Search results for: damage prediction models

Authors: Nathi Ram, Saurabh K. Yadav

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In turbomachinery, the turbulent flow occurs due to the use of high velocity of low kinematic viscosity lubricants and used in many industrial applications. In the present work, the performance of symmetric slot-entry hybrid worn journal bearing under laminar and turbulent lubrication has been investigated. For turbulent lubrication, the Reynolds equation has been modified using Constantinescu turbulent model. This modified equation has been solved using the finite element method. The effect of turbulent lubrication on bearing’s performance has been presented for symmetric hybrid journal bearing. The slot-entry hybrid worn journal bearing under turbulent/laminar regimes have been investigated. It has been observed that the stiffness and damping coefficients are more for the bearing having slot width ratio (SWR) of 0.25 than the bearing with SWR of 0.5 and 0.75 under the turbulent regime. Further, it is also observed that for constant wear depth parameter, stability threshold speed gets increased for bearing operates at slot width ratio 0.25 under turbulent lubrication.

Keywords: hydrostatic bearings, journal bearings, restrictors, turbulent flow models, finite element technique

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Authors: Mathias Cehlin, Arman Ameen, Ulf Larsson, Taghi Karimipanah

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The indoor environmental quality (IEQ) is increasingly recognized as a significant factor influencing the overall level of building occupants’ health, comfort and productivity. An air-conditioning and ventilation system is normally used to create and maintain good thermal comfort and indoor air quality. Providing occupant thermal comfort and well-being with minimized use of energy is the main purpose of heating, ventilating and air conditioning system. Among different types of ventilation systems, the most widely known and used ventilation systems are mixing ventilation (MV) and displacement ventilation (DV). Impinging jet ventilation (IJV) is a promising ventilation strategy developed in the beginning of 2000s. IJV has the advantage of supplying air downwards close to the floor with high momentum and thereby delivering fresh air further out in the room compare to DV. Operating in cooling mode, IJV systems can have higher ventilation effectiveness and heat removal effectiveness compared to MV, and therefore a higher energy efficiency. However, how is the performance of IJV when operating in heating mode? This paper presents the function of IJV in a typical office room for winter conditions (heating mode). In this paper, a validated CFD model, which uses the v2-f model is used for the prediction of air flow pattern, thermal comfort and air change effectiveness. The office room under consideration has the dimensions 4.2×3.6×2.5m, which can be designed like a single-person or two-person office. A number of important factors influencing in the room with IJV are studied. The considered parameters are: heating demand, number of occupants and supplied air conditions. A total of 6 simulation cases are carried out to investigate the effects of the considered parameters. Heat load in the room is contributed by occupants, computer and lighting. The model consists of one external wall including a window. The interaction effects of heat sources, supply air flow and down draught from the window result in a complex flow phenomenon. Preliminary results indicate that IJV can be used for heating of a typical office room. The IEQ seems to be suitable in the occupied region for the studied cases.

Keywords: computation fluid dynamics, impinging jet ventilation, indoor environmental quality, ventilation strategy

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Authors: Seunghwan Seo, Woo-Seok Lee, Ji-Sun Shin, Young Kyoung Rhee, Chang-Won Cho, Hee-Do Hong, Kyung-Tae Lee

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Doenjang, known as traditional Korean food, is product of a natural mixed fermentation process carried out by lactic acid bacteria (LAB). Lactobacillus sakei K040706 (K040706) has been accepted as the most populous LAB in over ripened doenjang. Recently, we reported the immunostimulatory effects of K040706 in RAW 264.7 macrophages and in a cyclophosphamide-induced mouse model. In this study, we investigated the ameliorative effects of K040706 in a dextran sulfate sodium (DSS)-induced colitis mouse model. We induced colitis using DSS in 5-week-ICR mice over 14 days with or without 0.1, 1 g/kg/day K040706 orally. The body weight, stool consistency, and gross bleeding were recorded for determination of the disease activity index (DAI). At the end of treatment, animals were sacrificed and colonic tissues were collected and subjected to histological experiments and myeloperoxidase (MPO) accumulation, cytokine determination, qRT-PCR and Western blot analysis. Results showed that K040706 significantly attenuated DSS-induced DAI score, shortening of colon length, enlargement of spleen and immune cell infiltrations into colonic tissues. Histological examinations indicated that K040706 suppressed edema, mucosal damage, and the loss of crypts induced by DSS. These results were correlated with the restoration of tight junction protein expression, such as, ZO-1 and occludin in K040706-treated mice. Moreover, K040706 reduced the abnormal secretions and mRNA expressions of pro-inflammatory mediators, such as nitric oxide (NO), tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β), and interleukin-6 (IL-6). DSS-induced mRNA expression of intercellular adhesion molecule (ICAM) and vascular cell adhesion molecule (VCAM) in colonic tissues was also downregulated by K040706 treatment. Furthermore, K040706 suppressed the protein and mRNA expression of toll-like receptor 4 (TLR4) and phosphorylation of NF-κB and signal transducer and activator of transcription 3 (STAT3). These results suggest that K040706 has an anti-colitic effect by inhibition of intestinal inflammatory responses in DSS-induced colitic mice.

Keywords: Lactobacillus sakei, NF-κB, STAT3, ulcerative colitis

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Authors: Azadeh Bashiri

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Introduction: Lack of proper diagnosis and inadequate treatment of asthma leads to physical and financial complications. This study aimed to use data mining techniques and creating a neural network intelligent system for diagnosis of asthma. Methods: The study population is the patients who had visited one of the Lung Clinics in Tehran. Data were analyzed using the SPSS statistical tool and the chi-square Pearson's coefficient was the basis of decision making for data ranking. The considered neural network is trained using back propagation learning technique. Results: According to the analysis performed by means of SPSS to select the top factors, 13 effective factors were selected, in different performances, data was mixed in various forms, so the different models were made for training the data and testing networks and in all different modes, the network was able to predict correctly 100% of all cases. Conclusion: Using data mining methods before the design structure of system, aimed to reduce the data dimension and the optimum choice of the data, will lead to a more accurate system. Therefore, considering the data mining approaches due to the nature of medical data is necessary.

Keywords: asthma, data mining, Artificial Neural Network, intelligent system

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Authors: Aleksandar Hatzivelkos

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The term ”compromise” is mostly used casually within the social choice theory. It is usually used as a mere result of the social choice function, and this omits its deeper meaning and ramifications. This paper is based on a mathematical model for the description of a compromise as a version of the Sorites paradox. It introduces a formal definition of d-measure of divergence from a compromise and models a notion of compromise that is often used only colloquially. Such a model for vagueness phenomenon, which lies at the core of the notion of compromise enables the introduction of new mathematical structures. In order to maximize compromise, different methods can be used. In this paper, we explore properties of a social welfare function TdM (from Total d-Measure), which is defined as a function which minimizes the total sum of d-measures of divergence over all possible linear orderings. We prove that TdM satisfy strict Pareto principle and behaves well asymptotically. Furthermore, we show that for certain domain restrictions, TdM satisfy positive responsiveness and IIIA (intense independence of irrelevant alternatives) thus being equivalent to Borda count on such domain restriction. This result gives new opportunities in social choice, especially when there is an emphasis on compromise in the decision-making process.

Keywords: borda count, compromise, measure of divergence, minimization

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Authors: Ahmed Mateen, Zhu Qingsheng, Faisal Shahzad

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Requirement Engineering (RE) is a part being created for programming structure during the software development lifecycle. Software product line development is a new topic area within the domain of software engineering. It also plays important role in decision making and it is ultimately helpful in rising business environment for productive programming headway. Decisions are central to engineering processes and they hold them together. It is argued that better decisions will lead to better engineering. To achieve better decisions requires that they are understood in detail. In order to address the issues, companies are moving towards Software Product Line Engineering (SPLE) which helps in providing large varieties of products with minimum development effort and cost. This paper proposed a new framework for software product line and compared with other models. The results can help to understand the needs in SPL testing, by identifying points that still require additional investigation. In our future scenario, we will combine this model in a controlled environment with industrial SPL projects which will be the new horizon for SPL process management testing strategies.

Keywords: requirements engineering, software product lines, scoping, process structure, domain specific language

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Authors: Babak Kamrani, Nozar Kishi

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Stochastic catalog represents the events module of the earthquake loss estimation models. It includes series of events with different magnitudes and corresponding frequencies/probabilities. For the development of the stochastic catalog, random or uniform sampling methods are used to sample the events from the seismicity model. For covering all the Magnitude Frequency Distribution (MFD), a huge number of events should be generated for the above-mentioned methods. Characteristic Event (CE) method chooses the events based on the interest of the insurance industry. We divide the MFD of each source into bins. We have chosen the bins based on the probability of the interest by the insurance industry. First, we have collected the information for the available seismic sources. Sources are divided into Fault sources, subduction, and events without specific fault source. We have developed the MFD for each of the individual and areal source based on the seismicity of the sources. Afterward, we have calculated the CE magnitudes based on the desired probability. To develop the stochastic catalog, we have introduced uncertainty to the location of the events too.

Keywords: stochastic catalogue, earthquake loss, uncertainty, characteristic event

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Authors: S. K. Verma, S. L. Sinha, D. K. Chandraker

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The Advanced Heavy Water Reactor (AHWR) is a vertical pressure tube type, heavy water moderated and boiling light water cooled natural circulation based reactor. The fuel bundle of AHWR contains 54 fuel rods arranged in three concentric rings of 12, 18 and 24 fuel rods. This fuel bundle is divided into a number of imaginary interacting flow passage called subchannels. Single phase flow condition exists in reactor rod bundle during startup condition and up to certain length of rod bundle when it is operating at full power. Prediction of the thermal margin of the reactor during startup condition has necessitated the determination of the turbulent mixing rate of coolant amongst these subchannels. Thus, it is vital to evaluate turbulent mixing between subchannels of AHWR rod bundle. With the remarkable progress in the computer processing power, the computational fluid dynamics (CFD) methodology can be useful for investigating the thermal–hydraulic characteristics phenomena in the nuclear fuel assembly. The present report covers the results of simulation of pressure drop, velocity variation and turbulence intensity on single rod bundle with 54 rods in circular arrays. In this investigation, 54-rod assemblies are simulated with ANSYS Fluent 15 using steady simulations with an ANSYS Workbench meshing. The simulations have been carried out with water for Reynolds number 9861.83. The rod bundle has a mean flow area of 4853.0584 mm2 in the bare region with the hydraulic diameter of 8.105 mm. In present investigation, a benchmark k-ε model has been used as a turbulence model and the symmetry condition is set as boundary conditions. Simulation are carried out to determine the turbulent mixing rate in the simulated subchannels of the reactor. The size of rod and the pitch in the test has been same as that of actual rod bundle in the prototype. Water has been used as the working fluid and the turbulent mixing tests have been carried out at atmospheric condition without heat addition. The mean velocity in the subchannel has been varied from 0-1.2 m/s. The flow conditions are found to be closer to the actual reactor condition.

Keywords: AHWR, CFD, single-phase turbulent mixing rate, thermal–hydraulic

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Authors: Mustafa Kaya

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In this study, the effect of pre-stressed strand diameters, providing the beam-to-column connections, was investigated from both experimental, and analytical aspects. In the experimental studies, the strength, stiffness, and energy dissipation capacities of the precast specimens comprising two pre-stressed strand samples of 12.70 mm, and 15.24 mm diameters, were compared with the reference specimen. The precast specimen with strands of 15.24 mm reached 96% of the maximum strength of the reference specimen; the amount of energy dissipated by this specimen until end of the test reached 48% of the amount of energy dissipated by the reference sample, and the stiffness of the same specimen at a 1.5% drift of reached 77% of the stiffness of the reference specimen at this drift. Parallel results were obtained during the analytical studies from the aspects of strength, and behavior, but the initial stiffness of the analytical models was lower than that of the test specimen.

Keywords: precast beam to column connection, moment resisting connection, post tensioned connections, finite element method

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Authors: Nolitha L. Skenjana, Bongani P. Kubheka, Maxwell A. Poswal

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The Eastern Cape Province of South Africa is characterized by subsistence farming, which is mostly distributed in the rural areas of the province. It is estimated that cereal crops such as maize and sorghum, and vegetables such as cabbage are grown in more than 400.000 rural households, with maize being the most dominant crop. However, compared to commercial agriculture, small-scale farmers receive minimal support from research and development, limited technology transfer on the latest production practices and systems and have poor production infrastructure and equipment. Similarly, there is limited farmers' appreciation on best practices in insect pest management and control. The paper presents findings from the primary literature and personal observations on insect pest management practices of small-scale farmers in the province. Inferences from literature and personal experiences in the production areas have led to a number of deductions regarding the level of exposure and extent of vulnerability. Farmers' pest management practices, which included not controlling at all though there is a pest problem, resulted in their crop stands to be more vulnerable to pest attacks. This became more evident with the recent brown locust, African armyworm, and Fall armyworm outbreaks, and with the incidences of opportunistic phytophagous insects previously collected on wild hosts only, found causing serious damages on crops. In most of these occurrences, damage to crops resulted in low or no yield. Improvements on farmers' reaction and response to pest problems were only observed in areas where focused awareness campaigns and trainings on specific pests and their management techniques were done. This then calls for a concerted effort from all role players in the sphere of small-scale crop production, to train and equip farmers with relevant skills, and provide them with information on affordable and climate-smart strategies and technologies in order to create a state of preparedness. This is necessary for the prevention of substantial crop losses that may exacerbate food insecurity in the province.

Keywords: Eastern Cape Province, small-scale farmers, insect pest management, vulnerability

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Authors: Mohanad Al-Behadili, Djamila Ouelhadj

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In this paper, a specific type of vehicle routing problem under stochastic demand (SVRP) is considered. This problem is of great importance because it models for many of the real world vehicle routing applications. This paper used a robust optimisation model to solve the problem along with the novel Simulation-Particle Swarm Optimisation (Sim-PSO) approach. The proposed Sim-PSO approach is based on the hybridization of the Monte Carlo simulation technique with the PSO algorithm. A comparative study between the proposed model and the Sim-PSO approach against other solution methods in the literature has been given in this paper. This comparison including the Analysis of Variance (ANOVA) to show the ability of the model and solution method in solving the complicated SVRP. The experimental results show that the proposed model and Sim-PSO approach has a significant impact on the obtained solution by providing better quality solutions comparing with well-known algorithms in the literature.

Keywords: stochastic vehicle routing problem, robust optimisation model, Monte Carlo simulation, particle swarm optimisation

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Authors: Nasim Nosoudi, Amir Zadeh, Hunter White, Joshua Conrad, Joon W. Shim

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De novo Malignancy has become one of the major causes of death after transplantation, so early cancer diagnosis and detection can drastically improve survival rates post-transplantation. Most previous work focuses on using artificial intelligence (AI) to predict transplant success or failure outcomes. In this work, we focused on predicting de novo malignancy after liver transplantation using AI. We chose the patients that had malignancy after liver transplantation with no history of malignancy pre-transplant. Their donors were cancer-free as well. We analyzed 254,200 patient profiles with post-transplant malignancy from the US Organ Procurement and Transplantation Network (OPTN). Several popular data mining methods were applied to the resultant dataset to build predictive models to characterize de novo malignancy after liver transplantation. Recipient's bilirubin, creatinine, weight, gender, number of days recipient was on the transplant waiting list, Epstein Barr Virus (EBV), International normalized ratio (INR), and ascites are among the most important factors affecting de novo malignancy after liver transplantation

Keywords: De novo malignancy, bilirubin, data mining, transplantation

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Authors: Jasminka Mujic, Karin Milde-Langosch, Volkmar Mueller, Mirza Suljagic, Tea Becirevic, Jozo Coric, Daria Ler

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MACC1 (metastasis associated in colon cancer-1) is a prognostic biomarker for tumor progression, metastasis, and survival of a variety of solid cancers. MACC1 also causes tumor growth in xenograft models and acts as a master regulator of the HGF/MET signaling pathway. In breast cancer, the expression of MACC1 determined by immunohistochemistry was significantly associated with positive lymph node status and advanced clinical stage. The aim of the present study was to further investigate the prognostic or predictive value of MACC1 expression in breast cancer using western blot analysis and immunohistochemistry. The results of our study have shown that high MACC1 expression in breast cancer is associated with shorter disease-free survival, especially in node-negative tumors. The MACC1 might be a suitable biomarker to select patients with a higher probability of recurrence which might benefit from adjuvant chemotherapy. Our results support a biologic role and potentially open the perspective for the use of MACC1 as predictive biomarker for treatment decision in breast cancer patients.

Keywords: breast cancer, biomarker, HGF/MET, MACC1

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Authors: Nikola Vlahovic, Blazenka Knezevic, Petra Batalic

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In this paper, we will present a research about feasibility of implementing unmanned aerial vehicles, also known as 'drones', in logistics. Research is based on available information about current incentives and experiments in application of delivery drones in commercial use. Overview of current pilot projects and literature, as well as an overview of detected challenges, will be compiled and presented. Based on these findings, we will present a conceptual model of business process that implements delivery drones in business to business logistic operations. Business scenario is based on a pharmaceutical supply chain. Simulation modeling will be used to create models for running experiments and collecting performance data. Comparative study of the presented conceptual model will be given. The work will outline the main advantages and disadvantages of implementing unmanned aerial vehicles in delivery services as a supplementary distribution channel along the supply chain.

Keywords: business process, delivery drones, logistics, simulation modelling, unmanned aerial vehicles

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Authors: Sandesh Achar

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Artificial intelligence is being increasingly incorporated into many applications across various sectors such as health, education, security, and agriculture. Recently, there has been rapid development in cloud computing technology, resulting in AI’s implementation into cloud computing to enhance and optimize the technology service rendered. The deployment of AI in cloud-based applications has brought about autonomous computing, whereby systems achieve stated results without human intervention. Despite the amount of research into autonomous computing, work incorporating AI/ML into cloud computing to enhance its performance and resource allocation remain a fundamental challenge. This paper highlights different manifestations, roles, trends, and challenges related to AI-based cloud computing models. This work reviews and highlights excellent investigations and progress in the domain. Future directions are suggested for leveraging AI/ML in next-generation computing for emerging computing paradigms such as cloud environments. Adopting AI-based algorithms and techniques to increase operational efficiency, cost savings, automation, reducing energy consumption and solving complex cloud computing issues are the major findings outlined in this paper.

Keywords: artificial intelligence, cloud computing, deep learning, machine learning, internet of things

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Authors: Zhengming Wu

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NanoFrazor lithography systems were developed as a first true alternative or extension to standard mask-less nanolithography methods like electron beam lithography (EBL). In contrast to EBL they are based on thermal scanning probe lithography (t-SPL). Here a heatable ultra-sharp probe tip with an apex of a few nm is used for patterning and simultaneously inspecting complex nanostructures. The heat impact from the probe on a thermal responsive resist generates those high-resolution nanostructures. The patterning depth of each individual pixel can be controlled with better than 1 nm precision using an integrated in-situ metrology method. Furthermore, the inherent imaging capability of the Nanofrazor technology allows for markerless overlay, which has been achieved with sub-5 nm accuracy as well as it supports stitching layout sections together with < 10 nm error. Pattern transfer from such resist features below 10 nm resolution were demonstrated. The technology has proven its value as an enabler of new kinds of ultra-high resolution nanodevices as well as for improving the performance of existing device concepts. The application range for this new nanolithography technique is very broad spanning from ultra-high resolution 2D and 3D patterning to chemical and physical modification of matter at the nanoscale. Nanometer-precise markerless overlay and non-invasiveness to sensitive materials are among the key strengths of the technology. However, while patterning at below 10 nm resolution is achieved, significantly increasing the patterning speed at the expense of resolution is not feasible by using the heated tip alone. Towards this end, an integrated laser write head for direct laser sublimation (DLS) of the thermal resist has been introduced for significantly faster patterning of micrometer to millimeter-scale features. Remarkably, the areas patterned by the tip and the laser are seamlessly stitched together and both processes work on the very same resist material enabling a true mix-and-match process with no developing or any other processing steps in between. The presentation will include examples for (i) high-quality metal contacting of 2D materials, (ii) tuning photonic molecules, (iii) generating nanofluidic devices and (iv) generating spintronic circuits. Some of these applications have been enabled only due to the various unique capabilities of NanoFrazor lithography like the absence of damage from a charged particle beam.

Keywords: nanofabrication, grayscale lithography, 2D materials device, nano-optics, photonics, spintronic circuits

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Authors: H. Shokouhmand, H. Sobhani, B. Sajadi, M. Degheh

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In recent years, experimental and numerical investigation of water UV reactors has increased significantly. The main drawback of experimental methods is confined and expensive survey of UV reactors features. In this study, a CFD model utilizing the eulerian-lagrangian framework is applied to analysis the disinfection performance of a closed conduit reactor which contains four UV lamps perpendicular to the flow. A discrete ordinates (DO) model was employed to evaluate the UV irradiance field. To investigate the importance of each of lamps on the inactivation performance, in addition to the reference model (with 4 bright lamps), several models with one or two bright lamps in various arrangements were considered. All results were reported in three inactivation kinetics. The results showed that the log inactivation of the two central bright lamps model was between 88-99 percent, close to the reference model results. Also, whatever the lamps are closer to the main flow region, they have more effect on microbial inactivation. The effect of some operational parameters such as water flow rate, inlet water temperature, and lamps power were also studied.

Keywords: Eulerian-Lagrangian framework, inactivation kinetics, log inactivation, water UV reactor

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Authors: Tarek M. Alguhane, Ayman H. Khalil, Nour M. Fayed, Ayman M. Ismail

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An existing RC building in Madinah is seismically evaluated with and without infill wall. Four model systems have been considered i. e. model I (no infill), model IIA (strut infill-update from field test), model IIB (strut infill- ASCE/SEI 41) and model IIC (strut infill-Soft storey-ASCE/SEI 41). Three dimensional pushover analyses have been carried out using SAP 2000 software incorporating inelastic material behavior for concrete, steel and infill walls. Infill wall has been modeled as equivalent strut according to suggested equation matching field test measurements and to the ASCE/SEI 41 equation. The effect of building modeling on the performance point as well as capacity and demand spectra due to EQ design spectrum function in Madinah area has been investigated. The response modification factor (R) for the 5 story RC building is evaluated from capacity and demand spectra (ATC-40) for the studied models. The results are summarized and discussed.

Keywords: infill wall, pushover analysis, response modification factor, seismic assessment

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Authors: Jiahui Song

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In order to predict or explain a complicated biological process, it is important first to construct mathematical models that can be used to yield analytical solutions. Through numerical simulation, mathematical model results can be used to test scenarios that might not be easily attained in a laboratory experiment, or to predict parameters or phenomena. High-intensity, nanosecond pulse electroporation has been a recent development in bioelectrics. The dynamic pore model can be achieved by including a dynamic aspect and a dependence on the pore population density into pore formation energy equation to analyze and predict such electroporation effects. For greater accuracy, with inclusion of atomistic details, molecular dynamics (MD) simulations were also carried out during this study. Besides inducing pores in cells, external voltages could also be used in principle to modulate action potential generation in nerves. This could have an application in electrically controlled ‘pain management’. Also a simple model-based rate equation treatment of the various cellular bio-chemical processes has been used to predict the pulse number dependent cell survival trends.

Keywords: model, high-intensity, nanosecond, bioelectrics

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Authors: Yu-Chien Huang, Shu-Chen Yang

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Introduction: Parenting style, non-attachment, and inferiority are important topics in psychology, but the related research on nonattachment is still lacking. Therefore, the purposes of this study were to explore the relationship between parenting style, nonattachment, and inferiority. Methods: We conducted a correlational study, and three instruments were utilized to collect data: parenting style scale, nonattachment scale, and inferiority scale. The inter-reliability Cronbach's α used in this research indicated good inter item reliability and the test-retest reliability that showed a good consistency. The data were analyzed using the descriptive statistics, Chi-square test, one way ANOVA, Pearson’s correlation, and regression analysis. Results: A total of 200 participators were tested in this research. As a result of the study, inferiority had a positive correlation with authoritarian parenting style; nonattachment had a negative correlation with authoritarian parenting style; and with inferiority, the hypothesis was supported. In the linear mediation models, nonattachment was found to be partially mediated the relationship between authoritarian parenting style and inferiority. Conclusion: These findings imply that interventions aimed at enhancing nonattachment as a way to improve inferiority are a good strategy.

Keywords: inferiority, nonattachment, parenting style, psychology

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Authors: DRIS Mohammed El-Amine, BOUNIF Abdelhamid

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This paper considers an experimental and numerical investigation of variable density in axisymmetric turbulent free jets. Special attention is paid to the study of the scalar dissipation rate. In this case, dynamic field equations are coupled to scalar field equations by the density which can vary by the thermal effect (jet heating). The numerical investigation is based on the first and second order turbulence models. For the discretization of the equations system characterizing the flow, the finite volume method described by Patankar (1980) was used. The experimental study was conducted in order to evaluate dynamical characteristics of a heated axisymmetric air flow using the Laser Doppler Anemometer (LDA) which is a very accurate optical measurement method. Experimental and numerical results are compared and discussed. This comparison do not show large difference and the results obtained are in general satisfactory.

Keywords: Scalar dissipation rate, thermal effects, turbulent axisymmetric jets, second order modelling, Velocimetry Laser Doppler.

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Authors: F. A. Hassona, M. D. Hashem, R. I. Melek, B. M. Hakeem

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A differential settlement at the end of a bridge near the interface between the abutment and the embankment is a persistent problem for highway agencies. The differential settlement produces the common ‘bump at the end of the bridge’. Reduction in steering response, distraction to the driver, added risk and expense to maintenance operation, and reduction in a transportation agency’s public image are all undesirable effects of these uneven and irregular transitions. This paper attempts to simulate the bump at the end of the bridge using PLAXIS finite element 2D program. PLAXIS was used to simulate a laboratory model called Bridge to Embankment Simulator of Transition (B.E.S.T.) device which was built by others to investigate this problem. A total of six numerical simulations were conducted using hardening- soil model with rational assumptions of missing soil parameters to estimate the bump at the end of the bridge. The results show good agreements between the numerical and the laboratory models. Important factors influencing bumps at bridge ends were also addressed in light of the model results.

Keywords: bridge approach slabs, bridge bump, hardening-soil, PLAXIS 2D, settlement

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Authors: L. Wilkening, G. Ackermann, T. T. Do

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This article presents an approach for stand-alone and grid-connected mode of a German low-voltage grid with high share of photovoltaic. For this purpose, suitable dynamic system models have been developed. This allows the simulation of dynamic events in very small time ranges and the operation management over longer periods of time. Using these simulations, suitable control parameters could be identified, and their effects on the grid can be analyzed. In order to validate the simulation results, a LV-grid test bench has been implemented at the University of Technology Hamburg. The developed control strategies are to be validated using real inverters, generators and different realistic loads. It is shown that a battery hybrid system installed next to a voltage transformer makes it possible to operate the LV-grid in stand-alone mode without using additional information and communication technology and without intervention in the existing grid units. By simulating critical days of the year, suitable control parameters for stable stand-alone operations are determined and set point specifications for different control strategies are defined.

Keywords: battery, e-mobility, photovoltaic, smart grid

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Authors: Mohammed Jibrin Ndejiko

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Modern and current models such as flow cell technology which enhances a non-destructive growth and inspection of the sessile microbial communities revealed a great understanding of biofilms. A continuous flow system was designed to evaluate possibility of biofilm formation by Escherichia coli DH5α on the stainless steel (type 304) under continuous nutrient supply. The result of the colony forming unit (CFU) count shows that bacterial attachment and subsequent biofilm formation on stainless steel coupons with average surface roughness of 1.5 ± 1.8 µm and 2.0 ± 0.09 µm were both significantly higher (p ≤ 0.05) than those of the stainless steel coupon with lower surface roughness of 0.38 ± 1.5 µm. These observations support the hypothesis that surface profile is one of the factors that influence biofilm formation on stainless steel surfaces. The SEM and FESEM micrographs of the stainless steel coupons also revealed the attached Escherichia coli DH5α biofilm and dehydrated extracellular polymeric substance on the stainless steel surfaces. Thus, the fabricated flow system represented a very useful tool to study biofilm formation under continuous nutrient supply.

Keywords: biofilm, flowcell, stainless steel, coupon

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Authors: Md. Abu Sufian, Robiqul Islam, Imam Hossain Shajid, Mahesh Hanumanthu, Jarasree Varadarajan, Md. Sipon Miah, Mingbo Niu

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Coronary Heart Disease (CHD) remains a principal cause of global morbidity and mortality, characterized by atherosclerosis—the build-up of fatty deposits inside the arteries. The study introduces an innovative methodology that leverages cloud-based platforms like AWS Live Streaming and Artificial Intelligence (AI) to early detect and prevent CHD symptoms in web applications. By employing novel simulation processes and AI algorithms, this research aims to significantly mitigate the health and societal impacts of CHD. Methodology: This study introduces a novel simulation process alongside a multi-phased model development strategy. Initially, health-related data, including heart rate variability, blood pressure, lipid profiles, and ECG readings, were collected through user interactions with web-based applications as well as API Integration. The novel simulation process involved creating synthetic datasets that mimic early-stage CHD symptoms, allowing for the refinement and training of AI algorithms under controlled conditions without compromising patient privacy. AWS Live Streaming was utilized to capture real-time health data, which was then processed and analysed using advanced AI techniques. The novel aspect of our methodology lies in the simulation of CHD symptom progression, which provides a dynamic training environment for our AI models enhancing their predictive accuracy and robustness. Model Development: it developed a machine learning model trained on both real and simulated datasets. Incorporating a variety of algorithms including neural networks and ensemble learning model to identify early signs of CHD. The model's continuous learning mechanism allows it to evolve adapting to new data inputs and improving its predictive performance over time. Results and Findings: The deployment of our model yielded promising results. In the validation phase, it achieved an accuracy of 92% in predicting early CHD symptoms surpassing existing models. The precision and recall metrics stood at 89% and 91% respectively, indicating a high level of reliability in identifying at-risk individuals. These results underscore the effectiveness of combining live data streaming with AI in the early detection of CHD. Societal Implications: The implementation of cloud-based AI for CHD symptom detection represents a significant step forward in preventive healthcare. By facilitating early intervention, this approach has the potential to reduce the incidence of CHD-related complications, decrease healthcare costs, and improve patient outcomes. Moreover, the accessibility and scalability of cloud-based solutions democratize advanced health monitoring, making it available to a broader population. This study illustrates the transformative potential of integrating technology and healthcare, setting a new standard for the early detection and management of chronic diseases.

Keywords: coronary heart disease, cloud-based ai, machine learning, novel simulation techniques, early detection, preventive healthcare

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Authors: H. Loumi-Fergane, A. Belaidi

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The problem of symmetries in field theory has been analyzed using geometric frameworks, such as the multisymplectic models by using in particular the multivector field formalism. In this paper, we expand the vector fields associated to infinitesimal symmetries which give rise to invariant quantities as Noether currents for classical field theories and relativistic mechanic using the multisymplectic geometry where the Poincaré-Cartan form has thus been greatly simplified using the Second Order Partial Differential Equation (SOPDE) for multi-vector fields verifying Euler equations. These symmetries have been classified naturally according to the construction of the fiber bundle used.  In this work, unlike other works using the analytical method, our geometric model has allowed us firstly to distinguish the angular moments of the gauge field obtained during different transformations while these moments are gathered in a single expression and are obtained during a rotation in the Minkowsky space. Secondly, no conditions are imposed on the Lagrangian of the mechanics with respect to its dependence in time and in qⁱ, the currents obtained naturally from the transformations are respectively the energy and the momentum of the system.

Keywords: conservation laws, field theories, multisymplectic geometry, relativistic mechanics

Procedia PDF Downloads 191

Authors: Seung Won Park

Abstract:

Pornographic images are becoming increasingly normalized as innovations in media technology arise, the porn industry explosively grows, and transnational capitalism spreads due to government deregulation and privatization of media. As the media evolves, pornography has become more and more violent and non-consensual; this growth of ‘raunch culture’ reifies the traditional power balance between men and women in which men are dominant, and women are submissive. This male domination objectifies and commodifies women, reducing them to merely sexual objects for the gratification of men. Women are exposed to pornographic images at younger and younger ages, providing unhealthy sexual role models and teaching them lessons on sexual behavior before the onset of puberty. The increasingly sexualized depiction of women in particular positions them as appropriately desirable and available to men. As a result, women are not only viewed as sexual prey but also end up treating themselves primarily as sexual objects, basing their worth off of their sexuality alone. Although many scholars are aware of and have written on the great lack of agency exercised by women in these representations, the general public tends to view some of these women as being empowered, rather than exploited. Scholarly discourse is constrained by the popular misconception that the construction of women’s sexuality in the media is controlled by women themselves.

Keywords: construction of gender, hypersexualization, media, objectification

Procedia PDF Downloads 283

Authors: A. Ibovi Mouondayi, S. Zaher, R. Assadi, K. Erraoui, S. Sboul, J. Daoudim, S. Bousselham, K. Nassar, S. Janani

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INTRODUCTION: Neuropathic pain (NP) caused by damage to the somatosensory nervous system has a significant impact on quality of life and is associated with a high economic burden on the individual and society. The treatment of neuropathic pain consists of the use of a wide range of therapeutic agents, including gabapentin, which is used in the treatment of neuropathic pain. OBJECTIF: The objective of this study was to evaluate the efficacy and tolerance of gabapentin in the treatment of neuropathic pain. MATERIAL AND METHOD: This is a monocentric, cross-sectional, descriptive, retrospective study conducted in our department over a period of 19 months from October 2020 to April 2022. The missing parameters were collected during phone calls of the patients concerned. The diagnostic tool adopted was the DN4 questionnaire in the dialectal Arabic version. The impact of NP was assessed by the visual analog scale (VAS) on pain, sleep, and function. The impact of PN on mood was assessed by the "Hospital anxiety, and depression scale HAD" score in the validated Arabic version. The exclusion criteria were patients followed up for depression and other psychiatric pathologies. RESULTS: A total of 67 patients' data were collected. The average age was 64 years (+/- 15 years), with extremes ranging from 26 years to 94 years. 58 women and 9 men with an M/F sex ratio of 0.15. Cervical radiculopathy was found in 21% of this population, and lumbosacral radiculopathy in 61%. Gabapentin was introduced in doses ranging from 300 to 1800 mg per day with an average dose of 864 mg (+/- 346) per day for an average duration of 12.6 months. Before treatment, 93% of patients had a non-restorative sleep quality (VAS>3). 54% of patients had a pain VAS greater than 5. The function was normal in only 9% of patients. The mean anxiety score was 3.25 (standard deviation: 2.70), and the mean HAD depression score was 3.79 (standard deviation: 1.79). After treatment, all patients had improved the quality of their sleep (p<0.0001). A significant difference was noted in pain VAS, function, as well as anxiety and depression, and HAD score. Gabapentin was stopped for side effects (dizziness and drowsiness) and/or unsatisfactory response. CONCLUSION: Our data demonstrate a favorable effect of gabapentin on the management of neuropathic pain with a significant difference before and after treatment on the quality of life of patients associated with an acceptable tolerance profile.

Keywords: neuropathic pain, chronic pain, treatment, gabapentin

Procedia PDF Downloads 86

Authors: Wuttigrai Ngamsirijit

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Talent management in today’s modern organizations has become data-driven due to a demand for objective human resource decision making and development of analytics technologies. HR managers have been faced with some obstacles in exploiting data and information to obtain their effective talent management decisions. These include process-based data and records; insufficient human capital-related measures and metrics; lack of capabilities in data modeling in strategic manners; and, time consuming to add up numbers and make decisions. This paper proposes a framework of talent management through integration of talent value chain and human capital analytics approaches. It encompasses key data, measures, and metrics regarding strategic talent management decisions along the organizational and talent value chain. Moreover, specific predictive and prescriptive models incorporating these data and information are recommended to help managers in understanding the state of talent, gaps in managing talent and the organization, and the ways to develop optimized talent strategies.    

Keywords: decision making, human capital analytics, talent management, talent value chain

Procedia PDF Downloads 160

Authors: Evangelia Gaitanidou, Evangelos Bekiaris

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Considering that resilience implies the ability of a system to adapt continuously in order to respond to its operational goals, a system is considered as more or less resilient depending on the level and time of recovering from disruptive events and/or shocks to its initial state. Regarding transport systems, enhancing resilience is considered imperative for two main reasons: Such systems provide critical support to every socio-economic activity, while being one of the most important economic sectors and, secondly, the paths that convey people, goods and information, are the same through which risks are propagated. RESOLUTE (RESilience management guidelines and Operationalization appLied to Urban Transport Environment) Horizon 2020 research project is answering those needs, by proposing and testing a set of guidelines for resilience management of the urban transport system. The methods and steps towards this goal, through a step-wise methodology, taking into account established models like FRAM (Functional Resonance Analysis Model), and upon gathering existing practices are described in this paper, together with an overview of the produced guidelines. The overall aim is to create a framework which public transport authorities could consult and apply, for rendering their infrastructure resilient against natural disaster and other threats.

Keywords: guidelines, infrastructure, resilience, transport

Procedia PDF Downloads 232