Search results for: erosion rate prediction
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 10434

Search results for: erosion rate prediction

6264 Faster, Lighter, More Accurate: A Deep Learning Ensemble for Content Moderation

Authors: Arian Hosseini, Mahmudul Hasan

Abstract:

To address the increasing need for efficient and accurate content moderation, we propose an efficient and lightweight deep classification ensemble structure. Our approach is based on a combination of simple visual features, designed for high-accuracy classification of violent content with low false positives. Our ensemble architecture utilizes a set of lightweight models with narrowed-down color features, and we apply it to both images and videos. We evaluated our approach using a large dataset of explosion and blast contents and compared its performance to popular deep learning models such as ResNet-50. Our evaluation results demonstrate significant improvements in prediction accuracy, while benefiting from 7.64x faster inference and lower computation cost. While our approach is tailored to explosion detection, it can be applied to other similar content moderation and violence detection use cases as well. Based on our experiments, we propose a "think small, think many" philosophy in classification scenarios. We argue that transforming a single, large, monolithic deep model into a verification-based step model ensemble of multiple small, simple, and lightweight models with narrowed-down visual features can possibly lead to predictions with higher accuracy.

Keywords: deep classification, content moderation, ensemble learning, explosion detection, video processing

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6263 Ambient Vibration Test and Numerical Modelling of Wind Turbine Towers including Soil Structure Interaction

Authors: Heba Kamal, Ghada Saudi

Abstract:

Due to The rapid expansion of energy and growing number of wind turbines construction in earthquake areas, a design method for simple and accurate evaluation of seismic load to ensure structural integrity is required. In Egypt, there are some appropriate places to build wind turbine towers lie in active seismically regions, so accurate analysis is necessary for prediction of seismic loads with consideration of intensity of the earthquake, soil and structural characteristics. In this research, seismic behavior of wind turbine towers Gamesa Type G52 in Zafarana Wind Farm Egypt is investigated using experimental work by ambient vibration test, and fully dynamic analysis based on time history from El Aqaba Earthquake 1995 using 3D by PLAXIS 3D software, including the soil structure interaction effect. The results obtained from dynamic analyses are discussed. From this study, it is concluded that, the fully dynamic seismic analysis based on used PLAXIS 3D with the aid of the full scale ambient vibration test gives almost good simulation for the seismic loads that can be applied to wind turbine tower design in Egypt.

Keywords: Wind turbine towers, Zafarana Wind Farm, Gamesa Type G52, ambient vibration test

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6262 Analysis of Secondary Stage Creep in Thick-Walled Composite Cylinders Subjected to Rotary Inertia

Authors: Tejeet Singh, Virat Khanna

Abstract:

Composite materials have drawn considerable attention of engineers due to their light weight and application at high thermo-mechanical loads. With regard to the prediction of the life of high temperature structural components like rotating cylinders and the evaluation of their deterioration with time, it is essential to have a full knowledge of creep characteristics of these materials. Therefore, in the present study the secondary stage creep stresses and strain rates are estimated in thick-walled composite cylinders subjected to rotary inertia at different angular speeds. The composite cylinder is composed of aluminum matrix (Al) and reinforced with silicon carbide (SiC) particles which are uniformly mixed. The creep response of the material of the cylinder is described by threshold stress based creep law. The study indicates that with the increase in angular speed, the radial, tangential, axial and effective stress increases to a significant value. However, the radial stress remains zero at inner radius and outer radius due to imposed boundary conditions of zero pressure. Further, the stresses are tensile in nature throughout the entire radius of composite cylinder. The strain rates are also influenced in the same manner as that of creep stresses. The creep rates will increase significantly with the increase of centrifugal force on account of rotation.

Keywords: composite, creep, rotating cylinder, angular speed

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6261 Modelling and Simulation of Natural Gas-Fired Power Plant Integrated to a CO2 Capture Plant

Authors: Ebuwa Osagie, Chet Biliyok, Yeung Hoi

Abstract:

Regeneration energy requirement and ways to reduce it is the main aim of most CO2 capture researches currently being performed and thus, post-combustion carbon capture (PCC) option is identified to be the most suitable for the natural gas-fired power plants. From current research and development (R&D) activities worldwide, two main areas are being examined in order to reduce the regeneration energy requirement of amine-based PCC, namely: (a) development of new solvents with better overall performance than 30wt% monoethanolamine (MEA) aqueous solution, which is considered as the base-line solvent for solvent-based PCC, (b) Integration of the PCC Plant to the power plant. In scaling-up a PCC pilot plant to the size required for a commercial-scale natural gas-fired power plant, process modelling and simulation is very essential. In this work, an integrated process made up of a 482MWe natural gas-fired power plant, an MEA-based PCC plant which is developed and validated has been modelled and simulated. The PCC plant has four absorber columns and a single stripper column, the modelling and simulation was performed with Aspen Plus® V8.4. The gas turbine, the heat recovery steam generator and the steam cycle were modelled based on a 2010 US DOE report, while the MEA-based PCC plant was modelled as a rate-based process. The scaling of the amine plant was performed using a rate based calculation in preference to the equilibrium based approach for 90% CO2 capture. The power plant was integrated to the PCC plant in three ways: (i) flue gas stream from the power plant which is divided equally into four stream and each stream is fed into one of the four absorbers in the PCC plant. (ii) Steam draw-off from the IP/LP cross-over pipe in the steam cycle of the power plant used to regenerate solvent in the reboiler. (iii) Condensate returns from the reboiler to the power plant. The integration of a PCC plant to the NGCC plant resulted in a reduction of the power plant output by 73.56 MWe and the net efficiency of the integrated system is reduced by 7.3 % point efficiency. A secondary aim of this study is the parametric studies which have been performed to assess the impacts of natural gas on the overall performance of the integrated process and this is achieved through investigation of the capture efficiencies.

Keywords: natural gas-fired, power plant, MEA, CO2 capture, modelling, simulation

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6260 Influence of IL-1β on Hamster Blastocyst Hatching via Regulation of Hatching Associated Proteases

Authors: Madhulika Pathak, Polani Seshagiri, Vani Venkatappa

Abstract:

Blastocyst hatching is an indispensable process for successful implantation. One of the major reasons for implantation failure in IVF clinic is poor quality of embryo, which are not development/hatching-competent. Therefore, attempts are required to develop or enhance the culture system with a molecule recapitulating the autocrine/paracrine factors containing the environment of in-vivo endometrial milieu. We have tried to explore the functional molecules involved in the hamster hatching phenomenon. Blastocyst hatching is governed by several molecules that are entwined and regulate this process, among which cytokines are known to be expressed and are still least explored. Two of such cytokines we have used for our study are IL-1β and its natural antagonist IL-1ra to understand the functional dynamics of cytokines involved in the hatching process. Using hamster, an intriguing experimental model for hatching behavior, we have shown the mRNA (qPCR) and protein (ICC) expression of IL-1β, IL-1ra and IL-1 receptor type 1 throughout all the stages of morula, blastocyst and hatched blastocyst. Post-asserting the expression, the functional role is shown by supplementation studies, where IL-1β supplementation showed enhancement in hatching level (IL-1β treated: 84.1 ± 4.2% vs control: 63.7 ± 3.1 %, N=11), further confirmed by the diminishing effect of IL-1ra on hatching rate (IL-1ra treated: 27.5 ± 11.1% vs control: 67.9 ± 3.1%). The exogenous supplementation of IL-1ra decreased the survival rate of embryos and affected the viability in dose-dependent manner, establishing the importance of IL-1β in blastocyst cell survival. Previously, the cathepsin L and B were established as the proteases that were involved in the hamster hatching process. The inducing effect of IL-1β was correlated with enhanced mRNA level, as analyzed by qPCR, for both CAT L (by 1.9 ± 0.5 fold) and CAT B (by 3.5 ± 0.1) fold which was diminished in presence of IL-1ra (Cat L by 88 percent and Cat B by 94 percent. Moreover, using a specific fluorescent substrate-based assay kit, the enzymatic activity of these proteases was found to be increased in presence of IL-1β (Cat L by 2.1 ± 0.1 fold and CAT B by 2.3 ± 0.7 fold) and was curtailed in presence of IL-1ra. These observations provide functional insights with respect to the involvement of cytokines in the hatching process. This has implications in understanding the hatching biology and improving the embryo development quality in IVF clinics.

Keywords: Blastocyst, Cytokines, Hatching, Interleukin

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6259 Jordanian Health Care Providers' Attitudes toward Overweigth and Obese Women during Childbirth

Authors: Salwa Obeisat

Abstract:

Obesity had become a global issue and a major public health concern, because of its impact on the public health. Obstetric and midwifery evidences reported that maternal obesity an important issue, because of its associated complications like obstructed labors, infections, and hemorrhage. People who are obese are often stigmatized and blamed for their weight. Health care providers are not immune to obesity-related prejudice, and the literature features several examples of their negative attitudes towards obese patients. In Jordan, few studies were conducted to investigate obesity prevalence rate and its associated factors. The purposes of this study were to assess the health care providers' attitudes toward overweight and obese women during the childbirth in the North of Jordan and to investigate the relationships between health care providers' socio-demographic characteristics and their attitudes. A descriptive, cross-sectional design was utilized. A convenient sample was consisted of 95 midwives, 30 nurses and 62 obstetricians, who were working in the labor rooms. A self-administered questionnaire consisted of three sections: demographical data, Arabic version of Fat Phobia Scale (FPS), and Arabic version of Nurses' Attitudes toward Obesity and Obese Patients Scale (NATOOPS). Results: The study findings revealed that the majority of Jordanian health care providers held negative attitudes toward overweight and obese women during childbirth. Midwives held less negative attitudes than did obstetricians and nurses. The majority of participants were perceived the overweight and obese pregnant women during childbirth as overate people, shapeless, slow and unattractive. Age, specialty, education and years of experience were found to be associated with health care providers’ attitudes. The Conclusion: Health care providers negative attitudes toward overweight and obese pregnant women are a cause for concern. Therefore, maternal obesity was needed to be more adequately addressed in basic education courses, and in the continuing professional education classes of practicing health care providers.

Keywords: attitudes, obesity, prevalence rate, nurses, midwives, obstetrician, childbirth

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6258 Quantitative Structure–Activity Relationship Analysis of Some Benzimidazole Derivatives by Linear Multivariate Method

Authors: Strahinja Z. Kovačević, Lidija R. Jevrić, Sanja O. Podunavac Kuzmanović

Abstract:

The relationship between antibacterial activity of eighteen different substituted benzimidazole derivatives and their molecular characteristics was studied using chemometric QSAR (Quantitative Structure–Activity Relationships) approach. QSAR analysis has been carried out on inhibitory activity towards Staphylococcus aureus, by using molecular descriptors, as well as minimal inhibitory activity (MIC). Molecular descriptors were calculated from the optimized structures. Principal component analysis (PCA) followed by hierarchical cluster analysis (HCA) and multiple linear regression (MLR) was performed in order to select molecular descriptors that best describe the antibacterial behavior of the compounds investigated, and to determine the similarities between molecules. The HCA grouped the molecules in separated clusters which have the similar inhibitory activity. PCA showed very similar classification of molecules as the HCA, and displayed which descriptors contribute to that classification. MLR equations, that represent MIC as a function of the in silico molecular descriptors were established. The statistical significance of the estimated models was confirmed by standard statistical measures and cross-validation parameters (SD = 0.0816, F = 46.27, R = 0.9791, R2CV = 0.8266, R2adj = 0.9379, PRESS = 0.1116). These parameters indicate the possibility of application of the established chemometric models in prediction of the antibacterial behaviour of studied derivatives and structurally very similar compounds.

Keywords: antibacterial, benzimidazole, molecular descriptors, QSAR

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6257 A Fuzzy Inference System for Predicting Air Traffic Demand Based on Socioeconomic Drivers

Authors: Nur Mohammad Ali, Md. Shafiqul Alam, Jayanta Bhusan Deb, Nowrin Sharmin

Abstract:

The past ten years have seen significant expansion in the aviation sector, which during the previous five years has steadily pushed emerging countries closer to economic independence. It is crucial to accurately forecast the potential demand for air travel to make long-term financial plans. To forecast market demand for low-cost passenger carriers, this study suggests working with low-cost airlines, airports, consultancies, and governmental institutions' strategic planning divisions. The study aims to develop an artificial intelligence-based methods, notably fuzzy inference systems (FIS), to determine the most accurate forecasting technique for domestic low-cost carrier demand in Bangladesh. To give end users real-world applications, the study includes nine variables, two sub-FIS, and one final Mamdani Fuzzy Inference System utilizing a graphical user interface (GUI) made with the app designer tool. The evaluation criteria used in this inquiry included mean square error (MSE), accuracy, precision, sensitivity, and specificity. The effectiveness of the developed air passenger demand prediction FIS is assessed using 240 data sets, and the accuracy, precision, sensitivity, specificity, and MSE values are 90.83%, 91.09%, 90.77%, and 2.09%, respectively.

Keywords: aviation industry, fuzzy inference system, membership function, graphical user interference

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6256 Use of Serum Creatinine as an Incentive to Increase Prep Uptake Among Key Population Groups in South-South Nigeria

Authors: Akhigbe Mark, Abang Roger, Mwoltu Nanaribet, Edet Blessing

Abstract:

Introduction.: The introduction of pre- exposure prophylaxis (PrEP) as a biomedical prevention method for HIV/AIDS has been around for more than a decade since the first confirmed evidence of its effectiveness when used daily as an oral pill. It is now a very valuable addition for people who are at higher risk of contracting HIV. Although globalacceptanceof PrEP hasincreased, PrEP is still highly concentrated in a small number of countries and within a small sub-population, with Kenya and South Africa accounting for only 19% of people who have received PrEP in Africa region, there is still a significant regionGap in PrEP availability and use, with only 28% of the target of 3 million in low-and middle countries currently using PrEP. Description: The purpose of this study is to find out if serum creatinine could be used as an incentive to improve PrEP uptake among Key population.Numerous approaches to increasing the uptake ofPrEP as a prevention mechanism for HIV in KPs has beenemployed, and one of them is serum creatinine. This approach is a biomarker of renal function, which was used in study as an incentive to increase PrEP uptake among key population groups (female sex workers, men who have sex with men, persons who inject drugs, transgender) in 3 states from South-South Nigeria. Whole blood samples are collected from clients, analysis of the samples is done using the clinical chemistry analyzer before they are initiated onto PrEP. Lessons learned and Recommendations: Secondary data was extracted from 3 states of HALG Implementing facilities in Southern part of Nigeria, PrEP uptake before and afterthe introduction of serum creatinine between March 2020 and August 2020 among key populationsin Nigeria. A total of 5664 patients were initiated on PrEP before, and after the introduction of serum creatinine, the PrEP uptake rate before (March 2020 to May 2020) introduction of serum creatinine accounted for only 5% of the total onset, and after (June 2020 to August 2020) introduction of serum creatinine, the uptake rate accounted for 95% of the total onset. These finding shows that increased uptake of PrEP before/after serum creatineindicates that serum creatine may be an effective stimulus for promoting PrEP in key populations.

Keywords: serum creatinine, incentives, PrEP, key populations, Nigeria

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6255 Collective Behavior of Mice Passing through a Middle-Exit or Corner-Exit under Panic

Authors: Teng Zhang, Xuelin Zhang, Shouxiang Lu, Changhai Li

Abstract:

The existence of animal groups and collective migration are common in nature, and collective behavior is attracting more and more attention of researchers. Previous results have shown that architectural design had an important effect on the process of crowd evacuation. In this paper, collective behavior of mice passing through a middle-exit or corner-exit under panic was investigated. Selfish behavior and herd behavior were easily observed in our video, which caused the congregation with high density near the exit. Triangle structure of congregation formed near the middle-exit while arch structure formed near the corner-exit. It is noteworthy that the exit located at the middle of the wall was more effective for evacuation than at the corner. Meanwhile, the escape sequence of mouse passing through the exit was investigated, and the result showed that the priority depends largely on its location in the congregation. With the level of stimulus increasing, these phenomena still exist. The frequency distributions of time intervals and the burst sizes were also analyzed in this study to explore the secret of collective behavior of mice. These results could provide evidence for the hypothesis or prediction about human behavior in crowd evacuation. However, it is not clear whether the simulated results from different species can correspond to reality or not. Broader comparison among different species about this topic will be eager to be conducted to deepen our understanding of collective behavior in nature.

Keywords: collective behavior, mice, evacuation, exit location

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6254 A Kernel-Based Method for MicroRNA Precursor Identification

Authors: Bin Liu

Abstract:

MicroRNAs (miRNAs) are small non-coding RNA molecules, functioning in transcriptional and post-transcriptional regulation of gene expression. The discrimination of the real pre-miRNAs from the false ones (such as hairpin sequences with similar stem-loops) is necessary for the understanding of miRNAs’ role in the control of cell life and death. Since both their small size and sequence specificity, it cannot be based on sequence information alone but requires structure information about the miRNA precursor to get satisfactory performance. Kmers are convenient and widely used features for modeling the properties of miRNAs and other biological sequences. However, Kmers suffer from the inherent limitation that if the parameter K is increased to incorporate long range effects, some certain Kmer will appear rarely or even not appear, as a consequence, most Kmers absent and a few present once. Thus, the statistical learning approaches using Kmers as features become susceptible to noisy data once K becomes large. In this study, we proposed a Gapped k-mer approach to overcome the disadvantages of Kmers, and applied this method to the field of miRNA prediction. Combined with the structure status composition, a classifier called imiRNA-GSSC was proposed. We show that compared to the original imiRNA-kmer and alternative approaches. Trained on human miRNA precursors, this predictor can achieve an accuracy of 82.34 for predicting 4022 pre-miRNA precursors from eleven species.

Keywords: gapped k-mer, imiRNA-GSSC, microRNA precursor, support vector machine

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6253 A Tool to Measure Efficiency and Trust Towards eXplainable Artificial Intelligence in Conflict Detection Tasks

Authors: Raphael Tuor, Denis Lalanne

Abstract:

The ATM research community is missing suitable tools to design, test, and validate new UI prototypes. Important stakes underline the implementation of both DSS and XAI methods into current systems. ML-based DSS are gaining in relevance as ATFM becomes increasingly complex. However, these systems only prove useful if a human can understand them, and thus new XAI methods are needed. The human-machine dyad should work as a team and should understand each other. We present xSky, a configurable benchmark tool that allows us to compare different versions of an ATC interface in conflict detection tasks. Our main contributions to the ATC research community are (1) a conflict detection task simulator (xSky) that allows to test the applicability of visual prototypes on scenarios of varying difficulty and outputting relevant operational metrics (2) a theoretical approach to the explanations of AI-driven trajectory predictions. xSky addresses several issues that were identified within available research tools. Researchers can configure the dimensions affecting scenario difficulty with a simple CSV file. Both the content and appearance of the XAI elements can be customized in a few steps. As a proof-of-concept, we implemented an XAI prototype inspired by the maritime field.

Keywords: air traffic control, air traffic simulation, conflict detection, explainable artificial intelligence, explainability, human-automation collaboration, human factors, information visualization, interpretability, trajectory prediction

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6252 Molecular Docking Assessment of Pesticides Binding to Bacterial Chitinases

Authors: Diana Larisa Vladoiu, Vasile Ostafe, Adriana Isvoran

Abstract:

Molecular docking calculations reveal that pesticides provide favorable interactions with the bacterial chitinases. Pesticides interact with both hydrophilic and aromatic residues involved in the active site of the enzymes, their positions partially overlapping the substrate and the inhibitors locations. Molecular docking outcomes, in correlation with experimental literature data, suggest that the pesticides may be degraded or having an inhibitor effect on the activity of these enzymes, depending of the application dose and rate.

Keywords: chitinases, inhibition, molecular docking, pesticides

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6251 Wave-Assisted Flapping Foil Propulsion: Flow Physics and Scaling Laws From Fluid-Structure Interaction Simulations

Authors: Rajat Mittal, Harshal Raut, Jung Hee Seo

Abstract:

Wave-assisted propulsion (WAP) systems convert wave energy into thrust using elastically mounted hydrofoils. We employ sharp-interface immersed boundary simulations to examine the effect of two key parameters on the flow physics, the fluid-structure interaction, as well as thrust performance of these systems - the stiffness of the torsional spring and the location of the rotational center. The variation in spring stiffness leads to different amplitude of pitch motion, phase difference with respect to heaving motion and thrust coefficient and we show the utility of ‘maps’ of energy exchange between the flow and the hydrofoil system, as a way to understand and predict this behavior. The Force Partitioning Method (FPM) is used to decompose the pressure forces into individual components and understand the mechanism behind increase in thrust. Next, a scaling law is presented for the thrust coefficient generated by heaving and pitching foil. The parameters within the scaling law are calculated based on direct-numerical simulations based parametric study utilized to generate the energy maps. The predictions of the proposed scaling law are then compared with those of a similar model from the literature, showing a noticeable improvement in the prediction of the thrust coefficient.

Keywords: propulsion, flapping foils, hydrodynamics, wave power

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6250 Multi-Objective Optimization of Run-of-River Small-Hydropower Plants Considering Both Investment Cost and Annual Energy Generation

Authors: Amèdédjihundé H. J. Hounnou, Frédéric Dubas, François-Xavier Fifatin, Didier Chamagne, Antoine Vianou

Abstract:

This paper presents the techno-economic evaluation of run-of-river small-hydropower plants. In this regard, a multi-objective optimization procedure is proposed for the optimal sizing of the hydropower plants, and NSGAII is employed as the optimization algorithm. Annual generated energy and investment cost are considered as the objective functions, and number of generator units (n) and nominal turbine flow rate (QT) constitute the decision variables. Site of Yeripao in Benin is considered as the case study. We have categorized the river of this site using its environmental characteristics: gross head, and first quartile, median, third quartile and mean of flow. Effects of each decision variable on the objective functions are analysed. The results gave Pareto Front which represents the trade-offs between annual energy generation and the investment cost of hydropower plants, as well as the recommended optimal solutions. We noted that with the increase of the annual energy generation, the investment cost rises. Thus, maximizing energy generation is contradictory with minimizing the investment cost. Moreover, we have noted that the solutions of Pareto Front are grouped according to the number of generator units (n). The results also illustrate that the costs per kWh are grouped according to the n and rise with the increase of the nominal turbine flow rate. The lowest investment costs per kWh are obtained for n equal to one and are between 0.065 and 0.180 €/kWh. Following the values of n (equal to 1, 2, 3 or 4), the investment cost and investment cost per kWh increase almost linearly with increasing the nominal turbine flowrate while annual generated. Energy increases logarithmically with increasing of the nominal turbine flowrate. This study made for the Yeripao river can be applied to other rivers with their own characteristics.

Keywords: hydropower plant, investment cost, multi-objective optimization, number of generator units

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6249 On Cold Roll Bonding of Polymeric Films

Authors: Nikhil Padhye

Abstract:

Recently a new phenomenon for bonding of polymeric films in solid-state, at ambient temperatures well below the glass transition temperature of the polymer, has been reported. This is achieved by bulk plastic compression of polymeric films held in contact. Here we analyze the process of cold-rolling of polymeric films via finite element simulations and illustrate a flexible and modular experimental rolling-apparatus that can achieve bonding of polymeric films through cold-rolling. Firstly, the classical theory of rolling a rigid-plastic thin-strip is utilized to estimate various deformation fields such as strain-rates, velocities, loads etc. in rolling the polymeric films at the specified feed-rates and desired levels of thickness-reduction(s). Predicted magnitudes of slow strain-rates, particularly at ambient temperatures during rolling, and moderate levels of plastic deformation (at which Bauschinger effect can be neglected for the particular class of polymeric materials studied here), greatly simplifies the task of material modeling and allows us to deploy a computationally efficient, yet accurate, finite deformation rate-independent elastic-plastic material behavior model (with inclusion of isotropic-hardening) for analyzing the rolling of these polymeric films. The interfacial behavior between the roller and polymer surfaces is modeled using Coulombic friction; consistent with the rate-independent behavior. The finite deformation elastic-plastic material behavior based on (i) the additive decomposition of stretching tensor (D = De + Dp, i.e. a hypoelastic formulation) with incrementally objective time integration and, (ii) multiplicative decomposition of deformation gradient (F = FeFp) into elastic and plastic parts, are programmed and carried out for cold-rolling within ABAQUS Explicit. Predictions from both the formulations, i.e., hypoelastic and multiplicative decomposition, exhibit a close match. We find that no specialized hyperlastic/visco-plastic model is required to describe the behavior of the blend of polymeric films, under the conditions described here, thereby speeding up the computation process .

Keywords: Polymer Plasticity, Bonding, Deformation Induced Mobility, Rolling

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6248 Estimation of Thermal Conductivity of Nanofluids Using MD-Stochastic Simulation-Based Approach

Authors: Sujoy Das, M. M. Ghosh

Abstract:

The thermal conductivity of a fluid can be significantly enhanced by dispersing nano-sized particles in it, and the resultant fluid is termed as "nanofluid". A theoretical model for estimating the thermal conductivity of a nanofluid has been proposed here. It is based on the mechanism that evenly dispersed nanoparticles within a nanofluid undergo Brownian motion in course of which the nanoparticles repeatedly collide with the heat source. During each collision a rapid heat transfer occurs owing to the solid-solid contact. Molecular dynamics (MD) simulation of the collision of nanoparticles with the heat source has shown that there is a pulse-like pick up of heat by the nanoparticles within 20-100 ps, the extent of which depends not only on thermal conductivity of the nanoparticles, but also on the elastic and other physical properties of the nanoparticle. After the collision the nanoparticles undergo Brownian motion in the base fluid and release the excess heat to the surrounding base fluid within 2-10 ms. The Brownian motion and associated temperature variation of the nanoparticles have been modeled by stochastic analysis. Repeated occurrence of these events by the suspended nanoparticles significantly contributes to the characteristic thermal conductivity of the nanofluids, which has been estimated by the present model for a ethylene glycol based nanofluid containing Cu-nanoparticles of size ranging from 8 to 20 nm, with Gaussian size distribution. The prediction of the present model has shown a reasonable agreement with the experimental data available in literature.

Keywords: brownian dynamics, molecular dynamics, nanofluid, thermal conductivity

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6247 Detecting Earnings Management via Statistical and Neural Networks Techniques

Authors: Mohammad Namazi, Mohammad Sadeghzadeh Maharluie

Abstract:

Predicting earnings management is vital for the capital market participants, financial analysts and managers. The aim of this research is attempting to respond to this query: Is there a significant difference between the regression model and neural networks’ models in predicting earnings management, and which one leads to a superior prediction of it? In approaching this question, a Linear Regression (LR) model was compared with two neural networks including Multi-Layer Perceptron (MLP), and Generalized Regression Neural Network (GRNN). The population of this study includes 94 listed companies in Tehran Stock Exchange (TSE) market from 2003 to 2011. After the results of all models were acquired, ANOVA was exerted to test the hypotheses. In general, the summary of statistical results showed that the precision of GRNN did not exhibit a significant difference in comparison with MLP. In addition, the mean square error of the MLP and GRNN showed a significant difference with the multi variable LR model. These findings support the notion of nonlinear behavior of the earnings management. Therefore, it is more appropriate for capital market participants to analyze earnings management based upon neural networks techniques, and not to adopt linear regression models.

Keywords: earnings management, generalized linear regression, neural networks multi-layer perceptron, Tehran stock exchange

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6246 Numerical Simulations for Nitrogen Flow in Piezoelectric Valve

Authors: Pawel Flaszynski, Piotr Doerffer, Jan Holnicki-Szulc, Grzegorz Mikulowski

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Results of numerical simulations for transonic flow in a piezoelectric valve are presented. The valve is the main part of an adaptive pneumatic shock absorber. Flow structure in the valve domain and the influence of the flow non-uniformity in the valve on a mass flow rate is investigated. Numerical simulation results are compared with experimental data.

Keywords: pneumatic valve, transonic flow, numerical simulations, piezoelectric valve

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6245 A Posterior Predictive Model-Based Control Chart for Monitoring Healthcare

Authors: Yi-Fan Lin, Peter P. Howley, Frank A. Tuyl

Abstract:

Quality measurement and reporting systems are used in healthcare internationally. In Australia, the Australian Council on Healthcare Standards records and reports hundreds of clinical indicators (CIs) nationally across the healthcare system. These CIs are measures of performance in the clinical setting, and are used as a screening tool to help assess whether a standard of care is being met. Existing analysis and reporting of these CIs incorporate Bayesian methods to address sampling variation; however, such assessments are retrospective in nature, reporting upon the previous six or twelve months of data. The use of Bayesian methods within statistical process control for monitoring systems is an important pursuit to support more timely decision-making. Our research has developed and assessed a new graphical monitoring tool, similar to a control chart, based on the beta-binomial posterior predictive (BBPP) distribution to facilitate the real-time assessment of health care organizational performance via CIs. The BBPP charts have been compared with the traditional Bernoulli CUSUM (BC) chart by simulation. The more traditional “central” and “highest posterior density” (HPD) interval approaches were each considered to define the limits, and the multiple charts were compared via in-control and out-of-control average run lengths (ARLs), assuming that the parameter representing the underlying CI rate (proportion of cases with an event of interest) required estimation. Preliminary results have identified that the BBPP chart with HPD-based control limits provides better out-of-control run length performance than the central interval-based and BC charts. Further, the BC chart’s performance may be improved by using Bayesian parameter estimation of the underlying CI rate.

Keywords: average run length (ARL), bernoulli cusum (BC) chart, beta binomial posterior predictive (BBPP) distribution, clinical indicator (CI), healthcare organization (HCO), highest posterior density (HPD) interval

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6244 Effects of Indole on Aerobic Biodegradation of Butanoic Acid by Pseudomonas aeruginosa and Serratia marcescens

Authors: J. B. J. Njalam’mano, E. M. N. Chirwa

Abstract:

In low resource settings in Africa and other developing regions, pit latrines remain the dominant basic minimum acceptable form of sanitation. However, unpleasant smells-malodours emitted from faecal sludge in the pit latrines, which elicit disgusting or repulsive response, are one of the factors that thwart people to use latrines and instead opt for open defecation as an alternative. This provides an important but often overlooked major impediment, dissuading people from adopting and using the pit latrines hence affecting successful, effective sanitation promotion. The malodours are primarily attributed to four odorants: butanoic acid (C₄H₈O₂), dimethyl trisulphide (C₂H₆S₃), indole (C₈H₇N) and para-cresol (C₇H₈O). Several pit latrine deodorisation methods such as addition of carbonous materials, use of ventilation systems and urine separation are available, and they continue to occupy their niche, but social, economic, environmental and technological shortfalls remain. Bioremediation has been gaining popularity because it is inexpensive, simple to operate and environmentally friendly. Recently, the biodegradation of butanoic acid as individual odorant has been studied. However, to the best of our knowledge, there have been no kinetic studies of the butanoic acid in the presence of other key odorous compounds. In this study, a series of experiments were conducted to investigate the effects of indole on the removal of butanoic acid under aerobic conditions using indigenous bacteria strains, Pseudomonas aeruginosa, and Serratia marcescens isolated from faecal sludge as pure cultures as well as mixed cultures. In this purpose, butanoic acid removal was performed in a batch reactor containing the bacterial strains in mineral salt medium (MSM) amended with 3000 ppm of butanoic acid at the temperature of 30°C, under continuous stirring rate of 150 rpm and the concentration of indole was varied from 50-200 ppm. The initial pH of the solution was in the range of 6.0-7.2. Overall, there were significant differences in the bacterial growth rate and total butanoic acid removal dependent on the concentration of indole in the solution.

Keywords: biodegradation, butanoic acid, indole, pit latrine

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6243 Genome Sequencing of the Yeast Saccharomyces cerevisiae Strain 202-3

Authors: Yina A. Cifuentes Triana, Andrés M. Pinzón Velásco, Marío E. Velásquez Lozano

Abstract:

In this work the sequencing and genome characterization of a natural isolate of Saccharomyces cerevisiae yeast (strain 202-3), identified with potential for the production of second generation ethanol from sugarcane bagasse hydrolysates is presented. This strain was selected because its capability to consume xylose during the fermentation of sugarcane bagasse hydrolysates, taking into account that many strains of S. cerevisiae are incapable of processing this sugar. This advantage and other prominent positive aspects during fermentation profiles evaluated in bagasse hydrolysates made the strain 202-3 a candidate strain to improve the production of second-generation ethanol, which was proposed as a first step to study the strain at the genomic level. The molecular characterization was carried out by genome sequencing with the Illumina HiSeq 2000 platform paired end; the assembly was performed with different programs, finally choosing the assembler ABYSS with kmer 89. Gene prediction was developed with the approach of hidden Markov models with Augustus. The genes identified were scored based on similarity with public databases of nucleotide and protein. Records were organized from ontological functions at different hierarchical levels, which identified central metabolic functions and roles of the S. cerevisiae strain 202-3, highlighting the presence of four possible new proteins, two of them probably associated with the positive consumption of xylose.

Keywords: cellulosic ethanol, Saccharomyces cerevisiae, genome sequencing, xylose consumption

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6242 Multicenter Evaluation of the ACCESS Anti-HCV Assay on the DxI 9000 ACCESS Immunoassay Analyzer, for the Detection of Hepatitis C Virus Antibody

Authors: Dan W. Rhodes, Juliane Hey, Magali Karagueuzian, Florianne Martinez, Yael Sandowski, Vanessa Roulet, Mahmoud Badawi, Mohammed-Amine Chakir, Valérie Simon, Jérémie Gautier, Françoise Le Boulaire, Catherine Coignard, Claire Vincent, Sandrine Greaume, Isabelle Voisin

Abstract:

Background: Beckman Coulter, Inc. (BEC) has recently developed a fully automated second-generation anti-HCV test on a new immunoassay platform. The objective of this multicenter study conducted in Europe was to evaluate the performance of the ACCESS anti-HCV assay on the recently CE-marked DxI 9000 ACCESS Immunoassay Analyzer as an aid in the diagnosis of HCV (Hepatitis C Virus) infection and as a screening test for blood and plasma donors. Methods: The clinical specificity of the ACCESS anti-HCV assay was determined using HCV antibody-negative samples from blood donors and hospitalized patients. Sample antibody status was determined by a CE-marked anti-HCV assay (Abbott ARCHITECTTM anti-HCV assay or Abbott PRISM HCV assay) with an additional confirmation method (Immunoblot testing with INNO-LIATM HCV Score - Fujirebio), if necessary, according to pre-determined testing algorithms. The clinical sensitivity was determined using known HCV antibody-positive samples, identified positive by Immunoblot testing with INNO-LIATM HCV Score - Fujirebio. HCV RNA PCR or genotyping was available on all Immunoblot positive samples for further characterization. The false initial reactive rate was determined on fresh samples from blood donors and hospitalized patients. Thirty (30) commercially available seroconversion panels were tested to assess the sensitivity for early detection of HCV infection. The study was conducted from November 2019 to March 2022. Three (3) external sites and one (1) internal site participated. Results: Clinical specificity (95% CI) was 99.7% (99.6 – 99.8%) on 5852 blood donors and 99.0% (98.4 – 99.4%) on 1527 hospitalized patient samples. There were 15 discrepant samples (positive on ACCESS anti-HCV assay and negative on both ARCHITECT and Immunoblot) observed with hospitalized patient samples, and of note, additional HCV RNA PCR results showed five (5) samples had positive HCV RNA PCR results despite the absence of HCV antibody detection by ARCHITECT and Immunoblot, suggesting a better sensitivity of the ACCESS anti-HCV assay with these five samples compared to the ARCHITECT and Immunoblot anti-HCV assays. Clinical sensitivity (95% CI) on 510 well-characterized, known HCV antibody-positive samples was 100.0% (99.3 – 100.0%), including 353 samples with known HCV genotypes (1 to 6). The overall false initial reactive rate (95% CI) on 6630 patient samples was 0.02% (0.00 – 0.09%). Results obtained on 30 seroconversion panels demonstrated that the ACCESS anti-HCV assay had equivalent sensitivity performances, with an average bleed difference since the first reactive bleed below one (1), compared to the ARCHITECTTM anti-HCV assay. Conclusion: The newly developed ACCESS anti-HCV assay from BEC for use on the DxI 9000 ACCESS Immunoassay Analyzer demonstrated high clinical sensitivity and specificity, equivalent to currently marketed anti-HCV assays, as well as a low false initial reactive rate.

Keywords: DxI 9000 ACCESS Immunoassay Analyzer, HCV, HCV antibody, Hepatitis C virus, immunoassay

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6241 Fuzzy Time Series Forecasting Based on Fuzzy Logical Relationships, PSO Technique, and Automatic Clustering Algorithm

Authors: A. K. M. Kamrul Islam, Abdelhamid Bouchachia, Suang Cang, Hongnian Yu

Abstract:

Forecasting model has a great impact in terms of prediction and continues to do so into the future. Although many forecasting models have been studied in recent years, most researchers focus on different forecasting methods based on fuzzy time series to solve forecasting problems. The forecasted models accuracy fully depends on the two terms that are the length of the interval in the universe of discourse and the content of the forecast rules. Moreover, a hybrid forecasting method can be an effective and efficient way to improve forecasts rather than an individual forecasting model. There are different hybrids forecasting models which combined fuzzy time series with evolutionary algorithms, but the performances are not quite satisfactory. In this paper, we proposed a hybrid forecasting model which deals with the first order as well as high order fuzzy time series and particle swarm optimization to improve the forecasted accuracy. The proposed method used the historical enrollments of the University of Alabama as dataset in the forecasting process. Firstly, we considered an automatic clustering algorithm to calculate the appropriate interval for the historical enrollments. Then particle swarm optimization and fuzzy time series are combined that shows better forecasting accuracy than other existing forecasting models.

Keywords: fuzzy time series (fts), particle swarm optimization, clustering algorithm, hybrid forecasting model

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6240 Insulin Resistance in Children and Adolescents in Relation to Body Mass Index, Waist Circumference and Body Fat Weight

Authors: E. Vlachopapadopoulou, E. Dikaiakou, E. Anagnostou, I. Panagiotopoulos, E. Kaloumenou, M. Kafetzi, A. Fotinou, S. Michalacos

Abstract:

Aim: To investigate the relation and impact of Body Mass Index (BMI), Waist Circumference (WC) and Body Fat Weight (BFW) on insulin resistance (MATSUDA INDEX < 2.5) in children and adolescents. Methods: Data from 95 overweight and obese children (47 boys and 48 girls) with mean age 10.7 ± 2.2 years were analyzed. ROC analysis was used to investigate the predictive ability of BMI, WC and BFW for insulin resistance and find the optimal cut-offs. The overall performance of the ROC analysis was quantified by computing area under the curve (AUC). Results: ROC curve analysis indicated that the optimal-cut off of WC for the prediction of insulin resistance was 97 cm with sensitivity equal to 75% and specificity equal to 73.1%. AUC was 0.78 (95% CI: 0.63-0.92, p=0.001). The sensitivity and specificity of obesity for the discrimination of participants with insulin resistance from those without insulin resistance were equal to 58.3% and 75%, respectively (AUC=0.67). BFW had a borderline predictive ability for insulin resistance (AUC=0.58, 95% CI: 0.43-0.74, p=0.101). The predictive ability of WC was equivalent with the correspondence predictive ability of BMI (p=0.891). Obese subjects had 4.2 times greater odds for having insulin resistance (95% CI: 1.71-10.30, p < 0.001), while subjects with WC more than 97 had 8.1 times greater odds for having insulin resistance (95% CI: 2.14-30.86, p=0.002). Conclusion: BMI and WC are important clinical factors that have significant clinical relation with insulin resistance in children and adolescents. The cut off of 97 cm for WC can identify children with greater likelihood for insulin resistance.

Keywords: body fat weight, body mass index, insulin resistance, obese children, waist circumference

Procedia PDF Downloads 322
6239 Simulation Approach for Analyzing Transportation Energy System in South Korea

Authors: Sungjun Hong, Youah Lee, Jongwook Kim

Abstract:

In the last COP21 held in Paris on 2015, Korean government announced that Intended Nationally Determined Contributions (INDC) was 37% based on BAU by 2030. The GHG reduction rate of the transportation sector is the strongest among all sectors by 2020. In order to cope with Korean INDC, Korean government established that 3rd eco-friendly car deployment national plans at the end of 2015. In this study, we make the energy system model for estimating GHG emissions using LEAP model.

Keywords: INDC, greenhouse gas, LEAP, transportation

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6238 Enhancing Aerodynamic Performance of Savonius Vertical Axis Turbine Used with Triboelectric Generator

Authors: Bhavesh Dadhich, Fenil Bamnoliya, Akshita Swaminathan

Abstract:

This project aims to design a system to generate energy from flowing wind due to the motion of a vehicle on the road or from the flow of wind in compact areas to utilize the wasteful energy into a useful one. It is envisaged through a design and aerodynamic performance improvement of a Savonius vertical axis wind turbine rotor and used in an integrated system with a Triboelectric Nanogenerator (TENG) that can generate a good amount of electrical energy. Aerodynamic calculations are performed numerically using Computational Fluid Dynamics software, and TENG's performance is evaluated analytically. The Turbine's coefficient of power is validated with published results for an inlet velocity of 7 m/s with a Tip Speed Ratio of 0.75 and found to reasonably agree with that of experiment results. The baseline design is modified with a new blade arc angle and rotor position angle based on the recommended parameter ranges suggested by previous researchers. Simulations have been performed for different T.S.R. values ranging from 0.25 to 1.5 with an interval of 0.25 with two applicable free stream velocities of 5 m/s and 7m/s. Finally, the newly designed VAWT CFD performance results are used as input for the analytical performance prediction of the triboelectric nanogenerator. The results show that this approach could be feasible and useful for small power source applications.

Keywords: savonius turbine, power, overlap ratio, tip speed ratio, TENG

Procedia PDF Downloads 125
6237 20th-Century River Course Changes and Their Relation to Sediment Carbon Distribution Patterns in the Yellow River Delta

Authors: Dongxue Li, Zhonghua Ning, Yi’na Li, Baoshan Cui, Wasner Daniel, Sebastian Dötterl

Abstract:

Most of the world's coastal alluvial plains can be significant carbon (C) eservoirs in which upland sediments are deposited and bury former topsoil, thereby contributing to soil C preservation, especially in river-controlled deltas like the Yellow River Delta, China. These deltas are affected by the continuous large amount of sediment transport and strong river dynamics from the upper reaches, which makes the river course in the deltas change frequently. However, the impact of varying river course changes on C stocks in these estuary wetlands is unclear. To investigate this, we drilled five 2 m cores along a sediment deposition sequence of the Yellow River Delta, which shifted its main course flow in the delta several times throughout the 20th century. Covering 80 years of sediment deposition, we explored both soil C stocks and their potential sources, and identified key soil physicochemical and hydrometeorological variables that correlate to C density and deposition rate. Further, the spatiotemporal C distribution and its relationship with these variables was examined. Our results showed that sediments at a soil depth of 200 cm in the main courses of the Yellow River corresponded to deposition ages ranging from 1942 to 1989. The oldest course has the lowest C stocks and showed C-enriched compared with younger courses. Contributions of soil C stemming from fresh particulate organic carbon from deposited upstream sources were significantly higher than local, in-situ vegetation. In addition, the carbon of the oldest and relatively young courses tends to be affected by interaction effects of hydrometeorological and physiochemical varibales, and that of the middle courses tends to be affected by independent variables. Our findings can help prioritize conservation efforts across different river courses and provide quantitative support for global carbon emission reduction by assessing sediment carbon reservoirs.

Keywords: alluvial plains, coastal wetland, core drilling, course diversion, organic carbon, sediment deposition rate, soil deposition

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6236 Distribution of HLA-DQA1 and HLA-DQB1 Alleles in Thais: Genetics Database Insight for COVID-19 Severity

Authors: Jinu Phonamontham

Abstract:

Coronavirus, also referred to as COVID-19, is a virus caused by the SARS-Cov-2 virus. The pandemic has caused over 10 million cases and 500,000 deaths worldwide through the end of June 2020. In a previous study, HLA-DQA1*01:02 allele was associated with COVID-19 disease (p-value = 0.0121). Furthermore, there was a statistical significance between HLA- DQB1*06:02 and COVID-19 in the Italian population by Bonferroni’s correction (p-value = 0.0016). Nevertheless, there is no data describing the distribution of HLA alleles as a valid marker for prediction of COVID-19 in the Thai population. We want to investigate the prevalence of HLA-DQA1*01:02 and HLA-DQB1*06:02 alleles that are associated with severe COVID-19 in the Thai population. In this study, we recruited 200 healthy Thai individuals. Genomic DNA samples were isolated from EDTA blood using Genomic DNA Mini Kit. HLA genotyping was conducted using the Lifecodes HLA SSO typing kits (Immucor, West Avenue, Stamford, USA). The frequency of HLA-DQA1 alleles in Thai population, consisting of HLA-DQA1*01:01 (27.75%), HLA-DQA1*01:02 (24.50%), HLA-DQA1*03:03 (13.00%), HLA-DQA1*06:01 (10.25%) and HLA-DQA1*02:01 (6.75%). Furthermore, the distributions of HLA-DQB1 alleles were HLA-DQB1*05:02 (21.50%), HLA-DQB1*03:01 (15.75%), HLA-DQB1*05:01 (14.50%), HLA-DQB1*03:03 (11.00%) and HLA-DQB1*02:02 (8.25%). Particularly, HLA- DQA1*01:02 (29.00%) allele was the highest frequency in the NorthEast group, but there was not significant difference when compared with the other regions in Thais (p-value = 0.4202). HLA-DQB1*06:02 allele was similarly distributed in Thai population and there was no significant difference between Thais and China (3.8%) and South Korea (6.4%) and Japan (8.2%) with p-value > 0.05. Whereas, South Africa (15.7%) has a significance with Thais by p-value of 0.0013. This study supports the specific genotyping of the HLA-DQA1*01:02 and HLA-DQB1*06:02 alleles to screen severe COVID-19 in Thai and many populations.

Keywords: HLA-DQA1*01:02, HLA-DQB1*06:02, Asian, Thai population

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6235 Corrosion of Fe-(9~37) Wt%Cr Alloys at 700-800 °C in N₂-H₂O-H₂S Mixed Gas

Authors: Min Jung Kim

Abstract:

Fe-(9, 19, 28, 37) wt%Cr alloys were corroded at 700 and 800 °C for 70 h under 1 atm of N₂, 1 atm of N₂/3.2%H₂O-mixed gas, and 1 atm of N₂/3.1%H₂O/2.42%H₂S-mixed gas. The corrosion rate of Fe-9Cr alloy increased with the addition of H₂O and increased further with the addition of H₂S in N₂/H₂O gas. Fe-9Cr alloy was non-protective in all gas types. In contrast, Fe-(19, 28, 37) wt%Cr alloys were protective in N₂ and N₂/H₂O-mixed gas because of the formation of the Cr₂O₃ layer. They were, however, non-protective in N₂/H₂O/H₂S-mixed gas because sulfidation dominated, forming the outer FeS layer and the inner Cr₂S₃ layer containing some FeCr₂S₄.

Keywords: Fe-(9, 19, 28, 37) wt%Cr alloys, corrosion, sulfidation, FeS

Procedia PDF Downloads 434