Isolate-Specific Effect of Entomopathogenic Endophytic Fungi on Population Growth of Two-Spotted Spider Mite (Tetranychus urticae Koch) and Levels of Steroidal Glycoalkaloids in Tomato

Journal of Chemical Ecology - Entomopathogenic fungi (EPF) can be experimentally established in several plant species as endophytes. Ecological effects of EPF inoculations on plant growth and...     

Solubility Enhancement of Fe in ZnO Nanoparticles Prepared by Co-Precipitation Method

Journal of Superconductivity and Novel Magnetism - Crystalline ZnO offers an excellent host matrix to create a dilute magnetic semiconductor (DMS) owing to its facile Zn-atom substitution with the...     

A study on the synthesis,characterization and properties of polyaniline/magnesium boride nanocomposites

The present paper reports the novel synthesis of polyaniline/magnesium boride (PAni/MgB₂) nanocomposites. Nanowires 50–100 nm in diameter grown by the sol–gel technique were incorporated in the PAni to prepare PAni/MgB₂ nanocomposites, which yielded an enhancement of conductivity by 5 orders of magnitude. PAni was synthesized through the chemical oxidative polymerization method. The composition of the prepared nanocomposites was tunable, i.e. the amount of dopant was varied and the effects on various parameters were observed by different techniques. The morphology of PAni/MgB₂ nanocomposites was determined using SEM. The temperature dependence of the conductivity of all composites was measured in the temperature range 300–450 K and it was observed that samples having a high concentration of MgB₂ show the highest conductivity. The molecular structure of the nanocomposites was further characterized by Fourier Transform IR spectroscopy which showed small structural changes in the backbone of PAni. I?V measurements showed that the current increases on increasing MgB₂ content. UV?visible spectra exposed the occurrence of an indirect optical transition in the composite. © 2013 Society of Chemical Industry     

The effect of magnetic and optic field in water electrolysis

Hydrogen production via water electrolysis was studied under the effect of magnetic and optical field. A diode solid state laser at blue, green and red were utilized as optical field source. Magnetic bar was employed as external magnetic field. The green laser has shown a greatest effect in hydrogen production due to its non-absorbance properties in the water. Thus its intensity of electrical field is high enough to dissociation of hydronium and hydroxide ions during orientation toward polarization of water. The potential to break the autoprotolysis and generate the auto-ionization is the mechanism of optical field to reveal the hydrogen production in water electrolysis. The magnetic field effect is more dominant to enhance the hydrogen production. The diamagnetic property of water has repelled the present of magnetic in water. Consequently the water splitting occurs due to the repulsive force induced by the external magnetic field. The magnetic distributed more homogenous in the water to involve more density of water molecule. As a result hydrogen production due to magnetic field is higher in comparison to optical field. However the combination both fields have generated superior effect whereby the hydrogen yields nine times higher in comparison to conventional water electrolysis.     

Fabrication of Hollow Microporous Carbon Spheres from Hyper‐Crosslinked Microporous Polymers

Porous carbon materials prepared from the porous organic polymers are currently the subject of extensive investigation. On the basis of their interesting applications, it is highly desirable to develop new synthetic methodologies to obtain carbon materials with controllable pore size and morphology. Herein, a facile synthesis of hollow microporous carbon spheres (HCSs) from hollow microporous organic capsules (HMOCs) with a good control over the pore morphology, hollow cavity, and the shell thickness is reported. The highly porous hollow carbon spheres are prepared by the pyrolysis of HMOCs‐based microporous polymers. The synthetic parameters, such as hypercrosslinking and pyrolysis conditions, are optimized to modify the porous structures and the properties. The morphology and porosity as well as energy storage applications of the microporous structures HCSs, derived through a combination of divinylbenzene‐crosslinking and micropore‐generating hypercrosslinking, are discussed. These findings provide a new benchmark for fabricating well‐defined HCSs with great promise for various applications.     

Machine Learning Empowered Security Management and Quality of Service Provision in SDN-NFV Environment

With the rising demand for data access, network service providers face the challenge of growing their capital and operating costs while at the same time enhancing network capacity and meeting the increased demand for access. To increase efficacy of Software Defined Network (SDN) and Network Function Virtualization (NFV) framework, we need to eradicate network security configuration errors that may create vulnerabilities to affect overall efficiency, reduce network performance, and increase maintenance cost. The existing frameworks lack in security, and computer systems face few abnormalities, which prompts the need for different recognition and mitigation methods to keep the system in the operational state proactively. The fundamental concept behind SDN-NFV is the encroachment from specific resource execution to the programming-based structure. This research is around the combination of SDN and NFV for rational decision making to control and monitor traffic in the virtualized environment. The combination is often seen as an extra burden in terms of resources usage in a heterogeneous network environment, but as well as it provides the solution for critical problems specially regarding massive network traffic issues. The attacks have been expanding step by step; therefore, it is hard to recognize and protect by conventional methods. To overcome these issues, there must be an autonomous system to recognize and characterize the network traffic’s abnormal conduct if there is any. Only four types of assaults, including HTTP Flood, UDP Flood, Smurf Flood, and SiDDoS Flood, are considered in the identified dataset, to optimize the stability of the SDN-NFV environment and security management, through several machine learning based characterization techniques like Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Logistic Regression (LR) and Isolation Forest (IF). Python is used for simulation purposes, including several valuable utilities like the mine package, the open-source Python ML libraries Scikit-learn, NumPy, SciPy, Matplotlib. Few Flood assaults and Structured Query Language (SQL) injections anomalies are validated and effectively-identified through the anticipated procedure. The classification results are promising and show that overall accuracy lies between 87% to 95% for SVM, LR, KNN, and IF classifiers in the scrutiny of traffic, whether the network traffic is normal or anomalous in the SDN-NFV environment.     

Partially oxidized cobalt species in nitrogen-doped carbon nanotubes: Enhanced catalytic performance to water-splitting

It's still an ongoing research challenge to explore non-precious metal-based catalysts for substituting precious metal catalysts during full water electrocatalysis. Herein, we reported the partially oxidized cobalt species in nitrogen-doped carbon nanotubes hierarchical structures to produce dual-functionality towards oxygen/hydrogen evolution reactions. The in situ transformation of carbon nanotubes and well-exposed metal-oxide contributes to mass diffusion and greater electrolyte-accessible surface area. The as-synthesized catalyst displays low overpotentials of 287 mV and 171 mV for oxygen and hydrogen evolution reactions at 10 mA cm^?2 of current density with remarkable performance during long-term stability. Furthermore, when employed as cathode and anode, a respectable performance of 1.68 V demonstrated our catalyst as an efficient bifunctional material for conducting water-splitting operation.     

Numerical Analysis of Novel Coronavirus (2019-nCov) Pandemic Model with Advection

Recently, the world is facing the terror of the novel corona-virus, termed as COVID-19. Various health institutes and researchers are continuously striving to control this pandemic. In this article, the SEIAR (susceptible, exposed, infected, symptomatically infected, asymptomatically infected and recovered) infection model of COVID-19 with a constant rate of advection is studied for the disease propagation. A simple model of the disease is extended to an advection model by accommodating the advection process and some appropriate parameters in the system. The continuous model is transposed into a discrete numerical model by discretizing the domains, finitely. To analyze the disease dynamics, a structure preserving non-standard finite difference scheme is designed. Two steady states of the continuous system are described i.e., virus free steady state and virus existing steady state. Graphical results show that both the steady states of the numerical design coincide with the fixed points of the continuous SEIAR model. Positivity of the state variables is ensured by applying the M-matrix theory. A result for the positivity property is established. For the proposed numerical design, two different types of the stability are investigated. Nonlinear stability and linear stability for the projected scheme is examined by applying some standard results. Von Neuman stability test is applied to ensure linear stability. The reproductive number is described and its pivotal role in stability analysis is also discussed. Consistency and convergence of the numerical model is also studied. Numerical graphs are presented via computer simulations to prove the worth and efficiency of the quarantine factor is explored graphically, which is helpful in controlling the disease dynamics. In the end, the conclusion of the study is also rendered.     

Agglomeration of Pakistani coal (Lakhra) using diesel oil

The upgradation of a low quality coal enables it suitable for wider applications. The Lakhra coal (Pakistan) belongs to the lignite coal category. This study investigates the agglomeration technique for beneficiation of Lakhra coal using diesel oil as an agglomerant. Three parameters were investigated such as the solid–liquid ratio, residence time, and shear velocity. Characterization of the Lakhra coal before and after agglomeration was carried out in order to determine its volatile matter, fixed carbon, ash and sulfur contents, and gross calorific value. According to the results, agglomerates contained fixed carbon 35.63%, volatile matter 42.21%, gross calorific value (GCV) 5570.6 kcal/kg, ash 17.07%, and sulfur 4.03%. The ash and sulfur reductions were 42.3% and 58.4%, respectively, suggesting significant reduction in ash and sulfur compared to the original coal. The clean coal, resulting from this cleaning process, is a good grade product which may be valued as a good fuel source for any coal fired utility.     

Accumulation of heavy metals in edible parts of vegetables irrigated with waste water and their daily intake to adults and children,District Mardan,Pakistan

Green vegetable crops irrigated with wastewater are highly contaminated with heavy metals and are the main source of human exposure to the contaminants. In this study accumulation of eight heavy metals (Cu, Ni, Zn, Cr, Fe, Mn, Co and Pb) in green vegetables like Allium cepa, Allium sativum, Solanum lycopersicum and Solanum melongena, irrigated with wastewater in Mardan are studied using Atomic Absorption spectrophotometer. The studied metals in vegetable grown on wastewater irrigated soil were significantly higher than those of tube well water irrigated soil and WHO/FAO permissible limits (P < 0.05). The most heavily contaminated vegetable was wastewater irrigated A. cepa, where the accumulation of Mn (28.05 mg kg^?1) in the edible parts was 50-fold greater than A. cepa irrigated with tube well water irrigated soil. It may be concluded that both adults and children consuming these vegetables grown in wastewater irrigated soil ingest significant amount of these metals and thus can cause serious health problems.