Search results for: electric energy generation system
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 25229

Search results for: electric energy generation system

5849 In-silico DFT Study, Molecular Docking, ADMET Predictions, and DMS of Isoxazolidine and Isoxazoline Analogs with Anticancer Properties

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

Abstract:

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

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

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5848 The Use of Artificial Intelligence to Harmonization in the Lawmaking Process

Authors: Supriyadi, Andi Intan Purnamasari, Aminuddin Kasim, Sulbadana, Mohammad Reza

Abstract:

The development of the Industrial Revolution Era 4.0 brought a significant influence in the administration of countries in all parts of the world, including Indonesia, not only in the administration and economic sectors but the ways and methods of forming laws should also be adjusted. Until now, the process of making laws carried out by the Parliament with the Government still uses the classical method. The law-making process still uses manual methods, such as typing harmonization of regulations, so that it is not uncommon for errors to occur, such as writing errors, copying articles and so on, things that require a high level of accuracy and relying on inventory and harmonization carried out manually by humans. However, this method often creates several problems due to errors and inaccuracies on the part of officers who harmonize laws after discussion and approval; this has a very serious impact on the system of law formation in Indonesia. The use of artificial intelligence in the process of forming laws seems to be justified and becomes the answer in order to minimize the disharmony of various laws and regulations. This research is normative research using the Legislative Approach and the Conceptual Approach. This research focuses on the question of how to use Artificial Intelligence for Harmonization in the Lawmaking Process.

Keywords: artificial intelligence, harmonization, laws, intelligence

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5847 The Impact of COVID-19 Pandemic on the Issue and Ideological Congruence of Trump and Bolsonaro Administrations

Authors: Flavio Contrera, Paulo Cesar Gregorio

Abstract:

Recent political developments and government control actions in the face of the COVID-19 pandemic draw attention to the contrast between the duties of government and the demands of democratic representation. Elected by mobilizing far-right issues, Trump and Bolsonaro moved away from the WHO guidelines but had to accommodate demands on the health and on the social protection system on the one hand and demands from the economic sector on the other. This study used the MARPOR Project method to assess the impact of the COVID-19 pandemic on the issue and ideological congruence between the electoral and governmental arena in both the Trump and Bolsonaro Administrations. Findings reveal issue congruence between arenas in "National Way of Life: Positive", "Law and Order," and "Technology and Infrastructure" for Donald Trump, and "Welfare State Expansion" for Bolsonaro. Ideological estimation results show that Trump and Bolsonaro positioned to the right in their presidential elections, initially moved to the center-right. However, welfare policies actions at high frequency during the COVID-19 pandemic moved the ideological estimations of both governments to the center-left, despite their denial rhetoric.

Keywords: congruence, COVID-19, Donald Trump, Jair Bolsonaro

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5846 An Image Segmentation Algorithm for Gradient Target Based on Mean-Shift and Dictionary Learning

Authors: Yanwen Li, Shuguo Xie

Abstract:

In electromagnetic imaging, because of the diffraction limited system, the pixel values could change slowly near the edge of the image targets and they also change with the location in the same target. Using traditional digital image segmentation methods to segment electromagnetic gradient images could result in lots of errors because of this change in pixel values. To address this issue, this paper proposes a novel image segmentation and extraction algorithm based on Mean-Shift and dictionary learning. Firstly, the preliminary segmentation results from adaptive bandwidth Mean-Shift algorithm are expanded, merged and extracted. Then the overlap rate of the extracted image block is detected before determining a segmentation region with a single complete target. Last, the gradient edge of the extracted targets is recovered and reconstructed by using a dictionary-learning algorithm, while the final segmentation results are obtained which are very close to the gradient target in the original image. Both the experimental results and the simulated results show that the segmentation results are very accurate. The Dice coefficients are improved by 70% to 80% compared with the Mean-Shift only method.

Keywords: gradient image, segmentation and extract, mean-shift algorithm, dictionary iearning

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5845 Switched System Diagnosis Based on Intelligent State Filtering with Unknown Models

Authors: Nada Slimane, Foued Theljani, Faouzi Bouani

Abstract:

The paper addresses the problem of fault diagnosis for systems operating in several modes (normal or faulty) based on states assessment. We use, for this purpose, a methodology consisting of three main processes: 1) sequential data clustering, 2) linear model regression and 3) state filtering. Typically, Kalman Filter (KF) is an algorithm that provides estimation of unknown states using a sequence of I/O measurements. Inevitably, although it is an efficient technique for state estimation, it presents two main weaknesses. First, it merely predicts states without being able to isolate/classify them according to their different operating modes, whether normal or faulty modes. To deal with this dilemma, the KF is endowed with an extra clustering step based fully on sequential version of the k-means algorithm. Second, to provide state estimation, KF requires state space models, which can be unknown. A linear regularized regression is used to identify the required models. To prove its effectiveness, the proposed approach is assessed on a simulated benchmark.

Keywords: clustering, diagnosis, Kalman Filtering, k-means, regularized regression

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5844 Multiband Fractal Patch Antenna for Small Spacecraft of Earth Remote Sensing

Authors: Beibit Karibayev, Akmaral Imanbayeva, Timur Namazbayev

Abstract:

Currently, the small spacecraft (SSC) industry is experiencing a big boom in popularity. This is primarily due to ease of use, low cost and mobility. In addition, these programs can be implemented not only at the state level but also at the level of companies, universities and other organizations. For remote sensing of the Earth (ERS), small spacecraft with an orientation system is used. It is important to take into account here that a remote sensing device, for example, a camera for photographing the Earth's surface, must be directed at the Earth's surface. But this, at first glance, the limitation can be turned into an advantage using a patch antenna. This work proposed to use a patch antenna based on a unidirectional fractal in the SSC. The CST Microwave Studio software package was used for simulation and research. Copper (ε = 1.0) was chosen as the emitting element and reflector. The height of the substrate was 1.6 mm, the type of substrate material was FR-4 (ε = 4.3). The simulation was performed in the frequency range of 0 – 6 GHz. As a result of the research, a patch antenna based on fractal geometry was developed for ERS nanosatellites. The capabilities of these antennas are modeled and investigated. A method for calculating and modeling fractal geometry for patch antennas has been developed.

Keywords: antenna, earth remote sensing, fractal, small spacecraft

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5843 Parameterized Lyapunov Function Based Robust Diagonal Dominance Pre-Compensator Design for Linear Parameter Varying Model

Authors: Xiaobao Han, Huacong Li, Jia Li

Abstract:

For dynamic decoupling of linear parameter varying system, a robust dominance pre-compensator design method is given. The parameterized pre-compensator design problem is converted into optimal problem constrained with parameterized linear matrix inequalities (PLMI); To solve this problem, firstly, this optimization problem is equivalently transformed into a new form with elimination of coupling relationship between parameterized Lyapunov function (PLF) and pre-compensator. Then the problem was reduced to a normal convex optimization problem with normal linear matrix inequalities (LMI) constraints on a newly constructed convex polyhedron. Moreover, a parameter scheduling pre-compensator was achieved, which satisfies robust performance and decoupling performances. Finally, the feasibility and validity of the robust diagonal dominance pre-compensator design method are verified by the numerical simulation of a turbofan engine PLPV model.

Keywords: linear parameter varying (LPV), parameterized Lyapunov function (PLF), linear matrix inequalities (LMI), diagonal dominance pre-compensator

Procedia PDF Downloads 386
5842 Data Integrity between Ministry of Education and Private Schools in the United Arab Emirates

Authors: Rima Shishakly, Mervyn Misajon

Abstract:

Education is similar to other businesses and industries. Achieving data integrity is essential in order to attain a significant supporting for all the stakeholders in the educational sector. Efficient data collect, flow, processing, storing and retrieving are vital in order to deliver successful solutions to the different stakeholders. Ministry of Education (MOE) in United Arab Emirates (UAE) has adopted ‘Education 2020’ a series of five-year plans designed to introduce advanced education management information systems. As part of this program, in 2010 MOE implemented Student Information Systems (SIS) to manage and monitor the students’ data and information flow between MOE and international private schools in UAE. This paper is going to discuss data integrity concerns between MOE, and private schools. The paper will clarify the data integrity issues and will indicate the challenges that face private schools in UAE.

Keywords: education management information systems (EMIS), student information system (SIS), United Arab Emirates (UAE), ministry of education (MOE), (KHDA) the knowledge and human development authority, Abu Dhabi educational counsel (ADEC)

Procedia PDF Downloads 207
5841 Assessment of Dose: Area Product of Common Radiographic Examinations in Selected Southern Nigerian Hospitals

Authors: Lateef Bamidele

Abstract:

Over the years, radiographic examinations are the most used diagnostic tools in the Nigerian health care system, but most diagnostic examinations carried out do not have records of patient doses. Lack of adequate information on patient doses has been a major hindrance in quantifying the radiological risk associated with radiographic examinations. This study aimed at estimating dose–area product (DAP) of patient examined in X-Ray units in selected hospitals in Southern Nigeria. The standard projections selected are chest posterior-anterior (PA), abdomen anterior-posterior (AP), pelvis AP, pelvis lateral (LAT), skull AP/PA, skull LAT, lumbar spine AP, lumbar spine, LAT. Measurement of entrance surface dose (ESD) was carried out using thermoluminescent dosimeter (TLD). Measured ESDs were converted into DAP using the beam area of patients. The results show that the mean DAP ranged from 0.17 to 18.35 Gycm². The results obtained in this study when compared with those of NRPB-HPE were found to be higher. These are an indication of non optimization of operational conditions.

Keywords: dose–area product, radiographic examinations, patient doses, optimization

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5840 Observations of Conformity in the Health Professions

Authors: Tanya Beran, Michelle Drefs, Ghazwan Altabbaa, Nouf Al Harbi, Noof Al Baz, Elizabeth Oddone Paolucci

Abstract:

Although research shows that interprofessional practice has desirable effects on patient care, its implementation can present challenges to its team members. In particular, they may feel pressured to agree with or conform to other members who share information that is contrary to their own understanding. Obtaining evidence of this phenomenon is challenging, as team members may underreport their conformity behaviors due to reasons such as social desirability. In this paper, a series of studies are reviewed in which several approaches to assessing conformity in the health care professions are tested. Simulations, questionnaires, and behavior checklists were developed to measure conformity behaviors. Insights from these studies show that a significant proportion of people conform either in the presence or absence of others, express a variety of verbal and nonverbal behaviors when considering whether to conform to others, may shift between conforming and moments later not conforming (and vice versa), and may not accurately report whether they conformed. A new method of measuring conformity using the implicit bias test is also discussed. People at all levels in the healthcare system are encouraged to develop both formal and informal.

Keywords: conformity, decision-making, inter-professional teams, simulation

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5839 Resilience Perspective on Response Strategies for Super-Standard Rain and Flood Disasters: A Case Study of the “Zhengzhou 7.20 Heavy Rain” Event

Authors: Luojie Tang

Abstract:

The article takes the "7.20 Heavy Rainstorm in Zhengzhou" as a starting point, collects relevant disaster data, reproduces the entire process of the disaster, and identifies the main problems exposed by the city in responding to super-standard rain and flood disasters. Based on the review of resilience theory, the article proposes a shift in thinking about the response to super-standard rain and flood disasters from the perspective of resilience, clarifies the differences in the emphasis on resilience at different stages of disasters, and preliminarily constructs a response system for super-standard rain and flood disasters based on the guidance of resilience theory. Finally, combined with the highlighted problems in the 7.20 Heavy Rainstorm in Zhengzhou, the article proposes targeted response strategies from three perspectives: institutional management, technological support, and infrastructure, under the perspective of resilience.

Keywords: resilient city, exceedance-based stormwater management, disaster risk reduction, megalopolis

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5838 Investigation of Compliance of the Prevailing Import Murabah'a to Sharia

Authors: Aqeel Akhtar

Abstract:

One of prevailing modes of finance in emerging Islamic banking system is Murabah’a; a financial transaction in which cost and profit both must be recognized by buyer. Otherwise the transaction would become invalid. In this mainstream, import Murabah’a transaction is divergent in such a way that the cost is not recognized and identified due to execution of import transaction in foreign currency i.e. US Dollar and the next transaction of Murabaha’a with the client is executed in local currency. Since this transaction is executed in dual currency i.e. bank pays supplier in foreign currency and executes Murabah’a with its client in local currency and it is not allowed in according to Islamic Injunctions as mentioned in hadith narrated by Hazrat Ibn-e-Umar (May Allah be pleased with them) used to sell his camels with Dirhams and take dinars instead and vice versa. Upon revealing before the Prophet (SAW), he was advised that it must not be contingent in the agreement and the ready rate would be applied and possession of one of the consideration is compulsory. The solution in this regard is that the import Murabah’a transaction should be in single currency, however, other currency can be paid in payment at the time of payment in a very indispensable situation provided that ready rate would be applied. Moreover, some of other solutions have also been given in this regard.

Keywords: shariah compliance, import murabaha, islamic banking, product development

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5837 Polymer Flooding: Chemical Enhanced Oil Recovery Technique

Authors: Abhinav Bajpayee, Shubham Damke, Rupal Ranjan, Neha Bharti

Abstract:

Polymer flooding is a dramatic improvement in water flooding and quickly becoming one of the EOR technologies. Used for improving oil recovery. With the increasing energy demand and depleting oil reserves EOR techniques are becoming increasingly significant .Since most oil fields have already begun water flooding, chemical EOR technique can be implemented by using fewer resources than any other EOR technique. Polymer helps in increasing the viscosity of injected water thus reducing water mobility and hence achieves a more stable displacement .Polymer flooding helps in increasing the injection viscosity as has been revealed through field experience. While the injection of a polymer solution improves reservoir conformance the beneficial effect ceases as soon as one attempts to push the polymer solution with water. It is most commonly applied technique because of its higher success rate. In polymer flooding, a water-soluble polymer such as Polyacrylamide is added to the water in the water flood. This increases the viscosity of the water to that of a gel making the oil and water greatly improving the efficiency of the water flood. It also improves the vertical and areal sweep efficiency as a consequence of improving the water/oil mobility ratio. Polymer flooding plays an important role in oil exploitation, but around 60 million ton of wastewater is produced per day with oil extraction together. Therefore the treatment and reuse of wastewater becomes significant which can be carried out by electro dialysis technology. This treatment technology can not only decrease environmental pollution, but also achieve closed-circuit of polymer flooding wastewater during crude oil extraction. There are three potential ways in which a polymer flood can make the oil recovery process more efficient: (1) through the effects of polymers on fractional flow, (2) by decreasing the water/oil mobility ratio, and (3) by diverting injected water from zones that have been swept. It has also been suggested that the viscoelastic behavior of polymers can improve displacement efficiency Polymer flooding may also have an economic impact because less water is injected and produced compared with water flooding. In future we need to focus on developing polymers that can be used in reservoirs of high temperature and high salinity, applying polymer flooding in different reservoir conditions and also combine polymer with other processes (e.g., surfactant/ polymer flooding).

Keywords: fractional flow, polymer, viscosity, water/oil mobility ratio

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5836 A Web-Based Self-Learning Grammar for Spoken Language Understanding

Authors: S. Biondi, V. Catania, R. Di Natale, A. R. Intilisano, D. Panno

Abstract:

One of the major goals of Spoken Dialog Systems (SDS) is to understand what the user utters. In the SDS domain, the Spoken Language Understanding (SLU) Module classifies user utterances by means of a pre-definite conceptual knowledge. The SLU module is able to recognize only the meaning previously included in its knowledge base. Due the vastity of that knowledge, the information storing is a very expensive process. Updating and managing the knowledge base are time-consuming and error-prone processes because of the rapidly growing number of entities like proper nouns and domain-specific nouns. This paper proposes a solution to the problem of Name Entity Recognition (NER) applied to a SDS domain. The proposed solution attempts to automatically recognize the meaning associated with an utterance by using the PANKOW (Pattern based Annotation through Knowledge On the Web) method at runtime. The method being proposed extracts information from the Web to increase the SLU knowledge module and reduces the development effort. In particular, the Google Search Engine is used to extract information from the Facebook social network.

Keywords: spoken dialog system, spoken language understanding, web semantic, name entity recognition

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5835 Discrete Group Search Optimizer for the Travelling Salesman Problem

Authors: Raed Alnajjar, Mohd Zakree, Ahmad Nazri

Abstract:

In this study, we apply Discrete Group Search Optimizer (DGSO) for solving Traveling Salesman Problem (TSP). The DGSO is a nature inspired optimization algorithm that imitates the animal behavior, especially animal searching behavior. The proposed DGSO uses a vector representation and some discrete operators, such as destruction, construction, differential evolution, swap and insert. The TSP is a well-known hard combinatorial optimization problem, which seeks to find the shortest path among numbers of cities. The performance of the proposed DGSO is evaluated and tested on benchmark instances which listed in LIBTSP dataset. The experimental results show that the performance of the proposed DGSO is comparable with the other methods in the state of the art for some instances. The results show that DGSO outperform Ant Colony System (ACS) in some instances whilst outperform other metaheuristic in most instances. In addition to that, the new results obtained a number of optimal solutions and some best known results. DGSO was able to obtain feasible and good quality solution across all dataset.

Keywords: discrete group search optimizer (DGSO); Travelling salesman problem (TSP); Variable neighborhood search(VNS)

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5834 Real-Time Sensor Fusion for Mobile Robot Localization in an Oil and Gas Refinery

Authors: Adewole A. Ayoade, Marshall R. Sweatt, John P. H. Steele, Qi Han, Khaled Al-Wahedi, Hamad Karki, William A. Yearsley

Abstract:

Understanding the behavioral characteristics of sensors is a crucial step in fusing data from several sensors of different types. This paper introduces a practical, real-time approach to integrate heterogeneous sensor data to achieve higher accuracy than would be possible from any one individual sensor in localizing a mobile robot. We use this approach in both indoor and outdoor environments and it is especially appropriate for those environments like oil and gas refineries due to their sparse and featureless nature. We have studied the individual contribution of each sensor data to the overall combined accuracy achieved from the fusion process. A Sequential Update Extended Kalman Filter(EKF) using validation gates was used to integrate GPS data, Compass data, WiFi data, Inertial Measurement Unit(IMU) data, Vehicle Velocity, and pose estimates from Fiducial marker system. Results show that the approach can enable a mobile robot to navigate autonomously in any environment using a priori information.

Keywords: inspection mobile robot, navigation, sensor fusion, sequential update extended Kalman filter

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5833 Autonomous Flight Performance Improvement of Load-Carrying Unmanned Aerial Vehicles by Active Morphing

Authors: Tugrul Oktay, Mehmet Konar, Mohamed Abdallah Mohamed, Murat Aydin, Firat Sal, Murat Onay, Mustafa Soylak

Abstract:

In this paper, it is aimed to improve autonomous flight performance of a load-carrying (payload: 3 kg and total: 6kg) unmanned aerial vehicle (UAV) through active wing and horizontal tail active morphing and also integrated autopilot system parameters (i.e. P, I, D gains) and UAV parameters (i.e. extension ratios of wing and horizontal tail during flight) design. For this purpose, a loadcarrying UAV (i.e. ZANKA-II) is manufactured in Erciyes University, College of Aviation, Model Aircraft Laboratory is benefited. Optimum values of UAV parameters and autopilot parameters are obtained using a stochastic optimization method. Using this approach autonomous flight performance of UAV is substantially improved and also in some adverse weather conditions an opportunity for safe flight is satisfied. Active morphing and integrated design approach gives confidence, high performance and easy-utility request of UAV users.

Keywords: unmanned aerial vehicles, morphing, autopilots, autonomous performance

Procedia PDF Downloads 653
5832 Evaluation of Urban Transportation Systems: Comparing and Selecting the Most Efficient Transportation Solutions

Authors: E. Azizi Asiyabar

Abstract:

The phenomenon of migration to larger cities has brought about a range of consequences, including increased travel demand and the necessity for smooth traffic flow to expedite transportation. Regrettably, insufficient urban transportation infrastructure has given rise to various issues, including air pollution, heightened fuel consumption, and wasted time. To address traffic-related problems and the economic, social, and environmental challenges that ensue, a well-equipped, efficient, fast, cost-effective, and high-capacity transportation system is imperative, with a focus on reliability. This study undertakes a comprehensive examination of rail transportation systems and subsequently compares their advantages and limitations. The findings of this investigation reveal that hybrid monorails exhibit lower maintenance requirements and associated costs when compared to other types of monorails, standard trains, and urban light rail systems. Given their favorable attributes in terms of pollution reduction, increased transportation speed, and enhanced quality of service, hybrid monorails emerge as a highly recommended and suitable option.

Keywords: comparing, most efficient, selecting, urban transportation

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5831 Sub-Saharan Africa: Role of Global Fashion System in Turbo-Charging Growth of Apparel Industry

Authors: Rajkishore Nayak, Tarun Panwar, Majo George

Abstract:

The study focuses on investigating the factors that influence the growth of fashion and textile manufacturing in the Sub-Saharan Africa (SSA) countries. This paper endeavours to identify, analyse and evaluate the critical factors associated with the growth of fashion and textile manufacturing in SSA countries. This research has done a Strength, Weakness, Opportunity, and Threat (SWOT) analysis based on the available literature and the knowledge of authors in garment manufacturing and export. It was found that the SSA countries have shown little growth in fashion and textile manufacturing and export from the starting of the year 2000. Unlike the developing countries such as Vietnam and Bangladesh, the total export to the US, the EU and other parts of the world has declined. On the other hand, the total supply of fashion and textiles to the domestic market has been in rise. However, the local communities still need to rely on other countries to meet their demand. Availability of cheaper imported clothes from other countries such as Bangladesh, China and Vietnam have made it difficult for the local manufacturers to produce at a cheaper price.

Keywords: Sub-Saharan Africa, developing countries, apparel industry, fashion and textile, sustainable fashion

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5830 Similar Correlation of Meat and Sugar to Global Obesity Prevalence

Authors: Wenpeng You, Maciej Henneberg

Abstract:

Background: Sugar consumption has been overwhelmingly advocated as a major dietary offender to obesity prevalence. Meat intake has been hypothesized as an obesity contributor in previous publications, but a moderate amount of meat to be included in our daily diet still has been suggested in many dietary guidelines. Comparable sugar and meat exposure data were obtained to assess the difference in relationships between the two major food groups and obesity prevalence at population level. Methods: Population level estimates of obesity and overweight rates, per capita per day exposure of major food groups (meat, sugar, starch crops, fibers, fats and fruits) and total calories, per capita per year GDP, urbanization and physical inactivity prevalence rate were extracted and matched for statistical analysis. Correlation coefficient (Pearson and partial) comparisons with Fisher’s r-to-z transformation and β range (β ± 2 SE) and overlapping in multiple linear regression (Enter and Stepwise) were used to examine potential differences in the relationships between obesity prevalence and sugar exposure and meat exposure respectively. Results: Pearson and partial correlations (controlled for total calories, physical inactivity prevalence, GDP and urbanization) analyses revealed that sugar and meat exposures correlated to obesity and overweight prevalence significantly. Fisher's r-to-z transformation did not show statistically significant difference in Pearson correlation coefficients (z=-0.53, p=0.5961) or partial correlation coefficients (z=-0.04, p=0.9681) between obesity prevalence and both sugar exposure and meat exposure. Both Enter and Stepwise models in multiple linear regression analysis showed that sugar and meat exposure were most significant predictors of obesity prevalence. Great β range overlapping in the Enter (0.289-0.573) and Stepwise (0.294-0.582) models indicated statistically sugar and meat exposure correlated to obesity without significant difference. Conclusion: Worldwide sugar and meat exposure correlated to obesity prevalence at the same extent. Like sugar, minimal meat exposure should also be suggested in the dietary guidelines.

Keywords: meat, sugar, obesity, energy surplus, meat protein, fats, insulin resistance

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5829 Mutation of Galp Improved Fermentation of Mixed Sugars to Succinate Using Engineered Escherichia coli As1600a

Authors: Apichai Sawisit, Sirima Suvarnakuta Jantama, Sunthorn Kanchanatawee, Lonnie O. Ingram, Kaemwich Jantama

Abstract:

Escherichia coli KJ122 was engineered to produce succinate from glucose using the wild type GalP for glucose uptake instead of the native phosphotransferase system (ptsI mutation). This strain ferments 10% (w/v) xylose poorly. Mutants were selected by serial transfers in AM1 mineral salts medium with 10% (w/v) xylose. Evolved mutants exhibited a similar improvement, co-fermentation of an equal mixture of xylose and glucose. One of these, AS1600a, produced 84.26±1.37 g/L succinate, equivalent to that produced by the parent (KJ122) strain from 10% glucose (85.46±1.78 g/L). AS1600a was sequenced and found to contain a mutation in galactose permease (GalP, G236D). Expressing the galP* mutation gene in KJ122ΔgalP resembled the xylose utilization phenotype of the mutant AS1600a. The strain AS1600a and KJ122ΔgalP (pLOI5746; galP*) also co-fermented a mixture of glucose, xylose, arabinose, and galactose in sugarcane bagasse hydrolysate for succinate production.

Keywords: xylose, furfural, succinat, sugarcane bagasse, E. coli

Procedia PDF Downloads 425
5828 Analysis of Patient No-Shows According to Health Conditions

Authors: Sangbok Lee

Abstract:

There has been much effort on process improvement for outpatient clinics to provide quality and acute care to patients. One of the efforts is no-show analysis or prediction. This work analyzes patient no-shows along with patient health conditions. The health conditions refer to clinical symptoms that each patient has, out of the followings; hyperlipidemia, diabetes, metastatic solid tumor, dementia, chronic obstructive pulmonary disease, hypertension, coronary artery disease, myocardial infraction, congestive heart failure, atrial fibrillation, stroke, drug dependence abuse, schizophrenia, major depression, and pain. A dataset from a regional hospital is used to find the relationship between the number of the symptoms and no-show probabilities. Additional analysis reveals how each symptom or combination of symptoms affects no-shows. In the above analyses, cross-classification of patients by age and gender is carried out. The findings from the analysis will be used to take extra care to patients with particular health conditions. They will be forced to visit clinics by being informed about their health conditions and possible consequences more clearly. Moreover, this work will be used in the preparation of making institutional guidelines for patient reminder systems.

Keywords: healthcare system, no show analysis, process improvment, statistical data analysis

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5827 Modification of Polyolefin Membrane Using Supercritical Carbon Dioxide for Redox Flow Batteries

Authors: Vadim V. Zefirov, Victor E. Sizov, Marina A. Pigaleva, Igor V. Elmanovich, Mikhail S. Kondratenko, Marat O. Gallyamov

Abstract:

This work presents a novel method for treating porous hydrophobic polyolefin membranes using supercritical carbon dioxide that allows usage of the modified membrane in redox flow batteries with an aqueous electrolyte. Polyolefin membranes are well known and widely used, however, they cannot be used as separators in redox flow batteries with an aqueous electrolyte since they have insufficient wettability, and therefore do not provide sufficient proton conductivity. The main aim of the presented work was the development of hydrophilic composites based on cheap membranes and precursors. Supercritical fluid was used as a medium for the deposition of the hydrophilic phase on the hydrophobic surface of the membrane. Due to the absence of negative capillary effects in a supercritical medium, a homogeneous composite is obtained as a result of synthesis. The in-situ synthesized silicon oxide nanoparticles and the chitosan polymer layer act as the hydrophilic phase and not only increase the affinity of the membrane towards the electrolyte, but also reduce the pore size of the polymer matrix, which positively affects the ion selectivity of the membrane. The composite material obtained as a result of synthesis has enhanced hydrophilic properties and is capable of providing proton conductivity in redox flow batteries. The morphology of the obtained composites was characterized by electron microscopy. To analyze the phase composition, infrared spectroscopy was used. The hydrophilic properties were studied by water contact angle measurements. In addition, the proton conductivity and ion selectivity of the obtained samples were studied, and tests in real redox flow batteries were performed. As a result, modified membrane was characterised in detail and moreover it was shown that modified cheap polyolefin membranes have pronounced proton conductivity and high ion selectivity, so their performance in a real redox flow battery approaches expensive commercial analogues, reaching 70% of energy efficiency.

Keywords: carbon dioxide, chitosan, polymer membrane, redox flow batteries, silica nanoparticles, supercritical fluid

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5826 Spray Characteristics of a Urea Injector Chamber to Improve NOx Conversion Efficiency for Diesel Engines Fueled with Biodiesels

Authors: Kazem Bashirnezhad, Seyed Ahmad Kebriyaee, saeed hoseyngholizadeh moghadam

Abstract:

The urea–SCR catalyst system has the advantages of high NOx conversion efficiency and a wide range of operating conditions. The key factors for successful implementation of urea–SCR technology is good mixing of urea (ammonia) and gas to reduce ammonia slip. Urea mixer components are required to facilitate evaporation and mixing, because it is difficult to evaporate urea in the liquid state; the injection parameters are the most critical factors affecting mixer performance. In this study, The effect of urea injection on NOx emissions in a six-cylinder, four-stroke internal combustion engine fueled with B80 biodiesel has been experimentally investigated. The results reveal that urea injection leads to a reduction of NOx emissions of B80 biodiesel fuel. Moreover, the influence of injection parameters on NOx reductions has been studied. The findings show that by increasing the injection temperature, more reduction in NOx emissions has been occurred. Also, urea mass flow rate increment leads to more NOx reduction. The same result has been obtained by an increase in spray angle.

Keywords: urea, NOx emissions, diesel engines, biodiesels

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5825 Time-Series Analysis of Port State Control Inspections for Tankers

Authors: Chien-Chung Yuan, Cunqiang Cai, Wu-Hsun Chung, Shu-Te Sung

Abstract:

A tanker is a critical vessel used to transport or store liquids or gases in bulk in maritime shipping. However, it is more dangerous than other types of vessels. Port State Control (PSC) inspection is an important measure to ensure maritime safety when such vessels traveling between ports. However, the current inspection system lacks a useful tool to observe the inspections for tankers and to identify non-random instances in PSC inspections. This study collects the inspection records in Taiwan’s ports from 2015 to 2018 and utilizes run charts to map the PSC inspections for tankers in terms of deficiencies. Based on these time-series charts, several patterns of deficiencies are identified. The results demonstrate that run charts are a useful tool to observe how the PSC inspections for tankers are performed. Also, the charts can help port administrations to identify abnormal phenomena for further investigation. Furthermore, with valuable information from the analysis, port administrations can take proactive improvement measures to ensure the safety of tanker shipping.

Keywords: port state control, tanker, run chart, deficiency

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5824 Analysing Causal Effect of London Cycle Superhighways on Traffic Congestion

Authors: Prajamitra Bhuyan

Abstract:

Transport operators have a range of intervention options available to improve or enhance their networks. But often such interventions are made in the absence of sound evidence on what outcomes may result. Cycling superhighways were promoted as a sustainable and healthy travel mode which aims to cut traffic congestion. The estimation of the impacts of the cycle superhighways on congestion is complicated due to the non-random assignment of such intervention over the transport network. In this paper, we analyse the causal effect of cycle superhighways utilising pre-innervation and post-intervention information on traffic and road characteristics along with socio-economic factors. We propose a modeling framework based on the propensity score and outcome regression model. The method is also extended to doubly robust set-up. Simulation results show the superiority of the performance of the proposed method over existing competitors. The method is applied to analyse a real dataset on the London transport network, and the result would help effective decision making to improve network performance.

Keywords: average treatment effect, confounder, difference-in-difference, intelligent transportation system, potential outcome

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5823 Physics-Informed Neural Network for Predicting Strain Demand in Inelastic Pipes under Ground Movement with Geometric and Soil Resistance Nonlinearities

Authors: Pouya Taraghi, Yong Li, Nader Yoosef-Ghodsi, Muntaseer Kainat, Samer Adeeb

Abstract:

Buried pipelines play a crucial role in the transportation of energy products such as oil, gas, and various chemical fluids, ensuring their efficient and safe distribution. However, these pipelines are often susceptible to ground movements caused by geohazards like landslides, fault movements, lateral spreading, and more. Such ground movements can lead to strain-induced failures in pipes, resulting in leaks or explosions, leading to fires, financial losses, environmental contamination, and even loss of human life. Therefore, it is essential to study how buried pipelines respond when traversing geohazard-prone areas to assess the potential impact of ground movement on pipeline design. As such, this study introduces an approach called the Physics-Informed Neural Network (PINN) to predict the strain demand in inelastic pipes subjected to permanent ground displacement (PGD). This method uses a deep learning framework that does not require training data and makes it feasible to consider more realistic assumptions regarding existing nonlinearities. It leverages the underlying physics described by differential equations to approximate the solution. The study analyzes various scenarios involving different geohazard types, PGD values, and crossing angles, comparing the predictions with results obtained from finite element methods. The findings demonstrate a good agreement between the results of the proposed method and the finite element method, highlighting its potential as a simulation-free, data-free, and meshless alternative. This study paves the way for further advancements, such as the simulation-free reliability assessment of pipes subjected to PGD, as part of ongoing research that leverages the proposed method.

Keywords: strain demand, inelastic pipe, permanent ground displacement, machine learning, physics-informed neural network

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5822 Multimodal Convolutional Neural Network for Musical Instrument Recognition

Authors: Yagya Raj Pandeya, Joonwhoan Lee

Abstract:

The dynamic behavior of music and video makes it difficult to evaluate musical instrument playing in a video by computer system. Any television or film video clip with music information are rich sources for analyzing musical instruments using modern machine learning technologies. In this research, we integrate the audio and video information sources using convolutional neural network (CNN) and pass network learned features through recurrent neural network (RNN) to preserve the dynamic behaviors of audio and video. We use different pre-trained CNN for music and video feature extraction and then fine tune each model. The music network use 2D convolutional network and video network use 3D convolution (C3D). Finally, we concatenate each music and video feature by preserving the time varying features. The long short term memory (LSTM) network is used for long-term dynamic feature characterization and then use late fusion with generalized mean. The proposed network performs better performance to recognize the musical instrument using audio-video multimodal neural network.

Keywords: multimodal, 3D convolution, music-video feature extraction, generalized mean

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5821 Cell-free Bioconversion of n-Octane to n-Octanol via a Heterogeneous and Bio-Catalytic Approach

Authors: Shanna Swart, Caryn Fenner, Athanasios Kotsiopoulos, Susan Harrison

Abstract:

Linear alkanes are produced as by-products from the increasing use of gas-to-liquid fuel technologies for synthetic fuel production and offer great potential for value addition. Their current use as low-value fuels and solvents do not maximize this potential. Therefore, attention has been drawn towards direct activation of these aliphatic alkanes to more useful products such as alcohols, aldehydes, carboxylic acids and derivatives. Cytochrome P450 monooxygenases (P450s) can be used for activation of these aliphatic alkanes using whole-cells or cell-free systems. Some limitations of whole-cell systems include reduced mass transfer, stability and possible side reactions. Since the P450 systems are little studied as cell-free systems, they form the focus of this study. Challenges of a cell-free system include co-factor regeneration, substrate availability and enzyme stability. Enzyme immobilization offers a positive outlook on this dilemma, as it may enhance stability of the enzyme. In the present study, 2 different P450s (CYP153A6 and CYP102A1) as well as the relevant accessory enzymes required for electron transfer (ferredoxin and ferredoxin reductase) and co-factor regeneration (glucose dehydrogenase) have been expressed in E. coli and purified by metal affinity chromatography. Glucose dehydrogenase (GDH), was used as a model enzyme to assess the potential of various enzyme immobilization strategies including; surface attachment on MagReSyn® microspheres with various functionalities and on electrospun nanofibers, using self-assembly based methods forming Cross Linked Enzymes (CLE), Cross Linked Enzyme Aggregates (CLEAs) and spherezymes as well as in a sol gel. The nanofibers were synthesized by electrospinning, which required the building of an electrospinning machine. The nanofiber morphology has been analyzed by SEM and binding will be further verified by FT-IR. Covalent attachment based methods showed limitations where only ferredoxin reductase and GDH retained activity after immobilization which were largely attributed to insufficient electron transfer and inactivation caused by the crosslinkers (60% and 90% relative activity loss for the free enzyme when using 0.5% glutaraldehyde and glutaraldehyde/ethylenediamine (1:1 v/v), respectively). So far, initial experiments with GDH have shown the most potential when immobilized via their His-tag onto the surface of MagReSyn® microspheres functionalized with Ni-NTA. It was found that Crude GDH could be simultaneously purified and immobilized with sufficient activity retention. Immobilized pure and crude GDH could be recycled 9 and 10 times, respectively, with approximately 10% activity remaining. The immobilized GDH was also more stable than the free enzyme after storage for 14 days at 4˚C. This immobilization strategy will also be applied to the P450s and optimized with regards to enzyme loading and immobilization time, as well as characterized and compared with the free enzymes. It is anticipated that the proposed immobilization set-up will offer enhanced enzyme stability (as well as reusability and easy recovery), minimal mass transfer limitation, with continuous co-factor regeneration and minimal enzyme leaching. All of which provide a positive outlook on this robust multi-enzyme system for efficient activation of linear alkanes as well as the potential for immobilization of various multiple enzymes, including multimeric enzymes for different bio-catalytic applications beyond alkane activation.

Keywords: alkane activation, cytochrome P450 monooxygenase, enzyme catalysis, enzyme immobilization

Procedia PDF Downloads 208
5820 The Use of Ultrasound as a Safe and Cost-Efficient Technique to Assess Visceral Fat in Children with Obesity

Authors: Bassma A. Abdel Haleem, Ehab K. Emam, George E. Yacoub, Ashraf M. Salem

Abstract:

Background: Obesity is an increasingly common problem in childhood. Childhood obesity is considered the main risk factor for the development of metabolic syndrome (MetS) (diabetes type 2, dyslipidemia, and hypertension). Recent studies estimated that among children with obesity 30-60% will develop MetS. Visceral fat thickness is a valuable predictor of the development of MetS. Computed tomography and dual-energy X-ray absorptiometry are the main techniques to assess visceral fat. However, they carry the risk of radiation exposure and are expensive procedures. Consequently, they are seldom used in the assessment of visceral fat in children. Some studies explored the potential of ultrasound as a substitute to assess visceral fat in the elderly and found promising results. Given the vulnerability of children to radiation exposure, we sought to evaluate ultrasound as a safer and more cost-efficient alternative for measuring visceral fat in obese children. Additionally, we assessed the correlation between visceral fat and obesity indicators such as insulin resistance. Methods: A cross-sectional study was conducted on 46 children with obesity (aged 6–16 years). Their visceral fat was evaluated by ultrasound. Subcutaneous fat thickness (SFT), i.e., the measurement from the skin-fat interface to the linea alba, and visceral fat thickness (VFT), i.e., the thickness from the linea alba to the aorta, were measured and correlated with anthropometric measures, fasting lipid profile, homeostatic model assessment for insulin resistance (HOMA-IR) and liver enzymes (ALT). Results: VFT assessed via ultrasound was found to strongly correlate with the BMI, HOMA-IR with AUC for VFT as a predictor of insulin resistance of 0.858 and cut off point of >2.98. VFT also correlates positively with serum triglycerides and serum ALT. VFT correlates negatively with HDL. Conclusions: Ultrasound, a safe and cost-efficient technique, could be a useful tool for measuring the abdominal fat thickness in children with obesity. Ultrasound-measured VFT could be an appropriate prognostic factor for insulin resistance, hypertriglyceridemia, and elevated liver enzymes in obese children.

Keywords: metabolic syndrome, pediatric obesity, sonography, visceral fat

Procedia PDF Downloads 107