Search results for: treatment based on acceptance and commitment
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 35510

Search results for: treatment based on acceptance and commitment

28850 The Impact of Nutritional Education for Peritoneal Dialysis Patients in Mongolia

Authors: Sanchir Erdenebayar, Namuuntsetseg Oyunbaatar

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Objectives: Peritoneal dialysis treatment is one of the important forms of kidney replacement therapy, and it has recently developed instantly in Mongolia for the past five years. Currently, more than 120 patients undergo peritoneal dialysis nationwide. These patients lack nutritional education, which predisposes them to protein deficiency and further impairs their quality of life. However, there is no study which is conducted among those about their dietary in Mongolia. Therefore, integrated nutrition information and educating them about dietary patterns to follow are urgently needed for PD patients. Methods: A cross-sectional study was carried out on 45 patients aged between 18 and 60 years who were undergoing CAPD at the biggest Medvic dialysis center in Ulaanbaatar. The knowledge of nutrition and food intake is assessed by interview based on a validated questionnaire prepared from KDIGO guidelines, semi-FFQ and a 24-hour dietary recall method. In addition, a biochemical blood test that includes total protein, albumin, calcium, phosphorus, potassium, and hemoglobin is used for an assessment of the patient’s current nutritional status. Results: Knowledge of nutritional status for CAPD was great, with 21.4% of patients and 78.65% having poor nutrition knowledge. The rate of mild to moderate malnutrition was 48.8% among research participants. Serum albumin was 38.4 ± 4.7 g/L, and total protein was 67.3±7.5g/l. Patients met 62.5± 26.5% of their daily intake nutritional requirement for calories and 72±40% of their nutritional requirement for protein. All patients’ energy intake was significantly /1328±304kcal/ lower than the energy requirement (2124±378kcal). Only 14.2% met the recommended dietary protein intake recommended to them of greater than 1.2 g/kg. Conclusions: As was established before, nutritional education has a vital positive impact on the health and nutritional status of peritoneal dialysis patients. The results of this study show that nutritional education programs are not enough adequate in peritoneal dialysis patients. There is a crucial priority to establish nutritional educational programs and guidelines for PD patients in Mongolia.

Keywords: renal diet, peritoneal dialysis, nutrition education, CKD diet

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28849 Self-Regulated Learning: A Required Skill for Web 2.0 Internet-Based Learning

Authors: Pieter Conradie, M. Marina Moller

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Web 2.0 Internet-based technologies have intruded all aspects of human life. Presently, this phenomenon is especially evident in the educational context, with increased disruptive Web 2.0 technology infusions dramatically changing educational practice. The most prominent of these Web 2.0 intrusions can be identified as Massive Open Online Courses (Coursera, EdX), video and photo sharing sites (Youtube, Flickr, Instagram), and Web 2.0 online tools utilize to create Personal Learning Environments (PLEs) (Symbaloo (aggregator), Delicious (social bookmarking), PBWorks (collaboration), Google+ (social networks), Wordspress (blogs), Wikispaces (wiki)). These Web 2.0 technologies have supported the realignment from a teacher-based pedagogy (didactic presentation) to a learner-based pedagogy (problem-based learning, project-based learning, blended learning), allowing greater learner autonomy. No longer is the educator the source of knowledge. Instead the educator has become the facilitator and mediator of the learner, involved in developing learner competencies to support life-long learning (continuous learning) in the 21st century. In this study, the self-regulated learning skills of thirty first-year university learners were explored by utilizing the Online Self-regulated Learning Questionnaire. Implementing an action research method, an intervention was affected towards improving the self-regulation skill set of the participants. Statistical significant results were obtained with increased self-regulated learning proficiency, positively impacting learner performance. Goal setting, time management, environment structuring, help seeking, task (learning) strategies and self-evaluation skills were confirmed as determinants of improved learner success.

Keywords: andragogy, online self-regulated learning questionnaire, self-regulated learning, web 2.0

Procedia PDF Downloads 420
28848 Comparative Analysis of Dissimilarity Detection between Binary Images Based on Equivalency and Non-Equivalency of Image Inversion

Authors: Adnan A. Y. Mustafa

Abstract:

Image matching is a fundamental problem that arises frequently in many aspects of robot and computer vision. It can become a time-consuming process when matching images to a database consisting of hundreds of images, especially if the images are big. One approach to reducing the time complexity of the matching process is to reduce the search space in a pre-matching stage, by simply removing dissimilar images quickly. The Probabilistic Matching Model for Binary Images (PMMBI) showed that dissimilarity detection between binary images can be accomplished quickly by random pixel mapping and is size invariant. The model is based on the gamma binary similarity distance that recognizes an image and its inverse as containing the same scene and hence considers them to be the same image. However, in many applications, an image and its inverse are not treated as being the same but rather dissimilar. In this paper, we present a comparative analysis of dissimilarity detection between PMMBI based on the gamma binary similarity distance and a modified PMMBI model based on a similarity distance that does distinguish between an image and its inverse as being dissimilar.

Keywords: binary image, dissimilarity detection, probabilistic matching model for binary images, image mapping

Procedia PDF Downloads 156
28847 MicroRNA Drivers of Resistance to Androgen Deprivation Therapy in Prostate Cancer

Authors: Philippa Saunders, Claire Fletcher

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INTRODUCTION: Prostate cancer is the most prevalent malignancy affecting Western males. It is initially an androgen-dependent disease: androgens bind to the androgen receptor and drive the expression of genes that promote proliferation and evasion of apoptosis. Despite reduced androgen dependence in advanced prostate cancer, androgen receptor signaling remains a key driver of growth. Androgen deprivation therapy (ADT) is, therefore, a first-line treatment approach and works well initially, but resistance inevitably develops. Abiraterone and Enzalutamide are drugs widely used in ADT and are androgen synthesis and androgen receptor signaling inhibitors, respectively. The shortage of other treatment options means acquired resistance to these drugs is a major clinical problem. MicroRNAs (miRs) are important mediators of post-transcriptional gene regulation and show altered expression in cancer. Several have been linked to the development of resistance to ADT. Manipulation of such miRs may be a pathway to breakthrough treatments for advanced prostate cancer. This study aimed to validate ADT resistance-implicated miRs and their clinically relevant targets. MATERIAL AND METHOD: Small RNA-sequencing of Abiraterone- and Enzalutamide-resistant C42 prostate cancer cells identified subsets of miRs dysregulated as compared to parental cells. Real-Time Quantitative Reverse Transcription PCR (qRT-PCR) was used to validate altered expression of candidate ADT resistance-implicated miRs 195-5p, 497-5p and 29a-5p in ADT-resistant and -responsive prostate cancer cell lines, patient-derived xenografts (PDXs) and primary prostate cancer explants. RESULTS AND DISCUSSION: This study suggests a possible role for miR-497-5p in the development of ADT resistance in prostate cancer. MiR-497-5p expression was increased in ADT-resistant versus ADT-responsive prostate cancer cells. Importantly, miR-497-5p expression was also increased in Enzalutamide-treated, castrated (ADT-mimicking) PDXs versus intact PDXs. MiR-195-5p was also elevated in ADT-resistant versus -responsive prostate cancer cells, while there was a drop in miR-29a-5p expression. Candidate clinically relevant targets of miR-497-5p in prostate cancer were identified by mining AGO-PAR-CLIP-seq data sets and may include AVL9 and FZD6. CONCLUSION: In summary, this study identified microRNAs that are implicated in prostate cancer resistance to androgen deprivation therapy and could represent novel therapeutic targets for advanced disease.

Keywords: microRNA, androgen deprivation therapy, Enzalutamide, abiraterone, patient-derived xenograft

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28846 Assessment-Assisted and Relationship-Based Financial Advising: Using an Empirical Assessment to Understand Personal Investor Risk Tolerance in Professional Advising Relationships

Authors: Jerry Szatko, Edan L. Jorgensen, Stacia Jorgensen

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A crucial component to the success of any financial advising relationship is for the financial professional to understand the perceptions, preferences and thought-processes carried by the financial clients they serve. Armed with this information, financial professionals are more quickly able to understand how they can tailor their approach to best match the individual preferences and needs of each personal investor. Our research explores the use of a quantitative assessment tool in the financial services industry to assist in the identification of the personal investor’s consumer behaviors, especially in terms of financial risk tolerance, as it relates to their financial decision making. Through this process, the Unitifi Consumer Insight Tool (UCIT) was created and refined to capture and categorize personal investor financial behavioral categories and the financial personality tendencies of individuals prior to the initiation of a financial advisement relationship. This paper discusses the use of this tool to place individuals in one of four behavior-based financial risk tolerance categories. Our discoveries and research were aided through administration of a web-based survey to a group of over 1,000 individuals. Our findings indicate that it is possible to use a quantitative assessment tool to assist in predicting the behavioral tendencies of personal consumers when faced with consumer financial risk and decisions.

Keywords: behavior-based advising, financial relationship building, risk capacity based on behavior, risk tolerance, systematic way to assist in financial relationship building

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28845 Evaluation of Antimicrobial Properties of Lactic Acid Bacteria of Enterococcus Genus

Authors: Kristina Karapetyan, Flora Tkhruni, Tsovinar Balabekyan, Arevik Israyelyan, Tatyana Khachatryan

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The ability of the lactic acid bacteria (LAB) to prevent and cure a variety of diseases, their protective role against infections and colonization of pathogenic microorganisms in the digestive tract, has lead to the coining of the term probiotics or pro-life. LAB inhibiting the growth of pathogenic and food spoilage microorganisms, maintaining the nutritive quality and improving the shelf life of foods. They have also been used as flavor and texture producers. Enterococcus strains have been used for treatment of diseases such as diarrhea or antibiotic associated diarrhea, inflammatory pathologies that affect colon such as irritable bowel syndrome, or immune regulation, diarrhea caused by antibiotic treatments. The obtaining and investigation of biological properties of proteinoceous antibiotics, on the basis of probiotic LAB shown, that bacteriocins, metabiotics, and peptides of LAB represent bactericides have a broad range of activity and are excellent candidates for development of new prophylactic and therapeutic substances to complement or replace conventional antibiotics. The genotyping by 16S rRNA sequencing for LAB were used. Cell free culture broth (CFC) broth was purified by the Gel filtration method on the Sephadex Superfine G 25 resin. Antimicrobial activity was determined by spot-on-lawn method and expressed in arbitrary units (AU/ml). The diversity of multidrug-resistance (MDR) of pathogenic strains to antibiotics, most widely used for treatment of human diseases in the Republics of Armenia and Nagorno Karabakh were examined. It was shown, that difference of resistance of pathogens to antibiotics depends on their isolation sources. The influences of partially purified antimicrobial preparations (AMP), obtained from the different strains of Enterococcus genus on the growth of MDR pathogenic bacteria were investigated. It was shown, that bacteriocin containing partially purified preparations, obtained from different strains of Enterococcus faecium and durans species, possess bactericidal or bacteriostatic activity against antibiotic resistant intestinal, spoilage and food-borne pathogens such as Listeria monocytogenes, Staphylococcus aureus, E. coli, and Salmonella. Endemic strains of LAB, isolated from Matsoni made from donkey, buffalo and goat milk, shown broad spectrum of activity against food spoiling microorganisms, moulds and fungi, such as Salmonella sp., Esherichia coli, Aspergillus and Penicillium species. Highest activity against MDR pathogens shown bacteria, isolated from goat milk products. High stability of the investigated strains of the genus Enerococcus, isolated from samples of matsun from different regions of Nagorno-Karabakh (NKR) to the antibiotics was shown. The obtained data show high stability of the investigated different strains of the genus Enerococcus. The high genetic diversity in Enterococcus group suggests adaptations for specific mutations in different environments. Thus, endemic strains of LAB are able to produce bacteriocins with high and different inhibitory activity against broad spectrum of microorganisms isolated from different sources and belong to different taxonomic group. Prospect of the use of certain antimicrobial preparations against pathogenic strains is obvious. These AMP can be applied for long term use against different etiology antibiotic resistant pathogens for prevention or treatment of infectional diseases as an alternative to antibiotics.

Keywords: antimicrobial biopreparation, endemic lactic acid bacteria, intra-species diversity, multidrug resistance of pathogens

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28844 Arabic Lexicon Learning to Analyze Sentiment in Microblogs

Authors: Mahmoud B. Rokaya

Abstract:

The study of opinion mining and sentiment analysis includes analysis of opinions, sentiments, evaluations, attitudes, and emotions. The rapid growth of social media, social networks, reviews, forum discussions, microblogs, and Twitter, leads to a parallel growth in the field of sentiment analysis. The field of sentiment analysis tries to develop effective tools to make it possible to capture the trends of people. There are two approaches in the field, lexicon-based and corpus-based methods. A lexicon-based method uses a sentiment lexicon which includes sentiment words and phrases with assigned numeric scores. These scores reveal if sentiment phrases are positive or negative, their intensity, and/or their emotional orientations. Creation of manual lexicons is hard. This brings the need for adaptive automated methods for generating a lexicon. The proposed method generates dynamic lexicons based on the corpus and then classifies text using these lexicons. In the proposed method, different approaches are combined to generate lexicons from text. The proposed method classifies the tweets into 5 classes instead of +ve or –ve classes. The sentiment classification problem is written as an optimization problem, finding optimum sentiment lexicons are the goal of the optimization process. The solution was produced based on mathematical programming approaches to find the best lexicon to classify texts. A genetic algorithm was written to find the optimal lexicon. Then, extraction of a meta-level feature was done based on the optimal lexicon. The experiments were conducted on several datasets. Results, in terms of accuracy, recall and F measure, outperformed the state-of-the-art methods proposed in the literature in some of the datasets. A better understanding of the Arabic language and culture of Arab Twitter users and sentiment orientation of words in different contexts can be achieved based on the sentiment lexicons proposed by the algorithm.

Keywords: social media, Twitter sentiment, sentiment analysis, lexicon, genetic algorithm, evolutionary computation

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28843 Demand for Index Based Micro-Insurance (IBMI) in Ethiopia

Authors: Ashenafi Sileshi Etefa, Bezawit Worku Yenealem

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Micro-insurance is a relatively new concept that is just being introduced in Ethiopia. For an agrarian economy dominated by small holder farming and vulnerable to natural disasters, mainly drought, the need for an Index-Based Micro Insurance (IBMI) is crucial. Since IBMI solves moral hazard, adverse selection, and access issues to poor clients, it is preferable over traditional insurance products. IBMI is being piloted in drought prone areas of Ethiopia with the aim of learning and expanding the service across the country. This article analyses the demand of IBMI and the barriers to demand and finds that the demand for IBMI has so far been constrained by lack of awareness, trust issues, costliness, and the level of basis risk; and recommends reducing the basis risk and increasing the role of government and farmer cooperatives.

Keywords: agriculture, index based micro-insurance (IBMI), drought, micro-finance institution (MFI)

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28842 Prevalence of Rituximab Efficacy Over Immunosuppressants in Therapy of Systemic Sclerosis

Authors: Liudmila Garzanova, Lidia Ananyeva, Olga Koneva, Olga Ovsyannikova, Oxana Desinova, Mayya Starovoytova, Rushana Shayahmetova, Anna Khelkovskaya-Sergeeva

Abstract:

Abstract Objectives. Rituximab (RTX) shown a positive effect in the treatment of systemic sclerosis (SSc). But there is still not enough data on comparing the effectiveness of RTX with immunosuppressants (IS). The aim of our study was to compare changes of lung function and skin score in SSc between two groups of patients (pts) - on RXT therapy (prescribed after ineffectiveness of previous therapy with IS) and on therapy with IS only. Methods. This study included 103 pts received RTX as an addition to previous therapy (group 1) and 65 pts received therapy with IS and prednisolone (group 2). The mean follow-up period was 12.6±10.7months. In group 1 the mean age was 47±12.9 years, female – 88 pts (84%), the diffuse cutaneous subset of the disease had 55 pts (53%). The mean disease duration was 6.2±5.5 years. 82% pts had interstitial lung disease (ILD) and 92% were positive for ANA, 67% of them were positive for antitopoisomerase-1. All pts received prednisolone at a dose of 11.3±4.5 mg/day, IS at inclusion received 47% of them. The cumulative mean dose of RTX was 1.7±0.6 g. In group 2 the mean age was 50.8±13.8 years, female-53 pts (82%), the diffuse cutaneous subset of the disease had 44 pts (68%). The mean disease duration was 8.8±7.7 years. 81% pts had ILD and 88% were positive for ANA, 58% of them were positive for antitopoisomerase-1. All pts received prednisolone at a dose of 8.69±4.28 mg/day, IS received 57% of them. Cyclophosphamide (CP) received 45% of pts. The cumulative mean dose of CP was 10.2±15.1g. D-penicillamine received 30% of pts. Other pts was on mycophenolate mofetil or methotrexate therapy in single cases. The pts of the compared groups did not differ in the main demographic and clinical parameters. The results are presented as delta (Δ) - difference between the baseline parameter and follow up point. Results. In group 1 there was an improvement of all outcome parameters: increased of forced vital capacity, % predicted - ΔFVC=4% (p=0.0004); Diffusing capacity for carbon monoxide, % predicted remained stable (ΔDLCO=0.1%); improvement of the Rodnan skin score-ΔmRss=3.4 (p=0.001); decrease of Activity index (EScSG-AI) - ΔActivity index=1.7 (p=0.001). In group 2 the changes was insignificant: ΔFVC=-2.3%, ΔmRss=0.87, ΔActivity index=0.3. But there was a significant decrease of DLCO: ΔDLCO=-5.1% (p=0.001). Conclusion. The results of our study confirm the data on the positive effect of RTX in complex therapy in pts with SSc (decrease of skin induration, increase of FVC, stabilization of DLCO). Meantime, pts on IS and prednisolone therapy shown the worsening of lung function and insignificant changes of other clinical parameters. RTX could be considered as a more effective option in complex treatment of SSc in comparison with IS therapy

Keywords: immunosuppressants, interstitial lung disease, systemic sclerosis, rituximab

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28841 Scalable Learning of Tree-Based Models on Sparsely Representable Data

Authors: Fares Hedayatit, Arnauld Joly, Panagiotis Papadimitriou

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Many machine learning tasks such as text annotation usually require training over very big datasets, e.g., millions of web documents, that can be represented in a sparse input space. State-of the-art tree-based ensemble algorithms cannot scale to such datasets, since they include operations whose running time is a function of the input space size rather than a function of the non-zero input elements. In this paper, we propose an efficient splitting algorithm to leverage input sparsity within decision tree methods. Our algorithm improves training time over sparse datasets by more than two orders of magnitude and it has been incorporated in the current version of scikit-learn.org, the most popular open source Python machine learning library.

Keywords: big data, sparsely representable data, tree-based models, scalable learning

Procedia PDF Downloads 270
28840 Combining the Dynamic Conditional Correlation and Range-GARCH Models to Improve Covariance Forecasts

Authors: Piotr Fiszeder, Marcin Fałdziński, Peter Molnár

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The dynamic conditional correlation model of Engle (2002) is one of the most popular multivariate volatility models. However, this model is based solely on closing prices. It has been documented in the literature that the high and low price of the day can be used in an efficient volatility estimation. We, therefore, suggest a model which incorporates high and low prices into the dynamic conditional correlation framework. Empirical evaluation of this model is conducted on three datasets: currencies, stocks, and commodity exchange-traded funds. The utilisation of realized variances and covariances as proxies for true variances and covariances allows us to reach a strong conclusion that our model outperforms not only the standard dynamic conditional correlation model but also a competing range-based dynamic conditional correlation model.

Keywords: volatility, DCC model, high and low prices, range-based models, covariance forecasting

Procedia PDF Downloads 192
28839 Analysis of the Movie “Life and a Day”

Authors: Mehravar Javid, Katherine Marshall Woods, Joseph Kosowsky, Anna Missner

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In this paper, "Life and a Day" is analyzed psychoanalytically with an emphasis on the ways by which addiction is influenced by personal psychology and familial ties. It explores the influence of parenting on one's sense of self and the function of therapeutic alliances in the treatment of addiction. The analysis also observes the main characters, with a special emphasis on Somayeh, who represents the continuation of her father's role in the family and faces identity and autonomy issues in the face of familial responsibilities. In addressing addiction, the document emphasizes the significance of comprehending family dynamics and individual psychological factors, emphasizing the interaction between personal trauma, family roles, and recovery.

Keywords: addiction, autonomy, family dynamics, identity, life and a day, psychoanalytic

Procedia PDF Downloads 98
28838 Investigation and Optimization of DNA Isolation Efficiency Using Ferrite-Based Magnetic Nanoparticles

Authors: Tímea Gerzsenyi, Ágnes M. Ilosvai, László Vanyorek, Emma Szőri-Dorogházi

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DNA isolation is a crucial step in many molecular biological applications for diagnostic and research purposes. However, traditional extraction requires toxic reagents, and commercially available kits are expensive, this leading to the recently wide-spread method, the magnetic nanoparticle (MNP)-based DNA isolation. Different ferrite containing MNPs were examined and compared in their plasmid DNA isolation efficiency. Among the tested MNPs, one has never been used for the extraction of plasmid molecules, marking a distinct application. pDNA isolation process was optimized for each type of nanoparticle and the best protocol was selected based on different criteria: DNA quantity, quality and integrity. With the best-performing magnetic nanoparticle, which excelled in all aspects, further tests were performed to recover genomic DNA from bacterial cells and a protocol was developed.

Keywords: DNA isolation, nanobiotechnology, magnetic nanoparticles, protocol optimization, pDNA, gDNA

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28837 A Review on the Use of Herbal Alternatives to Antibiotics in Poultry Diets

Authors: Sasan Chalaki, Seyed Ali Mirgholange, Touba Nadri, Saman Chalaki

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In the current world, proper poultry nutrition has garnered special attention as one of the fundamental factors for enhancing their health and performance. Concerns related to the excessive use of antibiotics in the poultry industry and their role in antibiotic resistance have transformed this issue into a global challenge in public health and the environment. On the other hand, poultry farming plays a vital role as a primary source of meat and eggs in human nutrition, and improving their health and performance is crucial. One effective approach to enhance poultry nutrition is the utilization of the antibiotic properties of plant-based ingredients. The use of plant-based alternatives as natural antibiotics in poultry nutrition not only aids in improving poultry health and performance but also plays a significant role in reducing the consumption of synthetic antibiotics and preventing antibiotic resistance-related issues. Plants contain various antibacterial compounds, such as flavonoids, tannins, and essential oils. These compounds are recognized as active agents in combating bacteria. Plant-based antibiotics are compounds extracted from plants with antibacterial properties. They are acknowledged as effective substitutes for chemical antibiotics in poultry diets. The advantages of plant-based antibiotics include reducing the risk of resistance to chemical antibiotics, increasing poultry growth performance, and lowering the risk of disease transmission.

Keywords: poultry, antibiotics, essential oils, plant-based

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28836 Bridge Health Monitoring: A Review

Authors: Mohammad Bakhshandeh

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Structural Health Monitoring (SHM) is a crucial and necessary practice that plays a vital role in ensuring the safety and integrity of critical structures, and in particular, bridges. The continuous monitoring of bridges for signs of damage or degradation through Bridge Health Monitoring (BHM) enables early detection of potential problems, allowing for prompt corrective action to be taken before significant damage occurs. Although all monitoring techniques aim to provide accurate and decisive information regarding the remaining useful life, safety, integrity, and serviceability of bridges, understanding the development and propagation of damage is vital for maintaining uninterrupted bridge operation. Over the years, extensive research has been conducted on BHM methods, and experts in the field have increasingly adopted new methodologies. In this article, we provide a comprehensive exploration of the various BHM approaches, including sensor-based, non-destructive testing (NDT), model-based, and artificial intelligence (AI)-based methods. We also discuss the challenges associated with BHM, including sensor placement and data acquisition, data analysis and interpretation, cost and complexity, and environmental effects, through an extensive review of relevant literature and research studies. Additionally, we examine potential solutions to these challenges and propose future research ideas to address critical gaps in BHM.

Keywords: structural health monitoring (SHM), bridge health monitoring (BHM), sensor-based methods, machine-learning algorithms, and model-based techniques, sensor placement, data acquisition, data analysis

Procedia PDF Downloads 96
28835 Case-Based Reasoning: A Hybrid Classification Model Improved with an Expert's Knowledge for High-Dimensional Problems

Authors: Bruno Trstenjak, Dzenana Donko

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Data mining and classification of objects is the process of data analysis, using various machine learning techniques, which is used today in various fields of research. This paper presents a concept of hybrid classification model improved with the expert knowledge. The hybrid model in its algorithm has integrated several machine learning techniques (Information Gain, K-means, and Case-Based Reasoning) and the expert’s knowledge into one. The knowledge of experts is used to determine the importance of features. The paper presents the model algorithm and the results of the case study in which the emphasis was put on achieving the maximum classification accuracy without reducing the number of features.

Keywords: case based reasoning, classification, expert's knowledge, hybrid model

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28834 Empirical Mode Decomposition Based Denoising by Customized Thresholding

Authors: Wahiba Mohguen, Raïs El’hadi Bekka

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This paper presents a denoising method called EMD-Custom that was based on Empirical Mode Decomposition (EMD) and the modified Customized Thresholding Function (Custom) algorithms. EMD was applied to decompose adaptively a noisy signal into intrinsic mode functions (IMFs). Then, all the noisy IMFs got threshold by applying the presented thresholding function to suppress noise and to improve the signal to noise ratio (SNR). The method was tested on simulated data and real ECG signal, and the results were compared to the EMD-Based signal denoising methods using the soft and hard thresholding. The results showed the superior performance of the proposed EMD-Custom denoising over the traditional approach. The performances were evaluated in terms of SNR in dB, and Mean Square Error (MSE).

Keywords: customized thresholding, ECG signal, EMD, hard thresholding, soft-thresholding

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28833 Determination of Cadmium and Lead in Sewage Sludge from the Middle Region (Misrata, Msallata and Tarhünah Cities) of Libya

Authors: J. A. Mayouf, Q. A. Najim, H. S. Al-Bayati

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The concentrations of cadmium and lead in sewage sludge samples were determined by Atomic Absorption Spectrometric Method. Samples of sewage sludge were obtained from three sewage treatment plants localised in Middle Region of Libya (Misrata, Msallata and Tarhünah cities). The results shows that, the mean levels of Cadmium for all regions are ranges from 81 to 123.4 ppm and these values are higher than the limitations for the international standard which are not registered more than 50 ppm (dry weight) in USA, Egypt and the EU countries. While, the lead concentrations are ranged from 8.0 to 189.2 ppm and all values are within the standard limits which graduated between (275–613) ppm.

Keywords: cadmium, lead, sewage, spectrometry

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28832 The Detection of Implanted Radioactive Seeds on Ultrasound Images Using Convolution Neural Networks

Authors: Edward Holupka, John Rossman, Tye Morancy, Joseph Aronovitz, Irving Kaplan

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A common modality for the treatment of early stage prostate cancer is the implantation of radioactive seeds directly into the prostate. The radioactive seeds are positioned inside the prostate to achieve optimal radiation dose coverage to the prostate. These radioactive seeds are positioned inside the prostate using Transrectal ultrasound imaging. Once all of the planned seeds have been implanted, two dimensional transaxial transrectal ultrasound images separated by 2 mm are obtained through out the prostate, beginning at the base of the prostate up to and including the apex. A common deep neural network, called DetectNet was trained to automatically determine the position of the implanted radioactive seeds within the prostate under ultrasound imaging. The results of the training using 950 training ultrasound images and 90 validation ultrasound images. The commonly used metrics for successful training were used to evaluate the efficacy and accuracy of the trained deep neural network and resulted in an loss_bbox (train) = 0.00, loss_coverage (train) = 1.89e-8, loss_bbox (validation) = 11.84, loss_coverage (validation) = 9.70, mAP (validation) = 66.87%, precision (validation) = 81.07%, and a recall (validation) = 82.29%, where train and validation refers to the training image set and validation refers to the validation training set. On the hardware platform used, the training expended 12.8 seconds per epoch. The network was trained for over 10,000 epochs. In addition, the seed locations as determined by the Deep Neural Network were compared to the seed locations as determined by a commercial software based on a one to three months after implant CT. The Deep Learning approach was within \strikeout off\uuline off\uwave off2.29\uuline default\uwave default mm of the seed locations determined by the commercial software. The Deep Learning approach to the determination of radioactive seed locations is robust, accurate, and fast and well within spatial agreement with the gold standard of CT determined seed coordinates.

Keywords: prostate, deep neural network, seed implant, ultrasound

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28831 Phytochemical Investigation of Berries of the Embelia schimperi Plant

Authors: Tariku Nefo Duke

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Embelia is a genus of climbing shrubs in the family Myrsinaceae. Embelia schimperi is as important in traditional medicine as the other species in the genus. The plant has been much known as a local medicine for the treatment of tapeworms. In this project, extraction, phytochemical screening tests, isolation, and characterization of berries of the Embelia schimperi plant have been conducted. The chemical investigations of methanol and ethyl acetate (1:1) ratio extracts of the berries lead to the isolation of three new compounds. The compounds were identified to be alkaloids coded as AD, AN, and AG. Structural elucidations of the isolated compounds were accomplished using spectroscopic methods (IR, UV, ¹H NMR, ¹³C NMR, DEPT and 2D NMR, HPLC, and LC-MS). The alkaloid coded as (AN) has a wide MIC range of 6.31-25.46 mg/mL against all tested bacteria strains.

Keywords: Embelia schimper, HPLC, alkaloids, 2D NMR, MIC

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28830 Rank-Based Chain-Mode Ensemble for Binary Classification

Authors: Chongya Song, Kang Yen, Alexander Pons, Jin Liu

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In the field of machine learning, the ensemble has been employed as a common methodology to improve the performance upon multiple base classifiers. However, the true predictions are often canceled out by the false ones during consensus due to a phenomenon called “curse of correlation” which is represented as the strong interferences among the predictions produced by the base classifiers. In addition, the existing practices are still not able to effectively mitigate the problem of imbalanced classification. Based on the analysis on our experiment results, we conclude that the two problems are caused by some inherent deficiencies in the approach of consensus. Therefore, we create an enhanced ensemble algorithm which adopts a designed rank-based chain-mode consensus to overcome the two problems. In order to evaluate the proposed ensemble algorithm, we employ a well-known benchmark data set NSL-KDD (the improved version of dataset KDDCup99 produced by University of New Brunswick) to make comparisons between the proposed and 8 common ensemble algorithms. Particularly, each compared ensemble classifier uses the same 22 base classifiers, so that the differences in terms of the improvements toward the accuracy and reliability upon the base classifiers can be truly revealed. As a result, the proposed rank-based chain-mode consensus is proved to be a more effective ensemble solution than the traditional consensus approach, which outperforms the 8 ensemble algorithms by 20% on almost all compared metrices which include accuracy, precision, recall, F1-score and area under receiver operating characteristic curve.

Keywords: consensus, curse of correlation, imbalance classification, rank-based chain-mode ensemble

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28829 Estimation of Antiurolithiatic Activity of a Biochemical Medicine, Magnesia phosphorica, in Ethylene Glycol-Induced Nephrolithiasis in Wistar Rats by Urine Analysis, Biochemical, Histopathological, and Electron Microscopic Studies

Authors: Priti S. Tidke, Chandragouda R. Patil

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The present study was designed to investigate the effect of Magnesia phosphorica, a biochemical medicine on urine screeing, biochemical, histopathological, and electron microscopic images in ethylene glycol induced nepholithiasis in rats.Male Wistar albino rats were divided into six groups and were orally administered saline once daily (IR-sham and IR-control) or Magnesia phosphorica 100 mg/kg twice daily for 24 days.The effect of various dilutions of biochemical Mag phos3x, 6x, 30x was determined on urine output by comparing the urine volume collected by keeping individual animals in metabolic cages. Calcium oxalate urolithiasis and hyperoxaluria in male Wistar rats was induced by oral administration of 0.75% Ethylene glycol p.o. daily for 24 days. Simultaneous administration of biochemical 3x, 6x, 30xMag phos (100mg/kg p.o. twice a day) along with ethylene glycol significantly decreased calcium oxalate, urea, creatinine, Calcium, Magnesium, Chloride, Phosphorus, Albumin, Alkaline Phosphatase content in urine compared with vehicle-treated control group.After the completion of treatment period animals were sacrificed, kidneys were removed and subjected to microscopic examination for possible stone formation. Histological estimation of kidney treated with biochemical Mag phos (3x, 6x, 30xMag phos 100 mg/kg, p.o.) along with ethylene glycol inhibited the growth of calculi and reduced the number of stones in kidney compared with control group. Biochemical Mag phos of 3x dilution and its crude equivalent also showed potent diuretic and antiurolithiatic activity in ethylene glycol induced urolithiasis. A significant decrease in the weight of stones was observed after treatment in animals which received biochemical Mag phos of 3x dilution and its crude equivalent in comparison with control groups. From this study, it can be proposed that the 3x dilution of biochemical Mag phos exhibits a significant inhibitory effect on crystal growth, with the improvement of kidney function and substantiates claims on the biological activity of twelve tissue remedies which can be proved scientifically through laboratory animal studies.

Keywords: Mag phos, Magnesia phosphorica, ciochemic medicine, urolithiasis, kidney stone, ethylene glycol

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28828 Impact of Gamma Irradiation on Biological Activities of Artemisia herba alba from Algeria

Authors: Abir Mohamed Mohamed Ibrahim, Amina Titouche, Mohamed Hazzit

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Phytotherapy is based on use of plant natural products holding the main sources of drugs with healing properties for the treatment of human, animal or vegetable diseases. With these aims, and to replace chemical preservatives in natural products, we are interested to use essential oils from Algerian endemic plants belonging to the Asteraceae family: Artemisia herba alba Asso, which was undergoes a hydro-distillation after its irradiation by Gamma rays at frequencies: 10, 20, and 30 KGray which gave respectively the following essential oil yields: 1.087%, 1.087%, 1.085%, compared with that of the untreated sample giving a yield of 1.27 %. Evaluation of the antioxidant activity in vitro of essential oil for A. herba alba has been assessed by two different methods: inhibition of DPPH radical and measurement of reducing power. The first method has not revealed a very big difference regardless of the dose of irradiation, the IC50 is about 4000 mg/l, the maximum of inhibition was around 49.4%, likewise, the test of reducing power awarded us a maximum reducing capacity was of 0.76%; both of results were registered by the specimen irradiated at 20 KGy, it has a more better antioxidant power than no irradiated sample but slightly. To combat Fusarium culmorum, causing the wilts and rots, we are focused on the antifungal screening of this aromatic plant. The results obtained, followed by measurements of Minimal Inhibitory Concentrations (MIC); showed promising inhibitory effect against pathogen tested. With a yield superior to l%, the essential oil has shown a remarkable efficiency on the stump, mainly for sample irradiate at 30KGray (MICs= 625 µg/ml; MICc= 1250 µg/ml) with MIC of 2%. These results demonstrate a good antifungal activity, to limit and even to stop the development of the pathogenic microorganism and also the positive effect of dose of irradiation to upgrade this capacity as well, to uphold the antioxidant capacity.

Keywords: artemisia herba alba Asso, essential oil yield, gamma ray, antioxidant activity, antifungal activity

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28827 Design and Optimization of Open Loop Supply Chain Distribution Network Using Hybrid K-Means Cluster Based Heuristic Algorithm

Authors: P. Suresh, K. Gunasekaran, R. Thanigaivelan

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Radio frequency identification (RFID) technology has been attracting considerable attention with the expectation of improved supply chain visibility for consumer goods, apparel, and pharmaceutical manufacturers, as well as retailers and government procurement agencies. It is also expected to improve the consumer shopping experience by making it more likely that the products they want to purchase are available. Recent announcements from some key retailers have brought interest in RFID to the forefront. A modified K- Means Cluster based Heuristic approach, Hybrid Genetic Algorithm (GA) - Simulated Annealing (SA) approach, Hybrid K-Means Cluster based Heuristic-GA and Hybrid K-Means Cluster based Heuristic-GA-SA for Open Loop Supply Chain Network problem are proposed. The study incorporated uniform crossover operator and combined crossover operator in GAs for solving open loop supply chain distribution network problem. The algorithms are tested on 50 randomly generated data set and compared with each other. The results of the numerical experiments show that the Hybrid K-means cluster based heuristic-GA-SA, when tested on 50 randomly generated data set, shows superior performance to the other methods for solving the open loop supply chain distribution network problem.

Keywords: RFID, supply chain distribution network, open loop supply chain, genetic algorithm, simulated annealing

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28826 A Comparison of Neural Network and DOE-Regression Analysis for Predicting Resource Consumption of Manufacturing Processes

Authors: Frank Kuebler, Rolf Steinhilper

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Artificial neural networks (ANN) as well as Design of Experiments (DOE) based regression analysis (RA) are mainly used for modeling of complex systems. Both methodologies are commonly applied in process and quality control of manufacturing processes. Due to the fact that resource efficiency has become a critical concern for manufacturing companies, these models needs to be extended to predict resource-consumption of manufacturing processes. This paper describes an approach to use neural networks as well as DOE based regression analysis for predicting resource consumption of manufacturing processes and gives a comparison of the achievable results based on an industrial case study of a turning process.

Keywords: artificial neural network, design of experiments, regression analysis, resource efficiency, manufacturing process

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28825 Deep-Learning Based Approach to Facial Emotion Recognition through Convolutional Neural Network

Authors: Nouha Khediri, Mohammed Ben Ammar, Monji Kherallah

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Recently, facial emotion recognition (FER) has become increasingly essential to understand the state of the human mind. Accurately classifying emotion from the face is a challenging task. In this paper, we present a facial emotion recognition approach named CV-FER, benefiting from deep learning, especially CNN and VGG16. First, the data is pre-processed with data cleaning and data rotation. Then, we augment the data and proceed to our FER model, which contains five convolutions layers and five pooling layers. Finally, a softmax classifier is used in the output layer to recognize emotions. Based on the above contents, this paper reviews the works of facial emotion recognition based on deep learning. Experiments show that our model outperforms the other methods using the same FER2013 database and yields a recognition rate of 92%. We also put forward some suggestions for future work.

Keywords: CNN, deep-learning, facial emotion recognition, machine learning

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28824 A Survey of Recognizing of Daily Living Activities in Multi-User Smart Home Environments

Authors: Kulsoom S. Bughio, Naeem K. Janjua, Gordana Dermody, Leslie F. Sikos, Shamsul Islam

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The advancement in information and communication technologies (ICT) and wireless sensor networks have played a pivotal role in the design and development of real-time healthcare solutions, mainly targeting the elderly living in health-assistive smart homes. Such smart homes are equipped with sensor technologies to detect and record activities of daily living (ADL). This survey reviews and evaluates existing approaches and techniques based on real-time sensor-based modeling and reasoning in single-user and multi-user environments. It classifies the approaches into three main categories: learning-based, knowledge-based, and hybrid, and evaluates how they handle temporal relations, granularity, and uncertainty. The survey also highlights open challenges across various disciplines (including computer and information sciences and health sciences) to encourage interdisciplinary research for the detection and recognition of ADLs and discusses future directions.

Keywords: daily living activities, smart homes, single-user environment, multi-user environment

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28823 A Rare Case Report of Non-Langerhans Cell Cutaneous Histiocytosis in a 6-Month Old Infant

Authors: Apoorva D. R.

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INTRODUCTION: Hemophagocytic lymphohistiocytosis (HLH) is a severe, potentially fatal syndrome in which there is excessive immune activation. The disease is seen in children and people of all ages, but infants from birth to 18 months are most frequently affected. HLH is a sporadic or familial condition that can be triggered by various events that disturb immunological homeostasis. In cases with a genetic predisposition and sporadic occurrences, infection is a frequent trigger. Because of the rarity of this disease, the diverse clinical presentation, and the lack of specificity in the clinical and laboratory results, prompt treatment is essential, but the biggest obstacle to a favorable outcome is frequently a delay in identification. CASE REPORT: Here we report a case of a 6-month-old male infant who presented to the dermatology outpatient with disseminated skin lesions present over the face, abdomen, scalp, and bilateral upper and lower limbs for the past month. The lesions were insidious in onset, initially started over the abdomen, and gradually progressed to involve other body parts. The patient also had a history of fever which was moderate in grade, on and off in nature for 1 month. There were no significant complaints in the past, family, or drug history. There was no history of feeding difficulties in the baby. Parents gave a history of developmental milestones appropriate for age. Examination findings include multiple well-defined monomorphic erythematous papules with a central crater present over bilateral cheeks. Few lichenoid shiny papules present over bilateral arms, legs, and abdomen. Ultrasound of the abdomen and pelvis showed mild degree hepatosplenomegaly, intraabdominal lymphadenopathy, and bilateral inguinal lymphadenopathy. Routine blood investigations showed anemia and lymphopenia. Multiple X-rays of the skull, chest, and bilateral upper and lower limbs were done and were normal. Histopathology features were suggestive of non-Langerhans cell cutaneous histiocytosis. CONCLUSION: HLH is a fatal and rare disease. A high level of suspicion and an interdisciplinary approach among experienced clinicians, pathologists, and microbiologists to define the diagnosis and causative disease are key to diagnosing this case. Early detection and treatment can reduce patient morbidity and mortality.

Keywords: histiocytosis, non langerhans cell, case report, fatal, rare

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28822 Adsoption Tests of Two Industrial Dyes by Hydroxyds of Metals

Authors: R. Berrached, H. Ait Mahamed, A. Iddou

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Water pollution is nowadays a serious problem, due to the increasing scarcity of water and thus to the impact induced by such pollution on the human health. Various techniques are made use of to deal with water pollution. Among the most used ones, some can be enumerated: the bacterian bed, the activated sludge, lagoons as biological processes and coagulation-flocculation as a physic-chemical process. These processes are very expensive and a decreasing in efficiency treatment with the increase of the initial pollutants concentration. This is the reason why research has been reoriented towards the use of adsorption process as an alternative solution instead of the other traditional processes. In our study, we have tempted to explore the characteristics of hydroxides of Al and Fe to purify contaminated water by two industrial dyes SBL blue and SRL-150 orange. Results have shown the efficiency of the two materials on the blue SBL dye.

Keywords: metallic hydroxydes, dyes, purification, adsorption

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28821 Design and Evaluation of an Online Case-Based Library for Technology Integration in Teacher Education

Authors: Mustafa Tevfik Hebebci, Ismail Sahin, Sirin Kucuk, Ismail Celik, Ahmet Oguz Akturk

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ADDIE is an instructional design model which has the five core elements: analyze, design, develop, implement, and evaluate. The ADDIE approach provides a systematic process for the analysis of instructional needs, the design and development of instructional programs and materials, implementation of a program, and the evaluation of the effectiveness of an instruction. The case-based study is an instructional design model that is a variant of project-oriented learning. Collecting and analyzing stories can be used in two primary ways -perform task analysis and as a learning support during instruction- by instructional designers. Besides, teachers use technology to develop students’ thinking, enriching the learning environment and providing permanent learning. The purpose of this paper is to introduce an interactive online case-study library website developed in a national project. The design goal of the website is to provide interactive, enhanced, case-based and online educational resource for educators through the purpose and within the scope of a national project. The ADDIE instructional design model was used in the development of the website for the interactive case-based library. This web-based library contains the navigation menus as the follows: “Homepage”, "Registration", "Branches", "Aim of The Research", "About TPACK", "National Project", "Contact Us", etc. This library is developed on a web-based platform, which is important in terms of manageability, accessibility, and updateability of data. Users are able to sort the displayed case-studies by their titles, dates, ratings, view counts, etc. In addition, they encouraged to rate and comment on the case-studies. The usability test is used and the expert opinion is taken for the evaluation of the website. This website is a tool to integrate technology in education. It is believed that this website will be beneficial for pre-service and in-service teachers in terms of their professional developments.

Keywords: design, ADDIE, case based library, technology integration

Procedia PDF Downloads 483