Early Islamic politics and government in Nahj al-balāghah

In this thesis, the political concepts of Nahj al-balāghah, a Shīte source of the eleventh century (fourth century after the Hijrah), is examined. The book contains books materials of political philosophy and evaluation of some political events which occurred in the caliphate of Rāshidūn (632-661 A.D.) especially 'Alī . However, the historical authenticity of the book is not the concern of this thesis and the main concentration is made on the early caliphal government and politics in the book with reference to the Islamic political initiatives of Islam in the prophetic society. The first step in our approach is to create awareness about the difficulties which appear in any attempt that deals with Islam and history. The different approaches of Muslims and non-Muslims to Islam and their different perceptions of religious politics are included in the first part. In addition, several political initiatives of Islam such as political economy, political activism, integration of society and so on are examined in the framework of the Qurān and Sunnah of the Prophet. This explanation enables us to observe the politics and government of the first successors of the Prophet in their ideological context. The second part is devoted to explain the major changes in Islamic politics and government after the Prophet. With this background, in the third part, the political contents of Nahj al-balāghah, or "the peak of eloquence", are analyzed without consideration as to whether 'Alī is its real author. There are some principles of political theory and philosophy, as well as a political account of several events in the book which are the main subjects of analysis of the present thesis. In its politico-theoretical dimension, the value of the world, the theological description of human freedom and responsibility, and the theoretical approach to society and history are explained. In its political capacity, issues such as the need for a government and the extent of toleration in it, the role of people, justice, leadership and its responsibilities are included in the third part

Determination of thermal conductivity of eutectic Al-Cu compounds utilizing experiments, molecular dynamics simulations and machine learning

In this study, the thermal conductivity ( κ ) of Al-Cu eutectics were investigated by experimental and computational methods to shed light on the role of these compounds in thermal properties of Al-Cu connections in compound casting. Specifically, the nonequilibrium molecular dynamics (MD) method was utilized to simulate the lattice thermal conductivity ( κ l ) of six compositions of Al-Cu with 5-30 at.% Cu. To extend the results of the MD simulations to bulk materials, instead of using conventional linear extrapolation methods, a machine learning approach was developed for the dataset acquired from the MD simulations. The bootstrapping approach was utilized to find the most suitable method among the support vector machine (SVM) with polynomial and radial basis function (RBF) kernels and the random forest method. The results showed that the SVM model with RBF kernel performed the best, and thus was used to predict the bulk κ l . Subsequently, the chosen compositions were produced by induction casting and their electrical conductivities were measured via eddy current method for calculating the electronic contribution of κ using the Wiedemann-Franz law. Finally, the actual κ of the alloys were measured using the xenon flash method and the results were compared with the computational values. It was shown that the MD method is capable of successfully simulating the thermal conductivity of this system. In addition, the experimental results demonstrated that the κ of Al-Cu eutectics decreases almost linearly with formation of the Al2Cu phase due to increase in the Cu content. Overall, the current findings can be used to enhance the κ of cooling devices made via Al-Cu compound casting

Synthesis, characterization, and assessment of a CeO2@Nanoclay nanocomposite for enhanced oil recovery

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. In this paper, synthesis and characterization of a novel CeO2 /nanoclay nanocomposite (NC) and its effects on IFT reduction and wettability alteration is reported in the literature for the first time. The NC was characterized using scanning electron microscopy (SEM), X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), energy-dispersive X-ray spectroscopy (EDS), and EDS MAP. The surface morphology, crystalline phases, and functional groups of the novel NC were investigated. Nanofluids with different concentrations of 100, 250, 500, 1000, 1500, and 2000 ppm were prepared and used as dispersants in porous media. The stability, pH, conductivity, IFT, and wettability alternation characteristics of the prepared nanofluids were examined to find out the optimum concentration for the selected carbonate and sandstone reservoir rocks. Conductivity and zeta potential measurements showed that a nanofluid with concentration of 500 ppm can reduce the IFT from 35 mN/m to 17 mN/m (48.5% reduction) and alter the contact angle of the tested carbonate and sandstone reservoir rock samples from 139◦ to 53◦ (38% improvement in wettability alteration) and 123◦ to 90◦ (27% improvement in wettability alteration), respectively. A cubic fluorite structure was identified for CeO2 using the standard XRD data. FESEM revealed that the surface morphology of the NC has a layer sheet morphology of CeO2/SiO2 nanocomposite and the particle sizes are approximately 20 to 26 nm. TGA analysis results shows that the novel NC has a high stability at 90◦C which is a typical upper bound temperature in petroleum reservoirs. Zeta potential peaks at concentration of 500 ppm which is a sign of stabilty of the nanofluid. The results of this study can be used in design of optimum yet effective EOR schemes for both carbobate and sandstone petroleum reservoirs

Alpha-N: Shortest Path Finder Automated Delivery Robot with Obstacle Detection and Avoiding System

Alpha N A self-powered, wheel driven Automated Delivery Robot is presented in this paper. The ADR is capable of navigating autonomously by detecting and avoiding objects or obstacles in its path. It uses a vector map of the path and calculates the shortest path by Grid Count Method of Dijkstra Algorithm. Landmark determination with Radio Frequency Identification tags are placed in the path for identification and verification of source and destination, and also for the recalibration of the current position. On the other hand, an Object Detection Module is built by Faster RCNN with VGGNet16 architecture for supporting path planning by detecting and recognizing obstacles. The Path Planning System is combined with the output of the GCM, the RFID Reading System and also by the binary results of ODM. This PPS requires a minimum speed of 200 RPM and 75 seconds duration for the robot to successfully relocate its position by reading an RFID tag. In the result analysis phase, the ODM exhibits an accuracy of 83.75 percent, RRS shows 92.3 percent accuracy and the PPS maintains an accuracy of 85.3 percent. Stacking all these 3 modules, the ADR is built, tested and validated which shows significant improvement in terms of performance and usability comparing with other service robots.Comment: 12 pages, 7 figures, To be appear in the proceedings of 12th Asian Conference on Intelligent Information and Database Systems 23-26 March 2020 Phuket, Thailan

Early Islamic politics and government in Nahj al-balaghah

SIGLEAvailable from British Library Document Supply Centre-DSC:DXN003771 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

Quantification of Triple Single-Leg Hop Test Temporospatial Parameters: A Validated Method Using Body-Worn Sensors for Functional Evaluation after Knee Injury

Lower extremity kinematic alterations associated with sport-related knee injuries may contribute to an unsuccessful return to sport or early-onset post-traumatic osteoarthritis. Also, without access to sophisticated motion-capture systems, temporospatial monitoring of horizontal hop tests during clinical assessments is limited. By applying an alternative measurement system of two inertial measurement units (IMUs) per limb, we obtained and validated flying/landing times and hop distances of triple single-leg hop (TSLH) test against motion-capture cameras, assessed these temporospatial parameters amongst injured and uninjured groups, and investigated their association with the Knee Injury and Osteoarthritis Outcome Score (KOOS). Using kinematic features of IMU recordings, strap-down integration, and velocity correction techniques, temporospatial parameters were validated for 10 able-bodied participants and compared between 22 youth with sport-related knee injuries and 10 uninjured youth. With median (interquartile range) errors less than 10(16) ms for flying/landing times, and less than 4.4(5.6)% and 2.4(3.0)% of reference values for individual hops and total TSLH progression, differences between hopping biomechanics of study groups were highlighted. For injured participants, second flying time and all hop distances demonstrated moderate to strong correlations with KOOS Symptom and Function in Daily Living scores. Detailed temporospatial monitoring of hop tests is feasible using the proposed IMUs system.Medicine, Faculty ofOther UBCNon UBCPhysical Therapy, Department ofReviewedFacult

Optimal path planning of multiple nanoparticles in continuous environment using a novel Adaptive Genetic Algorithm

This paper presents a novel Adaptive Genetic Algorithm for optimal path planning of multiple nanoparticles during the nanomanipulation process. The proposed approach determines the optimal manipulation path in the presence of surface roughness and environment obstacles by considering constraints imposed on the nanomanipulation process. In this research, first by discretizing the environment, an initial set of feasible paths were generated, and then, path optimization was continued in the original continuous environment (and not in the discrete environment). The presented novel approach for path planning in continuous environment (1) makes the algorithm independent of grid size, which is the main limitation in conventional path planning methods, and (2) creates a curve path, instead of piecewise linear one, which increases the accuracy and smoothness of the path considerably. Every path is evaluated based on three factors: the displacement effort (the area under critical force-time diagram during nanomanipulation), surface roughness along the path, and smoothness of the path. Using the weighted linear sum of the mentioned three factors as the objective function provides the opportunity to (1) find a path with optimal value for all factors, (2) increase/decrease the effect of a factor based on process considerations. While the former can be obtained by a simple weight tuning procedure introduced in this paper, the latter can be obtained by increasing/decreasing the weight value associated with a factor. In the case of multiple nanoparticles, a co-evolutionary adaptive algorithm is introduced to find the best destination for each nanoparticle, the best sequence of movement, and optimal path for each nanoparticle. By introducing two new operators, it was shown that the performance of the presented co-evolutionary mechanism outperforms the similar previous works. Finally, the proposed approach was also developed based on a modified Particle Swarm Optimization algorithm, and its performance was compared with the proposed Adaptive Genetic Algorithm. © 2018 Elsevier Inc.1