Search results for: time domain analysis
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 40048

Search results for: time domain analysis

33898 An Optimal Control Model for the Dynamics of Visceral Leishmaniasis

Authors: Ibrahim M. Elmojtaba, Rayan M. Altayeb

Abstract:

Visceral leishmaniasis (VL) is a vector-borne disease caused by the protozoa parasite of the genus leishmania. The transmission of the parasite to humans and animals occurs via the bite of adult female sandflies previously infected by biting and sucking blood of an infectious humans or animals. In this paper we use a previously proposed model, and then applied two optimal controls, namely treatment and vaccination to that model to investigate optimal strategies for controlling the spread of the disease using treatment and vaccination as the system control variables. The possible impact of using combinations of the two controls, either one at a time or two at a time on the spread of the disease is also examined. Our results provide a framework for vaccination and treatment strategies to reduce susceptible and infection individuals of VL in five years.

Keywords: visceral leishmaniasis, treatment, vaccination, optimal control, numerical simulation

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33897 Artificial Intelligence-Based Thermal Management of Battery System for Electric Vehicles

Authors: Raghunandan Gurumurthy, Aricson Pereira, Sandeep Patil

Abstract:

The escalating adoption of electric vehicles (EVs) across the globe has underscored the critical importance of advancing battery system technologies. This has catalyzed a shift towards the design and development of battery systems that not only exhibit higher energy efficiency but also boast enhanced thermal performance and sophisticated multi-material enclosures. A significant leap in this domain has been the incorporation of simulation-based design optimization for battery packs and Battery Management Systems (BMS), a move further enriched by integrating artificial intelligence/machine learning (AI/ML) approaches. These strategies are pivotal in refining the design, manufacturing, and operational processes for electric vehicles and energy storage systems. By leveraging AI/ML, stakeholders can now predict battery performance metrics—such as State of Health, State of Charge, and State of Power—with unprecedented accuracy. Furthermore, as Li-ion batteries (LIBs) become more prevalent in urban settings, the imperative for bolstering thermal and fire resilience has intensified. This has propelled Battery Thermal Management Systems (BTMs) to the forefront of energy storage research, highlighting the role of machine learning and AI not just as tools for enhanced safety management through accurate temperature forecasts and diagnostics but also as indispensable allies in the early detection and warning of potential battery fires.

Keywords: electric vehicles, battery thermal management, industrial engineering, machine learning, artificial intelligence, manufacturing

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33896 U.S. Trade and Trade Balance with China: Testing for Marshall-Lerner Condition and the J-Curve Hypothesis

Authors: Anisul Islam

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The U.S. has a very strong trade relationship with China but with a large and persistent trade deficit. Some has argued that the undervalued Chinese Yuan is to be blamed for the persistent trade deficit. The empirical results are mixed at best. This paper empirically estimates the U.S. export function along with the U.S. import function with its trade with China with the purpose of testing for the existence of the Marshall-Lerner (ML) condition as well for the possible existence of the J-curve hypothesis. Annual export and import data will be utilized for as long as the time series data exists. The export and import functions will be estimated using advanced econometric techniques, along with appropriate diagnostic tests performed to examine the validity and reliability of the estimated results. The annual time-series data covers from 1975 to 2022 with a sample size of 48 years, the longest period ever utilized before in any previous study. The data is collected from several sources, such as the World Bank’s World Development Indicators, IMF Financial Statistics, IMF Direction of Trade Statistics, and several other sources. The paper is expected to shed important light on the ongoing debate regarding the persistent U.S. trade deficit with China and the policies that may be useful to reduce such deficits over time. As such, the paper will be of great interest for the academics, researchers, think tanks, global organizations, and policy makers in both China and the U.S.

Keywords: exports, imports, marshall-lerner condition, j-curve hypothesis, united states, china

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33895 A Uniformly Convergent Numerical Scheme for a Singularly Perturbed Volterra Integrodifferential Equation

Authors: Nana Adjoah Mbroh, Suares Clovis Oukouomi Noutchie

Abstract:

Singularly perturbed problems are parameter dependent problems, and they play major roles in the modelling of real-life situational problems in applied sciences. Thus, designing efficient numerical schemes to solve these problems is of much interest since the exact solutions of such problems may not even exist. Generally, singularly perturbed problems are identified by a small parameter multiplying at least the highest derivative in the equation. The presence of this parameter causes the solution of these problems to be characterized by rapid oscillations. This unique feature renders classical numerical schemes inefficient since they are unable to capture the behaviour of the exact solution in the part of the domain where the rapid oscillations are present. In this paper, a numerical scheme is proposed to solve a singularly perturbed Volterra Integro-differential equation. The scheme is based on the midpoint rule and employs the non-standard finite difference scheme to solve the differential part whilst the composite trapezoidal rule is used for the integral part. A fully fledged error estimate is performed, and Richardson extrapolation is applied to accelerate the convergence of the scheme. Numerical simulations are conducted to confirm the theoretical findings before and after extrapolation.

Keywords: midpoint rule, non-standard finite difference schemes, Richardson extrapolation, singularly perturbed problems, trapezoidal rule, uniform convergence

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33894 Quantifying Freeway Capacity Reductions by Rainfall Intensities Based on Stochastic Nature of Flow Breakdown

Authors: Hoyoung Lee, Dong-Kyu Kim, Seung-Young Kho, R. Eddie Wilson

Abstract:

This study quantifies a decrement in freeway capacity during rainfall. Traffic and rainfall data were gathered from Highway Agencies and Wunderground weather service. Three inter-urban freeway sections and its nearest weather stations were selected as experimental sites. Capacity analysis found reductions of maximum and mean pre-breakdown flow rates due to rainfall. The Kruskal-Wallis test also provided some evidence to suggest that the variance in the pre-breakdown flow rate is statistically insignificant. Potential application of this study lies in the operation of real time traffic management schemes such as Variable Speed Limits (VSL), Hard Shoulder Running (HSR), and Ramp Metering System (RMS), where speed or flow limits could be set based on a number of factors, including rainfall events and their intensities.

Keywords: capacity randomness, flow breakdown, freeway capacity, rainfall

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33893 Understanding the Semantic Network of Tourism Studies in Taiwan by Using Bibliometrics Analysis

Authors: Chun-Min Lin, Yuh-Jen Wu, Ching-Ting Chung

Abstract:

The formulation of tourism policies requires objective academic research and evidence as support, especially research from local academia. Taiwan is a small island, and its economic growth relies heavily on tourism revenue. Taiwanese government has been devoting to the promotion of the tourism industry over the past few decades. Scientific research outcomes by Taiwanese scholars may and will help lay the foundations for drafting future tourism policy by the government. In this study, a total of 120 full journal articles published between 2008 and 2016 from the Journal of Tourism and Leisure Studies (JTSL) were examined to explore the scientific research trend of tourism study in Taiwan. JTSL is one of the most important Taiwanese journals in the tourism discipline which focuses on tourism-related issues and uses traditional Chinese as the study language. The method of co-word analysis from bibliometrics approaches was employed for semantic analysis in this study. When analyzing Chinese words and phrases, word segmentation analysis is a crucial step. It must be carried out initially and precisely in order to obtain meaningful word or word chunks for further frequency calculation. A word segmentation system basing on N-gram algorithm was developed in this study to conduct semantic analysis, and 100 groups of meaningful phrases with the highest recurrent rates were located. Subsequently, co-word analysis was employed for semantic classification. The results showed that the themes of tourism research in Taiwan in recent years cover the scope of tourism education, environmental protection, hotel management, information technology, and senior tourism. The results can give insight on the related issues and serve as a reference for tourism-related policy making and follow-up research.

Keywords: bibliometrics, co-word analysis, word segmentation, tourism research, policy

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33892 NOx Emission and Computational Analysis of Jatropha Curcus Fuel and Crude Oil

Authors: Vipan Kumar Sohpal, Rajesh K Sharma

Abstract:

Diminishing of conventional fuels and hysterical vehicles emission leads to deterioration of the environment, which emphasize the research to work on biofuels. Biofuels from different sources attract the attention of research due to low emission and biodegradability. Emission of carbon monoxide, carbon dioxide and H-C reduced drastically using Biofuels (B-20) combustion. Contrary to the conventional fuel, engine emission results indicated that nitrous oxide emission is higher in Biofuels. So this paper examines and compares the nitrogen oxide emission of Jatropha Curcus (JCO) B-20% blends with the vegetable oil. In addition to that computational analysis of crude non edible oil performed to assess the impact of composition on emission quality. In conclusion, JCO have the potential feedstock for the biodiesel production after the genetic modification in the plant.

Keywords: jatropha curcus, computational analysis, emissions, NOx biofuels

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33891 An Optimized Method for Calculating the Linear and Nonlinear Response of SDOF System Subjected to an Arbitrary Base Excitation

Authors: Hossein Kabir, Mojtaba Sadeghi

Abstract:

Finding the linear and nonlinear responses of a typical single-degree-of-freedom system (SDOF) is always being regarded as a time-consuming process. This study attempts to provide modifications in the renowned Newmark method in order to make it more time efficient than it used to be and make it more accurate by modifying the system in its own non-linear state. The efficacy of the presented method is demonstrated by assigning three base excitations such as Tabas 1978, El Centro 1940, and MEXICO CITY/SCT 1985 earthquakes to a SDOF system, that is, SDOF, to compute the strength reduction factor, yield pseudo acceleration, and ductility factor.

Keywords: single-degree-of-freedom system (SDOF), linear acceleration method, nonlinear excited system, equivalent displacement method, equivalent energy method

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33890 The Influence of Partial Replacement of Hydrated Lime by Pozzolans on Properties of Lime Mortars

Authors: Przemyslaw Brzyski, Stanislaw Fic

Abstract:

Hydrated lime, because of the life cycle (return to its natural form as a result of the setting and hardening) has a positive environmental impact. The lime binder is used in mortars. Lime is a slow setting binder with low mechanical properties. The aim of the study was to evaluate the possibility of improving the properties of the lime binder by using different pozzolanic materials as partial replacement of hydrated lime binder. Pozzolan materials are the natural or industrial waste, so do not affect the environmental impact of the lime binder. The following laboratory tests were performed: the analysis of the physical characteristics of the tested samples of lime mortars (bulk density, porosity), flexural and compressive strength, water absorption and the capillary rise of samples and consistency of fresh mortars. As a partial replacement of hydrated lime (in the amount of 10%, 20%, 30% by weight of lime) a metakaolin, silica fume, and zeolite were used. The shortest setting and hardening time showed mortars with the addition of metakaolin. All additives noticeably improved strength characteristic of lime mortars. With the increase in the amount of additive, the increase in strength was also observed. The highest flexural strength was obtained by using the addition of metakaolin in an amount of 20% by weight of lime (2.08 MPa). The highest compressive strength was obtained by using also the addition of metakaolin but in an amount of 30% by weight of lime (9.43 MPa). The addition of pozzolan caused an increase in the mortar tightness which contributed to the limitation of absorbability. Due to the different surface area, pozzolanic additives affected the consistency of fresh mortars. Initial consistency was assumed as plastic. Only the addition of silica fume an amount of 20 and 30% by weight of lime changed the consistency to the thick-plastic. The conducted study demonstrated the possibility of applying lime mortar with satisfactory properties. The features of lime mortars do not differ significantly from cement-based mortar properties and show a lower environmental impact due to CO₂ absorption during lime hardening. Taking into consideration the setting time, strength and consistency, the best results can be obtained with metakaolin addition to the lime mortar.

Keywords: lime, binder, mortar, pozzolan, properties

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33889 Understanding Mathematics Achievements among U. S. Middle School Students: A Bayesian Multilevel Modeling Analysis with Informative Priors

Authors: Jing Yuan, Hongwei Yang

Abstract:

This paper aims to understand U.S. middle school students’ mathematics achievements by examining relevant student and school-level predictors. Through a variance component analysis, the study first identifies evidence supporting the use of multilevel modeling. Then, a multilevel analysis is performed under Bayesian statistical inference where prior information is incorporated into the modeling process. During the analysis, independent variables are entered sequentially in the order of theoretical importance to create a hierarchy of models. By evaluating each model using Bayesian fit indices, a best-fit and most parsimonious model is selected where Bayesian statistical inference is performed for the purpose of result interpretation and discussion. The primary dataset for Bayesian modeling is derived from the Program for International Student Assessment (PISA) in 2012 with a secondary PISA dataset from 2003 analyzed under the traditional ordinary least squares method to provide the information needed to specify informative priors for a subset of the model parameters. The dependent variable is a composite measure of mathematics literacy, calculated from an exploratory factor analysis of all five PISA 2012 mathematics achievement plausible values for which multiple evidences are found supporting data unidimensionality. The independent variables include demographics variables and content-specific variables: mathematics efficacy, teacher-student ratio, proportion of girls in the school, etc. Finally, the entire analysis is performed using the MCMCpack and MCMCglmm packages in R.

Keywords: Bayesian multilevel modeling, mathematics education, PISA, multilevel

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33888 Intelligent Rescheduling Trains for Air Pollution Management

Authors: Kainat Affrin, P. Reshma, G. Narendra Kumar

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Optimization of timetable is the need of the day for the rescheduling and routing of trains in real time. Trains are scheduled in parallel with the road transport vehicles to the same destination. As the number of trains is restricted due to single track, customers usually opt for road transport to use frequently. The air pollution increases as the density of vehicles on road transport is increased. Use of an alternate mode of transport like train helps in reducing air-pollution. This paper mainly aims at attracting the passengers to Train transport by proper rescheduling of trains using hybrid of stop-skip algorithm and iterative convex programming algorithm. Rescheduling of train bi-directionally is achieved on a single track with dynamic dual time and varying stops. Introduction of more trains attract customers to use rail transport frequently, thereby decreasing the pollution. The results are simulated using Network Simulator (NS-2).

Keywords: air pollution, AODV, re-scheduling, WSNs

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33887 Integrating Cyber-Physical System toward Advance Intelligent Industry: Features, Requirements and Challenges

Authors: V. Reyes, P. Ferreira

Abstract:

In response to high levels of competitiveness, industrial systems have evolved to improve productivity. As a consequence, a rapid increase in volume production and simultaneously, a customization process require lower costs, more variety, and accurate quality of products. Reducing time-cycle production, enabling customizability, and ensure continuous quality improvement are key features in advance intelligent industry. In this scenario, customers and producers will be able to participate in the ongoing production life cycle through real-time interaction. To achieve this vision, transparency, predictability, and adaptability are key features that provide the industrial systems the capability to adapt to customer demands modifying the manufacturing process through an autonomous response and acting preventively to avoid errors. The industrial system incorporates a diversified number of components that in advanced industry are expected to be decentralized, end to end communicating, and with the capability to make own decisions through feedback. The evolving process towards advanced intelligent industry defines a set of stages to empower components of intelligence and enhancing efficiency to achieve the decision-making stage. The integrated system follows an industrial cyber-physical system (CPS) architecture whose real-time integration, based on a set of enabler technologies, links the physical and virtual world generating the digital twin (DT). This instance allows incorporating sensor data from real to virtual world and the required transparency for real-time monitoring and control, contributing to address important features of the advanced intelligent industry and simultaneously improve sustainability. Assuming the industrial CPS as the core technology toward the latest advanced intelligent industry stage, this paper reviews and highlights the correlation and contributions of the enabler technologies for the operationalization of each stage in the path toward advanced intelligent industry. From this research, a real-time integration architecture for a cyber-physical system with applications to collaborative robotics is proposed. The required functionalities and issues to endow the industrial system of adaptability are identified.

Keywords: cyber-physical systems, digital twin, sensor data, system integration, virtual model

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33886 Real-Time Hybrid Simulation for a Tuned Liquid Column Damper Implementation

Authors: Carlos Riascos, Peter Thomson

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Real-time hybrid simulation (RTHS) is a modern cyber-physical technique used for the experimental evaluation of complex systems, that treats the system components with predictable behavior as a numerical substructure and the components that are difficult to model as an experimental substructure. Therefore it is an attractive method for evaluation of the response of civil structures under earthquake, wind and anthropic loads. Another practical application of RTHS is the evaluation of control systems, as these devices are often nonlinear and their characterization is an important step in the design of controllers with the desired performance. In this paper, the response of three-story shear frame controlled by a tuned liquid column damper (TLCD) and subject to base excitation is considered. Both passive and semi-active control strategies were implemented and are compared. While the passive TLCD achieved a reduction of 50% in the acceleration response of the main structure in comparison with the structure without control, the semi-active TLCD achieved a reduction of 70%, and was robust to variations in the dynamic properties of the main structure. In addition, a RTHS was implemented with the main structure modeled as a linear, time-invariant (LTI) system through a state space representation and the TLCD, with both control strategies, was evaluated on a shake table that reproduced the displacement of the virtual structure. Current assessment measures for RTHS were used to quantify the performance with parameters such as generalized amplitude, equivalent time delay between the target and measured displacement of the shake table, and energy error using the measured force, and prove that the RTHS described in this paper is an accurate method for the experimental evaluation of structural control systems.

Keywords: structural control, hybrid simulation, tuned liquid column damper, semi-active sontrol strategy

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33885 Investigating the Relationship between Job Satisfaction, Role Identity, and Turnover Intention for Nurses in Outpatient Department

Authors: Su Hui Tsai, Weir Sen Lin, Rhay Hung Weng

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There are numerous outpatient departments at hospitals with enormous amounts of outpatients. Although the work of outpatient nursing staff does not include the ward, emergency and critical care units that involve patient life-threatening conditions, the work is cumbersome and requires facing and dealing with a large number of outpatients in a short period of time. Therefore, nursing staff often do not feel satisfied with their work and cannot identify with their professional role, leading to intentions to leave their job. Thus, the main purpose of this study is to explore the correlation between the job satisfaction and role identity of nursing staff with turnover intention. This research was conducted using a questionnaire, and the subjects were outpatient nursing staff in three regional hospitals in Southern Taiwan. A total of 175 questionnaires were distributed, and 166 valid questionnaires were returned. After collecting the data, the reliability and validity of the study variables were confirmed by confirmatory factor analysis. The influence of role identity and job satisfaction on nursing staff’s turnover intention was analyzed by descriptive analysis, one-way ANOVA, Pearson correlation analysis and multiple regression analysis. Results showed that 'role identity' had significant differences in different types of marriages. Job satisfaction of 'grasp of environment' had significant differences in different levels of education. Job satisfaction of 'professional growth' and 'shifts and days off' showed significant differences in different types of marriages. 'Role identity' and 'job satisfaction' were negatively correlated with turnover intention respectively. Job satisfaction of 'salary and benefits' and 'grasp of environment' were significant predictors of role identity. The higher the job satisfaction of 'salary and benefits' and 'grasp of environment', the higher the role identity. Job satisfaction of 'patient and family interaction' were significant predictors of turnover intention. The lower the job satisfaction of 'patient and family interaction', the higher the turnover intention. This study found that outpatient nursing staff had the lowest satisfaction towards salary structure. It is recommended that bonuses, promotion opportunities and other incentives be established to increase the role identity of outpatient nursing staff. The results showed that the higher the job satisfaction of 'salary and benefits' and 'grasp of environment', the higher the role identity. It is recommended that regular evaluations be conducted to reward nursing staff with excellent service and invite nursing staff to share their work experiences and thoughts, to enhance nursing staff’s expectation and identification of their occupational role, as well as instilling the concept of organizational service and organizational expectations of emotional display. The results showed that the lower the job satisfaction of 'patient and family interaction', the higher the turnover intention. It is recommended that interpersonal communication and workplace violence prevention educational training courses be organized to enhance the communication and interaction of nursing staff with patients and their families.

Keywords: outpatient, job satisfaction, turnover, intention

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33884 Temporal Variation of Surface Runoff and Interrill Erosion in Different Soil Textures of a Semi-arid Region, Iran

Authors: Ali Reza Vaezi, Naser Fakori Ivand, Fereshteh Azarifam

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Interrill erosion is the detachment and transfer of soil particles between the rills due to the impact of raindrops and the shear stress of shallow surface runoff. This erosion can be affected by some soil properties such as texture, amount of organic matter and stability of soil aggregates. Information on the temporal variation of interrill erosion during a rainfall event and the effect soil properties have on it can help in understanding the process of runoff production and soil loss between the rills in hillslopes. The importance of this study is especially grate in semi-arid regions, where the soil is weakly aggregated and vegetation cover is mostly poor. Therefore, this research was conducted to investigate the temporal variation of surface flow and interrill erosion and the effect of soil properties on it in some semi-arid soils. A field experiment was done in eight different soil textures under simulated rainfalls with uniform intensity. A total of twenty four plots were installed for eight study soils with three replicates in the form of a random complete block design along the land. The plots were 1.2 m (length) × 1 m (width) in dimensions which designed with a distance of 3 m from each other across the slope. Then, soil samples were purred into the plots. The plots were surrounded by a galvanized sheet, and runoff and soil erosion equipment were placed at their outlets. Rainfall simulation experiments were done using a designed portable simulator with an intensity of 60 mm per hour for 60 minutes. A plastic cover was used around the rainfall simulator frame to prevent the impact of the wind on the free fall of water drops. Runoff production and soil loss were measured during 1 hour time with 5-min intervals. In order to study soil properties, such as particle size distribution, aggregate stability, bulk density, ESP and Ks were determined in the laboratory. Correlation and regression analysis was done to determine the effect of soil properties on runoff and interrill erosion. Results indicated that the study soils have lower booth organic matter content and aggregate stability. The soils, except for coarse textured textures, are calcareous and with relatively higher exchangeable sodium percentages (ESP). Runoff production and soil loss didn’t occur in sand, which was associated with higher infiltration and drainage rates. In other study soils, interrill erosion occurred simultaneously with the generation of runoff. A strong relationship was found between interrill erosion and surface runoff (R2 = 0.75, p< 0.01). The correlation analysis showed that surface runoff was significantly affected by some soil properties consisting of sand, silt, clay, bulk density, gravel, hydraulic conductivity (Ks), lime (calcium carbonate), and ESP. The soils with lower Ks such as fine-textured soils, produced higher surface runoff and more interrill erosion. In the soils, Surface runoff production temporally increased during rainfall and finally reached a peak after about 25-35 min. Time to peak was very short (30 min) in fine-textured soils, especially clay, which was related to their lower infiltration rate.

Keywords: erosion plot, rainfall simulator, soil properties, surface flow

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33883 The Usefulness of Premature Chromosome Condensation Scoring Module in Cell Response to Ionizing Radiation

Authors: K. Rawojć, J. Miszczyk, A. Możdżeń, A. Panek, J. Swakoń, M. Rydygier

Abstract:

Due to the mitotic delay, poor mitotic index and disappearance of lymphocytes from peripheral blood circulation, assessing the DNA damage after high dose exposure is less effective. Conventional chromosome aberration analysis or cytokinesis-blocked micronucleus assay do not provide an accurate dose estimation or radiosensitivity prediction in doses higher than 6.0 Gy. For this reason, there is a need to establish reliable methods allowing analysis of biological effects after exposure in high dose range i.e., during particle radiotherapy. Lately, Premature Chromosome Condensation (PCC) has become an important method in high dose biodosimetry and a promising treatment modality to cancer patients. The aim of the study was to evaluate the usefulness of drug-induced PCC scoring procedure in an experimental mode, where 100 G2/M cells were analyzed in different dose ranges. To test the consistency of obtained results, scoring was performed by 3 independent persons in the same mode and following identical scoring criteria. Whole-body exposure was simulated in an in vitro experiment by irradiating whole blood collected from healthy donors with 60 MeV protons and 250 keV X-rays, in the range of 4.0 – 20.0 Gy. Drug-induced PCC assay was performed on human peripheral blood lymphocytes (HPBL) isolated after in vitro exposure. Cells were cultured for 48 hours with PHA. Then to achieve premature condensation, calyculin A was added. After Giemsa staining, chromosome spreads were photographed and manually analyzed by scorers. The dose-effect curves were derived by counting the excess chromosome fragments. The results indicated adequate dose estimates for the whole-body exposure scenario in the high dose range for both studied types of radiation. Moreover, compared results revealed no significant differences between scores, which has an important meaning in reducing the analysis time. These investigations were conducted as a part of an extended examination of 60 MeV protons from AIC-144 isochronous cyclotron, at the Institute of Nuclear Physics in Kraków, Poland (IFJ PAN) by cytogenetic and molecular methods and were partially supported by grant DEC-2013/09/D/NZ7/00324 from the National Science Centre, Poland.

Keywords: cell response to radiation exposure, drug induced premature chromosome condensation, premature chromosome condensation procedure, proton therapy

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33882 Utilization Of Medical Plants Tetrastigma glabratum (Blume) Planch from Mount Prau in the Blumah, Central Java

Authors: A. Lianah, B. Peter Sopade, C. Krisantini

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Walikadep/Tetrastigma glabratum (Blume) Planch is a traditional herb that has been used by people of Blumah village; it is believed to have a stimulant effect and ailments for many illnesses. Our survey demonstrated that the people of Blumah village has exploited walikadep from Protected Forest of Mount Prau. More than 10% of 448 households at Blumah village have used walikadep as traditional herb or jamu. Part of the walikadep plants used is the liquid extract of the stem. The population of walikadep is getting scarce and it is rarely found now. The objectives of this study are to examine the stimulant effect of walikadep, to measure growth and exploitation rate of walikadep, and to find ways to effectively propagate the plants, as well as identifying the impact on the environment through field experiments and explorative survey. Stimulant effect was tested using open-field and hole-board test. Data were collected through field observation and experiment, and data were analysed using lab test and Anova. Rate of exploitation and plant growth was measured using Regression analysis; comparison of plant growth in-situ and ex-situ used descriptive analysis. The environmental impact was measured by population structure vegetation analysis method by Shannon Weinner. The study revealed that the walikadep exudates did not have a stimulant effect. Exploitation of walikadep and the long time required to reach harvestable size resulted in the scarcity of the plant in the natural habitat. Plant growth was faster in-situ than ex-situ; and fast growth was obtained from middle part cuttings treated with vermicompost. Biodiversity index after exploitation was higher than before exploitation, possibly due to the toxic and allellopathic effect (phenolics) of the plant. Based on these findings, further research is needed to examine the toxic effects of the leave and stem extract of walikadep and their allelopathic effects. We recommend that people of Blumah village to stop using walikadep as the stimulant. The local people, village government in the regional and central levels, and perhutani should do an integrated efforts to conserve walikadep through Pengamanan Terpadu Konservasi Walikadep Lestari (PTKWL) program, so this population of this plant in the natural habitat can be maintained.

Keywords: utilization, medical plants, traditional, Tetastigma glabratum

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33881 Time Estimation of Return to Sports Based on Classification of Health Levels of Anterior Cruciate Ligament Using a Convolutional Neural Network after Reconstruction Surgery

Authors: Zeinab Jafari A., Ali Sharifnezhad B., Mohammad Razi C., Mohammad Haghpanahi D., Arash Maghsoudi

Abstract:

Background and Objective: Sports-related rupture of the anterior cruciate ligament (ACL) and following injuries have been associated with various disorders, such as long-lasting changes in muscle activation patterns in athletes, which might last after ACL reconstruction (ACLR). The rupture of the ACL might result in abnormal patterns of movement execution, extending the treatment period and delaying athletes’ return to sports (RTS). As ACL injury is especially prevalent among athletes, the lengthy treatment process and athletes’ absence from sports are of great concern to athletes and coaches. Thus, estimating safe time of RTS is of crucial importance. Therefore, using a deep neural network (DNN) to classify the health levels of ACL in injured athletes, this study aimed to estimate the safe time for athletes to return to competitions. Methods: Ten athletes with ACLR and fourteen healthy controls participated in this study. Three health levels of ACL were defined: healthy, six-month post-ACLR surgery and nine-month post-ACLR surgery. Athletes with ACLR were tested six and nine months after the ACLR surgery. During the course of this study, surface electromyography (sEMG) signals were recorded from five knee muscles, namely Rectus Femoris (RF), Vastus Lateralis (VL), Vastus Medialis (VM), Biceps Femoris (BF), Semitendinosus (ST), during single-leg drop landing (SLDL) and forward hopping (SLFH) tasks. The Pseudo-Wigner-Ville distribution (PWVD) was used to produce three-dimensional (3-D) images of the energy distribution patterns of sEMG signals. Then, these 3-D images were converted to two-dimensional (2-D) images implementing the heat mapping technique, which were then fed to a deep convolutional neural network (DCNN). Results: In this study, we estimated the safe time of RTS by designing a DCNN classifier with an accuracy of 90 %, which could classify ACL into three health levels. Discussion: The findings of this study demonstrate the potential of the DCNN classification technique using sEMG signals in estimating RTS time, which will assist in evaluating the recovery process of ACLR in athletes.

Keywords: anterior cruciate ligament reconstruction, return to sports, surface electromyography, deep convolutional neural network

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33880 Bacterial Cellulose/Silver-Doped Hydroxyapatite Composites for Tissue Engineering Application

Authors: Adrian Ionut Nicoara, Denisa Ionela Ene, Alina Maria Holban, Cristina Busuioc

Abstract:

At present, the development of materials with biomedical applications is a domain of interest that will produce a full series of benefits in engineering and medicine. In this sense, it is required to use a natural material, and this paper is focused on the development of a composite material based on bacterial cellulose – hydroxyapatite and silver nanoparticles with applications in hard tissue. Bacterial cellulose own features like biocompatibility, non-toxicity character and flexibility. Moreover, the bacterial cellulose can be conjugated with different forms of active silver to possess antimicrobial activity. Hydroxyapatite is well known that can mimic at a significant level the activity of the initial bone. The material was synthesized by using an ultrasound probe and finally characterized by several methods. Thereby, the morphological properties were analyzed by using Scanning Electron Microscopy (SEM) and Transmission Electron Microscopy (TEM). Because the synthesized material has medical application in restore the tissue and to fight against microbial invasion, the samples were tested from the biological point of view by evaluating the biodegradability in phosphate-buffered saline (PBS) and simulated body fluid (SBF) and moreover the antimicrobial effect was performed on Gram-positive bacterium Staphylococcus aureus, Gram-negative bacterium Escherichia coli, and fungi Candida albicans. The results reveal that the obtained material has specific characteristics for bone regeneration.

Keywords: bacterial cellulose, biomaterials, hydroxyapatite, scaffolds materials

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33879 Influence of Dryer Autumn Conditions on Weed Control Based on Soil Active Herbicides

Authors: Juergen Junk, Franz Ronellenfitsch, Michael Eickermann

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An appropriate weed management in autumn is a prerequisite for an economically successful harvest in the following year. In Luxembourg oilseed rape, wheat and barley is sown from August until October, accompanied by a chemical weed control with soil active herbicides, depending on the state of the weeds and the meteorological conditions. Based on regular ground and surface water-analysis, high levels of contamination by transformation products of respective herbicide compounds have been found in Luxembourg. The most ideal conditions for incorporating soil active herbicides are single rain events. Weed control may be reduced if application is made when weeds are under drought stress or if repeated light rain events followed by dry spells, because the herbicides tend to bind tightly to the soil particles. These effects have been frequently reported for Luxembourg throughout the last years. In the framework of a multisite long-term field experiment (EFFO) weed monitoring, plants observations and corresponding meteorological measurements were conducted. Long-term time series (1947-2016) from the SYNOP station Findel-Airport (WMO ID = 06590) showed a decrease in the number of days with precipitation. As the total precipitation amount has not significantly changed, this indicates a trend towards rain events with higher intensity. All analyses are based on decades (10-day periods) for September and October of each individual year. To assess the future meteorological conditions for Luxembourg, two different approaches were applied. First, multi-model ensembles from the CORDEX experiments (spatial resolution ~12.5 km; transient projections until 2100) were analysed for two different Representative Concentration Pathways (RCP8.5 and RCP4.5), covering the time span from 2005 until 2100. The multi-model ensemble approach allows for the quantification of the uncertainties and also to assess the differences between the two emission scenarios. Second, to assess smaller scale differences within the country a high resolution model projection using the COSMO-LM model was used (spatial resolution 1.3 km). To account for the higher computational demands, caused by the increased spatial resolution, only 10-year time slices have been simulated (reference period 1991-2000; near future 2041-2050 and far future 2091-2100). Statistically significant trends towards higher air temperatures, +1.6 K for September (+5.3 K far future) and +1.3 K for October (+4.3 K), were predicted for the near future compared to the reference period. Precipitation simultaneously decreased by 9.4 mm (September) and 5.0 mm (October) for the near future and -49 mm (September) and -10 mm (October) in the far future. Beside the monthly values also decades were analyzed for the two future time periods of the CLM model. For all decades of September and October the number of days with precipitation decreased for the projected near and far future. Changes in meteorological variables such as air temperature and precipitation did already induce transformations in weed societies (composition, late-emerging etc.) of arable ecosystems in Europe. Therefore, adaptations of agronomic practices as well as effective weed control strategies must be developed to maintain crop yield.

Keywords: CORDEX projections, dry spells, ensembles, weed management

Procedia PDF Downloads 223
33878 Copula-Based Estimation of Direct and Indirect Effects in Path Analysis Models

Authors: Alam Ali, Ashok Kumar Pathak

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Path analysis is a statistical technique used to evaluate the direct and indirect effects of variables in path models. One or more structural regression equations are used to estimate a series of parameters in path models to find the better fit of data. However, sometimes the assumptions of classical regression models, such as ordinary least squares (OLS), are violated by the nature of the data, resulting in insignificant direct and indirect effects of exogenous variables. This article aims to explore the effectiveness of a copula-based regression approach as an alternative to classical regression, specifically when variables are linked through an elliptical copula.

Keywords: path analysis, copula-based regression models, direct and indirect effects, k-fold cross validation technique

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33877 Ligandless Extraction and Determination of Trace Amounts of Lead in Pomegranate, Zucchini and Lettuce Samples after Dispersive Liquid-Liquid Microextraction with Ultrasonic Bath and Optimization of Extraction Condition with RSM Design

Authors: Fariba Tadayon, Elmira Hassanlou, Hasan Bagheri, Mostafa Jafarian

Abstract:

Heavy metals are released into water, plants, soil, and food by natural and human activities. Lead has toxic roles in the human body and may cause serious problems even in low concentrations, since it may have several adverse effects on human. Therefore, determination of lead in different samples is an important procedure in the studies of environmental pollution. In this work, an ultrasonic assisted-ionic liquid based-liquid-liquid microextraction (UA-IL-DLLME) procedure for the determination of lead in zucchini, pomegranate, and lettuce has been established and developed by using flame atomic absorption spectrometer (FAAS). For UA-IL-DLLME procedure, 10 mL of the sample solution containing Pb2+ was adjusted to pH=5 in a glass test tube with a conical bottom; then, 120 μL of 1-Hexyl-3-methylimidazolium hexafluoro phosphate (CMIM)(PF6) was rapidly injected into the sample solution with a microsyringe. After that, the resulting cloudy mixture was treated by ultrasonic for 5 min, then the separation of two phases was obtained by centrifugation for 5 min at 3000 rpm and IL-phase diluted with 1 cc ethanol, and the analytes were determined by FAAS. The effect of different experimental parameters in the extraction step including: ionic liquid volume, sonication time and pH was studied and optimized simultaneously by using Response Surface Methodology (RSM) employing a central composite design (CCD). The optimal conditions were determined to be an ionic liquid volume of 120 μL, sonication time of 5 min, and pH=5. The linear ranges of the calibration curve for the determination by FAAS of lead were 0.1-4 ppm with R2=0.992. Under optimized conditions, the limit of detection (LOD) for lead was 0.062 μg.mL-1, the enrichment factor (EF) was 93, and the relative standard deviation (RSD) for lead was calculated as 2.29%. The levels of lead for pomegranate, zucchini, and lettuce were calculated as 2.88 μg.g-1, 1.54 μg.g-1, 2.18 μg.g-1, respectively. Therefore, this method has been successfully applied for the analysis of the content of lead in different food samples by FAAS.

Keywords: Dispersive liquid-liquid microextraction, Central composite design, Food samples, Flame atomic absorption spectrometry.

Procedia PDF Downloads 270
33876 Stochastic Edge Based Anomaly Detection for Supervisory Control and Data Acquisitions Systems: Considering the Zambian Power Grid

Authors: Lukumba Phiri, Simon Tembo, Kumbuso Joshua Nyoni

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In Zambia recent initiatives by various power operators like ZESCO, CEC, and consumers like the mines to upgrade power systems into smart grids target an even tighter integration with information technologies to enable the integration of renewable energy sources, local and bulk generation, and demand response. Thus, for the reliable operation of smart grids, its information infrastructure must be secure and reliable in the face of both failures and cyberattacks. Due to the nature of the systems, ICS/SCADA cybersecurity and governance face additional challenges compared to the corporate networks, and critical systems may be left exposed. There exist control frameworks internationally such as the NIST framework, however, there are generic and do not meet the domain-specific needs of the SCADA systems. Zambia is also lagging in cybersecurity awareness and adoption, therefore there is a concern about securing ICS controlling key infrastructure critical to the Zambian economy as there are few known facts about the true posture. In this paper, we introduce a stochastic Edged-based Anomaly Detection for SCADA systems (SEADS) framework for threat modeling and risk assessment. SEADS enables the calculation of steady-steady probabilities that are further applied to establish metrics like system availability, maintainability, and reliability.

Keywords: anomaly, availability, detection, edge, maintainability, reliability, stochastic

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33875 Reliability Analysis for the Functioning of Complete and Low Capacity MLDB Systems in Piston Plants

Authors: Ramanpreet Kaur, Upasana Sharma

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The purpose of this paper is to address the challenges facing the water supply for the Machine Learning Database (MLDB) system at the piston foundry plant. In the MLDB system, one main unit, i.e., robotic, is connected by two sub-units. The functioning of the system depends on the robotic and water supply. Lack of water supply causes system failure. The system operates at full capacity with the help of two sub-units. If one sub-unit fails, the system runs at a low capacity. Reliability modeling is performed using semi-Markov processes and regenerative point techniques. Several system effects such as mean time to system failure, availability at full capacity, availability at reduced capacity, busy period for repair and expected number of visits have been achieved. Benefits have been analyzed. The graphical study is designed for a specific case using programming in C++ and MS Excel.

Keywords: MLDB system, robotic, semi-Markov process, regenerative point technique

Procedia PDF Downloads 94
33874 Application of a Model-Free Artificial Neural Networks Approach for Structural Health Monitoring of the Old Lidingö Bridge

Authors: Ana Neves, John Leander, Ignacio Gonzalez, Raid Karoumi

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Systematic monitoring and inspection are needed to assess the present state of a structure and predict its future condition. If an irregularity is noticed, repair actions may take place and the adequate intervention will most probably reduce the future costs with maintenance, minimize downtime and increase safety by avoiding the failure of the structure as a whole or of one of its structural parts. For this to be possible decisions must be made at the right time, which implies using systems that can detect abnormalities in their early stage. In this sense, Structural Health Monitoring (SHM) is seen as an effective tool for improving the safety and reliability of infrastructures. This paper explores the decision-making problem in SHM regarding the maintenance of civil engineering structures. The aim is to assess the present condition of a bridge based exclusively on measurements using the suggested method in this paper, such that action is taken coherently with the information made available by the monitoring system. Artificial Neural Networks are trained and their ability to predict structural behavior is evaluated in the light of a case study where acceleration measurements are acquired from a bridge located in Stockholm, Sweden. This relatively old bridge is presently still in operation despite experiencing obvious problems already reported in previous inspections. The prediction errors provide a measure of the accuracy of the algorithm and are subjected to further investigation, which comprises concepts like clustering analysis and statistical hypothesis testing. These enable to interpret the obtained prediction errors, draw conclusions about the state of the structure and thus support decision making regarding its maintenance.

Keywords: artificial neural networks, clustering analysis, model-free damage detection, statistical hypothesis testing, structural health monitoring

Procedia PDF Downloads 191
33873 The Analysis of a Reactive Hydromagnetic Internal Heat Generating Poiseuille Fluid Flow through a Channel

Authors: Anthony R. Hassan, Jacob A. Gbadeyan

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In this paper, the analysis of a reactive hydromagnetic Poiseuille fluid flow under each of sensitized, Arrhenius and bimolecular chemical kinetics through a channel in the presence of heat source is carried out. An exothermic reaction is assumed while the concentration of the material is neglected. Adomian Decomposition Method (ADM) together with Pade Approximation is used to obtain the solutions of the governing nonlinear non – dimensional differential equations. Effects of various physical parameters on the velocity and temperature fields of the fluid flow are investigated. The entropy generation analysis and the conditions for thermal criticality are also presented.

Keywords: chemical kinetics, entropy generation, thermal criticality, adomian decomposition method (ADM) and pade approximation

Procedia PDF Downloads 448
33872 Mitigation of Size Effects in Woven Fabric Composites Using Finite Element Analysis Approach

Authors: Azeez Shaik, Yagnik Kalariya, Amit Salvi

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High-performance requirements and emission norms were forcing the automobile industry to opt for lightweight materials which improve the fuel efficiency and absorb energy during crash applications. In such scenario, the woven fabric composites are providing better energy absorption compared to metals. Woven fabric composites have a repetitive unit cell (RUC) and the mechanical properties of these materials are highly dependent on RUC. This work investigates the importance of detailed modelling of the RUC, the size effects associated and the mitigation techniques to avoid them using Finite element analysis approach.

Keywords: repetitive unit cell, representative volume element, size effects, cohesive zone, finite element analysis

Procedia PDF Downloads 241
33871 Adsorption of Toluene from Aqueous Solutions by Porous Clay Hetero-Structures

Authors: F. Asadi, M. M. Zerafat, S. Sabbaghi

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Among water pollutants, volatile organic compounds can cause severe long lasting effects not only on biotic organism but also on human health. As a result, this material group has attracted more attention in recent years. Adsorption is one of the common processes for remediation of aromatic compounds. In this study, porous clay hetrostructers (PCHs) are synthesized through gallery template approach and cetyltrimethylammonium bromide and dodecylamine used as template and co-template, respectively. Porous clay is characterized by XRD and FTIR. Batch adsorption experiments were carried out to investigate the effect of various adsorption parameters like adsorbent dosage, pH, initial concentration and contact time. It was found that by increasing adsorbent dosage from 0.5gr/lit to 4gr/lit, toluene removal is increased from 34% to 88.1%. Increasing contact time and decreasing the pH of aqueous solution increases toluene removal efficiency.

Keywords: adsorption, clay, nano-porous, toluene

Procedia PDF Downloads 324
33870 Adequacy of Advanced Earthquake Intensity Measures for Estimation of Damage under Seismic Excitation with Arbitrary Orientation

Authors: Konstantinos G. Kostinakis, Manthos K. Papadopoulos, Asimina M. Athanatopoulou

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An important area of research in seismic risk analysis is the evaluation of expected seismic damage of structures under a specific earthquake ground motion. Several conventional intensity measures of ground motion have been used to estimate their damage potential to structures. Yet, none of them was proved to be able to predict adequately the seismic damage of any structural system. Therefore, alternative advanced intensity measures which take into account not only ground motion characteristics but also structural information have been proposed. The adequacy of a number of advanced earthquake intensity measures in prediction of structural damage of 3D R/C buildings under seismic excitation which attacks the building with arbitrary incident angle is investigated in the present paper. To achieve this purpose, a symmetric in plan and an asymmetric 5-story R/C building are studied. The two buildings are subjected to 20 bidirectional earthquake ground motions. The two horizontal accelerograms of each ground motion are applied along horizontal orthogonal axes forming 72 different angles with the structural axes. The response is computed by non-linear 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 determined for incident angle 0° as well as their maximum values over all seismic incident angles are correlated with 9 structure-specific ground motion intensity measures. The research identified certain intensity measures which exhibited strong correlation with the seismic damage of the two buildings. However, their adequacy 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 indices, non-linear response, seismic excitation angle, structure-specific intensity measures

Procedia PDF Downloads 486
33869 The Moderation Effect of Critical Item on the Strategic Purchasing: Quality Performance Relationship

Authors: Kwong Yeung

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Theories about strategic purchasing and quality performance are underdeveloped. Understanding the evolving role of purchasing from reactive to proactive is a pressing strategic issue. Using survey responses from 176 manufacturing and electronics industry professionals, we study the relationships between strategic purchasing and supply chain partners’ quality performance to answer the following questions: Can transaction cost economics be used to elucidate the strategic purchasing-quality performance relationship? Is this strategic purchasing-quality performance relationship moderated by critical item analysis? The findings indicate that critical item analysis positively and significantly moderates the strategic purchasing-quality performance relationship.

Keywords: critical item analysis, moderation, quality performance, strategic purchasing, transaction cost economics

Procedia PDF Downloads 551