Search results for: molecular dynamics simulation.

Authors: Mohamed Yousef, Magdy Samuel, Maha El-Meligy, Taher El-Bitar

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The present work is dealing with 2% Si-steel alloy. The alloy contains 0.05% C as well as 0.85% Al. The alloy under investigation would be used for electrical transformation purposes. A heating (expansion) - cooling (contraction) dilation investigation was executed to detect the a, a+g, and g transformation temperatures at the inflection points of the dilation curve. On heating, primary a  was detected at a temperature range between room temperature and 687 ^oC. The domain of a+g was detected in the range between 687 ^oC and 746 ^oC. g phase exists in the closed g region at the range between 746 ^oC and 1043 ^oC. The domain of a phase appears again at a temperature range between 1043 and 1105 ^oC, and followed by secondary a at temperature higher than 1105 ^oC. A physical simulation of thermo-mechanical processing on the as-cast alloy was carried out. The simulation process took into consideration the hot flat rolling pilot plant parameters. The process was executed on the thermo-mechanical simulator (Gleeble 3500). The process was designed to include seven consecutive passes. The 1^st pass represents the roughing stage, while the remaining six passes represent finish rolling stage. The whole process was executed at the temperature range from 1100 ^oC to 900 ^oC. The amount of strain starts with 23.5% at the roughing pass and decreases continuously to reach 7.5 % at the last finishing pass. The flow curve of the alloy can be abstracted from the stress-strain curves representing simulated passes. It shows alloy hardening from a pass to the other up to pass no. 6, as a result of decreasing the deformation temperature and increasing of cumulative strain. After pass no. 6, the deformation process enhances the dynamic recrystallization phenomena to appear, where the z-parameter would be high.

Keywords: si- steel, hot deformability, critical transformation temperature, physical simulation, thermo-mechanical processing, flow curve, dynamic softening.

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Authors: Komal Rathore, Aydin Sunol, Gita Iranipour, Luke Mulford

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Advanced wastewater treatment plants have complex biological kinetics, time variant influent flow rates and long processing times. Due to these factors, the modeling and operational control of advanced wastewater treatment plants become complicated. However, development of a robust model for advanced wastewater treatment plants has become necessary in order to increase the efficiency of the plants, reduce energy costs and meet the discharge limits set by the government. A dynamic model was designed using the Envirosim (Canada) platform software called BioWin for several wastewater treatment plants in Hillsborough County, Florida. Proper control strategies for various parameters such as mixed liquor suspended solids, recycle activated sludge and waste activated sludge were developed for models to match the plant performance. The models were tuned using both the influent and effluent data from the plant and their laboratories. The plant SCADA was used to predict the influent wastewater rates and concentration profiles as a function of time. The kinetic parameters were tuned based on sensitivity analysis and trial and error methods. The dynamic models were validated by using experimental data for influent and effluent parameters. The dissolved oxygen measurements were taken to validate the model by coupling them with Computational Fluid Dynamics (CFD) models. The Biowin models were able to exactly mimic the plant performance and predict effluent behavior for extended periods. The models are useful for plant engineers and operators as they can take decisions beforehand by predicting the plant performance with the use of BioWin models. One of the important findings from the model was the effects of recycle and wastage ratios on the mixed liquor suspended solids. The model was also useful in determining the significant kinetic parameters for biological wastewater treatment systems.

Keywords: BioWin, kinetic modeling, flowsheet simulation, dynamic modeling

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Authors: Viviana Ventre, Giacomo Di Tollo, Roberta Martino

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The portfolio selection problem includes the evaluation of many criteria that are difficult to compare directly and is characterized by uncertain elements. The portfolio selection problem can be modeled as a group decision problem in which several experts are invited to present their assessment. In this context, it is important to study and analyze the process of reaching a consensus among group members. Indeed, due to the various diversities among experts, reaching consensus is not necessarily always simple and easily achievable. Moreover, the concept of consensus is accompanied by the concept of false consensus, which is particularly interesting in the dynamics of group decision-making processes. False consensus can alter the evaluation and selection phase of the alternative and is the consequence of the decision maker's inability to recognize that his preferences are conditioned by subjective structures. The present work aims to investigate the dynamics of consensus attainment in a group decision problem in which equivalent portfolios are proposed. In particular, the study aims to analyze the impact of the subjective structure of the decision-maker during the evaluation and selection phase of the alternatives. Therefore, the experimental framework is divided into three phases. In the first phase, experts are sent to evaluate the characteristics of all portfolios individually, without peer comparison, arriving independently at the selection of the preferred portfolio. The experts' evaluations are used to obtain individual Analytical Hierarchical Processes that define the weight that each expert gives to all criteria with respect to the proposed alternatives. This step provides insight into how the decision maker's decision process develops, step by step, from goal analysis to alternative selection. The second phase includes the description of the decision maker's state through Markov chains. In fact, the individual weights obtained in the first phase can be reviewed and described as transition weights from one state to another. Thus, with the construction of the individual transition matrices, the possible next state of the expert is determined from the individual weights at the end of the first phase. Finally, the experts meet, and the process of reaching consensus is analyzed by considering the single individual state obtained at the previous stage and the false consensus bias. The work contributes to the study of the impact of subjective structures, quantified through the Analytical Hierarchical Process, and how they combine with the false consensus bias in group decision-making dynamics and the consensus reaching process in problems involving the selection of equivalent portfolios.

Keywords: analytical hierarchical process, consensus building, false consensus effect, markov chains, portfolio selection problem

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Authors: Doaa Hashad, Amany Elyamany, Perihan Salem

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Introduction: Hepatitis C virus infection (HCV) constitutes a serious dilemma that has an impact on the health of millions of Egyptians. Hepatitis C virus related hepatocellular carcinoma (HCV-HCC) is a crucial consequence of HCV that represents the third cause of cancer-related deaths worldwide. Aim of the study: assess the use of mitochondrial DNA (mtDNA) content as a non-invasive molecular biomarker in hepatitis c virus related hepatocellular carcinoma (HCV-HCC). Methods: A total of 135 participants were enrolled in the study. Volunteers were assigned to one of three groups equally; a group of HCV related cirrhosis (HCV-cirrhosis), a group of HCV-HCC and a control group of age- and sex- matched healthy volunteers with no evidence of liver disease. mtDNA was determined using a quantitative real-time PCR technique. Results: mtDNA content was lowest in HCV-HCC cases. No statistically significant difference was observed between the group of HCV-cirrhosis and the control group as regards mtDNA level. HCC patients with multi-centric hepatic lesions had significantly lower mtDNA content. On using receiver operating characteristic curve analysis, a cutoff of 34 was assigned for mtDNA content to distinguish between HCV-HCC and HCV-cirrhosis patients who are not yet complicated by malignancy. Lower mtDNA was associated with greater HCC risk on using healthy controls, HCV-cirrhosis, or combining both groups as a reference group. Conclusions: mtDNA content might constitute a non-invasive molecular biomarker that reflects tumor burden in HCV-HCC cases and could be used as a predictor of HCC risk in patients of HCV-cirrhosis. In addition, the non significant difference of mtDNA level between HCV-cirrhosis patients and healthy controls could eliminate the grey zone created by the use of AFP in some cirrhotic patients.

Keywords: DNA copy number, HCC, HCV, mitochondrial

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Authors: Jun Sung Go, Jong Kang Park, Jong Tae Kim

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As semi-conductor manufacturing technology evolves; the single event transient problem becomes more significant issue. Single event transient has a critical impact on both combinational and sequential logic circuits, so it is important to evaluate the soft error tolerance of the circuits at the design stage. In this paper, we present a soft error detecting simulation using scan chain. The simulation model generates a single event transient randomly in the circuit, and detects the soft error during the execution of the test patterns. We verified this model by inserting a scan chain in an 8051 microprocessor using 65 nm CMOS technology. While the test patterns generated by ATPG program are passing through the scan chain, we insert a single event transient and detect the number of soft errors per sub-module. The experiments show that the soft error rates per cell area of the SFR module is 277% larger than other modules.

Keywords: scan chain, single event transient, soft error, 8051 processor

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Authors: Zone-Ching Lin, Hao-Yuan Jheng, Shih-Hung Ma

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The present paper proposes using atomic force microscopy (AFM) and the concept of specific down force energy (SDFE) to establish a method for fabricating and cutting the burr for Y shape nanochannel on silicon (Si) substrate. For fabricating Y shape nanochannel, it first makes the experimental cutting path planning for fabricating Y shape nanochannel until the fifth cutting layer. Using the constant down force by AFM and SDFE theory and following the experimental cutting path planning, the cutting depth and width of each pass of Y shape nanochannel can be predicted by simulation. The paper plans the path for cutting the burr at the edge of Y shape nanochannel. Then, it carries out cutting the burr along the Y nanochannel edge by using a smaller down force. The height of standing burr at the edge is required to be below the set value of 0.54 nm. The results of simulation and experiment of fabricating and cutting the burr for Y shape nanochannel is further compared.

Keywords: atomic force microscopy (AFM), nanochannel, specific down force energy (SDFE), Y shape, burr, silicon

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Authors: H. Mousavi, M. Sharifi, H. Pourvaziri

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Redundancy Allocation Problem (RAP) is a well-known mathematical problem for modeling series-parallel systems. It is a combinatorial optimization problem which focuses on determining an optimal assignment of components in a system design. In this paper, to be more practical, we have considered the problem of redundancy allocation of series system with interval valued reliability of components. Therefore, during the search process, the reliabilities of the components are considered as a stochastic variable with a lower and upper bounds. In order to optimize the problem, we proposed a simulated annealing based on cloud theory (CBSAA). Also, the Monte Carlo simulation (MCS) is embedded to the CBSAA to handle the random variable components’ reliability. This novel approach has been investigated by numerical examples and the experimental results have shown that the CBSAA combining MCS is an efficient tool to solve the RAP of systems with interval-valued component reliabilities.

Keywords: redundancy allocation problem, simulated annealing, cloud theory, monte carlo simulation

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Authors: Charlene N. T. Mfangnia, Henri Tonnang, Berge Tsanou, Jeremy Herren

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The Microsporidia MB found in the populations of anopheles is a recently discovered symbiont responsible for the Plasmodium transmission blocking. From early studies, it was established that the symbiont can be transmitted vertically and horizontally. The present study uses compartmental mathematical modelling approach to investigate the dynamics of Microsporidia transmission in the mosquito population with the mindset of establishing a mechanism for use to control malaria. Data and information obtained from laboratory experiments are used to estimate the model parameters with and without temperature dependency of mosquito traits. We carry out the mathematical analysis focusing on the equilibria states and their stability for the autonomous model. Through the modelling experiments, we are able to assess and confirm the contribution of vertical and horizontal transmission in the proliferation of Microsporidia MB in the mosquito population. In addition, the basic and target reproductions are computed, and some long-term behaviours of the model, such as the local (and global) stability of equilibrium points, are rigorously analysed and illustrated numerically. We establish the conditions responsible for the low prevalence of the symbiont-infected mosquitoes observed in nature. Moreover, we identify the male death rate, the mating rate and the attractiveness of MB-positive mosquitoes as mosquito traits that significantly influence the spread of Microsporidia MB. Furthermore, we highlight the influence of temperature in the establishment and persistence of MB-infected mosquitoes in a given area.

Keywords: microsporidia MB, vertical transmission, horizontal transmission, compartmental modelling approach, temperature-dependent mosquito traits, malaria, plasmodium-transmission blocking

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Authors: Sukanya Devi Ramachandran, Vaishnavi Muralidharan, Kavya Chandrasekaran

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Polycaprolactone is polymer belonging to the polyester family that has noticeable characteristics of biodegradability and biocompatibility which is essential for medical applications. Polycaprolactone is produced by the ring opening polymerization of the monomer epsilon-Caprolactone (ε-CL) which is a closed ester, comprising of seven-membered ring. This process is normally catalysed by metallic components such as stannous octoate. It is difficult to remove the catalysts after the reaction, and they are also toxic to the human body. An alternate route of using enzymes as catalysts is being employed to reduce the toxicity. Lipase enzyme is a subclass of esterase that can easily attack the ester bonds of ε-CL. This research paper throws light on the extraction of lipase from germinating sunflower seeds and the activity of the biocatalyst in the polymerization of ε-CL. Germinating Sunflower seeds were crushed with fine sand in phosphate buffer of pH 6.5 into a fine paste which was centrifuged at 5000rpm for 10 minutes. The clear solution of the enzyme was tested for activity at various pH ranging from 5 to 7 and temperature ranging from 40oC to 70oC. The enzyme was active at pH6.0 and at 600C temperature. Polymerization of ε-CL was done using toluene as solvent with the catalysis of lipase enzyme, after which chloroform was added to terminate the reaction and was washed in cold methanol to obtain the polymer. The polymerization was done by varying the time from 72 hours to 6 days and tested for the molecular weight and the conversion of the monomer. The molecular weight obtained at 6 days is comparably higher. This method will be very effective, economical and eco-friendly to produce as the enzyme used can be regenerated as such at the end of the reaction and can be reused. The obtained polymers can be used for drug delivery and other medical applications.

Keywords: lipase, monomer, polycaprolactone, polymerization

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Authors: Samuel Fernandes, Dylan Kato, Emin Burak Onat, Patrick Keyantuo, Raja Sengupta, Amine Bouzaghrane

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The COVID-19 pandemic has spread across the United States, forcing cities to impose stay-at-home and shelter-in-place orders. Building operations had to adjust as non-essential personnel worked from home. But as buildings prepare for personnel to return, they need to plan for safe operations amid new COVID-19 guidelines. In this paper we propose a methodology for capacity and flow modeling of personnel within buildings to safely operate under COVID-19 guidelines. We model personnel flow within buildings by network flows with queuing constraints. We study maximum flow, minimum cost, and minimax objectives. We compare our network flow approach with a simulation model through a case study and present the results. Our results showcase various scenarios of how buildings could be operated under new COVID-19 guidelines and provide a framework for building operators to plan and operate buildings in this new paradigm.

Keywords: network analysis, building simulation, COVID-19

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Authors: Robert Prohaska, Arnaud Konan, Kenneth Kelly, Adam Ragatz, Adam Duran

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In an effort to evaluate the in-use performance of electrified Power Take-off (PTO) usage on bucket utility trucks operating under real-world conditions, data from 20 medium- and heavy-duty vehicles operating in California, USA were collected, compiled, and analyzed by the National Renewable Energy Laboratory's (NREL) Fleet Test and Evaluation team. In this paper, duty-cycle statistical analyses of class 5, medium-duty quick response trucks and class 8, heavy-duty material handler trucks are performed to examine and characterize vehicle dynamics trends and relationships based on collected in-use field data. With more than 100,000 kilometers of driving data collected over 880+ operating days, researchers have developed a robust methodology for identifying PTO operation from in-field vehicle data. Researchers apply this unique methodology to evaluate the performance and utilization of the conventional and electric PTO systems. Researchers also created custom representative drive-cycles for each vehicle configuration and performed modeling and simulation activities to evaluate the potential fuel and emissions savings for hybridization of the tractive driveline on these vehicles. The results of these analyses statistically and objectively define the vehicle dynamic and kinematic requirements for each vehicle configuration as well as show the potential for further system optimization through driveline hybridization. Results are presented in both graphical and tabular formats illustrating a number of key relationships between parameters observed within the data set that relates specifically to medium- and heavy-duty utility vehicles operating under real-world conditions.

Keywords: drive cycle, heavy-duty (HD), hybrid, medium-duty (MD), PTO, utility

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Authors: Evanka Madan, Madhu Puri, Dan Zilberstein, Rohini Muthuswami, Rentala Madhubala

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The extensive interaction between the host and pathogen metabolic networks decidedly shapes the outcome of infection. Utilization of arginine by the host and pathogen is critical for determining the outcome of pathogenic infection. Infections with L. donovani, an intracellular parasite, will lead to an extensive competition of arginine between the host and the parasite donovani infection. One of the major amino acid (AA) sensing signaling pathways in mammalian cells are the mammalian target of rapamycin complex I (mTORC1) pathway. mTORC1, as a sensor of nutrient, controls numerous metabolic pathways. Arginine is critical for mTORC1 activation. SLC38A9 is the arginine sensor for the mTORC1, being activated during arginine sufficiency. L. donovani transport arginine via a high-affinity transporter (LdAAP3) that is rapidly up-regulated by arginine deficiency response (ADR) in intracellular amastigotes. This study, to author’s best knowledge, investigates the interaction between two arginine sensing systems that act in the same compartment, the lysosome. One is important for macrophage defense, and the other is essential for pathogen virulence. We hypothesize that the latter modulates lysosome arginine to prevent host defense response. The work presented here identifies an upstream regulatory role of LdAAP3 in regulating the expression of SLC38A9-mTORC1 pathway, and consequently, their function in L. donovani infected THP-1 cells cultured in 0.1 mM and 1.5 mM arginine. It was found that in physiological levels of arginine (0.1 mM), infecting THP-1 with Leishmania leads to increased levels of SLC38A9 and mTORC1 via an increase in the expression of RagA. However, the reversal was observed with LdAAP3 mutants, reflecting the positive regulatory role of LdAAP3 on the host SLC38A9. At the molecular level, upon infection, mTORC1 and RagA were found to be activated at the surface of phagolysosomes which was found to form a complex with phagolysosomal localized SLC38A9. To reveal the relevance of SLC38A9 under physiological levels of arginine, endogenous SLC38A9 was depleted and a substantial reduction in the expression of host mTORC1, its downstream active substrate, p-P70S6K1 and parasite LdAAP3, was observed, thereby showing that silencing SLC38A9 suppresses ADR. In brief, to author’s best knowledge, these results reveal an upstream regulatory role of LdAAP3 in manipulating SLC38A9 arginine sensing in host macrophages. Our study indicates that intra-macrophage survival of L. donovani depends on the availability and transport of extracellular arginine. An understanding of the sensing pathway of both parasite and host will open a new perspective on the molecular mechanism of host-parasite interaction and consequently, as a treatment for Leishmaniasis.

Keywords: arginine sensing, LdAAP3, L. donovani, mTORC1, SLC38A9, THP-1

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Authors: K. R. Sreenivas, Shaurya Kaushal

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After sunset, under calm & clear-sky nocturnal conditions, the air layer near the surface containing aerosols cools through radiative processes to the upper atmosphere. Due to this cooling, surface air-layer temperature can fall 2-6 degrees C lower than the ground-surface temperature. This unstable convection layer, on the top, is capped by a stable inversion-boundary layer. Radiative divergence, along with the convection within the surface layer, governs the vertical transport of heat and moisture. Micro-physics in this layer have implications for the occurrence and growth of the fog layer. This particular configuration, featuring a convective mixed layer beneath a stably stratified inversion layer, exemplifies a classic case of penetrative convection. In this study, we conduct numerical simulations of the penetrative convection phenomenon within the nocturnal atmospheric surface layer and elucidate its relevance to the dynamics of fog layers. We employ field and laboratory measurements of aerosol number density to model the strength of the radiative cooling. Our analysis encompasses horizontally averaged, vertical profiles of temperature, density, and heat flux. The energetic incursion of the air from the mixed layer into the stable inversion layer across the interface results in entrainment and the growth of the mixed layer, modeling of which is the key focus of our investigation. In our research, we ascertain the appropriate length scale to employ in the Richardson number correlation, which allows us to estimate the entrainment rate and model the growth of the mixed layer. Our analysis of the mixed layer and the entrainment zone reveals a close alignment with previously reported laboratory experiments on penetrative convection. Additionally, we demonstrate how aerosol number density influences the growth or decay of the mixed layer. Furthermore, our study suggests that the presence of fog near the ground surface can induce extensive vertical mixing, a phenomenon observed in field experiments.

Keywords: inversion layer, penetrative convection, radiative cooling, fog occurrence

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Authors: Majid Arvan, Peyman Beygi, Sina Rokhsati

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In-time detection of fire in buildings is of great importance. Employing intelligent methods in data processing in fire detection systems leads to a significant reduction of fire damage at lowest cost. In this paper, the raw data obtained from the fire detection sensor networks in buildings is processed by using intelligent methods based on neural networks and the likelihood of fire happening is predicted. In order to enhance the quality of system, the noise in the sensor data is reduced by analyzing wavelets and applying SVD technique. Meanwhile, the proposed neural network is trained using particle swarm optimization (PSO). In the simulation work, the data is collected from sensor network inside the room and applied to the proposed network. Then the outputs are compared with conventional MLP network. The simulation results represent the superiority of the proposed method over the conventional one.

Keywords: intelligent fire detection, neural network, particle swarm optimization, fire sensor network

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Authors: Barenten Suciu

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In this work, effects of the friction and truncation on the dynamics of a double-cone gravitational motor, self-propelled on a straight V-shaped horizontal rail, are evaluated. Such mechanism has a variable radius of contact, and, on one hand, it is similar to a pulley mechanism that changes the potential energy into the kinetic energy of rotation, but on the other hand, it is similar to a pendulum mechanism that converts the potential energy of the suspended body into the kinetic energy of translation along a circular path. Movies of the self- propelled double-cones, made of S45C carbon steel and wood, along rails made of aluminum alloy, were shot for various opening angles of the rails. Kinematical features of the double-cones were estimated through the slow-motion processing of the recorded movies. Then, a kinematical model is derived under assumption that the distance traveled by the contact points on the rectilinear rails is identical with the distance traveled by the contact points on the truncated conical surface. Additionally, a dynamic model, for this particular contact problem, was proposed and validated against the experimental results. Based on such model, the traction force and the traction torque acting on the double-cone are identified. One proved that the rolling traction force is always smaller than the sliding friction force; i.e., the double-cone is rolling without slipping. Results obtained in this work can be used to achieve the proper design of such gravitational motor.

Keywords: Truncated double-cone, friction, rolling and sliding, dynamic model, gravitational motor

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Authors: David Oyewumi Oyekunle, David Preston, Florence Ibeh

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The paper provides an overview of the impacts of the human dimension in project management and team management on projects, which is increasingly affecting the performance of organizations. Recognizing its crucial significance, the research focuses on analyzing the psychological and interpersonal dynamics within project teams. This research is highly significant in the dynamic field of project management, as it addresses important gaps and offers vital insights that align with the constantly changing demands of the profession. A case study was conducted at the University of Salford to examine how human activity affects project management and performance. The study employed a mixed methodology to gain a deeper understanding of the real-world experiences of the subjects and project teams. Data analysis procedures to address the research objectives included the deductive approach, which involves testing a clear hypothesis or theory, as well as descriptive analysis and visualization. The survey comprised a sample size of 40 participants out of 110 project management professionals, including staff and final students in the Salford Business School, using a purposeful sampling method. To mitigate bias, the study ensured diversity in the sample by including both staff and final students. A smaller sample size allowed for more in-depth analysis and a focused exploration of the research objective. Conflicts, for example, are intricate occurrences shaped by a multitude of psychological stimuli and social interactions and may have either a deterrent perspective or a positive perspective on project performance and project management productivity. The study identified conflict elements, including culture, environment, personality, attitude, individual project knowledge, team relationships, leadership, and team dynamics among team members, as crucial human activities to minimize conflict. The findings are highly significant in the dynamic field of project management, as they address important gaps and offer vital insights that align with the constantly changing demands of the profession. It provided project professionals with valuable insights that can help them create a collaborative and high-performing project environment. Uncovering human influence on project performance, effective communication, optimal team synergy, and a keen understanding of project scope are necessary for the management of projects to attain exceptional performance and efficiency. For the research to achieve the aims of this study, it was acknowledged that the productive dynamics of teams and strong group cohesiveness are crucial for effectively managing conflicts in a beneficial and forward-thinking manner. Addressing the identified human influence will contribute to a more sustainable project management approach and offer opportunities for exploration and potential contributions to both academia and practical project management.

Keywords: human dimension, project management, team dynamics, conflict resolution

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Authors: Daniel Fundi Murithi

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Data from economic, social, clinical, and industrial studies are in some way incomplete or incorrect due to censoring. Such data may have adverse effects if used in the estimation problem. We propose the use of Maximum Likelihood Estimation (MLE) under a progressive type-II censoring scheme to remedy this problem. In particular, maximum likelihood estimates (MLEs) for the location (µ) and scale (λ) parameters of two Parameter Rayleigh distribution are realized under a progressive type-II censoring scheme using the Expectation-Maximization (EM) and the Newton-Raphson (NR) algorithms. These algorithms are used comparatively because they iteratively produce satisfactory results in the estimation problem. The progressively type-II censoring scheme is used because it allows the removal of test units before the termination of the experiment. Approximate asymptotic variances and confidence intervals for the location and scale parameters are derived/constructed. The efficiency of EM and the NR algorithms is compared given root mean squared error (RMSE), bias, and the coverage rate. The simulation study showed that in most sets of simulation cases, the estimates obtained using the Expectation-maximization algorithm had small biases, small variances, narrower/small confidence intervals width, and small root of mean squared error compared to those generated via the Newton-Raphson (NR) algorithm. Further, the analysis of a real-life data set (data from simple experimental trials) showed that the Expectation-Maximization (EM) algorithm performs better compared to Newton-Raphson (NR) algorithm in all simulation cases under the progressive type-II censoring scheme.

Keywords: expectation-maximization algorithm, maximum likelihood estimation, Newton-Raphson method, two-parameter Rayleigh distribution, progressive type-II censoring

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Authors: Laura Brennan, Ram Balakumar

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ChatGPT has been developed by Open AI (Nov 2022) as a powerful artificial intelligence (AI) language model which has been designed to produce human-like text from user written prompts. To gain the most from the system, user written prompts must give context specific information. This article aims to give guidance on how to optimise the ChatGPT system in the context of education for otolaryngology. Otolaryngology is a specialist field which sees little time dedicated to providing education to both medical students and doctors. Additionally, otolaryngology trainees have seen a reduction in learning opportunities since the COVID-19 pandemic. In this article we look at these various barriers to medical education in Otolaryngology training and suggest ways that ChatGPT can overcome them and assist in simulation-based training. Examples provide how this can be achieved using the Authors’ experience to further highlight the practicalities. What this article has found is that while ChatGPT cannot replace traditional mentorship and practical surgical experience, it can serve as an invaluable supplementary resource to simulation based medical education in Otolaryngology.

Keywords: artificial intelligence, otolaryngology, surgical training, medical education

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Authors: Tej Varma Y, Debi D. Pant

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Photophysics and rotational dynamics of the fluorescent probe, 6-methoxyquinoline (6MQ) with cationic surfactant, alkyltrimethylammonium bromide (nTAB) micelle solutions have been investigated (n = 12, 14 and 16). Absorption and emission peaks of the dye have been observed to shift at concentrations around critical micellar concentration (cmc) of nTAB compared to that of bulk solutions suggesting probe is in a lower polar environment. The probe senses changes in polarity (ET (30)) brought about by variation of surfactant chain length concentration and is invariably solubilized in the aqueous interface or palisade layer. The order of change in polarity observed was DTAB > CTAB > TTAB. The binding constant study shows that the probe binds strongest with TTAB (is of the order TTAB > CTAB > DTAB) due to deeper penetration into the micelle. The anisotropy decay for the probe in all the nTAB micelles studied have been rationalized based on a two-step model consisting of fast-restricted rotation of the probe and slow lateral diffusion of the probe in the micelle that is coupled to the overall rotation of the micelle. Fluorescence lifetime measurements of probe in the cationic micelles demonstrate the close proximity of the 6MQ to the Br - counterions. The fluorescence lifetimes of TTAB and DTAB are much shorter than in CTAB. These results indicate that 6MQ resides to a substantial degree in the head group region of the micelles. All the changes observed in the steady state fluorescence, microenvironment, fluorescence lifetimes, fluorescence anisotropy, and other calculations are in agreement with each other suggesting binding of the cationic surfactant with the neutral dye molecule.

Keywords: photophysics, chain length, ntaB, micelles

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Authors: Badr M. Alshammari, T. Guesmi

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In this paper, the concept of a non-dominated sorting multi-objective particle swarm optimization with local search (NSPSO-LS) is presented for the optimal design of multimachine power system stabilizers (PSSs). The controller design is formulated as an optimization problem in order to shift the system electromechanical modes in a pre-specified region in the s-plan. A composite set of objective functions comprising the damping factor and the damping ratio of the undamped and lightly damped electromechanical modes is considered. The performance of the proposed optimization algorithm is verified for the 3-machine 9-bus system. Simulation results based on eigenvalue analysis and nonlinear time-domain simulation show the potential and superiority of the NSPSO-LS algorithm in tuning PSSs over a wide range of loading conditions and large disturbance compared to the classic PSO technique and genetic algorithms.

Keywords: multi-objective optimization, particle swarm optimization, power system stabilizer, low frequency oscillations

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Authors: Gustavo Funes, Eduardo Peters, Jose Delpiano

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It is widely known that photovoltaic technology has been massively distributed over the last decade despite its low-efficiency ratio. Dust deposition reduces this efficiency even more, lowering the energy production and module lifespan. In this work, we developed an artificial vision algorithm based on CIELAB color space to identify dust over panels in an autonomous way. We performed several experiments photographing three different types of panels, 30W, 340W and 410W. Those panels were soiled artificially with uniform and non-uniform distributed dust. The algorithm proposed uses statistical tools to provide a simulation with a 100% soiled panel and then performs a comparison to get the percentage of dirt in the experimental data set. The simulation uses a seed that is obtained by taking a dust sample from the maximum amount of dust from the dataset. The final result is the dirt percentage and the possible distribution of dust over the panel. Dust deposition is a key factor for plant owners to determine cleaning cycles or identify nonuniform depositions that could lead to module failure and hot spots.

Keywords: dust detection, photovoltaic, artificial vision, soiling

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Authors: Nahid Tavakoli, Mohammad H. Yarmohammadian, Ali Samimi

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In earthquake situation, medical response communities such as field and referral hospitals are challenged with injured victims’ identification and tracking. In our project, it was developed a patient tracking platform (PTP) where first responders triage the patients with an electronic tag which report the location and some information of each patient during his/her movement. This platform includes: 1) near field communication (NFC) tags (ISO 14443), 2) smart mobile phones (Android-base version 4.2.2), 3) Base station laptops (Windows), 4) server software, 5) Android software to use by first responders, 5) disaster command software, and 6) system architecture. Our model has been completed through literature review, Delphi technique, focus group, design the platform, and implement in an earthquake exercise. This paper presents consideration for content, function, and technologies that must apply for patient tracking in medical emergencies situations. It is demonstrated the robustness of the patient tracking platform (PTP) in tracking 6 patients in a simulated earthquake situation in the yard of the relief and rescue department of Isfahan’s Red Crescent.

Keywords: test and evaluation, patient tracking platform, earthquake, simulation

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Authors: K. Yahia, A. Ghoggal, A. Titaouine, S. E. Zouzou, F. Benchabane

Abstract:

This paper deals with the problem of stator faults diagnosis in induction motors. Using the discrete wavelet transform (DWT) for the current Park’s vector modulus (CPVM) analysis, the inter-turn short-circuit faults diagnosis can be achieved. This method is based on the decomposition of the CPVM signal, where wavelet approximation and detail coefficients of this signal have been extracted. The energy evaluation of a known bandwidth detail permits to define a fault severity factor (FSF). This method has been tested through the simulation of an induction motor using a mathematical model based on the winding-function approach. Simulation, as well as experimental, results show the effectiveness of the used method.

Keywords: Induction Motors (IMs), Inter-turn Short-Circuits Diagnosis, Discrete Wavelet Transform (DWT), Current Park’s Vector Modulus (CPVM)

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Authors: Katie E. Jennings

Abstract:

The interactions between family dynamics and environmental factors with mental health vulnerability in individuals are well known and are a theme for on-going research and debate. The impact upon mental health issues and forensic issues on family dynamics, experience, and emotional wellbeing cannot be over-Emphasised. For forensic patients with diagnosed mental disorders, these relationships and environments may have also been functionally linked to the development and maintenance of those disorders; with significant adverse childhood experiences being a common feature of many Patient’s histories. Mental health hospitals remove the patient from their home environments and provide treatment outside of these relationships and often outside of the home area. There is, therefore, a major focus on Services ensuring that patients are able to build and maintain relationships with family and friends, requiring services to involve families in Patients' care and treatment wherever possible. There are standards set by Government and clinical bodies that require absolute demonstration of the inclusion of family and friends in all aspects of the care and treatment of forensic patients. For some patients and family members, this push to take on a “role” in care can be unhelpful, extremely stressful, and has constant implications for the potential delicate reparation of relationships. Based on work undertaken for over 20 years in forensic mental health settings, this paper explores the positive psychology approach to a dimensional model to family inclusion in mental health care that learns from family court work and allows for the maintenance of relationships to be at both proximal and Distil levels; to prevent the replication of abuse, decrease the need for falsehoods and assist the recovery of all. The model is based on allowing families to choose to not be involved or be involved in different ways if this is seen to be more helpful. It also allows patients to choose the level of potential involvement that they would find helpful, and for this to be reviewed at a timeframe agreed by all parties, rather than when the next survey is due or the patient has a significant care meeting. This paper is significant as there is a lack of research to support services to use a positive psychology approach to work in this area, the assumption that being asked to be involved must be positive for all seems naïve at best for this patient group. Work relating to the psychology of family can significantly contribute to the development of knowledge in this area. The development of a dimensional model will support choice within families and assist in the development of more honest and open relationships.

Keywords: family dynamics, forensic, mental disorder, positive psychology

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Authors: Di Yao, Gunther Prokop, Kay Buttner

Abstract:

Dynamic parameters, including the center of gravity, mass and inertia moments of vehicle, play an essential role in vehicle simulation, collision test and real-time control of vehicle active systems. To identify the important vehicle dynamic parameters, a systematic parameter identification procedure is studied in this work. In the first step of the procedure, a conceptual parallel manipulator (virtual test rig), which possesses three rotational degrees-of-freedom, is firstly proposed. To realize kinematic characteristics of the conceptual parallel manipulator, the kinematic analysis consists of inverse kinematic and singularity architecture is carried out. Based on the Euler's rotation equations for rigid body dynamics, the dynamic model of parallel manipulator and derivation of measurement matrix for parameter identification are presented subsequently. In order to reduce the sensitivity of parameter identification to measurement noise and other unexpected disturbances, a parameter optimization process of searching for optimal exciting trajectory of parallel manipulator is conducted in the following section. For this purpose, the 321-Euler-angles defined by parameterized finite-Fourier-series are primarily used to describe the general exciting trajectory of parallel manipulator. To minimize the condition number of measurement matrix for achieving better parameter identification accuracy, the unknown coefficients of parameterized finite-Fourier-series are estimated by employing an iterative algorithm based on MATLAB®. Meanwhile, the iterative algorithm will ensure the parallel manipulator still keeps in an achievable working status during the execution of optimal exciting trajectory. It is showed that the proposed procedure and methods in this work can effectively identify the vehicle dynamic parameters and could be an important application of parallel manipulator in the fields of parameter identification and test rig development.

Keywords: parameter identification, parallel manipulator, singularity architecture, dynamic modelling, exciting trajectory

Procedia PDF Downloads 247

Authors: Anderson Rocha-Buelvas, Jaqueline Mena Huertas, Edith Burbano Rosero, Arsenio Hidalgo Troya, Mauricio Casas Cruz

Abstract:

COVID-19 is a disruptive pandemic for the public health and economic system of whole countries, including Colombia. Nariño Department is the southwest of the country and draws attention to being on the border with Ecuador, constantly facing demographic transition affecting infections between countries. In Nariño, the early routine diagnosis of SARS-CoV-2, which can be handled at BSL-2, has affected the transmission dynamics of COVID-19. However, new emerging and re-emerging viruses with biological flexibility classified as a Risk Group 3 agent can take advantage of epidemiological opportunities, generating the need to increase clinical diagnosis, mainly in border regions between countries. The overall objective of this project was to assure the quality of the analytical process in the diagnosis of high biological risk pathogens in Nariño by building a laboratory that includes biosafety level (BSL)-2 and (BSL)-3 containment zones. The delimitation of zones was carried out according to the Verification Tool of the National Health Institute of Colombia and following the standard requirements for the competence of testing and calibration laboratories of the International Organization for Standardization. This is achieved by harmonization of methods and equipment for effective and durable diagnostics of the large-scale spread of highly pathogenic microorganisms, employing negative-pressure containment systems and UV Systems in accordance with a finely controlled electrical system and PCR systems as new diagnostic tools. That increases laboratory capacity. Protection in BSL-3 zones will separate the handling of potentially infectious aerosols within the laboratory from the community and the environment. It will also allow the handling and inactivation of samples with suspected pathogens and the extraction of molecular material from them, allowing research with pathogens with high risks, such as SARS-CoV-2, Influenza, and syncytial virus, and malaria, among others. The diagnosis of these pathogens will be articulated across the spectrum of basic, applied, and translational research that could receive about 60 daily samples. It is expected that this project will be articulated with the health policies of neighboring countries to increase research capacity.

Keywords: medical laboratory science, SARS-CoV-2, public health surveillance, Colombia

Procedia PDF Downloads 67

Authors: Amina Lyria Deghal Cheridi, Abla Chaker, Ahcene Loubar

Abstract:

Relap5 system code is one among powerful tools, which is used in the area of design and safety evaluation. This work aims to simulate the behavior of a radiant steam boiler at the steady-state conditions using Relap5 code system. To perform this study, a detailed Relap5 model is built including all the parts of the steam boiler. The control and regulation systems are also considered. To reproduce the most important parameters and phenomena with an acceptable accuracy and fidelity, a strong qualification work is undertaken concerning the facility nodalization. It consists of making a comparison between the code results and the plant available data in steady-state operation mode. Therefore, the model qualification results at the steady-state are in good agreement with the steam boiler experimental data. The steam boiler Relap5 model has proved satisfactory; and the model was capable of predicting the main thermal-hydraulic steady-state conditions of the steam boiler.

Keywords: industrial steam boiler, model qualification, natural circulation, relap5/mod3.2, steady state simulation

Procedia PDF Downloads 253

Authors: J. A. Ujam, J. L. Chukwuneke, C. H. Achebe, G. O. R. Ikwu

Abstract:

This work investigates the effect of head and bucket splitter angle on the power output of a pelton turbine (water turbine), so as to boost the efficiency of Hydro-electric power generation systems. A simulation program was developed using MatLab to depict the force generated by the bucket as the water jet strikes the existing splitter angle (100 to 150) and predicted (10 to 250) splitter angles. Result shows that in addition to the existing splitter angle, six more angles have been investigated for the two operating conditions to give maximum power. The angles are 250, 60 and 190 for high head and low flow with increased pressure while low head and high flow with decreased pressure are 230, 210 and 30 in order of the maximum generating power. The Turbine power output for simulation was more than that of the experiment. This was as a result of their head conditions and the bucket splitter angle.

Keywords: bucket splitter angle, force, head, modelling, pelton turbine, power output, shaft output

Procedia PDF Downloads 334

Authors: Αlexios Kotsakis, Stefanos Katsavounis, Dimitra Alexiou

Abstract:

Networks can be utilized to represent project planning problems, using nodes for activities and arcs to indicate precedence relationship between them. For fixed activity duration, a simple algorithm calculates the amount of time required to complete a project, followed by the activities that comprise the critical path. Program Evaluation and Review Technique (PERT) generalizes the above model by incorporating uncertainty, allowing activity durations to be random variables, producing nevertheless a relatively crude solution in planning problems. In this paper, based on the findings of the relevant literature, which strongly suggests that a Beta distribution can be employed to model earthmoving activities, we utilize Monte Carlo simulation, to estimate the project completion time distribution and measure the influence of skewness, an element inherent in activities of modern technical projects. We also extract the activity criticality index, with an ultimate goal to produce more accurate planning estimations.

Keywords: beta distribution, PERT, Monte Carlo simulation, skewness, project completion time distribution

Procedia PDF Downloads 130

Authors: Shuba Anastasiia, Kuchmenko Tatiana, Umarkhanov Ruslan

Abstract:

The development of new sensitive coatings for sensors is one of the key directions in the development of sensor technologies. Recently, there has been a trend towards the creation of multicomponent coatings for sensors, which make it possible to increase the sensitivity, and specificity, and improve the performance properties of sensors. When analyzing samples with a complex matrix of biological origin, the inclusion of micelles of bioactive substances (amino and nucleic acids, peptides, proteins) in the composition of the sensor coating can also increase useful analytical information. The purpose of this work is to evaluate the analytical characteristics of composite coatings of piezoelectric quartz sensors based on medium-molecular viscous sorbents with incorporated micellar casein concentrate during the sorption of vapors of volatile organic compounds. The sorption properties of the coatings were studied by piezoelectric quartz microbalance. Macromolecular compounds (dicyclohexyl-18-crown-6, triton X-100, lanolin, micellar casein concentrate) were used as sorbents. Highly volatile organic compounds of various classes (alcohols, acids, aldehydes, esters) and water were selected as test substances. It has been established that composite coatings of sensors with the inclusion of micellar casein are more stable and selective to vapors of highly volatile compounds than to water vapors. The method and technique of forming a composite coating using molecular viscous sorbents do not affect the kinetic features of VOC sorption. When casein micelles are used, the features of kinetic sorption depend on the matrix of the coating.

Keywords: piezoquartz sensor, viscous sorbents, micellar casein, coating, volatile compounds

Procedia PDF Downloads 83