Search results for: damage prediction models

Authors: K. Roushanger, A. Soleymanzadeh

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Weirs are structures often used in irrigation techniques, sewer networks and flood protection. However, the hydraulic behavior of this type of weir is complex and difficult to predict accurately. An accurate flow prediction over a weir mainly depends on the proper estimation of discharge coefficient. In this study, the Genetic Expression Programming (GEP) approach was used for predicting trapezoidal and rectangular sharp-crested side weirs discharge coefficient. Three different performance indexes are used as comparing criteria for the evaluation of the model’s performances. The obtained results approved capability of GEP in prediction of trapezoidal and rectangular side weirs discharge coefficient. The results also revealed the influence of downstream Froude number for trapezoidal weir and upstream Froude number for rectangular weir in prediction of the discharge coefficient for both of side weirs.

Keywords: discharge coefficient, genetic expression programming, trapezoidal weir

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Authors: S. Daqiqeh Rezaei, S. Mohajerzadeh, M. R. Sharifi

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Pedicle screws are used to stabilize vertebrae and treat several types of spinal diseases and injuries. Multiaxial pedicle screws are a type of pedicle screw that increase surgical versatility, but they also increase design complexity. Failure of multiaxial pedicle screws caused by static loading, dynamic loading and fatigue can lead to irreparable damage to the patient. Inappropriate deformation of the multiaxial pedicle screw tulip can cause system failure. Investigation of deformation and stress in these tulips can be employed to optimize multiaxial pedicle screw design. The sensitivity of this matter necessitates precise analyzing and modeling of pedicle screws. In this work, three commercial multiaxial pedicle screw tulips and a newly designed tulip are investigated using finite element analysis. Employing video measuring machine (VMM), tulips are modeled. Afterwards, utilizing ANSYS, static analysis is performed on these models. In the end, stresses and displacements of the models are compared.

Keywords: pedicle screw, multiaxial pedicle screw, finite element analysis, static analysis

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Authors: Subhankar Karmakar, Madhan Kumar Vasudevan, Manivannan Muniyandi

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Thermal Grill Illusion (TGI) elicits a strong and often painful sensation of burn when interlacing warm and cold stimuli that are individually non-painful, excites thermoreceptors beneath the skin. Among several theories of TGI, the “disinhibition” theory is the most widely accepted in the literature. According to this theory, TGI is the result of the disinhibition or unmasking of the pain-sensitive HPC (Heat-Pinch-Cold) nerve fibers due to the inhibition of cold-sensitive nerve fibers that are responsible for masking HPC nerve fibers. Although researchers focused on understanding TGI throughexperiments and models, none of them investigated the prediction of TGI pain intensity through a computational model. Furthermore, the comparison of psychophysically perceived TGI intensity with neurophysiological models has not yet been studied. The prediction of pain intensity through a computational model of TGI can help inoptimizing thermal displays and understanding pathological conditions related to temperature perception. The current studyfocuses on developing a computational model to predict the intensity of TGI pain and experimentally observe the perceived TGI pain. The computational model is developed based on the disinhibition theory and by utilizing the existing popular models of warm and cold receptors in the skin. The model aims to predict the neuronal activity of the HPC nerve fibers. With a temperature-controlled thermal grill setup, fifteen participants (ten males and five females) were presented with five temperature differences between warm and cold grills (each repeated three times). All the participants rated the perceived TGI pain sensation on a scale of one to ten. For the range of temperature differences, the experimentally observed perceived intensity of TGI is compared with the neuronal activity of pain-sensitive HPC nerve fibers. The simulation results show a monotonically increasing relationship between the temperature differences and the neuronal activity of the HPC nerve fibers. Moreover, a similar monotonically increasing relationship is experimentally observed between temperature differences and the perceived TGI intensity. This shows the potential comparison of TGI pain intensity observed through the experimental study with the neuronal activity predicted through the model. The proposed model intends to bridge the theoretical understanding of the TGI and the experimental results obtained through psychophysics. Further studies in pain perception are needed to develop a more accurate version of the current model.

Keywords: thermal grill Illusion, computational modelling, simulation, psychophysics, haptics

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Authors: Yu Zhang, Pedro Desouza

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Since big data has become substantially more accessible and manageable due to the development of powerful tools for dealing with unstructured data, people are eager to mine information from social media resources that could not be handled in the past. Sentiment analysis, as a novel branch of text mining, has in the last decade become increasingly important in marketing analysis, customer risk prediction and other fields. Scientists and researchers have undertaken significant work in creating and improving their sentiment models. In this paper, we present a concept of selecting appropriate classifiers based on the features and qualities of data sources by comparing the performances of five classifiers with three popular social media data sources: Twitter, Amazon Customer Reviews, and Movie Reviews. We introduced a couple of innovative models that outperform traditional sentiment classifiers for these data sources, and provide insights on how to further improve the predictive power of sentiment analysis. The modelling and testing work was done in R and Greenplum in-database analytic tools.

Keywords: sentiment analysis, social media, Twitter, Amazon, data mining, machine learning, text mining

Procedia PDF Downloads 336

Authors: Ekin Ozer

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Assessment of structural reliability is essential for efficient use of civil infrastructure which is subjected hazardous events. Dynamic analysis of finite element models is a commonly used tool to simulate structural behavior and estimate its performance accordingly. However, theoretical models purely based on preliminary assumptions and design drawings may deviate from the actual behavior of the structure. This study proposes up-to-date reliability estimation procedures which engages actual bridge vibration data modifying finite element models for finite element model updating and performing reliability estimation, accordingly. The proposed method utilizes vibration response measurements of bridge structures to identify modal parameters, then uses these parameters to calibrate finite element models which are originally based on design drawings. The proposed method does not only show that reliability estimation based on updated models differs from the original models, but also infer that non-updated models may overestimate the structural capacity.

Keywords: earthquake engineering, engineering vibrations, reliability estimation, structural health monitoring

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Authors: Malarvizhi Selvaraj, Paul Fergus, Andy Shaw

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Uterine contractions produced during labour have the potential to damage the foetus by diminishing the maternal blood flow to the placenta. In order to observe this phenomenon labour and delivery are routinely monitored using cardiotocography monitors. An obstetrician usually makes the diagnosis of foetus hypoxia by interpreting cardiotocography recordings. However, cardiotocography capture and interpretation is time-consuming and subjective, often lead to misclassification that causes damage to the foetus and unnecessary caesarean section. Both of these have a high impact on the foetus and the cost to the national healthcare services. Automatic detection of foetal heart rate may be an objective solution to help to reduce unnecessary medical interventions, as reported in several studies. This paper aim is to provide a system for better identification and interpretation of abnormalities of the fetal heart rate using RStudio. An open dataset of 552 Intrapartum recordings has been filtered with 0.034 Hz filters in an attempt to remove noise while keeping as much of the discriminative data as possible. Features were chosen following an extensive literature review, which concluded with FIGO features such as acceleration, deceleration, mean, variance and standard derivation. The five features were extracted from 552 recordings. Using these features, recordings will be classified either normal or abnormal. If the recording is abnormal, it has got more chances of hypoxia.

Keywords: cardiotocography, foetus, intrapartum, hypoxia

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Authors: O. A. Ajigini, E. N. Mwim

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Cybersecurity is the protection of computers, programs, networks, and data from attack, damage, unauthorised, unintended access, change, or destruction. Organisations collect, process and store their confidential and sensitive information on computers and transmit this data across networks to other computers. Moreover, the advent of internet technologies has led to various cyberattacks resulting in dangerous consequences for organisations. Therefore, with the increase in the volume and sophistication of cyberattacks, there is a need to develop models and make recommendations for the management of cybersecurity threats in organisations. This paper reports on various threats that cause malicious damage to organisations in cyberspace and provides measures on how these threats can be eliminated or reduced. The paper explores various aspects of protection measures against cybersecurity threats such as handling of sensitive data, network security, protection of information assets and cybersecurity awareness. The paper posits a model and recommendations on how to manage cybersecurity threats in organisations effectively. The model and the recommendations can then be utilised by organisations to manage the threats affecting their cyberspace. The paper provides valuable information to assist organisations in managing their cybersecurity threats and hence protect their computers, programs, networks and data in cyberspace. The paper aims to assist organisations to protect their information assets and data from cyberthreats as part of the contributions toward community engagement.

Keywords: confidential information, cyberattacks, cybersecurity, cyberspace, sensitive information

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Authors: Javad Khaligh, Aghileh Heydari, Ali Akbar Heydari

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Mathematical epidemiological models for the spread of disease through a population are used to predict the prevalence of a disease or to study the impacts of treatment or prevention measures. Initial conditions for these models are measured from statistical data collected from a population since these initial conditions can never be exact, the presence of chaos in mathematical models has serious implications for the accuracy of the models as well as how epidemiologists interpret their findings. This paper confirms the chaotic behavior of a model for dengue fever and SI by investigating sensitive dependence, bifurcation, and 0-1 test under a variety of initial conditions.

Keywords: epidemiological models, SEIR disease model, bifurcation, chaotic behavior, 0-1 test

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Authors: Kennedy Efosa Ehimwenma, Sujatha Krishnamoorthy, Safiya Al‑Sharji

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The probability computation of events is in the interval of [0, 1], which are values that are determined by the number of outcomes of events in a sample space S. The probability Pr(A) that an event A will never occur is 0. The probability Pr(B) that event B will certainly occur is 1. This makes both events A and B a certainty. Furthermore, the sum of probabilities Pr(E₁) + Pr(E₂) + … + Pr(Eₙ) of a finite set of events in a given sample space S equals 1. Conversely, the difference of the sum of two probabilities that will certainly occur is 0. This paper first discusses Bayes, the complement of probability, and the difference of probability for occurrences of learning-events before applying them in the prediction of learning objects in student learning. Given the sum of 1; to make a recommendation for student learning, this paper proposes that the difference of argMaxPr(S) and the probability of student-performance quantifies the weight of learning objects for students. Using a dataset of skill-set, the computational procedure demonstrates i) the probability of skill-set events that have occurred that would lead to higher-level learning; ii) the probability of the events that have not occurred that requires subject-matter relearning; iii) accuracy of the decision tree in the prediction of student performance into class labels and iv) information entropy about skill-set data and its implication on student cognitive performance and recommendation of learning.

Keywords: complement of probability, Bayes’ rule, prediction, pre-assessments, computational education, information theory

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Authors: Haj Najafi Leila, Tehranizadeh Mohsen

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Dependencies between diverse factors involved in probabilistic seismic loss evaluation are recognized to be an imperative issue in acquiring accurate loss estimates. Dependencies among component damage costs could be taken into account considering two partial distinct states of independent or perfectly-dependent for component damage states; however, in our best knowledge, there is no available procedure to take account of loss dependencies in story level. This paper attempts to present a method called "modal cost superposition method" for decoupling story damage costs subjected to earthquake ground motions dealt with closed form differential equations between damage cost and engineering demand parameters which should be solved in complex system considering all stories' cost equations by the means of the introduced "substituted matrixes of mass and stiffness". Costs are treated as probabilistic variables with definite statistic factors of median and standard deviation amounts and a presumed probability distribution. To supplement the proposed procedure and also to display straightforwardness of its application, one benchmark study has been conducted. Acceptable compatibility has been proven for the estimated damage costs evaluated by the new proposed modal and also frequently used stochastic approaches for entire building; however, in story level, insufficiency of employing modification factor for incorporating occurrence probability dependencies between stories has been revealed due to discrepant amounts of dependency between damage costs of different stories. Also, more dependency contribution in occurrence probability of loss could be concluded regarding more compatibility of loss results in higher stories than the lower ones, whereas reduction in incorporation portion of cost modes provides acceptable level of accuracy and gets away from time consuming calculations including some limited number of cost modes in high mode situation.

Keywords: dependency, story-cost, cost modes, engineering demand parameter

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Authors: Youcef Faci, Djillali Allou, Ahmed Mebtouche, Badredine Maalem

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The inclination of the bolt in a fastened joint of composite material during a tensile test can be influenced by several parameters, including material properties, bolt diameter and length, the type of composite material being used, the size and dimensions of the bolt, bolt preload, surface preparation, the design and configuration of the joint, and finally testing conditions. These parameters should be carefully considered and controlled to ensure accurate and reliable results during tensile testing of composite materials with fastened joints. Our work focuses on the effect of the stacking sequence and the geometry of specimens. An experimental test is carried out to obtain the inclination of a bolt during a tensile test of a composite material using acoustic emission and digital image correlation. Several types of damage were obtained during load. Digital image correlation techniques permit to obtain the inclination of bolt angle value during tensile test. We concluded that the inclination of the bolt during a tensile test of a composite material can be related to the damage that occurs in the material. It can cause stress concentrations and localized deformation in the material, leading to damage such as delamination, fiber breakage, matrix cracking, and other forms of failure.

Keywords: damage, digital image correlation, bolt inclination angle, joint

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Authors: Xiaodong Li, Peng Gao, Chao-Jung Huang, Shiying Hao, Xuefeng B. Ling, Yongxia Han, Yaqi Zhang, Le Zheng, Chengyin Ye, Modi Liu, Minjie Xia, Changlin Fu, Bo Jin, Karl G. Sylvester, Eric Widen

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Predicting the risk of Pancreatic Adenocarcinoma (PA) in advance can benefit the quality of care and potentially reduce population mortality and morbidity. The aim of this study was to develop and prospectively validate a risk prediction model to identify patients at risk of new incident PA as early as 3 months before the onset of PA in a statewide, general population in Maine. The PA prediction model was developed using Deep Neural Networks, a deep learning algorithm, with a 2-year electronic-health-record (EHR) cohort. Prospective results showed that our model identified 54.35% of all inpatient episodes of PA, and 91.20% of all PA that required subsequent chemoradiotherapy, with a lead-time of up to 3 months and a true alert of 67.62%. The risk assessment tool has attained an improved discriminative ability. It can be immediately deployed to the health system to provide automatic early warnings to adults at risk of PA. It has potential to identify personalized risk factors to facilitate customized PA interventions.

Keywords: cancer prediction, deep learning, electronic health records, pancreatic adenocarcinoma

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Authors: Jaroslav Masek, Juraj Camaj, Eva Nedeliakova

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The paper is focused on the operational model for transport the single wagon consignments on railway network by using two different models of train formation. The paper gives an overview of possibilities of improving the quality of transport services. Paper deals with two models used in problematic of train formatting - time continuously and time discrete. By applying these models in practice, the transport company can guarantee a higher quality of service and expect increasing of transport performance. The models are also applicable into others transport networks. The models supplement a theoretical problem of train formation by new ways of looking to affecting the organization of wagon flows.

Keywords: train formation, wagon flows, marshalling yard, railway technology

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Authors: M. Sadeghi, H. Pezeshk, R. Tusserkani, A. Sharifi Zarchi, A. Malekpour, M. Foroughmand, S. Goliaei, M. Totonchi, N. Ansari–Pour

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The role and relative importance of intrinsic and extrinsic factors in the development of complex diseases such as cancer still remains a controversial issue. Determining the amount of variation explained by these factors needs experimental data and statistical models. These models are nevertheless based on the occurrence and accumulation of random mutational events during stem cell division, thus rendering cancer development a stochastic outcome. We demonstrate that not only individual genome sequencing is uninformative in determining cancer risk, but also assigning a unique genome sequence to any given individual (healthy or affected) is not meaningful. Current whole-genome sequencing approaches are therefore unlikely to realize the promise of personalized medicine. In conclusion, since genome sequence differs from cell to cell and changes over time, it seems that determining the risk factor of complex diseases based on genome sequence is somewhat unrealistic, and therefore, the resulting data are likely to be inherently uninformative.

Keywords: cancer risk, extrinsic factors, genome sequencing, intrinsic factors

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Authors: Aboussalih Amira, Zarza Tahar, Fedaoui Kamel, Baroura Lazhar, Hammoudi Salah

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316 L steel is a stainless steel frequently used in orthopedic surgery; in the design of implants (hip, knee, shoulder, ankle, etc.), in dental surgery, cardiology, ophthalmology. Before any use, it is essential to predict the macroscopic phenomenological behavior of the material, and to analyze its response. The behavior of 316 L steel in low cycle fatigue, under uniaxial cyclic loading of tension/compression, producing significant plastic deformations leading to material damage. This investigation allowed us to characterize the behavior of the 316L steel employed in the locking of the compression plates (LCP), of which they are generally used in orthopedics to stabilize the fractured bone parts. And to perceive the phenomenon of Ratcheting leading to the damage of LCP by an excess of plastic deformation under nonsymmetrical alternated imposed constraint in low cycle fatigue.

Keywords: 316L SS, locking compression plate, low cycle fatigue, ratcheting

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Authors: Marine Segui, Ruxandra Mihaela Botez

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OpenVSP is an aerodynamic solver developed by National Aeronautics and Space Administration (NASA) that allows building a reliable model of an aircraft. This software performs an aerodynamic simulation according to the angle of attack of the aircraft makes between the incoming airstream, and its speed. A reliable aerodynamic model of the Cessna Citation X was designed but it required a lot of computation time. As a consequence, a prediction method was established that allowed predicting lift and drag coefficients for all Mach numbers and for all angles of attack, exclusively for stall conditions, from a computation of three angles of attack and only one Mach number. Aerodynamic coefficients given by the prediction method for a Cessna Citation X model were finally compared with aerodynamics coefficients obtained using a complete OpenVSP study.

Keywords: aerodynamic, coefficient, cruise, improving, longitudinal, openVSP, solver, time

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Authors: Yagya Murti Aryal, Bipin Adhikari, Pradeep Gyawali

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The Lesser Himalaya zone of Nepal consists of thrusting and folding belts, which play an important role in the sustainable management of groundwater in the Himalayan regions. The study area is located in the Dolakha and Ramechhap Districts of Bagmati Province, Nepal. Geologically, these districts are situated in the Lesser Himalayas and partly encompass the Higher Himalayan rock sequence, which includes low-grade to high-grade metamorphic rocks. Following the Gorkha Earthquake in 2015, numerous springs dried up, and many others are currently experiencing depletion due to the distortion of the natural groundwater flow. The primary objective of this study is to identify potential groundwater areas and determine suitable sites for artificial groundwater recharge. Two distinct statistical approaches were used to develop models: The Frequency Ratio (FR) and Shannon Entropy (SE) methods. The study utilized both primary and secondary datasets and incorporated significant role and controlling factors derived from field works and literature reviews. Field data collection involved spring inventory, soil analysis, lithology assessment, and hydro-geomorphology study. Additionally, slope, aspect, drainage density, and lineament density were extracted from a Digital Elevation Model (DEM) using GIS and transformed into thematic layers. For training and validation, 114 springs were divided into a 70/30 ratio, with an equal number of non-spring pixels. After assigning weights to each class based on the two proposed models, a groundwater potential map was generated using GIS, classifying the area into five levels: very low, low, moderate, high, and very high. The model's outcome reveals that over 41% of the area falls into the low and very low potential categories, while only 30% of the area demonstrates a high probability of groundwater potential. To evaluate model performance, accuracy was assessed using the Area under the Curve (AUC). The success rate AUC values for the FR and SE methods were determined to be 78.73% and 77.09%, respectively. Additionally, the prediction rate AUC values for the FR and SE methods were calculated as 76.31% and 74.08%. The results indicate that the FR model exhibits greater prediction capability compared to the SE model in this case study.

Keywords: groundwater potential mapping, frequency ratio, Shannon’s Entropy, Lesser Himalaya Zone, sustainable groundwater management

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Authors: Asim Alsharif, Christophe Pinna, Hassan Ghadbeigi

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The development of next-generation advanced high strength steels (AHSS) used in the automotive industry requires a better understanding of local deformation and damage development at the scale of their microstructures. This work is focused on dual-phase DP1000 steels and involves micro-mechanical tensile testing inside a scanning electron microscope (SEM) combined with digital image correlation (DIC) to quantify the heterogeneity of deformation in both ferrite and martensite and its evolution up to fracture. Natural features of the microstructure are used for the correlation carried out using Davis LaVision software. Strain localization is observed in both phases with tensile strain values up to 130% and 110% recorded in ferrite and martensite respectively just before final fracture. Damage initiation sites have been observed during deformation in martensite but could not be correlated to local strain values. A finite element (FE) model of the microstructure has then been developed using Abaqus to map stress distributions over representative areas of the microstructure by forcing the model to deform as in the experiment using DIC-measured displacement maps as boundary conditions. A MATLAB code has been developed to automatically mesh the microstructure from SEM images and to map displacement vectors from DIC onto the FE mesh. Results show a correlation of damage initiation at the interface between ferrite and martensite with local principal stress values of about 1700MPa in the martensite phase. Damage in ferrite is now being investigated, and results are expected to bring new insight into damage development in DP steels.

Keywords: advanced high strength steels, digital image correlation, finite element modelling, micro-mechanical testing

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Authors: Farzad Danaei, Yilmaz Akkaya

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In many civil engineering applications, especially in the construction of large concrete structures, the early age behavior of concrete has shown to be a crucial problem. The uneven rise in temperature within the concrete in these constructions is the fundamental issue for quality control. Therefore, developing accurate and fast temperature prediction models is essential. The thermal properties of concrete fluctuate over time as it hardens, but taking into account all of these fluctuations makes numerical models more complex. Experimental measurement of the thermal properties at the laboratory conditions also can not accurately predict the variance of these properties at site conditions. Therefore, specific heat capacity and the heat conductivity coefficient are two variables that are considered constant values in many of the models previously recommended. The proposed equations demonstrate that these two quantities are linearly decreasing as cement hydrates, and their value are related to the degree of hydration. The effects of changing the thermal conductivity and specific heat capacity values on the maximum temperature and the time it takes for concrete to reach that temperature are examined in this study using numerical sensibility analysis, and the results are compared to models that take a fixed value for these two thermal properties. The current study is conducted in 7 different mix designs of concrete with varying amounts of supplementary cementitious materials (fly ash and ground granulated blast furnace slag). It is concluded that the maximum temperature will not change as a result of the constant conductivity coefficient, but variable specific heat capacity must be taken into account, also about duration when a concrete's central node reaches its max value again variable specific heat capacity can have a considerable effect on the final result. Also, the usage of GGBFS has more influence compared to fly ash.

Keywords: early-age concrete, mass concrete, specific heat capacity, thermal conductivity coefficient

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Authors: Hasan G. Elmazoghi, Aisha I. Alzayani, Lubna S. Bentaher

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Rainfall is a highly non-linear phenomena, which requires application of powerful supervised data mining techniques for its accurate prediction. In this study the Artificial Neural Network (ANN) technique is used to predict the mean monthly historical rainfall data collected from BENINA station in Benghazi for 31 years, the period of “1977-2006” and the results are compared against the observed values. The specific objective to achieve this goal was to determine the best combination of weather variables to be used as inputs for the ANN model. Several statistical parameters were calculated and an uncertainty analysis for the results is also presented. The best ANN model is then applied to the data of one year (2007) as a case study in order to evaluate the performance of the model. Simulation results reveal that application of ANN technique is promising and can provide reliable estimates of rainfall.

Keywords: neural networks, rainfall, prediction, climatic variables

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Authors: Ifigeneia V. Mavragani, Zacharenia Nikitaki, George Kalantzis, George Iliakis, Alexandros G. Georgakilas

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Complex DNA damage consisting of a combination of DNA lesions, such as Double Strand Breaks (DSBs) and non-DSB base lesions occurring in a small volume is considered as one of the most important biological endpoints regarding ionizing radiation (IR) exposure. Strong theoretical (Monte Carlo simulations) and experimental evidence suggests an increment of the complexity of DNA damage and therefore repair resistance with increasing linear energy transfer (LET). Experimental detection of complex (clustered) DNA damage is often associated with technical deficiencies limiting its measurement, especially in cellular or tissue systems. Our groups have recently made significant improvements towards the identification of key parameters relating to the efficient detection of complex DSBs and non-DSBs in human cellular systems exposed to IR of varying quality (γ-, X-rays 0.3-1 keV/μm, α-particles 116 keV/μm and 36Ar ions 270 keV/μm). The induction and processing of DSB and non-DSB-oxidative clusters were measured using adaptations of immunofluorescence (γH2AX or 53PB1 foci staining as DSB probes and human repair enzymes OGG1 or APE1 as probes for oxidized purines and abasic sites respectively). In the current study, Relative Biological Effectiveness (RBE) values for DSB and non-DSB induction have been measured in different human normal (FEP18-11-T1) and cancerous cell lines (MCF7, HepG2, A549, MO59K/J). The experimental results are compared to simulation data obtained using a validated microdosimetric fast Monte Carlo DNA Damage Simulation code (MCDS). Moreover, this simulation approach is implemented in two realistic clinical cases, i.e. prostate cancer treatment using X-rays generated by a linear accelerator and a pediatric osteosarcoma case using a 200.6 MeV proton pencil beam. RBE values for complex DNA damage induction are calculated for the tumor areas. These results reveal a disparity between theory and experiment and underline the necessity for implementing highly precise and more efficient experimental and simulation approaches.

Keywords: complex DNA damage, DNA damage simulation, protons, radiotherapy

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

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

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

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Authors: Zouhour Neji Ben Salem

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Microscopic evacuation focuses on the evacuee behavior and way of search of safety place in an egress situation. In recent years, several models handled microscopic evacuation problem. Among them, we have proposed Artificial Neural Network (ANN) as an alternative to mathematical models that can deal with such problem. In this paper, we present two ANN models: SOM map and Hopfield Network used to predict the evacuee behavior in a disaster situation. These models are tested in a real case, the second floor of Tunisian children hospital evacuation in case of fire. The two models are studied and compared in order to evaluate their performance.

Keywords: artificial neural networks, self-organization map, hopfield network, microscopic evacuation, fire building evacuation

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Authors: Hamza Nejib, Okba Taouali

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This paper presents two of the most knowing kernel adaptive filtering (KAF) approaches, the kernel least mean squares and the kernel recursive least squares, in order to predict a new output of nonlinear signal processing. Both of these methods implement a nonlinear transfer function using kernel methods in a particular space named reproducing kernel Hilbert space (RKHS) where the model is a linear combination of kernel functions applied to transform the observed data from the input space to a high dimensional feature space of vectors, this idea known as the kernel trick. Then KAF is the developing filters in RKHS. We use two nonlinear signal processing problems, Mackey Glass chaotic time series prediction and nonlinear channel equalization to figure the performance of the approaches presented and finally to result which of them is the adapted one.

Keywords: online prediction, KAF, signal processing, RKHS, Kernel methods, KRLS, KLMS

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Authors: Ashirgul Kozhagulova, Ainash Shabdirova, Galym Tokazhanov, Minh Nguyen

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The synthetic rocks have been advantageous over the natural rocks in terms of availability and the consistent studying the impact of a particular parameter. The artificial rocks can be fabricated using variety of techniques such as mixing sand and Portland cement or gypsum, firing the mixture of sand and fine powder of borosilicate glass or by in-situ precipitation of calcite solution. In this study, sodium silicate solution has been used as the cementing agent for the quartz sand. The molded soft cylindrical sandstone samples are placed in the gas-tight pressure vessel, where the hardening of the material takes place as the chemical reaction between carbon dioxide and the silicate solution progresses. The vessel allows uniform disperse of carbon dioxide and control over the ambient gas pressure. Current paper shows how the bonding material is initially distributed in the intergranular space and the surface of the sand particles by the usage of Electron Microscopy and the Energy Dispersive Spectroscopy. During the study, the strength of the cement bond as a function of temperature is observed. The impact of cementing agent dosage on the micro and macro characteristics of the sandstone is investigated. The analysis of the cement bond at micro level helps to trace the changes to particles bonding damage after a potential yielding. Shearing behavior and compressional response have been examined resulting in the estimation of the shearing resistance and cohesion force of the sandstone. These are considered to be main input values to the mathematical prediction models of sand production from weak clastic oil reservoir formations.

Keywords: artificial sanstone, cement bond, microstructure, SEM, triaxial shearing

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Authors: Marisa Chrysochoou, James Mahoney, Kay Wille

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Pyrrhotite is an iron-sulfide mineral which releases sulfuric acid when exposed to water and oxygen. The presence of this mineral in concrete foundations across Connecticut and Massachusetts in the US is causing in some cases premature failure. This has resulted in a devastating crisis for all parties affected by this type of failure which can take up to 15-25 years before internal damage becomes visible on the surface. This study shares laboratory results aimed to investigate the fundamental mechanisms of pyrrhotite reaction and to further the understanding of its deterioration kinetics within concrete. This includes the following analyses: total sulfur, wavelength dispersive X-ray fluorescence, expansion, reaction rate combined with ion-chromatography, as well as damage evolution using electro-chemical acceleration. This information is coupled to a statistical analysis of over 150 analyzed concrete foundations. Those samples were obtained and process using a developed and validated sampling method that is minimally invasive to the foundation in use, provides representative samples of the concrete matrix across the entire foundation, and is time and cost-efficient. The processed samples were then analyzed using a developed modular testing method based on total sulfur and wavelength dispersive X-ray fluorescence analysis to quantify the amount of pyrrhotite. As part of the statistical analysis the results were grouped into the following three categories: no damage observed and no pyrrhotite detected, no damage observed and pyrrhotite detected and damaged observed and pyrrhotite detected. As expected, a strong correlation between amount of pyrrhotite, age of the concrete and damage is observed. Information from the laboratory investigation and from the statistical analysis of field samples will aid in forming a scientific basis to support the decision process towards sustainable financial and administrative solutions by state and local stakeholders.

Keywords: concrete, pyrrhotite, risk of failure, statistical analysis

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Authors: Yuan Yue, Wen-Wei Wang

Abstract:

The objective of this research is to comprehensively evaluate the impact of alkaline environments on the durability of Glass Fiber Reinforced Polymer (GFRP) reinforcements in concrete structures and further explore their potential value within the construction industry. Specifically, we investigate the effects of two widely used high-performance concrete (HPC) materials on the durability of GFRP bars when embedded within them under varying temperature conditions. A total of 279 GFRP bar specimens were manufactured for microcosmic and mechanical performance tests. Among them, 270 specimens were used to test the residual tensile strength after 120 days of immersion, while 9 specimens were utilized for microscopic testing to analyze degradation damage. SEM techniques were employed to examine the microstructure of GFRP and cover concrete. Unidirectional tensile strength experiments were conducted to determine the remaining tensile strength after corrosion. The experimental variables consisted of four types of concrete (engineering cementitious composite (ECC), ultra-high-performance concrete (UHPC), and two types of ordinary concrete with different compressive strengths) as well as three acceleration temperatures (20, 40, and 60℃). The experimental results demonstrate that high-performance concrete (HPC) offers superior protection for GFRP bars compared to ordinary concrete. Two types of HPC enhance durability through different mechanisms: one by reducing the pH of the concrete pore fluid and the other by decreasing permeability. For instance, ECC improves embedded GFRP's durability by lowering the pH of the pore fluid. After 120 days of immersion at 60°C under accelerated conditions, ECC (pH=11.5) retained 68.99% of its strength, while PC1 (pH=13.5) retained 54.88%. On the other hand, UHPC enhances FRP steel's durability by increasing porosity and compactness in its protective layer to reinforce FRP reinforcement's longevity. Due to fillers present in UHPC, it typically exhibits lower porosity, higher densities, and greater resistance to permeation compared to PC2 with similar pore fluid pH levels, resulting in varying degrees of durability for GFRP bars embedded in UHPC and PC2 after 120 days of immersion at a temperature of 60°C - with residual strengths being 66.32% and 60.89%, respectively. Furthermore, SEM analysis revealed no noticeable evidence indicating fiber deterioration in any examined specimens, thus suggesting that uneven stress distribution resulting from interface segregation and matrix damage emerges as a primary causative factor for tensile strength reduction in GFRP rather than fiber corrosion. Moreover, long-term prediction models were utilized to calculate residual strength values over time for reinforcement embedded in HPC under high temperature and high humidity conditions - demonstrating that approximately 75% of its initial strength was retained by reinforcement embedded in HPC after 100 years of service.

Keywords: GFRP bars, HPC, degeneration, durability, residual tensile strength.

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Authors: Osariyekemwen, Daniel Nosakhare

Abstract:

Some ceramic wastes, such as discarded (condemn) Plaster of Paris (POP) in Auchi Polytechnic, Edo State, constitute environmental hazards. This study, therefore, bridges the forgoing gaps by undertaking the use of these discarded (POP) moulds to produced ceramic models for making casting moulds for mass production. This is in line with the possibility of using this medium to properly manage the discarded (condemn) Plaster of Paris (POP) that littered our immediate environment. Presently these are major wastes disposal in the department. Hence, the study has been made to fabricate sanitary miniature models and contract fuse models, respectively. Findings arising from this study show that discarded (condemn) Plaster of Paris (POP) can be carved when to set it neither shrink nor expand; hence warping is quite unusual. Above all, it also gives good finishing with little deterioration with time when compared to clay models.

Keywords: plaster of Paris, condemn, moulds, models, production

Procedia PDF Downloads 169

Authors: Tiberiu Socaciu, Tudor Colomeischi, Eugenia Iancu

Abstract:

Business failure affects in various proportions shareholders, managers, lenders (banks), suppliers, customers, the financial community, government and society as a whole. In the era in which we have telecommunications networks, exists an interdependence of markets, the effect of a failure of a company is relatively instant. To effectively manage risk exposure is thus require sophisticated support systems, supported by analytical tools to measure, monitor, manage and control operational risks that may arise. As we know, bankruptcy is a phenomenon that managers do not want no matter what stage of life is the company they direct / lead. In the analysis made by us, by the nature of economic models that are reviewed (Altman, Conan-Holder etc.), estimating the risk of bankruptcy of a company corresponds to some extent with its own business cycle tracing of the company. Various models for predicting bankruptcy take into account direct / indirect aspects such as market position, company growth trend, competition structure, characteristics and customer retention, organization and distribution, location etc. From the perspective of our research we will now review the economic models known in theory and practice for estimating the risk of bankruptcy; such models are based on indicators drawn from major accounting firms.

Keywords: Anglo-Saxon models, continental models, national models, statistical models

Procedia PDF Downloads 386

Authors: Szu-Chieh Yu, Pei-Chin Chiand, Chih-Yi Lin, Yi-Wen Chien

Abstract:

UV radiation from sunlight cause numbers of acute and chronic skin damage which can result in inflammation, immune changes, physical changes and DNA damage that facilitates skin aging and the development of skin carcinogenesis. Reactive oxygen species (ROS) are generated by excessive solar UV radiation, resulting in oxidative damage to cellar components, proteins, lipids, and nucleic acids. Thus, antioxidation plays an important role that protects skin against ROS-induced injury. Safflower (Carthamus tinctorius L.) is an important Chinese medicine contained abundance flavones and hydroxysafflor yellow A (HSYA) which is main active ingredient. HSYA is part of quinochalcone and has unique structures of hydroxy groups that provided the antioxidant effect. In this study, the aim was to investigate the protective role of HYSA in human keratinocytes (HaCaT) against UVA-induced oxidative damage and the possible mechanism. The HaCaT cells were UVA-irradiated and the effects of HYSA on cell viability, reactive oxygen species generation, DNA fragmentation and lipid peroxidation were measured. The mRNA expression of matrix metalloproteinase Ι (MMP Ι), cyclooxygenase-2 (COX-2) were determined by RT-PCR. In this study, UVA exposure lead to decrease in cell viability and increase in reactive oxygen species generation in HaCaT cells. HYSA could effectively increase the viability of HaCaT cells after UVA exposure and protect them from UVA-induced oxidative stress. Moreover, HYSA can reduce inflammation through inhibition the mRNA expression of MMP Ι and COX-2. Our results suggest that HSYA can act as a free radical scavenger while keratinocytes were photodamaged. HYSA could be a useful natural medicine for the protection of epidermal cells from UVA-induced damage and will be developed into products for skin care.

Keywords: HaCaT keratinocytes, hydroxysafflor yellow A (HSYA), MMP Ι, oxidative stress

Procedia PDF Downloads 366