Search results for: biophysical and biochemical techniques

Authors: Mounir Adal, Baalal Azeddine, Afifi Moulay Larbi

Abstract:

Numerical analysis is a branch of mathematics devoted to the development of iterative matrix calculation techniques. We are searching for operations optimization as objective to calculate and solve systems of equations of order n with time and energy saving for computers that are conducted to calculate and analyze big data by solving matrix equations. Furthermore, this scientific discipline is producing results with a margin of error of approximation called rates. Thus, the results obtained from the numerical analysis techniques that are held on computer software such as MATLAB or Simulink offers a preliminary diagnosis of the situation of the environment or space targets. By this we can offer technical procedures needed for engineering or scientific studies exploitable by engineers for water.

Keywords: numerical analysis methods, obstacles solving, engineering, simulation, numerical modeling, iteration, computer, MATLAB, water, underground, velocity

Procedia PDF Downloads 462

Authors: Elizabeth M. Annoni, Elena G. Tolkacheva

Abstract:

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia that is a known prognostic marker for stroke, heart failure and death. Reentrant mechanisms of rotor formation, which are stable electrical sources of cardiac excitation, are believed to cause AF. No existing commercial mapping systems have been demonstrated to consistently and accurately predict rotor locations outside of the pulmonary veins in patients with persistent AF. There is a clear need for robust spatio-temporal techniques that can consistently identify rotors using unique characteristics of the electrical recordings at the pivot point that can be applied to clinical intracardiac mapping. Recently, we have developed four new signal analysis approaches – Shannon entropy (SE), Kurtosis (Kt), multi-scale frequency (MSF), and multi-scale entropy (MSE) – to identify the pivot points of rotors. These proposed techniques utilize different cardiac signal characteristics (other than local activation) to uncover the intrinsic complexity of the electrical activity in the rotors, which are not taken into account in current mapping methods. We validated these techniques using high-resolution optical mapping experiments in which direct visualization and identification of rotors in ex-vivo Langendorff-perfused hearts were possible. Episodes of ventricular tachycardia (VT) were induced using burst pacing, and two examples of rotors were used showing 3-sec episodes of a single stationary rotor and figure-8 reentry with one rotor being stationary and one meandering. Movies were captured at a rate of 600 frames per second for 3 sec. with 64x64 pixel resolution. These optical mapping movies were used to evaluate the performance and robustness of SE, Kt, MSF and MSE techniques with respect to the following clinical limitations: different time of recordings, different spatial resolution, and the presence of meandering rotors. To quantitatively compare the results, SE, Kt, MSF and MSE techniques were compared to the “true” rotor(s) identified using the phase map. Accuracy was calculated for each approach as the duration of the time series and spatial resolution were reduced. The time series duration was decreased from its original length of 3 sec, down to 2, 1, and 0.5 sec. The spatial resolution of the original VT episodes was decreased from 64x64 pixels to 32x32, 16x16, and 8x8 pixels by uniformly removing pixels from the optical mapping video.. Our results demonstrate that Kt, MSF and MSE were able to accurately identify the pivot point of the rotor under all three clinical limitations. The MSE approach demonstrated the best overall performance, but Kt was the best in identifying the pivot point of the meandering rotor. Artifacts mildly affect the performance of Kt, MSF and MSE techniques, but had a strong negative impact of the performance of SE. The results of our study motivate further validation of SE, Kt, MSF and MSE techniques using intra-atrial electrograms from paroxysmal and persistent AF patients to see if these approaches can identify pivot points in a clinical setting. More accurate rotor localization could significantly increase the efficacy of catheter ablation to treat AF, resulting in a higher success rate for single procedures.

Keywords: Atrial Fibrillation, Optical Mapping, Signal Processing, Rotors

Procedia PDF Downloads 324

Authors: André Smith, Amr Abdel-Dayem

Abstract:

The stereo matching problem, while having been present for several decades, continues to be an active area of research. The goal of this research is to find correspondences between elements found in a set of stereoscopic images. With these pairings, it is possible to infer the distance of objects within a scene, relative to the observer. Advancements in this field have led to experimentations with various techniques, from graph-cut energy minimization to artificial neural networks. At the basis of these techniques is a cost function, which is used to evaluate the likelihood of a particular match between points in each image. While at its core, the cost is based on comparing the image pixel data; there is a general lack of consistency as to what image data representation to use. This paper presents an experimental analysis to compare the effectiveness of more common image data representations. The goal is to determine the effectiveness of these data representations to reduce the cost for the correct correspondence relative to other possible matches.

Keywords: colour data, local stereo matching, stereo correspondence, disparity map

Procedia PDF Downloads 370

Authors: S. Shankar Bharathi

Abstract:

Inspection of surface defects on metallic components has always been challenging due to its specular property. Occurrences of defects such as scratches, rust, pitting are very common in metallic surfaces during the manufacturing process. These defects if unchecked can hamper the performance and reduce the life time of such component. Many of the conventional image processing algorithms in detecting the surface defects generally involve segmentation techniques, based on thresholding, edge detection, watershed segmentation and textural segmentation. They later employ other suitable algorithms based on morphology, region growing, shape analysis, neural networks for classification purpose. In this paper the work has been focused only towards detecting scratches. Global and other thresholding techniques were used to extract the defects, but it proved to be inaccurate in extracting the defects alone. However, this paper does not focus on comparison of different segmentation techniques, but rather describes a novel approach towards segmentation combined with hausdorff dilation distance. The proposed algorithm is based on the distribution of the intensity levels, that is, whether a certain gray level is concentrated or evenly distributed. The algorithm is based on extraction of such concentrated pixels. Defective images showed higher level of concentration of some gray level, whereas in non-defective image, there seemed to be no concentration, but were evenly distributed. This formed the basis in detecting the defects in the proposed algorithm. Hausdorff dilation distance based on mathematical morphology was used to strengthen the segmentation of the defects.

Keywords: metallic surface, scratches, segmentation, hausdorff dilation distance, machine vision

Procedia PDF Downloads 427

Authors: Zine-Eddine Bouras, Abdelouaheb Talai

Abstract:

During the last two decades, the software evolution community has intensively tackled the software merging issue whose main objective is to merge in a consistent way different versions of software in order to obtain a new version. Well-established approaches, mainly based on the dependence analysis techniques, have been used to bring suitable solutions. These approaches concern the source code or software architectures. However, these solutions are more expensive due to the complexity and size. In this paper, we overcome this problem by operating at a high level of abstraction. The objective of this paper is to investigate the software merging at the level of UML activity diagrams, which is a new interesting issue. Its purpose is to merge activity diagrams instead of source code. The proposed approach, based on dependence analysis techniques, is illustrated through an appropriate case study.

Keywords: activity diagram, activity diagram slicing, dependency analysis, software merging

Procedia PDF Downloads 327

Authors: Qing K. Zhu

Abstract:

Very Large Scale Integration (VLSI) design becomes very complex due to the continuous integration of millions of gates in one chip based on Moore’s law. Designers have encountered numerous report files during design iterations using timing and noise analysis tools. This paper presented our work using data mining techniques combined with HTML tables to extract and represent critical timing/noise data. When we apply this data-mining tool in real applications, the running speed is important. The software employs table look-up techniques in the programming for the reasonable running speed based on performance testing results. We added several advanced features for the application in one industry chip design.

Keywords: VLSI design, data mining, big data, HTML forms, web, VLSI, EDA, timing, noise

Procedia PDF Downloads 254

Authors: Mehwish Asghar

Abstract:

Breast Cancer (BC) is a common type of cancer among women. Its screening is usually performed using different imaging modalities such as magnetic resonance imaging, mammogram, X-ray, CT, etc. Among these modalities’ mammogram is considered a powerful tool for diagnosis and screening of breast cancer. Sophisticated machine learning approaches have shown promising results in complementing human diagnosis. Generally, machine learning methods can be divided into two major classes: one is Radiomics analysis (RA), where image features are extracted manually; and the other one is the concept of convolutional neural networks (CNN), in which the computer learns to recognize image features on its own. This research aims to improve the incidence of early detection, thus reducing the mortality rate caused by breast cancer through the latest advancements in computer science, in general, and machine learning, in particular. It has also been aimed to ease the burden of doctors by improving and automating the process of breast cancer detection. This research is related to a relative analysis of different techniques for the implementation of different models for detecting and classifying breast cancer. The main goal of this research is to provide a detailed view of results and performances between different techniques. The purpose of this paper is to explore the potential of a convolutional neural network (CNN) w.r.t feature extractor and as a classifier. Also, in this research, it has been aimed to add the module of Radiomics for comparison of its results with deep learning techniques.

Keywords: breast cancer (BC), machine learning (ML), convolutional neural network (CNN), radionics, magnetic resonance imaging, artificial intelligence

Procedia PDF Downloads 225

Authors: Nelson R. Osungbemiro, O. A. Bello-Olusoji, M. Oladipupo

Abstract:

This study was carried out to determine the effects of probiotics Pseudomonas fluorescens on the growth performance, histology examination and immune modulation of African Catfish, (Clarias gariepinus) challenged with Clostridium botulinum. P. fluorescens, and C. botulinum isolates were removed from the gut, gill and skin organs of procured adult samples of Clarias gariepinus from commercial fish farms in Akure, Ondo State, Nigeria. The physical and biochemical tests were performed on the bacterial isolates using standard microbiological techniques for their identification. Antibacterial activity tests on P. fluorescens showed inhibition zone with mean value of 3.7 mm which indicates high level of antagonism. The experimental diets were prepared at different probiotics bacterial concentration comprises of five treatments of different bacterial suspension, including the control (T1), T2 (10³), T3 (10⁵), T4 (10⁷) and T5 (10⁹). Three replicates for each treatment type were prepared. Growth performance and nutrients utilization indices were calculated. The proximate analysis of fish carcass and experimental diet was carried out using standard methods. After feeding for 70 days, haematological values and histological test were done following standard methods; also a subgroup from each experimental treatment was challenged by inoculating Intraperitonieally (I/P) with different concentration of pathogenic C. botulinum. Statistically, there were significant differences (P < 0.05) in the growth performance and nutrient utilization of C. gariepinus. Best weight gain and feed conversion ratio were recorded in fish fed T4 (10⁷) and poorest value obtained in the control. Haematological analyses of C. gariepinus fed the experimental diets indicated that all the fish fed diets with P. fluorescens had marked significantly (p < 0.05) higher White Blood Cell than the control diet. The results of the challenge test showed that fish fed the control diet had the highest mortality rate. Histological examination of the gill, intestine, and liver of fish in this study showed several histopathological alterations in fish fed the control diets compared with those fed the P. fluorescens diets. The study indicated that the optimum level of P. fluorescens required for C. gariepinus growth and white blood cells formation is 10⁷ CFU g⁻¹, while carcass protein deposition required 10⁵ CFU g⁻¹ of P. fluorescens concentration. The study also confirmed P. fluorescens as efficient probiotics that is capable of improving the immune response of C. gariepinus against the attack of a virulent fish pathogen, C. botulinum.

Keywords: Clarias gariepinus, Clostridium botulinum, probiotics, Pseudomonas fluorescens

Procedia PDF Downloads 162

Authors: Rasha F. Sharaf

Abstract:

Treatment of dental caries in young children is considered a great challenge for all dentists, especially with uncooperative children. Recently non-invasive techniques have been highlighted as they alleviate the need for local anesthesia and other painful procedures during management of carious teeth and, at the same time, increase the success rate of the treatment done. Silver Diamine Fluoride (SDF) is one of the most effective cariostatic materials that arrest the progression of carious lesions and aid in remineralizing the demineralized tooth structure. Both fluoride and silver ions proved to have an antibacterial action and aid in the precipitation of an insoluble layer that prevents further decay. At the same time, Moringa proved to have an effective antibacterial action against different types of bacteria, therefore, it can be used as a non-invasive technique for the management of caries in children. One of the important theories for the control of caries is by depriving the cariogenic bacteria from nutrients causing their starvation and death, which can be achieved by applying stainless steel crown on primary molars with carious lesions which are not involving the pulp, and this technique is known as Hall technique. The success rate of the Hall technique can be increased by arresting the carious lesion using either SDF or Moringa and gaining the benefit of their antibacterial action. Multiple clinical cases with 1 year follow up will be presented, comparing different treatment options, and using various materials and techniques for non-invasive and non-painful management of carious primary teeth.

Keywords: SDF, hall technique, carious primary teeth, moringa extract

Procedia PDF Downloads 96

Authors: Khadija Al Farei, Prakash Kumar, Vikas Rao Naidu

Abstract:

Games are being developed with different genres for different age groups, for many decades. In many places, educational games are playing a vital role for active classroom environment and better learning among students. Currently, the educational games have assumed an important place in children and teenagers lives. The role of educational games is important for improving the learning capability among the students especially of this generation, who really live among electronic gadgets. Hence, it is now important to make sure that in our educational system, we are updated with all such advancement in technologies. Already much research is going on in this area of edutainment. This research paper will review around ten different research papers to find the relation between the education learning techniques and games. The result of this review provides guidelines for enhanced teaching and learning solutions in education. In-house developed educational games proved to be more effective, compared to the one which is readily available in the market.

Keywords: education, education game, educational technology, edutainment, game genres, gaming in education

Procedia PDF Downloads 415

Authors: Abdolvahab Ehsani Rad, Mohd Shafry Mohd Rahim, Alireza Norouzi

Abstract:

Medical image analysis is one of the great effects of computer image processing. There are several processes to analysis the medical images which the segmentation process is one of the challenging and most important step. In this paper the segmentation method proposed in order to segment the dental radiograph images. Thresholding method has been applied to simplify the images and to morphologically open binary image technique performed to eliminate the unnecessary regions on images. Furthermore, horizontal and vertical integral projection techniques used to extract the each individual tooth from radiograph images. Segmentation process has been done by applying the level set method on each extracted images. Nevertheless, the experiments results by 90% accuracy demonstrate that proposed method achieves high accuracy and promising result.

Keywords: integral production, level set method, morphological operation, segmentation

Procedia PDF Downloads 317

Authors: Gurjit Kaur, Neena Gupta

Abstract:

In this paper, we have analyzed and compared the performance of various coding schemes. The basic ID prime sequence codes are unique in only dimension, i.e. time slots, whereas 2D coding techniques are not unique by their time slots but with their wavelengths also. In this research, we have evaluated and compared the performance of 1D and 2D coding techniques constructed using prime sequence coding pattern for Optical Code Division Multiple Access (OCDMA) system on a single platform. Analysis shows that 2D prime code supports lesser number of active users than 1D codes, but they are having large code family and are the most secure codes compared to other codes. The performance of all these codes is analyzed on basis of number of active users supported at a Bit Error Rate (BER) of 10-9.

Keywords: CDMA, OCDMA, BER, OOC, PC, EPC, MPC, 2-D PC/PC, λc, λa

Procedia PDF Downloads 337

Authors: Shohreh Ghasemi

Abstract:

Introduction: Managing oral and maxillofacial trauma is a multifaceted challenge, as it can have life-threatening consequences and significant functional and aesthetic impact. Navigation techniques have been introduced to improve surgical precision to meet this challenge. A machine learning algorithm was also developed to support clinical decision-making regarding treating oral and maxillofacial trauma. Given these advances, this systematic meta-analysis aims to assess the efficacy of navigational techniques in treating oral and maxillofacial trauma and explore the impact of machine learning on their management. Methods: A detailed and comprehensive analysis of studies published between January 2010 and September 2021 was conducted through a systematic meta-analysis. This included performing a thorough search of Web of Science, Embase, and PubMed databases to identify studies evaluating the efficacy of navigational techniques and the impact of machine learning in managing oral and maxillofacial trauma. Studies that did not meet established entry criteria were excluded. In addition, the overall quality of studies included was evaluated using Cochrane risk of bias tool and the Newcastle-Ottawa scale. Results: Total of 12 studies, including 869 patients with oral and maxillofacial trauma, met the inclusion criteria. An analysis of studies revealed that navigation techniques effectively improve surgical accuracy and minimize the risk of complications. Additionally, machine learning algorithms have proven effective in predicting treatment outcomes and identifying patients at high risk for complications. Conclusion: The introduction of navigational technology has great potential to improve surgical precision in oral and maxillofacial trauma treatment. Furthermore, developing machine learning algorithms offers opportunities to improve clinical decision-making and patient outcomes. Still, further studies are necessary to corroborate these results and establish the optimal use of these technologies in managing oral and maxillofacial trauma

Keywords: trauma, machine learning, navigation, maxillofacial, management

Procedia PDF Downloads 58

Authors: Sara ElElimy, Samir Moustafa

Abstract:

Mobile network operators start to face many challenges in the digital era, especially with high demands from customers. Since mobile network operators are considered a source of big data, traditional techniques are not effective with new era of big data, Internet of things (IoT) and 5G; as a result, handling effectively different big datasets becomes a vital task for operators with the continuous growth of data and moving from long term evolution (LTE) to 5G. So, there is an urgent need for effective Big data analytics to predict future demands, traffic, and network performance to full fill the requirements of the fifth generation of mobile network technology. In this paper, we introduce data science techniques using machine learning and deep learning algorithms: the autoregressive integrated moving average (ARIMA), Bayesian-based curve fitting, and recurrent neural network (RNN) are employed for a data-driven application to mobile network operators. The main framework included in models are identification parameters of each model, estimation, prediction, and final data-driven application of this prediction from business and network performance applications. These models are applied to Telecom Italia Big Data challenge call detail records (CDRs) datasets. The performance of these models is found out using a specific well-known evaluation criteria shows that ARIMA (machine learning-based model) is more accurate as a predictive model in such a dataset than the RNN (deep learning model).

Keywords: big data analytics, machine learning, CDRs, 5G

Procedia PDF Downloads 139

Authors: S. Zouainia, R. Djebar, H. Berrebah, A. Sayeb

Abstract:

This work focused on the study of physiological and biochemical changes observed in tadpoles exposed to fungicide Rana saharica Artea 330ec recently introduced in Algeria. For this, we tested the effect of xenobiotics on growth and development of tadpoles; among the studied parameters: total protein, glutathione and respiratory activity. The study of physiological parameters showed that the tadpoles change perfectly in the absence of toxic and in favorable conditions (pH, temperature). Our results showed an increased rate of protein and GSH in the presence of the fungicide Artea 330ec. The latter causes uninhibited very highly significant respiratory activity of tadpoles treated. The presence of xenobiotics in the breeding tadpoles water causes disturbances in behavior and food metabolism.

Keywords: amphibians, fungicides, pesticides, pollution

Procedia PDF Downloads 408

Authors: Galina N. Parshina, Olga N. Shemshura, Ulzhan S. Mukiyanova, Gulnur M. Beisetbayeva

Abstract:

From a medical point of view some species from the family Lamiaceae Lindl. attract the attention of scientists. Many plant species from this family are used in science and medicine. Some researchers believe that the medicinal properties of these plants are caused by the action on the organism of the individual components (camphor, menthol, thymol, eugenol, phenols, flavonoids, alcohols, and their derivatives) or the entire complex of essential oils. Biologically active substances (BAS), isolated from these medicinal plants can be an effective supplement in the complex treatment of infectious diseases. The substances of the phenolic group such as flavonoids and phenolic acids; and also alkaloids included in the component composition of the plants from the family Lamiaceae Lindl. present the scientific and practical interest for future investigations of their biological activity and development of medicinal products. The research objects are the species from the family Lamiaceae Lindl., cultivated in the North-Kazakhstan region. In this abstract, we present the results of the investigation of polyphenolic complex (flavonoids and phenolic acids) and alkaloids in aqueous and ethanol extracts. Investigation of the qualitative composition of flavonoids in the aqueous extracts showed that the species Monarda Diana contains flavone, Dracocephalum moldavica contains rutin, Ocimum basilicum (purple form) contains both ruin and quercetin. Biochemical analysis revealed that the ethanol extract of Monarda Diana has phenolic acids, similar to protocatechuic and benzoic acids by their chromatographic characteristics. But the aqueous extract contains four phenolic acids, one of which is an analogue of gentisic acid; and the other three are not identified yet. The phenolic acids such as benzoic and gentisic acids identified in ethanol extracts of species Ocimum basilicum (purple form) and Satureja hortensis, correspondingly. But the same phenolic acids did not appear in aqueous extracts. The phenolic acids were not determined neither in the ethanol or aqueous extracts of species Dracocephalum moldavica. The biochemical analysis did not reveal the content of alkaloids in aqueous extracts of investigated plants. However, the alkaloids in the amount of 5-13 components were identified in the ethanolic extracts of plants by the qualitative reactions. The results of analysis with reagent of Dragendorff showed that next amounts of alkaloids were identified in extracts of Monarda Diana (6-7), Satureja hortensis (6), Ocimum basilicum (7-9) and Dracocephalum moldavica (5-6). The reactions with reagent of Van-Urca showed that next amounts of alkaloids were identified in extracts of Monarda Diana (9-12), Satureja hortensis (9-10), two alkaloids of them with Rf6=0,39 and Rf6=0,31 similar to roquefortine), Ocimum basilicum (11) and Dracocephalum moldavica (13, two of them with Rf5=0,34 and Rf5=0,33 by their chromatographic characteristics similar to epikostaklavin).

Keywords: biologically active substances, Lamiaceae, component composition, medicinal plant

Procedia PDF Downloads 503

Authors: Shohreh Ghasemi

Abstract:

Introduction: Melanoma is a complex disease with various clinical and histopathological features that impact prognosis and treatment decisions. Traditional methods of melanoma prognosis involve manual examination and interpretation of clinical and histopathological data by dermatologists and pathologists. However, the subjective nature of these assessments can lead to inter-observer variability and suboptimal prognostic accuracy. AI, with its ability to analyze vast amounts of data and identify patterns, has emerged as a promising tool for improving melanoma prognosis. Methods: A comprehensive literature search was conducted to identify studies that employed AI techniques for melanoma prognosis. The search included databases such as PubMed and Google Scholar, using keywords such as "artificial intelligence," "melanoma," and "prognosis." Studies published between 2010 and 2022 were considered. The selected articles were critically reviewed, and relevant information was extracted. Results: The review identified various AI methodologies utilized in melanoma prognosis, including machine learning algorithms, deep learning techniques, and computer vision. These techniques have been applied to diverse data sources, such as clinical images, dermoscopy images, histopathological slides, and genetic data. Studies have demonstrated the potential of AI in accurately predicting melanoma prognosis, including survival outcomes, recurrence risk, and response to therapy. AI-based prognostic models have shown comparable or even superior performance compared to traditional methods.

Keywords: artificial intelligence, melanoma, accuracy, prognosis prediction, image analysis, personalized medicine

Procedia PDF Downloads 81

Authors: Tarek Aboueldahab, Hanan Farag

Abstract:

Parallel Job Shop Scheduling Problem (JSP) is a multi-objective and multi constrains NP- optimization problem. Traditional Artificial Intelligence techniques have been widely used; however, they could be trapped into the local minimum without reaching the optimum solution, so we propose a hybrid Artificial Intelligence model (AI) with Discrete Breeding Swarm (DBS) added to traditional Artificial Intelligence to avoid this trapping. This model is applied in the cost minimization of the Car Sequencing and Operator Allocation (CSOA) problem. The practical experiment shows that our model outperforms other techniques in cost minimization.

Keywords: parallel job shop scheduling problem, artificial intelligence, discrete breeding swarm, car sequencing and operator allocation, cost minimization

Procedia PDF Downloads 187

Authors: G. M. Hamada, A. A. Al-Gathe, A. M. Al-Khudafi

Abstract:

Determination of water saturation in sandstone is a vital question to determine the initial oil or gas in place in reservoir rocks. Water saturation determination using electrical measurements is mainly on Archie’s formula. Consequently accuracy of Archie’s formula parameters affects water saturation values rigorously. Determination of Archie’s parameters a, m, and n is proceeded by three conventional techniques, Core Archie-Parameter Estimation (CAPE) and 3-D. This work introduces the hybrid system of parallel self-organizing neural network (PSONN) targeting accepted values of Archie’s parameters and, consequently, reliable water saturation values. This work focuses on Archie’s parameters determination techniques; conventional technique, CAPE technique, and 3-D technique, and then the calculation of water saturation using current. Using the same data, a hybrid parallel self-organizing neural network (PSONN) algorithm is used to estimate Archie’s parameters and predict water saturation. Results have shown that estimated Arche’s parameters m, a, and n are highly accepted with statistical analysis, indicating that the PSONN model has a lower statistical error and higher correlation coefficient. This study was conducted using a high number of measurement points for 144 core plugs from a sandstone reservoir. PSONN algorithm can provide reliable water saturation values, and it can supplement or even replace the conventional techniques to determine Archie’s parameters and thereby calculate water saturation profiles.

Keywords: water saturation, Archie’s parameters, artificial intelligence, PSONN, sandstone reservoir

Procedia PDF Downloads 128

Authors: Gauravi Agarkar, Mahendra Rai

Abstract:

Fungi are closely associated with the plants in various types of interactions such as mycorrhizal, parasitic or endophytic. Some of these interactions are beneficial and a few are harmful to the host plants. It has been suggested that these plant-associated fungi are able to change their lifestyle abd this means endophyte may become parasite or vice versa. This phenomenon may have profound effect on plant-fungal interactions and various ecological niches. Therefore, it is necessary to identify the factors that trigger the change in fungal lifestyle and understand whether these different lifestyles are interconnected at some points either by physiological, biochemical or molecular routes. This review summarizes the factors affecting plant fungal interactions and discusses the possible mechanisms for lifestyles switching of fungi based on available experimental evidences. Research should be boosted in this direction to fetch more advantages in future and to avoid the severe consequences in agriculture and other related fields.

Keywords: endophytic, lifestyle switching, mycorrhizal, parasitic, plant-fungal interactions

Procedia PDF Downloads 415

Authors: Morinta Rosandini

Abstract:

Bima Tembe is an excellent sample of cultural artifact that many people regard it as: (1) manufactured by a traditional techniques, (2) contained with variety forms and great philosophical motifs, and (3) having valued functions related to women status in the society. This research examined elements of Bima Tembe and their relations and one of the usage of tembe, named Rimpus. The elements include: (1) the traditional techniques of making Bima Tembe, (2) the variety forms (3) and philosophical motifs of Bima Tembe. Rimpu, is a cultural women clothes in Bima, which use Bima Tembe as a main part. From this reseacrh found that the Bima Tembe made by weaving technique using a traditional loom, and has two types of Tembe; Tembe Istana and Tembe Rakyat, with various motif each type. The The usage of Rimpu is as a symbol of the obedience to God and the type of Rimpu indicate the women status in the society.

Keywords: bima, tembe, rimpu, clothes

Procedia PDF Downloads 421

Authors: Alaaeddeen M. Seufi

Abstract:

Many have been published on therapeutic derivatives from living organisms including insects. In addition to traditional maggot therapy, more than 900 therapeutic products were isolated from insects. Most people look at insects as enemies and others believe that insects are friends. Many beneficial insects rather than Honey Bees, Silk Worms and Shellac insect could insure human-insect friendship. In addition, insects could be MicroFactories, Biosensors or Bioreactors. InsectFarm is an amazing example of the applied research that transfers insects from laboratory to market by Prof Mircea Ciuhrii and co-workers. They worked for 18 years to derive therapeutics from insects. Their research resulted in production of more than 30 commercial medications derived from insects (e.g. Imunomax, Noblesse, etc.). Two general approaches were followed to discover drugs from living organisms. Some laboratories preferred biochemical approach to purify components of the innate immune system of insects and insect metabolites as well. Then the purified components could be tested for many therapeutic trials. Other researchers preferred molecular approach based on proteomic studies. Components of the innate immune system of insects were then tested for their medical activities. Our Laboratory team preferred to induce insect immune system (using oral, topical and injection routes of administration), then a transcriptomic study was done to discover the induced genes and to identify specific biomarkers that can help in drug discovery. Biomarkers play an important role in medicine and in drug discovery and development as well. Optimum biomarker development and application will require a team approach because of the multifaceted nature of biomarker selection, validation, and application. This team uses several techniques such as pharmacoepidemiology, pharmacogenomics, and functional proteomics; bioanalytical development and validation; modeling and simulation to improve and refine drug development. Our Achievements included the discovery of four components of the innate immune system of Spodoptera littoralis and Musca domestica. These components were designated as SpliDef (defesin), SpliLec (lectin), SpliCec (cecropin) and MdAtt (attacin). SpliDef, SpliLec and MdAtt were confirmed as antimicrobial peptides, while SpliCec was additionally confirmed as anticancer peptide. Our current research is going on to achieve something in antioxidants and anticoagulants from insects. Our perspective is to achieve something in the mass production of prototypes of our products and to reach it to the commercial level. These achievements are the integrated contributions of everybody in our team staff.

Keywords: AMPs, insect, innate immunitty, therappeutics

Procedia PDF Downloads 370

Authors: Benyam Zenebe, Tesfaye Sisay, Gurja Belay, Workabeba Abebe

Abstract:

Background: The prevalence and antibiogram of pathogenic E. coli strains, which cause diarrhea vary from region to region, and even within countries in the same geographical area. In Ethiopia, diagnostic approaches to E. coli induced diarrhea in children less than five years of age are not standardized. The aim of this study was to determine the involvement of pathogenic E. coli strains in child diarrhea and determine the antibiograms of the isolates in children less than 5 years of age with diarrhea at Addis Ababa University College of Health Sciences TikurAnbessa Specialized Hospital, Addis Ababa, Ethiopia. Methods: A purposive study that included 98 diarrheic children less than five years of age was conducted at Addis Ababa University College of Health Sciences, TikurAnbessa Specialized Hospital, Addis Ababa, Ethiopia to detect pathogenic E. coli biotypes. Stool culture was used to identify presumptive E. coliisolates. Presumptive isolates were confirmed by biochemical tests, and antimicrobial susceptibility tests were performed on confirmed E. coli isolates by the disk diffusion method. DNA was extracted from confirmed isolates by a heating method and subjected to Polymerase Chain Reaction or the presence of virulence genes. Amplified PCR products were analyzed by agarose gel electrophoresis. Data were collected on child demographics and clinical conditions using administered questionnaires. The prevalence of E. coli strains from the total diarrheic children, and the prevalence of pathogenic strains from total E. coli isolates along with their susceptibility profiles; the distribution of pathogenic E.coli biotypes among different age groups and between the sexes were determined by using descriptive statistics. Result: Out of 98 stool specimens collected from diarrheic children less than 5 years of age, 75 presumptive E. coli isolates were identified by culture; further confirmation by biochemical tests showed that only 56 of the isolates were E. coli; 29 of the isolates were found in male children and 27 of them in female children. Out of the 58 isolates of E. coli, 25 pathotypes belonging to different classes of pathogenic strains: STEC, EPEC, EHEC, EAEC were detected by using the PCR technique. Pathogenic E. coli exhibited high rates of antibiotic resistance to many of the antibiotics tested. Moreover, they exhibited multiple drug resistance. Conclusion: This study found that the isolation rate of E. coli and the involvement of antibiotic-resistant pathogenic E. coli in diarrheic children is prominent, and hence focus should be given on the diagnosis and antimicrobial sensitivity testing of pathogenic E. coli at Addis Ababa University College of Health Sciences TikurAnbessa Specialized Hospital. Among antibiotics tested, Cefotitan could be a drug of choice to treat E. coli.

Keywords: antibiotic susceptibility profile, children, diarrhea, E. coli, pathogenic

Procedia PDF Downloads 234

Authors: Nader Al-Rashidi, David Greenhalgh

Abstract:

Mathematical modelling techniques are now being used by health organizations worldwide to help understand the likely impact that intervention strategies treatment options and combinations of these have on the prevalence and incidence of hepatitis C virus (HCV) in the people who inject drugs (PWID) population. In this poster, we develop a deterministic, compartmental mathematical model to approximate the spread of the HCV in a PWID population that has been divided into two groups by time since onset of injection. The model assumes that after injection needles adopt the most infectious state of their previous state or that of the PWID who last injected with them. Using analytical techniques, we find that the model behaviour is determined by the basic reproductive number R₀, where R₀ = 1 is a critical threshold separating two different outcomes. The disease-free equilibrium is globally stable if R₀ ≤ 1 and unstable if R₀ > 1. Additionally, we make some simulations where have confirmed that the model tends to this endemic equilibrium value with realistic parameter values giving an HCV prevalence.

Keywords: hepatitis C, people who inject drugs, HCV, PWID

Procedia PDF Downloads 144

Authors: Walid S. Alfuhaid, Saud A. Alghamdi, John M. Watkins, M. Edwin Sawan

Abstract:

Designing a controller for stochastic decentralized interconnected large scale systems usually involves a high degree of complexity and computation ability. Noise, observability, and controllability of all system states, connectivity, and channel bandwidth are other constraints to design procedures for distributed large scale systems. The quasi-steady state model investigated in this paper is a reduced order model of the original system using singular perturbation techniques. This paper results in an optimal control synthesis to design an observer based feedback controller by standard stochastic control theory techniques using Linear Quadratic Gaussian (LQG) approach and Kalman filter design with less complexity and computation requirements. Numerical example is given at the end to demonstrate the efficiency of the proposed method.

Keywords: decentralized, optimal control, output, singular perturb

Procedia PDF Downloads 370

Authors: K. Majumdar, S. Datta

Abstract:

Electricity is recognized as fundamental to industrialization and improving the quality of life of the people. Harnessing the immense untapped hydropower potential in Tripura region opens avenues for growth and provides an opportunity to improve the well-being of the people of the region, while making substantial contribution to the national economy. Gumti hydro power plant generates power to mitigate the crisis of power in Tripura, India. The first unit of hydro power plant (5 MW) was commissioned in June 1976 & another two units of 5 MW was commissioned simultaneously. But out of 15 MW capacity at present only 8-9 MW power is produced from Gumti hydro power plant during rainy season. But during lean season the production reduces to 0.5 MW due to shortage of water. Now, it is essential to implement some mitigation measures so that the further atrocities can be prevented and originality will be possible to restore. The decision making ability of the Analytic Hierarchy Process (AHP) and Concordance Analysis Techniques (CAT) are utilized to identify the better decision or solution to the present problem. Some related attributes are identified by the method of surveying within the experts and the available reports and literatures. Similar criteria are removed and ultimately seven relevant ones are identified. All the attributes are compared with each other and rated accordingly to their importance over the other with the help of Pair wise Comparison Matrix. In the present investigation different mitigation measures are identified and compared to find the best suitable alternative which can solve the present uncertainties involving the existence of the Gumti Hydro Power Plant.

Keywords: concordance analysis techniques, analytic hierarchy process, hydro power

Procedia PDF Downloads 354

Authors: Ying Ying Liu, Austin Cooke, Parimala Thulasiraman

Abstract:

Internet of Things (IoT) has attracted a recent spark in research on Internet of Vehicles (IoV). In this paper, we focus on one research area in IoV: preserving location privacy of vehicle data. We discuss existing location privacy preserving techniques and provide a scheme for evaluating these techniques under IoV traffic condition. We propose a different strategy in applying Differential Privacy using k-d tree data structure to preserve location privacy and experiment on real world Gowalla data set. We show that our strategy produces differentially private data, good preservation of utility by achieving similar regression accuracy to the original dataset on an LSTM (Long Term Short Term Memory) neural network traffic predictor.

Keywords: differential privacy, internet of things, internet of vehicles, location privacy, privacy preservation scheme

Procedia PDF Downloads 179

Authors: Suleiman Obeidat, Nabeel Mandahawi

Abstract:

In this work, the packaging process for a move is improved. The customers of this move need their household stuff to be moved from their current house to the new one with minimum damage, in an organized manner, on time and with the minimum cost. Our goal was to improve the process between 10% and 20% time efficiency, 90% reduction in damaged parts and an acceptable improvement in the cost of the total move process. The expected ROI was 833%. Many improvement techniques have been used in terms of the way the boxes are prepared, their preparation cost, packing the goods, labeling them and moving them to a place for moving out. DMAIC technique is used in this work: SIPOC diagram, value stream map of “As Is” process, Root Cause Analysis, Maps of “Future State” and “Ideal State” and an Improvement Plan. A value of ROI=624% is obtained which is lower than the expected value of 833%. The work explains the techniques of improvement and the deficiencies in the old process.

Keywords: packaging, lean tools, six sigma, DMAIC methodology, SIPOC

Procedia PDF Downloads 428

Authors: Noura Al Akkari, Aurélie Foucquier, Sylvain Lespinats

Abstract:

Load monitoring is a management process for energy consumption towards energy savings and energy efficiency. Non Intrusive Load Monitoring (NILM) is one method of load monitoring used for disaggregation purposes. NILM is a technique for identifying individual appliances based on the analysis of the whole residence data retrieved from the main power meter of the house. Our NILM framework starts with data acquisition, followed by data preprocessing, then event detection, feature extraction, then general appliance modeling and identification at the final stage. The event detection stage is a core component of NILM process since event detection techniques lead to the extraction of appliance features. Appliance features are required for the accurate identification of the household devices. In this research work, we aim at developing a new event detection methodology with accurate load disaggregation to extract appliance features. Time-domain features extracted are used for tuning general appliance models for appliance identification and classification steps. We use unsupervised algorithms such as Dynamic Time Warping (DTW). The proposed method relies on detecting areas of operation of each residential appliance based on the power demand. Then, detecting the time at which each selected appliance changes its states. In order to fit with practical existing smart meters capabilities, we work on low sampling data with a frequency of (1/60) Hz. The data is simulated on Load Profile Generator software (LPG), which was not previously taken into consideration for NILM purposes in the literature. LPG is a numerical software that uses behaviour simulation of people inside the house to generate residential energy consumption data. The proposed event detection method targets low consumption loads that are difficult to detect. Also, it facilitates the extraction of specific features used for general appliance modeling. In addition to this, the identification process includes unsupervised techniques such as DTW. To our best knowledge, there exist few unsupervised techniques employed with low sampling data in comparison to the many supervised techniques used for such cases. We extract a power interval at which falls the operation of the selected appliance along with a time vector for the values delimiting the state transitions of the appliance. After this, appliance signatures are formed from extracted power, geometrical and statistical features. Afterwards, those formed signatures are used to tune general model types for appliances identification using unsupervised algorithms. This method is evaluated using both simulated data on LPG and real-time Reference Energy Disaggregation Dataset (REDD). For that, we compute performance metrics using confusion matrix based metrics, considering accuracy, precision, recall and error-rate. The performance analysis of our methodology is then compared with other detection techniques previously used in the literature review, such as detection techniques based on statistical variations and abrupt changes (Variance Sliding Window and Cumulative Sum).

Keywords: general appliance model, non intrusive load monitoring, events detection, unsupervised techniques;

Procedia PDF Downloads 82

Authors: Ekaterina S. Marchenko, Gulsharat A. Baigonakova, Kirill M. Dubovikov, Igor A. Khlusov

Abstract:

NiTi alloys combine biomechanical and biochemical properties. This makes them a perfect candidate for medical applications. However, there is a serious problem with these alloys, such as the release of Ni from the matrix. Ni ions are known to be toxic to living tissues and leach from the matrix into the surrounding implant tissues due to corrosion after prolonged use. To prevent the release of Ni ions, corrosive strong coatings are usually used. Titanium nitride-based coatings are perfect corrosion inhibitors and also have good bioactive properties. However, there is an opportunity to improve the biochemical compatibility of the surface by depositing another layer. This layer can consist of elements such as calcium and phosphorus. The Ca and P ions form different calcium phosphate phases, which are present in the mineral part of human bones. We therefore believe that these elements must promote osteogenesis and osteointegration. In view of the above, the aim of this study is to investigate the effect of crystallinity on the biocompatibility of a two-layer coating deposited on NiTi substrate by sputtering. The first step of the research, apart from the NiTi polishing, is the layer-by-layer deposition of Ti-Ni-Ti by magnetron sputtering and the subsequent synthesis of this composite in an N atmosphere at 900 °C. The total thickness of the corrosion resistant layer is 150 nm. Plasma assisted RF sputtering was then used to deposit a bioactive film on the titanium nitride layer. A Ca-P powder target was used to obtain such a film. We deposited three types of Ca-P layers with different crystallinity and compared them in terms of cytotoxicity. One group of samples had no Ca-P coating and was used as a control. We obtained different crystallinity by varying the sputtering parameters such as bias voltage, plasma source current and pressure. XRD analysis showed that all coatings are calcium phosphate, but the sample obtained at maximum bias and plasma source current and minimum pressure has the most intense peaks from the coating phase. SEM and EDS showed that all three coatings have a homogeneous and dense structure without cracks and consist of calcium, phosphorus and oxygen. Cytotoxic tests carried out on three types of samples with Ca-P coatings and a control group showed that the control sample and the sample with Ca-P coating obtained at maximum bias voltage and plasma source current and minimum pressure had the lowest number of dead cells on the surface, around 11 ± 4%. Two other types of samples with Ca-P coating have 40 ± 9% and 21 ± 7% dead cells on the surface. It can therefore be concluded that these two sputtering modes have a negative effect on the corrosion resistance of the whole samples. The third sputtering mode does not affect the corrosion resistance and has the same level of cytotoxicity as the control. It can be concluded that the most suitable sputtering mode is the third with maximum bias voltage and plasma source current and minimum pressure.

Keywords: calcium phosphate coating, cytotoxicity, NiTi alloy, two-layer coating

Procedia PDF Downloads 66