Search results for: drug property prediction
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5570

Search results for: drug property prediction

890 Magnetoelastically Induced Perpendicular Magnetic Anisotropy and Perpendicular Exchange Bias of CoO/CoPt Multilayer Films

Authors: Guo Lei, Wang Yue, Nakamura Yoshio, Shi Ji

Abstract:

Recently, perpendicular exchange bias (PEB) is introduced as an active topic attracting continuous efforts. Since its discovery, extrinsic control of PEB has been proposed, due to its scientific significance in spintronic devices and potential application in high density magnetic random access memory with perpendicular magnetic tunneling junction (p-MTJ). To our knowledge, the researches aiming to controlling PEB so far are focused mainly on enhancing the interfacial exchange coupling by adjusting the FM/AFM interface roughness, or optimizing the crystalline structures of FM or AFM layer by employing different seed layers. In present work, the effects of magnetoelastically induced PMA on PEB have been explored in [CoO5nm/CoPt5nm]5 multilayer films. We find the PMA strength of FM layer also plays an important role on PEB at the FM/AFM interface and it is effective to control PEB of [CoO5nm/CoPt5nm]5 multilayer films by changing the magnetoelastically induced PMA of CoPt layer. [CoO5nm/CoPt5nm]5 multilayer films were deposited by magnetron sputtering on fused quartz substrate at room temperature, then annealed at 100°C, 250°C, 300°C and 375°C for 3h, respectively. XRD results reveal that all the samples are well crystallized with preferred fcc CoPt (111) orientation. The continuous multilayer structure with sharp component transition at the CoO5nm/CoPt5nm interface are identified clearly by transmission electron microscopy (TEM), x-ray reflectivity (XRR) and atomic force microscope (AFM). CoPt layer in-plane tensile stress is calculated by sin2φ method, and we find it increases gradually upon annealing from 0.99 GPa (as-deposited) up to 3.02 GPa (300oC-annealed). As to the magnetic property, significant enhancement of PMA is achieved in [CoO5nm/CoPt5nm]5 multilayer films after annealing due to the increase of CoPt layer in-plane tensile stress. With the enhancement of magnetoelastically induced PMA, great improvement of PEB is also achieved in [CoO5nm/CoPt5nm]5 multilayer films, which increases from 130 Oe (as-deposited) up to 1060 Oe (300oC-annealed), showing the same change tendency as PMA and the strong correlation with CoPt layer in-plane tensile stress. We consider it is the increase of CoPt layer in-plane tensile stress that leads to the enhancement of PMA, and thus the enhancement of magnetoelastically induced PMA results in the improvement of PEB in [CoO5nm/CoPt5nm]5 multilayer films.

Keywords: perpendicular exchange bias, magnetoelastically induced perpendicular magnetic anisotropy, CoO5nm/CoPt5nm]5 multilayer film with in-plane stress, perpendicular magnetic tunneling junction

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889 Numerical Investigation of Dynamic Stall over a Wind Turbine Pitching Airfoil by Using OpenFOAM

Authors: Mahbod Seyednia, Shidvash Vakilipour, Mehran Masdari

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Computations for two-dimensional flow past a stationary and harmonically pitching wind turbine airfoil at a moderate value of Reynolds number (400000) are carried out by progressively increasing the angle of attack for stationary airfoil and at fixed pitching frequencies for rotary one. The incompressible Navier-Stokes equations in conjunction with Unsteady Reynolds Average Navier-Stokes (URANS) equations for turbulence modeling are solved by OpenFOAM package to investigate the aerodynamic phenomena occurred at stationary and pitching conditions on a NACA 6-series wind turbine airfoil. The aim of this study is to enhance the accuracy of numerical simulation in predicting the aerodynamic behavior of an oscillating airfoil in OpenFOAM. Hence, for turbulence modelling, k-ω-SST with low-Reynolds correction is employed to capture the unsteady phenomena occurred in stationary and oscillating motion of the airfoil. Using aerodynamic and pressure coefficients along with flow patterns, the unsteady aerodynamics at pre-, near-, and post-static stall regions are analyzed in harmonically pitching airfoil, and the results are validated with the corresponding experimental data possessed by the authors. The results indicate that implementing the mentioned turbulence model leads to accurate prediction of the angle of static stall for stationary airfoil and flow separation, dynamic stall phenomenon, and reattachment of the flow on the surface of airfoil for pitching one. Due to the geometry of the studied 6-series airfoil, the vortex on the upper surface of the airfoil during upstrokes is formed at the trailing edge. Therefore, the pattern flow obtained by our numerical simulations represents the formation and change of the trailing-edge vortex at near- and post-stall regions where this process determines the dynamic stall phenomenon.

Keywords: CFD, moderate Reynolds number, OpenFOAM, pitching oscillation, unsteady aerodynamics, wind turbine

Procedia PDF Downloads 194
888 Statistical Modeling and by Artificial Neural Networks of Suspended Sediment Mina River Watershed at Wadi El-Abtal Gauging Station (Northern Algeria)

Authors: Redhouane Ghernaout, Amira Fredj, Boualem Remini

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Suspended sediment transport is a serious problem worldwide, but it is much more worrying in certain regions of the world, as is the case in the Maghreb and more particularly in Algeria. It continues to take disturbing proportions in Northern Algeria due to the variability of rains in time and in space and constant deterioration of vegetation. Its prediction is essential in order to identify its intensity and define the necessary actions for its reduction. The purpose of this study is to analyze the concentration data of suspended sediment measured at Wadi El-Abtal Hydrometric Station. It also aims to find and highlight regressive power relationships, which can explain the suspended solid flow by the measured liquid flow. The study strives to find models of artificial neural networks linking the flow, month and precipitation parameters with solid flow. The obtained results show that the power function of the solid transport rating curve and the models of artificial neural networks are appropriate methods for analysing and estimating suspended sediment transport in Wadi Mina at Wadi El-Abtal Hydrometric Station. They made it possible to identify in a fairly conclusive manner the model of neural networks with four input parameters: the liquid flow Q, the month and the daily precipitation measured at the representative stations (Frenda 013002 and Ain El-Hadid 013004 ) of the watershed. The model thus obtained makes it possible to estimate the daily solid flows (interpolate and extrapolate) even beyond the period of observation of solid flows (1985/86 to 1999/00), given the availability of the average daily liquid flows and daily precipitation since 1953/1954.

Keywords: suspended sediment, concentration, regression, liquid flow, solid flow, artificial neural network, modeling, mina, algeria

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887 A Study on Awareness and Attitude of First-Year Medical Students on Epilepsy in University of Khartoum 2020-2021

Authors: Mohammed E. Ibrahim, Baraa A. Taha, Kamil M. A. Shabban

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Background: Epilepsy is a common but widely misunderstood illness. Consequently, patients with epilepsy suffer from considerable stigmatization in society. This social stigma and discrimination often cause more suffering for the patients than the disease itself. Since very few studies have explored the misperceptions about epilepsy among university students in Sudan, it is not possible to provide focused intervention aimed at eliminating this discrimination. Methods: A cross-sectional study was applied among the first-year medical students at the University of Khartoum between December (2020) and February (2021). A 29-item standardized questionnaire was self-administered by 198 students (out of 320) who agreed to participate in this study. Google form was the tool used to collect the data. The data were analyzed using the Statistical Package for Social Science software version 26. Result: Overall, the results indicate a negative trend in knowledge and attitude toward epilepsy. The vast majority of the respondents (84.8%) have read or heard about epilepsy, while 43.9% had seen someone with epilepsy. Only 7.5% of the participants reported that epilepsy is contagious, whereas 43.4% of them think that epilepsy is a psychological disorder. About 62.2% of students think head/birth trauma is a cause of epilepsy. On the other side, about 15.7% and 5.1% believed that evil spirits and punishment from god can also be a possible cause of epilepsy; we found these false beliefs are more common in participants from rural areas (p-value < 0.05). In regard to attitude, 19.7% of students thought that it is inappropriate for a patient with epilepsy to have a child. This attitude correlates with the mother’s education as the percentage is higher for those who have lower mother’s education (through secondary school education and below) (p < 0.05). The majority of Our participant knew that some people with epilepsy need life-long drug treatment; this belief was found to be more common in females than their counterparts(p < 0.05). . Finally, most of the respondents (93.9%) thought that a child with epilepsy Can be successful in a normal class. This belief is four-time as common in participants whose mothers have higher education (through university education and above) compared with corresponding respondents (p < 0.05). Conclusion: This study concludes that students' knowledge about epilepsy is limited and requires immediate intervention through educational campaigns to develop a well-informed and tolerant community.

Keywords: epilepsy, awareness, attitude, university students, Sudan

Procedia PDF Downloads 127
886 Design and Development of Bioactive a-Hydroxy Carboxylate Group Modified MnFe₂O₄ Nanoparticle: Comparative Fluorescence Study, Magnetism and DNA Nuclease Activity

Authors: Indranil Chakraborty, Kalyan Mandal

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Three new α-hydroxy carboxylate group functionalized MnFe₂O₄ nanoparticles (NPs) have been developed to explore the microscopic origin of ligand modified fluorescence and magnetic properties of nearly monodispersed MnFe₂O₄ NPs. The surface functionalization has been carried out with three small organic ligands (tartrate, malate, and citrate) having different number of α-hydroxy carboxylate functional group along with steric effect. Detailed study unveils that α-hydroxy carboxylate moiety of the ligands plays key role to generate intrinsic fluorescence in functionalized MnFe₂O₄ NPs through the activation of ligand to metal charge transfer transitions, associated with ligand-Mn²⁺/Fe³⁺ interactions along with d-d transition corresponding to d-orbital energy level splitting of Fe³⁺ ions on NP surface. Further, MnFe₂O₄ NPs show a maximum 140.88% increase in coercivity and 97.95% decrease in magnetization compared to its bare one upon functionalization. The ligands that induce smallest crystal field splitting of d-orbital energy level of transition metal ions are found to result in strongest ferromagnetic activation of the NPs. Finally, our developed tartrate functionalized MnFe₂O₄ (T-MnFe₂O₄) NPs have been utilized for studying DNA binding interaction and nuclease activity for stimulating their beneficial activities toward diverse biomedical applications. The spectroscopic measurements indicate that T-MnFe₂O₄ NPs bind calf thymus DNA by intercalative mode. The ability of T-MnFe₂O₄ NPs to induce DNA cleavage was studied by gel electrophoresis technique where the complex is found to promote the cleavage of pBR322 plasmid DNA from the super coiled form I to linear coiled form II and nicked coiled form III with good efficiency. This may be taken into account for designing new biomolecular detection agents and anti-cancer drug which can open up a new door toward diverse non-invasive biomedical applications.

Keywords: MnFe₂O₄ nanoparticle, α-hydroxy carboxylic acid, comparative fluorescence, magnetism study, DNA interaction, nuclease activity

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885 3D-Printing Compressible Macroporous Polymer Using Poly-Pickering-High Internal Phase Emulsions as Micromixer

Authors: Hande Barkan-Ozturk, Angelika Menner, Alexander Bismarck

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Microfluidic mixing technology grew rapidly in the past few years due to its many advantages over the macro-scale mixing, especially the ability to use small amounts of internal volume and also very high surface-to-volume ratio. The Reynold number identify whether the mixing is operated by the laminar or turbulence flow. Therefore, mixing with very fast kinetic can be achieved by diminishing the channel dimensions to decrease Reynold number and the laminar flow can be accomplished. Moreover, by using obstacles in the micromixer, the mixing length and the contact area between the species have been increased. Therefore, the channel geometry and its surface property have great importance to reach satisfactory mixing results. Since poly(-merised) High Internal Phase Emulsions (polyHIPEs) have more than 74% porosity and their pores are connected each other with pore throats, which cause high permeability, they are ideal candidate to build a micromixer. The HIPE precursor is commonly produced by using an overhead stirrer to obtain relatively large amount of emulsion in batch process. However, we will demonstrate that a desired amount of emulsion can be prepared continuously with micromixer build from polyHIPE, and such HIPE can subsequently be employed as ink in 3D printing process. In order to produce the micromixer a poly-Pickering(St-co-DVB)HIPE with 80% porosity was prepared with modified silica particles as stabilizer and surfactant Hypermer 2296 to obtain open porous structure and after coating of the surface, the three 1/16' ' PTFE tubes to transfer continuous (CP) and internal phases (IP) and the other is to collect the emulsion were placed. Afterwards, the two phases were injected in the ratio 1:3 CP:IP with syringe dispensers, respectively, and highly viscoelastic H(M)IPE, which can be used as an ink in 3D printing process, was gathered continuously. After the polymerisation of the resultant emulsion, polyH(M)IPE has interconnected porous structure identical to the monolithic polyH(M)IPE indicating that the emulsion can be prepared constantly with poly-Pickering-HIPE as micromixer and it can be used to prepare desired pattern with a 3D printer. Moreover, the morphological properties of the emulsion can be adjustable by changing flow ratio, flow speed and structure of the micromixer.

Keywords: 3D-Printing, emulsification, macroporous polymer, micromixer, polyHIPE

Procedia PDF Downloads 155
884 The State of Research on Medicinal Plants in Morocco

Authors: Alami Ilyass, Loubna Kharchoufa, Elachouri Mostafa

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The two great realms of living diversity are cultural and biological. Today, both are being lost at an alarming rate. Of all the Earth’s biological diversity, plant kingdom is of high significance, and most essential to human welfare, in fact, medicinal plants are extensively exploited for countless purposes. Among these multiple uses, medicinal plants are the most important source of medicine for humankind healthcare and well being. In recent years there has been a great surge of public interest in the use of herbs and plants. Some scientists have viewed this phenomenon as a modern “herbal renaissance”. The importance of plants as medicines in developed and developing countries has recently been acknowledged by the United Nations (UN). However, to date fewer than 5% of the approximately 250,000 species of higher plants have been exhaustively studied for their potential pharmacological activity. A number of drugs from ethnobotanical leads have provided significant milestones in Western medicine. Despite this success, pharmacognosy research on Moroccan flora needs more studies aimed at the exploration of their therapeutic potential. A major weakness is the absence of strong funding agencies in the country, and a real national drug discovery program. Moreover, the lack of the coordination between different universities and research institutions leads, in most cases, to a waste of time, money and efforts of many researchers. In this work, we focus our attention on research into traditional indigenous medicinal plants in Morocco. Three parts constitute the head lines of this work: In the first one, we take up Moroccan biodiversity matter, the second part is devoted principally to the state of research into medicinal plants by Moroccan scholars and the last one is consecrated to the debate of factors which handicap the progress of research on phytomedicine in Morocco. The objectives of the present study are twofold: first, to highlight the state of the medicinal plants researches in Morocco. Second goal is to assess and correlate the levels of knowledge of the local flora to the research on medicinal plants to attempt to build capacity for research within Moroccan Scientific community at rate of developing country.

Keywords: Morocco, medicinal plants, ethnobotanical, pharmacognosy, phytomedicine

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883 Frequency Selective Filters for Estimating the Equivalent Circuit Parameters of Li-Ion Battery

Authors: Arpita Mondal, Aurobinda Routray, Sreeraj Puravankara, Rajashree Biswas

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The most difficult part of designing a battery management system (BMS) is battery modeling. A good battery model can capture the dynamics which helps in energy management, by accurate model-based state estimation algorithms. So far the most suitable and fruitful model is the equivalent circuit model (ECM). However, in real-time applications, the model parameters are time-varying, changes with current, temperature, state of charge (SOC), and aging of the battery and this make a great impact on the performance of the model. Therefore, to increase the equivalent circuit model performance, the parameter estimation has been carried out in the frequency domain. The battery is a very complex system, which is associated with various chemical reactions and heat generation. Therefore, it’s very difficult to select the optimal model structure. As we know, if the model order is increased, the model accuracy will be improved automatically. However, the higher order model will face the tendency of over-parameterization and unfavorable prediction capability, while the model complexity will increase enormously. In the time domain, it becomes difficult to solve higher order differential equations as the model order increases. This problem can be resolved by frequency domain analysis, where the overall computational problems due to ill-conditioning reduce. In the frequency domain, several dominating frequencies can be found in the input as well as output data. The selective frequency domain estimation has been carried out, first by estimating the frequencies of the input and output by subspace decomposition, then by choosing the specific bands from the most dominating to the least, while carrying out the least-square, recursive least square and Kalman Filter based parameter estimation. In this paper, a second order battery model consisting of three resistors, two capacitors, and one SOC controlled voltage source has been chosen. For model identification and validation hybrid pulse power characterization (HPPC) tests have been carried out on a 2.6 Ah LiFePO₄ battery.

Keywords: equivalent circuit model, frequency estimation, parameter estimation, subspace decomposition

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882 The Extent of Land Use Externalities in the Fringe of Jakarta Metropolitan: An Application of Spatial Panel Dynamic Land Value Model

Authors: Rahma Fitriani, Eni Sumarminingsih, Suci Astutik

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In a fast growing region, conversion of agricultural lands which are surrounded by some new development sites will occur sooner than expected. This phenomenon has been experienced by many regions in Indonesia, especially the fringe of Jakarta (BoDeTaBek). Being Indonesia’s capital city, rapid conversion of land in this area is an unavoidable process. The land conversion expands spatially into the fringe regions, which were initially dominated by agricultural land or conservation sites. Without proper control or growth management, this activity will invite greater costs than benefits. The current land use is the use which maximizes its value. In order to maintain land for agricultural activity or conservation, some efforts are needed to keep the land value of this activity as high as possible. In this case, the knowledge regarding the functional relationship between land value and its driving forces is necessary. In a fast growing region, development externalities are the assumed dominant driving force. Land value is the product of the past decision of its use leading to its value. It is also affected by the local characteristics and the observed surrounded land use (externalities) from the previous period. The effect of each factor on land value has dynamic and spatial virtues; an empirical spatial dynamic land value model will be more useful to capture them. The model will be useful to test and to estimate the extent of land use externalities on land value in the short run as well as in the long run. It serves as a basis to formulate an effective urban growth management’s policy. This study will apply the model to the case of land value in the fringe of Jakarta Metropolitan. The model will be used further to predict the effect of externalities on land value, in the form of prediction map. For the case of Jakarta’s fringe, there is some evidence about the significance of neighborhood urban activity – negative externalities, the previous land value and local accessibility on land value. The effects are accumulated dynamically over years, but they will fully affect the land value after six years.

Keywords: growth management, land use externalities, land value, spatial panel dynamic

Procedia PDF Downloads 247
881 3D Interpenetrated Network Based on 1,3-Benzenedicarboxylate and 1,2-Bis(4-Pyridyl) Ethane

Authors: Laura Bravo-García, Gotzone Barandika, Begoña Bazán, M. Karmele Urtiaga, Luis M. Lezama, María I. Arriortua

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Solid coordination networks (SCNs) are materials consisting of metal ions or clusters that are linked by polyfunctional organic ligands and can be designed to form tridimensional frameworks. Their structural features, as for example high surface areas, thermal stability, and in other cases large cavities, have opened a wide range of applications in fields like drug delivery, host-guest chemistry, biomedical imaging, chemical sensing, heterogeneous catalysis and others referred to greenhouse gases storage or even separation. In this sense, the use of polycarboxylate anions and dipyridyl ligands is an effective strategy to produce extended structures with the needed characteristics for these applications. In this context, a novel compound, [Cu4(m-BDC)4(bpa)2DMF]•DMF has been obtained by microwave synthesis, where m-BDC is 1,3-benzenedicarboxylate and bpa 1,2-bis(4-pyridyl)ethane. The crystal structure can be described as a three dimensional framework formed by two equal, interpenetrated networks. Each network consists of two different CuII dimers. Dimer 1 have two coppers with a square pyramidal coordination, and dimer 2 have one with a square pyramidal coordination and other with octahedral one, the last dimer is unique in literature. Therefore, the combination of both type of dimers is unprecedented. Thus, benzenedicarboxylate ligands form sinusoidal chains between the same type of dimers, and also connect both chains forming these layers in the (100) plane. These layers are connected along the [100] direction through the bpa ligand, giving rise to a 3D network with 10 Å2 voids in average. However, the fact that there are two interpenetrated networks results in a significant reduction of the available volume. Structural analysis was carried out by means of single crystal X-ray diffraction and IR spectroscopy. Thermal and magnetic properties have been measured by means of thermogravimetry (TG), X-ray thermodiffractometry (TDX), and electron paramagnetic resonance (EPR). Additionally, CO2 and CH4 high pressure adsorption measurements have been carried out for this compound.

Keywords: gas adsorption, interpenetrated networks, magnetic measurements, solid coordination network (SCN), thermal stability

Procedia PDF Downloads 313
880 Evaluation of Compatibility between Produced and Injected Waters and Identification of the Causes of Well Plugging in a Southern Tunisian Oilfield

Authors: Sonia Barbouchi, Meriem Samcha

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Scale deposition during water injection into aquifer of oil reservoirs is a serious problem experienced in the oil production industry. One of the primary causes of scale formation and injection well plugging is mixing two waters which are incompatible. Considered individually, the waters may be quite stable at system conditions and present no scale problems. However, once they are mixed, reactions between ions dissolved in the individual waters may form insoluble products. The purpose of this study is to identify the causes of well plugging in a southern Tunisian oilfield, where fresh water has been injected into the producing wells to counteract the salinity of the formation waters and inhibit the deposition of halite. X-ray diffraction (XRD) mineralogical analysis has been carried out on scale samples collected from the blocked well. Two samples collected from both formation water and injected water were analysed using inductively coupled plasma atomic emission spectroscopy, ion chromatography and other standard laboratory techniques. The results of complete waters analysis were the typical input parameters, to determine scaling tendency. Saturation indices values related to CaCO3, CaSO4, BaSO4 and SrSO4 scales were calculated for the water mixtures at different share, under various conditions of temperature, using a computerized scale prediction model. The compatibility study results showed that mixing the two waters tends to increase the probability of barite deposition. XRD analysis confirmed the compatibility study results, since it proved that the analysed deposits consisted predominantly of barite with minor galena. At the studied temperatures conditions, the tendency for barite scale is significantly increasing with the increase of fresh water share in the mixture. The future scale inhibition and removal strategies to be implemented in the concerned oilfield are being derived in a large part from the results of the present study.

Keywords: compatibility study, produced water, scaling, water injection

Procedia PDF Downloads 159
879 Improvement in Blast Furnace Performance Using Softening - Melting Zone Profile Prediction Model at G Blast Furnace, Tata Steel Jamshedpur

Authors: Shoumodip Roy, Ankit Singhania, K. R. K. Rao, Ravi Shankar, M. K. Agarwal, R. V. Ramna, Uttam Singh

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The productivity of a blast furnace and the quality of the hot metal produced are significantly dependent on the smoothness and stability of furnace operation. The permeability of the furnace bed, as well as the gas flow pattern, influences the steady control of process parameters. The softening – melting zone that is formed inside the furnace contributes largely in distribution of the gas flow and the bed permeability. A better shape of softening-melting zone enhances the performance of blast furnace, thereby reducing the fuel rates and improving furnace life. Therefore, predictive model of the softening- melting zone profile can be utilized to control and improve the furnace operation. The shape of softening-melting zone depends upon the physical and chemical properties of the agglomerates and iron ore charged in the furnace. The variations in the agglomerate proportion in the burden at G Blast furnace disturbed the furnace stability. During such circumstances, it was analyzed that a w-shape softening-melting zone profile was formed inside the furnace. The formation of w-shape zone resulted in poor bed permeability and non-uniform gas flow. There was a significant increase in the heat loss at the lower zone of the furnace. The fuel demand increased, and the huge production loss was incurred. Therefore, visibility of softening-melting zone profile was necessary in order to pro-actively optimize the process parameters and thereby to operate the furnace smoothly. Using stave temperatures, a model was developed that predicted the shape of the softening-melting zone inside the furnace. It was observed that furnace operated smoothly during inverse V-shape of the zone and vice-versa during w-shape. This model helped to control the heat loss, optimize the burden distribution and lower the fuel rate at G Blast Furnace, TSL Jamshedpur. As a result of furnace stabilization productivity increased by 10% and fuel rate reduced by 80 kg/thm. Details of the process have been discussed in this paper.

Keywords: agglomerate, blast furnace, permeability, softening-melting

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878 Role of P53, KI67 and Cyclin a Immunohistochemical Assay in Predicting Wilms’ Tumor Mortality

Authors: Ahmed Atwa, Ashraf Hafez, Mohamed Abdelhameed, Adel Nabeeh, Mohamed Dawaba, Tamer Helmy

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Introduction and Objective: Tumour staging and grading do not usually reflect the future behavior of Wilms' tumor (WT) regarding mortality. Therefore, in this study, P53, Ki67 and cyclin A immunohistochemistry were used in a trial to predict WT cancer-specific survival (CSS). Methods: In this nonconcurrent cohort study, patients' archived data, including age at presentation, gender, history, clinical examination and radiological investigations, were retrieved then the patients were reviewed at the outpatient clinic of a tertiary care center by history-taking, clinical examination and radiological investigations to detect the oncological outcome. Cases that received preoperative chemotherapy or died due to causes other than WT were excluded. Formalin-fixed, paraffin-embedded specimens obtained from the previously preserved blocks at the pathology laboratory were taken on positively charged slides for IHC with p53, Ki67 and cyclin A. All specimens were examined by an experienced histopathologist devoted to the urological practice and blinded to the patient's clinical findings. P53 and cyclin A staining were scored as 0 (no nuclear staining),1 (<10% nuclear staining), 2 (10-50% nuclear staining) and 3 (>50% nuclear staining). Ki67 proliferation index (PI) was graded as low, borderline and high. Results: Of the 75 cases, 40 (53.3%) were males and 35 (46.7%) were females, and the median age was 36 months (2-216). With a mean follow-up of 78.6±31 months, cancer-specific mortality (CSM) occurred in 15 (20%) and 11 (14.7%) patients, respectively. Kaplan-Meier curve was used for survival analysis, and groups were compared using the Log-rank test. Multivariate logistic regression and Cox regression were not used because only one variable (cyclin A) had shown statistical significance (P=.02), whereas the other significant factor (residual tumor) had few cases. Conclusions: Cyclin A IHC should be considered as a marker for the prediction of WT CSS. Prospective studies with a larger sample size are needed.

Keywords: wilms’ tumour, nephroblastoma, urology, survival

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877 Fuzzy Logic Classification Approach for Exponential Data Set in Health Care System for Predication of Future Data

Authors: Manish Pandey, Gurinderjit Kaur, Meenu Talwar, Sachin Chauhan, Jagbir Gill

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Health-care management systems are a unit of nice connection as a result of the supply a straightforward and fast management of all aspects relating to a patient, not essentially medical. What is more, there are unit additional and additional cases of pathologies during which diagnosing and treatment may be solely allotted by victimization medical imaging techniques. With associate ever-increasing prevalence, medical pictures area unit directly acquired in or regenerate into digital type, for his or her storage additionally as sequent retrieval and process. Data Mining is the process of extracting information from large data sets through using algorithms and Techniques drawn from the field of Statistics, Machine Learning and Data Base Management Systems. Forecasting may be a prediction of what's going to occur within the future, associated it's an unsure method. Owing to the uncertainty, the accuracy of a forecast is as vital because the outcome foretold by foretelling the freelance variables. A forecast management should be wont to establish if the accuracy of the forecast is within satisfactory limits. Fuzzy regression strategies have normally been wont to develop shopper preferences models that correlate the engineering characteristics with shopper preferences relating to a replacement product; the patron preference models offer a platform, wherever by product developers will decide the engineering characteristics so as to satisfy shopper preferences before developing the merchandise. Recent analysis shows that these fuzzy regression strategies area units normally will not to model client preferences. We tend to propose a Testing the strength of Exponential Regression Model over regression toward the mean Model.

Keywords: health-care management systems, fuzzy regression, data mining, forecasting, fuzzy membership function

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876 Achieving Process Stability through Automation and Process Optimization at H Blast Furnace Tata Steel, Jamshedpur

Authors: Krishnendu Mukhopadhyay, Subhashis Kundu, Mayank Tiwari, Sameeran Pani, Padmapal, Uttam Singh

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Blast Furnace is a counter current process where burden descends from top and hot gases ascend from bottom and chemically reduce iron oxides into liquid hot metal. One of the major problems of blast furnace operation is the erratic burden descent inside furnace. Sometimes this problem is so acute that burden descent stops resulting in Hanging and instability of the furnace. This problem is very frequent in blast furnaces worldwide and results in huge production losses. This situation becomes more adverse when blast furnaces are operated at low coke rate and high coal injection rate with adverse raw materials like high alumina ore and high coke ash. For last three years, H-Blast Furnace Tata Steel was able to reduce coke rate from 450 kg/thm to 350 kg/thm with an increase in coal injection to 200 kg/thm which are close to world benchmarks and expand profitability. To sustain this regime, elimination of irregularities of blast furnace like hanging, channeling, and scaffolding is very essential. In this paper, sustaining of zero hanging spell for consecutive three years with low coke rate operation by improvement in burden characteristics, burden distribution, changes in slag regime, casting practices and adequate automation of the furnace operation has been illustrated. Models have been created to comprehend and upgrade the blast furnace process understanding. A model has been developed to predict the process of maintaining slag viscosity in desired range to attain proper burden permeability. A channeling prediction model has also been developed to understand channeling symptoms so that early actions can be initiated. The models have helped to a great extent in standardizing the control decisions of operators at H-Blast Furnace of Tata Steel, Jamshedpur and thus achieving process stability for last three years.

Keywords: hanging, channelling, blast furnace, coke

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875 Modelling the Impact of Installation of Heat Cost Allocators in District Heating Systems Using Machine Learning

Authors: Danica Maljkovic, Igor Balen, Bojana Dalbelo Basic

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Following the regulation of EU Directive on Energy Efficiency, specifically Article 9, individual metering in district heating systems has to be introduced by the end of 2016. These directions have been implemented in member state’s legal framework, Croatia is one of these states. The directive allows installation of both heat metering devices and heat cost allocators. Mainly due to bad communication and PR, the general public false image was created that the heat cost allocators are devices that save energy. Although this notion is wrong, the aim of this work is to develop a model that would precisely express the influence of installation heat cost allocators on potential energy savings in each unit within multifamily buildings. At the same time, in recent years, a science of machine learning has gain larger application in various fields, as it is proven to give good results in cases where large amounts of data are to be processed with an aim to recognize a pattern and correlation of each of the relevant parameter as well as in the cases where the problem is too complex for a human intelligence to solve. A special method of machine learning, decision tree method, has proven an accuracy of over 92% in prediction general building consumption. In this paper, a machine learning algorithms will be used to isolate the sole impact of installation of heat cost allocators on a single building in multifamily houses connected to district heating systems. Special emphasises will be given regression analysis, logistic regression, support vector machines, decision trees and random forest method.

Keywords: district heating, heat cost allocator, energy efficiency, machine learning, decision tree model, regression analysis, logistic regression, support vector machines, decision trees and random forest method

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874 Examining Predictive Coding in the Hierarchy of Visual Perception in the Autism Spectrum Using Fast Periodic Visual Stimulation

Authors: Min L. Stewart, Patrick Johnston

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Predictive coding has been proposed as a general explanatory framework for understanding the neural mechanisms of perception. As such, an underweighting of perceptual priors has been hypothesised to underpin a range of differences in inferential and sensory processing in autism spectrum disorders. However, empirical evidence to support this has not been well established. The present study uses an electroencephalography paradigm involving changes of facial identity and person category (actors etc.) to explore how levels of autistic traits (AT) affect predictive coding at multiple stages in the visual processing hierarchy. The study uses a rapid serial presentation of faces, with hierarchically structured sequences involving both periodic and aperiodic repetitions of different stimulus attributes (i.e., person identity and person category) in order to induce contextual expectations relating to these attributes. It investigates two main predictions: (1) significantly larger and late neural responses to change of expected visual sequences in high-relative to low-AT, and (2) significantly reduced neural responses to violations of contextually induced expectation in high- relative to low-AT. Preliminary frequency analysis data comparing high and low-AT show greater and later event-related-potentials (ERPs) in occipitotemporal areas and prefrontal areas in high-AT than in low-AT for periodic changes of facial identity and person category but smaller ERPs over the same areas in response to aperiodic changes of identity and category. The research advances our understanding of how abnormalities in predictive coding might underpin aberrant perceptual experience in autism spectrum. This is the first stage of a research project that will inform clinical practitioners in developing better diagnostic tests and interventions for people with autism.

Keywords: hierarchical visual processing, face processing, perceptual hierarchy, prediction error, predictive coding

Procedia PDF Downloads 100
873 Influence of Deficient Materials on the Reliability of Reinforced Concrete Members

Authors: Sami W. Tabsh

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The strength of reinforced concrete depends on the member dimensions and material properties. The properties of concrete and steel materials are not constant but random variables. The variability of concrete strength is due to batching errors, variations in mixing, cement quality uncertainties, differences in the degree of compaction and disparity in curing. Similarly, the variability of steel strength is attributed to the manufacturing process, rolling conditions, characteristics of base material, uncertainties in chemical composition, and the microstructure-property relationships. To account for such uncertainties, codes of practice for reinforced concrete design impose resistance factors to ensure structural reliability over the useful life of the structure. In this investigation, the effects of reductions in concrete and reinforcing steel strengths from the nominal values, beyond those accounted for in the structural design codes, on the structural reliability are assessed. The considered limit states are flexure, shear and axial compression based on the ACI 318-11 structural concrete building code. Structural safety is measured in terms of a reliability index. Probabilistic resistance and load models are compiled from the available literature. The study showed that there is a wide variation in the reliability index for reinforced concrete members designed for flexure, shear or axial compression, especially when the live-to-dead load ratio is low. Furthermore, variations in concrete strength have minor effect on the reliability of beams in flexure, moderate effect on the reliability of beams in shear, and sever effect on the reliability of columns in axial compression. On the other hand, changes in steel yield strength have great effect on the reliability of beams in flexure, moderate effect on the reliability of beams in shear, and mild effect on the reliability of columns in axial compression. Based on the outcome, it can be concluded that the reliability of beams is sensitive to changes in the yield strength of the steel reinforcement, whereas the reliability of columns is sensitive to variations in the concrete strength. Since the embedded target reliability in structural design codes results in lower structural safety in beams than in columns, large reductions in material strengths compromise the structural safety of beams much more than they affect columns.

Keywords: code, flexure, limit states, random variables, reinforced concrete, reliability, reliability index, shear, structural safety

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872 Enhancement in Antimicrobial and Antioxidant Activity of Cuminum cyminum L. through Niosome Nanocarries

Authors: Fatemeh Haghiralsadat, Mohadese Hashemi, Elham Akhoundi Kharanaghi, Mojgan Yazdani, Mahboobe Sharafodini, Omid Javani

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Niosomes are colloidal particles formed from the self-assembly of non-ionic surfactants in aqueous medium resulting in closed bilayer structures. As a consequence of this hydrophilic and hydrophobic structure, niosomes have the capacity to entrap compounds of different solubilities. Niosomes are promising vehicle for drug delivery which protect sensitive drugs and improve the therapeutic index of drugs by restricting their action to target cells. Essential oils are complex mixtures of volatile compounds such as terpenoids, phenol-derived aromatic components that have been used for many biological properties including bactericidal, fungicidal, insecticidal, antioxidant, anti-tyrosinase and other medicinal properties. Encapsulation of essential oils in niosomes can be an attractive method to overcome their limitation such as volatility, easily decomposition by heat, humidity, light, or oxygen. Cuminum cyminum L. (Cumin) is an aromatic plant included in the Apiaceae family and is used to flavor foods, added to fragrances, and for medical preparations which is indigenous to Egypt, the Mediterranean region, Iran and India. The major components of the Cumin oil were reported as cuminaldehyde, γ -terpinene, β-pinene, p-cymene, p-mentha-1, 3-dien-7-al, and p-mentha-1, 4-dien-7-al which provide the antimicrobial and antioxidant activity. The aim of this work was to formulate Cumin essential oil-loaded niosomes to improve water solubility of natural product and evaluate its physico-chemical features and stability. Cumin oil was obtained through steam distillation using a clevenger-type apparatus and GC/MS was applied to identify the main components of the essential oil. Niosomes were prepared by using thin film hydration method and nanoparticles were characterized for particle size, dispersity index, zeta potential, encapsulation efficiency, in vitro release, and morphology.

Keywords: Cuminum cyminum L., Cumin, niosome, essential oil, encapsulation

Procedia PDF Downloads 508
871 Dipeptide Functionalized Nanoporous Anodic Aluminium Oxide Membrane for Capturing Small Molecules

Authors: Abdul Mutalib Md Jani, Abdul Hadi Mahmud, Mohd Tajuddin Mohd Ali

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The rapid growth of interest in surface modification of nanostructures materials that exhibit improved structural and functional properties is attracting more researchers. The unique properties of highly ordered nanoporous anodic aluminium oxide (NAAO) membrane have been proposed as a platform for biosensing applications. They exhibit excellent physical and chemical properties with high porosity, high surface area, tunable pore sizes and excellent chemical resistance. In this study, NAAO was functionalized with 3-aminopropyltriethoxysilane (APTES) to prepared silane-modified NAAO. Amine functional groups are formed on the surface of NAAO during silanization and were characterized using Fourier Transform Infrared spectroscopy (FTIR). The synthesis of multi segment of peptide on NAAO surfaces can be realized by changing the surface chemistry of the NAAO membrane via click chemistry. By click reactions, utilizing alkyne terminated with amino group, various peptides tagged on NAAO can be envisioned from chiral natural or unnatural amino acids using standard coupling methods (HOBt, EDCI and HBTU). This strategy seemly versatile since coupling strategy of dipeptide with another amino acids, leading to tripeptide, tetrapeptide or pentapeptide, can be synthesized without purification. When an appropriate terminus is selected, multiple segments of amino acids can be successfully synthesized on the surfaces. The immobilized NAAO should be easily separated from the reaction medium by conventional filtration, thus avoiding complicated purification methods. Herein, we proposed to synthesize multi fragment peptide as a model for capturing and attaching various small biomolecules on NAAO surfaces and can be also applied as biosensing device, drug delivery systems and biocatalyst.

Keywords: nanoporous anodic aluminium oxide, silanization, peptide synthesise, click chemistry

Procedia PDF Downloads 270
870 In-silico DFT Study, Molecular Docking, ADMET Predictions, and DMS of Isoxazolidine and Isoxazoline Analogs with Anticancer Properties

Authors: Moulay Driss Mellaoui, Khadija Zaki, Khalid Abbiche, Abdallah Imjjad, Rachid Boutiddar, Abdelouahid Sbai, Aaziz Jmiai, Souad El Issami, Al Mokhtar Lamsabhi, Hanane Zejli

Abstract:

This study presents a comprehensive analysis of six isoxazolidine and isoxazoline derivatives, leveraging a multifaceted approach that combines Density Functional Theory (DFT), AdmetSAR analysis, and molecular docking simulations to explore their electronic, pharmacokinetic, and anticancer properties. Through DFT analysis, using the B3LYP-D3BJ functional and the 6-311++G(d,p) basis set, we optimized molecular geometries, analyzed vibrational frequencies, and mapped Molecular Electrostatic Potentials (MEP), identifying key sites for electrophilic attacks and hydrogen bonding. Frontier Molecular Orbital (FMO) analysis and Density of States (DOS) plots revealed varying stability levels among the compounds, with 1b, 2b, and 3b showing slightly higher stability. Chemical potential assessments indicated differences in binding affinities, suggesting stronger potential interactions for compounds 1b and 2b. AdmetSAR analysis predicted favorable human intestinal absorption (HIA) rates for all compounds, highlighting compound 3b superior oral effectiveness. Molecular docking and molecular dynamics simulations were conducted on isoxazolidine and 4-isoxazoline derivatives targeting the EGFR receptor (PDB: 1JU6). Molecular docking simulations confirmed the high affinity of these compounds towards the target protein 1JU6, particularly compound 3b, among the isoxazolidine derivatives, compound 3b exhibited the most favorable binding energy, with a g score of -8.50 kcal/mol. Molecular dynamics simulations over 100 nanoseconds demonstrated the stability and potential of compound 3b as a superior candidate for anticancer applications, further supported by structural analyses including RMSD, RMSF, Rg, and SASA values. This study underscores the promising role of compound 3b in anticancer treatments, providing a solid foundation for future drug development and optimization efforts.

Keywords: isoxazolines, DFT, molecular docking, molecular dynamic, ADMET, drugs.

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869 In vitro Modeling of Aniridia-Related Keratopathy by the Use of Crispr/Cas9 on Limbal Epithelial Cells and Rescue

Authors: Daniel Aberdam

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Haploinsufficiency of PAX6 in humans is the main cause of congenital aniridia, a rare eye disease characterized by reduced visual acuity. Patients have also progressive disorders including cataract, glaucoma and corneal abnormalities making their condition very challenging to manage. Aniridia-related keratopathy (ARK), caused by a combination of factors including limbal stem-cell deficiency, impaired healing response, abnormal differentiation, and infiltration of conjunctival cells onto the corneal surface, affects up to 95% of patients. It usually begins in the first decade of life resulting in recurrent corneal erosions, sub-epithelial fibrosis with corneal decompensation and opacification. Unfortunately, current treatment options for aniridia patients are currently limited. Although animal models partially recapitulate this disease, there is no in vitro cellular model of AKT needed for drug/therapeutic tools screening and validation. We used genome editing (CRISPR/Cas9 technology) to introduce a nonsense mutation found in patients into one allele of the PAX6 gene into limbal stem cells. Resulting mutated clones, expressing half of the amount of PAX6 protein and thus representative of haploinsufficiency were further characterized. Sequencing analysis showed that no off-target mutations were induced. The mutated cells displayed reduced cell proliferation and cell migration but enhanced cell adhesion. Known PAX6 targets expression was also reduced. Remarkably, addition of soluble recombinant PAX6 protein into the culture medium was sufficient to activate endogenous PAX6 gene and, as a consequence, rescue the phenotype. It strongly suggests that our in vitro model recapitulates well the epithelial defect and becomes a powerful tool to identify drugs that could rescue the corneal defect in patients. Furthermore, we demonstrate that the homeotic transcription factor Pax6 is able to be uptake naturally by recipient cells to function into the nucleus.

Keywords: Pax6, crispr/cas9, limbal stem cells, aniridia, gene therapy

Procedia PDF Downloads 198
868 Numerical Modeling and Prediction of Nanoscale Transport Phenomena in Vertically Aligned Carbon Nanotube Catalyst Layers by the Lattice Boltzmann Simulation

Authors: Seungho Shin, Keunwoo Choi, Ali Akbar, Sukkee Um

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In this study, the nanoscale transport properties and catalyst utilization of vertically aligned carbon nanotube (VACNT) catalyst layers are computationally predicted by the three-dimensional lattice Boltzmann simulation based on the quasi-random nanostructural model in pursuance of fuel cell catalyst performance improvement. A series of catalyst layers are randomly generated with statistical significance at the 95% confidence level to reflect the heterogeneity of the catalyst layer nanostructures. The nanoscale gas transport phenomena inside the catalyst layers are simulated by the D3Q19 (i.e., three-dimensional, 19 velocities) lattice Boltzmann method, and the corresponding mass transport characteristics are mathematically modeled in terms of structural properties. Considering the nanoscale reactant transport phenomena, a transport-based effective catalyst utilization factor is defined and statistically analyzed to determine the structure-transport influence on catalyst utilization. The tortuosity of the reactant mass transport path of VACNT catalyst layers is directly calculated from the streaklines. Subsequently, the corresponding effective mass diffusion coefficient is statistically predicted by applying the pre-estimated tortuosity factors to the Knudsen diffusion coefficient in the VACNT catalyst layers. The statistical estimation results clearly indicate that the morphological structures of VACNT catalyst layers reduce the tortuosity of reactant mass transport path when compared to conventional catalyst layer and significantly improve consequential effective mass diffusion coefficient of VACNT catalyst layer. Furthermore, catalyst utilization of the VACNT catalyst layer is substantially improved by enhanced mass diffusion and electric current paths despite the relatively poor interconnections of the ion transport paths.

Keywords: Lattice Boltzmann method, nano transport phenomena, polymer electrolyte fuel cells, vertically aligned carbon nanotube

Procedia PDF Downloads 192
867 Predicting Radioactive Waste Glass Viscosity, Density and Dissolution with Machine Learning

Authors: Joseph Lillington, Tom Gout, Mike Harrison, Ian Farnan

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The vitrification of high-level nuclear waste within borosilicate glass and its incorporation within a multi-barrier repository deep underground is widely accepted as the preferred disposal method. However, for this to happen, any safety case will require validation that the initially localized radionuclides will not be considerably released into the near/far-field. Therefore, accurate mechanistic models are necessary to predict glass dissolution, and these should be robust to a variety of incorporated waste species and leaching test conditions, particularly given substantial variations across international waste-streams. Here, machine learning is used to predict glass material properties (viscosity, density) and glass leaching model parameters from large-scale industrial data. A variety of different machine learning algorithms have been compared to assess performance. Density was predicted solely from composition, whereas viscosity additionally considered temperature. To predict suitable glass leaching model parameters, a large simulated dataset was created by coupling MATLAB and the chemical reactive-transport code HYTEC, considering the state-of-the-art GRAAL model (glass reactivity in allowance of the alteration layer). The trained models were then subsequently applied to the large-scale industrial, experimental data to identify potentially appropriate model parameters. Results indicate that ensemble methods can accurately predict viscosity as a function of temperature and composition across all three industrial datasets. Glass density prediction shows reliable learning performance with predictions primarily being within the experimental uncertainty of the test data. Furthermore, machine learning can predict glass dissolution model parameters behavior, demonstrating potential value in GRAAL model development and in assessing suitable model parameters for large-scale industrial glass dissolution data.

Keywords: machine learning, predictive modelling, pattern recognition, radioactive waste glass

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866 Promotional Mix as a Determinant of Consumer Buying Decision in the Food and Beverages Industry: A Case Study of Nigeria Bottling Company Plc., Asejire Ibadan

Authors: Adedeji S. Adegoke, Olakunle N. Popoola

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Promotion is indispensible and inestimable property of marketing through which different organizations persuade their prospective customers. The idea of passing information about a product to the consumer at outside the world is known as promotional activities. A study was determined whether there was relationship between promotional mix and consumer buying decision, that is may be customers were influenced by promotion. It was investigated to determine whether promotion can be used to influence competitors’ activities in the market and also research was conducted to determine if there was any problem encountered by Nigeria bottling company plc, in promoting its beverages products. The various forms of promotional mix available for an organization were examined and recommended the appropriate promotional mix that company can adopt to boost the company sales. The research design was depended on the primary and secondary data. The primary data were information collected from the subjects using methods of data collection, that is through the use of questionnaire, interview, direct observation, etc. The secondary data consist of information that already exists having been collected for another purpose by some researchers. These include internal and external sources. The questionnaire was designed and administered to the staff of production and marketing department of Nigeria bottling company plc., which served as the population of this study, out of which sample was drawn randomly from the population, using sample random technique. It was deduced that 90% of the respondents opined that advertising influenced competition in the market and that there was a good sale after they started advert while 10% of them were not sure. At advertising level, 85% of the respondents chose 81-100% as the increase in the percentage recorded in their sales level, while 10% of them agreed that increase in the percentage recorded in their sales was within 61-80% and 5% of them chose 45-60% as the percentage increase in their sales record. Due to unstable economic condition of the Nigeria, many business organizations adopted the promotional strategies. Apart from advertising, it was discovered through research that sales promotion served as an incentive to consumers of Nigeria bottling company plc at a time offer gifts and prizes to consumers which drastically increased their level of sales. Since advertising and sales promotion increased the level of sales, more money should be allocated for this purpose to maintain market share and thereby increase profit.

Keywords: consumer, marketing, organization, promotional mix

Procedia PDF Downloads 150
865 A Next Generation Multi-Scale Modeling Theatre for in silico Oncology

Authors: Safee Chaudhary, Mahnoor Naseer Gondal, Hira Anees Awan, Abdul Rehman, Ammar Arif, Risham Hussain, Huma Khawar, Zainab Arshad, Muhammad Faizyab Ali Chaudhary, Waleed Ahmed, Muhammad Umer Sultan, Bibi Amina, Salaar Khan, Muhammad Moaz Ahmad, Osama Shiraz Shah, Hadia Hameed, Muhammad Farooq Ahmad Butt, Muhammad Ahmad, Sameer Ahmed, Fayyaz Ahmed, Omer Ishaq, Waqar Nabi, Wim Vanderbauwhede, Bilal Wajid, Huma Shehwana, Muhammad Tariq, Amir Faisal

Abstract:

Cancer is a manifestation of multifactorial deregulations in biomolecular pathways. These deregulations arise from the complex multi-scale interplay between cellular and extracellular factors. Such multifactorial aberrations at gene, protein, and extracellular scales need to be investigated systematically towards decoding the underlying mechanisms and orchestrating therapeutic interventions for patient treatment. In this work, we propose ‘TISON’, a next-generation web-based multiscale modeling platform for clinical systems oncology. TISON’s unique modeling abstraction allows a seamless coupling of information from biomolecular networks, cell decision circuits, extra-cellular environments, and tissue geometries. The platform can undertake multiscale sensitivity analysis towards in silico biomarker identification and drug evaluation on cellular phenotypes in user-defined tissue geometries. Furthermore, integration of cancer expression databases such as The Cancer Genome Atlas (TCGA) and Human Proteome Atlas (HPA) facilitates in the development of personalized therapeutics. TISON is the next-evolution of multiscale cancer modeling and simulation platforms and provides a ‘zero-code’ model development, simulation, and analysis environment for application in clinical settings.

Keywords: systems oncology, cancer systems biology, cancer therapeutics, personalized therapeutics, cancer modelling

Procedia PDF Downloads 210
864 Prediction of Seismic Damage Using Scalar Intensity Measures Based on Integration of Spectral Values

Authors: Konstantinos G. Kostinakis, Asimina M. Athanatopoulou

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A key issue in seismic risk analysis within the context of Performance-Based Earthquake Engineering is the evaluation of the expected seismic damage of structures under a specific earthquake ground motion. The assessment of the seismic performance strongly depends on the choice of the seismic Intensity Measure (IM), which quantifies the characteristics of a ground motion that are important to the nonlinear structural response. Several conventional IMs of ground motion have been used to estimate their damage potential to structures. Yet, none of them has been proved to be able to predict adequately the seismic damage. Therefore, alternative, scalar intensity measures, which take into account not only ground motion characteristics but also structural information have been proposed. Some of these IMs are based on integration of spectral values over a range of periods, in an attempt to account for the information that the shape of the acceleration, velocity or displacement spectrum provides. The adequacy of a number of these IMs in predicting the structural damage of 3D R/C buildings is investigated in the present paper. The investigated IMs, some of which are structure specific and some are nonstructure-specific, are defined via integration of spectral values. To achieve this purpose three symmetric in plan R/C buildings are studied. The buildings are subjected to 59 bidirectional earthquake ground motions. The two horizontal accelerograms of each ground motion are applied along the structural axes. The response is determined by nonlinear time history analysis. The structural damage is expressed in terms of the maximum interstory drift as well as the overall structural damage index. The values of the aforementioned seismic damage measures are correlated with seven scalar ground motion IMs. The comparative assessment of the results revealed that the structure-specific IMs present higher correlation with the seismic damage of the three buildings. However, the adequacy of the IMs for estimation of the structural damage depends on the response parameter adopted. Furthermore, it was confirmed that the widely used spectral acceleration at the fundamental period of the structure is a good indicator of the expected earthquake damage level.

Keywords: damage measures, bidirectional excitation, spectral based IMs, R/C buildings

Procedia PDF Downloads 317
863 D-Epi App: Mobile Application to Control Sodium Valproat Administration in Children with Idiopatic Epilepsy in Indonesia

Authors: Nyimas Annissa Mutiara Andini

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There are 325,000 children younger than age 15 in the U.S. have epilepsy. In Indonesia, 40% of 3,5 millions cases of epilepsy happens in children. The most common type of epilepsy, which affects 6 out of 10 people with the disorder, is called idiopathic epilepsy and which has no identifiable cause. One of the most commonly used medications in the treatment of this childhood epilepsy is sodium valproate. Administration of sodium valproat in children has a problem to fail. Nearly 60% of pediatric patients known were mildly, moderately, or severely non-adherent with therapy during the first six months of treatment. Many parents or caregiver took far less medication than prescribed, and the treatment-adherence pattern for the majority of patients was established during the first month of treatment. 42% of the patients were almost always given their medications as prescribed but 13% had very poor adherence even in the early weeks and months of treatment. About 7% of patients initially gave the medication correctly 90% of the time, but adherence dropped to around 20% within six months of starting treatment. Over the six months of observation, the total missing of administration is about four out of 14 doses in any given week. This fail can cause the epilepsy to relapse. Whereas, current reported epilepsy disorder were significantly more likely than those never diagnosed to experience depression (8% vs 2%), anxiety (17% vs 3%), attention-deficit/hyperactivity disorder (23% vs 6%), developmental delay (51% vs 3%), autism/autism spectrum disorder (16% vs 1%), and headaches (14% vs 5%) (all P< 0.05). They had a greater risk of limitation in the ability to do things (relative risk: 9.22; 95% CI: 7.56–11.24), repeating a school grade (relative risk: 2.59; CI: 1.52–4.40), and potentially having unmet medical and mental health needs. In the other side, technology can help to make our life easier. One of the technology, that we can use is a mobile application. A mobile app is a software program we can download and access directly using our phone. Indonesians are highly mobile centric. They use, on average, 6.7 applications over a 30 day period. This paper is aimed to describe an application that could help to control a sodium valproat administration in children; we call it as D-Epi app. D-Epi app is a downloadable application that can help parents or caregiver alert by a timer-related application to warn whether it is the time to administer the sodium valproat. It works not only as a standard alarm, but also inform important information about the drug and emergency stuffs to do to children with epilepsy. This application could help parents and caregiver to take care a child with epilepsy in Indonesia.

Keywords: application, children, D-Epi, epilepsy

Procedia PDF Downloads 269
862 The Effects of Cultural Distance and Institutions on Foreign Direct Investment Choices: Evidence from Turkey and China

Authors: Nihal Kartaltepe Behram, Göksel Ataman, Dila Okçu

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With the development of foreign direct investments, the social, cultural, political and economic interactions between countries and institutions have become visible and they have become determining factors for the strategic structuring and market goals. In this context the purpose of this study is to investigate the effects of cultural distance and institutions on foreign direct investment choices in terms of location and investment model. For international establishments, the concept of culture, as well as the concept of cultural distance, is taken specifically into consideration, especially in the selection of methods for entering the market. In the researches and empirical studies conducted, a direct relationship between cultural distance and foreign direct investments is set and institutions and effective variable factors are examined at the level of defining the investment types. When the detailed calculation strategies and empirical researches and studies are taken into consideration, the most common methods for determining the direct investment model, considering the cultural distances, are full-ownership enterprises and joint ventures. Also, when all of the factors affecting the investments are taken into consideration, it was seen that the effect of institutions such as Government Intervention, Intellectual Property Rights, Corruption and Contract Enforcements is very important. Furthermore agglomeration is more intense and effective on the investment, compared to other factors. China has been selected as the target country, due to its effectiveness in world economy and its contributions to developing countries, which has commercial relationships with. Qualitative research methods are used for this study conducted, to measure the effects of determinative variable factors in the hypotheses of study, on the direct foreign investors and to evaluate the findings. In this study in-depth interview is used as a data collection method and the data analysis is made through descriptive analysis. Foreign Direct Investments are so reactive to institutions and cultural distance is identified by all interviews and analysis. On the other hand, agglomeration is the most strong determiner factor on foreign direct investors in Chinese Market. The reason of this factors, which comprise the sectorial aggregate, are not the strongest factors as agglomeration that the most important finding. We expect that this study became a beneficial guideline for developed and developing countries and local and national institutions’ strategic plans.

Keywords: China, cultural distance, Foreign Direct Investments, institutions

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861 Bioinformatics Approach to Identify Physicochemical and Structural Properties Associated with Successful Cell-free Protein Synthesis

Authors: Alexander A. Tokmakov

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Cell-free protein synthesis is widely used to synthesize recombinant proteins. It allows genome-scale expression of various polypeptides under strictly controlled uniform conditions. However, only a minor fraction of all proteins can be successfully expressed in the systems of protein synthesis that are currently used. The factors determining expression success are poorly understood. At present, the vast volume of data is accumulated in cell-free expression databases. It makes possible comprehensive bioinformatics analysis and identification of multiple features associated with successful cell-free expression. Here, we describe an approach aimed at identification of multiple physicochemical and structural properties of amino acid sequences associated with protein solubility and aggregation and highlight major correlations obtained using this approach. The developed method includes: categorical assessment of the protein expression data, calculation and prediction of multiple properties of expressed amino acid sequences, correlation of the individual properties with the expression scores, and evaluation of statistical significance of the observed correlations. Using this approach, we revealed a number of statistically significant correlations between calculated and predicted features of protein sequences and their amenability to cell-free expression. It was found that some of the features, such as protein pI, hydrophobicity, presence of signal sequences, etc., are mostly related to protein solubility, whereas the others, such as protein length, number of disulfide bonds, content of secondary structure, etc., affect mainly the expression propensity. We also demonstrated that amenability of polypeptide sequences to cell-free expression correlates with the presence of multiple sites of post-translational modifications. The correlations revealed in this study provide a plethora of important insights into protein folding and rationalization of protein production. The developed bioinformatics approach can be of practical use for predicting expression success and optimizing cell-free protein synthesis.

Keywords: bioinformatics analysis, cell-free protein synthesis, expression success, optimization, recombinant proteins

Procedia PDF Downloads 407