Search results for: dynamic network flow

Authors: Maha Soltan, Amal Z. Hassan, Howaida I. Abd-Alla, Atef G. Hanna

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Two naturally known cardenolides; acovenoside A and acobioside A were isolated from the Egyptian cultivar; Acokanthera spectabilis leaves. It is an ornamental and poisonous plant that has been traditionally claimed for their medicinal properties against infectious microbes, killing worms and curing some inflammations at little amounts. We examined the growth inhibition effects of both cardenolides against four types of human cancer cell lines using Sulphorhodamine B assay. In addition, the clonogenic assay was also performed for testing the growth inhibiting power of the isolated compounds. An in vitro mechanistic investigation was further accomplished against hepatocellular carcinoma HepG2 cell line. Microscopic examination, colorimetric ELISA and flow cytometry techniques were our tools of proving at least part of the anticancer pathway of the tested compounds. Both compounds were able to inhibit the growth of 4 human cancer cell lines at less than 100 nM. In addition, they were able to activate the executioner Caspase-3 and apoptosis was then induced as a consequence of cell growth arrest at G2/M. An attention must be payed to those bioactive agents particularly when giving their activity against cancer cells at considerable small values while presenting safe therapeutic margins as indicated by literature.

Keywords: anticancer, cardenolides, Caspase-3, apoptosis

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Authors: Kwok W. Mui, Ling T. Wong, F. Xiao, Chin T. Cheung, Ho C. Yu

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This study addresses a concept of the Sustainable Building Environmental Model (SBEM) developed to optimize energy consumption in air conditioning and ventilation (ACV) systems without any deterioration of indoor environmental quality (IEQ). The SBEM incorporates two main components: an adaptive comfort temperature control module (ACT) and a new carbon dioxide demand control module (nDCV). These two modules take an innovative approach to maintain satisfaction of the Indoor Environmental Quality (IEQ) with optimum energy consumption, they provide a rational basis of effective control. A total of 2133 sets of measurement data of indoor air temperature (Ta), relative humidity (Rh) and carbon dioxide concentration (CO2) were conducted in some Hong Kong offices to investigate the potential of integrating the SBEM. A simulation was used to evaluate the dynamic performance of the energy and air conditioning system with the integration of the SBEM in an air-conditioned building. It allows us make a clear picture of the control strategies and performed any pre-tuned of controllers before utilized in real systems. With the integration of SBEM, it was able to save up to 12.3% in simulation and 15% in field measurement of overall electricity consumption, and maintain the average carbon dioxide concentration within 1000ppm and occupant dissatisfaction in 20%.

Keywords: sustainable building environmental model (SBEM), adaptive comfort temperature (ACT), new demand control ventilation (nDCV), energy saving

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Authors: Hadeer R. M. Tawfik, Rania A. K. Birry, Amani A. Saad

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Eyes are considered to be the most sensitive and important organ for human being. Thus, any eye disorder will affect the patient in all aspects of life. Cataract is one of those eye disorders that lead to blindness if not treated correctly and quickly. This paper demonstrates a model for automatic detection, classification, and grading of cataracts based on image processing techniques and artificial intelligence. The proposed system is developed to ease the cataract diagnosis process for both ophthalmologists and patients. The wavelet transform combined with 2D Log Gabor Wavelet transform was used as feature extraction techniques for a dataset of 120 eye images followed by a classification process that classified the image set into three classes; normal, early, and advanced stage. A comparison between the two used classifiers, the support vector machine SVM and the artificial neural network ANN were done for the same dataset of 120 eye images. It was concluded that SVM gave better results than ANN. SVM success rate result was 96.8% accuracy where ANN success rate result was 92.3% accuracy.

Keywords: cataract, classification, detection, feature extraction, grading, log-gabor, neural networks, support vector machines, wavelet

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Authors: Madhu Gupta, G. P. Agrawa, Suresh P. Vyas

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Certain tumor cells overexpress a membrane-spanning molecule aminopeptidase N (CD13) isoform, which is the receptor for peptides containing the NGR motif. NGR-modified Docetaxel (DTX)-loaded PEG-b-PLGA polymeric nanoparticles (cNGR-DNB-NPs) were developed and evaluated for their in vitro potential in HT-1080 cell line. The cNGR-DNB-NPs containing particles were about 148 nm in diameter with spherical shape and high encapsulation efficiency. Cellular uptake was confirmed both qualitatively and quantitatively by Confocal Laser Scanning Microscopy (CLSM) and flow cytometry. Both quantitatively and qualitatively results confirmed the NGR conjugated nanoparticles revealed the higher uptake of nanoparticles by CD13-overexpressed tumor cells. Free NGR inhibited the cellular uptake of cNGR-DNB-NPs, revealing the mechanism of receptor mediated endocytosis. In vitro cytotoxicity studies demonstrated that cNGR-DNB-NPs, formulation was more cytotoxic than unconjugated one, which were consistent well with the observation of cellular uptake. Hence, the selective delivery of cNGR-DNB-NPs formulation in CD13-overexpressing tumors represents a potential approach for the design of nanocarrier-based dual targeted delivery systems for targeting the tumor cells and vasculature.

Keywords: solid Tumor, docetaxel, targeting, NGR ligand

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Authors: Hexiong Liu

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Powder metallurgy is the optimal method for the consolidation and preparation of W(Mo) alloys, which exhibit excellent application prospects at high temperatures. The properties of W(Mo) alloys are closely related to the sintered density. However, controlling the sintered density and porosity of these alloys is still challenging. In the past, the regulation methods mainly focused on time-consuming and costly trial-and-error experiments. In this study, the sintering data for more than a dozen W(Mo) alloys constituted a small-scale dataset, including both solid and liquid phases of sintering. Furthermore, simple descriptors were used to predict the sintered density of W(Mo) alloys based on the descriptor selection strategy and machine learning method (ML), where the ML algorithm included the least absolute shrinkage and selection operator (Lasso) regression, k-nearest neighbor (k-NN), random forest (RF), and multi-layer perceptron (MLP). The results showed that the interpretable descriptors extracted by our proposed selection strategy and the MLP neural network achieved a high prediction accuracy (R>0.950). By further predicting the sintered density of W(Mo) alloys using different sintering processes, the error between the predicted and experimental values was less than 0.063, confirming the application potential of the model.

Keywords: sintered density, machine learning, interpretable descriptors, W(Mo) alloy

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Authors: Djeamsly Salomon

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Background: Epidemiological surveillance is a dynamic national system used to observe all aspects of the evolution of priority health problems, through: collection, analysis, systematic interpretation of information, and dissemination of results with necessary recommendations. The study was conducted to assess the mandatory disease surveillance system in the Sud Department. Methods: A study was conducted from March to May 2021 with key players involved in surveillance at the level of health institutions in the department . The CDC's 2021 updated guideline was used to evaluate the system. We collected information about the operation, attributes, and usefulness of the surveillance system using interviewer-administered questionnaires. Epi-Info7.2 and Excel 2016 were used to generate the mean, frequencies and proportions. Results: Of 30 participants, 23 (77%) were women. The average age was 39 years[30-56]. 25 (83%) had training in epidemiological surveillance. (50%) of the forms checked were signed by the supervisor. Collection tools were available at (80%). Knowledge of at least 7 notifiable diseases was high (100%). Among the respondents, 29 declared that the collection tools were simple, 27 had already filled in a notification form. The maximum time taken to fill out a form was 10 minutes. The feedback between the different levels was done at (60%). Conclusion: The surveillance system is useful, simple, acceptable, representative, flexible, stable and responsive. The data generated was of high quality. However, it is threatened by the lack of supervision of sentinel sites, lack of investigation and weak feedback. This evaluation demonstrated the urgent need to improve supervision in the sites and to feedback information. Strengthen epidemiological surveillance.

Keywords: evaluation, notifiable diseases, surveillance, system

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Authors: Tarang Varmora, Krupa Shah, Karan Patel

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Environmental pollution and shortage of conventional fuel are the main concerns in the transportation sector. Most of the vehicles use an internal combustion engine (ICE), powered by gasoline fuels. This results into emission of toxic gases. Hybrid electric vehicle (HEV) powered by electric machine and ICE is capable of reducing emission of toxic gases and fuel consumption. However to build HEV, it is required to accommodate motor and batteries in the vehicle along with engine and fuel tank. Thus, overall weight of the vehicle increases. To improve the fuel economy and acceleration, the weight of the HEV can be minimized. In this paper, the design methodology to reduce the weight of the hybrid racing car is proposed. To this end, the chassis design is optimized. Further, attempt is made to obtain the maximum strength with minimum material weight. The best configuration out of the three main configurations such as series, parallel and the dual-mode (series-parallel) is chosen. Moreover, the most suitable type of motor, battery, braking system, steering system and suspension system are identified. The racing car is designed and analyzed in the simulating software. The safety of the vehicle is assured by performing static and dynamic analysis on the chassis frame. From the results, it is observed that, the weight of the racing car is reduced by 11 % without compromising on safety and cost. It is believed that the proposed design and specifications can be implemented practically for manufacturing hybrid racing car.

Keywords: design optimization, hybrid racing car, simulation, vehicle, weight reduction

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Authors: Ahmed M. Ashteyat

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Artificial Neural Network (ANN) models have been widely used in material modeling, inter-correlations, as well as behavior and trend predictions when the nonlinear relationship between system parameters cannot be quantified explicitly and mathematically. In this paper, ANN was used to predict the residual modulus of elasticity (RME) of self compacted concrete (SCC) damaged by heat. The ANN model was built, trained, tested and validated using a total of 112 experimental data sets, gathered from available literature. The data used in model development included temperature, relative humidity conditions, mix proportions, filler types, and fiber type. The result of ANN training, testing, and validation indicated that the RME of SCC, exposed to different temperature and relative humidity levels, could be predicted accurately with ANN techniques. The reliability between the predicated outputs and the actual experimental data was 99%. This show that ANN has strong potential as a feasible tool for predicting residual elastic modulus of SCC damaged by heat within the range of input parameter. The ANN model could be used to estimate the RME of SCC, as a rapid inexpensive substitute for the much more complicated and time consuming direct measurement of the RME of SCC.

Keywords: residual modulus of elasticity, artificial neural networks, self compacted-concrete, material modeling

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Authors: Meftah M. Elsaraiti, Samir Milad Elsariti

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Steel slag is a by-product of the steel production and utilizing it potentially as new or substitute materials in road construction is advantageous regarding cost reduction and flattening improvement or properties pavement. Ease of use, low cost, and resource availability are some of few advantages of reuse and recycling of steel slag. This study assesses the use of Steel Slag Aggregates (SSA) as an alternative to natural road building aggregates. This paper discusses the basic characteristics of steel slag based on extensive laboratory tests, and to determine the possibilities of using steel slag in road construction. Samples were taken from the furnaces directly at different times and dates. Moreover, random samples were also taken from the slag field from various areas at different far distances from each other. A necessary analysis was performed through the use of (XRF). Three different percentages of SSA (0, 50 and 100%) were added as an alternative to natural aggregate in hot mix asphalt (HMA) production. The proposed design of the mix was made according to the Marshall mix design. The results of the experiments revealed that the percentages of iron oxide ranged from (9 to 26%) and that the addition of SSA has a significant improvement on HMA properties. It was observed that the Marshall stability obtained in the mix of 100% slag ranged from 600 to 800 N as a minimum, and the flow of Marshall obtained from 2.4 to 3.23 mm and the specification requires from 2 to 4 mm. The results may be showed possibilities to use steel slag as new or substitute materials in road construction in Libya.

Keywords: by-product material, properties, road construction, steel slag

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Authors: Barbara Ballan

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Environmental Justice (EJ) and Environmental Social Governance (ESG) are trending terms used to address the impacts of corporate actions and environmental and social regulations on the people and the planet. ESG is a private governance invention (though increasingly required by public law) that aims to disclose environmental and social criteria while fostering value for businesses. On the other hand, EJ was borne as a social movement that evolved into a regulatory tool employed by EJ advocates and governmental agencies to assess inequalities in environmental impacts and regulations. However, EJ usage is expanding, and private environmental governance in the form of ESG disclosure frameworks is incorporating EJ criteria, indexes, and tools as part of its metric-driven approach. There is an existing tension between (1) the notion of social justice at the heart of the environmental justice movement and (2) the nature of for-profit corporations which generate value by externalizing costs, translated to environmental injustices. This study aims to explore the paradoxical relation of ESG, including EJ criteria, despite their opposing notions, in response to the need for innovative mechanisms to address today’s pressing social and environmental challenges. To that end, this study will evaluate and critically assess the inclusion of EJ in ESG reporting. Furthermore, it identifies gaps in ESG frameworks and proposes the integration of EJ tools to address these deficiencies. This work is intended to help both businesses looking to expand their ESG frameworks and include EJ criteria to inform corporate decisions and assure long-term corporate viability, as well as EJ supporters in understanding the complex dynamic of ESG disclosure for the pursuit of EJ objectives.

Keywords: environmental justice, ESG, sustainability reporting, corporate law, environmental law, social justice

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Authors: Michael Gerges, Ograbe Ahiakwo, Martin Jaeger, Ahmad Asaad

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Recent advances of Building Information Modeling (BIM) especially in the Middle East have increased remarkably. Dubai has been taking a lead on this by making it mandatory for BIM to be adopted for all projects that involve complex architecture designs. This is because BIM is a dynamic process that assists all stakeholders in monitoring the project status throughout different project phases with great transparency. It focuses on utilizing information technology to improve collaboration among project participants during the entire life cycle of the project from the initial design, to the supply chain, resource allocation, construction and all productivity requirements. In view of this trend, the paper examines the extent of applying BIM in the State of Kuwait, by exploring practitioners’ perspectives on BIM, especially their perspectives on main barriers and main advantages. To this end structured interviews were carried out based on questionnaires and with a range of different construction professionals. The results revealed that practitioners perceive improved communication and mitigated project risks by encouraged collaboration between project participants. However, it was also observed that the full implementation of BIM in the State of Kuwait requires concerted efforts to make clients demanding BIM, counteract resistance to change among construction professionals and offer more training for design team members. This paper forms part of an on-going research effort on BIM and its application in the State of Kuwait and it is on this basis that further research on the topic is proposed.

Keywords: building information modeling, BIM, construction industry, Kuwait

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Authors: Tasir Khan, Yejuan Wang

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The study of extreme rainfall events is very important for flood management in river basins and the design of water conservancy infrastructure. Evaluation of quantiles of annual maximum rainfall (AMRF) is required in different environmental fields, agriculture operations, renewable energy sources, climatology, and the design of different structures. Therefore, the annual maximum rainfall (AMRF) was performed at different stations in Pakistan. Multiple probability distributions, log normal (LN), generalized extreme value (GEV), Gumbel (max), and Pearson type3 (P3) were used to find out the most appropriate distributions in different stations. The L moments method was used to evaluate the distribution parameters. Anderson darling test, Kolmogorov- Smirnov test, and chi-square test showed that two distributions, namely GUM (max) and LN, were the best appropriate distributions. The quantile estimate of a multi-parameter PD offers extreme rainfall through a specific location and is therefore important for decision-makers and planners who design and construct different structures. This result provides an indication of these multi-parameter distribution consequences for the study of sites and peak flow prediction and the design of hydrological maps. Therefore, this discovery can support hydraulic structure and flood management.

Keywords: RAMSE, multiple frequency analysis, annual maximum rainfall, L-moments

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Authors: Yakubu Bala Mohammed, Nadire Chavus, Mohammed Bulama

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Generative Pre-trained Transformer (ChatGPT) represents an artificial intelligence (AI) tool capable of swiftly generating comprehensive responses to prompts and follow-up inquiries. This emerging AI tool was introduced in November 2022 by OpenAI firm, an American AI research laboratory, utilizing substantial language models. This present study aims to delve into the potential future consequences of ChatGPT usage in education using AI-based algorithms. The paper will bring forth the likely potential risks of ChatGBT utilization, such as academic integrity concerns, unfair learning assessments, excessive reliance on AI, and dissemination of inaccurate information using four machine learning algorithms: eXtreme-Gradient Boosting (XGBoost), Support vector machine (SVM), Emotional artificial neural network (EANN), and Random forest (RF) would be used to analyze the study collected data due to their robustness. Finally, the findings of the study will assist education stakeholders in understanding the future implications of ChatGPT usage in education and propose solutions and directions for upcoming studies.

Keywords: machine learning, ChatGPT, education, learning, implications

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Authors: Tang Wei, Yang Xiaofeng, Gui Yewei, Du Yanxia

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Complex lifting entry was selected for precise landing performance during the Mars Science Laboratory entry. This study aims to develop the three-dimensional numerical method for precise computation and the surface panel method for rapid engineering prediction. Detailed flow field analysis for Mars exploration mission was performed by carrying on a series of fully three-dimensional Navier-Stokes computations. The static aerodynamic performance was then discussed, including the surface pressure, lift and drag coefficient, lift-to-drag ratio with the numerical and engineering method. Computation results shown that the shock layer is thin because of lower effective specific heat ratio, and that calculated results from both methods agree well with each other, and is consistent with the reference data. Aerodynamic performance analysis shows that CG location determines trim characteristics and pitch stability, and certain radially and axially shift of the CG location can alter the capsule lifting entry performance, which is of vital significance for the aerodynamic configuration des0ign and inner instrument layout of the Mars entry capsule.

Keywords: Mars entry capsule, static aerodynamics, computational fluid dynamics, hypersonic

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Authors: Ambuj Srivastava, Narender Singh

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This paper presents the effect of installation of cylindrical external store on the performance, stability, control and handling qualities of light transport category aircraft. A pair of long cylindrical store was installed symmetrically on either side of the fuselage (port and starboard) ahead of the wing and below the fuselage bottom surface running below pilot and co-pilot window. The cylindrical store was installed as hanging from aircraft surface through specially designed brackets. The adjoining structure was sufficiently reinforced for bearing aerodynamic loads. The length to diameter ratio of long cylindrical store was ~20. Based on academic studies and flow simulation analysis, a considerable detrimental effect on single engine second segment climb performance was found which was later validated through extensive flight testing exercise. The methodology of progressive flight envelope opening was adopted. The certification was sought from Regional airworthiness authorities and for according approval.

Keywords: second segment climb, maximum operating speed, cruise performance (single engine and twin engine), minimum control speed, and additional trim required

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Authors: K. Rusnakova, D. Gerych, M. Stehlik

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Postural stability is a complex process involving actions of biomechanical, motor, sensory and central nervous system components. Numerous joint systems, muscles involved, the complexity of sporting movements and situations require perfect coordination of the body's movement patterns. To adapt to a constantly changing situation in such a dynamic environment as physical performance, optimal input of information from visual, vestibular and somatosensory sensors are needed. Combat soldiers are required to perform physically and mentally demanding tasks in adverse conditions, and poor postural stability has been identified as a risk factor for lower extremity musculoskeletal injury. The aim of this study is to investigate whether some personality traits are related to the performance of static postural stability among soldiers of combat troops. NEO personality inventory (NEO-PI-R) was used to identify personality traits and the Nintendo Wii Balance Board was used to assess static postural stability of soldiers. Postural stability performance was assessed by changes in center of pressure (CoP) and center of gravity (CoG). A posturographic test was performed for 60 s with eyes opened during quiet upright standing. The results showed that facets of neuroticism and conscientiousness personality traits were significantly correlated with measured parameters of CoP and CoG. This study can help for better understanding the relationship between personality traits and static postural stability. The results can be used to optimize the training process at the individual level.

Keywords: neuroticism, conscientiousness, postural stability, combat troops

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Authors: Rebhi A. Damseh, H. M. Duwairi, Benbella A. Shannak

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This work deals with heat and mass transfer by steady laminar boundary layer flow of a Newtonian, viscous fluid over a vertical flat plate with variable surface heat flux embedded in a fluid saturated porous medium in the presence of thermophoresis particle deposition effect. The governing partial differential equations are transformed into no-similar form by using special transformation and solved numerically by using an implicit finite difference method. Many results are obtained and a representative set is displaced graphically to illustrate the influence of the various physical parameters on the wall thermophoresis deposition velocity and concentration profiles. It is found that the increasing of thermophoresis constant or temperature differences enhances heat transfer rates from vertical surfaces and increase wall thermophoresis velocities; this is due to favourable temperature gradients or buoyancy forces. It is also found that the effect of thermophoresis phenomena is more pronounced near pure natural convection heat transfer limit; because this phenomenon is directly a temperature gradient or buoyancy forces dependent. Comparisons with previously published work in the limits are performed and the results are found to be in excellent agreement.

Keywords: thermophoresis, porous medium, variable surface heat flux, heat transfer

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Authors: Sang Beom Kim, Kyung Ju Kim, Myung Hoon Cho, Ji Hoon Kim, Soo Hyung Kim

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In this study, we systematically investigated the effect of nanoscale energetic materials in formulations of aluminum nanoparticles (Al NPs; heat source)/copper oxide nanoparticles (CuO NPs; oxidizer) on the combustion and gas-generating properties of sodium azide microparticles (NaN3 MPs; gas-generating agent) for potential applications in gas generators. The burn rate of the NaN3 MP/CuO NP composite powder was only ~0.3 m/s. However, the addition of Al NPs to the NaN3 MP/CuO NP matrix caused the rates to reach ~5.3 m/s, respectively. In addition, the N2 gas volume flow rate generated by the ignition of the NaN3 MP/CuO NP composite powder was only ~0.6 L/s, which was significantly increased to ~3.9 L/s by adding Al NPs to the NaN3 MP/CuO NP composite powder. This suggested that the highly reactive NPs, with the assistance of CuO NPs, were effective heat-generating sources enabling the complete thermal decomposition of NaN3 MPs upon ignition. Al NPs were highly effective in the gas generators because of the increased reactivity induced by the reduced particle size. Finally, we successfully demonstrated that a homemade airbag with a specific volume of ~140 mL could be rapidly and fully inflated by the thermal activation of nanoscale energetic material-added gas-generating agents (i.e., NaN3 MP/Al NP/CuO NP composites) within the standard time of ~50 ms for airbag inflation.

Keywords: nanoenergetic materials, aluminum nanoparticles, copper oxide nanoparticles, gas generators

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Authors: Mais Haj Qasem, Maen M. Al Assaf, Ali Rodan

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Parallel hybrid storage systems consist of a hierarchy of different storage devices that vary in terms of data reading speed performance. As we ascend in the hierarchy, data reading speed becomes faster. Thus, migrating the application’ important data that will be accessed in the near future to the uppermost level will reduce the application I/O waiting time; hence, reducing its execution elapsed time. In this research, we implement trace-driven two-levels parallel hybrid storage system prototype that consists of HDDs and SSDs. The prototype uses data mining techniques to classify application’ data in order to determine its near future data accesses in parallel with the its on-demand request. The important data (i.e. the data that the application will access in the near future) are continuously migrated to the uppermost level of the hierarchy. Our simulation results show that our data migration approach integrated with data mining techniques reduces the application execution elapsed time when using variety of traces in at least to 22%.

Keywords: hybrid storage system, data mining, recurrent neural network, support vector machine

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Authors: Satpal Singh, Subhash Chander

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An experimental study has been conducted to evaluate the thermal performance of the CNG/air dual flame impinging normally on to a flat surface. The stability limits for the dual flame under both impinging and free conditions have been evaluated to select experimental operating range. Dual flame shape and structure have been explained with direct flame image and schematic diagram indicating modification in recirculation zone in presence of inner flame. Effects of various operating parameters like H/Dh, Re(o), Φ(o), and θ(o) on heat transfer characteristics have been discussed. Inner non-swirling flame Reynolds number (Re(i)) and equivalence ratio (Φ(i)) were kept constant. Heating patterns in the impingement region around the stagnation point have been altered significantly with change in the values of H/Dh, Re(o), Φ(o), and θ(o). The axial flow of inner flame has been notably effected with increase in Re(o). Heating was most favorable near stoichiometeric conditions of the outer swirling flame. However, the effect of change in swirl intensity (expressed in terms of θ(o)) on overall heat transfer efficiency was not as significant as in the case of other parameters. It has been inferred that best performance (higher uniformity and efficiency) of the dual flame impinging on a flat surface can be achieved at moderate value of separation distance (H/Dh of 2-3) and outer swirling flame Reynolds number (Re(o) of 7000-9000) under stoichiometeric conditions.

Keywords: dual flame, heat transfer, impingement, swirling insert, transmission efficiency

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Authors: Muzaffar Iqbal, Essam Ezzeldin, Khalid A. Al-Rashood

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Pomalidomide is a second generation oral immunomodulatory agent, being used for the treatment of multiple myeloma in patients with disease refractory to lenalidomide and bortezomib. In this study, a sensitive UPLC-MS/MS assay was developed and validated for high-throughput determination of pomalidomide in rat plasma using celecoxib as an internal standard (IS). Liquid liquid extraction using dichloromethane as extracting agent was employed to extract pomalidomide and IS from 200 µL of plasma. Chromatographic separation was carried on Acquity BEHTM C18 column (50 × 2.1 mm, 1.7 µm) using an isocratic mobile phase of acetonitrile:10 mM ammonium acetate (80:20, v/v), at a flow rate of 0.250 mL/min. Both pomalidomide and IS were eluted at 0.66 ± 0.03 and 0.80 ± 0.03 min, respectively with a total run time of 1.5 min only. Detection was performed on a triple quadrupole tandem mass spectrometer using electrospray ionization in negative mode. The precursor to product ion transitions of m/z 272.01 → 160.89 for pomalidomide and m/z 380.08 → 316.01 for IS were used to quantify them respectively, using multiple reaction monitoring mode. The developed method was validated according to regulatory guideline for bioanalytical method validation. The linearity in plasma sample was achieved in the concentration range of 0.47–400 ng/mL (r2 ≥ 0.997). The intra and inter-day precision values were ≤ 11.1% (RSD, %) whereas accuracy values ranged from - 6.8 – 8.5% (RE, %). In addition, other validation results were within the acceptance criteria and the method was successfully applied in a pharmacokinetic study of pomalidomide in rats.

Keywords: pomalidomide, pharmacokinetics, LC-MS/MS, celecoxib

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Authors: Moon Moon Devi, Ran Budnik

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The current large area cosmic ray detector surface arrays typically measure only the net flux and arrival-time of the charged particles produced in an extensive air shower (EAS). Measurement of the individual charged particles at a surface array will provide additional distinguishing parameters to identify the primary and to map the very high energy interactions in the upper layers of the atmosphere. In turn, these may probe anomalies in QCD interactions at energies beyond the reach of current accelerators. The recent attempts of studying the individual muon tracks are limited in their expandability to larger arrays and can only probe primary particles with energy up to about 10^15.5 eV. New developments in detector technology allow for a realistic cost of large area detectors, however with limitations on energy resolutions, directional information, and dynamic range. In this study, we perform a simulation study using CORSIKA to combine the energy spectrum and lateral spread of the muons with the longitudinal depth (Xmax) of an EAS initiated by a primary at ultra high energies (10¹⁶ – 10¹⁹) eV. Using proton and iron as the shower primaries, we show that the muon observables and Xmax together can be used to distinguish the primary. This study can be used to design a future detector for the surface array, which will be able to enhance our knowledge of primaries and QCD interactions.

Keywords: ultra high energy extensive air shower, muon tracking, air shower primaries, QCD interactions

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Authors: Masaki Yamaguchi, Daimei Sasayama, Shinsuke Washizuka

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The goal of this study was to examine the possibility of salivary cytokines for the screening of attention deficit hyperactivity disorder (ADHD) in children. We carried out a case-control study, including 19 children with ADHD and 17 healthy children (controls). A multiplex bead array immunoassay was used to conduct a multi-analysis of 27 different salivary cytokines. Six salivary cytokines (interleukin (IL)-1β, IL-8, IL12p70, granulocyte colony-stimulating factor (G-CSF), interferon gamma (IFN-γ), and vascular endothelial growth factor (VEGF)) were significantly associated with the presence of ADHD (p < 0.05). An informative salivary cytokine panel was developed using VEGF by logistic regression analysis (odds ratio: 0.251). Receiver operating characteristic analysis revealed that assessment of a panel using VEGF showed “good” capability for discriminating between ADHD patients and controls (area under the curve: 0.778). ADHD has been hypothesized to be associated with reduced cerebral blood flow in the frontal cortex, due to reduced VEGF levels. Our study highlights the possibility of utilizing differential salivary cytokine levels for point-of-care testing (POCT) of biomarkers in children with ADHD.

Keywords: cytokine, saliva, attention deficit hyperactivity disorder, child

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Authors: Pouya Khaleghi

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Dental implants are a successful treatment modality for restoring both function and aesthetics. Dental implant treatment has predictive results in the replacement of the lost teeth and has a high success rate even in the long term. The most important factor which is responsible for the positive course of implant treatment is the process of osseointegration between the implant structure and the host’s bone tissue. During recent years, many studies have focused on surgical and prosthetic factors, as well as the implant-related factors. However, implant failure still occurs despite the improvements that have led to the increased survival rate of dental implants, which suggests the possible role of some host-related risk factors. Vitamin D is a fat-soluble vitamin regulating calcium and phosphorus metabolism in tissues. The role of vitamin D in bone healing has been under investigation for several years. Vitamin D deficiency has also been associated with impaired and delayed callus formation and fractures healing; however, the role of vitamin D has not been clarified. Therefore, it is extremely important to study the phenomenon of a connection formed between bone tissue and the surface of a titanium implant and find correlations between the 25- hydroxycholecalciferol concentration in blood serum and the course of osseointegration. Because the processes of bone remodeling are very dynamic in the period of actual osseointegration, it is necessary to obtain the correct concentration of vitamin D3 metabolites in blood serum. In conclusion, the correct level of 25-hydroxycholecalciferol on the day of surgery and vitamin D deficiency treatment have a significant influence on the increase in the bone level at the implant site during the process of osseointegration assessed radiologically.

Keywords: implant, osseointegration, vitamin d, dental

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Authors: Nadjoua Bourmatte, Hacène Houari

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Glass has been indispensable to men’s life due to its properties, including pliability to take any shape with ease, bright surface, resistance to abrasion, reasonable safety and durability. Waste glass creates serious environmental problems, mainly due to the inconsistency of waste glass streams. With increasing environmental pressure to reduce solid waste and to recycle as much as possible, the concrete industry has adopted a number of methods to achieve this goal. The object of this research work is to study the effect of using recycled glass waste, as a partial replacement of fine aggregate, on the fresh and hardened properties of concrete. Recycled glass was used to replace fine aggregate in proportions of 0%, 25% and 50%. We could observe that the Glass waste aggregates are lighter than natural aggregates and they show a very low water absorption. The experimental results showed that the slump flow increased with the increase of recycled glass content. On the other hand, the compressive strength and tensile strength of recycled glass mixtures decreased with the increase in the recycled glass content. The results showed that recycled glass aggregate can successfully be used with limited level for producing concrete. The standard sand was substituted with aggregates based on glass waste for manufacturing mortars, Mortar based on glass shows a compressive strength and low bending with a 1/2 ratio with control mortar strength.

Keywords: concrete, environment, glass waste, recycling

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Authors: Sakiru Badmos, David R. Cole, Alberto Striolo

Abstract:

It is known that confinement in nm-size pores affects many structural and transport properties of water and co-existing volatile species. Of particular interest for fluids in sub-surface systems, in catalysis, and in separations are reports that confinement can enhance the solubility of gases in water. Equilibrium molecular dynamics simulations were performed for aqueous H₂S confined in slit-shaped silica pores at 313K. The effect of pore width on the H₂S solubility in water was investigated. Other properties of interest include the molecular distribution of the various fluid molecules within the pores, the hydration structure for solvated H₂S molecules, and the dynamical properties of the confined fluids. The simulation results demonstrate that confinement reduces the H₂S solubility in water and that the solubility increases with pore size. Analysis of spatial distribution functions suggests that these results are due to perturbations on the coordination of water molecules around H₂S due to confinement. Confinement is found to dampen the dynamical properties of aqueous H₂S as well. Comparing the results obtained for aqueous H₂S to those reported elsewhere for aqueous CH₄, it can be concluded that H₂S permeates hydrated slit-shaped silica nano-pores faster than CH₄. In addition to contributing to better understanding the behavior of fluids in subsurface formations, these observations could also have important implications for developing new natural gas sweetening technologies.

Keywords: confinement, interfacial properties, molecular dynamic simulation, sub-surface formations

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Authors: Christos Spandonidis, Stefanos Tsantilas, Elias Sedikos, Nektarios Galiatsatos, Fotios Giannopoulos, Panagiotis Papadopoulos, Nikolaos Demagos, Dimitrios Reppas, Christos Giordamlis

Abstract:

In the present paper, a low cost, compact and modular Internet of Things (IoT) platform for air quality monitoring in urban areas is presented. This platform comprises of dedicated low cost, low power hardware and the associated embedded software that enable measurement of particles (PM2.5 and PM10), NO, CO, CO₂ and O₃ concentration in the air, along with relative temperature and humidity. This integrated platform acts as part of a greater air pollution data collecting wireless network that is able to monitor the air quality in various regions and neighborhoods of an urban area, by providing sensor measurements at a high rate that reaches up to one sample per second. It is therefore suitable for Big Data analysis applications such as air quality forecasts, weather forecasts and traffic prediction. The first real world test for the developed platform took place in Thessaloniki, Greece, where 16 devices were installed in various buildings in the city. In the near future, many more of these devices are going to be installed in the greater Thessaloniki area, giving a detailed air quality map of the city.

Keywords: distributed sensor system, environmental monitoring, Internet of Things, smart cities

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Authors: Muhammad Bilal Ameen, M. Zubair Akbar Qureshi

Abstract:

The current investigation of two-dimensional hybrid nanofluid flows with two coaxial parallel disks has been presented. Consider the hybrid nanofluid has been taken as steady-state. Consider the coaxial disks that have been porous. Consider the heat equation to examine joule heating and viscous dissipation effects. Nonlinear partial differential equations have been solved numerically. For shear stress and heat transfer, results are tabulated. Hybrid nanoparticles and Eckert numbers are increasing for heat transfer. Entropy generation is expanded with radiation parameters Eckert, Reynold, Prandtl, and Peclet numbers. A set of ordinary differential equations is obtained to utilize the capable transformation variables. The numerical solution of the continuity, momentum, energy, and entropy generation equations is obtaining using the command bvp4c of Matlab as a solver. To explore the impact of main parameters like suction/infusion, Prandtl, Reynold, Eckert, Peclet number, and volume fraction parameters, various graphs have been plotted and examined. It is concluded that a convectional nanofluid is highly compared by entropy generation with the boundary layer of hybrid nanofluid.

Keywords: entropy generation, hybrid nano fluid, heat transfer, porous disks

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Authors: Rita Sassine, Yassine Hassani, Mohamad Al Omari, Stéphanie Guibert

Abstract:

Building Information Modelling (BIM) is the process of creating, managing, and centralizing information during the building lifecycle. BIM can be used all over a construction project, from the initiation phase to the planning and execution phases to the maintenance and lifecycle management phase. For existing buildings, BIM can be used for specific applications such as lifecycle management. However, most of the existing buildings don’t have a BIM model. Creating a compatible BIM for existing buildings is very challenging. It requires special equipment for data capturing and efforts to convert these data into a BIM model. The main difficulties for such projects are to define the data needed, the level of development (LOD), and the methodology to be adopted. In addition to managing information for an existing building, studying the impact of the built environment is a challenging topic. So, integrating the existing terrain that surrounds buildings into the digital model is essential to be able to make several simulations as flood simulation, energy simulation, etc. Making a replication of the physical model and updating its information in real-time to make its Digital Twin (DT) is very important. The Digital Terrain Model (DTM) represents the ground surface of the terrain by a set of discrete points with unique height values over 2D points based on reference surface (e.g., mean sea level, geoid, and ellipsoid). In addition, information related to the type of pavement materials, types of vegetation and heights and damaged surfaces can be integrated. Our aim in this study is to define the methodology to be used in order to provide a 3D BIM model for the site and the existing building based on the case study of “Ecole Spéciale des Travaux Publiques (ESTP Paris)” school of engineering campus. The property is located on a hilly site of 5 hectares and is composed of more than 20 buildings with a total area of 32 000 square meters and a height between 50 and 68 meters. In this work, the campus precise levelling grid according to the NGF-IGN69 altimetric system and the grid control points are computed according to (Réseau Gédésique Français) RGF93 – Lambert 93 french system with different methods: (i) Land topographic surveying methods using robotic total station, (ii) GNSS (Global Network Satellite sytem) levelling grid with NRTK (Network Real Time Kinematic) mode, (iii) Point clouds generated by laser scanning. These technologies allow the computation of multiple building parameters such as boundary limits, the number of floors, the floors georeferencing, the georeferencing of the 4 base corners of each building, etc. Once the entry data are identified, the digital model of each building is done. The DTM is also modeled. The process of altimetric determination is complex and requires efforts in order to collect and analyze multiple data formats. Since many technologies can be used to produce digital models, different file formats such as DraWinG (DWG), LASer (LAS), Comma-separated values (CSV), Industry Foundation Classes (IFC) and ReViT (RVT) will be generated. Checking the interoperability between BIM models is very important. In this work, all models are linked together and shared on 3DEXPERIENCE collaborative platform.

Keywords: building information modeling, digital terrain model, existing buildings, interoperability

Procedia PDF Downloads 95

Authors: Payel Datta, Abhishek Das, Abhishek Roychoudhury, Dhiman Chattopadhyay, Tanushyam Chattopadhyay

Abstract:

Machine learning (ML) and deep learning (DL) is most predominantly used in image/video processing, natural language processing (NLP), audio and speech recognition but not that much used in system performance evaluation. In this paper, authors are going to describe the architecture of an abstraction layer constructed using ML/DL to detect the system failure. This proposed system is used to detect the system failure by evaluating the performance metrics of an IoT service deployment under constrained infrastructure environment. This system has been tested on the manually annotated data set containing different metrics of the system, like number of threads, throughput, average response time, CPU usage, memory usage, network input/output captured in different hardware environments like edge (atom based gateway) and cloud (AWS EC2). The main challenge of developing such system is that the accuracy of classification should be 100% as the error in the system has an impact on the degradation of the service performance and thus consequently affect the reliability and high availability which is mandatory for an IoT system. Proposed ML/DL classifiers work with 100% accuracy for the data set of nearly 4,000 samples captured within the organization.

Keywords: machine learning, system performance, performance metrics, IoT, edge

Procedia PDF Downloads 181