Search results for: convection-diffusion controlled model

Authors: Ismail Okur, Betul Taspinar, Turkan Pasali Kilit, Eda O. Okur, Ferruh Taspinar

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Type 2 Diabetes Mellitus (T2DM) is one of the most important global health emergencies and every year more and more people are affected by T2DM. T2DM causes life-changing complications by affecting organ and systems. Although diet and exercise are the best way to treat patients with T2DM, those patients generally have a sedentary life style. This study was planned to determine whether patients with T2DM have kinesiophobia (fear of movement). A controlled trial was conducted on 87 adults. Forty-one individuals with T2DM (study group, 34 female and 7 male) and 46 nondiabetic individuals (control group, 39 female and 7 male) were included in the study. Patients were screened for fear of movement using the Tampa Scale for Kinesiophobia (TSK). The data including age, sex, weight, height, and TSK scores were obtained. Mann Whitney U test were used to analyse the data. The mean ages and BMI of study and control groups were 51.98 ± 6.03 year and 49.52 ± 5.61 year and 31.82 ± 2.88 kg/m2 and 30.22 ± 2.91 kg/m2, respectively. The groups have similar demographic properties. The kinesiophobia scores of study and control groups were 42.78 ± 5.50 and 39.48 ± 5.05, respectively and the difference was statistically significant (p=0.05). This study showed that patients with T2DM had high kinesiophobia scores rather than nondiabetics. Those patients might avoid to do exercise. In other words, patients with T2DM might have lower physical activity level. Therefore the authors suggest that to evaluate and interfere with kinesiophobia before conducting exercise therapy will be useful for diabetes care.

Keywords: diabetes, fear of movement, kinesiophobia, type 2 diabetes mellitus

Procedia PDF Downloads 359

Authors: G. La Scalia, M. Enea, R. Micale, O. Corona, L. Settanni

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The quality and condition of perishable products delivered to the market and their subsequent selling prices are directly affected by the care taken during harvesting and handling. Mechanical injury, in fact, occurs at all stages, from pre-harvest operations through post-harvest handling, packing and transport to the market. The main implications of this damage are the reduction of the product’s quality and economical losses related to the shelf life diminution. For most perishable products, the shelf life is relatively short and it is typically dictated by microbial growth related to the application of dynamic and static loads during transportation. This paper presents the correlation between vibration levels and microbiological growth on strawberries and woodland strawberries and detects the presence of volatile organic compounds (VOC) in order to develop an intelligent logistic unit capable of monitoring VOCs using a specific sensor system. Fresh fruits were exposed to vibrations by means of a vibrating table in a temperature-controlled environment. Microbiological analyses were conducted on samples, taken at different positions along the column of the crates. The values obtained were compared with control samples not exposed to vibrations and the results show that different positions along the column influence the development of bacteria, yeasts and filamentous fungi.

Keywords: microbiological analysis, shelf life, transport damage, volatile organic compounds

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Authors: Usama Abdulwahab, Mohammed Wahab

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This paper presents the application of uncapacitated facility location problems (UFLP) and 1-median problems to support decision making in blood supply chain networks. A plethora of factors make blood supply-chain networks a complex, yet vital problem for the regional blood bank. These factors are rapidly increasing demand; criticality of the product; strict storage and handling requirements; and the vastness of the theater of operations. As in the UFLP, facilities can be opened at any of $m$ predefined locations with given fixed costs. Clients have to be allocated to the open facilities. In classical location models, the allocation cost is the distance between a client and an open facility. In this model, the costs are the allocation cost, transportation costs, and inventory costs. In order to address this problem the median algorithm is used to analyze inventory, evaluate supply chain status, monitor performance metrics at different levels of granularity, and detect potential problems and opportunities for improvement. The Euclidean distance data for some Ontario cities (demand nodes) are used to test the developed algorithm. Sitation software, lagrangian relaxation algorithm, and branch and bound heuristics are used to solve this model. Computational experiments confirm the efficiency of the proposed approach. Compared to the existing modeling and solution methods, the median algorithm approach not only provides a more general modeling framework but also leads to efficient solution times in general.

Keywords: approximate dynamic programming, facility location, perishable product, inventory model, blood platelet, P-median problem

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Authors: Mohamed Abdel-Monem, Gamal Sowilam, Omar Hegazy

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This paper presents a technical assessment of an electric vehicle with two independent rear-wheel motor and an improved traction control system. The electric differential and the control strategy have been implemented to assure that in a straight trajectory, the two rear-wheels run exactly at the same speed, considering the same/different road conditions under the left and right side of the wheels. In case of turning to right/left, the difference between the two rear-wheels speeds assures a vehicle trajectory without sliding, thanks to a harmony between the electric differential and the control strategy. The present article demonstrates a complete model and analysis of a traction control system, considering four different traction scenarios, for two independent rear-wheels motors for electric vehicles. Furthermore, the vehicle model, including wheel dynamics, load forces, electric differential, and control strategy, is designed and verified by using MATLAB/Simulink environment.

Keywords: electric vehicle, energy saving, multi-motor, electric differential, simulation and control

Procedia PDF Downloads 341

Authors: A. Abdikian

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A quantum breathing mode has been theatrically studied in quantum dusty plasma. By using linear quantum hydrodynamic model, not only the quantum dispersion relation of rotation mode but also void structure has been derived in the presence of an external magnetic field. Although the phase velocity of the magnetized quantum breathing mode is greater than that of unmagnetized quantum breathing mode, attenuation of the magnetized quantum breathing mode along radial distance seems to be slower than that of unmagnetized quantum breathing mode. Clearly, drawing the quantum breathing mode in the presence and absence of a magnetic field, we found that the magnetic field alters the distribution of dust particles and changes the radial and azimuthal velocities around the axis. Because the magnetic field rotates the dust particles and collects them, it could compensate the void structure.

Keywords: the linear quantum hydrodynamic model, the magnetized quantum breathing mode, the quantum dispersion relation of rotation mode, void structure

Procedia PDF Downloads 277

Authors: Bandhan Dey, Muhsina Bintoon Yiasha, Gulam Sulaman Choudhury

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Chest disease is one of the most problematic ailments in our regular life. There are many known chest diseases out there. Diagnosing them correctly plays a vital role in the process of treatment. There are many methods available explicitly developed for different chest diseases. But the most common approach for diagnosing these diseases is through X-ray. In this paper, we proposed a multi-classification deep learning model for diagnosing COVID-19, lung cancer, pneumonia, tuberculosis, and atelectasis from chest X-rays. In the present work, we used the transfer learning method for better accuracy and fast training phase. The performance of three architectures is considered: InceptionV3, VGG-16, and VGG-19. We evaluated these deep learning architectures using public digital chest x-ray datasets with six classes (i.e., COVID-19, lung cancer, pneumonia, tuberculosis, atelectasis, and normal). The experiments are conducted on six-classification, and we found that VGG16 outperforms other proposed models with an accuracy of 95%.

Keywords: deep learning, image classification, X-ray images, Tensorflow, Keras, chest diseases, convolutional neural networks, multi-classification

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Authors: Nurfirdawati Muhamad Hanafi, Azmanirah Ab Rahman, Marina Ibrahim Mukhtar, Jamil Ahmad, Sarebah Warman

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This study was conducted to generate empirical evidence on validity and reliability of the item of Competency Assessment Implementation (CAI) Instrument using Rasch Model for polythomous data aided by Winstep software version 3.68. The construct validity was examined by analyzing the point-measure correlation index (PTMEA), in fit and outfit MNSQ values; meanwhile the reliability was examined by analyzing item reliability index. A survey technique was used as the major method with the CAI instrument on 156 teachers from vocational schools. The results have shown that the reliability of CAI Instrument items were between 0.80 and 0.98. PTMEA Correlation is in positive values, in which the item is able to distinguish between the ability of the respondent. Statistical data obtained shows that out of 154 items, 12 items from the instrument suggested to be omitted. This study is hoped could bring a new direction to the process of data analysis in educational research.

Keywords: competency assessment, reliability, validity, item analysis

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Authors: Nurulhikma Md Isa, Intan Elya Suka, Nur Farhana Roslan, Chew Bee Lynn

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The evolutionarily conserved N-end rule pathway marks proteins for degradation by the Ubiquitin Proteosome System (UPS) based on the nature of their N-terminal residue. Proteins with a destabilizing N-terminal residue undergo a series of condition-dependent N-terminal modifications, resulting in their ubiquitination and degradation. Intensive research has been carried out in Arabidopsis previously. The group VII Ethylene Response Factor (ERFs) transcription factors are the first N-end rule pathway substrates found in Arabidopsis and their role in regulating oxygen sensing. ERFs also function as central hubs for the perception of gaseous signals in plants and control different plant developmental including germination, stomatal aperture, hypocotyl elongation and stress responses. However, nothing is known about the role of this pathway during fruit development and ripening aspect. The plant model system Arabidopsis cannot represent fleshy fruit model system therefore tomato is the best model plant to study. PROTEOLYSIS6 (PRT6) is an E3 ubiquitin ligase of the N-end rule pathway. Two homologs of PRT6 sequences have been identified in tomato genome database using the PRT6 protein sequence from model plant Arabidopsis thaliana. Homology search against Ensemble Plant database (tomato) showed Solyc09g010830.2 is the best hit with highest score of 1143, e-value of 0.0 and 61.3% identity compare to the second hit Solyc10g084760.1. Further homology search was done using NCBI Blast database to validate the data. The result showed best gene hit was XP_010325853.1 of uncharacterized protein LOC101255129 (Solanum lycopersicum) with highest score of 1601, e-value 0.0 and 48% identity. Both Solyc09g010830.2 and uncharacterized protein LOC101255129 were genes located at chromosome 9. Further validation was carried out using BLASTP program between these two sequences (Solyc09g010830.2 and uncharacterized protein LOC101255129) to investigate whether they were the same proteins represent PRT6 in tomato. Results showed that both proteins have 100 % identity, indicates that they were the same gene represents PRT6 in tomato. In addition, we used two different RNAi constructs that were driven under 35S and Polygalacturonase (PG) promoters to study the function of PRT6 during tomato developmental stages and ripening processes.

Keywords: ERFs, PRT6, tomato, ubiquitin

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Authors: İsmail Seçer, Taştan Seçer

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In this study, the effect of the group counseling on the victimhood perceptions of the primary school 7th and 8th grade students who are determined to be the subject of peer victimization and their dealing way with it was analyzed. The research model is Solomon Four Group Experimental Model. In this model, there are four groups that were determined with random sampling. Two of the groups have been used as experimental group and the other two have been used as control group. Solomon model is defined as real experimental model. In real experimental models, there are multiple groups consisting of subject which have similar characteristics, and selection of the subjects is done with random sampling. For this purpose, 230 students from Kültür Kurumu Primary School in Erzurum were asked to fill Adolescent Peer Victim Form. 100 students whose victim scores were higher and who were determined to be the subject of bullying were talked face to face and informed about the current study, and they were asked if they were willing to participate or not. As a result of these interviews, 60 students were determined to participate in the experimental study and four group consisting of 15 people were created with simple random sampling method. After the groups had been formed, experimental and control group were determined with casting lots. After determining experimental and control groups, an 11-session group counseling activity which was prepared by the researcher according to the literature was applied. The purpose of applying group counseling is to change the ineffective dealing ways with bullying and their victimhood perceptions. Each session was planned to be 75 minutes and applied as planned. In the control groups, counseling activities in the primary school counseling curricula was applied for 11 weeks. As a result of the study, physical, emotional and verbal victimhood perceptions of the participants in the experimental groups were decreased significantly compared to pre-experimental situations and to those in control group. Besides, it was determined that this change observed in the victimhood perceptions of the experimental group occurred independently from the effect of variables such as gender, age and academic success. The first evidence of the study related to the dealing ways is that the scores of the participants in the experimental group related to the ineffective dealing ways such as despair and avoidance is decreased significantly compared to the pre-experimental situation and to those in control group. The second evidence related to the dealing ways is that the scores of the participants in the experimental group related to effective dealing ways such as seeking for help, consulting social support, resistance and optimism is increased significantly compared to the pre-experimental situation and to those in control group. According to the evidence obtained through the study, it can be said that group counseling is an effective approach to change the victimhood perceptions of the individuals who are the subject of bullying and their dealing strategies with it.

Keywords: bullying, perception of victimization, coping strategies, ancova analysis

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Authors: L. Q. Yuan, J. Yang, A. Siddiqui

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A new regression uncertainty analysis methodology was applied to determine the uncertainties of the critical heat flux (CHF) power correlation for an advanced 43-element bundle design, which was developed by Canadian Nuclear Laboratories (CNL) to achieve improved economics, resource utilization and energy sustainability. The new methodology is considered more appropriate than the traditional methodology in the assessment of the experimental uncertainty associated with regressions. The methodology was first assessed using both the Monte Carlo Method (MCM) and the Taylor Series Method (TSM) for a simple linear regression model, and then extended successfully to a non-linear CHF power regression model (CHF power as a function of inlet temperature, outlet pressure and mass flow rate). The regression uncertainty assessed by MCM agrees well with that by TSM. An equation to evaluate the CHF power regression uncertainty was developed and expressed as a function of independent variables that determine the CHF power.

Keywords: CHF experiment, CHF correlation, regression uncertainty, Monte Carlo Method, Taylor Series Method

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Authors: Kalu Uka Orji, Nasiman Sapari, Khamaruzaman W. Yusof

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Exposure of galena (PbS), tealite (PbSnS2), and other associated minerals during mining activities release lead (Pb) and other heavy metals into the mining water through oxidation and dissolution. Heavy metal pollution has become an environmental challenge. Lead, for instance, can cause toxic effects to human health, including brain damage. Ex-mining pond water was reported to contain lead as high as 69.46 mg/L. Conventional treatment does not easily remove lead from water. A promising and emerging treatment technology for lead removal is the application of the electrocoagulation (EC) process. However, some of the problems associated with EC are systematic reactor design, selection of maximum EC operating parameters, scale-up, among others. This study investigated an EC process for the removal of lead from synthetic ex-mining pond water using a batch reactor and Fe electrodes. The effects of various operating parameters on lead removal efficiency were examined. The results obtained indicated that the maximum removal efficiency of 98.6% was achieved at an initial PH of 9, the current density of 15mA/cm2, electrode spacing of 0.3cm, treatment time of 60 minutes, Liquid Motion of Magnetic Stirring (LM-MS), and electrode arrangement = BP-S. The above experimental data were further modeled and optimized using a 2-Level 4-Factor Full Factorial design, a Response Surface Methodology (RSM). The four factors optimized were the current density, electrode spacing, electrode arrangements, and Liquid Motion Driving Mode (LM). Based on the regression model and the analysis of variance (ANOVA) at 0.01%, the results showed that an increase in current density and LM-MS increased the removal efficiency while the reverse was the case for electrode spacing. The model predicted the optimal lead removal efficiency of 99.962% with an electrode spacing of 0.38 cm alongside others. Applying the predicted parameters, the lead removal efficiency of 100% was actualized. The electrode and energy consumptions were 0.192kg/m3 and 2.56 kWh/m3 respectively. Meanwhile, the adsorption kinetic studies indicated that the overall lead adsorption system belongs to the pseudo-second-order kinetic model. The adsorption dynamics were also random, spontaneous, and endothermic. The higher temperature of the process enhances adsorption capacity. Furthermore, the adsorption isotherm fitted the Freundlish model more than the Langmuir model; describing the adsorption on a heterogeneous surface and showed good adsorption efficiency by the Fe electrodes. Adsorption of Pb2+ onto the Fe electrodes was a complex reaction, involving more than one mechanism. The overall results proved that EC is an efficient technique for lead removal from synthetic mining pond water. The findings of this study would have application in the scale-up of EC reactor and in the design of water treatment plants for feed-water sources that contain lead using the electrocoagulation method.

Keywords: ex-mining water, electrocoagulation, lead, adsorption kinetics

Procedia PDF Downloads 135

Authors: Leonardo Alfredo Mendoza, Cristian Munoz, Marco Aurelio Pacheco, Manoela Kohler, Evelyn Batista, Rodrigo Moura

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Natural Language Processing (NLP) techniques are increasingly more powerful to be able to interpret the feelings and reactions of a person to a product or service. Sentiment analysis has become a fundamental tool for this interpretation but has few applications in languages other than English. This paper presents a classification of sentiment analysis in Portuguese with a base of comments from social networks in Portuguese. A word embedding's representation was used with a 50-Dimension GloVe pre-trained model, generated through a corpus completely in Portuguese. To generate this classification, the bidirectional long short-term memory and bidirectional Gated Recurrent Unit (GRU) models are used, reaching results of 99.1%.

Keywords: natural processing language, sentiment analysis, bidirectional long short-term memory, BI-LSTM, gated recurrent unit, GRU

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Authors: Ziani Zakarya, Mahdad Moustafa Yassine

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Greenhouse farming has greatly contributed to the development of modern agriculture by optimizing crops, especially market gardening, ornamental horticulture, and recently, fruit species ... Greenhouse cultivation has enabled farmers to produce fruits and vegetables out of season while guaranteeing them a good production, and therefore a considerable gain throughout the year. However, this mode of production has shown its limits, especially in extreme conditions, such as the continental steppe climate and the Saharan climate, which are characterized by significant thermal amplitudes and strong winds, making it impossible to use conventional greenhouses for several months, of the year. In Algeria and precisely in the highlands, the use of greenhouses by farmers is very rare or occasional, especially in spring, because the limiting factors mentioned above are frequent there, causing significant damage to the plant product and to the environment. infrastructure. The same observation is observed in the Saharan regions but with less frequencies. Certainly, the use of controlled multi-chapel greenhouses would solve the problem, but at what cost? These hi-tech infrastructures are very expensive to purchase but also to maintain, so few farmers have the financial means to obtain them. In addition, the existence of intelligent and less expensive polymer films, whose properties could control greenhouse production parameters, in particular, the temperature parameter, maybe a judicious solution for the development of new generations of greenhouses that can be used in extreme conditions and normal.

Keywords: greenhouse, polymer film, modern agriculture, optimizing crops

Procedia PDF Downloads 154

Authors: Wenqing Fan, Yixuan Cheng, Wei Huang

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The diversity and complexity of modern IT systems make it almost impossible for internal teams to find vulnerabilities in all software before the software is officially released. The emergence of threat intelligence and vulnerability reporting policy has greatly reduced the burden on software vendors and organizations to find vulnerabilities. However, to prove the existence of the reported vulnerability, it is necessary but difficult for security incident response team to build a deliberated vulnerable environment from the vulnerability report with limited and incomplete information. This paper presents a structured, standardized, machine-oriented vulnerability intelligence format, that can be used to automate the orchestration of Deliberated Vulnerable Environment (DVE). This paper highlights the important role of software configuration and proof of vulnerable specifications in vulnerability intelligence, and proposes a triad model, which is called DIR (Dependency Configuration, Installation Configuration, Runtime Configuration), to define software configuration. Finally, this paper has also implemented a prototype system to demonstrate that the orchestration of DVE can be automated with the intelligence.

Keywords: DIR triad model, DVE, vulnerability intelligence, vulnerability recurrence

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Authors: Abdusalam Sharf

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In the oil and gas industries, one of the most important issues in drilling wells is understanding the behavior of a flow through an annulus gap in a vertical position, whose outer wall is stationary whilst the inner wall rotates. The main emphasis is placed on a comparison of experimental and computational investigations into the effects of the rotation speed of the inner pipe on the axial velocity profiles. The computational investigations were carried out by employing CFD software, and Gambit and Fluent. Three turbulence models were used: standard, RNG with enhanced wall treatment, and SST model. The profiles of the axial velocity had investigated at different rotation speeds of the inner pipe with three different volumetric flow rates. The comparison results showed that the calculations satisfactorily predict the qualitative features of the axial and swirl velocity profiles and the RNG model performs the best results.

Keywords: computational fluid dynamics (CFD), SST k−ω shear-stress transport (k−ω mode variant), RNG k–ε renormalisation group (k−ε mode variant), y+ dimensionless distance from wall

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Authors: Hong Bae Kim, Chang Ho Hur

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Many governments have tried to reduce CO₂ emissions which are believed to be the main cause for global warming. The deployment of electric automobiles is regarded as an effective way to reduce CO₂ emissions. The Korean government has planned to deploy about 200,000 electric automobiles. The policy for the deployment of electric automobiles aims at not only decreasing gasoline consumption but also increasing electricity production. However, if an electricity consuming regions is not consistent with an electricity producing region, the policy generates environmental problems between regions. Hence, this paper has established the energy multi-region input-output model to specifically analyze the impacts of the deployment of electric automobiles on regional energy consumption and CO₂ emissions. Finally, the paper suggests policy directions regarding the deployment of electric automobiles.

Keywords: electric automobiles, CO2 emissions, regional imbalances in electricity production and consumption, energy multi-region input-output model

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Authors: Sang Kompiang Wirawan, Pandu Prabowo Jati, I Wayan Warmada

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Klaten Indonesian natural zeolite can be used as powder or pellet adsorbent. Pellet adsorbent has been made from activated natural zeolite powder by a conventional pressing method. Starch and formaldehyde were added as binder to strengthen the construction of zeolite pellet. To increase the absorptivity and its capacity, natural zeolite was activated first chemically and thermally. This research examined adsorption process of water from Isopropyl Alcohol (IPA)-water system using zeolite adsorbent pellet from natural zeolite powder which has been activated with H2SO4 0.1 M and 0.3 M. Adsorbent was pelleted by pressing apparatus at certain pressure to make specification in 1.96 cm diameter, 0.68 cm thickness which the natural zeolite powder (-80 mesh). The system of isopropyl-alcohol water contained 80% isopropyl-alcohol. Adsorption process was held in close-loop continuous apparatus which the zeolite pellet was put inside a column and the solution of IPA-water was circulated at certain flow. Concentration changing was examined thoroughly at a certain time. This adsorption process included mass transfer from bulk liquid into film layer and from film layer into the solid particle. Analysis of rate constant was using first order isotherm model that simulated with MATLAB. Besides using first order isotherm, intra-particle diffusion model was proposed by using pore diffusion model. The study shows that adsorbent activated by H2SO4 0.1 M has good absorptivity with mass transfer constant at 0.1286 min-1.

Keywords: intra-particle diffusion, fractional attainment, first order isotherm, zeolite

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Authors: Yufeng Li, Yinan Ma, Jing Wu, Chengnian Long

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Infrared object detection aims at separating small and dim target from clutter background and its capabilities extend beyond the limits of visible light, making it invaluable in a wide range of applications such as improving safety, security, efficiency, and functionality. However, existing methods are usually sensitive to the noise of the input infrared image, leading to a decrease in target detection accuracy and an increase in the false alarm rate in high-noise environments. To address this issue, an infrared small target detection algorithm called YOLO-IR is proposed in this paper to improve the robustness to high infrared noise. To address the problem that high noise significantly reduces the clarity and reliability of target features in infrared images, we design a soft-threshold coordinate attention mechanism to improve the model’s ability to extract target features and its robustness to noise. Since the noise may overwhelm the local details of the target, resulting in the loss of small target features during depth down-sampling, we propose a deep and shallow feature fusion neck to improve the detection accuracy. In addition, because the generalized Intersection over Union (IoU)-based loss functions may be sensitive to noise and lead to unstable training in high-noise environments, we introduce a Wasserstein-distance based loss function to improve the training of the model. The experimental results show that YOLO-IR achieves a 5.0% improvement in recall and a 6.6% improvement in F1-score over existing state-of-art model.

Keywords: infrared small target detection, high noise, robustness, soft-threshold coordinate attention, feature fusion

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Authors: Pakhapoom Sarapat, James M. Hill, Duangkamon Baowan

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Carbon nanotori provide several properties such as high tensile strength and heat resistance. They are promised to be ideal structures for encapsulation, and their encapsulation ability can be determined by the interaction energy between the carbon nanotori and the encapsulated nanostructures. Such interaction energy is evaluated using Lennard-Jones potential and continuum approximation. Here, four problems relating to toroidal molecules are determined in order to find the most stable configuration. Firstly, the interaction energy between a carbon nanotorus and an atom is examined. The second problem relates to the energy of a fullerene encapsulated inside a carbon nanotorus. Next, the interaction energy between two symmetrically situated and parallel nanotori is considered. Finally, the classical mechanics is applied to model the interaction energy between the toroidal structure of cyclodextrin and the spherical DNA molecules. These mathematical models might be exploited to study a number of promising devices for future developments in bio and nanotechnology.

Keywords: carbon nanotori, continuum approximation, interaction energy, Lennard-Jones potential, nanotechnology

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Authors: Sonia Ben Hamza, Sabra Habli, Nejla Mahjoub Said, Hervé Bournot, Georges Le Palec

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The distribution characteristics of pollutants released at different vertical inlet positions of an open channel are investigated with a three-dimensional numerical model. Pollutants are injected from time-dependent sources in a turbulent free surface flow. Numerical computations were carried out using ANSYS Fluent which is based on the finite volume approach. The air/water interface was modeled with the volume of the fluid method (VOF). By focusing on investigating the influences of flow on pollutants, it is found that pollutant released from the bottom position of the channel takes more time to disperse in the longitudinal direction of the flow in comparison with the case of pollutant released near the free surface. On the other hand, the pollutant released from the bottom position generates a vertical dispersion with decreased amplitude. These findings may assist in cost-effective scientific countermeasures to be taken for accident or planned pollutant discharged into a river.

Keywords: numerical simulation, pollutant release, turbulent free surface flow, VOF model

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Authors: Fadi Al Khatib, Raouf Mbarki, Malek Adouni

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In various sport and recreational activities, the patellofemoral joint undergoes large forces and moments while accommodating the significant knee joint movement. In doing so, this joint is commonly the source of anterior knee pain related to instability in normal patellar tracking and excessive pressure syndrome. One well-observed explanation of the instability of the normal patellar tracking is the patellofemoral ligaments and patellar tendon damage. Improved knowledge of the damage mechanism mediating ligaments and tendon injuries can be a great help not only in rehabilitation and prevention procedures but also in the design of better reconstruction systems in the management of knee joint disorders. This damage mechanism, specifically due to excessive mechanical loading, has been linked to the micro level of the fibred structure precisely to the tropocollagen molecules and their connection density. We argue defining a clear frame starting from the bottom (micro level) to up (macro level) in the hierarchies of the soft tissue may elucidate the essential underpinning on the state of the ligaments damage. To do so, in this study a multiscale fibril reinforced hyper elastoplastic Finite Element model that accounts for the synergy between molecular and continuum syntheses was developed to determine the short-term stresses/strains patellofemoral ligaments and tendon response. The plasticity of the proposed model is associated only with the uniaxial deformation of the collagen fibril. The yield strength of the fibril is a function of the cross-link density between tropocollagen molecules, defined here by a density function. This function obtained through a Coarse-graining procedure linking nanoscale collagen features and the tissue level materials properties using molecular dynamics simulations. The hierarchies of the soft tissues were implemented using the rule of mixtures. Thereafter, the model was calibrated using a statistical calibration procedure. The model then implemented into a real structure of patellofemoral ligaments and patellar tendon (OpenKnee) and simulated under realistic loading conditions. With the calibrated material parameters the calculated axial stress lies well with the experimental measurement with a coefficient of determination (R2) equal to 0.91 and 0.92 for the patellofemoral ligaments and the patellar tendon respectively. The ‘best’ prediction of the yielding strength and strain as compared with the reported experimental data yielded when the cross-link density between the tropocollagen molecule of the fibril equal to 5.5 ± 0.5 (patellofemoral ligaments) and 12 (patellar tendon). Damage initiation of the patellofemoral ligaments was located at the femoral insertions while the damage of the patellar tendon happened in the middle of the structure. These predicted finding showed a meaningful correlation between the cross-link density of the tropocollagen molecules and the stiffness of the connective tissues of the extensor mechanism. Also, damage initiation and propagation were documented with this model, which were in satisfactory agreement with earlier observation. To the best of our knowledge, this is the first attempt to model ligaments from the bottom up, predicted depending to the tropocollagen cross-link density. This approach appears more meaningful towards a realistic simulation of a damaging process or repair attempt compared with certain published studies.

Keywords: tropocollagen, multiscale model, fibrils, knee ligaments

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Authors: Bhavna Malik

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The study is build on a theoretical framework that links characteristics of job, key attitudes and intention to leave, why faculty may be disengaging from institutional service. The literature indicates that job characteristics, key attitudes and intention to leave are very important for effective organizational functioning. In general, the literature showed that some job characteristics might be the antecedents of job satisfaction and the aggregate variable job scope was positively associated with organizational commitment, and these key attitudes predicted intention to leave negatively. The present study attempted to propose a new integrative model of the relationships among job characteristics, key attitudes, and intention to leave. The main purpose of the present study is to examine the effects of job characteristics on intention to leave. While examining the role of job characteristics, the mediating roles of key attitudes were taken into account in order to better understand how job characteristics affect the exhibition of intention to leave. The secondary purpose is to investigate the effects of job characteristics on key attitudes, and the effects of key attitudes on intention to leave. Job characteristics of remuneration, resource for professional activities, career opportunities were positively associated with the work attitude of job satisfaction. The aggregate job scope was positively associated with the work attitude of organizational commitment although no single job characteristic was significantly associated with organizational commitment. Commitment, however, did not significantly affect time spent on institutional service. Two job characteristics—time spent on research and time spent on teaching—were negatively associated with this behavior. In general, the literature showed that some job characteristics might be the antecedents of job satisfaction and the aggregate variable job scope was positively associated with organizational commitment, and these key attiudes predicted intention to leave negatively. In turn, job satisfaction and organizational commitment were negatively associated with the intention to leave. In addition to these, organizational commitment was negatively associated with the intention to leave. However, no significant direct association was found between job characteristics and intention to leave.

Keywords: Job Characteristics Model, job satisfaction, organizational commitment, intention to leave

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Authors: José Leandro Melgar Néris, Claudinéia Brazil, Luciane Teresa Salvi, Isabel Cristina Damin

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The impact the climate change is not recent, the main variable in the hydrological cycle is the sequence and shortage of a drought, which has a significant impact on the socioeconomic, agricultural and environmental spheres. This study aims to characterize and quantify, based on precipitation climatic projections, the rainy and dry events in the region of the Uruguay River Basin, through the Standardized Precipitation Index (SPI). The database is the image that is part of the Intercomparison of Model Models, Phase 5 (CMIP5), which provides condition prediction models, organized according to the Representative Routes of Concentration (CPR). Compared to the normal set of climates in the Uruguay River Watershed through precipitation projections, seasonal precipitation increases for all proposed scenarios, with a low climate trend. From the data of this research, the idea is that this article can be used to support research and the responsible bodies can use it as a subsidy for mitigation measures in other hydrographic basins.

Keywords: climate change, climatic model, dry events, precipitation projections

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Authors: Akane Uda, Ami Tabata, Mi An, Misa Komaki, Ryotaro Ito, Mayumi Inoue, Takehiro Sasai, Yusuke Kusano, Toshihiro Kato

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Early intervention is recommended for children with autism spectrum disorder (ASD), and an increasing number of children have received support and intervention before school age in recent years. In this study, we systematically reviewed preschool interventions focused on repetitive behaviors observed in children with ASD, which are often observed at younger ages. Inclusion criteria were as follows : (1) Child of preschool status (age ≤ 7 years) with a diagnosis of ASD (including autism, Asperger's, and pervasive developmental disorder) or a parent (caregiver) with a preschool child with ASD, (2) Physician-confirmed diagnosis of ASD (autism, Asperger's, and pervasive developmental disorder), (3) Interventional studies for repetitive behaviors, (4) Original articles published within the past 10 years (2012 or later), (5) Written in English and Japanese. Exclusion criteria were as follows: (1) Systematic reviews or meta-analyses, (2) Conference reports or books. We carefully scrutinized databases to remove duplicate references and used a two-step screening process to select papers. The primary screening included close scrutiny of titles and abstracts to exclude articles that did not meet the eligibility criteria. During the secondary screening, we carefully read the complete text to assess eligibility, which was double-checked by six members at the laboratory. Disagreements were resolved through consensus-based discussion. Our search yielded 304 papers, of which nine were included in the study. The level of evidence was as follows: three randomized controlled trials (level 2), four pre-post studies (level 4b), and two case reports (level 5). Seven articles selected for this study described the effectiveness of interventions. Interventions for repetitive behaviors in preschool children with ASD were categorized as five interventions that directly involved the child and four educational programs for caregivers and parents. Studies that directly intervened with children used early intensive intervention based on applied behavior analysis (Early Start Denver Model, Early Intensive Behavioral Intervention, and the Picture Exchange Communication System) and individualized education based on sensory integration. Educational interventions for caregivers included two methods; (a) education regarding combined methods and practices of applied behavior analysis in addition to classification and coping methods for repetitive behaviors, and (b) education regarding evaluation methods and practices based on children’s developmental milestones in play. With regard to the neurophysiological basis of repetitive behaviors, environmental factors are implicated as possible contributors. We assumed that applied behavior analysis was shown to be effective in reducing repetitive behaviors because analysis focused on the interaction between the individual and the environment. Additionally, with regard to educational interventions for caregivers, the intervention was shown to promote behavioral change in children based on the caregivers' understanding of the classification of repetitive behaviors and the children’s developmental milestones in play and adjustment of the person-environment context led to a reduction in repetitive behaviors.

Keywords: autism spectrum disorder, early intervention, repetitive behaviors, systematic review

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Authors: Sidique Gawusu, Xiaobing Zhang

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Turbulence models play a significant role in all computational fluid dynamics based modelling approaches. There is, however, no general turbulence model suitable for all flow scenarios. Therefore, a successful numerical modelling approach is only achievable if a more appropriate closure model is used. This paper evaluates different turbulence models in numerical modelling of oil-water flow within the Eulerian-Eulerian approach. A comparison among the obtained numerical results and published benchmark data showed reasonable agreement. The domain was meshed using structured mesh, and grid test was performed to ascertain grid independence. The evaluation of the models was made through analysis of velocity and pressure profiles across the domain. The models were tested for their suitability to accurately obtain a scalable and precise numerical experience. As a result, it is found that all the models except Standard-ω provide comparable results. The study also revealed new insights on flow in porous media, specifically oil reservoirs.

Keywords: turbulence modelling, simulation, multi-phase flows, water-flooding, heavy oil

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Authors: Anatoliy Kharkhurin

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Modifications that the prefix ‘trans-‘ refers to start within a person. This presentation focuses on the transpersonal that goes beyond the individual (trans-personal) to encompass wider aspects of humanities, specifically peak experience as a culminating stage of the creative act. It proposes a model according to which the peak experience results from a harmonious vibration of four spheres, which transcend an individual’s capacities and bring one to a qualitatively different level of experience. Each sphere represents an aspect of creative activity: superconscious, intellectual, emotive and active. Each sphere corresponds to one of four creative functions: authenticity, novelty, aesthetics, and utility, respectively. The creative act starts in the superconscious sphere: the supreme pleasure of Creation is reflected in creative pleasure, which is realized in creative will. These three instances serve as a source of force axes, which penetrate other spheres, and in place of infiltration establish restrictive, expansive, and integrative principles, respectively; the latter balances the other two and ensures a harmonious vibration within a sphere. This Hegelian-like triad is realized within each sphere in the form of creative capacities. The intellectual sphere nurtures capacities to invent and to elaborate, which are integrated by capacity to conceptualize. The emotive sphere nurtures satiation and restrictive capacities integrated by capacity to balance. The active sphere nurtures goal orientation and stabilization capacities integrated by capacity for self-expression. All four spheres vibrate within each other – the superconscious sphere being in the core of the structure followed by intellectual, emotive, and active spheres, respectively – thereby reflecting the path of creative production. If the spheres vibrate in-phase, their amplitudes amplify the creative energy; if in antiphase – the amplitudes reduce the creative energy. Thus, creative act is perceived as continuum with perfectly harmonious vibration within and between the spheres on one side and perfectly disharmonious vibration on the other.

Keywords: creativity, model, transpersonal, peak experience

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Authors: Maryam Karimi, Rouzbeh Nazari

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Introduction: Understanding thermal distribution in the micro-urban climate has now been necessary for urban planners or designers due to the impact of complex micro-scale features of Urban Heat Island (UHI) on the built environment and public health. Hence, understanding the interrelation between urban components and thermal pattern can assist planners in the proper addition of vegetation to build-environment, which can minimize the UHI impact. To characterize the need for urban green infrastructure (UGI) through better urban planning, this study proposes the use of RayMan model to measure the impact of air quality and increased temperature based on urban morphology in the selected metropolitan cities. This project will measure the impact of build environment for urban and regional planning using human biometeorological evaluations (Tmrt). Methods: We utilized the RayMan model to estimate the Tmrt in an urban environment incorporating location and height of buildings and trees as a supplemental tool in urban planning and street design. The estimated Tmrt value will be compared with existing surface and air temperature data to find the actual temperature felt by pedestrians. Results: Our current results suggest a strong relationship between sky-view factor (SVF) and increased surface temperature in megacities based on current urban morphology. Conclusion: This study will help with Quantifying the impacts of the built environment and surface properties on surrounding temperature, identifying priority urban neighborhoods by analyzing Tmrt and air quality data at the pedestrian level, and characterizing the need for urban green infrastructure cooling potential.

Keywords: built environment, urban planning, urban cooling, extreme heat

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Authors: Shayan Mohajer Hamidi

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Federated Learning (FL) has emerged as a promising paradigm for training machine learning models on distributed data without the need for centralized data aggregation. In the realm of wireless communications, FL has the potential to leverage the vast amounts of data generated by wireless devices to improve model performance and enable intelligent applications. However, the fairness aspect of FL in wireless communications remains largely unexplored. This abstract presents an idea for fair federated learning in wireless communications, addressing the challenges of imbalanced data distribution, privacy preservation, and resource allocation. Firstly, the proposed approach aims to tackle the issue of imbalanced data distribution in wireless networks. In typical FL scenarios, the distribution of data across wireless devices can be highly skewed, resulting in unfair model updates. To address this, we propose a weighted aggregation strategy that assigns higher importance to devices with fewer samples during the aggregation process. By incorporating fairness-aware weighting mechanisms, the proposed approach ensures that each participating device's contribution is proportional to its data distribution, thereby mitigating the impact of data imbalance on model performance. Secondly, privacy preservation is a critical concern in federated learning, especially in wireless communications where sensitive user data is involved. The proposed approach incorporates privacy-enhancing techniques, such as differential privacy, to protect user privacy during the model training process. By adding carefully calibrated noise to the gradient updates, the proposed approach ensures that the privacy of individual devices is preserved without compromising the overall model accuracy. Moreover, the approach considers the heterogeneity of devices in terms of computational capabilities and energy constraints, allowing devices to adaptively adjust the level of privacy preservation to strike a balance between privacy and utility. Thirdly, efficient resource allocation is crucial for federated learning in wireless communications, as devices operate under limited bandwidth, energy, and computational resources. The proposed approach leverages optimization techniques to allocate resources effectively among the participating devices, considering factors such as data quality, network conditions, and device capabilities. By intelligently distributing the computational load, communication bandwidth, and energy consumption, the proposed approach minimizes resource wastage and ensures a fair and efficient FL process in wireless networks. To evaluate the performance of the proposed fair federated learning approach, extensive simulations and experiments will be conducted. The experiments will involve a diverse set of wireless devices, ranging from smartphones to Internet of Things (IoT) devices, operating in various scenarios with different data distributions and network conditions. The evaluation metrics will include model accuracy, fairness measures, privacy preservation, and resource utilization. The expected outcomes of this research include improved model performance, fair allocation of resources, enhanced privacy preservation, and a better understanding of the challenges and solutions for fair federated learning in wireless communications. The proposed approach has the potential to revolutionize wireless communication systems by enabling intelligent applications while addressing fairness concerns and preserving user privacy.

Keywords: federated learning, wireless communications, fairness, imbalanced data, privacy preservation, resource allocation, differential privacy, optimization

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Authors: Tayyaba Ghani, Mazhar Mehmood, Mohammad Mujahid

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TiO₂ nanotubes are receiving immense attraction in the field of dye-sensitized solar cells due to their well-defined nanostructures, efficient electron transport and large surface area as compared to other one dimensional structures. In the present work, we have investigated the influence of temperature on the morphology of anodically produced self-organized Titanium oxide nanotubes (TiNTs). TiNTs are synthesized by two-step anodization method in an ethylene glycol based electrolytes containing ammonium fluoride. Experiments are performed at constant anodization voltage for two hours. An investigation by the SEM images reveals that if the temperature is kept constant during the anodizing experiment, variation in the average tube diameter is significantly reduced. However, if the temperature is not controlled then due to the exothermic nature of reactions for the formation of TiNTs, the temperature of electrolyte keep on increasing. This variation in electrolyte bath temperature introduced strong variations in tube diameter (20 nm to 160 nm) along the length of tubes. Current profiles, recorded during the anodization experiment, predict the effect of constant and varying experimental temperatures as well. In both cases, XRD results show the complete anatase crystal structure of nanotube upon annealing at 450 °C. Present work highlights the importance of constant temperature during the anodization experiments in order to develop an ordered array of nanotubes with a uniform tube diameter.

Keywords: anodization, ordering, temperature, TiO₂ nanotubes

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Authors: Muhammed Ashiq Villanthenkodath, Shreya Pal

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Purpose: This study scrutinizes the impact of economic globalization on ecological footprint while endogenizing economic growth and energy consumption from 1990 to 2018 in India. Design/methodology/approach: The standard unit root test has been employed for time series analysis to unveil the integration order. Then, the cointegration was confirmed using autoregressive distributed lag (ARDL) analysis. Further, the study executed the dynamic ARDL simulation model to estimate long-run and short-run results along with simulation and robotic prediction. Findings: The cointegration analysis confirms the existence of a long-run association among variables. Further, economic globalization reduces the ecological footprint in the long run. Similarly, energy consumption decreases the ecological footprint. In contrast, economic growth spurs the ecological footprint in India. Originality/value: This study contributes to the literature in many ways. First, unlike studies that employ CO2 emissions and globalization nexus, this study employs ecological footprint for measuring environmental quality; since it is the broader measure of environmental quality, it can offer a wide range of climate change mitigation policies for India. Second, the study executes a multivariate framework with updated series from 1990 to 2018 in India to explore the link between EF, economic globalization, energy consumption, and economic growth. Third, the dynamic autoregressive distributed lag (ARDL) model has been used to explore the short and long-run association between the series. Finally, to our limited knowledge, this is the first study that uses economic globalization in the EF function of India amid facing a trade-off between sustainable economic growth and the environment in the era of globalization.

Keywords: economic globalization, ecological footprint, India, dynamic ARDL simulation model

Procedia PDF Downloads 106