoor adult patients of ACS were eligible. Sex, age groups, and residence and presence of DM were variables. Frequency and distribution were analyzed by count and percentage. Hypotheses for distribution were substantiated by chisquare goodness-of-fit and of association by chi-square test of association. Results: Out of 331 patients with ACS, 225 (68.0%) were men and 106 (32.0%) women, 221 (66.8%) =60 years and 110 (33.2%) >60 years, and 210 (63.4%) urban and 121 (35.6%) rural. Frequency of DM was 79/331 (23.87%). Out of 79 patients with DM, men were 44 (13.29%), women 35 (10.57%), age group =60 years 57 (17.22%), >60 years 22 (6.65%), urban 53 (16.01%) and rural 60 (7.85%). Our prevalence of DM was lower than expected (p=.00214), our distribution by sex was similar to expected (p=.4993) while our distribution for age groups (p=.01209) and residence (p=.00005) were not similar to expected. Presence of DM was associated to sex (p=.011) but not to age groups (p=.0304) and residence (p=.5241). Conclusion: Prevalence of DM in adult ACS population of D.I.Khan Division, Pakistan was found lower than expected. The prevalence was more in men than women, more in younger age group (=60 years) than older age group (>60 years) and more in urban than rural population. Our prevalence of DM was lower than expected, our distribution by sex was similar to expected while our distribution for age groups and residence were not similar to expected. The presence of DM was associated to sex but not to age groups and residence. [ABSTRACT FROM AUTHOR]