Search results for: lung extraction
572 A Visual Analytics Tool for the Structural Health Monitoring of an Aircraft Panel
Authors: F. M. Pisano, M. Ciminello
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Aerospace, mechanical, and civil engineering infrastructures can take advantages from damage detection and identification strategies in terms of maintenance cost reduction and operational life improvements, as well for safety scopes. The challenge is to detect so called “barely visible impact damage” (BVID), due to low/medium energy impacts, that can progressively compromise the structure integrity. The occurrence of any local change in material properties, that can degrade the structure performance, is to be monitored using so called Structural Health Monitoring (SHM) systems, in charge of comparing the structure states before and after damage occurs. SHM seeks for any "anomalous" response collected by means of sensor networks and then analyzed using appropriate algorithms. Independently of the specific analysis approach adopted for structural damage detection and localization, textual reports, tables and graphs describing possible outlier coordinates and damage severity are usually provided as artifacts to be elaborated for information extraction about the current health conditions of the structure under investigation. Visual Analytics can support the processing of monitored measurements offering data navigation and exploration tools leveraging the native human capabilities of understanding images faster than texts and tables. Herein, a SHM system enrichment by integration of a Visual Analytics component is investigated. Analytical dashboards have been created by combining worksheets, so that a useful Visual Analytics tool is provided to structural analysts for exploring the structure health conditions examined by a Principal Component Analysis based algorithm.Keywords: interactive dashboards, optical fibers, structural health monitoring, visual analytics
Procedia PDF Downloads 120571 Mordenite as Catalyst Support for Complete Volatile Organic Compounds Oxidation
Authors: Yuri A. Kalvachev, Totka D. Todorova
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Zeolite mordenite has been investigated as a transition metal support for the preparation of efficient catalysts in the oxidation of volatile organic compounds (VOCs). The highly crystalline mordenite samples were treated with hydrofluoric acid and ammonium fluoride to get hierarchical material with secondary porosity. The obtained supports by this method have a high active surface area, good diffusion properties and prevent the extraction of metal components during catalytic reactions. The active metal phases platinum and copper were loaded by impregnation on both mordenite materials (parent and acid treated counterparts). Monometalic Pt and Cu, and bimetallic Pt/Cu catalysts were obtained. The metal phases were fine dispersed as nanoparticles on the functional porous materials. The catalysts synthesized in this way were investigated in the reaction of complete oxidation of propane and benzene. Platinum, copper and platinum/copper were loaded and there catalytic activity was investigated and compared. All samples are characterized by X-ray diffraction analysis, nitrogen adsorption, scanning electron microscopy (SEM), X-ray photoelectron measurements (XPS) and temperature programed reduction (TPR). The catalytic activity of the samples obtained is investigated in the reaction of complete oxidation of propane and benzene by using of Gas Chromatography (GC). The oxidation of three organic molecules was investigated—methane, propane and benzene. The activity of metal loaded mordenite catalysts for methane oxidation is almost the same for parent and treated mordenite as a support. For bigger molecules as propane and benzene, the activity of catalysts based on treated mordenite is higher than those based on parent zeolite.Keywords: metal loaded catalysts, mordenite, VOCs oxidation, zeolites
Procedia PDF Downloads 121570 Preserving Urban Cultural Heritage with Deep Learning: Color Planning for Japanese Merchant Towns
Authors: Dongqi Li, Yunjia Huang, Tomo Inoue, Kohei Inoue
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With urbanization, urban cultural heritage is facing the impact and destruction of modernization and urbanization. Many historical areas are losing their historical information and regional cultural characteristics, so it is necessary to carry out systematic color planning for historical areas in conservation. As an early focus on urban color planning, Japan has a systematic approach to urban color planning. Hence, this paper selects five merchant towns from the category of important traditional building preservation areas in Japan as the subject of this study to explore the color structure and emotion of this type of historic area. First, the image semantic segmentation method identifies the buildings, roads, and landscape environments. Their color data were extracted for color composition and emotion analysis to summarize their common features. Second, the obtained Internet evaluations were extracted by natural language processing for keyword extraction. The correlation analysis of the color structure and keywords provides a valuable reference for conservation decisions for this historic area in the town. This paper also combines the color structure and Internet evaluation results with generative adversarial networks to generate predicted images of color structure improvements and color improvement schemes. The methods and conclusions of this paper can provide new ideas for the digital management of environmental colors in historic districts and provide a valuable reference for the inheritance of local traditional culture.Keywords: historic districts, color planning, semantic segmentation, natural language processing
Procedia PDF Downloads 80569 Unlocking Justice: Exploring the Power and Challenges of DNA Analysis in the Criminal Justice System
Authors: Sandhra M. Pillai
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This article examines the relevance, difficulties, and potential applications of DNA analysis in the criminal justice system. A potent tool for connecting suspects to crime sites, clearing the innocent of wrongdoing, and resolving cold cases, DNA analysis has transformed forensic investigations. The scientific foundations of DNA analysis, including DNA extraction, sequencing, and statistical analysis, are covered in the article. To guarantee accurate and trustworthy findings, it also discusses the significance of quality assurance procedures, chain of custody, and DNA sample storage. DNA analysis has significantly advanced science, but it also brings up substantial moral and legal issues. To safeguard individual rights and uphold public confidence, privacy concerns, possible discrimination, and abuse of DNA information must be properly addressed. The paper also emphasises the effects of the criminal justice system on people and communities while highlighting the necessity of equity, openness, and fair access to DNA testing. The essay describes the obstacles and future directions for DNA analysis. It looks at cutting-edge technology like next-generation sequencing, which promises to make DNA analysis quicker and more affordable. To secure the appropriate and informed use of DNA evidence, it also emphasises the significance of multidisciplinary collaboration among scientists, law enforcement organisations, legal experts, and policymakers. In conclusion, DNA analysis has enormous potential for improving the course of criminal justice. We can exploit the potential of DNA technology while respecting the ideals of justice, fairness, and individual rights by navigating the ethical, legal, and societal issues and encouraging discussion and collaboration.Keywords: DNA analysis, DNA evidence, reliability, validity, legal frame, admissibility, ethical considerations, impact, future direction, challenges
Procedia PDF Downloads 60568 Computational Intelligence and Machine Learning for Urban Drainage Infrastructure Asset Management
Authors: Thewodros K. Geberemariam
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The rapid physical expansion of urbanization coupled with aging infrastructure presents a unique decision and management challenges for many big city municipalities. Cities must therefore upgrade and maintain the existing aging urban drainage infrastructure systems to keep up with the demands. Given the overall contribution of assets to municipal revenue and the importance of infrastructure to the success of a livable city, many municipalities are currently looking for a robust and smart urban drainage infrastructure asset management solution that combines management, financial, engineering and technical practices. This robust decision-making shall rely on sound, complete, current and relevant data that enables asset valuation, impairment testing, lifecycle modeling, and forecasting across the multiple asset portfolios. On this paper, predictive computational intelligence (CI) and multi-class machine learning (ML) coupled with online, offline, and historical record data that are collected from an array of multi-parameter sensors are used for the extraction of different operational and non-conforming patterns hidden in structured and unstructured data to determine and produce actionable insight on the current and future states of the network. This paper aims to improve the strategic decision-making process by identifying all possible alternatives; evaluate the risk of each alternative, and choose the alternative most likely to attain the required goal in a cost-effective manner using historical and near real-time urban drainage infrastructure data for urban drainage infrastructures assets that have previously not benefited from computational intelligence and machine learning advancements.Keywords: computational intelligence, machine learning, urban drainage infrastructure, machine learning, classification, prediction, asset management space
Procedia PDF Downloads 146567 Credit Card Fraud Detection with Ensemble Model: A Meta-Heuristic Approach
Authors: Gong Zhilin, Jing Yang, Jian Yin
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The purpose of this paper is to develop a novel system for credit card fraud detection based on sequential modeling of data using hybrid deep learning models. The projected model encapsulates five major phases are pre-processing, imbalance-data handling, feature extraction, optimal feature selection, and fraud detection with an ensemble classifier. The collected raw data (input) is pre-processed to enhance the quality of the data through alleviation of the missing data, noisy data as well as null values. The pre-processed data are class imbalanced in nature, and therefore they are handled effectively with the K-means clustering-based SMOTE model. From the balanced class data, the most relevant features like improved Principal Component Analysis (PCA), statistical features (mean, median, standard deviation) and higher-order statistical features (skewness and kurtosis). Among the extracted features, the most optimal features are selected with the Self-improved Arithmetic Optimization Algorithm (SI-AOA). This SI-AOA model is the conceptual improvement of the standard Arithmetic Optimization Algorithm. The deep learning models like Long Short-Term Memory (LSTM), Convolutional Neural Network (CNN), and optimized Quantum Deep Neural Network (QDNN). The LSTM and CNN are trained with the extracted optimal features. The outcomes from LSTM and CNN will enter as input to optimized QDNN that provides the final detection outcome. Since the QDNN is the ultimate detector, its weight function is fine-tuned with the Self-improved Arithmetic Optimization Algorithm (SI-AOA).Keywords: credit card, data mining, fraud detection, money transactions
Procedia PDF Downloads 123566 A Systematic Review and Meta-Analysis of Diabetes Ketoacidosis in Ethiopia
Authors: Addisu Tadesse Sahile, Mussie Wubshet Teka, Solomon Muluken Ayehu
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Background: Diabetes is one of the common public health problems of the century that was estimated to affect one in a tenth of the world population by the year 2030, where diabetes ketoacidosis is one of its common acute complications. Objectives: The aim of this review was to assess the magnitude of diabetes ketoacidosis among patients with type 1 diabetes in Ethiopia. Methods: A systematic data search was done across Google Scholar, PubMed, Web of Science, and African Online Journals. Two reviewers carried out the selection, reviewing, screening, and extraction of the data independently by using a Microsoft Excel Spreadsheet. The Joanna Briggs Institute's prevalence critical appraisal tool was used to assess the quality of evidence. All studies conducted in Ethiopia that reported diabetes ketoacidosis rates among type 1 diabetes were included. The extracted data was imported into the comprehensive meta-analysis version 3.0 for further analysis. Heterogeneity was checked by Higgins’s method, whereas the publication bias was checked by using Beggs and Eggers’s tests. A random-effects meta-analysis model with a 95% confidence interval was computed to estimate the pooled prevalence. Furthermore, subgroup analysis based on the study area (Region) and the sample size was carried out. Result and Conclusion: After review made across a total of 51 articles, of which 12 articles fulfilled the inclusion criteria and were included in the meta-analysis. The pooled prevalence of diabetes ketoacidosis among type 1 diabetes in Ethiopia was 53.2% (95%CI: 43.1%-63.1%). The highest prevalence of DKA was reported in the Tigray region of Ethiopia, whereas the lowest was reported in the Southern region of Ethiopia. Concerned bodies were suggested to work on the escalated burden of diabetes ketoacidosis in Ethiopia.Keywords: DKA, Type 1 diabetes, Ethiopia, systematic review, meta-analysis
Procedia PDF Downloads 49565 Magnetized Cellulose Nanofiber Extracted from Natural Resources for the Application of Hexavalent Chromium Removal Using the Adsorption Method
Authors: Kebede Gamo Sebehanie, Olu Emmanuel Femi, Alberto Velázquez Del Rosario, Abubeker Yimam Ali, Gudeta Jafo Muleta
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Water pollution is one of the most serious worldwide issues today. Among water pollution, heavy metals are becoming a concern to the environment and human health due to their non-biodegradability and bioaccumulation. In this study, a magnetite-cellulose nanocomposite derived from renewable resources is employed for hexavalent chromium elimination by adsorption. Magnetite nanoparticles were synthesized directly from iron ore using solvent extraction and co-precipitation technique. Cellulose nanofiber was extracted from sugarcane bagasse using the alkaline treatment and acid hydrolysis method. Before and after the adsorption process, the MNPs-CNF composites were evaluated using X-ray diffraction (XRD), Scanning electron microscope (SEM), Fourier transform infrared (FTIR), and Vibrator sample magnetometer (VSM), and Thermogravimetric analysis (TGA). The impacts of several parameters such as pH, contact time, initial pollutant concentration, and adsorbent dose on adsorption efficiency and capacity were examined. The kinetic and isotherm adsorption of Cr (VI) was also studied. The highest removal was obtained at pH 3, and it took 80 minutes to establish adsorption equilibrium. The Langmuir and Freundlich isotherm models were used, and the experimental data fit well with the Langmuir model, which has a maximum adsorption capacity of 8.27 mg/g. The kinetic study of the adsorption process using pseudo-first-order and pseudo-second-order equations revealed that the pseudo-second-order equation was more suited for representing the adsorption kinetic data. Based on the findings, pure MNPs and MNPs-CNF nanocomposites could be used as effective adsorbents for the removal of Cr (VI) from wastewater.Keywords: magnetite-cellulose nanocomposite, hexavalent chromium, adsorption, sugarcane bagasse
Procedia PDF Downloads 119564 Identification of Clinical Characteristics from Persistent Homology Applied to Tumor Imaging
Authors: Eashwar V. Somasundaram, Raoul R. Wadhwa, Jacob G. Scott
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The use of radiomics in measuring geometric properties of tumor images such as size, surface area, and volume has been invaluable in assessing cancer diagnosis, treatment, and prognosis. In addition to analyzing geometric properties, radiomics would benefit from measuring topological properties using persistent homology. Intuitively, features uncovered by persistent homology may correlate to tumor structural features. One example is necrotic cavities (corresponding to 2D topological features), which are markers of very aggressive tumors. We develop a data pipeline in R that clusters tumors images based on persistent homology is used to identify meaningful clinical distinctions between tumors and possibly new relationships not captured by established clinical categorizations. A preliminary analysis was performed on 16 Magnetic Resonance Imaging (MRI) breast tissue segments downloaded from the 'Investigation of Serial Studies to Predict Your Therapeutic Response with Imaging and Molecular Analysis' (I-SPY TRIAL or ISPY1) collection in The Cancer Imaging Archive. Each segment represents a patient’s breast tumor prior to treatment. The ISPY1 dataset also provided the estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) status data. A persistent homology matrix up to 2-dimensional features was calculated for each of the MRI segmentation. Wasserstein distances were then calculated between all pairwise tumor image persistent homology matrices to create a distance matrix for each feature dimension. Since Wasserstein distances were calculated for 0, 1, and 2-dimensional features, three hierarchal clusters were constructed. The adjusted Rand Index was used to see how well the clusters corresponded to the ER/PR/HER2 status of the tumors. Triple-negative cancers (negative status for all three receptors) significantly clustered together in the 2-dimensional features dendrogram (Adjusted Rand Index of .35, p = .031). It is known that having a triple-negative breast tumor is associated with aggressive tumor growth and poor prognosis when compared to non-triple negative breast tumors. The aggressive tumor growth associated with triple-negative tumors may have a unique structure in an MRI segmentation, which persistent homology is able to identify. This preliminary analysis shows promising results in the use of persistent homology on tumor imaging to assess the severity of breast tumors. The next step is to apply this pipeline to other tumor segment images from The Cancer Imaging Archive at different sites such as the lung, kidney, and brain. In addition, whether other clinical parameters, such as overall survival, tumor stage, and tumor genotype data are captured well in persistent homology clusters will be assessed. If analyzing tumor MRI segments using persistent homology consistently identifies clinical relationships, this could enable clinicians to use persistent homology data as a noninvasive way to inform clinical decision making in oncology.Keywords: cancer biology, oncology, persistent homology, radiomics, topological data analysis, tumor imaging
Procedia PDF Downloads 129563 A Multi-Templated Fe-Ni-Cu Ion Imprinted Polymer for the Selective and Simultaneous Removal of Toxic Metallic Ions from Wastewater
Authors: Morlu Stevens, Bareki Batlokwa
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The use of treated wastewater is widely employed to compensate for the scarcity of safe and uncontaminated freshwater. However, the existence of toxic heavy metal ions in the wastewater pose a health hazard to animals and the environment, hence, the importance for an effective technique to tackle the challenge. A multi-templated ion imprinted sorbent (Fe,Ni,Cu-IIP) for the simultaneous removal of heavy metal ions from waste water was synthesised employing molecular imprinting technology (MIT) via thermal free radical bulk polymerization technique. Methacrylic acid (MAA) was employed as the functional monomer, and ethylene glycol dimethylacrylate (EGDMA) as cross-linking agent, azobisisobutyronitrile (AIBN) as the initiator, Fe, Ni, Cu ions as template ions, and 1,10-phenanthroline as the complexing agent. The template ions were exhaustively washed off the synthesized polymer by solvent extraction in several washing steps, while periodically increasing solvent (HCl) concentration from 1.0 M to 10.0 M. The physical and chemical properties of the sorbents were investigated using Fourier Transform Infrared Spectroscopy (FT-IR), X-ray Diffraction (XRD) and Atomic Force Microscopy (AFM) were employed. Optimization of operational parameters such as time, pH and sorbent dosage to evaluate the effectiveness of sorbents were investigated and found to be 15 min, 7.5 and 666.7 mg/L respectively. Selectivity of ion-imprinted polymers and competitive sorption studies between the template and similar ions were carried out and showed good selectivity towards the targeted metal ion by removing 90% - 98% of the templated ions as compared to 58% - 62% of similar ions. The sorbents were further applied for the selective removal of Fe, Ni and Cu from real wastewater samples and recoveries of 92.14 ± 0.16% - 106.09 ± 0.17% and linearities of R2 = 0.9993 - R2 = 0.9997 were achieved.Keywords: ion imprinting, ion imprinted polymers, heavy metals, wastewater
Procedia PDF Downloads 311562 Changes on Some Physical and Chemical Properties of Red Beetroot Juice during Ultrasound Pretreatment
Authors: Serdal Sabanci, Mutlu Çevik, Derya Tezcan, Cansu Çelebi, Filiz Içier
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Ultrasound is defined as sound waves having frequencies higher than 20 kHz, which is greater than the limits of the human hearing range. In recent years, ultrasonic treatment is an emerging technology being used increasingly in the food industry. It is applied as an alternative technique for different purposes such as microbial and enzyme inactivation, extraction, drying, filtration, crystallization, degas, cutting etc. Red beetroot (Beta vulgaris L.) is a root vegetable which is rich in mineral components, folic acid, dietary fiber, anthocyanin pigments. In this study, the application of low frequency high intensity ultrasound to the red beetroot slices and red beetroot juice for different treatment times (0, 5, 10, 15, 20 min) was investigated. Ultrasonicated red beetroot slices were also squeezed immediately. Changes on colour, betanin, pH and titratable acidity properties of red beetroot juices (the ultrasonicated juice (UJ) and the juice from ultrasonicated slices (JUS)) were determined. Although there was no significant difference statistically in the changes of color value of JUS samples due to ultrasound application (p>0.05), the color properties of UJ samples ultrasonicated for low durations were statistically different from raw material (p<0.05). The difference between color values of UJ and raw material disappeared (p>0.05) as the ultrasonication duration increased. The application of ultrasound to red beet root slices adversely affected and decreased the betanin content of JUS samples. On the other hand, the betanin content of UJ samples increased as the ultrasonication duration increased. Ultrasound treatment did not affect pH and titratable acidity of red beetroot juices statistically (p>0.05). The results suggest that ultrasound technology is the simple and economical technique which may successfully be employed for the processing of red beetroot juice with improved color and betanin quality. However, further investigation is still needed to confirm this.Keywords: red beetroot, ultrasound, color, betanin
Procedia PDF Downloads 392561 Combined Pneumomediastinum and Pneumothorax Due to Hyperemesis Gravidarum
Authors: Fayez Hanna, Viet Tran
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A 20 years old lady- primigravida 6 weeks pregnant with unremarkable past history, presented to the emergency department at the Royal Hobart Hospital, Tasmania, Australia, with hyperemesis gravidarum associated with, dehydration and complicated with hematemesis and chest pain resistant. Accordingly, we conducted laboratory investigations which revealed: FBC: WBC 23.9, unremarkable U&E, LFT, lipase and her VBG showed a pH 7.4, pCo2 36.7, cK+ 3.2, cNa+ 142. The decision was made to do a chest X-ray (CXR) after explaining the risks/benefit of performing radiographic investigations during pregnancy and considering the patient's plan for the termination of the pregnancy as she was not ready for motherhood for shared decision-making and consent to look for pneumoperitoneum to suggest perforated viscus that might cause the hematemesis. However, the CXR showed pneumomediastinum but no evidence of pneumoperitoneum or pneumothorax. Consequently, a decision was made to proceed with CT oesophagography with imaging pre and post oral contrast administration to identify a potential oesophageal tear since it could not be excluded using a plain film of the CXR. The CT oesophagography could not find a leak for the administered oral contrast and thus, no oesophageal tear could be confirmed but could not exclude the Mallory-Weiss tear (lower oesophageal tear). Further, the CT oesophagography showed an extensive pneumomediastinum that could not be confirmed to be pulmonary in origin noting the presence of bilateral pulmonary interstitial emphysema and pneumothorax in the apex of the right lung that was small. The patient was admitted to the Emergency Department Inpatient Unit for monitoring, supportive therapy, and symptomatic management. Her hyperemesis was well controlled with ondansetron 8mg IV, metoclopramide 10mg IV, doxylamine 25mg PO, pyridoxine 25mg PO, esomeprazole 40mg IV and oxycodone 5mg PO was given for pain control and 2 litter of IV fluid. The patient was stabilized after 24 hours and discharged home on ondansetron 8mg every 8 hours whereas the patient had a plan for medical termination of pregnancy. Three weeks later, the patient represented with nausea and vomiting complicated by a frank hematemesis. Her observation chart showed HR 117- other vital signs were normal. Pathology showed WBC 14.3 with normal U&E and Hb. The patient was managed in the Emergency Department with the same previous regimen and was discharged home on same previous regimes. Five days later, she presented again with nausea, vomiting and hematemesis and was admitted under obstetrics and gynaecology for stabilization then discharged home with a plan for surgical termination of pregnancy after 3-days rather than the previously planned medical termination of pregnancy to avoid extension of potential oesophageal tear. The surgical termination and follow up period were uneventful. The case is considered rare as pneumomediastinum is a very rare complication of hyperemesis gravidarum where vomiting-induced barotrauma leads to a ruptured oesophagus and air leak into the mediastinum. However no rupture oesophagus in our case. Although the combination of pneumothorax and pneumomediastinum without oesophageal tear was reported only 8 times in the literature, but none of them was due to hyperemesis gravidarum.Keywords: Pneumothorax, pneumomediastinum, hyperemesis gravidarum, pneumopericardium
Procedia PDF Downloads 93560 A Study on Soil Micro-Arthropods Assemblage in Selected Plantations in The Nilgiris, Tamilnadu
Authors: J. Dharmaraj, C. Gunasekaran
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Invertebrates are the reliable ecological indicators of disturbance of the forest ecosystems and they respond to environment changes more quickly than other fauna. Among these the terrestrial invertebrates are vital to functioning ecosystems, contributing to processes such as decomposition, nutrient cycling and soil fertility. The natural ecosystems of the forests have been subject to various types of disturbances, which lead to decline of flora and fauna. The comparative diversity of micro-arthropods in natural forest, wattle plantation and eucalyptus plantations were studied in Nilgiris. The study area was divided in to five major sites (Emerald (Site-I), Thalaikundha (Site-II), Kodapmund (Site-III), Aravankad (Site-IV), Kattabettu (Site-V). The research was conducted during period from March 2014 to August 2014. The leaf and soil samples were collected and isolated by using Berlese funnel extraction methods. Specimens were isolated and identified according to their morphology (Balogh 1972). In the present study results clearly showed the variation in soil pH, NPK (Major Nutrients) and organic carbon among the study sites. The chemical components of the leaf litters of the plantation decreased the diversity of micro-arthropods and decomposition rate leads to low amount of carbon and other nutrients present in the soil. Moreover eucalyptus and wattle plantations decreases the availability of the ground water source to other plantations and micro-arthropods and hences affects the soil fertility. Hence, the present study suggests to minimize the growth of wattle and eucalyptus tree plantations in the natural areas which may help to reduce the decline of forests.Keywords: micro-arthropods, assemblage, berlese funnel, morphology, NPK, nilgiris
Procedia PDF Downloads 300559 Frequency of Alloimmunization in Sickle Cell Disease Patients in Africa: A Systematic Review with Meta-analysis
Authors: Theresa Ukamaka Nwagha, Angela Ogechukwu Ugwu, Martins Nweke
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Background and Objectives: Blood transfusion is an effective and proven treatment for some severe complications of sickle cell disease. Recurrent transfusions have put patients with sickle cell disease at risk of developing antibodies against the various antigens they were exposed to. This study aims to investigate the frequency of red blood cell alloimmunization in patients with sickle disease in Africa. Materials and Methods: This is a systematic review of peer-reviewed literature published in English. The review was conducted consistent with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist. Data sources for the review include MEDLINE, PubMed, CINAHL, and Academic Search Complete. Included in this review are articles that reported the frequency/prevalence of red blood cell alloimmunization in sickle cell disease patients in Africa. Eligible studies were subjected to independent full-text screening and data extraction. Risk of bias assessment was conducted with the aid of the mixed method appraisal tool. We employed a random-effects model of meta-analysis to estimate the pooled prevalence. We computed Cochrane’s Q statistics and I2 and prediction interval to quantify heterogeneity in effect size. Results: The prevalence estimates range from 2.6% to 29%. Pooled prevalence was estimated to be 10.4% (CI 7.7.–13.8); PI = 3.0 – 34.0%), with significant heterogeneity (I2 = 84.62; PI = 2.0-32.0%) and publication bias (Egger’s t-test = 1.744, p = 0.0965). Conclusion: The frequency of red cell alloantibody varies considerably in Africa. The alloantibodies appeared frequent in this order: the Rhesus, Kell, Lewis, Duffy, MNS, and LutheranKeywords: frequency, red blood cell, alloimmunization, sickle cell disease, Africa
Procedia PDF Downloads 92558 An Integrated Label Propagation Network for Structural Condition Assessment
Authors: Qingsong Xiong, Cheng Yuan, Qingzhao Kong, Haibei Xiong
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Deep-learning-driven approaches based on vibration responses have attracted larger attention in rapid structural condition assessment while obtaining sufficient measured training data with corresponding labels is relevantly costly and even inaccessible in practical engineering. This study proposes an integrated label propagation network for structural condition assessment, which is able to diffuse the labels from continuously-generating measurements by intact structure to those of missing labels of damage scenarios. The integrated network is embedded with damage-sensitive features extraction by deep autoencoder and pseudo-labels propagation by optimized fuzzy clustering, the architecture and mechanism which are elaborated. With a sophisticated network design and specified strategies for improving performance, the present network achieves to extends the superiority of self-supervised representation learning, unsupervised fuzzy clustering and supervised classification algorithms into an integration aiming at assessing damage conditions. Both numerical simulations and full-scale laboratory shaking table tests of a two-story building structure were conducted to validate its capability of detecting post-earthquake damage. The identifying accuracy of a present network was 0.95 in numerical validations and an average 0.86 in laboratory case studies, respectively. It should be noted that the whole training procedure of all involved models in the network stringently doesn’t rely upon any labeled data of damage scenarios but only several samples of intact structure, which indicates a significant superiority in model adaptability and feasible applicability in practice.Keywords: autoencoder, condition assessment, fuzzy clustering, label propagation
Procedia PDF Downloads 92557 Work System Design in Productivity for Small and Medium Enterprises: A Systematic Literature Review
Authors: Silipa Halofaki, Devi R. Seenivasagam, Prashant Bijay, Kritin Singh, Rajeshkannan Ananthanarayanan
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This comprehensive literature review delves into the effects and applications of work system design on the performance of Small and Medium-sized Enterprises (SMEs). The review process involved three independent reviewers who screened 514 articles through a four-step procedure: removing duplicates, assessing keyword relevance, evaluating abstract content, and thoroughly reviewing full-text articles. Various criteria, such as relevance to the research topic, publication type, study type, language, publication date, and methodological quality, were employed to exclude certain publications. A portion of articles that met the predefined inclusion criteria were included as a result of this systematic literature review. These selected publications underwent data extraction and analysis to compile insights regarding the influence of work system design on SME performance. Additionally, the quality of the included studies was assessed, and the level of confidence in the body of evidence was established. The findings of this review shed light on how work system design impacts SME performance, emphasizing important implications and applications. Furthermore, the review offers suggestions for further research in this critical area and summarizes the current state of knowledge in the field. Understanding the intricate connections between work system design and SME success can enhance operational efficiency, employee engagement, and overall competitiveness for SMEs. This comprehensive examination of the literature contributes significantly to both academic research and practical decision-making for SMEs.Keywords: literature review, productivity, small and medium sized enterprises-SMEs, work system design
Procedia PDF Downloads 85556 Evaluation of Life Cycle Assessment in Furniture Manufacturing by Analytical Hierarchy Process
Authors: Majid Azizi, Payam Ghorbannezhad, Mostafa Amiri, Mohammad Ghofrani
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Environmental issues in the furniture industry are of great importance due to the use of natural materials such as wood and chemical substances like adhesives and paints. These issues encompass environmental conservation and managing pollution and waste generated. Improper use of wood resources, along with the use of chemicals and their release, leads to the depletion of natural resources, damage to forests, and the emission of greenhouse gases. Therefore, identifying influential indicators in the life cycle assessment of classic furniture and proposing solutions to reduce environmental impacts becomes crucial. In this study, the life cycle of classic furniture was evaluated using a hierarchical analytical process from cradle to grave. The life cycle assessment was employed to assess the environmental impacts of the furniture industry, ranging from raw material extraction to waste disposal and recycling. The most significant indicators in the furniture industry's production chain were also identified. The results indicated that the wood quality indicator is the most essential factor in the life cycle of classic furniture. Furthermore, the relative contribution of each type of traditional furniture was proposed concerning impact categories in the life cycle assessment. The results showed that among the three proposed types, the design and production of furniture with prefabricated parts had the most negligible impact in categories such as global warming potential and ozone layer depletion compared to furniture design with solid wood and furniture design with recycled components. Among the three suggested types of furniture to reduce environmental impacts, producing furniture with solid wood or other woods was chosen as the most crucial solution.Keywords: life cycle assessment, analytic hierarchy process, environmental issues, furniture
Procedia PDF Downloads 57555 Low-Cost Image Processing System for Evaluating Pavement Surface Distress
Authors: Keerti Kembhavi, M. R. Archana, V. Anjaneyappa
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Most asphalt pavement condition evaluation use rating frameworks in which asphalt pavement distress is estimated by type, extent, and severity. Rating is carried out by the pavement condition rating (PCR), which is tedious and expensive. This paper presents the development of a low-cost technique for image pavement distress analysis that permits the identification of pothole and cracks. The paper explores the application of image processing tools for the detection of potholes and cracks. Longitudinal cracking and pothole are detected using Fuzzy-C- Means (FCM) and proceeded with the Spectral Theory algorithm. The framework comprises three phases, including image acquisition, processing, and extraction of features. A digital camera (Gopro) with the holder is used to capture pavement distress images on a moving vehicle. FCM classifier and Spectral Theory algorithms are used to compute features and classify the longitudinal cracking and pothole. The Matlab2016Ra Image preparing tool kit utilizes performance analysis to identify the viability of pavement distress on selected urban stretches of Bengaluru city, India. The outcomes of image evaluation with the utilization semi-computerized image handling framework represented the features of longitudinal crack and pothole with an accuracy of about 80%. Further, the detected images are validated with the actual dimensions, and it is seen that dimension variability is about 0.46. The linear regression model y=1.171x-0.155 is obtained using the existing and experimental / image processing area. The R2 correlation square obtained from the best fit line is 0.807, which is considered in the linear regression model to be ‘large positive linear association’.Keywords: crack detection, pothole detection, spectral clustering, fuzzy-c-means
Procedia PDF Downloads 174554 Deep Learning-Based Approach to Automatic Abstractive Summarization of Patent Documents
Authors: Sakshi V. Tantak, Vishap K. Malik, Neelanjney Pilarisetty
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A patent is an exclusive right granted for an invention. It can be a product or a process that provides an innovative method of doing something, or offers a new technical perspective or solution to a problem. A patent can be obtained by making the technical information and details about the invention publicly available. The patent owner has exclusive rights to prevent or stop anyone from using the patented invention for commercial uses. Any commercial usage, distribution, import or export of a patented invention or product requires the patent owner’s consent. It has been observed that the central and important parts of patents are scripted in idiosyncratic and complex linguistic structures that can be difficult to read, comprehend or interpret for the masses. The abstracts of these patents tend to obfuscate the precise nature of the patent instead of clarifying it via direct and simple linguistic constructs. This makes it necessary to have an efficient access to this knowledge via concise and transparent summaries. However, as mentioned above, due to complex and repetitive linguistic constructs and extremely long sentences, common extraction-oriented automatic text summarization methods should not be expected to show a remarkable performance when applied to patent documents. Other, more content-oriented or abstractive summarization techniques are able to perform much better and generate more concise summaries. This paper proposes an efficient summarization system for patents using artificial intelligence, natural language processing and deep learning techniques to condense the knowledge and essential information from a patent document into a single summary that is easier to understand without any redundant formatting and difficult jargon.Keywords: abstractive summarization, deep learning, natural language Processing, patent document
Procedia PDF Downloads 116553 Monitoring Air Pollution Effects on Children for Supporting Public Health Policy: Preliminary Results of MAPEC_LIFE Project
Authors: Elisabetta Ceretti, Silvia Bonizzoni, Alberto Bonetti, Milena Villarini, Marco Verani, Maria Antonella De Donno, Sara Bonetta, Umberto Gelatti
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Introduction: Air pollution is a global problem. In 2013, the International Agency for Research on Cancer (IARC) classified air pollution and particulate matter as carcinogenic to human. The study of the health effects of air pollution in children is very important because they are a high-risk group in terms of the health effects of air pollution and early exposure during childhood can increase the risk of developing chronic diseases in adulthood. The MAPEC_LIFE (Monitoring Air Pollution Effects on Children for supporting public health policy) is a project founded by EU Life+ Programme which intends to evaluate the associations between air pollution and early biological effects in children and to propose a model for estimating the global risk of early biological effects due to air pollutants and other factors in children. Methods: The study was carried out on 6-8-year-old children living in five Italian towns in two different seasons. Two biomarkers of early biological effects, primary DNA damage detected with the comet assay and frequency of micronuclei, were investigated in buccal cells of children. Details of children diseases, socio-economic status, exposures to other pollutants and life-style were collected using a questionnaire administered to children’s parents. Child exposure to urban air pollution was assessed by analysing PM0.5 samples collected in the school areas for PAHs and nitro-PAHs concentration, lung toxicity and in vitro genotoxicity on bacterial and human cells. Data on the chemical features of the urban air during the study period were obtained from the Regional Agency for Environmental Protection. The project created also the opportunity to approach the issue of air pollution with the children, trying to raise their awareness on air quality, its health effects and some healthy behaviors by means of an educational intervention in the schools. Results: 1315 children were recruited for the study and participate in the first sampling campaign in the five towns. The second campaign, on the same children, is still ongoing. The preliminary results of the tests on buccal mucosa cells of children will be presented during the conference as well as the preliminary data about the chemical composition and the toxicity and genotoxicity features of PM0.5 samples. The educational package was tested on 250 children of the primary school and showed to be very useful, improving children knowledge about air pollution and its effects and stimulating their interest. Conclusions: The associations between levels of air pollutants, air mutagenicity and biomarkers of early effects will be investigated. A tentative model to calculate the global absolute risk of having early biological effects for air pollution and other variables together will be proposed and may be useful to support policy-making and community interventions to protect children from possible health effects of air pollutants.Keywords: air pollution exposure, biomarkers of early effects, children, public health policy
Procedia PDF Downloads 323552 Solvent-Aided Dispersion of Tannic Acid to Enhance Flame Retardancy of Epoxy
Authors: Matthew Korey, Jeffrey Youngblood, John Howarter
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Background and Significance: Tannic acid (TA) is a bio-based high molecular weight organic, aromatic molecule that has been found to increase thermal stability and flame retardancy of many polymer matrices when used as an additive. Although it is biologically sourced, TA is a pollutant in industrial wastewater streams, and there is a desire to find applications in which to downcycle this molecule after extraction from these streams. Additionally, epoxy thermosets have revolutionized many industries, but are too flammable to be used in many applications without additives which augment their flame retardancy (FR). Many flame retardants used in epoxy thermosets are synthesized from petroleum-based monomers leading to significant environmental impacts on the industrial scale. Many of these compounds also have significant impacts on human health. Various bio-based modifiers have been developed to improve the FR of the epoxy resin; however, increasing FR of the system without tradeoffs with other properties has proven challenging, especially for TA. Methodologies: In this work, TA was incorporated into the thermoset by use of solvent-exchange using methyl ethyl ketone, a co-solvent for TA, and epoxy resin. Samples were then characterized optically (UV-vis spectroscopy and optical microscopy), thermally (thermogravimetric analysis and differential scanning calorimetry), and for their flame retardancy (mass loss calorimetry). Major Findings: Compared to control samples, all samples were found to have increased thermal stability. Further, the addition of tannic acid to the polymer matrix by the use of solvent greatly increased the compatibility of the additive in epoxy thermosets. By using solvent-exchange, the highest loading level of TA found in literature was achieved in this work (40 wt%). Conclusions: The use of solvent-exchange shows promises for circumventing the limitations of TA in epoxy.Keywords: sustainable, flame retardant, epoxy, tannic acid
Procedia PDF Downloads 122551 Prevalence of Visual Impairment among School Children in Ethiopia: A Systematic Review and Meta-Analysis
Authors: Merkineh Markos Lorato, Gedefaw Diress Alene
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Introduction: Visual impairment is any condition of the eye or visual system that results in loss/reduction of visual functioning. It significantly influences the academic routine and social activities of children, and the effect is severe for low-income countries like Ethiopia. So, this study aimed to determine the pooled prevalence of visual impairment among school children in Ethiopia. Methods: Databases such as Medical Literature Analysis and Retrieval System Online, Excerpta Medica dataBASE, World Wide Web of Science, and Cochrane Library searched to retrieve eligible articles. In addition, Google Scholar and a reference list of the retrieved eligible articles were addressed. Studies that reported the prevalence of visual impairment were included to estimate the pooled prevalence. Data were extracted using a standardized data extraction format prepared in Microsoft Excel and analysis was held using STATA 11 statistical software. I² was used to assess the heterogeneity. Because of considerable heterogeneity, a random effect meta-analysis model was used to estimate the pooled prevalence of visual impairment among school children in Ethiopia. Results: The result of 9 eligible studies showed that the pooled prevalence of visual impairment among school children in Ethiopia was 7.01% (95% CI: 5.46, 8.56%). In the subgroup analysis, the highest prevalence was reported in South Nations Nationalities and Tigray region together (7.99%; 3.63, 12.35), while the lowest prevalence was reported in Addis Ababa (5.73%; 3.93, 7.53). Conclusion: The prevalence of visual impairment among school children is significantly high in Ethiopia. If it is not detected and intervened early, it will cause a lifetime threat to visually impaired school children, so that school vision screening program plan and its implementation may cure the life quality of future generations in Ethiopia.Keywords: visual impairment, school children, Ethiopia, prevalence
Procedia PDF Downloads 29550 Patient Tracking Challenges During Disasters and Emergencies
Authors: Mohammad H. Yarmohammadian, Reza Safdari, Mahmoud Keyvanara, Nahid Tavakoli
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One of the greatest challenges in disaster and emergencies is patient tracking. The concept of tracking has different denotations. One of the meanings refers to tracking patients’ physical locations and the other meaning refers to tracking patients ‘medical needs during emergency services. The main goal of patient tracking is to provide patient safety during disaster and emergencies and manage the flow of patient and information in different locations. In most of cases, there are not sufficient and accurate data regarding the number of injuries, medical conditions and their accommodation and transference. The objective of the present study is to survey on patient tracking issue in natural disaster and emergencies. Methods: This was a narrative study in which the population was E-Journals and the electronic database such as PubMed, Proquest, Science direct, Elsevier, etc. Data was gathered by Extraction Form. All data were analyzed via content analysis. Results: In many countries there is no appropriate and rapid method for tracking patients and transferring victims after the occurrence of incidents. The absence of reliable data of patients’ transference and accommodation, even in the initial hours and days after the occurrence of disasters, and coordination for appropriate resource allocation, have faced challenges for evaluating needs and services challenges. Currently, most of emergency services are based on paper systems, while these systems do not act appropriately in great disasters and incidents and this issue causes information loss. Conclusion: Patient tracking system should update the location of patients or evacuees and information related to their states. Patients’ information should be accessible for authorized users to continue their treatment, accommodation and transference. Also it should include timely information of patients’ location as soon as they arrive somewhere and leave therein such a way that health care professionals can be able to provide patients’ proper medical treatment.Keywords: patient tracking, challenges, disaster, emergency
Procedia PDF Downloads 298549 A Comprehensive Study and Evaluation on Image Fashion Features Extraction
Authors: Yuanchao Sang, Zhihao Gong, Longsheng Chen, Long Chen
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Clothing fashion represents a human’s aesthetic appreciation towards everyday outfits and appetite for fashion, and it reflects the development of status in society, humanity, and economics. However, modelling fashion by machine is extremely challenging because fashion is too abstract to be efficiently described by machines. Even human beings can hardly reach a consensus about fashion. In this paper, we are dedicated to answering a fundamental fashion-related problem: what image feature best describes clothing fashion? To address this issue, we have designed and evaluated various image features, ranging from traditional low-level hand-crafted features to mid-level style awareness features to various current popular deep neural network-based features, which have shown state-of-the-art performance in various vision tasks. In summary, we tested the following 9 feature representations: color, texture, shape, style, convolutional neural networks (CNNs), CNNs with distance metric learning (CNNs&DML), AutoEncoder, CNNs with multiple layer combination (CNNs&MLC) and CNNs with dynamic feature clustering (CNNs&DFC). Finally, we validated the performance of these features on two publicly available datasets. Quantitative and qualitative experimental results on both intra-domain and inter-domain fashion clothing image retrieval showed that deep learning based feature representations far outweigh traditional hand-crafted feature representation. Additionally, among all deep learning based methods, CNNs with explicit feature clustering performs best, which shows feature clustering is essential for discriminative fashion feature representation.Keywords: convolutional neural network, feature representation, image processing, machine modelling
Procedia PDF Downloads 134548 Optimization of Digestive Conditions of Opuntia ficus-indica var. Saboten using Food-Grade Enzymes
Authors: Byung Wook Yang, Sae Kyul Kim, Seung Il Ahn, Jae Hee Choi, Heejung Jung, Yejin Choi, Byung Yong Kim, Young Tae Hahm
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Opuntia ficus-indica is a member of the Cactaceae family that is widely grown in all the semiarid countries throughout the world. Opuntia ficus-indica var. Saboten (OFS), commonly known as prickly pear cactus, is commercially cultivated as a dietary foodstuffs and medicinal stuffs in Jeju Island, Korea. Owing to high viscosity of OFS’ pad, its application to the commercial field has been limited. When the low viscosity of OFS’s pad is obtained, it is useful for the manufacture of healthy food in the related field. This study was performed to obtain the optimal digestion conditions of food-grade enzymes (Pectinex, Viscozyme and Celluclast) with the powder of OFS stem. And also, the contents of water-soluble dietary fiber (WSDF) of the dried powder prepared by the extraction of OFS stem were monitored and optimized using the response surface methodology (RSM), which included 20 experimental points with 3 replicates for two independent variables (fermentation temperature and time). A central composite design was used to monitor the effect of fermentation temperature (30-90 °C, X1) and fermentation time (1-10h, X2) on dependent variables, such as viscosity (Y1), water-soluble dietary fiber (Y2) and dietary fiber yield (Y3). Estimated maximum values at predicted optimum conditions were in agreement with experimental values. Optimum temperature and duration were 50°C and 12 hours, respectively. Viscosity value reached 3.4 poise. Yield of water-soluble dietary fiber is determined in progress.Keywords: Opuntia ficus-indica var. saboten, enzymatic fermentation, response surface methodology, water-soluble dietary fiber, viscosity
Procedia PDF Downloads 341547 A Sentence-to-Sentence Relation Network for Recognizing Textual Entailment
Authors: Isaac K. E. Ampomah, Seong-Bae Park, Sang-Jo Lee
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Over the past decade, there have been promising developments in Natural Language Processing (NLP) with several investigations of approaches focusing on Recognizing Textual Entailment (RTE). These models include models based on lexical similarities, models based on formal reasoning, and most recently deep neural models. In this paper, we present a sentence encoding model that exploits the sentence-to-sentence relation information for RTE. In terms of sentence modeling, Convolutional neural network (CNN) and recurrent neural networks (RNNs) adopt different approaches. RNNs are known to be well suited for sequence modeling, whilst CNN is suited for the extraction of n-gram features through the filters and can learn ranges of relations via the pooling mechanism. We combine the strength of RNN and CNN as stated above to present a unified model for the RTE task. Our model basically combines relation vectors computed from the phrasal representation of each sentence and final encoded sentence representations. Firstly, we pass each sentence through a convolutional layer to extract a sequence of higher-level phrase representation for each sentence from which the first relation vector is computed. Secondly, the phrasal representation of each sentence from the convolutional layer is fed into a Bidirectional Long Short Term Memory (Bi-LSTM) to obtain the final sentence representations from which a second relation vector is computed. The relations vectors are combined and then used in then used in the same fashion as attention mechanism over the Bi-LSTM outputs to yield the final sentence representations for the classification. Experiment on the Stanford Natural Language Inference (SNLI) corpus suggests that this is a promising technique for RTE.Keywords: deep neural models, natural language inference, recognizing textual entailment (RTE), sentence-to-sentence relation
Procedia PDF Downloads 343546 Forensic Applications of Quantum Dots
Authors: Samaneh Nabavi, Hadi Shirzad, Somayeh Khanjani, Shirin Jalili
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Quantum dots (QDs) are semiconductor nanocrystals that exhibit intrinsic optical and electrical properties that are size dependent due to the quantum confinement effect. Quantum confinement is brought about by the fact that in bulk semiconductor material the electronic structure consists of continuous bands, and that as the size of the semiconductor material decreases its radius becomes less than the Bohr exciton radius (the distance between the electron and electron-hole) and discrete energy levels result. As a result QDs have a broad absorption range and a narrow emission which correlates to the band gap energy (E), and hence QD size. QDs can thus be tuned to give the desired wavelength of fluorescence emission.Due to their unique properties, QDs have attracted considerable attention in different scientific areas. Also, they have been considered for forensic applications in recent years. The ability of QDs to fluoresce up to 20 times brighter than available fluorescent dyes makes them an attractive nanomaterial for enhancing the visualization of latent fingermarks, or poorly developed fingermarks. Furthermore, the potential applications of QDs in the detection of nitroaromatic explosives, such as TNT, based on directive fluorescence quenching of QDs, electron transfer quenching process or fluorescence resonance energy transfer have been paid to attention. DNA analysis is associated tightly with forensic applications in molecular diagnostics. The amount of DNA acquired at a criminal site is inherently limited. This limited amount of human DNA has to be quantified accurately after the process of DNA extraction. Accordingly, highly sensitive detection of human genomic DNA is an essential issue for forensic study. QDs have also a variety of advantages as an emission probe in forensic DNA quantification.Keywords: forensic science, quantum dots, DNA typing, explosive sensor, fingermark analysis
Procedia PDF Downloads 849545 Studies on the Proximate Composition and Functional Properties of Extracted Cocoyam Starch Flour
Authors: Adebola Ajayi, Francis B. Aiyeleye, Olakunke M. Makanjuola, Olalekan J. Adebowale
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Cocoyam, a generic term for both xanthoma and colocasia, is a traditional staple root crop in many developing countries in Africa, Asia and the Pacific. It is mostly cultivated as food crop which is very rich in vitamin B6, magnesium and also in dietary fiber. The cocoyam starch is easily digested and often used for baby food. Drying food is a method of food preservation that removes enough moisture from the food so bacteria, yeast and molds cannot grow. It is a one of the oldest methods of preserving food. The effect of drying methods on the proximate composition and functional properties of extracted cocoyam starch flour were studied. Freshly harvested cocoyam cultivars at matured level were washed with portable water, peeled, washed and grated. The starch in the grated cocoyam was extracted, dried using sun drying, oven and cabinet dryers. The extracted starch flour was milled into flour using Apex mill and packed and sealed in low-density polyethylene film (LDPE) 75 micron thickness with Nylon sealing machine QN5-3200HI and kept for three months under ambient temperature before analysis. The result showed that the moisture content, ash, crude fiber, fat, protein and carbohydrate ranged from 6.28% to 12.8% 2.32% to 3.2%, 0.89% to 2.24%%, 1.89% to 2.91%, 7.30% to 10.2% and 69% to 83% respectively. The functional properties of the cocoyam starch flour ranged from 2.65ml/g to 4.84ml/g water absorption capacity, 1.95ml/g to 3.12ml/g oil absorption capacity, 0.66ml/g to 7.82ml/g bulk density and 3.82% to 5.30ml/g swelling capacity. Significant difference (P≥0.5) was not obtained across the various drying methods used. The drying methods provide extension to the shelf-life of the extracted cocoyam starch flour.Keywords: cocoyam, extraction, oven dryer, cabinet dryer
Procedia PDF Downloads 288544 Innovative Strategies for Chest Wall Reconstruction Following Resection of Recurrent Breast Carcinoma
Authors: Sean Yao Zu Kong, Khong Yik Chew
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Introduction: We described a case report of the successful use of advanced surgical techniques in a patient with recurrent breast cancer who underwent a wide resection including the hemi-sternum, clavicle, multiple ribs, and a lobe of the lung due to tumor involvement. This extensive resection exposed critical structures, requiring a creative approach to reconstruction. To address this complex chest wall reconstruction, a free fibula flap and a 4-zone rectus abdominis musculocutaneous flap were successfully utilized. The use of a free vascularized bone flap allowed for rapid osteointegration and resistance against osteoradionecrosis after adjuvant radiation, while a four-zone tram flap allowed for reconstruction of both the chest wall and breast mound. Although limited recipient vessels made free flaps challenging, the free fibula flap served as both a bony reconstruction and vascular conduit, supercharged with the distal peroneal artery and veins of the peroneal artery from the fibula graft. Our approach highlights the potential of advanced surgical techniques to improve outcomes in complex cases of chest wall reconstruction in patients with recurrent breast cancer, which is becoming increasingly relevant as breast cancer incidence rates increases. Case presentation: This report describes a successful reconstruction of a patient with recurrent breast cancer who required extensive resection, including the anterior chest wall, clavicle, and sternoclavicular joint. Challenges arose due to the loss of accessory muscles and the non-rigid rib cage, which could lead to compromised ventilation and instability. A free fibula osteocutaneous flap and a four-zone TRAM flap with vascular supercharging were utilized to achieve long-term stability and function. The patient has since fully recovered, and during the review, both flaps remained viable, and chest mound reconstruction was satisfactory. A planned nipple/areolar reconstruction was offered pending the patient’s decision after adjuvant radiotherapy. Conclusion: In conclusion, this case report highlights the successful use of innovative surgical techniques in addressing a complex case of recurrent breast cancer requiring extensive resection and radical reconstruction. Our approach, utilized a combination of a free fibula flap and a 4-zone rectus abdominis musculocutaneous flap, demonstrates the potential for advanced techniques in chest wall reconstruction to minimize complications and ensure long-term stability and function. As the incidence of breast cancer continues to rise, it is crucial that healthcare professionals explore and utilize innovative techniques to improve patient outcomes and quality of life.Keywords: free fibula flap, rectus abdominis musculocutaneous flap, post-adjuvant radiotherapy, reconstructive surgery, malignancy
Procedia PDF Downloads 59543 Antiproliferative Effect of Polyphenols from Crocus sativus L. Leaves on Human Colon Adenocarcinoma Cells (Caco-2)
Authors: Gonzalo Ortiz de Elguea-Culebras, Raúl Sánchez-Vioquea, Adela Mena-Morales, Manuel Alaiz, Enrique Melero-Bravo, Esteban García-Romero, Javier Vioque, Lourdes Marchante-Cuevas, Julio Girón-Calle
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Saffron (Crocus sativus L.) is a highly valued crop for the manufacture of spice that consists of the dried stigma of the flowers. This is in contrast to other underutilized parts of the saffron plant as leaves, which represent abundant biomass whose use might help to enhance the sustainability of the saffron crop. Saffron leaves contain significant amounts of phenolic compounds, 7.8 equivalent grams of gallic acid per 100g of extract, and are very promising compounds in terms of exploring novel uses of saffron leaves. Given that phenolic compounds have numerous effects on cancer-related biological pathways, we have investigated the in vitro antiproliferative effect of saffron leaf polyphenols against human colon adenocarcinoma cells (Caco-2). Polyphenols were extracted from leaves with 70% ethanol, defatted with hexane, and purified by solid phase extraction using C18 silica gel and then silica gel 60. Analysis of polyphenols was performed by HPLC-ESI-MS. Di-, tri-, and tetrahexosides of quercetin, kaempferol, and isorhamnetin, as well as C-hexosides like isoorientin and vitexin, were tentatively identified. Polyphenols strongly inhibited the proliferation of Caco-2 cells, which is consistent with model studies in which several of the polyphenols identified in saffron leaves have demonstrated their potential as chemopreventive agents in cancer. Due to the low profitability that saffron leaf currently represents, we consider these results very encouraging and that this by-product deserves further investigation as a potential source of active molecules against colorectal cancer.Keywords: saffron leaves, agricultural by-products, polyphenols, antiproliferative effect, human colon adenocarcinoma cells
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