Abstract Infinitives and gerunds are non-finite verb forms which cannot be indicated by tense, number, or person. The construction of non-finite verbs is intricate because of their nature of meanings, forms, and functions. The major problem is that both infinitival and gerundial complements have identical functions and occupy identical positions in the sentences. Thus, there is a confusion in using an infinitival and gerundial forms after aspectual verbs. The selection of either one of these two forms as complements is controlled syntactically or semantically. Moreover, both forms can be used usually with similar predicate but with neat difference in meaning. In addition, there are problems with controlling the use of aspect, since aspectual verbs have specific syntactic and semantic restrictions. The study aims at investigating the use of infinitival and gerundial constructions and of aspectual verbs in selected British and American Novels, and identifying the syntactic and semantic behvior of aspectual verbs. The following procedures will be followed in the present study. Providing a theoretical background of the infinitival and gerundial complements and of aspectual verbs. Selecting the data from British and American novels, and analzing the novels according to the model of Smith (1997) about the classification of aspectual verbs. It has been concluded that the infinitive has been used more in the American novel, while the gerund has been used more in the British novel. The perfective viewpoint has been utilized more in the British novel, while the imperfective viewpoint has been utilized more in the American novel in the grammatical aspect. The high percentage of infinitive and imperfective viewpoint in the American novel clarifies the tendency to indicate an uncompleted action, while the high percentage of gerund and perfective viewpoint in the British novel clarifies the tendency to indicate a completed action. Stative and Activity verbs in the lexical aspect have been formed the highest percentage in both British and American novels in spite of the differences in the frequency of these verbs between novels. The following procedures will be followed in the present study. Providing a theoretical background of the infinitival and gerundial complements and of aspectual verbs. Selecting the data from British and American novels, and analzing the novels according to the model of Smith (1997) about the classification of aspectual verbs. It has been concluded that the infinitive has been used more in the American novel, while the gerund has been used more in the British novel. The perfective viewpoint has been utilized more in the British novel, while the imperfective viewpoint has been utilized more in the American novel in the grammatical aspect. The high percentage of infinitive and imperfective viewpoint in the American novel clarifies the tendency to indicate an uncompleted action, while the high percentage of gerund and perfective viewpoint in the British novel clarifies the tendency to indicate a completed action. Stative and Activity verbs in the lexical aspect have been formed the highest percentage in both British and American novels in spite of the differences in the frequency of these verbs between novels.
Hypothesis Nanofluid flooding has been identified as a promising method for enhanced oil recovery (EOR) and improved Carbon geo-sequestration (CGS). However, it is unclear how nanoparticles (NPs) influence the CO2-brine interfacial tension (γ), which is a key parameter in pore-to reservoirs-scale fluid dynamics, and consequently project success. The effects of pressure, temperature, salinity, and NPs concentration on CO2-silica (hydrophilic or hydrophobic) nanofluid γ was thus systematically investigated to understand the influence of nanofluid flooding on CO2 geo-storage. Experiments Pendant drop method was used to measure CO2/nanofluid γ at carbon storage conditions using high pressure-high temperature optical cell. Findings CO2/nano
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This study discusses risk management strategies caused by pandemic-related (Covid-19) suspensions in thirty-six engineering projects of different types and sizes selected from countries in the middle east and especially Iraq. The primary data collection method was a survey and questionnaire completed by selected project crew and laborers. Data were processed using Microsoft Excel to construct models to help decision-makers find solutions to the scheduling problems that may be expected to occur during a pandemic. A theoretical and practical concept for project risk management that addresses a range of global and local issues that affect schedule and cost is presented and results indicate that the most significant delays are due to a
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This study was conducted to assess the hydrocarbon degradation abilities of Sphingomonas paucimobilis, Pentoae species, Staphylococcus aureus, and Enterobacter cloacae, which isolated from diesel contaminated soil samples. Single strains and mixed bacterial consortia have been investigated their ability to degrade 1.0 % (v/v) of diesel oil in Bushnell- Haas medium as sole.carbon.and.energy.source. At temperature 30∘C, the individual.bacterial.isolates exhibited low growth and low degradation.than did the.mixed. bacterial.culture. After 28 days.of incubation the.combination.of four isolates degraded.an upper limit.of diesel 88.4%. This was. continued.by 85.1% by S. paucimobilis, 84 % by Pentoae sp., 79% by S.aureus, and
... Show MoreCritical buckling and natural frequencies behavior of laminated composite thin plates subjected to in-plane uniform load is obtained using classical laminated plate theory (CLPT). Analytical investigation is presented using Ritz- method for eigenvalue problems of buckling load solutions for laminated symmetric and anti-symmetric, angle and cross ply composite plate with different elastic supports along its edges. Equation of motion of the plate was derived using principle of virtual work and solved using modified Fourier displacement function that satisfies general edge conditions. Various numerical investigation were studied to exhibit a convergence and accuracy of the present solution for considering some design parameters such as edge
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Manganese sulfate and Punica granatum plant extract were used to create MnO2 nanoparticles, which were then characterized using techniques like Fourier transform infrared spectroscopy, ultraviolet-visible spectroscopy, atomic force microscopy, X-ray diffraction, transmission electron microscopy, scanning electron microscopy, and energy-dispersive X-ray spectroscopy. The crystal's size was calculated to be 30.94nm by employing the Debye Scherrer equation in X-ray diffraction. MnO2 NPs were shown to be effective in adsorbing M(II) = Co, Ni, and Cu ions, proving that all three metal ions may be removed from water in one go. Ni(II) has a higher adsorption rate throughout the board. Co, Ni, and Cu ion removal efficiencie
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Manganese sulfate and Punica granatum plant extract were used to create MnO2 nanoparticles, which were then characterized using techniques like Fourier transform infrared spectroscopy, ultraviolet-visible spectroscopy, atomic force microscopy, X-ray diffraction, transmission electron microscopy, scanning electron microscopy, and energy-dispersive X-ray spectroscopy. The crystal's size was calculated to be 30.94nm by employing the Debye Scherrer equation in X-ray diffraction. MnO2 NPs were shown to be effective in adsorbing M(II) = Co, Ni, and Cu ions, proving that all three metal ions may be removed from water in one go. Ni(II) has a higher adsorption rate throughout the board. Co, Ni, and Cu ion removal efficiencies were 32.79%, 75
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Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c
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