Search results for: degradation signal
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3286

Search results for: degradation signal

2116 A Study on Method for Identifying Capacity Factor Declination of Wind Turbines

Authors: Dongheon Shin, Kyungnam Ko, Jongchul Huh

Abstract:

The investigation on wind turbine degradation was carried out using the nacelle wind data. The three Vestas V80-2MW wind turbines of Sungsan wind farm in Jeju Island, South Korea were selected for this work. The SCADA data of the wind farm for five years were analyzed to draw power curve of the turbines. It is assumed that the wind distribution is the Rayleigh distribution to calculate the normalized capacity factor based on the drawn power curve of the three wind turbines for each year. The result showed that the reduction of power output from the three wind turbines occurred every year and the normalized capacity factor decreased to 0.12%/year on average.

Keywords: wind energy, power curve, capacity factor, annual energy production

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2115 Ibrutinib and the Potential Risk of Cardiac Failure: A Review of Pharmacovigilance Data

Authors: Abdulaziz Alakeel, Roaa Alamri, Abdulrahman Alomair, Mohammed Fouda

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Introduction: Ibrutinib is a selective, potent, and irreversible small-molecule inhibitor of Bruton's tyrosine kinase (BTK). It forms a covalent bond with a cysteine residue (CYS-481) at the active site of Btk, leading to inhibition of Btk enzymatic activity. The drug is indicated to treat certain type of cancers such as mantle cell lymphoma (MCL), chronic lymphocytic leukaemia and Waldenström's macroglobulinaemia (WM). Cardiac failure is a condition referred to inability of heart muscle to pump adequate blood to human body organs. There are multiple types of cardiac failure including left and right-sided heart failure, systolic and diastolic heart failures. The aim of this review is to evaluate the risk of cardiac failure associated with the use of ibrutinib and to suggest regulatory recommendations if required. Methodology: Signal Detection team at the National Pharmacovigilance Center (NPC) of Saudi Food and Drug Authority (SFDA) performed a comprehensive signal review using its national database as well as the World Health Organization (WHO) database (VigiBase), to retrieve related information for assessing the causality between cardiac failure and ibrutinib. We used the WHO- Uppsala Monitoring Centre (UMC) criteria as standard for assessing the causality of the reported cases. Results: Case Review: The number of resulted cases for the combined drug/adverse drug reaction are 212 global ICSRs as of July 2020. The reviewers have selected and assessed the causality for the well-documented ICSRs with completeness scores of 0.9 and above (35 ICSRs); the value 1.0 presents the highest score for best-written ICSRs. Among the reviewed cases, more than half of them provides supportive association (four probable and 15 possible cases). Data Mining: The disproportionality of the observed and the expected reporting rate for drug/adverse drug reaction pair is estimated using information component (IC), a tool developed by WHO-UMC to measure the reporting ratio. Positive IC reflects higher statistical association while negative values indicates less statistical association, considering the null value equal to zero. The results of (IC=1.5) revealed a positive statistical association for the drug/ADR combination, which means “Ibrutinib” with “Cardiac Failure” have been observed more than expected when compared to other medications available in WHO database. Conclusion: Health regulators and health care professionals must be aware for the potential risk of cardiac failure associated with ibrutinib and the monitoring of any signs or symptoms in treated patients is essential. The weighted cumulative evidences identified from causality assessment of the reported cases and data mining are sufficient to support a causal association between ibrutinib and cardiac failure.

Keywords: cardiac failure, drug safety, ibrutinib, pharmacovigilance, signal detection

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2114 The Effect of Chloride Dioxide and High Concentration of CO2 Gas Injection on the Quality and Shelf-Life for Exporting Strawberry 'Maehyang' in Modified Atmosphere Condition

Authors: Hyuk Sung Yoon, In-Lee Choi, Mohammad Zahirul Islam, Jun Pill Baek, Ho-Min Kang

Abstract:

The strawberry ‘Maehyang’ cultivated in South Korea has been increased to export to Southeast Asia. The degradation of quality often occurs in strawberries during short export period. Botrytis cinerea has been known to cause major damage to the export strawberries and the disease was caused during shipping and distribution. This study was conducted to find out the sterilized effect of chlorine dioxide(ClO2) gas and high concentration of CO2 gas injection for ‘Maehyang’ strawberry and it was packaged with oxygen transmission rate (OTR) films. The strawberry was harvested at 80% color changed stage and packaged with OTR film and perforated film (control). The treatments were a MAP used by with 20,000 cc·m-2·day·atm OTR film and gas injection in packages. The gas type of ClO2 and CO2 were injected into OTR film packages, and treatments were 6 mg/L ClO2, 15% CO2, and they were combined. The treated strawberries were stored at 3℃ for 30 days. Fresh weight loss rate was less than 1% in all OTR film packages but it was more than 15% in a perforated film treatment that showed severe deterioration of visual quality during storage. Carbon dioxide concentration within a package showed approximately 15% of the maximum CO2 concentration in all treatments except control until the 21st day, it was the tolerated range of maximum CO2 concentration of strawberry in recommended CA or MA conditions. But, it increased to almost 50% on the 30th day. Oxygen concentration showed a decrease down to approximately 0% in all treatments except control for 25 days. Ethylene concentration was shown to be steady until the 17th day, but it quickly increased on the 17th day and dropped down on the final storage day (30th day). All treatments did not show any significant differences in gas treatments. Firmness increased in CO2 (15%) and ClO2 (6mg/L) + CO2 (15%) treatments during storage. It might be the effect of high concentration CO2 known by reducing decay and cell wall degradation. The soluble solid decreased in all treatments during storage. These results were caused to use up the sugar by the increase of respiration during storage. The titratable acidity showed a similarity in all treatments. Incidence of fungi was 0% in CO2 (15%) and ClO2 (6mg/L)+ CO2 (15%), but was more than 20% in a perforated film treatment. Consequently, The result indicates that Chloride Dioxide(ClO2) and high concentration of CO2 inhibited fungi growth. Due to the fact that fresh weight loss rate and incidence of fungi were lower, the ClO2(6mg/L)+ CO2(15%) prove to be most efficient in sterilization. These results suggest that Chloride Dioxide (ClO2) and high concentration of CO2 gas injection treatments were an effective decontamination technique for improving the safety of strawberries.

Keywords: chloride dioxide, high concentration of CO2, modified atmosphere condition, oxygen transmission rate films

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2113 C2N2 Adsorption on the Surface of a BN Nanosheet: A DFT Study

Authors: Maziar Noei

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Calculation showed that when the nanosheet is doped by Si, the adsorption energy is about -85.62 to -87.43kcal/mol and also the amount of HOMO/LUMO energy gap (Eg) will reduce significantly. Boron nitride nanosheet is a suitable adsorbent for cyanogen and can be used in separation processes cyanogen. It seems that nanosheet (BNNS) is a suitable semiconductor after doping. The doped BNNS in the presence of cyanogens (C2N2) an electrical signal is generating directly and, therefore, can potentially be used for cyanogen sensors.

Keywords: nanosheet, DFT, cyanogen, sensors

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2112 Normalized P-Laplacian: From Stochastic Game to Image Processing

Authors: Abderrahim Elmoataz

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More and more contemporary applications involve data in the form of functions defined on irregular and topologically complicated domains (images, meshs, points clouds, networks, etc). Such data are not organized as familiar digital signals and images sampled on regular lattices. However, they can be conveniently represented as graphs where each vertex represents measured data and each edge represents a relationship (connectivity or certain affinities or interaction) between two vertices. Processing and analyzing these types of data is a major challenge for both image and machine learning communities. Hence, it is very important to transfer to graphs and networks many of the mathematical tools which were initially developed on usual Euclidean spaces and proven to be efficient for many inverse problems and applications dealing with usual image and signal domains. Historically, the main tools for the study of graphs or networks come from combinatorial and graph theory. In recent years there has been an increasing interest in the investigation of one of the major mathematical tools for signal and image analysis, which are Partial Differential Equations (PDEs) variational methods on graphs. The normalized p-laplacian operator has been recently introduced to model a stochastic game called tug-of-war-game with noise. Part interest of this class of operators arises from the fact that it includes, as particular case, the infinity Laplacian, the mean curvature operator and the traditionnal Laplacian operators which was extensiveley used to models and to solve problems in image processing. The purpose of this paper is to introduce and to study a new class of normalized p-Laplacian on graphs. The introduction is based on the extension of p-harmonious function introduced in as discrete approximation for both infinity Laplacian and p-Laplacian equations. Finally, we propose to use these operators as a framework for solving many inverse problems in image processing.

Keywords: normalized p-laplacian, image processing, stochastic game, inverse problems

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2111 Taguchi Robust Design for Optimal Setting of Process Wastes Parameters in an Automotive Parts Manufacturing Company

Authors: Charles Chikwendu Okpala, Christopher Chukwutoo Ihueze

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As a technique that reduces variation in a product by lessening the sensitivity of the design to sources of variation, rather than by controlling their sources, Taguchi Robust Design entails the designing of ideal goods, by developing a product that has minimal variance in its characteristics and also meets the desired exact performance. This paper examined the concept of the manufacturing approach and its application to brake pad product of an automotive parts manufacturing company. Although the firm claimed that only defects, excess inventory, and over-production were the few wastes that grossly affect their productivity and profitability, a careful study and analysis of their manufacturing processes with the application of Single Minute Exchange of Dies (SMED) tool showed that the waste of waiting is the fourth waste that bedevils the firm. The selection of the Taguchi L9 orthogonal array which is based on the four parameters and the three levels of variation for each parameter revealed that with a range of 2.17, that waiting is the major waste that the company must reduce in order to continue to be viable. Also, to enhance the company’s throughput and profitability, the wastes of over-production, excess inventory, and defects with ranges of 2.01, 1.46, and 0.82, ranking second, third, and fourth respectively must also be reduced to the barest minimum. After proposing -33.84 as the highest optimum Signal-to-Noise ratio to be maintained for the waste of waiting, the paper advocated for the adoption of all the tools and techniques of Lean Production System (LPS), and Continuous Improvement (CI), and concluded by recommending SMED in order to drastically reduce set up time which leads to unnecessary waiting.

Keywords: lean production system, single minute exchange of dies, signal to noise ratio, Taguchi robust design, waste

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2110 Classifying Turbomachinery Blade Mode Shapes Using Artificial Neural Networks

Authors: Ismail Abubakar, Hamid Mehrabi, Reg Morton

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Currently, extensive signal analysis is performed in order to evaluate structural health of turbomachinery blades. This approach is affected by constraints of time and the availability of qualified personnel. Thus, new approaches to blade dynamics identification that provide faster and more accurate results are sought after. Generally, modal analysis is employed in acquiring dynamic properties of a vibrating turbomachinery blade and is widely adopted in condition monitoring of blades. The analysis provides useful information on the different modes of vibration and natural frequencies by exploring different shapes that can be taken up during vibration since all mode shapes have their corresponding natural frequencies. Experimental modal testing and finite element analysis are the traditional methods used to evaluate mode shapes with limited application to real live scenario to facilitate a robust condition monitoring scheme. For a real time mode shape evaluation, rapid evaluation and low computational cost is required and traditional techniques are unsuitable. In this study, artificial neural network is developed to evaluate the mode shape of a lab scale rotating blade assembly by using result from finite element modal analysis as training data. The network performance evaluation shows that artificial neural network (ANN) is capable of mapping the correlation between natural frequencies and mode shapes. This is achieved without the need of extensive signal analysis. The approach offers advantage from the perspective that the network is able to classify mode shapes and can be employed in real time including simplicity in implementation and accuracy of the prediction. The work paves the way for further development of robust condition monitoring system that incorporates real time mode shape evaluation.

Keywords: modal analysis, artificial neural network, mode shape, natural frequencies, pattern recognition

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2109 Effect of Transition Metal (Fe, Mn) Ion Doping on TiO2 Nano Particles

Authors: Kirit Siddhapara, Dimple Shah

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In this research, we have studied the doping behaviors of two transition metal ion dopants on the crystal phase, particle sizes, XRD patterns, EDAX spectra, and photoreactivity of TiO2 nanoparticles. The crystalline size of TiO2 is close to 4 nm Calculated from (1 0 1) peak by using FWHM method in Scherrer’s equation. Test metal ion concentrations ranged from 1% to 4 at.%, we report the growth of [Fe, Mn]xTiO2 nanocrystals prepared by Sol-Gel technique, followed by freeze-drying treatment at -30°C temperature for 12hrs. The obtained Gel was thermally treated at different temperature like 200°C, 400°C, 600°C, 800°C. Thermal gravimetric analysis (TGA) shows that dopant concentration affects thermal decomposition. The photoreactivities of transition metal ion-doped TiO2 nanoparticles under UV irradiation were quantified by the degradation of formaldehyde.

Keywords: growth from solution, sol-gel method, nanomaterials, oxides, magnetic materials, titanium compounds

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2108 Temperature-Based Detection of Initial Yielding Point in Loading of Tensile Specimens Made of Structural Steel

Authors: Aqsa Jamil, Tamura Hiroshi, Katsuchi Hiroshi, Wang Jiaqi

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The yield point represents the upper limit of forces which can be applied to a specimen without causing any permanent deformation. After yielding, the behavior of the specimen suddenly changes, including the possibility of cracking or buckling. So, the accumulation of damage or type of fracture changes depending on this condition. As it is difficult to accurately detect yield points of the several stress concentration points in structural steel specimens, an effort has been made in this research work to develop a convenient technique using thermography (temperature-based detection) during tensile tests for the precise detection of yield point initiation. To verify the applicability of thermography camera, tests were conducted under different loading conditions and measuring the deformation by installing various strain gauges and monitoring the surface temperature with the help of a thermography camera. The yield point of specimens was estimated with the help of temperature dip, which occurs due to the thermoelastic effect during the plastic deformation. The scattering of the data has been checked by performing a repeatability analysis. The effects of temperature imperfection and light source have been checked by carrying out the tests at daytime as well as midnight and by calculating the signal to noise ratio (SNR) of the noised data from the infrared thermography camera, it can be concluded that the camera is independent of testing time and the presence of a visible light source. Furthermore, a fully coupled thermal-stress analysis has been performed by using Abaqus/Standard exact implementation technique to validate the temperature profiles obtained from the thermography camera and to check the feasibility of numerical simulation for the prediction of results extracted with the help of the thermographic technique.

Keywords: signal to noise ratio, thermoelastic effect, thermography, yield point

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2107 An Analytical Metric and Process for Critical Infrastructure Architecture System Availability Determination in Distributed Computing Environments under Infrastructure Attack

Authors: Vincent Andrew Cappellano

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In the early phases of critical infrastructure system design, translating distributed computing requirements to an architecture has risk given the multitude of approaches (e.g., cloud, edge, fog). In many systems, a single requirement for system uptime / availability is used to encompass the system’s intended operations. However, when architected systems may perform to those availability requirements only during normal operations and not during component failure, or during outages caused by adversary attacks on critical infrastructure (e.g., physical, cyber). System designers lack a structured method to evaluate availability requirements against candidate system architectures through deep degradation scenarios (i.e., normal ops all the way down to significant damage of communications or physical nodes). This increases risk of poor selection of a candidate architecture due to the absence of insight into true performance for systems that must operate as a piece of critical infrastructure. This research effort proposes a process to analyze critical infrastructure system availability requirements and a candidate set of systems architectures, producing a metric assessing these architectures over a spectrum of degradations to aid in selecting appropriate resilient architectures. To accomplish this effort, a set of simulation and evaluation efforts are undertaken that will process, in an automated way, a set of sample requirements into a set of potential architectures where system functions and capabilities are distributed across nodes. Nodes and links will have specific characteristics and based on sampled requirements, contribute to the overall system functionality, such that as they are impacted/degraded, the impacted functional availability of a system can be determined. A machine learning reinforcement-based agent will structurally impact the nodes, links, and characteristics (e.g., bandwidth, latency) of a given architecture to provide an assessment of system functional uptime/availability under these scenarios. By varying the intensity of the attack and related aspects, we can create a structured method of evaluating the performance of candidate architectures against each other to create a metric rating its resilience to these attack types/strategies. Through multiple simulation iterations, sufficient data will exist to compare this availability metric, and an architectural recommendation against the baseline requirements, in comparison to existing multi-factor computing architectural selection processes. It is intended that this additional data will create an improvement in the matching of resilient critical infrastructure system requirements to the correct architectures and implementations that will support improved operation during times of system degradation due to failures and infrastructure attacks.

Keywords: architecture, resiliency, availability, cyber-attack

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2106 Study of Transport in Electronic Devices with Stochastic Monte Carlo Method: Modeling and Simulation along with Submicron Gate (Lg=0.5um)

Authors: N. Massoum, B. Bouazza

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In this paper, we have developed a numerical simulation model to describe the electrical properties of GaInP MESFET with submicron gate (Lg = 0.5 µm). This model takes into account the three-dimensional (3D) distribution of the load in the short channel and the law effect of mobility as a function of electric field. Simulation software based on a stochastic method such as Monte Carlo has been established. The results are discussed and compared with those of the experiment. The result suggests experimentally that, in a very small gate length in our devices (smaller than 40 nm), short-channel tunneling explains the degradation of transistor performance, which was previously enhanced by velocity overshoot.

Keywords: Monte Carlo simulation, transient electron transport, MESFET device, simulation software

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2105 Selection of Optimal Reduced Feature Sets of Brain Signal Analysis Using Heuristically Optimized Deep Autoencoder

Authors: Souvik Phadikar, Nidul Sinha, Rajdeep Ghosh

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In brainwaves research using electroencephalogram (EEG) signals, finding the most relevant and effective feature set for identification of activities in the human brain is a big challenge till today because of the random nature of the signals. The feature extraction method is a key issue to solve this problem. Finding those features that prove to give distinctive pictures for different activities and similar for the same activities is very difficult, especially for the number of activities. The performance of a classifier accuracy depends on this quality of feature set. Further, more number of features result in high computational complexity and less number of features compromise with the lower performance. In this paper, a novel idea of the selection of optimal feature set using a heuristically optimized deep autoencoder is presented. Using various feature extraction methods, a vast number of features are extracted from the EEG signals and fed to the autoencoder deep neural network. The autoencoder encodes the input features into a small set of codes. To avoid the gradient vanish problem and normalization of the dataset, a meta-heuristic search algorithm is used to minimize the mean square error (MSE) between encoder input and decoder output. To reduce the feature set into a smaller one, 4 hidden layers are considered in the autoencoder network; hence it is called Heuristically Optimized Deep Autoencoder (HO-DAE). In this method, no features are rejected; all the features are combined into the response of responses of the hidden layer. The results reveal that higher accuracy can be achieved using optimal reduced features. The proposed HO-DAE is also compared with the regular autoencoder to test the performance of both. The performance of the proposed method is validated and compared with the other two methods recently reported in the literature, which reveals that the proposed method is far better than the other two methods in terms of classification accuracy.

Keywords: autoencoder, brainwave signal analysis, electroencephalogram, feature extraction, feature selection, optimization

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2104 Influence of Processing Regime and Contaminants on the Properties of Postconsumer Thermoplastics

Authors: Fares Alsewailem

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Material recycling of thermoplastic waste offers practical solution for municipal solid waste reduction. Post-consumer plastics such as polyethylene (PE), polyethyleneterephtalate (PET), and polystyrene (PS) may be separated from each other by physical methods such as density difference and hence processed as single plastic, however one should be cautious about the contaminants presence in the waste stream inform of paper, glue, etc. since these articles even in trace amount may deteriorate properties of the recycled plastics especially the mechanical properties. furthermore, melt processing methods used to recycle thermoplastics such as extrusion and compression molding may induce degradation of some of the recycled plastics such as PET and PS. In this research, it is shown that care should be taken when processing recycled plastics by melt processing means in two directions, first contaminants should be extremely minimized, and secondly melt processing steps should also be minimum.

Keywords: Recycling, PET, PS, HDPE, mechanical

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2103 Enzymatic Hydrolysis of Sugar Cane Bagasse Using Recombinant Hemicellulases

Authors: Lorena C. Cintra, Izadora M. De Oliveira, Amanda G. Fernandes, Francieli Colussi, Rosália S. A. Jesuíno, Fabrícia P. Faria, Cirano J. Ulhoa

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Xylan is the main component of hemicellulose and for its complete degradation is required cooperative action of a system consisting of several enzymes including endo-xylanases (XYN), β-xylosidases (XYL) and α-L-arabinofuranosidases (ABF). The recombinant hemicellulolytic enzymes an endoxylanase (HXYN2), β-xylosidase (HXYLA), and an α-L-arabinofuranosidase (ABF3) were used in hydrolysis tests. These three enzymes are produced by filamentous fungi and were expressed heterologously and produced in Pichia pastoris previously. The aim of this work was to evaluate the effect of recombinant hemicellulolytic enzymes on the enzymatic hydrolysis of sugarcane bagasse (SCB). The interaction between the three recombinant enzymes during SCB pre-treated by steam explosion hydrolysis was performed with different concentrations of HXYN2, HXYLA and ABF3 in different ratios in according to a central composite rotational design (CCRD) 23, including six axial points and six central points, totaling 20 assays. The influence of the factors was assessed by analyzing the main effects and interaction between the factors, calculated using Statistica 8.0 software (StatSoft Inc. Tulsa, OK, USA). The Pareto chart was constructed with this software and showed the values of the Student’s t test for each recombinant enzyme. It was considered as response variable the quantification of reducing sugars by DNS (mg/mL). The Pareto chart showed that the recombinant enzyme ABF3 exerted more significant effect during SCB hydrolysis, with higher concentrations and with the lowest concentration of this enzyme. It was performed analysis of variance according to Fisher method (ANOVA). In ANOVA for the release of reducing sugars (mg/ml) as the variable response, the concentration of ABF3 showed significance during hydrolysis SCB. The result obtained by ANOVA, is in accordance with those presented in the analysis method based on the statistical Student's t (Pareto chart). The degradation of the central chain of xylan by HXYN2 and HXYLA was more strongly influenced by ABF3 action. A model was obtained, and it describes the performance of the interaction of all three enzymes for the release of reducing sugars, and can be used to better explain the results of the statistical analysis. The formulation capable of releasing the higher levels of reducing sugars had the following concentrations: HXYN2 with 600 U/g of substrate, HXYLA with 11.5 U.g-1 and ABF3 with 0.32 U.g-1. In conclusion, the recombinant enzyme that has a more significant effect during SCB hydrolysis was ABF3. It is noteworthy that the xylan present in the SCB is arabinoglucoronoxylan, due to this fact debranching enzymes are important to allow access of enzymes that act on the central chain.

Keywords: experimental design, hydrolysis, recombinant enzymes, sugar cane bagasse

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2102 Electrochemical Corrosion and Mechanical Properties of Structural Materials for Oil and Gas Applications in Simulated Deep-Sea Well Environments

Authors: Turin Datta, Kisor K. Sahu

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Structural materials used in today’s oil and gas exploration and drilling of both onshore and offshore oil and gas wells must possess superior tensile properties, excellent resistance to corrosive degradation that includes general, localized (pitting and crevice) and environment assisted cracking such as stress corrosion cracking and hydrogen embrittlement. The High Pressure and High Temperature (HPHT) wells are typically operated at temperature and pressure that can exceed 300-3500F and 10,000psi (69MPa) respectively which necessitates the use of exotic materials in these exotic sources of natural resources. This research investigation is focussed on the evaluation of tensile properties and corrosion behavior of AISI 4140 High-Strength Low Alloy Steel (HSLA) possessing tempered martensitic microstructure and Duplex 2205 Stainless Steel (DSS) having austenitic and ferritic phase. The selection of this two alloys are primarily based on economic considerations as 4140 HSLA is cheaper when compared to DSS 2205. Due to the harsh aggressive chemical species encountered in deep oil and gas wells like chloride ions (Cl-), carbon dioxide (CO2), hydrogen sulphide (H2S) along with other mineral organic acids, DSS 2205, having a dual-phase microstructure can mitigate the degradation resulting from the presence of both chloride ions (Cl-) and hydrogen simultaneously. Tensile properties evaluation indicates a ductile failure of DSS 2205 whereas 4140 HSLA exhibit quasi-cleavage fracture due to the phenomenon of ‘tempered martensitic embrittlement’. From the potentiodynamic polarization testing, it is observed that DSS 2205 has higher corrosion resistance than 4140 HSLA; the former exhibits passivity signifying resistance to localized corrosion while the latter exhibits active dissolution in all the environmental parameters space that was tested. From the Scanning Electron Microscopy (SEM) evaluation, it is understood that stable pits appear in DSS 2205 only when the temperature exceeds the critical pitting temperature (CPT). SEM observation of the corroded 4140 HSLA specimen tested in aqueous 3.5 wt.% NaCl solution reveals intergranular cracking which appears due to the adsorption and diffusion of hydrogen during polarization, thus, causing hydrogen-induced cracking/hydrogen embrittlement. General corrosion testing of DSS 2205 in acidic brine (pH~3.0) solution at ambient temperature using coupons indicate no weight loss even after three months whereas the corrosion rate of AISI 4140 HSLA is significantly higher after one month of testing.

Keywords: DSS 2205, polarization, pitting, SEM

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2101 An Approach to Study the Biodegradation of Low Density Polyethylene Using Microbial Strains of Bacillus subtilus, Aspergillus niger, Pseudomonas fluroscence in Different Media Form and Salt Condition

Authors: Monu Ojha, Rahul Rana, Satywati Sharma, Kavya Dashora

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The global production rate of plastics has increased enormously and global demand for polyethylene resins –High-density polyethylene (HDPE), Linear low-density polyethylene (LLDPE) and Low-density polyethylene (LDPE) is expected to rise drastically, with very high value. These get accumulated in the environment, posing a potential ecological threat as they are degrading at a very slow rate and remain in the environment indefinitely. The aim of the present study was to investigate the potential of commonly found soil microbes like Bacillus subtilus, Aspergillus niger, Pseudomonas fluroscence for their ability to biodegrade LDPE in the lab on solid and liquid media conditions as well as in presence of 1% salt in the soil. This study was conducted at Indian Institute of Technology, Delhi, India from July to September where average temperature and RH (Relative Humidity) were 33 degrees Celcius and 80% respectively. It revealed that the weight loss of LDPE strip obtained from market of approximately 4x6 cm dimensions is more in liquid broth media than in solid agar media. The percentage weight loss by P. fluroscence, A. niger and B. subtilus observed after 80 days of incubation was 15.52, 9.24 and 8.99% respectively in broth media and 6.93, 2.18 and 4.76 % in agar media. The LDPE strips from same source and on the same were subjected to soil in presence of above microbes with 1% salt (NaCl: obtained from commercial table salt) with temperature and RH 33 degree Celcius and 80%. It was found that the rate of degradation increased in the soil than under lab conditions. The rate of weight loss of LDPE strips under same conditions given in lab was found to be 32.98, 15.01 and17.09 % by P. fluroscence, A. niger and B. subtilus respectively. The breaking strength was found to be 9.65N, 29N and 23.85 N for P. fluroscence, A. niger and B. subtilus respectively. SEM analysis conducted on Zeiss EVO 50 confirmed that surface of LDPE becomes physically weak after biological treatment. There was the increase in the surface roughness indicating Surface erosion of LDPE film. FTIR (Fourier-transform infrared spectroscopy) analysis of the degraded LDPE films showed stretching of aldehyde group at 3334.92 and 3228.84 cm-1,, C–C=C symmetric of aromatic ring at 1639.49 cm-1.There was also C=O stretching of aldehyde group at 1735.93 cm-1. N=O peak bend was also observed which corresponds to 1365.60 cm-1, C–O stretching of ether group at 1217.08 and 1078.21 cm-1.

Keywords: microbial degradation, LDPE, Aspergillus niger, Bacillus subtilus, Peudomonas fluroscence, common salt

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2100 2.4 GHz 0.13µM Multi Biased Cascode Power Amplifier for ISM Band Wireless Applications

Authors: Udayan Patankar, Shashwati Bhagat, Vilas Nitneware, Ants Koel

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An ISM band power amplifier is a type of electronic amplifier used to convert a low-power radio-frequency signal into a larger signal of significant power, typically used for driving the antenna of a transmitter. Due to drastic changes in telecommunication generations may lead to the requirements of improvements. Rapid changes in communication lead to the wide implementation of WLAN technology for its excellent characteristics, such as high transmission speed, long communication distance, and high reliability. Many applications such as WLAN, Bluetooth, and ZigBee, etc. were evolved with 2.4GHz to 5 GHz ISM Band, in which the power amplifier (PA) is a key building block of RF transmitters. There are many manufacturing processes available to manufacture a power amplifier for desired power output, but the major problem they have faced is about the power it consumed for its proper working, as many of them are fabricated on the GaN HEMT, Bi COMS process. In this paper we present a CMOS Base two stage cascode design of power amplifier working on 2.4GHz ISM frequency band. To lower the costs and allow full integration of a complete System-on-Chip (SoC) we have chosen 0.13µm low power CMOS technology for design. While designing a power amplifier, it is a real task to achieve higher power efficiency with minimum resources. This design showcase the Multi biased Cascode methodology to implement a two-stage CMOS power amplifier using ADS and LTSpice simulating tool. Main source is maximum of 2.4V which is internally distributed into different biasing point VB driving and VB driven as required for distinct stages of two stage RF power amplifier. It shows maximum power added efficiency near about 70.195% whereas its Power added efficiency calculated at 1 dB compression point is 44.669 %. Biased MOSFET is used to reduce total dc current as this circuit is designed for different wireless applications comes under 2.4GHz ISM Band.

Keywords: RFIC, PAE, RF CMOS, impedance matching

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2099 Radiation Hardness Materials Article Review

Authors: S. Abou El-Azm, U. Kruchonak, M. Gostkin, A. Guskov, A. Zhemchugov

Abstract:

Semiconductor detectors are widely used in nuclear physics and high-energy physics experiments. The application of semiconductor detectors could be limited by their ultimate radiation resistance. The increase of radiation defects concentration leads to significant degradation of the working parameters of semiconductor detectors. The investigation of radiation defects properties in order to enhance the radiation hardness of semiconductor detectors is an important task for the successful implementation of a number of nuclear physics experiments; we presented some information about radiation hardness materials like diamond, sapphire and CdTe. Also, the results of measurements I-V characteristics, charge collection efficiency and its dependence on the bias voltage for different doses of high resistivity (GaAs: Cr) and Si at LINAC-200 accelerator and reactor IBR-2 are presented.

Keywords: semiconductor detectors, radiation hardness, GaAs, Si, CCE, I-V, C-V

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2098 The Relationship between Spindle Sound and Tool Performance in Turning

Authors: N. Seemuang, T. McLeay, T. Slatter

Abstract:

Worn tools have a direct effect on the surface finish and part accuracy. Tool condition monitoring systems have been developed over a long period and used to avoid a loss of productivity resulting from using a worn tool. However, the majority of tool monitoring research has applied expensive sensing systems not suitable for production. In this work, the cutting sound in turning machine was studied using microphone. Machining trials using seven cutting conditions were conducted until the observable flank wear width (FWW) on the main cutting edge exceeded 0.4 mm. The cutting inserts were removed from the tool holder and the flank wear width was measured optically. A microphone with built-in preamplifier was used to record the machining sound of EN24 steel being face turned by a CNC lathe in a wet cutting condition using constant surface speed control. The sound was sampled at 50 kS/s and all sound signals recorded from microphone were transformed into the frequency domain by FFT in order to establish the frequency content in the audio signature that could be then used for tool condition monitoring. The extracted feature from audio signal was compared to the flank wear progression on the cutting inserts. The spectrogram reveals a promising feature, named as ‘spindle noise’, which emits from the main spindle motor of turning machine. The spindle noise frequency was detected at 5.86 kHz of regardless of cutting conditions used on this particular CNC lathe. Varying cutting speed and feed rate have an influence on the magnitude of power spectrum of spindle noise. The magnitude of spindle noise frequency alters in conjunction with the tool wear progression. The magnitude increases significantly in the transition state between steady-state wear and severe wear. This could be used as a warning signal to prepare for tool replacement or adapt cutting parameters to extend tool life.

Keywords: tool wear, flank wear, condition monitoring, spindle noise

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2097 Assessment of Solid Insulating Material Using Partial Discharge Characteristics

Authors: Qasim Khan, Furkan Ahmad, Asfar A. Khan, M. Saad Alam, Faiz Ahmad

Abstract:

In this paper, partial discharge analysis is performed in cavities artificially created in insulation. The setup is according with Cigre-II Method. Circular Samples created from Perspex Sheet with different configuration with changing number of cavities. Assessment of insulation health can be performed by Partial Discharge measurement as this has been found to be important means of condition monitoring. The experiments are done using MPD 540, which is a modern partial discharge measurement system. By analyzing the PD activity obtained for various voids/cavities, it is observed that the PD voltages show variation for cavity’s diameter, depth even for its ratios. This can be employed for scrutiny of insulation system.

Keywords: partial discharges, condition monitoring, insulation defects, degradation and corrosion, PMMA

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2096 Assessing Lithium Recovery from Secondary Sources

Authors: Carolina A. Santos, Alexandra B. Ribeiro

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Climate change and environmental degradation are threats to humanity. Europe has been addressing these problems, namely through the Green Deal, with the use of batteries in mobility and energy fields. However, these require the use of critical raw materials, like lithium, which demand is estimated to grow 60 times in the next 30 years. Thus, it is fundamental to promote a circular economy with lithium recovery from secondary resources. These are nowadays key topics, which will be even more relevant in the future, so a new way to approach them is needed and must be encouraged. Therefore, one of our main goals is to analyse two methods of lithium retrieval from secondary sources, bioleaching, and electrodialysis, and assess them regarding their sustainability. The latest results show good efficiency of removal with both methods, even though there are some matrix interferences. Hence, further investment and research are needed in order to make this process sustainable and our society more circular.

Keywords: lithium, sustainable mining, social license to operate, bioleaching, electrodialysis

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2095 Influence and Interaction of Temperature, H2S and pH on Concrete Sewer Pipe Corrosion

Authors: Anna Romanova, Mojtaba Mahmoodian, Morteza A. Alani

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Concrete sewer pipes are known to suffer from a process of hydrogen sulfide gas induced sulfuric acid corrosion. This leads to premature pipe degradation, performance failure and collapses which in turn may lead to property and health damage. The above work reports on a field study undertaken in working sewer manholes where the parameters of effluent temperature and pH as well as ambient temperature and concentration of hydrogen sulfide were continuously measured over a period of two months. Early results suggest that effluent pH has no direct effect on hydrogen sulfide build up; on average the effluent temperature is 3.5°C greater than the ambient temperature inside the manhole and also it was observed that hydrogen sulfate concentration increases with increasing temperature.

Keywords: concrete corrosion, hydrogen sulfide gas, temperature, sewer pipe

Procedia PDF Downloads 551
2094 HPSEC Application as a New Indicator of Nitrification Occurrence in Water Distribution Systems

Authors: Sina Moradi, Sanly Liu, Christopher W. K. Chow, John Van Leeuwen, David Cook, Mary Drikas, Soha Habibi, Rose Amal

Abstract:

In recent years, chloramine has been widely used for both primary and secondary disinfection. However, a major concern with the use of chloramine as a secondary disinfectant is the decay of chloramine and nitrification occurrence. The management of chloramine decay and the prevention of nitrification are critical for water utilities managing chloraminated drinking water distribution systems. The detection and monitoring of nitrification episodes is usually carried out through measuring certain water quality parameters, which are commonly referred to as indicators of nitrification. The approach taken in this study was to collect water samples from different sites throughout a drinking water distribution systems, Tailem Bend – Keith (TBK) in South Australia, and analyse the samples by high performance size exclusion chromatography (HPSEC). We investigated potential association between the water qualities from HPSEC analysis with chloramine decay and/or nitrification occurrence. MATLAB 8.4 was used for data processing of HPSEC data and chloramine decay. An increase in the absorbance signal of HPSEC profiles at λ=230 nm between apparent molecular weights of 200 to 1000 Da was observed at sampling sites that experienced rapid chloramine decay and nitrification while its absorbance signal of HPSEC profiles at λ=254 nm decreased. An increase in absorbance at λ=230 nm and AMW < 500 Da was detected for Raukkan CT (R.C.T), a location that experienced nitrification and had significantly lower chloramine residual (<0.1 mg/L). This increase in absorbance was not detected in other sites that did not experience nitrification. Moreover, the UV absorbance at 254 nm of the HPSEC spectra was lower at R.C.T. than other sites. In this study, a chloramine residual index (C.R.I) was introduced as a new indicator of chloramine decay and nitrification occurrence, and is defined based on the ratio of area underneath the HPSEC spectra at two different wavelengths of 230 and 254 nm. The C.R.I index is able to indicate DS sites that experienced nitrification and rapid chloramine loss. This index could be useful for water treatment and distribution system managers to know if nitrification is occurring at a specific location in water distribution systems.

Keywords: nitrification, HPSEC, chloramine decay, chloramine residual index

Procedia PDF Downloads 282
2093 Chassis Level Control Using Proportional Integrated Derivative Control, Fuzzy Logic and Deep Learning

Authors: Atakan Aral Ormancı, Tuğçe Arslantaş, Murat Özcü

Abstract:

This study presents the design and implementation of an experimental chassis-level system for various control applications. Specifically, the height level of the chassis is controlled using proportional integrated derivative, fuzzy logic, and deep learning control methods. Real-time data obtained from height and pressure sensors installed in a 6x2 truck chassis, in combination with pulse-width modulation signal values, are utilized during the tests. A prototype pneumatic system of a 6x2 truck is added to the setup, which enables the Smart Pneumatic Actuators to function as if they were in a real-world setting. To obtain real-time signal data from height sensors, an Arduino Nano is utilized, while a Raspberry Pi processes the data using Matlab/Simulink and provides the correct output signals to control the Smart Pneumatic Actuator in the truck chassis. The objective of this research is to optimize the time it takes for the chassis to level down and up under various loads. To achieve this, proportional integrated derivative control, fuzzy logic control, and deep learning techniques are applied to the system. The results show that the deep learning method is superior in optimizing time for a non-linear system. Fuzzy logic control with a triangular membership function as the rule base achieves better outcomes than proportional integrated derivative control. Traditional proportional integrated derivative control improves the time it takes to level the chassis down and up compared to an uncontrolled system. The findings highlight the superiority of deep learning techniques in optimizing the time for a non-linear system, and the potential of fuzzy logic control. The proposed approach and the experimental results provide a valuable contribution to the field of control, automation, and systems engineering.

Keywords: automotive, chassis level control, control systems, pneumatic system control

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2092 An Improved Cooperative Communication Scheme for IoT System

Authors: Eui-Hak Lee, Jae-Hyun Ro, Hyoung-Kyu Song

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In internet of things (IoT) system, the communication scheme with reliability and low power is required to connect a terminal. Cooperative communication can achieve reliability and lower power than multiple-input multiple-output (MIMO) system. Cooperative communication increases the reliability with low power, but decreases a throughput. It has a weak point that the communication throughput is decreased. In this paper, a novel scheme is proposed to increase the communication throughput. The novel scheme is a transmission structure that increases transmission rate. And a decoding scheme according to the novel transmission structure is proposed. Simulation results show that the proposed scheme increases the throughput without bit error rate (BER) performance degradation.

Keywords: cooperative communication, IoT, STBC, transmission rate

Procedia PDF Downloads 382
2091 Motif Search-Aided Screening of the Pseudomonas syringae pv. Maculicola Genome for Genes Encoding Tertiary Alcohol Ester Hydrolases

Authors: M. L. Mangena, N. Mokoena, K. Rashamuse, M. G. Tlou

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Tertiary alcohol ester (TAE) hydrolases are a group of esterases (EC 3.1.1.-) that catalyze the kinetic resolution of TAEs and as a result, they are sought-after for the production of optically pure tertiary alcohols (TAs) which are useful as building blocks for number biologically active compounds. What sets these enzymes apart is, the presence of a GGG(A)X-motif in the active site which appears to be the main reason behind their activity towards the sterically demanding TAEs. The genome of Pseudomonas syringae pv. maculicola (Psm) comprises a multitude of genes that encode esterases. We therefore, hypothesize that some of these genes encode TAE hydrolases. In this study, Psm was screened for TAE hydrolase activity using the linalyl acetate (LA) plate assay and a positive reaction was observed. As a result, the genome of Psm was screened for esterases with a GGG(A)X-motif using the motif search tool and two potential TAE hydrolase genes (PsmEST1 and 2, 1100 and 1000bp, respectively) were identified, PsmEST1 was amplified by PCR and the gene sequenced for confirmation. Analysis of the sequence data with the SingnalP 4.1 server revealed that the protein comprises a signal peptide (22 amino acid residues) on the N-terminus. Primers specific for the gene encoding the mature protein (without the signal peptide) were designed such that they contain NdeI and XhoI restriction sites for directional cloning of the PCR products into pET28a. The gene was expressed in E. coli JM109 (DE3) and the clones screened for TAE hydrolase activity using the LA plate assay. A positive clone was selected, overexpressed and the protein purified using nickel affinity chromatography. The activity of the esterase towards LA was confirmed using thin layer chromatography.

Keywords: hydrolases, tertiary alcohol esters, tertiary alcohols, screening, Pseudomonas syringae pv., maculicola genome, esterase activity, linalyl acetate

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2090 Behavioral Effects of Oxidant and Reduced Chemorepellent on Mutant and Wild-Type Tetrahymena thermophila

Authors: Ananya Govindarajan

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Tetrahymena thermophila is a single-cell, eukaryotic organism that belongs to the Protozoa Kingdom. Tetrahymena thermophila is often used in signal transduction pathway studies because of its ability to model sensory input and the effects of environmental conditions such as chemicals and temperature. The recently discovered G37 chemorepellent receptor showed increased responsiveness to all chemorepellents. Investigating the mutant G37 Tetrahymena gene in various test solutions, including ferric chloride, ferrous sulfate, hydrogen peroxide, tetrazolium blue, potassium chloride, and dithiothreitol were performed to determine the role of oxidants and reducing agents with the mutant and wild-type cells (CU427) to assess the role of the receptor. Behavioral assays and recordings processed by ImageJ indicated that ferric chloride, hydrogen peroxide, and tetrazolium blue yielded little to no chemorepellent responses from G37 cells (<20% ARs). CU427 cells were over-responsive based on the mean percent of cells (>50% ARs). Reducing agents elicited chemorepellent responses from both G37 and CU427, in addition to potassium chloride. Cell responses were classified as over-responsive (>50% ARs). Dithiothreitol yielded unexpected results as G37 (37.0% ARs) and CU427 (38.1% ARs) had relatively similar responses and were only responsive and not over-responsive to the reducing agent test chemical solution. Ultimately, this indicates that the G37 receptor is more interactive with molecules that are reducing agents or non-oxidant compounds; G37 may be unable to sense and respond to oxidants effectively, further elucidating the pathways of the G37 strain and nature of this receptor. Results also indicate that the CSF most likely contained an oxidant, like ferric chloride. This research can be further applied to neuronal influences and how specific compounds may affect human neurons individually and their excitability as the responses model action potentials and membrane potential.

Keywords: tetrahymena thermophila, signal transduction, chemosensory, oxidant, reducing agent

Procedia PDF Downloads 118
2089 Measurement System for Human Arm Muscle Magnetic Field and Grip Strength

Authors: Shuai Yuan, Minxia Shi, Xu Zhang, Jianzhi Yang, Kangqi Tian, Yuzheng Ma

Abstract:

The precise measurement of muscle activities is essential for understanding the function of various body movements. This work aims to develop a muscle magnetic field signal detection system based on mathematical analysis. Medical research has underscored that early detection of muscle atrophy, coupled with lifestyle adjustments such as dietary control and increased exercise, can significantly enhance muscle-related diseases. Currently, surface electromyography (sEMG) is widely employed in research as an early predictor of muscle atrophy. Nonetheless, the primary limitation of using sEMG to forecast muscle strength is its inability to directly measure the signals generated by muscles. Challenges arise from potential skin-electrode contact issues due to perspiration, leading to inaccurate signals or even signal loss. Additionally, resistance and phase are significantly impacted by adipose layers. The recent emergence of optically pumped magnetometers introduces a fresh avenue for bio-magnetic field measurement techniques. These magnetometers possess high sensitivity and obviate the need for a cryogenic environment unlike superconducting quantum interference devices (SQUIDs). They detect muscle magnetic field signals in the range of tens to thousands of femtoteslas (fT). The utilization of magnetometers for capturing muscle magnetic field signals remains unaffected by issues of perspiration and adipose layers. Since their introduction, optically pumped atomic magnetometers have found extensive application in exploring the magnetic fields of organs such as cardiac and brain magnetism. The optimal operation of these magnetometers necessitates an environment with an ultra-weak magnetic field. To achieve such an environment, researchers usually utilize a combination of active magnetic compensation technology with passive magnetic shielding technology. Passive magnetic shielding technology uses a magnetic shielding device built with high permeability materials to attenuate the external magnetic field to a few nT. Compared with more layers, the coils that can generate a reverse magnetic field to precisely compensate for the residual magnetic fields are cheaper and more flexible. To attain even lower magnetic fields, compensation coils designed by Biot-Savart law are involved to generate a counteractive magnetic field to eliminate residual magnetic fields. By solving the magnetic field expression of discrete points in the target region, the parameters that determine the current density distribution on the plane can be obtained through the conventional target field method. The current density is obtained from the partial derivative of the stream function, which can be represented by the combination of trigonometric functions. Optimization algorithms in mathematics are introduced into coil design to obtain the optimal current density distribution. A one-dimensional linear regression analysis was performed on the collected data, obtaining a coefficient of determination R2 of 0.9349 with a p-value of 0. This statistical result indicates a stable relationship between the peak-to-peak value (PPV) of the muscle magnetic field signal and the magnitude of grip strength. This system is expected to be a widely used tool for healthcare professionals to gain deeper insights into the muscle health of their patients.

Keywords: muscle magnetic signal, magnetic shielding, compensation coils, trigonometric functions.

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2088 Community Development and Preservation of Heritage in Igbo Area of Nigeria

Authors: Elochukwu A. Nwankwo, Matthias U. Agboeze

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Many heritage sites abound in the shores of Nigeria with enormous tourism potentials. Heritage sites do not only depict the cultural and historical transmutation of people but also functions in the image design and promotion of a locality. This reveals the unique role of heritage sites to structural development of an area. Heritage sites have of recent been a victim of degradation and social abuse arising from seasonal ignorance; hence minimizing its potentials to the socio-economic development of an area. This paper is emphasizing on the adoption of community development approaches in heritage preservation in Igbo area. Its modalities, applications, challenges and prospect were discussed. Such understanding will serve as a catalyst in aiding general restoration and preservation of heritage sites in Nigeria and other African states.

Keywords: heritage resources, community development, preservation, sustainable development, approaches

Procedia PDF Downloads 298
2087 Curcumin Nanomedicine: A Breakthrough Approach for Enhanced Lung Cancer Therapy

Authors: Shiva Shakori Poshteh

Abstract:

Lung cancer is a highly prevalent and devastating disease, representing a significant global health concern with profound implications for healthcare systems and society. Its high incidence, mortality rates, and late-stage diagnosis contribute to its formidable nature. To address these challenges, nanoparticle-based drug delivery has emerged as a promising therapeutic strategy. Curcumin (CUR), a natural compound derived from turmeric, has garnered attention as a potential nanomedicine for lung cancer treatment. Nanoparticle formulations of CUR offer several advantages, including improved drug delivery efficiency, enhanced stability, controlled release kinetics, and targeted delivery to lung cancer cells. CUR exhibits a diverse array of effects on cancer cells. It induces apoptosis by upregulating pro-apoptotic proteins, such as Bax and Bak, and downregulating anti-apoptotic proteins, such as Bcl-2. Additionally, CUR inhibits cell proliferation by modulating key signaling pathways involved in cancer progression. It suppresses the PI3K/Akt pathway, crucial for cell survival and growth, and attenuates the mTOR pathway, which regulates protein synthesis and cell proliferation. CUR also interferes with the MAPK pathway, which controls cell proliferation and survival, and modulates the Wnt/β-catenin pathway, which plays a role in cell proliferation and tumor development. Moreover, CUR exhibits potent antioxidant activity, reducing oxidative stress and protecting cells from DNA damage. Utilizing CUR as a standalone treatment is limited by poor bioavailability, lack of targeting, and degradation susceptibility. Nanoparticle-based delivery systems can overcome these challenges. They enhance CUR’s bioavailability, protect it from degradation, and improve absorption. Further, Nanoparticles enable targeted delivery to lung cancer cells through surface modifications or ligand-based targeting, ensuring sustained release of CUR to prolong therapeutic effects, reduce administration frequency, and facilitate penetration through the tumor microenvironment, thereby enhancing CUR’s access to cancer cells. Thus, nanoparticle-based CUR delivery systems promise to improve lung cancer treatment outcomes. This article provides an overview of lung cancer, explores CUR nanoparticles as a treatment approach, discusses the benefits and challenges of nanoparticle-based drug delivery, and highlights prospects for CUR nanoparticles in lung cancer treatment. Future research aims to optimize these delivery systems for improved efficacy and patient prognosis in lung cancer.

Keywords: lung cancer, curcumin, nanomedicine, nanoparticle-based drug delivery

Procedia PDF Downloads 60