Although the concept of difference is as old as the foundational concept of similarity, the modern (and contemporary) understanding of difference as a working notion that not only differentiates, but also approximates conflicting elements in an all encompassing system owes a great deal to the German philosopher Georg Wilhelm Friedrich Hegel (1770-1831). An idealist to the backbone, Hegel bequeathed to modern philosophy the postulation that the identity of an individual rests not in itself but in the relationship that individual‟s identity entertains with other members of society. In his classic Phenomenology of Spirit, Hegel explains how humans come to consciousness (pivotal concept in Idealism) through a strenuous, albeit apparently intuitive, process which he calls “the dialectic” that he exemplifies in the famous Master-Slave dialectic.1
Hegel assumes that humans are not born with an independent, formative consciousness, but, on the contrary, they aspire to acquire self-consciousness when the self (which Hegel alternatively calls “being-for-self”) is acknowledged and recognized by other fellows—an arduous, but imperative, dynamic that Hegel terms “being-for-others.” Self-consciousness is attained only after the self
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undergoes painstaking “stages” involved in the system of human relationships, which is representative of the Hegelian dialectic. This all-encompassing, ever changing system holistically places the individual “self” in relation to other “selves” while itself remains in constant motion. Accordingly, meaning and truth are never determinately fixed because they are always in process since, says Hegel, “the action has a double significance not only because it is directed against itself as well as against the other, but also because it is indivisibly the action of one as well as of the other.”2
This paper presents a nonlinear finite element modeling and analysis of steel fiber reinforced concrete (SFRC) deep beams with and without openings in web subjected to two- point loading. In this study, the beams were modeled using ANSYS nonlinear finite element
software. The percentage of steel fiber was varied from 0 to 1.0%.The influence of fiber content in the concrete deep beams has been studied by measuring the deflection of the deep beams at mid- span and marking the cracking patterns, compute the failure loads for each deep beam, and also study the shearing and first principal stresses for the deep beams with and without openings and with different steel fiber ratios. The above study indicates that the location of openings an
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In this study, an improved process was proposed for the synthesis of structure-controlled Cu2O nanoparticles, using a simplified wet chemical method at room temperature. A chemical solution route was established to synthesize Cu2O crystals with various sizes and morphologies. The structure, morphology, and optical properties of Cu2O nanoparticles were analyzed by X-ray diffraction, SEM (scanning electron microscope), and UV-Vis spectroscopy. By adjusting the aqueous mixture solutions of NaOH and NH2OH•HCl, the synthesis of Cu2O crystals with different morphology and size could be realized. Strangely, it was found that the change in the ratio of de-ionized water and NaOH aqueous solution led to the synthesis of Cu2O crystals of differen
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Stone Matrix Asphalt (SMA) is a gap-graded asphalt concrete hot blend combining high-quality coarse aggregate with a rich asphalt cement content. This blend generates a stable paving combination with a powerful stone-on-stone skeleton that offers excellent durability and routing strength. The objectives of this work are: Studying the durability performance of stone matrix asphalt (SMA) mixture in terms of moisture damage and temperature susceptibility and Discovering the effect of stabilized additive (Fly Ash ) on the performance of stone matrix asphalt (SMA) mixture. In this investigation, the durability of stone matrix asphalt concrete was assessed in terms of temperature susceptibility, resistance to moisture damage, and sensitivity t
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Nanoparticles (NPs) have unique capabilities that make them an eye-opener opportunity for the upstream oil industry. Their nano-size allows them to flow within reservoir rocks without the fear of retention between micro-sized pores. Incorporating NPs with drilling and completion fluids has proved to be an effective additive that improves various properties such as mud rheology, filtration, thermal conductivity, and wellbore stability. However, the biodegradability of drilling fluid chemicals is becoming a global issue as the discharged wetted cuttings raise toxicity concerns and environmental hazards. Therefore, it is urged to utilize chemicals that tend to break down and susceptible to biodegradation. This research presents the pra
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In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial
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This study aimed to isolate and identify Cryptococcus species from three distinct sources: sputum samples of pigeon fanciers, dried pigeon droppings, and eucalyptus tree leaves. A total of 150 specimens were collected over a two-month period, comprising 50 samples each from human sputum, pigeon droppings collected across various areas of Baghdad, and eucalyptus leaves obtained from the Baghdad College of Veterinary Medicine. All samples were cultured on Sabouraud dextrose agar supplemented with chloramphenicol and incubated at 25°C for 2–3 days. From the initial cultures, 20 isolates presumptively identified as Cryptococcus spp. were obtained: 6 isolates (12%) from human sputum, 9 isolates (18%) from pigeon droppings, and 5 isol
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To reduce the effects of discharging heated water disposed into a river flow by a single thermal source, two parameters were changed to get the minimum effect using optimization. The first parameter is to distribute the total flow of the heated water between two disposal points (double source) instead of one and the second is to change the distance between these two points. In order to achieve the solution, a two dimensional numerical model was developed to simulate and predict the changes in temperature distribution in the river due to disposal of the heated water using these two points of disposal.
MATLAB-7 software was used to build a program that could solve the governing partial equations of thermal pollution in rivers by using t