Search results for: deep injection well

Authors: Raju Murugan, Pankaj S. Kolhe

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The present study is mainly focusing on the numerical simulation of Flow Blurring (FB) twin fluid injection concept was proposed by Ganan-Calvo, which involves back flow atomization based on global bifurcation of liquid and gas streams, thus creating two-phase flow near the injector exit. The interesting feature of FB injector spray is an insignificant effect of variation in atomizing air to liquid ratio (ALR) on a spray cone angle. Besides, FB injectors produce a nearly uniform spatial distribution of mean droplet diameter and are least susceptible to variation in thermo-physical properties of fuels, making it a perfect candidate for fuel flexible combustor development. The FB injector working principle has been realized through experimental flow visualization techniques only. The present study explores potential of ANSYS Fluent based Large Eddy Simulation(LES) with volume of fluid (VOF) method to investigate two-phase flow just upstream of injector dump plane and spray quality immediate downstream of injector dump plane. Note that, water and air represent liquid and gas phase in all simulations and ALR is varied by changing the air mass flow rate alone. Preliminary results capture two phase flow just upstream of injector dump plane and qualitative agreement is observed with the available experimental literature.

Keywords: flow blurring twin fluid atomization, large eddy simulation, volume of fluid, air to liquid ratio

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Authors: Sarra Khelifi, Youcef Guerabli, Ahcene Boumaiza

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Advances in techniques for measuring individual crystallographic orientations have made it possible to investigate the role of local crystallography during the plastic deformation of materials. In this study, the change in crystallographic orientation distribution during deformation by deep drawing in carbon steel has been investigated in order to understand their role in propagation and arrest of crack. The results show that the change of grain orientation from initial recrystallization texture components of {111}<112> to deformation orientation {111}<110> incites the initiation and propagation of cracks in the region of {111}<112> small grains. Moreover, the misorientation profile and local orientation are analyzed in detail to discuss the change from {111}<112> to {111}<110>. The deformation of the grain with {111}<110> orientation is discussed in terms of stops of the crack in carbon steel during drawing. The SEM-EBSD technique was used to reveal the change of orientation; XRD was performed for the characterization of the global evolution of texture for deformed samples.

Keywords: fracture, heterogeneity, misorientation profile, stored energy

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Authors: Zoe Polk

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In cities across the US, race continues to predict an individual’s likelihood to be employed, to receive a quality education, to live in a safe neighborhood, to life expectancy to contacts with the criminal justice system. Deep and pervasive disparities exist despite laws enacted at the federal, state and local level to eliminate discrimination. This paper examines the strengths of the U.S. civil rights movement in making discrimination a moral issue. Following the passage of the 1964 Civil Rights Act, cities throughout the US adopted laws that mirror the language, theories of practice and enforcement of the law. This paper argues that while those laws were relevant to the way discrimination was conducted in that time, they are limited in their ability to help cities address discrimination today. This paper reviews health indicators This paper concludes that in order for cities to create environments where race no longer predicts one’s success, cities must conduct institutional and structural racism audits.

Keywords: racism, racial equity, constitutional law, social justice

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Authors: Saed Khawaldeh, Mohamed Elsharnouby, Alaa Eddin Alchalabi, Usama Pervaiz, Tajwar Aleef, Vu Hoang Minh

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Taxonomic classification has a wide-range of applications such as finding out more about the evolutionary history of organisms that can be done by making a comparison between species living now and species that lived in the past. This comparison can be made using different kinds of extracted species’ data which include DNA sequences. Compared to the estimated number of the organisms that nature harbours, humanity does not have a thorough comprehension of which specific species they all belong to, in spite of the significant development of science and scientific knowledge over many years. One of the methods that can be applied to extract information out of the study of organisms in this regard is to use the DNA sequence of a living organism as a marker, thus making it available to classify it into a taxonomy. The classification of living organisms can be done in many machine learning techniques including Neural Networks (NNs). In this study, DNA sequences classification is performed using Convolutional Neural Networks (CNNs) which is a special type of NNs.

Keywords: deep networks, convolutional neural networks, taxonomic classification, DNA sequences classification

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Authors: Hrishi Rakshit, Pooneh Bagheri Zadeh

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This paper investigates the performance of drone classification methods using conventional DCNN with different hyperparameters, when additional drone audio data is embedded in the dataset for training and further classification. In this paper, first a custom dataset is created using different images of drones from University of South California (USC) datasets and Leeds Beckett university datasets with embedded drone audio signal. The three well-known DCNN architectures namely, Resnet50, Darknet53 and Shufflenet are employed over the created dataset tuning their hyperparameters such as, learning rates, maximum epochs, Mini Batch size with different optimizers. Precision-Recall curves and F1 Scores-Threshold curves are used to evaluate the performance of the named classification algorithms. Experimental results show that Resnet50 has the highest efficiency compared to other DCNN methods.

Keywords: drone classifications, deep convolutional neural network, hyperparameters, drone audio signal

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Authors: Vasudev Das

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The specific problem is that many leaders of the 21st century do not understand that the extermination of embryos wreaks havoc on peace leadership. The purpose of the document review is to understand embryology in facilitating peace leadership. Extermination of human embryos generates a requital wave of violence which later falls on human society in the form of disturbances, considering that violence breeds further violence as a consequentiality. The study results reveal that a deep understanding of embryology facilitates peace leadership, given that minimizing embryo extermination enhances non-violence in the global village. Neo-Newtonians subscribe to the idea that every action has an equal and opposite reaction. The US Federal Government recognizes the embryo or fetus as a member of Homo sapiens. The social change implications of this study are that understanding human embryology promotes peace leadership, considering that the consequentiality of embryo extermination can serve as a deterrent for violence on embryos.

Keywords: consequentiality, Homo sapiens, neo-Newtonians, violence

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Authors: Shao-Di Feng, Von-Wun Soo

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To generate symbolic music with specific emotions is a challenging task due to symbolic music datasets that have emotion labels are scarce and incomplete. This research aims to generate more refined emotions based on the training datasets that are only labeled with four quadrants in Russel’s 2D emotion model. We focus on the theory of Music Fadernet and map arousal and valence to the low-level attributes, and build a symbolic music generation model by combining transformer and GM-VAE. We adopt an in-attention mechanism for the model and improve it by allowing modulation by conditional information. And we show the music generation model could control the generation of music according to the emotions specified by users in terms of high-level linguistic expression and by manipulating their corresponding low-level musical attributes. Finally, we evaluate the model performance using a pre-trained emotion classifier against a pop piano midi dataset called EMOPIA, and by subjective listening evaluation, we demonstrate that the model could generate music with more refined emotions correctly.

Keywords: music generation, music emotion controlling, deep learning, semi-supervised learning

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Authors: Mputu Ngandu Simon

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Culture and religion are two of the most significant markers of an individual or group's identity. Religion finds its expression in a given culture, and culture is the costume in which a religion is dressed. In other words, there is a crucial relationship between religion and culture which should not be ignored. On the one hand, religion influences the way in which a culture is consumed. A person's consumption of a certain cultural practice is influenced by his/her religious identity. On the other hand, cultural identity plays an important role in how a religion is practiced by its adherents. Some cultural practices become more credible when interpreted in religious terms just as religious doctrines and dogmas need cultural interpretation to be understood by a given people in a given context. This relationship goes so deep that sometimes the boundaries between culture and religion become blurred, and people end up mixing religion and culture. In some cases, the two are considered to be one and the same thing. However, despite this apparent sameness, religion and culture are two distinct aspects of identity, and they should always be considered as such. One results from knowledge, while the other has beliefs as its foundation. This essay explores the difference between cultural and religious identity by drawing from existing literature on this topic as a whole before applying that knowledge to two specific case studies: Christianity and Islam in some African and Asian countries.

Keywords: culture, religion, identity, knowledge, belief

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Authors: Hatem Ashur Masoud Shreha

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Aromatase inhibitors administered before sexual differentiation of the gonads in chicken embryo can induce sex reversal in female layer chickens (phenotypic male). To analyze the process of sex reversal, we have followed for several months the changes induced by Fadrozole, a nonsteroidal aromatase inhibitor on morphology of female sex-reversed and female sex-reversed supplemented with L-tyrosine which was previously shown to stimulate release of Gn Rh. Fadrozole (1mg/egg) was injected into eggs on day four of incubation before sex differentiation. phenotypic males and phenotypic males treated with L-tyrosine and males hatched from eggs injected Fadrozole were sacrificed by slaughtering at 16 weeks old and the remaining chicks were sacrificed at 28 weeks old. Both sexes from control chickens were sacrificed at the same age (16 &28 weeks). Hatchability, behavior, body weight, shank length, comb weight, testes weight, blood cells count and wattle weight of sex reversal were tested at 16 and 28 weeks. The results showed that body weight, comb weight, wattles weight and shank length of sex-reversed females were significantly different from control female. Behavior of phenotypic males and phenotypic males fed on L-tyrosine showed aggressive sexual behavior like that of control males and absence of laying behavior. In conclusion our results confirm that Fadrazole injection in eggs before sex differentiation produce a male behavior and morphological index of male in female chicken.

Keywords: sex-reversal, fadrozole, phenotypic male, L-tyrosine

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Authors: Anupriya, Bikramjit Sinfh, Radhay Shyam

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In order to improve mixing phenomena and combustion processes in supersonic flow, the current work has concentrated on identifying the ideal cavity parameters using CFD ANSYS Fluent. Offset ratios (OR) and aft ramp angles () have been manipulated in simulations of several models, but the length-to-depth ratio has remained the same. The length-to-depth ratio of all cavity flows is less than 10, making them all open. Hydrogen fuel was injected into a supersonic air flow with a Mach number of 3.75 using a chamber with a 1 mm diameter and a transverse slot nozzle. The free stream had conditions of a pressure of 1.2 MPa, a temperature of 299K, and a Reynolds number of 2.07x107. This method has the ability to retain a flame since the cavity facilitates rapid mixing of fuel and oxidizer and decreases total pressure losses. The impact of the cavity on combustion efficiency and total pressure loss is discussed, and the results are compared to those of a model without a cavity. Both the mixing qualities and the combustion processes were enhanced in the model with the cavity. The overall pressure loss as well as the effectiveness of the combustion process both increase with the increase in the ramp angle to the rear. When OR is increased, however, resistance to the supersonic flow field is reduced, which has a detrimental effect on both parameters. For a given ramp height, larger pressure losses were observed at steeper ramp angles due to increased eddy-viscous turbulent flow and increased wall drag.

Keywords: total pressure loss, flame holder, supersonic combustion, combustion efficiency, cavity, nozzle

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Authors: Sahar Oudeh, Abbas Javaheri Vayeghan, Mahmood Ahmadi-Hamedani

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This study aimed to investigate the effect of diabetic duration on platelet and platelet indices in streptozotocin-induced diabetic male and female rats. Thirty-two healthy adult Wistar rats (16 females and 16 males) were randomly divided into 4 groups of eight, including 1) control group (4 females and 4 males who did not undergo any treatment until the end of 28 days), 2) 7-day diabetic group (4 females and 4 males who were diabetic for 7 days and were euthanized after 7 days), 3) 14-day diabetic group (4 females and 4 males who were diabetic for 14 days and were euthanized after 14 days), and 28-day diabetic group (4 females and 4 males who were diabetic for 28 days and were euthanized after 28 days). Diabetes was induced by intraperitoneal injection of streptozotocin (65 mg/kg). After induction of diabetes in the groups, blood samples were taken from their hearts after anesthesia, and platelet counts (PLT) and platelet indices were measured by an automatic blood cell counter (Nihon Kohden, Celltac Alpha VET MEK-6550, Japan). Statistical differences among groups were analyzed using one-way analysis of variance (ANOVA) followed by Tukey’s multiple tests. The results of this study showed that PLT and mean platelet volume (MPV) significantly increased in 7 and 14-day diabetic groups compared to the control group, whereas plateletcrit (PCT) and platelet distribution rate (PDW) significantly increased in 14 and 28-day diabetic groups, respectively. Significant differences were observed between female and male rats in PCT and PLT in the 14-day diabetic group and PDW in the 28-day diabetic group. According to the results of this study, measurement and analysis of platelet indices can be used as a method for the early diagnosis of diabetes and its complications.

Keywords: diabetic duration, streptozotocin, female and male rats, platelet indices

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Authors: F. C. Amadi, G. C. Enyi, G. Nasr

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Relative permeabilities are practical factors that are used to correct the single phase Darcy’s law for application to multiphase flow. For effective characterisation of large-scale multiphase flow in hydrocarbon recovery, relative permeability and capillary pressures are used. These parameters are acquired via special core flooding experiments. Special core analysis (SCAL) module of reservoir simulation is applied by engineers for the evaluation of these parameters. But, core flooding experiments in shale core sample are expensive and time consuming before various flow assumptions are achieved for instance Darcy’s law. This makes it imperative for the application of coreflooding simulations in which various analysis of relative permeabilities and capillary pressures of multiphase flow can be carried out efficiently and effectively at a relative pace. This paper presents a Sendra software simulation of core flooding to achieve to relative permeabilities and capillary pressures using different correlations. The approach used in this study was three steps. The first step, the basic petrophysical parameters of Marcellus shale sample such as porosity was determined using laboratory techniques. Secondly, core flooding was simulated for particular scenario of injection using different correlations. And thirdly the best fit correlations for the estimation of relative permeability and capillary pressure was obtained. This research approach saves cost and time and very reliable in the computation of relative permeability and capillary pressures at steady or unsteady state, drainage or imbibition processes in oil and gas industry when compared to other methods.

Keywords: relative permeabilty, porosity, 1-D black oil simulator, capillary pressures

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Authors: David Loh, Wan Chee Wai, Pei Nan, Chen Zhe

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To increase the conveyance capacity to Western Singapore and to meet Singapore’s long-term water needs in a more cost-effective manner, four new transmission pipelines consisting of two 2200 mm diameter water pipes and two 1200mm diameter water pipes will be needed by 2024 to convey water from a Water Reclamation Plant to existing networks in the west region of Singapore. Out of the several possible routes studied, the most cost-effective and technically feasible route was selected to lay the proposed 1.6km-long pipelines that cross a channel via a 6m diameter subsea tunnel. This paper outlines the challenges the team faced throughout the project thus far. It also examined the difficulties such as (1) construction of a 56m-deep launching shaft near a highly sensitive 700mm diameter Gas Transmission Pipeline (GTP) and at a location with high groundwater; (2) manpower and supply disruptions caused by the COVID-19 pandemic situation.

Keywords: underwater tunnel, subsea engineering, subsea tunnel construction, waterpipe construction

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Authors: Abraham Kuruvilla

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Since the inception of Christianity, one of the most important precepts has been that of the ‘word becoming flesh.’ Incarnation, as we understand it, is that the ‘word became flesh.’ As we know, it is a commonly held understanding that the concept of Logos was borrowed from the Greek religion. Such understanding has dominated our thought process. This is problematic as it does not draw out the deep roots of Logos. The understanding of Logos also existed in religion such as Hinduism. For the Hindu faith, the understanding of Shabd is pivotal. It could be arguably equated with the understanding of the Logos. The paper looks into the connection of the primal Christian doctrine of the Logos with that of the Hindu understanding of Shabd. The methodology of the paper would be a comparative theological analysis with the New Testament understanding of the Logos with that of the understanding of Shabd as perceived in the different Vedas of the Hindu faith. The paper would come to the conclusion that there is a conceptual connectivity between Logos and the Shabd. As such the understanding of Logos cannot just be attributed to the Greek understanding of Logos, but rather it predates the Greek understanding of Logos by being connected to the Hindu understanding of Shabd. Accordingly, such comparison brings out the implication for a constructive dialogue between Christianity and the Hindu faith.

Keywords: Christianity, Hinudism, Logos, Shabd

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Authors: Muhammad Ahnaf Zahin, Yaw Adu-Gyamfi

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Bus transit is a crucial component of transportation networks, especially in urban areas. Any intelligent transportation system must have accurate real-time information on bus travel times since it minimizes waiting times for passengers at different stations along a route, improves service reliability, and significantly optimizes travel patterns. Bus agencies must enhance the quality of their information service to serve their passengers better and draw in more travelers since people waiting at bus stops are frequently anxious about when the bus will arrive at their starting point and when it will reach their destination. For solving this issue, different models have been developed for predicting bus travel times recently, but most of them are focused on smaller road networks due to their relatively subpar performance in high-density urban areas on a vast network. This paper develops a deep learning-based architecture using a single-step multi-station forecasting approach to predict average bus travel times for numerous routes, stops, and trips on a large-scale network using heterogeneous bus transit data collected from the GTFS database. Over one week, data was gathered from multiple bus routes in Saint Louis, Missouri. In this study, Gated Recurrent Unit (GRU) neural network was followed to predict the mean vehicle travel times for different hours of the day for multiple stations along multiple routes. Historical time steps and prediction horizon were set up to 5 and 1, respectively, which means that five hours of historical average travel time data were used to predict average travel time for the following hour. The spatial and temporal information and the historical average travel times were captured from the dataset for model input parameters. As adjacency matrices for the spatial input parameters, the station distances and sequence numbers were used, and the time of day (hour) was considered for the temporal inputs. Other inputs, including volatility information such as standard deviation and variance of journey durations, were also included in the model to make it more robust. The model's performance was evaluated based on a metric called mean absolute percentage error (MAPE). The observed prediction errors for various routes, trips, and stations remained consistent throughout the day. The results showed that the developed model could predict travel times more accurately during peak traffic hours, having a MAPE of around 14%, and performed less accurately during the latter part of the day. In the context of a complicated transportation network in high-density urban areas, the model showed its applicability for real-time travel time prediction of public transportation and ensured the high quality of the predictions generated by the model.

Keywords: gated recurrent unit, mean absolute percentage error, single-step forecasting, travel time prediction.

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Authors: L. Bikulciene, E. Venskaityte, G. Jarusevicius

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Non-stationary and nonlinear signals generated by living complex systems defy traditional mechanistic approaches, which are based on homeostasis. Previous our studies have shown that the evaluation of the interactions of physiological signals by using special analysis methods is suitable for observation of physiological processes. It is demonstrated the possibility of using deep physiological model, based interpretation of the changes of the human body’s functional states combined with an application of the analytical method based on matrix theory for the physiological signals analysis, which was applied on high risk cardiac patients. It is shown that evaluation of cardiac signals interactions show peculiar for each individual functional changes at the onset of hemodynamic restoration procedure. Therefore we suggest that the alterations of functional state of the body, after patients overcome surgery can be complemented by the data received from the suggested approach of the evaluation of functional variables interactions.

Keywords: cardiac diseases, complex systems theory, ECG analysis, matrix analysis

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Authors: Habab Ahmed Hassan Abuzeid

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Organizations are social systems. If one wishes to work in them or to manage them, it is necessary to understand how they operate. Organizations combine science and people–technology and humanity. Unless we have qualified people to design and implement, techniques alone will not produce desirable results. Human behavior in organizations is rather unpredictable. It is unpredictable because it arises from people’s deep-seated needs and value systems. However, it can be partially understood in terms of the framework of behavioral science, management and other disciplines. There is no idealistic solution to organizational problems. All that can be done is to increase our understanding and skills so that human relations at work can be enhanced. In this paper, we consider management of organization behavior utilizing human resources. Study the elements of organization behavior, the effectiveness of mechanism to enhance staff relationships. Many approaches could be applied for healthy organizational environment, it’s highlighted more details in this paper. Organization behavior can raise the employees’ engagement, loyalty and commitment; to accomplish the goal.

Keywords: environment, engagement, human resources, organization behavior

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Authors: Abdelkader Soumaya, Aymen Arfaoui, Noureddine Ben Ayed, Ali Kadri

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The Chotts belt represents the southernmost folded structure in the Tunisian Atlas domain. It is dominated by inherited deep extensional E-W trending fault zones, which are reactivated as strike-slip faults during the Cenozoic compression. By examining the geological maps at different scales and based on the fieldwork data, we propose new structural interpretations for the geometries and fault kinematics in the Chotts chain. A set of ENE-WSW right-lateral en echelon folds, with curved shapes and steeply inclined southern limbs, is visible in the map view of this belt. These asymmetric tight anticlines are affected by E-W trending fault segments linked by local bends and stepovers. The revealed kinematic indicators along one of these E-W striated faults (Tafferna segment), such as breccias and gently inclined slickenlines (N094, 80N, 15°W pitch angles), show direct evidence of dextral strike-slip movement. The calculated stress tensors from corresponding faults slip data reveal an overall strike-slip tectonic regime with reverse component and NW-trending sub-horizontal σ1 axis ranking between N130 to N150. From west to east, we distinguished several types of structures along the segmented dextral fault system of the Chotts Range. The NE-SW striking fold-thrust belt (~25 km-long) between two continuously linked E-W fault segments (NW of Tozeur town) has been suggested as a local restraining bend. The central part of the Chotts chain is occupied by the ENE-striking Ksar Asker anticlines (Taferna, Torrich, and Sif Laham), which are truncated by a set of E-W strike-slip fault segments. Further east, the fault segments of Hachichina and Sif Laham connected across the NW-verging asymmetric fold-thrust system of Bir Oum Ali, which can be interpreted as a left-stepping contractional bend (~20 km-long). The oriental part of the Chotts belt corresponds to an array of subparallel E-W oriented fault segments (i.e., Beidha, Bouloufa, El Haidoudi-Zemlet El Beidha) with similar lengths (around 10 km). Each of these individual separated segments is associated with curved ENE-trending en echelon right-stepping anticlines. These folds are affected by a set of conjugate R and R′ shear-type faults indicating a dextral strike-lip motion. In addition, the relay zones between these E-W overstepping fault segments define local releasing stepovers dominated by NW-SE subsidiary faults. Finally, the Chotts chain provides well-exposed examples of strike-slip tectonics along E-W distributed fault segments. Each fault zone shows a typical strike-slip architecture, including parallel fault segments connecting via local stepovers or bends. Our new structural interpretations for this region reveal a great influence of the E-W deep fault segments on regional tectonic deformations and stress field during the Cenozoic shortening.

Keywords: chotts belt, tunisian atlas, strike-slip fault, stepovers, fault segments

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Authors: Donya Ashtiani Haghighi, Amirali Baniasadi

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Coronavirus (COVID-19) disease has spread abruptly all over the world since the end of 2019. Computed tomography (CT) scans and X-ray images are used to detect this disease. Different Deep Neural Network (DNN)-based diagnosis solutions have been developed, mainly based on Convolutional Neural Networks (CNNs), to accelerate the identification of COVID-19 cases. However, CNNs lose important information in intermediate layers and require large datasets. In this paper, Capsule Network (CapsNet) is used. Capsule Network performs better than CNNs for small datasets. Accuracy of 0.9885, f1-score of 0.9883, precision of 0.9859, recall of 0.9908, and Area Under the Curve (AUC) of 0.9948 are achieved on the Capsule-based framework with hyperparameter tuning. Moreover, different dropout rates are investigated to decrease overfitting. Accordingly, a dropout rate of 0.1 shows the best results. Finally, we remove one convolution layer and decrease the number of trainable parameters to 146,752, which is a promising result.

Keywords: capsule network, dropout, hyperparameter tuning, classification

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Authors: S. J. Addinell, T. Richard, B. Evans

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The Deep Exploration Technologies Cooperative Research Centre (DET CRC) is researching and developing a new coiled tubing based greenfields mineral exploration drilling system utilising downhole water powered percussive drill tooling. This new drilling system is aimed at significantly reducing the costs associated with identifying mineral resource deposits beneath deep, barron cover. This system has shown superior rates of penetration in water-rich hard rock formations at depths exceeding 500 meters. Several key challenges exist regarding the deployment and use of these bottom hole assemblies for mineral exploration, and this paper discusses some of the key technical challenges. This paper presents experimental results obtained from the research program during laboratory and field testing of the prototype drilling system. A study of the morphological aspects of the cuttings generated during the percussive drilling process is presented and shows a strong power law relationship for particle size distributions. Several percussive drilling parameters such as RPM, applied fluid pressure and weight on bit have been shown to influence the particle size distributions of the cuttings generated. This has direct influence on other drilling parameters such as flow loop performance, cuttings dewatering, and solids control. Real-time, accurate knowledge of percussive system operating parameters will assist the driller in maximising the efficiency of the drilling process. The applied fluid flow, fluid pressure, and rock properties are known to influence the natural oscillating frequency of the percussive hammer, but this paper also shows that drill bit design, drill bit wear and the applied weight on bit can also influence the oscillation frequency. Due to the changing drilling conditions and therefore changing operating parameters, real-time understanding of the natural operating frequency is paramount to achieving system optimisation. Several techniques to understand the oscillating frequency have been investigated and presented. With a conventional top drive drilling rig, spectral analysis of applied fluid pressure, hydraulic feed force pressure, hold back pressure and drill string vibrations have shown the presence of the operating frequency of the bottom hole tooling. Unfortunately, however, with the implementation of a coiled tubing drilling rig, implementing a positive displacement downhole motor to provide drill bit rotation, these signals are not available for interrogation at the surface and therefore another method must be considered. The investigation and analysis of ground vibrations using geophone sensors, similar to seismic-while-drilling techniques have indicated the presence of the natural oscillating frequency of the percussive hammer. This method is shown to provide a robust technique for the determination of the downhole percussive oscillation frequency when used with a coiled tubing drill rig.

Keywords: cuttings characterization, drilling optimization, oscillation frequency, percussive drilling, spectral analysis

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Authors: H. M. Imam, H. M. Rezk, A. F. Tohamy

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Background: Human umbilical cord blood (HUCB) is considered as a unique source for stem cells. HUCB contain different types of progenitor cells which could differentiate into hepatocytes. Aims: To investigate the potential of rat's liver damage repair using human umbilical cord mesenchymal stem cells (hUCMSCs). We investigated the feasibility for hUCMSCs in recovery from liver damage. Moreover, investigating fibrotic liver repair and using the CCl4-induced model for liver damage in the rat. Methods: Rats were injected with 0.5 ml/kg CCl4 to induce liver damage and progressive liver fibrosis. hUCMSCs were injected into the rats through the tail vein; Stem cells were transplanted at a dose of 1×106 cells/rat after 72 hours of CCl4 injection without receiving any immunosuppressant. After (6 and 8 weeks) of transplantation, blood samples were collected to assess liver functions (ALT, AST, GGT and ALB) and level of Procollagen III as a liver fibrosis marker. In addition, hepatic tissue regeneration was assessed histopathologically and immunohistochemically using antihuman monoclonal antibodies against CD34, CK19 and albumin. Results: Biochemical and histopathological analysis showed significantly increased recovery from liver damage in the transplanted group. In addition, HUCB stem cells transdifferentiated into functional hepatocytes in rats with hepatic injury which results in improving liver structure and function. Conclusion: Our findings suggest that transplantation of hUCMSCs may be a novel therapeutic approach for treating liver fibrosis. Therefore, hUCMSCs are a potential option for treatment of liver cirrhosis.

Keywords: carbon tetra chloride, liver fibrosis, mesenchymal stem cells, rat

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Authors: Aula Khatteb Abu-Liel

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The study investigated the effects of diglossia and orthography on reading in Arabic, manipulating reading in Spoken Arabic (SA), using Arabizi, in which it is written using Latin letters on computers/phones, and the two forms of the conventional written form Modern Standard Arabic (MSA): vowelled (shallow) and unvowelled (deep). 77 skilled readers in 8th grade performed oral reading of single words and narrative and expository texts, and silent reading comprehension of both genres of text. Oral reading and comprehension revealed different patterns. Single words and texts were read faster and more accurately in unvoweled MSA, slowest and least accurately in vowelled MSA, and in-between in Arabizi. Comprehension was highest for vowelled MSA. Narrative texts were better than expository texts in Arabizi with the opposite pattern in MSA. The results suggest that frequency of the type of texts and the way in which phonology is encoded affect skilled reading.

Keywords: Arabic, Arabize, computer mediated communication, diglossia, modern standard Arabic

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Authors: Lalit Kishore, Randhir Singh

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Diabetic nephropathy (DN) is the major cause of morbidity among diabetic patients. In this study, the effect of Bacopa monnieri Linn. (Brahmi, BM), was studied in a Streptozotocin (STZ)-induced experimental rat model of DN. Diabetic nephropathy was induced in Male Wistar rats (body weight- 300± 10 gms) by single intra-peritoneal injection of STZ (45mg/kg, i.p.) after 15 min of Nicotinamide (230 mg/kg) administration. Different doses of alcoholic extract i.e. 100, 200 and 400 mg/kg was given for 45 days by oral gavage after induction of DN. Blood glucose level, serum insulin, glycosylated haemoglobin, renal parameters (serum urea, uric acid, creatinine and BUN) and lipid profile (total cholesterol, triglycerides, HDL, LDL and VLDL levels) were measured. Concentration of thiobarbituric acid reactive species (TBARS) and levels of antioxidant enzymes of reduced glutathione (GSH), superoxide dismutase (SOD), and catalase (CAT) were evaluated in the kidney, liver and pancreas. At the end of treatment period the alcoholic extract of BM reduced the elevated level of blood glucose, serum insulin, renal parameters, lipid levels, TBARS, AGE’s in kidney and significantly increased body weight, HDL and antioxidant enzymes in dose dependent manner as compared to diabetic control animals. These results suggested the BM possesses significant renoprotective activity.

Keywords: AGE's, lipid profile, oxidative stress, renal parameters

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Authors: Sanjukta Badhai, Durga Barik, Bairagi C. Mallick

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In the present study, Beta-Sitosterol in Lawsonia methanolic leaf extract embedded in controlled release nanocomposite was prepared and evaluated for in vivo anticancer efficacy in dimethyl hydrazine (DMH) induced colon cancer. In the present study, colon cancer was induced by s.c injection of DMH (20 mg/kg b.wt) for 15 weeks. The animals were divided into five groups as follows control, DMH alone, DMH and Beta Sitosterol nanocomposite (50mg/kg), DMH and Beta Sitosterol nanocomposite (100 mg/kg) and DMH and Standard Silymarin (100mg/kg) and the treatment was carried out for 15 weeks. At the end of the study period, the blood was withdrawn, and serum was separated for haematological, biochemical analysis and tumor markers. Further, the colonic tissue was removed for the estimation of antioxidants and histopathological analysis. The results of the study displays that DMH intoxication elicits altered haematological parameters (RBC,WBC, and Hb), elevated lipid peroxidation and decreased antioxidants level (SOD, CAT, GPX, GST and GSH), elevated lipid profiles (cholesterol and triglycerides), tumor markers (CEA and AFP) and altered colonic tissue histology. Meanwhile, treatment with Beta Sitosterol nanocomposites significantly restored the altered biochemicals parameters in DMH induced colon cancer mediated by its anticancer efficacy. Further, Beta Sitosterol nanocomposite (100 mg/kg) showed marked efficacy.

Keywords: nanocomposites, herbal formulation, henna, beta sitosterol, colon cancer, dimethyl hydrazine, antioxidant, lipid peroxidation

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Authors: Avinoam Rabinovich

Abstract:

CO₂ geological storage is a proven technology for reducing anthropogenic carbon emissions, which is paramount for achieving the ambitious net zero emissions goal. Core flooding experiments are an important step in any CO₂ storage project, allowing us to gain information on the flow of CO₂ and brine in the porous rock extracted from the reservoir. This information is important for understanding basic mechanisms related to CO₂ geological storage as well as for reservoir modeling, which is an integral part of a field project. In this work, a different method for constructing accurate models of CO₂-brine core flooding will be presented. Results for synthetic cases and real experiments will be shown and compared with numerical models to exhibit their predictive capabilities. Furthermore, the various mechanisms which impact the CO₂ distribution and trapping in the rock samples will be discussed, and examples from models and experiments will be provided. The new method entails solving an inverse problem to obtain a three-dimensional permeability distribution which, along with the relative permeability and capillary pressure functions, constitutes a model of the flow experiments. The model is more accurate when data from a number of experiments are combined to solve the inverse problem. This model can then be used to test various other injection flow rates and fluid fractions which have not been tested in experiments. The models can also be used to bridge the gap between small-scale capillary heterogeneity effects (sub-core and core scale) and large-scale (reservoir scale) effects, known as the upscaling problem.

Keywords: CO₂ geological storage, residual trapping, capillary heterogeneity, core flooding, CO₂-brine flow

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Authors: Chungkuk Jin, Moohyun Kim, Woo Chul Chung

Abstract:

This paper presents global performance and dynamic behaviors of a discrete-pontoon-type floating bridge with mooring lines in time domain under wind and wave excitations. The structure is designed for long-distance and deep-water crossing and consists of the girder, columns, pontoons, and mooring lines. Their functionality and behaviors are investigated by using elastic-floater/mooring fully-coupled dynamic simulation computer program. Dynamic wind, first- and second-order wave forces, and current loads are considered as environmental loads. Girder’s dynamic responses and mooring tensions are analyzed under different analysis methods and environmental conditions. Girder’s lateral responses are highly influenced by the second-order wave and wind loads while the first-order wave load mainly influences its vertical responses.

Keywords: floating bridge, mooring line, pontoon, wave excitation

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Authors: Jiaying Zhang, Xin Mu, Chang Ni, Jeff L. Zhang

Abstract:

Magnetic resonance elastography (MRE) non-invasively assesses tissue elastic properties, such as shear modulus, by measuring tissue’s displacement in response to mechanical waves. The estimated metrics on tissue elasticity or stiffness have been shown to be valuable for monitoring physiologic or pathophysiologic status of tissue, such as a tumor or fatty liver. To quantify tissue shear modulus from MRE-acquired displacements (essentially an inverse problem), multiple approaches have been proposed, including Local Frequency Estimation (LFE) and Direct Inversion (DI). However, one common problem with these methods is that the estimates are severely noise-sensitive due to either the inverse-problem nature or noise propagation in the pixel-by-pixel process. With the advent of deep learning (DL) and its promise in solving inverse problems, a few groups in the field of MRE have explored the feasibility of using DL methods for quantifying shear modulus from MRE data. Most of the groups chose to use real MRE data for DL model training and to cut training images into smaller patches, which enriches feature characteristics of training data but inevitably increases computation time and results in outcomes with patched patterns. In this study, simulated wave images generated by Finite Differential Time Domain (FDTD) simulation are used for network training, and U-Net is used to extract features from each training image without cutting it into patches. The use of simulated data for model training has the flexibility of customizing training datasets to match specific applications. The proposed method aimed to estimate tissue shear modulus from MRE data with high robustness to noise and high model-training efficiency. Specifically, a set of 3000 maps of shear modulus (with a range of 1 kPa to 15 kPa) containing randomly positioned objects were simulated, and their corresponding wave images were generated. The two types of data were fed into the training of a U-Net model as its output and input, respectively. For an independently simulated set of 1000 images, the performance of the proposed method against DI and LFE was compared by the relative errors (root mean square error or RMSE divided by averaged shear modulus) between the true shear modulus map and the estimated ones. The results showed that the estimated shear modulus by the proposed method achieved a relative error of 4.91%±0.66%, substantially lower than 78.20%±1.11% by LFE. Using simulated data, the proposed method significantly outperformed LFE and DI in resilience to increasing noise levels and in resolving fine changes of shear modulus. The feasibility of the proposed method was also tested on MRE data acquired from phantoms and from human calf muscles, resulting in maps of shear modulus with low noise. In future work, the method’s performance on phantom and its repeatability on human data will be tested in a more quantitative manner. In conclusion, the proposed method showed much promise in quantifying tissue shear modulus from MRE with high robustness and efficiency.

Keywords: deep learning, magnetic resonance elastography, magnetic resonance imaging, shear modulus estimation

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Authors: Zeev Wiesman, Paula Berman, Nitzan Meiri, Charles Linder

Abstract:

Supramolecular chemistry refers to the domain of chemistry beyond that of molecules and focuses on the chemical systems made up of a discrete number of assembled molecular sub units or components. Biodiesel components self arrangements is closely related/affect their physical properties in combustion systems and emission. Due to technological difficulties, knowledge regarding the molecular packing of FAMEs (biodiesel) in the liquid phase is limited. Spectral tools such as X-ray and NMR are known to provide evidences related to molecular structure organization. Recently, it was reported by our research group that using 1H Time Domain NMR methodology based on relaxation time and self diffusion coefficients, FAMEs clusters with different motilities can be accurately studied in the liquid phase. Head to head dimarization with quasi-smectic clusters organization, based on molecular motion analysis, was clearly demonstrated. These findings about the assembly/packing of the FAME components are directly associated with fluidity/viscosity of the biodiesel. Furthermore, these findings may provide information of micro/nano-particles that are formed in the delivery and injection system of various combustion systems (affected by thermodynamic conditions). Various relevant parameters to combustion such as: distillation/Liquid Gas phase transition, cetane number/ignition delay, shoot, oxidation/NOX emission maybe predicted. These data may open the window for further optimization of FAME/diesel mixture in terms of combustion and emission.

Keywords: supermolecular chemistry, FAMEs, liquid phase, fluidity, LF-NMR

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Authors: Chastiti Mediafira Wulolo

Abstract:

Our Eyes is a cooperation pact in the field of intelligence information exchanges initiated by the Indonesian Ministry of Defense, which has been signed by Indonesia, Philippines, Malaysia, Brunei Darussalam, Thailand, and Singapore. This cooperation mostly engages the military acts as a central role, but this pact still requires the involvement of various parties such as police and other linear institution. This paper will use a qualitative content analysis method by doing some deep analyzing the pattern of cooperation itself. As the implementation of translantic counter-terrorism cooperation, this research will address how the role of Our Eyes can be optimized as a form of government’s response towards the contemporary threat in the Dynamics of Strategic Environmental Security in the Asia Pacific Region. Optimizing the role of this cooperation will also acquire from the previous counter-terrorism cooperation in ASEAN region, so it expects that Our Eyes collaboration can be the most effective cooperation in overcoming terrorism issues in ASEAN, eventually in Asia Pacific.

Keywords: our eyes, Defense Ministry of Indonesia, ASEAN, counter-terrorism

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Authors: David Tena-Gago, Jose M. Alcaraz Calero, Qi Wang

Abstract:

The evolution and integration of automated vehicles have become more and more tangible in recent years. State-of-the-art technological advances in the field of camera-based Artificial Intelligence (AI) and computer vision greatly favor the performance and reliability of the Advanced Driver Assistance System (ADAS), leading to a greater knowledge of vehicular operation and resembling human behavior. However, the exclusive use of this technology still seems insufficient to control vehicular operation at 100%. To reveal the degree of accuracy of the current camera-based automated driving AI modules, this paper studies the structure and behavior of one of the main solutions in a controlled testing environment. The results obtained clearly outline the lack of reliability when using exclusively the AI model in the perception stage, thereby entailing using additional complementary sensors to improve its safety and performance.

Keywords: accuracy assessment, AI-driven mobility, artificial intelligence, automated vehicles

Procedia PDF Downloads 111