120 research outputs found
Correction to: A study of plithogenic graphs: applications in spreading coronavirus disease (COVID-19) globally (Journal of Ambient Intelligence and Humanized Computing, (2022), 10.1007/s12652-022-03772-6)
No full textIn this article the author name 'Tauseef Ahmad' was incorrectly written as 'Tauseef Ahmed’
Nanostructured Magnetic Films Produced by Magnetic Nanoparticles
No full textGas-phase Fe nanoparticles with a diameter ~ 2nm, have been used in all the nanostructured material in this thesis. In pure Fe nanoparticle systems with different thicknesses, two important parameters the exchange interaction (Hex) and random anisotropy (Hr) were investigated using the Random Anisotropy Model (RAM). This reveals that for the same particle size Hex remains almost constant for varying Fe thicknesses; whereas Hr increases with the increase of Fe film thickness. This is ascribed to increasing strain imposed at the nanoparticle level. The observed high values of Hr are related to an oxide on the cluster surface in these films, whose effect is also observed in low temperature magnetometry data. This shows the appearance of exchange bias in the films. The RAM approach when applied to Fe clusters in Co matrices, reveals much lower values of Hr than found in pure Fe nanoparticles and both Hr and Hex show an increase with the Volume Fraction (VF) of Fe in Co. The increase in Hex is ascribed to the increasing spin moment with Fe volume fraction. The nature of Fe clusters in very thick layers produce a high frequency Ferromagnetic Resonance response in the radio frequency range, which is an important finding for many applications.
The EXAFS study of Fe nanoparticles in Cr matrices show no structural modification relative to the bulk bcc structure of both elements. The magnetometry results suggest that in dilute Fe concentration films, the observed decrease in the overall magnetization is due to the development of a nonmagnetic shell at the interface between Fe and Cr at each cluster boundary. This is reinforced by the lack of any evidence of EB. With increasing VF at about 10% of Fe there is strong evidence of the formation of a super-spin-glass (SSG) that shows the characteristic memory effect. Increasing the Fe nanoparticles VF to 20% Fe in Cr, the magnetization exceeds that expected for Fe indicating that the interaction induces some of the Cr to order ferromagnetically.
Core-shell nanoparticle systems have been synthesised by a method that allows a complete control over the morphology of these assemblies. Atomic investigations in Fe@Cu CS nanoparticles reveal that Fe nanoparticles adopt the fcc structure with a 20 monolayer Cu shell thickness and stay in the bcc structure for 1-2 monolayer thick Cu shells. No alteration in the Fe atomic structure has been reported for different Au shell thicknesses in Fe@Au. The magnetic data show a reduced magnetization of the FM-AFM Fe@Cr CS nanoparticles as compared to the bulk value which is also ascribed to the formation of a non-magnetic Fe shell at the interface
Role of biocontrol agents in weed management – recent developments and trends
Full text linkWithin integrated pest management programs, biological control of unwanted plants has remarkable capacity to provide viable, effective, and economic control of weeds. When using bio-herbicides, crop production and quality improve with virtually no damage to the ecosystem. Bioherbicides are target-specific, destroy only selected weeds that have been sprayed for and do not cause harm to non-target plants. Bio-herbicides can be quickly incorporated into weed control programs, which can reduce chemical herbicide dependence. We are also raising the chance of environmental pollution by pesticides. There are only a few bio-herbicides available on commercial bases although work began earlier in the 1940s. Sources of commercialized bioherbicides include Phytophthora palmivora (Devine), Collectotrichum gleosporiodes (Collego), Colletotrichum gloeosporioides (Binomial) and Streptomyces viridochromogenes (Bialaphos and Glufosinate). Virulence for pathogens and their environmental requirement are major constraints for bioherbicide development. Specific bio-herbicides should be useful in finding position in irrigated fields, wildlife while thriving weeds with pests or resistant weed control.Within integrated pest management programs, biological control of unwanted plants has remarkable capacity to provide viable, effective, and economic control of weeds. When using bio-herbicides, crop production and quality improve with virtually no damage to the ecosystem. Bioherbicides are target-specific, destroy only selected weeds that have been sprayed for and do not cause harm to non-target plants. Bio-herbicides can be quickly incorporated into weed control programs, which can reduce chemical herbicide dependence. We are also raising the chance of environmental pollution by pesticides. There are only a few bio-herbicides available on commercial bases although work began earlier in the 1940s. Sources of commercialized bioherbicides include Phytophthora palmivora (Devine), Collectotrichum gleosporiodes (Collego), Colletotrichum gloeosporioides (Binomial) and Streptomyces viridochromogenes (Bialaphos and Glufosinate). Virulence for pathogens and their environmental requirement are major constraints for bioherbicide development. Specific bio-herbicides should be useful in finding position in irrigated fields, wildlife while thriving weeds with pests or resistant weed control
Phytotoxic Activity of Bioactive Compounds from Four Plants against Selected Weeds in Agriculture
Full text linkAim of the study:
Heavy doses of synthetic weed control chemicals have caused herbicide resistance in weeds. Natural compounds produced by living organisms constitute a wide field for ecologically safe herbicides. The current investigation was directed to test allelopathic potential of hexane extracts of selected plants against common weeds of agriculture.
Material and methods:
Allelopathic potential of Carica papaya, Rhazya stricta, Lantana camara and Pinus roxburghii hexane extracts against weeds viz. Euphorbia helioscopia, Rumex dentatus, Phalaris minor, Avena fatua and Chenopodium album was determined at 100%, 75% and 50% concentration on soil, filter paper and agar. Parameters for assessing allelopathic potential were the germination (%), plumule and radicle size (cm). Data analysis was performed using the software STATISTIX 9.
Results and conclusions:
Based on the findings, it was determined that R. stricta, C. papaya, L. camara and P. roxburghii hexane extract possesses possible suppression effects among which L. camara had the most conspicuous inhibition effects on selected weeds. The inhibitory effects of germination and growth were establishing in order R. stricta > L. camara > C. papaya > P. Roxburghii. Field analysis to assess the phytotoxic ability of these species to be used as herbicide is recommended
Optical and Magnetic Response of Pure and CU-Ions Substituted Dysprosium Oxide Thin Films for Various Applications
Full text linkDysprosium oxide (Dy2O3) and Cu/Dy2O3 thin films of thickness 117.14 nm and 258.30 nm, respectively were successfully deposited via a well-known DC-magnetron sputtering technique. Field emission scanning electron microscopy clarifies the growth of uniform and fine granular particles on silicon substrate. The hexagonal closed pack structure for both the thin films has been observed by the x-ray diffraction analysis and it was observed that by inclusion of copper the HCP structure of thin film was retain with a slight shift in the main peak. The reduction from 3.9 eV to 3.8 eV in the energy band gap value was observed by incorporation of copper ions Dy2O3 thin films. The M-H loops obtained through Vibrating Sample Magnetometer (VSM) shows that Dy2O3 thin film behave ferromagnetically at low temperature with a saturation magnetization value of 2860 emu/cc and evolves through its phase transition temperatures and behave paramagnetically at room temperature. In Cu/Dy2O3 case, the diamagnetic response of Cu dominates and produces reverse hysteresis loop at both temperatures make it a suitable candidate for energy and memory storage devices applications
Implementing an Effective Cost Control Strategy at Stations: Case Study of PIA
No full textThis case study describes the process of developing and implementing a strategy to control costs and reduce losses on account of frauds, accounting errors, wrong payments, etc., at the worldwide outstations of an airline where traditional oversight methods had fallen short of management expectations. By identifying the systemic weaknesses in various areas of station disbursement accounting arising out of lack of training, non-availability of important corporate policies and management directives and lack of standard procedures for preparing and dispatching disbursement reports to head office, a comprehensive Stations Disbursement Manual was developed to train and empower the managers at stations to control and release payments in a responsible manner
An Empirical Study of Machine Learning Techniques for Classifying Emotional States from EEG Data
No full textWith the great advancement in robot technology, smart human-robot interaction is considered to be the most wanted success by the researchers these days. If a robot can identify emotions and intentions of a human interacting with it, that would make robots more useful. Electroencephalography (EEG) is considered one effective way of recording emotions and motivations of a human using brain. Various machine learning techniques are used successfully to classify EEG data accurately. K-Nearest Neighbor, Bayesian Network, Artificial Neural Networks and Support Vector Machine are among the suitable machine learning techniques to classify EEG data. The aim of this thesis is to evaluate different machine learning techniques to classify EEG data associated with specific affective/emotional states. Different methods based on different signal processing techniques are studied to find a suitable method to process the EEG data. Various number of EEG data features are used to identify those which give best results for different classification techniques. Different methods are designed to format the dataset for EEG data. Formatted datasets are then evaluated on various machine learning techniques to find out which technique can accurately classify EEG data according to associated affective/emotional states. Research method includes conducting an experiment. The aim of the experiment was to find the various emotional states in subjects as they look on different pictures and record the EEG data. The obtained EEG data is processed, formatted and evaluated on various machine learning techniques to find out which technique can accurately classify EEG data according to associated affective/emotional states. The experiment confirms the choice of a technique for improving the accuracy of results. According to the results, Support Vector Machine is the first and Regression Tree is the second best to classify EEG data associated with specific affective/emotional states with accuracies up to 70.00% and 60.00% respectively. SVM is better in performance than RT. However, RT is famous for providing better accuracies for diverse EEG data
Implementing an Effective Cost Control Strategy at Stations: Case Study of PIA
Full text linkThis case study describes the process of developing and implementing a strategy to control costs and reduce losses on account of frauds, accounting errors, wrong payments, etc., at the worldwide outstations of an airline where traditional oversight methods had fallen short of management expectations. By identifying the systemic weaknesses in various areas of station disbursement accounting arising out of lack of training, non-availability of important corporate policies and management directives and lack of standard procedures for preparing and dispatching disbursement reports to head office, a comprehensive Stations Disbursement Manual was developed to train and empower the managers at stations to control and release payments in a responsible manner
Nanostructured magnetic films produced by magnetic nanoparticles
No full textGas-phase Fe nanoparticles with a diameter ~ 2nm, have been used in all the nanostructured material in this thesis. In pure Fe nanoparticle systems with different thicknesses, two important parameters the exchange interaction (Hex) and random anisotropy (Hr) were investigated using the Random Anisotropy Model (RAM). This reveals that for the same particle size Hex remains almost constant for varying Fe thicknesses; whereas Hr increases with the increase of Fe film thickness. This is ascribed to increasing strain imposed at the nanoparticle level. The observed high values of Hr are related to an oxide on the cluster surface in these films, whose effect is also observed in low temperature magnetometry data. This shows the appearance of exchange bias in the films. The RAM approach when applied to Fe clusters in Co matrices, reveals much lower values of Hr than found in pure Fe nanoparticles and both Hr and Hex show an increase with the Volume Fraction (VF) of Fe in Co. The increase in Hex is ascribed to the increasing spin moment with Fe volume fraction. The nature of Fe clusters in very thick layers produce a high frequency Ferromagnetic Resonance response in the radio frequency range, which is an important finding for many applications. The EXAFS study of Fe nanoparticles in Cr matrices show no structural modification relative to the bulk bcc structure of both elements. The magnetometry results suggest that in dilute Fe concentration films, the observed decrease in the overall magnetization is due to the development of a nonmagnetic shell at the interface between Fe and Cr at each cluster boundary. This is reinforced by the lack of any evidence of EB. With increasing VF at about 10% of Fe there is strong evidence of the formation of a super-spin-glass (SSG) that shows the characteristic memory effect. Increasing the Fe nanoparticles VF to 20% Fe in Cr, the magnetization exceeds that expected for Fe indicating that the interaction induces some of the Cr to order ferromagnetically. Core-shell nanoparticle systems have been synthesised by a method that allows a complete control over the morphology of these assemblies. Atomic investigations in Fe@Cu CS nanoparticles reveal that Fe nanoparticles adopt the fcc structure with a 20 monolayer Cu shell thickness and stay in the bcc structure for 1-2 monolayer thick Cu shells. No alteration in the Fe atomic structure has been reported for different Au shell thicknesses in Fe@Au. The magnetic data show a reduced magnetization of the FM-AFM Fe@Cr CS nanoparticles as compared to the bulk value which is also ascribed to the formation of a non-magnetic Fe shell at the interface.EThOS - Electronic Theses Online ServiceGBUnited Kingdo
Isolation of vitexin as natural bio-herbicide from Lantana camara leaves
No full text‘Yield maximization’ is the last word of modern agriculture for food security of ever increasing population of the world. Maximizing world’s agricultural efficiency depends largely on controlling a variety of pests and diseases. Among pests, weeds have largest negative impact on crop productivity. Among main strategies used to control weeds (i.e., physical, mechanical, chemical and biological) the chemical method is most popular for decreasing negative effects of weeds in crops. But, herbicide-resistant weeds have been emerging due to extensive use of synthetic chemical herbicides, and public concerns over impact of synthetic herbicidal chemicals on environment and human health are increasing. Natural compounds, known as “bio-herbicides” pose a big area for environmentally safe herbicides, based on compounds produced by living organisms. In current study, crude methanol extract of invasive toxic plant Lantana camara leaves was prepared by cold maceration technique and was subjected to fractionation. Fractionation resulted in three organic (ethyl acetate, chloroform and n-hexane) and one aqueous fraction for the crude extract. Bioassays were performed at 10,000ppm, 1,000 ppm and 500ppm concentration against selected weed test species (monocot: Avena fatua and Phalaris minor; Dicot: Rumex dentatus and Chenopodium album). Chloroform fraction was selected on the basis for its highest herbicidal activity. Silica gel was used for column chromatography. Sample was loaded after adsorption on silica gel by making a uniform and even layer. Mobile phase of Hexane: Ethyl acetate (60:40) was used based on TLC profiling. A total of 31 elusions were collected in small column vials. They were left overnight to make them concentrated and were again subjected to Thin Layer Chromatography (TLC). Vanillin TLC stains was used for visualization purpose. Fractions with similar TLC pattern were combined and bio-assayed against radish seeds at 1mg/mL. Sub-fraction (iii) of fraction 23 showed highest growth inhibition therefore selected for further analysis. GC-MS (Shimadzu GC-MS-QP2010 ultra) with Helium gas as carrier was used to find out purity of compound and possible compound identification. GCMS analysis showed the compound as Vitexin (C21H20O10) (flavone glucoside). To the best of our knowledge Lantana camara leaves have not been previously reported to possess flavonoid compound ‘vitexin’ and tested against weeds of wheat crop
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