Search results for: bacterial foraging optimization
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4231

Search results for: bacterial foraging optimization

3511 Impedance Based Biosensor for Agricultural Pathogen Detection

Authors: Rhea Patel, Madhuri Vinchurkar, Rajul Patkar, Gopal Pranjale, Maryam Shojaei Baghini

Abstract:

One of the major limitations on food resources worldwide is the deterioration of plant products due to pathogenic infections. Early screening of plants for pathogenic infections can serve as a boon in the Agricultural sector. The standard microbiology techniques has not kept pace with the rapid enumeration and automated methods for bacteria detection. Electrochemical Impedance Spectroscopy (EIS) serves as a label free bio sensing technique to monitor pathogens in real time. The changes in the electrical impedance of a growing bacterial culture can be monitored to detect activity of microorganisms. In this study, we demonstrate development of a gold interdigitated electrode (gold IDE) based impedance biosensor to detect bacterial cells in real on-field crop samples. To calibrate our impedance measurement system, nutrient broth suspended Escherichia coli cells were used. We extended this calibrated protocol to identify the agricultural pathogens in real potato tuber samples. Distinct difference was seen in the impedance recorded for the healthy and infected potato samples. Our results support the potential application of this Impedance based biosensor in Agricultural pathogen detection.

Keywords: agriculture, biosensor, electrochemical impedance spectroscopy, microelectrode, pathogen detection

Procedia PDF Downloads 135
3510 Optimization of the Enzymatic Synthesis of the Silver Core-Shell Nanoparticles

Authors: Lela Pintarić, Iva Rezić, Ana Vrsalović Presečki

Abstract:

Considering an enormous increase of the use of metal nanoparticles with the exactly defined characteristics, the main goal of this research was to found the optimal and environmental friendly method of their synthesis. The synthesis of the inorganic core-shell nanoparticles was optimized as a model. The core-shell nanoparticles are composed of the enzyme core belted with the metal ions, oxides or salts as a shell. In this research, enzyme urease was the core catalyst and the shell nanoparticle was made of silver. Silver nanoparticles are widespread utilized and some of their common uses are: as an addition to disinfectants to ensure an aseptic environment for the patients, as a surface coating for neurosurgical shunts and venous catheters, as an addition to implants, in production of socks for diabetics and athletic clothing where they improve antibacterial characteristics, etc. Characteristics of synthesized nanoparticles directly depend on of their size, so the special care during this optimization was given to the determination of the size of the synthesized nanoparticles. For the purpose of the above mentioned optimization, sixteen experiments were generated by the Design of Experiments (DoE) method and conducted under various temperatures, with different initial concentration of the silver nitrate and constant concentration of the urease of two separate manufacturers. Synthesized nanoparticles were analyzed by the Nanoparticle Tracking Analysis (NTA) method on Malvern NanoSight NS300. Results showed that the initial concentration of the silver ions does not affect the concentration of the synthesized silver nanoparticles neither their size distribution. On the other hand, temperature of the experiments has affected both of the mentioned values.

Keywords: core-shell nanoparticles, optimization, silver, urease

Procedia PDF Downloads 295
3509 Fast Generation of High-Performance Driveshafts: A Digital Approach to Automated Linked Topology and Design Optimization

Authors: Willi Zschiebsch, Alrik Dargel, Sebastian Spitzer, Philipp Johst, Robert Böhm, Niels Modler

Abstract:

In this article, we investigate an approach that digitally links individual development process steps by using the drive shaft of an aircraft engine as a representative example of a fiber polymer composite. Such high-performance, lightweight composite structures have many adjustable parameters that influence the mechanical properties. Only a combination of optimal parameter values can lead to energy efficient lightweight structures. The development tools required for the Engineering Design Process (EDP) are often isolated solutions, and their compatibility with each other is limited. A digital framework is presented in this study, which allows individual specialised tools to be linked via the generated data in such a way that automated optimization across programs becomes possible. This is demonstrated using the example of linking geometry generation with numerical structural analysis. The proposed digital framework for automated design optimization demonstrates the feasibility of developing a complete digital approach to design optimization. The methodology shows promising potential for achieving optimal solutions in terms of mass, material utilization, eigenfrequency, and deformation under lateral load with less development effort. The development of such a framework is an important step towards promoting a more efficient design approach that can lead to stable and balanced results.

Keywords: digital linked process, composite, CFRP, multi-objective, EDP, NSGA-2, NSGA-3, TPE

Procedia PDF Downloads 56
3508 An Alternative Antimicrobial Approach to Fight Bacterial Pathogens from Phellinus linteus

Authors: S. Techaoei, K. Jarmkom, P. Eakwaropas, W. Khobjai

Abstract:

The objective of this research was focused on investigating in vitro antimicrobial activity of Phellinus linteus fruiting body extracts on Pseudomonas aeruginosa, Escherichia coli, Staphylococcus aureus and Methicillin-resistant Staphylococcus aureus. Phellinus linteus fruiting body was extracted with ethanol and ethyl acetate and was vaporized. The disc diffusion assay was used to assess antimicrobial activity against tested bacterial strains. Primary screening of chemical profile of crude extract was determined by using thin layer chromatography. The positive control and the negative control were used as erythromycin and dimethyl sulfoxide, respectively. Initial screening of Phellinus linteus crude extract with the disc diffusion assay demonstrated that only ethanol had greater antimicrobial activity against Pseudomonas aeruginosa, Escherichia coli, Staphylococcus aureus and Methicillin-resistant Staphylococcus aureus. The MIC assay showed that the lower MIC was observed with 0.5 mg/ml of Pseudomonas aeruginosa and Methicillin-resistant Staphylococcus aureus and 0.25 mg/ml. of Escherichia coli and Staphylococcus aureus, respectively. TLC chemical profile of extract was represented at Rf ≈ 0.71-0.76.

Keywords: Staphylococcus aureus, Escherichia coli, Phellinus linteus, Methicillin-resistant Staphylococcus aureus, antimicrobial activity

Procedia PDF Downloads 267
3507 Research on Knowledge Graph Inference Technology Based on Proximal Policy Optimization

Authors: Yihao Kuang, Bowen Ding

Abstract:

With the increasing scale and complexity of knowledge graph, modern knowledge graph contains more and more types of entity, relationship, and attribute information. Therefore, in recent years, it has been a trend for knowledge graph inference to use reinforcement learning to deal with large-scale, incomplete, and noisy knowledge graph and improve the inference effect and interpretability. The Proximal Policy Optimization (PPO) algorithm utilizes a near-end strategy optimization approach. This allows for more extensive updates of policy parameters while constraining the update extent to maintain training stability. This characteristic enables PPOs to converge to improve strategies more rapidly, often demonstrating enhanced performance early in the training process. Furthermore, PPO has the advantage of offline learning, effectively utilizing historical experience data for training and enhancing sample utilization. This means that even with limited resources, PPOs can efficiently train for reinforcement learning tasks. Based on these characteristics, this paper aims to obtain better and more efficient inference effect by introducing PPO into knowledge inference technology.

Keywords: reinforcement learning, PPO, knowledge inference, supervised learning

Procedia PDF Downloads 43
3506 Multi-Objective Discrete Optimization of External Thermal Insulation Composite Systems in Terms of Thermal and Embodied Energy Performance

Authors: Berfin Yildiz

Abstract:

These days, increasing global warming effects, limited amount of energy resources, etc., necessitates the awareness that must be present in every profession group. The architecture and construction sectors are responsible for both the embodied and operational energy of the materials. This responsibility has led designers to seek alternative solutions for energy-efficient material selection. The choice of energy-efficient material requires consideration of the entire life cycle, including the building's production, use, and disposal energy. The aim of this study is to investigate the method of material selection of external thermal insulation composite systems (ETICS). Embodied and in-use energy values of material alternatives were used for the evaluation in this study. The operational energy is calculated according to the u-value calculation method defined in the TS 825 (Thermal Insulation Requirements) standard for Turkey, and the embodied energy is calculated based on the manufacturer's Energy Performance Declaration (EPD). ETICS consists of a wall, adhesive, insulation, lining, mechanical, mesh, and exterior finishing materials. In this study, lining, mechanical, and mesh materials were ignored because EPD documents could not be obtained. The material selection problem is designed as a hypothetical volume area (5x5x3m) and defined as a multi-objective discrete optimization problem for external thermal insulation composite systems. Defining the problem as a discrete optimization problem is important in order to choose between materials of various thicknesses and sizes. Since production and use energy values, which are determined as optimization objectives in the study, are often conflicting values, material selection is defined as a multi-objective optimization problem, and it is aimed to obtain many solution alternatives by using Hypervolume (HypE) algorithm. The enrollment process started with 100 individuals and continued for 50 generations. According to the obtained results, it was observed that autoclaved aerated concrete and Ponce block as wall material, glass wool, as insulation material gave better results.

Keywords: embodied energy, multi-objective discrete optimization, performative design, thermal insulation

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3505 Analysis of the Lung Microbiome in Cystic Fibrosis Patients Using 16S Sequencing

Authors: Manasvi Pinnaka, Brianna Chrisman

Abstract:

Cystic fibrosis patients often develop lung infections that range anywhere in severity from mild to life-threatening due to the presence of thick and sticky mucus that fills their airways. Since many of these infections are chronic, they not only affect a patient’s ability to breathe but also increase the chances of mortality by respiratory failure. With a publicly available dataset of DNA sequences from bacterial species in the lung microbiome of cystic fibrosis patients, the correlations between different microbial species in the lung and the extent of deterioration of lung function were investigated. 16S sequencing technologies were used to determine the microbiome composition of the samples in the dataset. For the statistical analyses, referencing helped distinguish between taxonomies, and the proportions of certain taxa relative to another were determined. It was found that the Fusobacterium, Actinomyces, and Leptotrichia microbial types all had a positive correlation with the FEV1 score, indicating the potential displacement of these species by pathogens as the disease progresses. However, the dominant pathogens themselves, including Pseudomonas aeruginosa and Staphylococcus aureus, did not have statistically significant negative correlations with the FEV1 score as described by past literature. Examining the lung microbiology of cystic fibrosis patients can help with the prediction of the current condition of lung function, with the potential to guide doctors when designing personalized treatment plans for patients.

Keywords: bacterial infections, cystic fibrosis, lung microbiome, 16S sequencing

Procedia PDF Downloads 79
3504 Antimicrobial Effect of Essential Oil of Plant Schinus molle on Some Bacteria Pathogens

Authors: Mehani Mouna, Ladjel segni

Abstract:

Humans use plants for thousands of years to treat various ailments, In many developing countries, Much of the population relies on traditional doctors and their collections of medicinal plants to cure them. Essential oils have many therapeutic properties. In herbal medicine, They are used for their antiseptic properties against infectious diseases of fungal origin, Against dermatophytes, Those of bacterial origin. The aim of our study is to determine the antimicrobial effect of essential oils of the plant Schinus molle on some pathogenic bacteria. It is a medicinal plant used in traditional therapy. Essential oils have many therapeutic properties. In herbal medicine, They are used for their antiseptic properties against infectious diseases of fungal origin, Against dermatophytes, Those of bacterial origin. The test adopted is based on the diffusion method on solid medium (Antibiogram), This method allows to determine the susceptibility or resistance of an organism according to the sample studied. Our study reveals that the essential oil of the plant Schinus molle has a different effect on the resistance of germs: For Pseudomonas aeruginosa strain is a moderately sensitive with an inhibition zone of 10 mm, Further Antirobactere, Escherichia coli and Proteus are strains that represent a high sensitivity, A zone of inhibition equal to 14.66 mm.

Keywords: Essential oil, microorganism, antibiogram, shinus molle

Procedia PDF Downloads 322
3503 Pallet Tracking and Cost Optimization of the Flow of Goods in Logistics Operations by Serial Shipping Container Code

Authors: Dominika Crnjac Milic, Martina Martinovic, Vladimir Simovic

Abstract:

The case study method in this paper shows the implementation of Information Technology (IT) and the Serial Shipping Container Code (SSCC) in a Croatian company that deals with logistics operations and provides logistics services in the cold chain segment. This company is aware of the sensitivity of the goods entrusted to them by the user of the service, as well as of the importance of speed and accuracy in providing logistics services. To that end, it has implemented and used the latest IT to ensure the highest standard of high-quality logistics services to its customers. Looking for efficiency and optimization of supply chain management, while maintaining a high level of quality of the products that are sold, today's users of outsourced logistics services are open to the implementation of new IT products that ultimately deliver savings. By analysing the positive results and the difficulties that arise when using this technology, we aim to provide an insight into the potential of this approach of the logistics service provider.

Keywords: logistics operations, serial shipping container code, information technology, cost optimization

Procedia PDF Downloads 348
3502 Series-Parallel Systems Reliability Optimization Using Genetic Algorithm and Statistical Analysis

Authors: Essa Abrahim Abdulgader Saleem, Thien-My Dao

Abstract:

The main objective of this paper is to optimize series-parallel system reliability using Genetic Algorithm (GA) and statistical analysis; considering system reliability constraints which involve the redundant numbers of selected components, total cost, and total weight. To perform this work, firstly the mathematical model which maximizes system reliability subject to maximum system cost and maximum system weight constraints is presented; secondly, a statistical analysis is used to optimize GA parameters, and thirdly GA is used to optimize series-parallel systems reliability. The objective is to determine the strategy choosing the redundancy level for each subsystem to maximize the overall system reliability subject to total cost and total weight constraints. Finally, the series-parallel system case study reliability optimization results are showed, and comparisons with the other previous results are presented to demonstrate the performance of our GA.

Keywords: reliability, optimization, meta-heuristic, genetic algorithm, redundancy

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3501 Hybrid Intelligent Optimization Methods for Optimal Design of Horizontal-Axis Wind Turbine Blades

Authors: E. Tandis, E. Assareh

Abstract:

Designing the optimal shape of MW wind turbine blades is provided in a number of cases through evolutionary algorithms associated with mathematical modeling (Blade Element Momentum Theory). Evolutionary algorithms, among the optimization methods, enjoy many advantages, particularly in stability. However, they usually need a large number of function evaluations. Since there are a large number of local extremes, the optimization method has to find the global extreme accurately. The present paper introduces a new population-based hybrid algorithm called Genetic-Based Bees Algorithm (GBBA). This algorithm is meant to design the optimal shape for MW wind turbine blades. The current method employs crossover and neighborhood searching operators taken from the respective Genetic Algorithm (GA) and Bees Algorithm (BA) to provide a method with good performance in accuracy and speed convergence. Different blade designs, twenty-one to be exact, were considered based on the chord length, twist angle and tip speed ratio using GA results. They were compared with BA and GBBA optimum design results targeting the power coefficient and solidity. The results suggest that the final shape, obtained by the proposed hybrid algorithm, performs better compared to either BA or GA. Furthermore, the accuracy and speed convergence increases when the GBBA is employed

Keywords: Blade Design, Optimization, Genetic Algorithm, Bees Algorithm, Genetic-Based Bees Algorithm, Large Wind Turbine

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3500 Optimization of Plastic Injection Molding Parameters by Altering Gate and Runner of Feeding System

Authors: Ali Ramezani

Abstract:

Balancing feeding system of plastic injection molding has overriding importance as it minimizes the process’s product defects such as weld line, shrinkage, sink marks and warpage. This article presents the difference between optimization of feeding system in identical multi-cavity molding and family molding using Moldflow Plastic Insight software. In this work, the effect of dimension, shape, position and type of gates and runners on the products quality was studied. The optimization was carried out by analyzing plastic injection molding process parameters, including melt temperature, mold temperature, cooling time, cooling temperature packing time and packing pressure. It was found that symmetrical feeding system is the most efficient shape for diminishing defects in identical multi-cavity molding. However, the same results were not concluded for family molding due to the differences between volume, mass, thickness and shape of cavities.

Keywords: balancing feeding system, family molding, multi-cavity, Moldflow, plastic injection

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3499 Comparative Performance of Retting Methods on Quality Jute Fibre Production and Water Pollution for Environmental Safety

Authors: A. K. M. Zakir Hossain, Faruk-Ul Islam, Muhammad Alamgir Chowdhury, Kazi Morshed Alam, Md. Rashidul Islam, Muhammad Humayun Kabir, Noshin Ara Tunazzina, Taufiqur Rahman, Md. Ashik Mia, Ashaduzzaman Sagar

Abstract:

The jute retting process is one of the key factors for the excellent jute fibre production as well as maintaining water quality. The traditional method of jute retting is time-consuming and hampers the fish cultivation by polluting the water body. Therefore, a low cost, time-saving, environment-friendly, and improved technique is essential for jute retting to overcome this problem. Thus the study was focused to compare the extent of water pollution and fibre quality of two retting systems, i.e., traditional retting practices over-improved retting method (macha retting) by assessing different physico-chemical and microbiological properties of water and fibre quality parameters. Water samples were collected from the top and bottom of the retting place at the early, mid, and final stages of retting from four districts of Bangladesh viz., Gaibandha, Kurigram, Lalmonirhat, and Rangpur. Different physico-chemical parameters of water samples viz., pH, dissolved oxygen (DO), conductivity (CD), total dissolved solids (TDS), hardness, calcium, magnesium, carbonate, bicarbonate, chloride, phosphorus and sulphur content were measured. Irrespective of locations, the DO of the final stage retting water samples was very low as compared to the mid and early stage, and the DO of traditional jute retting method was significantly lower than the improved macha method. The pH of the water samples was slightly more acidic in the traditional retting method than that of the improved macha method. Other physico-chemical parameters of the water sample were found higher in the traditional method over-improved macha retting in all the stages of retting. Bacterial species were isolated from the collected water samples following the dilution plate technique. Microbiological results revealed that water samples of improved macha method contained more bacterial species that are supposed to involve in jute retting as compared to water samples of the traditional retting method. The bacterial species were then identified by the sequencing of 16SrDNA. Most of the bacterial species identified belong to the genera Pseudomonas, Bacillus, Pectobacterium, and Stenotrophomonas. In addition, the tensile strength of the jute fibre was tested, and the results revealed that the improved macha method showed higher mechanical strength than the traditional method in most of the locations. The overall results indicate that the water and fibre quality were found better in the improved macha retting method than the traditional method. Therefore, a time-saving and cost-friendly improved macha retting method can be widely adopted for the jute retting process to get the quality jute fiber and to keep the environment clean and safe.

Keywords: jute retting methods, physico-chemical parameters, retting microbes, tensile strength, water quality

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3498 Basic Modal Displacements (BMD) for Optimizing the Buildings Subjected to Earthquakes

Authors: Seyed Sadegh Naseralavi, Mohsen Khatibinia

Abstract:

In structural optimizations through meta-heuristic algorithms, analyses of structures are performed for many times. For this reason, performing the analyses in a time saving way is precious. The importance of the point is more accentuated in time-history analyses which take much time. To this aim, peak picking methods also known as spectrum analyses are generally utilized. However, such methods do not have the required accuracy either done by square root of sum of squares (SRSS) or complete quadratic combination (CQC) rules. The paper presents an efficient technique for evaluating the dynamic responses during the optimization process with high speed and accuracy. In the method, first by using a static equivalent of the earthquake, an initial design is obtained. Then, the displacements in the modal coordinates are achieved. The displacements are herein called basic modal displacements (MBD). For each new design of the structure, the responses can be derived by well scaling each of the MBD along the time and amplitude and superposing them together using the corresponding modal matrices. To illustrate the efficiency of the method, an optimization problems is studied. The results show that the proposed approach is a suitable replacement for the conventional time history and spectrum analyses in such problems.

Keywords: basic modal displacements, earthquake, optimization, spectrum

Procedia PDF Downloads 343
3497 The Biology of Persister Cells and Antibiotic Resistance

Authors: Zikora K. G. Anyaegbunam, Annabel A. Nnawuihe, Ngozi J. Anyaegbunam, Emmanuel A. Eze

Abstract:

The discovery and production of new antibiotics is unavoidable in the fight against drug-resistant bacteria. However, this is only part of the problem; we have never really had medications that could completely eradicate an infection. All pathogens create a limited number of dormant persister cells that are resistant to antibiotic treatment. When the concentration of antibiotics decreases, surviving persisters repopulate the population, resulting in a recurrent chronic infection. Bacterial populations have an alternative survival strategy to withstand harsh conditions or antibiotic exposure, in addition to the well-known methods of antibiotic resistance and biofilm formation. Persister cells are a limited subset of transiently antibiotic-tolerant phenotypic variations capable of surviving high-dose antibiotic therapy. Persisters that flip back to a normal phenotype can restart growth when antibiotic pressure drops, assuring the bacterial population's survival. Persister cells have been found in every major pathogen, and they play a role in antibiotic tolerance in biofilms as well as the recalcitrance of chronic infections. Persister cells has been implicated to play a role in the establishment of antibiotic resistance, according to growing research. Thusthe need to basically elucidate the biology of persisters and how they are linked to antibiotic resistance, and as well it's link to diseases.

Keywords: persister cells, phenotypic variations, repopulation, mobile genetic transfers, antibiotic resistance

Procedia PDF Downloads 186
3496 Algorithm Development of Individual Lumped Parameter Modelling for Blood Circulatory System: An Optimization Study

Authors: Bao Li, Aike Qiao, Gaoyang Li, Youjun Liu

Abstract:

Background: Lumped parameter model (LPM) is a common numerical model for hemodynamic calculation. LPM uses circuit elements to simulate the human blood circulatory system. Physiological indicators and characteristics can be acquired through the model. However, due to the different physiological indicators of each individual, parameters in LPM should be personalized in order for convincing calculated results, which can reflect the individual physiological information. This study aimed to develop an automatic and effective optimization method to personalize the parameters in LPM of the blood circulatory system, which is of great significance to the numerical simulation of individual hemodynamics. Methods: A closed-loop LPM of the human blood circulatory system that is applicable for most persons were established based on the anatomical structures and physiological parameters. The patient-specific physiological data of 5 volunteers were non-invasively collected as personalized objectives of individual LPM. In this study, the blood pressure and flow rate of heart, brain, and limbs were the main concerns. The collected systolic blood pressure, diastolic blood pressure, cardiac output, and heart rate were set as objective data, and the waveforms of carotid artery flow and ankle pressure were set as objective waveforms. Aiming at the collected data and waveforms, sensitivity analysis of each parameter in LPM was conducted to determine the sensitive parameters that have an obvious influence on the objectives. Simulated annealing was adopted to iteratively optimize the sensitive parameters, and the objective function during optimization was the root mean square error between the collected waveforms and data and simulated waveforms and data. Each parameter in LPM was optimized 500 times. Results: In this study, the sensitive parameters in LPM were optimized according to the collected data of 5 individuals. Results show a slight error between collected and simulated data. The average relative root mean square error of all optimization objectives of 5 samples were 2.21%, 3.59%, 4.75%, 4.24%, and 3.56%, respectively. Conclusions: Slight error demonstrated good effects of optimization. The individual modeling algorithm developed in this study can effectively achieve the individualization of LPM for the blood circulatory system. LPM with individual parameters can output the individual physiological indicators after optimization, which are applicable for the numerical simulation of patient-specific hemodynamics.

Keywords: blood circulatory system, individual physiological indicators, lumped parameter model, optimization algorithm

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3495 An Efficient Design of Static Synchronous Series Compensator Based Fractional Order PID Controller Using Invasive Weed Optimization Algorithm

Authors: Abdelghani Choucha, Lakhdar Chaib, Salem Arif

Abstract:

This paper treated the problem of power system stability with the aid of Static Synchronous Series Compensator (SSSC) installed in the transmission line of single machine infinite bus (SMIB) power system. A fractional order PID (FOPID) controller has been applied as a robust controller for optimal SSSC design to control the power system characteristics. Additionally, the SSSC based FOPID parameters are smoothly tuned using Invasive Weed Optimization algorithm (IWO). To verify the strength of the proposed controller, SSSC based FOPID controller is validated in a wide range of operating condition and compared with the conventional scheme SSSC-POD controller. The main purpose of the proposed process is greatly enhanced the dynamic states of the tested system. Simulation results clearly prove the superiority and performance of the proposed controller design.

Keywords: SSSC-FOPID, SSSC-POD, SMIB power system, invasive weed optimization algorithm

Procedia PDF Downloads 172
3494 Optimal Wheat Straw to Bioethanol Supply Chain Models

Authors: Abdul Halim Abdul Razik, Ali Elkamel, Leonardo Simon

Abstract:

Wheat straw is one of the alternative feedstocks that may be utilized for bioethanol production especially when sustainability criteria are the major concerns. To increase market competitiveness, optimal supply chain plays an important role since wheat straw is a seasonal agricultural residue. In designing the supply chain optimization model, economic profitability of the thermochemical and biochemical conversion routes options were considered. It was found that torrefied pelletization with gasification route to be the most profitable option to produce bioethanol from the lignocellulosic source of wheat straw.

Keywords: bio-ethanol, optimization, supply chain, wheat straw

Procedia PDF Downloads 716
3493 Artificial Intelligence-Based Chest X-Ray Test of COVID-19 Patients

Authors: Dhurgham Al-Karawi, Nisreen Polus, Shakir Al-Zaidi, Sabah Jassim

Abstract:

The management of COVID-19 patients based on chest imaging is emerging as an essential tool for evaluating the spread of the pandemic which has gripped the global community. It has already been used to monitor the situation of COVID-19 patients who have issues in respiratory status. There has been increase to use chest imaging for medical triage of patients who are showing moderate-severe clinical COVID-19 features, this is due to the fast dispersal of the pandemic to all continents and communities. This article demonstrates the development of machine learning techniques for the test of COVID-19 patients using Chest X-Ray (CXR) images in nearly real-time, to distinguish the COVID-19 infection with a significantly high level of accuracy. The testing performance has covered a combination of different datasets of CXR images of positive COVID-19 patients, patients with viral and bacterial infections, also, people with a clear chest. The proposed AI scheme successfully distinguishes CXR scans of COVID-19 infected patients from CXR scans of viral and bacterial based pneumonia as well as normal cases with an average accuracy of 94.43%, sensitivity 95%, and specificity 93.86%. Predicted decisions would be supported by visual evidence to help clinicians speed up the initial assessment process of new suspected cases, especially in a resource-constrained environment.

Keywords: COVID-19, chest x-ray scan, artificial intelligence, texture analysis, local binary pattern transform, Gabor filter

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3492 Campylobacteriosis as a Zoonotic Disease

Authors: A. Jafarzadeh, G. R. Hashemi Tabar

Abstract:

Campylobacteriosis is caused by Campylobacter organisms. This is most commonly caused by C. jejuni, It is among the most common bacterial infections of humans, often a foodborne illness. It produces an inflammatory, sometimes bloody, diarrhea or dysentery syndrome, mostly including cramps, fever and pain. It is found in cattle, swine, and birds, where it is non-pathogenic. But the illness can also be caused by C. coli (also found in cattle, swine, and birds) C. upsaliensis (found in cats and dogs) and C. lari (present in seabirds in particular). Infection with a Campylobacter species is one of the most common causes of human bacterial gastroenteritis. For instance, an estimated 2 million cases of Campylobacter enteritis occur annually in the U.S., accounting for 5-7% of cases of gastroenteritis. Furthermore, in the United Kingdom during 2000 Campylobacter jejuni was involved in 77.3% in all cases of foodborne illness. 15 out of every 100,000 people are diagnosed with campylobacteriosis every year, and with many cases going unreported, up to 0.5% of the general population may unknowingly harbor Campylobacter in their gut annually. A large animal reservoir is present as well, with up to 100% of poultry, including chickens, turkeys, and waterfowl, having asymptomatic infections in their intestinal tracts. An infected chicken may contain up to 109 bacteria per 25 grams, and due to the installations, the bacteria is rapidly spread to other chicken. This vastly exceeds the infectious dose of 1000-10,000 bacteria for humans. In this article this disease is fully discussed in human and animals.

Keywords: campylobacteriosis, human, animal, zoonosis

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3491 Modelling and Optimization of Laser Cutting Operations

Authors: Hany Mohamed Abdu, Mohamed Hassan Gadallah, El-Giushi Mokhtar, Yehia Mahmoud Ismail

Abstract:

Laser beam cutting is one nontraditional machining process. This paper optimizes the parameters of Laser beam cutting machining parameters of Stainless steel (316L) by considering the effect of input parameters viz. power, oxygen pressure, frequency and cutting speed. Statistical design of experiments are carried in three different levels and process responses such as 'Average kerf taper (Ta)' and 'Surface Roughness (Ra)' are measured accordingly. A quadratic mathematical model (RSM) for each of the responses is developed as a function of the process parameters. Responses predicted by the models (as per Taguchi’s L27 OA) are employed to search for an optimal parametric combination to achieve desired yield of the process. RSM models are developed for mean responses, S/N ratio, and standard deviation of responses. Optimization models are formulated as single objective problem subject to process constraints. Models are formulated based on Analysis of Variance (ANOVA) using MATLAB environment. Optimum solutions are compared with Taguchi Methodology results.

Keywords: optimization, laser cutting, robust design, kerf width, Taguchi method, RSM and DOE

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3490 Methane Production from Biomedical Waste (Blood)

Authors: Fatima M. Kabbashi, Abdalla M. Abdalla, Hussam K. Hamad, Elias S. Hassan

Abstract:

This study investigates the production of renewable energy (biogas) from biomedical hazard waste (blood) and eco-friendly disposal. Biogas is produced by the bacterial anaerobic digestion of biomaterial (blood). During digestion process bacterial feeding result in breaking down chemical bonds of the biomaterial and changing its features, by the end of the digestion (biogas production) the remains become manure as known. That has led to the economic and eco-friendly disposal of hazard biomedical waste (blood). The samples (Whole blood, Red blood cells 'RBCs', Blood platelet and Fresh Frozen Plasma ‘FFP’) are collected and measured in terms of carbon to nitrogen C/N ratio and total solid, then filled in connected flasks (three flasks) using water displacement method. The results of trails showed that the platelet and FFP failed to produce flammable gas, but via a gas analyzer, it showed the presence of the following gases: CO, HC, CO₂, and NOX. Otherwise, the blood and RBCs produced flammable gases: Methane-nitrous CH₃NO (99.45%), which has a blue color flame and carbon dioxide CO₂ (0.55%), which has red/yellow color flame. Methane-nitrous is sometimes used as fuel for rockets, some aircraft and racing cars.

Keywords: renewable energy, biogas, biomedical waste, blood, anaerobic digestion, eco-friendly disposal

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3489 Antibacterial Activity of the Essential Oil of Origanum glandulosum on Bacterial Strains of Hospital Origin Most Implicated in Nosocomial Infections

Authors: A. Lardjam, R. Mazid, S. Y. Boudghene, A. Izarouken, Y. Dali, N. Djebli, H. Toumi

Abstract:

Origanum glandulosum is an aromatic plant, common in Algeria and widely used by local people for its medicinal properties. The essential oil from this plant, which grows in the west of Algeria, was studied to evaluate and determine its antibacterial activity. The extraction of the essential oil was performed by water steam distillation; the yield obtained from the aerial parts (1.78 %) is interesting, its chromatographic profile revealed by TLC showed the presence of phenolic compounds thymol and carvacrol. The evaluation of the activity of the essential oil of Origanum glandulosum on bacterial strains of hospital origin, ATCC, MRB, and HRB, most implicated in nosocomial infections (Staphylococcus aureus ATCC 25923, Staphylococcus aureus ATCC 43300, Enterococcus faecalis ATCC 29212, Escherichia coli ATCC 25922, Pseudomonas aeruginosa ATCC 27853, Staphylococcus aureus resistant to meticillin, Enterococcus faecium, VA R and R TEC, Acinetobacter baumanii, IMP R and R CAZ, Klebsiella pneumonia carbapenemase-producing) by the method of aromatogramme and micro atmosphere, shows that the antibacterial potency of this oil is very high, expressed by significant inhibition diameters on all strains except Pseudomonas aeruginosa, and low MICs and is characterized by a bactericidal action.

Keywords: antibacterial activity, essential oil, HRB, MBR, nosocomial infections, origanum glandulosum

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3488 Optimization of Surface Coating on Magnetic Nanoparticles for Biomedical Applications

Authors: Xiao-Li Liu, Ling-Yun Zhao, Xing-Jie Liang, Hai-Ming Fan

Abstract:

Owing to their unique properties, magnetic nanoparticles have been used as diagnostic and therapeutic agents for biomedical applications. Highly monodispersed magnetic nanoparticles with controlled particle size and surface coating have been successfully synthesized as a model system to investigate the effect of surface coating on the T2 relaxivity and specific absorption rate (SAR) under an alternating magnetic field, respectively. Amongst, by using mPEG-g-PEI to solubilize oleic-acid capped 6 nm magnetic nanoparticles, the T2 relaxivity could be significantly increased by up to 4-fold as compared to PEG coated nanoparticles. Moreover, it largely enhances the cell uptake with a T2 relaxivity of 92.6 mM-1s-1 for in vitro cell MRI. As for hyperthermia agent, SAR value increase with the decreased thickness of PEG surface coating. By elaborate optimization of surface coating and particle size, a significant increase of SAR (up to 74%) could be achieved with a minimal variation on the saturation magnetization (<5%). The 19 nm magnetic nanoparticles with 2000 Da PEG exhibited the highest SAR of 930 W•g-1 among the samples, which can be maintained in various simulated physiological conditions. This systematic work provides a general strategy for the optimization of surface coating of magnetic core for high performance MRI contrast agent and hyperthermia agent.

Keywords: magnetic nanoparticles, magnetic hyperthermia, magnetic resonance imaging, surface modification

Procedia PDF Downloads 492
3487 Isolation and Characterization of Endophytic Bacteria Associated with Root-Nodules of Medicago sativa in Al-Ahasa Region

Authors: Ashraf Y. Z. Khalifa, Mohammed A. Almalki

Abstract:

Medicago sativa (Alfalfa) is an important forage crop legume worldwide including Saudia Arabia due to its high nutritive value. Soil bacteria exist in root or root-nodules of Medicago sativa in either symbiotic relationships or in associations. The aim of the present study was to isolate and characterize endophytic bacteria that live in association with non-nodulated roots of Medicago sativa growing in Al-Ahsaa region, Saudia Arabia. Several bacterial strains were isolated from sterilized roots of Medicago sativa. Strains were characterized using 16S rRNA gene sequences, phylogenetic relationships analysis, morphological and biochemical characteristics. The strains utilized 50% (10 out of 20) of the different chemical substrates contained in the API20E strip. In general, many strains had the ability to ferment/oxidise all the carbohydrate tested except for rhamnose and the polyol carbohydrate, inositol. Comparative sequence analysis of the 16S rDNA gene indicated that the strains were closely related to the genus Bacillus. Furthermore, the growth parameters of Vigna sinensis were enhanced upon single-inoculation of the isolated strains, compared to the uninoculated control plants. The results highlighted that the root-nodules of Medicago sativa harbor non-nodulating bacterial strains that could have significant agricultural applications.

Keywords: Medicago sativa, endophytic bacteria, Pisum sativum, Vigna sinensis

Procedia PDF Downloads 360
3486 Impact of the Electricity Market Prices during the COVID-19 Pandemic on Energy Storage Operation

Authors: Marin Mandić, Elis Sutlović, Tonći Modrić, Luka Stanić

Abstract:

With the restructuring and deregulation of the power system, storage owners, generation companies or private producers can offer their multiple services on various power markets and earn income in different types of markets, such as the day-ahead, real-time, ancillary services market, etc. During the COVID-19 pandemic, electricity prices, as well as ancillary services prices, increased significantly. The optimization of the energy storage operation was performed using a suitable model for simulating the operation of a pumped storage hydropower plant under market conditions. The objective function maximizes the income earned through energy arbitration, regulation-up, regulation-down and spinning reserve services. The optimization technique used for solving the objective function is mixed integer linear programming (MILP). In numerical examples, the pumped storage hydropower plant operation has been optimized considering the already achieved hourly electricity market prices from Nord Pool for the pre-pandemic (2019) and the pandemic (2020 and 2021) years. The impact of the electricity market prices during the COVID-19 pandemic on energy storage operation is shown through the analysis of income, operating hours, reserved capacity and consumed energy for each service. The results indicate the role of energy storage during a significant fluctuation in electricity and services prices.

Keywords: electrical market prices, electricity market, energy storage optimization, mixed integer linear programming (MILP) optimization

Procedia PDF Downloads 156
3485 Optimal Design of Composite Patch for a Cracked Pipe by Utilizing Genetic Algorithm and Finite Element Method

Authors: Mahdi Fakoor, Seyed Mohammad Navid Ghoreishi

Abstract:

Composite patching is a common way for reinforcing the cracked pipes and cylinders. The effects of composite patch reinforcement on fracture parameters of a cracked pipe depend on a variety of parameters such as number of layers, angle, thickness, and material of each layer. Therefore, stacking sequence optimization of composite patch becomes crucial for the applications of cracked pipes. In this study, in order to obtain the optimal stacking sequence for a composite patch that has minimum weight and maximum resistance in propagation of cracks, a coupled Multi-Objective Genetic Algorithm (MOGA) and Finite Element Method (FEM) process is proposed. This optimization process has done for longitudinal and transverse semi-elliptical cracks and optimal stacking sequences and Pareto’s front for each kind of cracks are presented. The proposed algorithm is validated against collected results from the existing literature.

Keywords: multi objective optimization, pareto front, composite patch, cracked pipe

Procedia PDF Downloads 294
3484 The Importance of Optimization of Halal Tourism: A Study of the Development of Halal Tourism in Indonesia

Authors: Rizqi W. Romadhon, Nur Arifan

Abstract:

Halal Tourism is a part of tourism industry which is based on Islamic Principle and addressed to the Muslim tourist. The potency of halal tourism is very broad to be developed, because the growth of Muslim populations is rapidly increasing. Indonesia is one of the biggest countries with Majority of its population is Muslim, therefore human resources and natural resources have very good potential to be part of the Halal tourism industry. But the fact is Indonesia can not optimize the potential of human resources and natural resources as well as neighboring countries carried out. This paper will discuss the reasons of the importance of developing Halal tourism, and the factors influencing the success of developing halal tourism in Indonesia, and also the optimization strategies which can be adopted by the government so that the Halal tourism industry in Indonesia has a sustainable competitive advantage. The existence of this research is expected to government, tourism agents and others can optimize the potency of Indonesia’s Human resources and natural resources for developing Halal tourism industry in Indonesia.

Keywords: halal tourism, Islamic principle, optimization, sustainable competitive advantage

Procedia PDF Downloads 359
3483 Solutions to Probabilistic Constrained Optimal Control Problems Using Concentration Inequalities

Authors: Tomoaki Hashimoto

Abstract:

Recently, optimal control problems subject to probabilistic constraints have attracted much attention in many research field. Although probabilistic constraints are generally intractable in optimization problems, several methods haven been proposed to deal with probabilistic constraints. In most methods, probabilistic constraints are transformed to deterministic constraints that are tractable in optimization problems. This paper examines a method for transforming probabilistic constraints into deterministic constraints for a class of probabilistic constrained optimal control problems.

Keywords: optimal control, stochastic systems, discrete-time systems, probabilistic constraints

Procedia PDF Downloads 260
3482 Inverse Mapping of Weld Bead Geometry in Shielded Metal Arc-Welding: Genetic Algorithm Approach

Authors: D. S. Nagesh, G. L. Datta

Abstract:

In the field of welding, various studies had been made by some of the previous investigators to predict as well as optimize weld bead geometric descriptors. Modeling of weld bead shape is important for predicting the quality of welds. In most of the cases, design of experiments technique to postulate multiple linear regression equations have been used. Nowadays, Genetic Algorithm (GA) an intelligent information treatment system with the characteristics of treating complex relationships as seen in welding processes used as a tool for inverse mapping/optimization of the process is attempted.

Keywords: smaw, genetic algorithm, bead geometry, optimization/inverse mapping

Procedia PDF Downloads 438