Search results for: prognosis prediction

Authors: O. B. Iskender, K. V. Ling, V. Dubanchet, L. Simonini

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This paper discusses the recent advances and future prospects of spacecraft position and attitude control using Model Predictive Control (MPC). First, the challenges of the space missions are summarized, in particular, taking into account the errors, uncertainties, and constraints imposed by the mission, spacecraft and, onboard processing capabilities. The summary of space mission errors and uncertainties provided in categories; initial condition errors, unmodeled disturbances, sensor, and actuator errors. These previous constraints are classified into two categories: physical and geometric constraints. Last, real-time implementation capability is discussed regarding the required computation time and the impact of sensor and actuator errors based on the Hardware-In-The-Loop (HIL) experiments. The rationales behind the scenarios’ are also presented in the scope of space applications as formation flying, attitude control, rendezvous and docking, rover steering, and precision landing. The objectives of these missions are explained, and the generic constrained MPC problem formulations are summarized. Three key design elements used in MPC design: the prediction model, the constraints formulation and the objective cost function are discussed. The prediction models can be linear time invariant or time varying depending on the geometry of the orbit, whether it is circular or elliptic. The constraints can be given as linear inequalities for input or output constraints, which can be written in the same form. Moreover, the recent convexification techniques for the non-convex geometrical constraints (i.e., plume impingement, Field-of-View (FOV)) are presented in detail. Next, different objectives are provided in a mathematical framework and explained accordingly. Thirdly, because MPC implementation relies on finding in real-time the solution to constrained optimization problems, computational aspects are also examined. In particular, high-speed implementation capabilities and HIL challenges are presented towards representative space avionics. This covers an analysis of future space processors as well as the requirements of sensors and actuators on the HIL experiments outputs. The HIL tests are investigated for kinematic and dynamic tests where robotic arms and floating robots are used respectively. Eventually, the proposed algorithms and experimental setups are introduced and compared with the authors' previous work and future plans. The paper concludes with a conjecture that MPC paradigm is a promising framework at the crossroads of space applications while could be further advanced based on the challenges mentioned throughout the paper and the unaddressed gap.

Keywords: convex optimization, model predictive control, rendezvous and docking, spacecraft autonomy

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Authors: Shun-Qi Zhang, Shu-Yang Zhang, Min Chen

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Applying strong electric field on piezoelectric actuators, on one hand very significant electroelastic material nonlinear effects will occur, on the other hand piezo plates and shells may undergo large displacements and rotations. In order to give a precise prediction of piezolaminated smart structures under large electric field, this paper develops a finite element (FE) model accounting for both electroelastic material nonlinearity and geometric nonlinearity with large rotations based on the first order shear deformation (FSOD) hypothesis. The proposed FE model is applied to analyze a piezolaminated semicircular shell structure.

Keywords: smart structures, piezolamintes, material nonlinearity, strong electric field

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Authors: Majdi M. Alomari, Nafesah I. Alshdaifat, Mohammad S. Widyan

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Different countries have introduced different schemes and policies to counter global warming. The rationale behind the proposed policies and the potential barriers to successful implementation of the policies adopted by the countries were analyzed and estimated based on different models. It is argued that these models enhance the transparency and provide a better understanding to the policy makers. However, these models are underpinned with several structural and baseline assumptions. These assumptions, modeling features and future prediction of emission reductions and other implication such as cost and benefits of a transition to a low-carbon economy and its economy wide impacts were discussed. On the other hand, there are potential barriers in the form political, financial, and cultural and many others that pose a threat to the mitigation options.

Keywords: energy models, environmental policy instruments, mitigating CO2 emission, economic wide impact

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Authors: J. H. Kim, J. H. Kwon, J. S. Park, K. J. Lim

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This paper has investigated a technique that predicts the performance of a bar-type unimorph piezoelectric vibration actuator depending on the frequency. This paper has been proposed an equivalent circuit that can be easily analyzed for the bar-type unimorph piezoelectric vibration actuator. In the dynamic analysis, rigidity and resonance frequency, which are important mechanical elements, were derived using the basic beam theory. In the equivalent circuit analysis, the displacement and bandwidth of the piezoelectric vibration actuator depending on the frequency were predicted. Also, for the reliability of the derived equations, the predicted performance depending on the shape change was compared with the result of a finite element analysis program.

Keywords: actuator, piezoelectric, performance, unimorph

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Authors: Elyce Cardonick, Shistri Dhar, Linsdey Seidman

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Background: When breast cancer is diagnosed during pregnancy, the prognosis is comparable to non-pregnant women matched for prognostic indicators when pregnant women receive treatment without delay. Chemotherapy, including taxanes, can be given during pregnancy with normal neonatal development in exposed fetuses. Methods: Cases of primary breast cancer were extracted from the Cancer and Pregnancy Registry and longitudinal study at Cooper Medical School, which collects cases of pregnant women diagnosed and treated for cancer into a single database. Obstetrical, oncology and pediatric records were reviewed, including annual neonatal developmental, behavioral and medical assessments. Results: 270 pregnant women were diagnosed with primary breast cancer at a mean gestational age of 14.7+9weeks. Mean maternal age at diagnosis 34.5+4.5 years. Receptor status is comparable to non-pregnant women of reproductive age. Forty-nine women were advised to terminate. Two hundred two women underwent surgery;244 women received chemotherapy in pregnancy after the first trimester; the majority of Doxorubucin/Cytoxan; 81 of the cases included a taxane. At a mean of 90 months, follow up obtained on 255 newborns.192/255 newborns are meeting developmental milestones. Respiratory illnesses, including asthma, and bronchiolitis, were reported in 64 newborns, the most common medical condition reported. Thirty-one children are undergoing treatment for GERD, 11 for urinary tract infections, and 7 are undergoing treatment for anemia. Twenty-six children with expressive or articulation language delays, 21/26 are mild. Eleven children with gross/ 7 with fine motor delays. Eight children are treated for ADHD, 4 for anxiety and 4 have social skill impairment. The majority of children with developmental, language or motor delays were born preterm. Conclusion: After chemotherapy exposure in utero for breast cancer, the majority of newborns are meeting developmental milestones and are medically healthy. The goal for treating pregnant women with breast cancer is to aim for delivery close to the term.

Keywords: breast cancer, pregnancy, chemotherapy, newborn

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Authors: Saurabh Sharma, Yong Sun, Bruce Vernham

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Accurate prediction of NOx emission is a continuous challenge in the field of diesel engine-out emission modeling. Performing experiments for each conditions and scenario cost significant amount of money and man hours, therefore model-based development strategy has been implemented in order to solve that issue. NOx formation is highly dependent on the burn gas temperature and the O₂ concentration inside the cylinder. The current empirical models are developed by calibrating the parameters representing the engine operating conditions with respect to the measured NOx. This makes the prediction of purely empirical models limited to the region where it has been calibrated. An alternative solution to that is presented in this paper, which focus on the utilization of in-cylinder combustion parameters to form a predictive semi-empirical NOx model. The result of this work is shown by developing a fast and predictive NOx model by using the physical parameters and empirical correlation. The model is developed based on the steady state data collected at entire operating region of the engine and the predictive combustion model, which is developed in Gamma Technology (GT)-Power by using Direct Injected (DI)-Pulse combustion object. In this approach, temperature in both burned and unburnt zone is considered during the combustion period i.e. from Intake Valve Closing (IVC) to Exhaust Valve Opening (EVO). Also, the oxygen concentration consumed in burnt zone and trapped fuel mass is also considered while developing the reported model.  Several statistical methods are used to construct the model, including individual machine learning methods and ensemble machine learning methods. A detailed validation of the model on multiple diesel engines is reported in this work. Substantial numbers of cases are tested for different engine configurations over a large span of speed and load points. Different sweeps of operating conditions such as Exhaust Gas Recirculation (EGR), injection timing and Variable Valve Timing (VVT) are also considered for the validation. Model shows a very good predictability and robustness at both sea level and altitude condition with different ambient conditions. The various advantages such as high accuracy and robustness at different operating conditions, low computational time and lower number of data points requires for the calibration establishes the platform where the model-based approach can be used for the engine calibration and development process. Moreover, the focus of this work is towards establishing a framework for the future model development for other various targets such as soot, Combustion Noise Level (CNL), NO₂/NOx ratio etc.

Keywords: diesel engine, machine learning, NOₓ emission, semi-empirical

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Authors: Z. Sadeghi, M. R. Omidkhah, M. E. Masoomi

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The purpose of this paper is to examine gas transport behavior of mixed matrix membranes (MMMs) combined with porous particles. Main existing models are categorized in two main groups; two-phase (ideal contact) and three-phase (non-ideal contact). A new coefficient, J, was obtained to express equations for estimating effect of the particle porosity in two-phase and three-phase models. Modified models evaluates with existing models and experimental data using Matlab software. Comparison of gas permeability of proposed modified models with existing models in different MMMs shows a better prediction of gas permeability in MMMs.

Keywords: mixed matrix membrane, permeation models, porous particles, porosity

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Authors: Shabnam Abdi, Behzad Toosi

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Background: Melanoma is the most lethal type of malignant skin cancer in humans and dogs since it spreads rapidly throughout the body. Despite significant advances in treatment, cancer at an advanced stage has a poor prognosis. Hence, more effective treatments are needed to enhance outcomes with fewer side effects. Erythropoietin-producing hepatocellular receptors are the largest family of receptor tyrosine kinases and are divided into two subfamilies, EphA and EphB, both of which play a significant role in disease, especially cancer. Due to their association with proliferation and invasion in many aggressive types of cancer, Eph receptor tyrosine kinases (Eph RTKs) are promising cancer therapy molecules. Because these receptors have not been studied in canine melanoma, we investigated how EphA2 influences survival and tumorigenicity of melanoma cells. Methods: Expression of EphA2 protein in canine melanoma cell lines and human melanoma cell line was evaluated by Western blot. Melanoma cells were transduced with lentiviral particles encoding Eph-targeting shRNAs or non-silencing shRNAs (control) for silencing the expression of EphA2 receptor, and silencing was confirmed by Western blotting and immunofluorescence. The effect of siRNA treatment on cellular proliferation, colony formation, tumorsphere assay, invasion was analyzed by Resazurin assay Matrigel invasion assay, respectively. Results: Expression of EphA2 was detected in canine and human melanoma cell lines. Moreover, stably silencing EphA2 by specific shRNAs significantly and consistently decreased the expression of EphA2 protein in both human and canine melanoma cells. Proliferation, colony formation, tumorsphere and invasion of melanoma cells were significantly decreased in EphA2 siRNA-treated cells compared to control. Conclusion: Our data provide the first functional evidence that the EphA2 receptor plays a critical role in the malignant cellular behavior of melanoma in both human and dogs.

Keywords: ephA2, targeting, melanoma, human, canine

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Authors: Vitalijs Lusis, Andrejs Krasnikovs

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Fiber reinforced concrete is important material for load bearing structural elements. Usually fibers are homogeneously distributed in a concrete body having arbitrary spatial orientations. At the same time, in many situations, fiber concrete with oriented fibers is more optimal. Is obvious, that is possible to create constructions with oriented short fibers in them, in different ways. Present research is devoted to one of such approaches- fiber reinforced concrete prisms having dimensions 100 mm×100 mm×400 mm with layers of non-homogeneously distributed fibers inside them were fabricated. Simultaneously prisms with homogeneously dispersed fibers were produced for reference as well. Prisms were tested under four point bending conditions. During the tests vertical deflection at the center of every prism and crack opening were measured (using linear displacements transducers in real timescale). Prediction results were discussed.

Keywords: fiber reinforced concrete, 4-point bending, steel fiber, construction engineering

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Authors: F. Louati, H. Trabelsi, M. Jamei

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Desiccation cracks following drainage-humidification cycles. With water loss, mainly due to evaporation, suction in the soil increases, producing volumetric shrinkage and tensile stress. When the tensile stress reaches tensile strength, the soil cracks. Desiccation cracks networks can directly control soil hydraulic properties. The aim of this study was for quantifying the hydraulic properties for examples the water retention curve, the saturated hydraulic conductivity, the unsaturated hydraulic conductivity function, the shrinkage dynamics in Tibar soil- clay soil in the Northern of Tunisia. Then a numerical simulation of unsaturated hydraulic properties for a crack network has been attempted. The finite elements code ‘CODE_BRIGHT’ can be used to follow the hydraulic distribution in cracked porous media.

Keywords: desiccation, cracks, permeability, unsaturated hydraulic flow, simulation

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Authors: Reda Mankbadi

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In this paper we explore the use of a second-order unstructured-grid, finite-volume code for direct noise prediction. We consider a Mach 1.5 jet impinging on a perpendicular flat plate. Hybrid LES-RANS simulations are used to calculate directly both the flow field and the radiated sound. The ANSYS Fluent commercial code is utilized for the calculations. The acoustic field is obtained directly from the simulations and is compared with the integral approach of Ffowcs Williams-Hawkings (FWH). Results indicate the existence of a preferred radiation angle. The spectrum obtained is in good agreement with observations. This points out to the possibility of handling the effects of complicated geometries on noise radiation by using unstructured second-orders codes.

Keywords: CFD, Ffowcs Williams-Hawkings (FWH), imping jet, ANSYS fluent commercial code, hybrid LES-RANS simulations

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Authors: Debjit Ray

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Horizontal gene transfer (HGT) and recombination leads to the emergence of bacterial antibiotic resistance and pathogenic traits. HGT events can be identified by comparing a large number of fully sequenced genomes across a species or genus, define the phylogenetic range of HGT, and find potential sources of new resistance genes. In-depth comparative phylogenomics can also identify subtle genome or plasmid structural changes or mutations associated with phenotypic changes. Comparative phylogenomics requires that accurately sequenced, complete and properly annotated genomes of the organism. Assembling closed genomes requires additional mate-pair reads or “long read” sequencing data to accompany short-read paired-end data. To bring down the cost and time required of producing assembled genomes and annotating genome features that inform drug resistance and pathogenicity, we are analyzing the performance for genome assembly of data from the Illumina NextSeq, which has faster throughput than the Illumina HiSeq (~1-2 days versus ~1 week), and shorter reads (150bp paired-end versus 300bp paired end) but higher capacity (150-400M reads per run versus ~5-15M) compared to the Illumina MiSeq. Bioinformatics improvements are also needed to make rapid, routine production of complete genomes a reality. Modern assemblers such as SPAdes 3.6.0 running on a standard Linux blade are capable in a few hours of converting mixes of reads from different library preps into high-quality assemblies with only a few gaps. Remaining breaks in scaffolds are generally due to repeats (e.g., rRNA genes) are addressed by our software for gap closure techniques, that avoid custom PCR or targeted sequencing. Our goal is to improve the understanding of emergence of pathogenesis using sequencing, comparative genomics, and machine learning analysis of ~1000 pathogen genomes. Machine learning algorithms will be used to digest the diverse features (change in virulence genes, recombination, horizontal gene transfer, patient diagnostics). Temporal data and evolutionary models can thus determine whether the origin of a particular isolate is likely to have been from the environment (could it have evolved from previous isolates). It can be useful for comparing differences in virulence along or across the tree. More intriguing, it can test whether there is a direction to virulence strength. This would open new avenues in the prediction of uncharacterized clinical bugs and multidrug resistance evolution and pathogen emergence.

Keywords: genomics, pathogens, genome assembly, superbugs

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Authors: S. Bennoud, M. Zergoug

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The numerical simulation of electromagnetic interactions is still a challenging problem, especially in problems that result in fully three dimensional mathematical models. The goal of this work is to use mathematical modeling to characterize the reliability and capacity of eddy current technique to detect and characterize defects embedded in aeronautical in-service pieces. The finite element method is used for describing the eddy current technique in a mathematical model by the prediction of the eddy current interaction with defects. However, this model is an approximation of the full Maxwell equations. In this study, the analysis of the problem is based on a three dimensional finite element model that computes directly the electromagnetic field distortions due to defects.

Keywords: eddy current, finite element method, non destructive testing, numerical simulations

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Authors: Shadia Al-Bahlani, Ruqaya Al-Rashdi, Shadia Al-Sinawi, Maya Al-Bahri

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Background: Breast cancer is the most common cancer in women worldwide. Triple-negative breast cancer (TNBC) is an aggressive type of breast cancer, which is defined by the absence of Estrogen (ER), Progesterone (PR) and Human epidermal growth factor (Her-2) receptors. The calpain system plays an important role in many cellular processes including apoptosis, necrosis, cell signaling and proliferation. The role of clapins in pathogenesis and tumor progression has been studied in certain cancer types; however, its definite role is not yet established in breast cancer especially in the TNBC subtype. Objectives: This study aims to measure calpain-1 expression and correlate this measurement with the proliferating/apoptotic index as well with the prognostic factors in TNBC patients’ tissue. Materials and Methods: Thirty nine paraffin blocks from patients diagnosed with TNBC were used to measure the expression of calpain-1 and Ki-67 (proliferating marker) proteins using immunohistochemistry. Apoptosis was assessed morphological and biochemically using conventional Haematoxylin and Eosin (H&E) staining method and terminal deoxynucleotidyl transferase-mediate dUTP nick and labeling (TUNEL) assay respectively. Data was statistically analyzed using Pearson X2 test of association. Results: Calpain-1 content was visualized in the nucleus of the TNBC cells and its expression varied from low to high among the patients tissue. Calpain expression showed no significant correlation with the proliferating/apoptotic index as well with the clinicopathological variables. Apoptotic counts quantified by H&E staining showed significant association with the apoptotic TUNEL assay, validating both approaches. Conclusion: Although calpain-1 expression showed no significant association with the clinical outcome, its variable level of expression might indicate a hidden role in breast cancer tissue. Larger number of samples and different mode of assessments are needed to fully investigate such role. Exploring the involvement of calpain-1 in cancer progression might help in considering it as a biomarker of breast cancer.

Keywords: breast cancer, calpain, apoptosis, prognosis

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Authors: S. Ghafoori, A. Al-Harbi, B. Al-Ajmi, A. Al-Shaalan, A. Al-Ajmi, M. Ali Juma

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Seismic methods play an important role in the exploration for hydrocarbon reservoirs. However, the success of the method depends strongly on the reliability of the measured or predicted information regarding the velocity of sound in the media. Speed of sound has been used to study the thermodynamic properties of fluids. In this study, experimental data are reported and analyzed on the speed of sound in toluene and octane binary mixture. Three-factor three-level Box-Benhkam design is used to determine the significance of each factor, the synergetic effects of the factors, and the most significant factors on speed of sound. The developed mathematical model and statistical analysis provided a critical analysis of the simultaneous interactive effects of the independent variables indicating that the developed quadratic models were highly accurate and predictive.

Keywords: experimental design, octane, speed of sound, toluene

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Authors: Soo-Yong Cho, Chong-Hyun Cho, Chae-Whan Rim, Sang-Kyu Choi, Jin-Gyun Kim, Ju-Seok Nam

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Recently, vertical axis wind turbines (VAWT) have been widely used to produce electricity even in urban. They have several merits such as low sound noise, easy installation of the generator and simple structure without yaw-control mechanism and so on. However, their blades are operated under the influence of the trailing vortices generated by the preceding blades. This phenomenon deteriorates its output power and makes difficulty predicting correctly its performance. In order to improve the performance of VAWT, wind power towers can be applied. Usually, the wind power tower can be constructed as a multi-story building to increase the frontal area of the wind stream. Hence, multiple sets of the VAWT can be installed within the wind power tower, and they can be operated at high elevation. Many different types of wind power tower can be used in the field. In this study, a wind power tower with circular column shape was applied, and the VAWT was installed at the center of the wind power tower. Seven guide walls were used as a strut between the floors of the wind power tower. These guide walls were utilized not only to increase the wind velocity within the wind power tower but also to adjust the wind direction for making a better working condition on the VAWT. Hence, some important design variables, such as the distance between the wind turbine and the guide wall, the outer diameter of the wind power tower, the direction of the guide wall against the wind direction, should be considered to enhance the output power on the VAWT. A numerical analysis was conducted to find the optimum dimension on design variables by using the computational fluid dynamics (CFD) among many prediction methods. The CFD could be an accurate prediction method compared with the stream-tube methods. In order to obtain the accurate results in the CFD, it needs the transient analysis and the full three-dimensional (3-D) computation. However, this full 3-D CFD could be hard to be a practical tool because it requires huge computation time. Therefore, the reduced computational domain is applied as a practical method. In this study, the computations were conducted in the reduced computational domain and they were compared with the experimental results in the literature. It was examined the mechanism of the difference between the experimental results and the computational results. The computed results showed this computational method could be an effective method in the design methodology using the optimization algorithm. After validation of the numerical method, the CFD on the wind power tower was conducted with the important design variables affecting the performance of VAWT. The results showed that the output power of the VAWT obtained using the wind power tower was increased compared to them obtained without the wind power tower. In addition, they showed that the increased output power on the wind turbine depended greatly on the dimension of the guide wall.

Keywords: CFD, performance, VAWT, wind power tower

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Authors: Sarah Gounden, Mukesh Dheda, Boikhutso Tlou, Elizabeth Ojewole, Frasia Oosthuizen

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Background: Antiretroviral therapy (ART) has been effective in the reduction of mortality and resulted in an improvement in the prognosis of HIV-infected patients. However, treatment with antiretrovirals (ARVs) has led to the development of many adverse drug reactions (ADRs). It is, therefore, necessary to determine the safety profile of these medicines in a South African population in order to ensure safe and optimal medicine use. Objectives: The aim of this study was to quantify ADRs experienced with the different ARVs currently used in South Africa, to determine the safety profile of ARV medicine in South Africa based on reported ADRs, and to determine the ARVs with the lowest risk profile based on specific patient populations. Methodology: This was a quantitative study. Individual case safety reports for the period January 2010 – December 2013 were obtained from the National Pharmacovigilance Center; these reports contained information on ADRs, ARV medicine, and patient demographics. Data was analysed to find associations that may exist between ADRs experienced, ARV medicines used and patient demographics. Results: A total of 1916 patient reports were received of which 1534 met the inclusion criteria for the study. The ARV with the lowest risk of ADRs were found to be lamivudine (0.51%, n=12), followed by lopinavir/ritonavir combination (0.8%, n=19) and abacavir (0.64%, n=15). A higher incidence of ADRs was observed in females compared to males. The age group 31–50 years and the weight group 61–80 kg had the highest incidence of ADRs reported. Conclusion: This study found that the safest ARVs to be used in a South African population are lamivudine, abacavir, and the lopinavir/ritonavir combination. Gender differences play a significant role in the occurrence of ADRs and both anatomical and physiological differences account for this. An increased BMI (body mass index) in both men and women showed an increase in the incidence of ADRs associated with ARV therapy.

Keywords: adverse drug reaction, antiretrovirals, HIV/AIDS, pharmacovigilance, South Africa

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Authors: Ulrike Dowie, Ralph Grothmann

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Rational planning decisions are based upon forecasts. Precise forecasting has, therefore, a central role in business. The prediction of customer demand is a prime example. This paper introduces recurrent neural networks to model customer demand and combines the forecast with uncertainty measures to derive decision support of the demand planning department. It identifies and describes the keys to the successful implementation of an AI-based solution: bringing together data with business knowledge, AI methods, and user experience, and applying agile software development practices.

Keywords: agile software development, AI project success factors, deep learning, demand forecasting, forecast uncertainty, neural networks, supply chain management

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Authors: Florin Leon

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This paper describes a simulator of traffic scenarios tailored to facilitate autonomous driving model training for urban environments. With the rising prominence of self-driving vehicles, the need for diverse datasets is very important. The proposed simulator provides a flexible framework that allows the generation of custom scenarios needed for the validation and enhancement of trajectory prediction algorithms. Its controlled yet dynamic environment addresses the challenges associated with real-world data acquisition and ensures adaptability to diverse driving scenarios. By providing an adaptable solution for scenario creation and algorithm testing, this tool proves to be a valuable resource for advancing autonomous driving technology that aims to ensure safe and efficient self-driving vehicles.

Keywords: autonomous driving, car simulator, machine learning, model training, urban simulation environment

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Authors: Mahesh K. Chudasama, Harit K. Raval

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3-roller conical bending process is widely used in the industries for manufacturing of conical sections and shells. It involves static as well dynamic bending stages. Analytical models for prediction of bending force during static as well as dynamic bending stage are available in the literature. In this paper, bending forces required for static bending stage and dynamic bending stages have been compared using the analytical models. It is concluded that force required for dynamic bending is very less as compared to the bending force required during the static bending stage.

Keywords: analytical modeling, cone frustum, dynamic bending, static bending

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Authors: Yifat Koren Carmi, Abed Agbarya, Hazem Khamaisi, Raymond Farah, Yelena Shechtman, Roman Korobochka, Jacob Gopas, Jamal Mahajna

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Ovarian cancer (OC), the second most common form of gynecological malignancy, has a poor prognosis and is frequently identified in its late stages. The recommended treatment for OC typically includes a platinum-based chemotherapy, like carboplatin. Nonetheless, OC treatment has proven challenging due to toxicity and development of acquired resistance to therapy. Chemoresistance is a significant obstacle to a long-lasting response in OC patients, believed to arise from alterations within the cancer cells as well as within the tumor microenvironments (TME). Malignant ascites is a presenting feature in more than one-third of OC patients. It serves as a reservoir for a complex mixture of soluble factors, metabolites, and cellular components, providing a pro-inflammatory and tumor-promoting microenvironment for the OC cells. Malignant ascites is also associated with metastasis and chemoresistance. In an attempt to elucidate the role of TME in chemoresistance of OC, we monitored the ability of soluble factors derived from ascites fluids to affect platinum sensitivity of OC cells. This research, compared ascites fluids from non-malignant cirrhotic patients to those from OC patients in terms of their ability to alter the platinum sensitivity of OC cells. Our findings indicated that exposure to OC ascites induces platinum chemoresistance on OC cells in 11 out of 13 cases (85%). In contrast, 75% of cirrhosis ascites (3 out of 4) failed to confer platinum chemoresistance to OC cells. Cytokine array analysis revealed that IL-6, and to a lesser extent HGF were enriched in OC ascites, whereas IL-22 was enriched in cirrhosis ascites. Pharmaceutical inhibitors that target the IL-6/JAK signaling pathway were mildly effective in overcoming the platinum chemoresistance induced by malignant ascites. In contrast, Crizotinib an HGF/c-MET inhibitor, and 2-hydroxyestradiol (2HE2) were effective in restoring platinum chemoresistance to OC. Our findings demonstrate the importance of OC ascites in supporting platinum chemoresistance as well as the potential of a combination therapy with Crizotinib and the estradiol metabolite 2HE2 to regain OC cells chemosensitivity.

Keywords: ovarian cancer, platinum chemoresistance, malignant ascites, tumor microenvironment, IL-6, 2-hydroxyestradiol, HGF, crizotinib

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Authors: Eung-Seok Park, Tae-Chul Jeong, Hyun-Jong Park, Hyun-Woo Jun, Dong-Woo Kang, Ju Lee

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This presents a methodology to determine detail design directions of an 150kW-class IPMSM (interior permanent magnet synchronous motor) and its detail design. The basic design of the stator and rotor was conducted. After dividing the designed models into the best cases and the worst cases based on rotor shape parameters, Sensitivity analysis and 3D Voltage-Inductance Map (3D EL-Map) parameters were analyzed. Then, the design direction for the final model was predicted. Based on the prediction, the final model was extracted with Trend analysis. Lastly, the final model was validated with experiments.

Keywords: PMSM, optimal design, rotor design, voltage-inductance map

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Authors: Atchara Sankom, Warapa Mahakarnchanakul, Ronnarit Rittiron, Tanaboon Sajjaanantakul, Thammasak Thongket

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Vegetables are frequently contaminated with pesticides residues resulting in the most food safety concern among agricultural products. The objective of this work was to develop a method to detect the organophosphate (OP) pesticides residues in vegetables using Near Infrared (NIR) spectroscopy technique. Low concentration (ppm) of OP pesticides in vegetables were investigated. The experiment was divided into 2 sections. In the first section, Chinese kale spiked with different concentrations of chlorpyrifos pesticide residues (0.5-100 ppm) was chosen as the sample model to demonstrate the appropriate conditions of sample preparation, both for a solution or solid sample. The spiked samples were extracted with acetone. The sample extracts were applied as solution samples, while the solid samples were prepared by the dry-extract system for infrared (DESIR) technique. The DESIR technique was performed by embedding the solution sample on filter paper (GF/A) and then drying. The NIR spectra were measured with the transflectance mode over wavenumber regions of 12,500-4000 cm⁻¹. The QuEChERS method followed by gas chromatography-mass spectrometry (GC-MS) was performed as the standard method. The results from the first section showed that the DESIR technique with NIR spectroscopy demonstrated good accurate calibration result with R² of 0.93 and RMSEP of 8.23 ppm. However, in the case of solution samples, the prediction regarding the NIR-PLSR (partial least squares regression) equation showed poor performance (R² = 0.16 and RMSEP = 23.70 ppm). In the second section, the DESIR technique coupled with NIR spectroscopy was applied to the detection of OP pesticides in vegetables. Vegetables (Chinese kale, cabbage and hot chili) were spiked with OP pesticides (chlorpyrifos ethion and profenofos) at different concentrations ranging from 0.5 to 100 ppm. Solid samples were prepared (based on the DESIR technique), then samples were scanned by NIR spectrophotometer at ambient temperature (25+2°C). The NIR spectra were measured as in the first section. The NIR- PLSR showed the best calibration equation for detecting low concentrations of chlorpyrifos residues in vegetables (Chinese kale, cabbage and hot chili) according to the prediction set of R2 and RMSEP of 0.85-0.93 and 8.23-11.20 ppm, respectively. For ethion residues, the best calibration equation of NIR-PLSR showed good indexes of R² and RMSEP of 0.88-0.94 and 7.68-11.20 ppm, respectively. As well as the results for profenofos pesticide, the NIR-PLSR also showed the best calibration equation for detecting the profenofos residues in vegetables according to the good index of R² and RMSEP of 0.88-0.97 and 5.25-11.00 ppm, respectively. Moreover, the calibration equation developed in this work could rapidly predict the concentrations of OP pesticides residues (0.5-100 ppm) in vegetables, and there was no significant difference between NIR-predicted values and actual values (data from GC-MS) at a confidence interval of 95%. In this work, the proposed method using NIR spectroscopy involving the DESIR technique has proved to be an efficient method for the screening detection of OP pesticides residues at low concentrations, and thus increases the food safety potential of vegetables for domestic and export markets.

Keywords: NIR spectroscopy, organophosphate pesticide, vegetable, food safety

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Authors: Elena M. Capitanul, Carlos A. Nunes Cosenza, Walid El Moudani, Felix Mora Camino

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The construction of a new airport or the extension of an existing one requires massive investments and many times public private partnerships were considered in order to make feasible such projects. One characteristic of these projects is uncertainty with respect to financial and environmental impacts on the medium to long term. Another one is the multistage nature of these types of projects. While many airport development projects have been a success, some others have turned into a nightmare for their promoters. This communication puts forward a new approach for airport investment risk assessment. The approach takes explicitly into account the degree of uncertainty in activity levels prediction and proposes milestones for the different stages of the project for minimizing risk. Uncertainty is represented through fuzzy dual theory and risk management is performed using dynamic programming. An illustration of the proposed approach is provided.

Keywords: airports, fuzzy logic, risk, uncertainty

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Authors: Afaneen Anwer, Samara M. Kamil

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Load Forecast required prediction accuracy based on optimal operation and maintenance. A good accuracy is the basis of economic dispatch, unit commitment, and system reliability. A good load forecasting system fulfilled fast speed, automatic bad data detection, and ability to access the system automatically to get the needed data. In this paper, the formulation of the load forecasting is discussed and the solution is obtained by using artificial neural network method. A MATLAB environment has been used to solve the load forecasting schedule of Iraqi super grid network considering the daily load for three years. The obtained results showed a good accuracy in predicting the forecasted load.

Keywords: load forecasting, neural network, back-propagation algorithm, Iraqi power system

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Authors: Madhu Jain, Rakesh Kumar Meena

Abstract:

This paper investigates a finite M/G/1 fault tolerant multi-component machining system. The system incorporates the features such as standby support, threshold recovery and imperfect coverage make the study closer to real time systems. The performance prediction of M/G/1 fault tolerant system is carried out using recursive approach by treating remaining service time as a supplementary variable. The numerical results are presented to illustrate the computational tractability of analytical results by taking three different service time distributions viz. exponential, 3-stage Erlang and deterministic. Moreover, the cost function is constructed to determine the optimal choice of system descriptors to upgrading the system.

Keywords: fault tolerant, machine repair, threshold recovery policy, imperfect coverage, supplementary variable technique

Procedia PDF Downloads 278

Authors: F. Polito, M. Cucinotta, A. Conti, C. Lo Giudice, C. Tomasello, F. Angileri, D. La Torre, M. Aguennouz

Abstract:

Glioblastoma multiforme (GBM) is the most aggressive form of brain tumors, with an extremely poor prognosis. Telomeres lenght is associated with tumor progression in several type of human cancers and telomere elongation is a common molecular feature of advanced malignancies. Among the telomeric shelterin proteins PTOP is required for telomeric protein complex assembly, telomerase recruitment and activity, and telomere length regulation through a PTOP-telomerase interaction. Previous studies suggest that PTOP upregulation is involved in radioresistance and telomere lengthening in colorectal cancer cells. Moreover, in human osteosarcoma cells PTOP deletion led to telomere shortening, increased apoptosis and radiation sensitivity enhancement. However, to date, little is known about the role of PTOP in progression of glioma cancers. In light of this background aim of the study is to investigate the expression of PTOP in different grades of human glioma and its correlation with the pathological grade of gliomas, grades of malignancy, proliferative activity and apoptosis. Fifteen Low Grade Astrocytomas (LGA), 18 Anaplastic Astrocytomas (AA) and 26 Glioblastoma Multiforme (GBM) samples were analyzed. Three samples of normal brain tissue (NBT) were used as controls. The expression levels of PTOP, h-TERT, BIRC1 and cyclin D1 were determined by real time PCR and/or western blot. Results obtained shows that PTOP expression in glioma tissues is tightly correlated with clinical grade ( p < 0.01 ). No correlation was found between PTOP expression and other clinicopathologic parameters. The expression of PTOP was positively correlated with the expression of hTERT and TERF1. Furthermore PTOP positively correlates with cyclin D1 and negatively correlates with the expression of BIRC1. Our findings indicate that PTOP might play key role in the progression of glioma regulating telomerase activity and likely through regulation of cell cycle and apoptosis. In conclusion results obtained prompted us to speculate that PTOP might represents a potential molecular bio marker and a therapeutic target for the treatment of glioblastoma tumors.

Keywords: glioblastoma, PTOP, telomere, brain tumors

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Authors: Woo-Young Jung, Minho Kwon

Abstract:

Seismic design criteria based on performance of structures have recently been adopted by practicing engineers in response to destructive earthquakes. A simple but efficient structural-analysis tool capable of predicting both the strength and ductility is needed to analyze reinforced concrete (RC) structures under such event. A three-dimensional lattice model is developed in this study to analyze torsions in high-strength RC members. Optimization techniques for determining optimal variables in each lattice model are introduced. Pure torsion tests of RC members are performed to validate the proposed model. Correlation studies between the numerical and experimental results confirm that the proposed model is well capable of representing salient features of the experimental results.

Keywords: torsion, non-linear analysis, three-dimensional lattice, high-strength concrete

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Authors: N. Boutra, N. Ravot, J. Benoit, O. Picon

Abstract:

Submarine power cables used for offshore wind farms electric energy distribution and transmission are subject to numerous threats. Some of the risks are associated with transport, installation and operating in harsh marine environment. This paper describes the feasibility of an electromagnetic low frequency sensing technique for submarine power cable failure prediction. The impact of a structural damage shape and material variability on the induced electric field is evaluated. The analysis is performed by modeling the cable using the finite element method, we use sensitivity analysis in order to identify the main damage characteristics affecting electric field variation. Lastly, we discuss the results obtained.

Keywords: electromagnetism, finite element method, sensitivity analysis, submarine power cables

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Authors: A. Medjnoun, R. Bahar

Abstract:

The disorders caused by the shrinking-swelling phenomenon are prevalent in arid and semi-arid in the presence of swelling clay. This soil has the characteristic of changing state under the effect of water solicitation (wetting and drying). A set of geotechnical parameters is necessary for the characterization of this soil type, such as state parameters, physical and chemical parameters and mechanical parameters. Some of these tests are very long and some are very expensive, hence the use or methods of predictions. The complexity of this phenomenon and the difficulty of its characterization have prompted researchers to use several identification parameters in the prediction of swelling potential. This document is an analytical and statistical study of geotechnical parameters affecting the potential of swelling clays. This work is performing on a database obtained from investigations swelling Algerian soil. The obtained observations have helped us to understand the soil swelling structure and its behavior.

Keywords: analysis, estimated model, parameter identification, swelling of clay

Procedia PDF Downloads 396