Search results for: smoker detection
546 99mTc Scintimammography in an Equivocal Breast Lesion
Authors: Malak Shawky Matter Elyas
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Introduction: Early detection of breast cancer is the main tool to decrease morbidity and mortality rates. Many diagnostic tools are used, such as mammograms, ultrasound and magnetic resonance imaging, but none of them is conclusive, especially in very small sizes, less than 1 cm. So, there is a need for more accurate tools. Patients and methods: This study involved 13 patients with different breast lesions. 6 Patients had breast cancer, and one of them had metastatic axillary lymph nodes without clinically nor mammographically detected breast mass proved by biopsy and histopathology. Of the other 7 Patients, 4 of them had benign breast lesions proved by biopsy and histopathology, and 3 Patients showed Equivocal breast lesions on a mammogram. A volume of 370-444Mbq of (99m) Tc/ bombesin was injected. Dynamic 1-min images by Gamma Camera were taken for 20 minutes immediately after injection in the anterior view. Thereafter, two static images in anterior and prone lateral views by Gamma Camera were taken for 5 minutes. Finally, single-photon emission computed tomography images were taken for each patient. The definitive diagnosis was based on biopsy and histopathology. Results: 6 Patients with breast cancer proved by biopsy and histopathology showed Positive findings on Sestamibi (Scintimammography). 1 out of 4 Patients with benign breast lesions proved by biopsy and histopathology showed Positive findings on Sestamibi (Scintimammography) while the other 3 Patients showed Negative findings on Sestamibi. 3 Patients out of 3 Patients with equivocal breast findings on mammogram showed Positive Findings on Sestamibi (Scintimammography) and proved by biopsy and histopathology. Conclusions: While we agree that Scintimammography will not replace mammograms as a mass screening tool, we believe that many patients will benefit from Scintimammography, especially women with dense breast tissues and in the presence of breast implants that are difficult to diagnose by mammogram, wherein its sensitivity is low and in women with metastatic axillary lymph nodes without clinically nor mammographically findings. We can use Scintimammography in sentinel lymph node mapping as a more accurate tool, especially since it is non-invasive.Keywords: breast., radiodiagnosis, lifestyle, surgery
Procedia PDF Downloads 31545 E-Learning Platform for School Kids
Authors: Gihan Thilakarathna, Fernando Ishara, Rathnayake Yasith, Bandara A. M. R. Y.
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E-learning is a crucial component of intelligent education. Even in the midst of a pandemic, E-learning is becoming increasingly important in the educational system. Several e-learning programs are accessible for students. Here, we decided to create an e-learning framework for children. We've found a few issues that teachers are having with their online classes. When there are numerous students in an online classroom, how does a teacher recognize a student's focus on academics and below-the-surface behaviors? Some kids are not paying attention in class, and others are napping. The teacher is unable to keep track of each and every student. Key challenge in e-learning is online exams. Because students can cheat easily during online exams. Hence there is need of exam proctoring is occurred. In here we propose an automated online exam cheating detection method using a web camera. The purpose of this project is to present an E-learning platform for math education and include games for kids as an alternative teaching method for math students. The game will be accessible via a web browser. The imagery in the game is drawn in a cartoonish style. This will help students learn math through games. Everything in this day and age is moving towards automation. However, automatic answer evaluation is only available for MCQ-based questions. As a result, the checker has a difficult time evaluating the theory solution. The current system requires more manpower and takes a long time to evaluate responses. It's also possible to mark two identical responses differently and receive two different grades. As a result, this application employs machine learning techniques to provide an automatic evaluation of subjective responses based on the keyword provided to the computer as student input, resulting in a fair distribution of marks. In addition, it will save time and manpower. We used deep learning, machine learning, image processing and natural language technologies to develop these research components.Keywords: math, education games, e-learning platform, artificial intelligence
Procedia PDF Downloads 156544 The Relationship between Representational Conflicts, Generalization, and Encoding Requirements in an Instance Memory Network
Authors: Mathew Wakefield, Matthew Mitchell, Lisa Wise, Christopher McCarthy
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The properties of memory representations in artificial neural networks have cognitive implications. Distributed representations that encode instances as a pattern of activity across layers of nodes afford memory compression and enforce the selection of a single point in instance space. These encoding schemes also appear to distort the representational space, as well as trading off the ability to validate that input information is within the bounds of past experience. In contrast, a localist representation which encodes some meaningful information into individual nodes in a network layer affords less memory compression while retaining the integrity of the representational space. This allows the validity of an input to be determined. The validity (or familiarity) of input along with the capacity of localist representation for multiple instance selections affords a memory sampling approach that dynamically balances the bias-variance trade-off. When the input is familiar, bias may be high by referring only to the most similar instances in memory. When the input is less familiar, variance can be increased by referring to more instances that capture a broader range of features. Using this approach in a localist instance memory network, an experiment demonstrates a relationship between representational conflict, generalization performance, and memorization demand. Relatively small sampling ranges produce the best performance on a classic machine learning dataset of visual objects. Combining memory validity with conflict detection produces a reliable confidence judgement that can separate responses with high and low error rates. Confidence can also be used to signal the need for supervisory input. Using this judgement, the need for supervised learning as well as memory encoding can be substantially reduced with only a trivial detriment to classification performance.Keywords: artificial neural networks, representation, memory, conflict monitoring, confidence
Procedia PDF Downloads 127543 Implicit Responses for Assessment of Autism Based on Natural Behaviors Obtained Inside Immersive Virtual Environment
Authors: E. Olmos-Raya, A. Cascales Martínez, N. Minto de Sousa, M. Alcañiz Raya
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The late detection and subjectivity of the assessment of Autism Spectrum Disorder (ASD) imposed a difficulty for the children’s clinical and familiar environment. The results showed in this paper, are part of a research project about the assessment and training of social skills in children with ASD, whose overall goal is the use of virtual environments together with physiological measures in order to find a new model of objective ASD assessment based on implicit brain processes measures. In particular, this work tries to contribute by studying the differences and changes in the Skin Conductance Response (SCR) and Eye Tracking (ET) between a typical development group (TD group) and an ASD group (ASD group) after several combined stimuli using a low cost Immersive Virtual Environment (IVE). Subjects were exposed to a virtual environment that showed natural scenes that stimulated visual, auditory and olfactory perceptual system. By exposing them to the IVE, subjects showed natural behaviors while measuring SCR and ET. This study compared measures of subjects diagnosed with ASD (N = 18) with a control group of subjects with typical development (N=10) when exposed to three different conditions: only visual (V), visual and auditory (VA) and visual, auditory and olfactory (VAO) stimulation. Correlations between SCR and ET measures were also correlated with the Autism Diagnostic Observation Schedule (ADOS) test. SCR measures showed significant differences among the experimental condition between groups. The ASD group presented higher level of SCR while we did not find significant differences between groups regarding DF. We found high significant correlations among all the experimental conditions in SCR measures and the subscale of ADOS test of imagination and symbolic thinking. Regarding the correlation between ET measures and ADOS test, the results showed significant relationship between VA condition and communication scores.Keywords: autism, electrodermal activity, eye tracking, immersive virtual environment, virtual reality
Procedia PDF Downloads 139542 A Low Cost Gain-Coupled Distributed Feedback Laser Based on Periodic Surface p-Contacts
Authors: Yongyi Chen, Li Qin, Peng Jia, Yongqiang Ning, Yun Liu, Lijun Wang
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The distributed feedback (DFB) lasers are indispensable in optical phase array (OPA) used for light detection and ranging (LIDAR) techniques, laser communication systems and integrated optics, thanks to their stable single longitudinal mode and narrow linewidth properties. Traditional index-coupled (IC) DFB lasers with uniform gratings have an inherent problem of lasing two degenerated modes. Phase shifts are usually required to eliminate the mode degeneration, making the grating structure complex and expensive. High-quality antireflection (AR) coatings on both lasing facets are also essential owing to the random facet phases introduced by the chip cleavage process, which means half of the lasing energy is wasted. Gain-coupled DFB (GC-DFB) lasers based on the periodic gain (or loss) are announced to have single longitudinal mode as well as capable of the unsymmetrical coating to increase lasing power and efficiency thanks to facet immunity. However, expensive and time-consuming technologies such as epitaxial regrowth and nanoscale grating processing are still required just as IC-DFB lasers, preventing them from practical applications and commercial markets. In this research, we propose a low-cost, single-mode regrowth-free GC-DFB laser based on periodic surface p-contacts. The gain coupling effect is achieved simply by periodic current distribution in the quantum well caused by periodic surface p-contacts, introducing very little index-coupling effect that can be omitted. It is prepared by i-line lithography, without nanoscale grating fabrication or secondary epitaxy. Due to easy fabrication techniques, it provides a method to fabricate practical low cost GC-DFB lasers for widespread practical applications.Keywords: DFB laser, gain-coupled, low cost, periodic p-contacts
Procedia PDF Downloads 128541 Drought Detection and Water Stress Impact on Vegetation Cover Sustainability Using Radar Data
Authors: E. Farg, M. M. El-Sharkawy, M. S. Mostafa, S. M. Arafat
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Mapping water stress provides important baseline data for sustainable agriculture. Recent developments in the new Sentinel-1 data which allow the acquisition of high resolution images and varied polarization capabilities. This study was conducted to detect and quantify vegetation water content from canopy backscatter for extracting spatial information to encourage drought mapping activities throughout new reclaimed sandy soils in western Nile delta, Egypt. The performance of radar imagery in agriculture strongly depends on the sensor polarization capability. The dual mode capabilities of Sentinel-1 improve the ability to detect water stress and the backscatter from the structure components improves the identification and separation of vegetation types with various canopy structures from other features. The fieldwork data allowed identifying of water stress zones based on land cover structure; those classes were used for producing harmonious water stress map. The used analysis techniques and results show high capability of active sensors data in water stress mapping and monitoring especially when integrated with multi-spectral medium resolution images. Also sub soil drip irrigation systems cropped areas have lower drought and water stress than center pivot sprinkler irrigation systems. That refers to high level of evaporation from soil surface in initial growth stages. Results show that high relationship between vegetation indices such as Normalized Difference Vegetation Index NDVI the observed radar backscattering. In addition to observational evidence showed that the radar backscatter is highly sensitive to vegetation water stress, and essentially potential to monitor and detect vegetative cover drought.Keywords: canopy backscatter, drought, polarization, NDVI
Procedia PDF Downloads 144540 Photodegradation of Profoxydim Herbicide in Amended Paddy Soil-Water System
Authors: A. Cervantes-Diaz, B. Sevilla-Moran, Manuel Alcami, Al Mokhtar Lamsabhi, J. L. Alonso-Prados, P. Sandin-España
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Profoxydim is a post-emergence herbicide belonging to the cyclohexanedione oxime family, used to control weeds in rice crops. The use of soil organic amendments has increased significantly in the last decades, and their effects on the behavior of many herbicides are still unknown. Additionally, it is known that photolysis is an important degradation process to be considered when evaluating the persistence of this family of herbicides in the environment. In this work, the photodegradation of profoxydim in an amended paddy soil-water system with alperujo compost was studied. Photodegradation experiments were carried out under laboratory conditions using simulated solar light (Suntest equipment) in order to evaluate the reaction kinetics of the active substance. The photochemical behavior of profoxydim was investigated in soil with and without alperujo amendment. Furthermore, due to the rice crop characteristics, profoxydim photodegradation in water in contact with these types of soils was also studied. Determination of profoxydim degradation kinetics was performed by High-Performance Liquid Chromatography with Diode-Array Detection (HPLC-DAD). Furthermore, we followed the evolution of resulting transformation by-products, and their tentative identification was achieved by mass spectrometry. All the experiments allowed us to fit the data of profoxydim photodegradation to a first-order kinetic. Photodegradation of profoxydim was very rapid in all cases. The half-lives in aqueous matrices were in the range of 86±0.3 to 103±0.5 min. The addition of alperujo amendment to the soil produced an increase in the half-life from 62±0.2 min (soil) to 75±0.3 min (amended soil). In addition, a comparison to other organic amendments was also performed. Results showed that the presence of the organic amendment retarded the photodegradation in paddy soil and water. Regarding degradation products, the main process involved was the cleavage of the oxime moiety giving rise to the formation of the corresponding imine compound.Keywords: by-products, herbicide, organic amendment, photodegradation, profoxydim
Procedia PDF Downloads 79539 Seroprevalence and Potential Risk Factors of Bovine Brucellosis under Diverse Production Systems in Central Punjab, Paksitan
Authors: A. Khan, I. Khan, M. Younus, S. E. Haque, U. Waheed, H. Neubauer, A. A. Anjum, S. A. Muhammad, A. Idrees T. Abbas, S. Raza, M. A. Ali, M. Farooq, M. Mahmood, A. Hussain, H. Danish, U. Tayyab, M. Zafar, M. Aslam.
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Brucellosis is one of the major problems of milk producing animals in our country which deteriorate the health of livestock. It is a disease of zoonotic significance which is capable of producing disease in humans leading to infertility, orchitis, abortions, and synovitis. In this particular study, milk and serum samples of cattle and buffalo (n=402) were collected from different districts of Punjab including Narowal, Gujranwala and Gujrat. Milk samples were analyzed by Milk Ring Test (MRT), while serum samples were tested through Rose Bengal Plate agglutination Test (RBPT) and Indirect Enzyme Linked Immunosorbant Assay (i-ELISA). The sample tested with MRT were 9.5% positive, including cattle 9.6% and buffalo 9.3%. While using the RBPT test for the detection of serum samples and for screening purpose it was observed that 16.4% animals were seropositive, cattle were 18.8% and buffalo were 13.9% seropositive. The higher prevalence of brucellosis indicates the danger of the disease to human population. The serum samples positive by RBPT were further confirmed by the use of most specific and sensitive serological test known as i-ELISA. 11.4% animals were confirmed as seropositive by i-ELISA including cattle 13.5% seropositive and buffalo 9.3%. The results indicated high seroprevalence of brucellosis in cattle as compared to buffalos. Different risk factors were also studied to know the association between disease and their spread. Advanced age, larger herds, history of abortion and pregnancy of the animals is considered to be the important factors for the prevalence and spread of the hazardous zoonotic disease. It is a core issue of developing countries like Pakistan and has major public health impact.Keywords: humans, bovines, infertility, orchitis, abortions, seroprevalence, brucellosis
Procedia PDF Downloads 484538 Congenital Heart Defect(CHD) “The Silent Crises”; The Need for New Innovative Ways to Save the Ghanaian Child - A Retrospective Study
Authors: Priscilla Akua Agyapong
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Background: In a country of nearly 34 million people, Ghana suffers from rapidly growing pediatric CHD cases and not enough pediatric specialists to attend to the burgeoning needs of these children. Most of the cases are either missed or diagnosed late, resulting in increased mortality. According to the National Cardiothoracic Centre, 1 in every 100,000 births in Ghana has CHD; however, there is limited data on the clinical presentation and its management, one of the many reasons I decided to do this case study coupled with the loss my 2 month old niece to multiple Ventricular Septal Defect 3 years ago due late diagnoses. Method: A retrospective cohort study was performed at the child health clinic of one of Ghana’s public tertiary Institutions using data from their electronic health record (EHR) from February 2021 to April 2022. All suspected or provisionally diagnosed cases were included in the analysis. Results: Records of over 3000 children were reviewed with an approximate male to female ratio of 1:1.53 cases diagnosed during the period of study, most of whom were less than 5 years of age. 25 cases had complete clinical records, with acyanotic septal defects being the most diagnosed. 62.5% of the cases were ventricular septal defects, followed by Patent Ductus Arteriosus (23%) and Atrial Septal Defects (4.5%). Tetralogy of Fallot was the most predominant and complex cyanotic CHD with 10%. Conclusion: The indeterminate coronary anatomy of infants makes it difficult to use only echocardiography and other conventional clinical methods in screening for CHDs. There are rising modernizations and new innovative ways that can be employed in Ghana for early detection, hence preventing the delay of a potential surgical repair. It is, therefore, imperative to create the needed awareness about these “SILENT CRISES” and help save the Ghanaian child’s life.Keywords: congenital heart defect(CHD), ventricular septal defect(VSD), atrial septal defect(ASD), patent ductus arteriosus(PDA)
Procedia PDF Downloads 89537 Assessment of Predictive Confounders for the Prevalence of Breast Cancer among Iraqi Population: A Retrospective Study from Baghdad, Iraq
Authors: Nadia H. Mohammed, Anmar Al-Taie, Fadia H. Al-Sultany
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Although breast cancer prevalence continues to increase, mortality has been decreasing as a result of early detection and improvement in adjuvant systemic therapy. Nevertheless, this disease required further efforts to understand and identify the associated potential risk factors that could play a role in the prevalence of this malignancy among Iraqi women. The objective of this study was to assess the perception of certain predictive risk factors on the prevalence of breast cancer types among a sample of Iraqi women diagnosed with breast cancer. This was a retrospective observational study carried out at National Cancer Research Center in College of Medicine, Baghdad University from November 2017 to January 2018. Data of 100 patients with breast cancer whose biopsies examined in the National Cancer Research Center were included in this study. Data were collected to structure a detailed assessment regarding the patients’ demographic, medical and cancer records. The majority of study participants (94%) suffered from ductal breast cancer with mean age 49.57 years. Among those women, 48.9% were obese with body mass index (BMI) 35 kg/m2. 68.1% of them had positive family history of breast cancer and 66% had low parity. 40.4% had stage II ductal breast cancer followed by 25.5% with stage III. It was found that 59.6% and 68.1% had positive oestrogen receptor sensitivity and positive human epidermal growth factor (HER2/neu) receptor sensitivity respectively. In regard to the impact of prediction of certain variables on the incidence of ductal breast cancer, positive family history of breast cancer (P < 0.0001), low parity (P< 0.0001), stage I and II breast cancer (P = 0.02) and positive HER2/neu status (P < 0.0001) were significant predictive factors among the study participants. The results from this study provide relevant evidence for a significant positive and potential association between certain risk factors and the prevalence of breast cancer among Iraqi women.Keywords: Ductal Breast Cancer, Hormone Sensitivity, Iraq, Risk Factors
Procedia PDF Downloads 128536 Satureja bachtiarica Bunge Induce Apoptosis via Mitochondrial Intrinsic Pathway and G1 Cell Cycle Arrest
Authors: Hamed Karimian, Noraziah Nordin, Mohamad Ibrahim Noordin, Syam Mohan, Mahboubeh Razavi, Najihah Mohd Hashim, Happipah Mohd Ali
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Satureja bachtiarica Bunge is a perennial medicinal plant belonging to the Lamiaceae family and endemic species in Iran. Satureja bachtiarica Bunge with the local name of Marzeh koohi is edible vegetable use as flavoring agent, anti-bacterial and to relieve cough and indigestion. In this study, the anti-cancer effect of Satureja bachtiarica Bunge on the MDA-MB-231 cell line as an Breast cancer cell model has been analyzed for the first time. Satureja bachtiarica Bunge was extracted using different solvents in the order of increasing polarity. Cytotoxicity activity of hexane extract of Satureja bachtiarica Bunge (SBHE) was observed using MTT assay. Acridine orange/Propidium iodide staining was used to detect early apoptosis; Annexin-V-FITC assay was carried out to observe the detection of cell-surface Phosphatidylserine (PS), with Annexin-Vserving as a marker for apoptotic cells. Caspase 3/7, 8 and-9 assays showed significantly activation of caspase-9 where lead intrinsic mitochondrial pathway. Bcl-2/Bax expressions and cell cycle arrest were also investigated. SBHE had exhibited significantly higher cytotoxicity against MDA-MB-231 Cell line compare to other cell lines. A significant increase in chromatin condensation in the cell nucleus was observed by fluorescence analysis. Treatment of MDA-MB-231 cells with SBHE encouraged apoptosis, by down-regulating Bcl-2 and up-regulating Bax, which lead the activation of caspase 9. Moreover, SBHE treatment significantly arrested MDA-MB-231 cells in the G1 phase. Together, the results presented in this study demonstrated that SBHE inhibited the proliferation of MDA-MB-231 cells, leading cell cycle arrest and programmed cell death, which was confirmed to be through the mitochondrial pathway.Keywords: Satureja bachtiarica Bunge, MDA-MB-231, apoptosis, annexin-V, cell cycle
Procedia PDF Downloads 337535 Detecting Local Clusters of Childhood Malnutrition in the Island Province of Marinduque, Philippines Using Spatial Scan Statistic
Authors: Novee Lor C. Leyso, Maylin C. Palatino
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Under-five malnutrition continues to persist in the Philippines, particularly in the island Province of Marinduque, with prevalence of some forms of malnutrition even worsening in recent years. Local spatial cluster detection provides a spatial perspective in understanding this phenomenon as key in analyzing patterns of geographic variation, identification of community-appropriate programs and interventions, and focused targeting on high-risk areas. Using data from a province-wide household-based census conducted in 2014–2016, this study aimed to determine and evaluate spatial clusters of under-five malnutrition, across the province and within each municipality at the individual level using household location. Malnutrition was defined as weight-for-age z-score that fall outside the 2 standard deviations from the median of the WHO reference population. The Kulldorff’s elliptical spatial scan statistic in binomial model was used to locate clusters with high-risk of malnutrition, while adjusting for age and membership to government conditional cash transfer program as proxy for socio-economic status. One large significant cluster of under-five malnutrition was found southwest of the province, in which living in these areas at least doubles the risk of malnutrition. Additionally, at least one significant cluster were identified within each municipality—mostly located along the coastal areas. All these indicate apparent geographical variations across and within municipalities in the province. There were also similarities and disparities in the patterns of risk of malnutrition in each cluster across municipalities, and even within municipality, suggesting underlying causes at work that warrants further investigation. Therefore, community-appropriate programs and interventions should be identified and should be focused on high-risk areas to maximize limited government resources. Further studies are also recommended to determine factors affecting variations in childhood malnutrition considering the evidence of spatial clustering found in this study.Keywords: Binomial model, Kulldorff’s elliptical spatial scan statistic, Philippines, under-five malnutrition
Procedia PDF Downloads 140534 Association Analysis of Putative Loci with Coronary Artery Disease
Authors: Asma Naseer Cheema, Attya Bhatti, Jabar Ali, John Peter
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Background: High cholesterol levels, endothelial dysfunction, inefficient coagulation cascade and hyper inflammatory response all are the basis of coronary artery disease (CAD). Several studies are carried out to see the genetic influence of these factors on disease outcome. Objective: The objective of our study was to see the association of 10 putative loci with coronary artery disease in our population. Materials & Methods: We screened our population for 10 putative loci of CAD showing significant association (p < 5x10-8) with candidate genes (regulating the cholesterol metabolism, endothelial function, coagulation cascade and inflammatory response of body). Hardy-Weinberg equilibrium and linkage disequilibrium in cases and controls s were estimated separately. Approximately 5-10 ng of dried DNA in 384 well plate format was used to genotype each sample on the Sequenom iPLEX assay at University of Pittsburgh Genomics and Proteomics Core Laboratories. It was built on single-base primer extension with the MALDI-TOF MS detection possessing high sensitivity and specificity. The SNPs were genotyped through Taqman assay. Hardy Weinberg test was applied. The 10 SNPs were selected as genetic markers for this study (rs579459, rs1561198, rs2954029, rs1122608, rs17114036, rs9515203, rs10947789, rs7173743, rs2895811, rs2075650). Results: Mean age of the patient was 52 ± 11 years. Blood pressure and positive family history was found a significant risk factor for CAD. None of the selected SNPs showed significant association with coronary artery disease in our population (p>0.05). Conclusion: rs579459, rs1561198, rs2954029, rs1122608, rs17114036, rs9515203, rs10947789, rs7173743, rs2895811, rs2075650 are not significant genetic markers for CAD in our population.Keywords: CAD, genetic markers, loci, risk factors
Procedia PDF Downloads 369533 Implementation of Algorithm K-Means for Grouping District/City in Central Java Based on Macro Economic Indicators
Authors: Nur Aziza Luxfiati
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Clustering is partitioning data sets into sub-sets or groups in such a way that elements certain properties have shared property settings with a high level of similarity within one group and a low level of similarity between groups. . The K-Means algorithm is one of thealgorithmsclustering as a grouping tool that is most widely used in scientific and industrial applications because the basic idea of the kalgorithm is-means very simple. In this research, applying the technique of clustering using the k-means algorithm as a method of solving the problem of national development imbalances between regions in Central Java Province based on macroeconomic indicators. The data sample used is secondary data obtained from the Central Java Provincial Statistics Agency regarding macroeconomic indicator data which is part of the publication of the 2019 National Socio-Economic Survey (Susenas) data. score and determine the number of clusters (k) using the elbow method. After the clustering process is carried out, the validation is tested using themethodsBetween-Class Variation (BCV) and Within-Class Variation (WCV). The results showed that detection outlier using z-score normalization showed no outliers. In addition, the results of the clustering test obtained a ratio value that was not high, namely 0.011%. There are two district/city clusters in Central Java Province which have economic similarities based on the variables used, namely the first cluster with a high economic level consisting of 13 districts/cities and theclustersecondwith a low economic level consisting of 22 districts/cities. And in the cluster second, namely, between low economies, the authors grouped districts/cities based on similarities to macroeconomic indicators such as 20 districts of Gross Regional Domestic Product, with a Poverty Depth Index of 19 districts, with 5 districts in Human Development, and as many as Open Unemployment Rate. 10 districts.Keywords: clustering, K-Means algorithm, macroeconomic indicators, inequality, national development
Procedia PDF Downloads 158532 Optimizing Perennial Plants Image Classification by Fine-Tuning Deep Neural Networks
Authors: Khairani Binti Supyan, Fatimah Khalid, Mas Rina Mustaffa, Azreen Bin Azman, Amirul Azuani Romle
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Perennial plant classification plays a significant role in various agricultural and environmental applications, assisting in plant identification, disease detection, and biodiversity monitoring. Nevertheless, attaining high accuracy in perennial plant image classification remains challenging due to the complex variations in plant appearance, the diverse range of environmental conditions under which images are captured, and the inherent variability in image quality stemming from various factors such as lighting conditions, camera settings, and focus. This paper proposes an adaptation approach to optimize perennial plant image classification by fine-tuning the pre-trained DNNs model. This paper explores the efficacy of fine-tuning prevalent architectures, namely VGG16, ResNet50, and InceptionV3, leveraging transfer learning to tailor the models to the specific characteristics of perennial plant datasets. A subset of the MYLPHerbs dataset consisted of 6 perennial plant species of 13481 images under various environmental conditions that were used in the experiments. Different strategies for fine-tuning, including adjusting learning rates, training set sizes, data augmentation, and architectural modifications, were investigated. The experimental outcomes underscore the effectiveness of fine-tuning deep neural networks for perennial plant image classification, with ResNet50 showcasing the highest accuracy of 99.78%. Despite ResNet50's superior performance, both VGG16 and InceptionV3 achieved commendable accuracy of 99.67% and 99.37%, respectively. The overall outcomes reaffirm the robustness of the fine-tuning approach across different deep neural network architectures, offering insights into strategies for optimizing model performance in the domain of perennial plant image classification.Keywords: perennial plants, image classification, deep neural networks, fine-tuning, transfer learning, VGG16, ResNet50, InceptionV3
Procedia PDF Downloads 64531 Evaluation of Two DNA Extraction Methods for Minimal Porcine (Pork) Detection in Halal Food Sample Mixture Using Taqman Real-time PCR Technique
Authors: Duaa Mughal, Syeda Areeba Nadeem, Shakil Ahmed, Ishtiaq Ahmed Khan
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The identification of porcine DNA in Halal food items is critical to ensuring compliance with dietary restrictions and religious beliefs. In Islam, Porcine is prohibited as clearly mentioned in Quran (Surah Al-Baqrah, Ayat 173). The purpose of this study was to compare two DNA extraction procedures for detecting 0.001% of porcine DNA in processed Halal food sample mixtures containing chicken, camel, veal, turkey and goat meat using the TaqMan Real-Time PCR technology. In this research, two different commercial kit protocols were compared. The processed sample mixtures were prepared by spiking known concentration of porcine DNA to non-porcine food matrices. Afterwards, TaqMan Real-Time PCR technique was used to target a particular porcine gene from the extracted DNA samples, which was quantified after extraction. The results of the amplification were evaluated for sensitivity, specificity, and reproducibility. The results of the study demonstrated that two DNA extraction techniques can detect 0.01% of porcine DNA in mixture of Halal food samples. However, as compared to the alternative approach, Eurofins| GeneScan GeneSpin DNA Isolation kit showed more effective sensitivity and specificity. Furthermore, the commercial kit-based approach showed great repeatability with minimal variance across repeats. Quantification of DNA was done by using fluorometric assay. In conclusion, the comparison of DNA extraction methods for detecting porcine DNA in Halal food sample mixes using the TaqMan Real-Time PCR technology reveals that the commercial kit-based approach outperforms the other methods in terms of sensitivity, specificity, and repeatability. This research helps to promote the development of reliable and standardized techniques for detecting porcine DNA in Halal food items, religious conformity and assuring nutritional.Keywords: real time PCR (qPCR), DNA extraction, porcine DNA, halal food authentication, religious conformity
Procedia PDF Downloads 78530 Design and Fabrication of Piezoelectric Tactile Sensor by Deposition of PVDF-TrFE with Spin-Coating Method for Minimally Invasive Surgery
Authors: Saman Namvarrechi, Armin A. Dormeny, Javad Dargahi, Mojtaba Kahrizi
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Since last two decades, minimally invasive surgery (MIS) has grown significantly due to its advantages compared to the traditional open surgery like less physical pain, faster recovery time and better healing condition around incision regions; however, one of the important challenges in MIS is getting an effective sensing feedback within the patient’s body during operations. Therefore, surgeons need efficient tactile sensing like determining the hardness of contact tissue for investigating the patient’s health condition. In such a case, MIS tactile sensors are preferred to be able to provide force/pressure sensing, force position, lump detection, and softness sensing. Among different pressure sensor technologies, the piezoelectric operating principle is the fittest for MIS’s instruments, such as catheters. Using PVDF with its copolymer, TrFE, as a piezoelectric material, is a common method of design and fabrication of a tactile sensor due to its ease of implantation and biocompatibility. In this research, PVDF-TrFE polymer is deposited via spin-coating method and treated with various post-deposition processes to investigate its piezoelectricity and amount of electroactive β phase. These processes include different post thermal annealing, the effect of spin-coating speed, different layer of deposition, and the presence of additional hydrate salt. According to FTIR spectroscopy and SEM images, the amount of the β phase and porosity of each sample is determined. In addition, the optimum experimental study is established by considering every aspect of the fabrication process. This study clearly shows the effective way of deposition and fabrication of a tactile PVDF-TrFE based sensor and an enhancement methodology to have a higher β phase and piezoelectric constant in order to have a better sense of touch at the end effector of biomedical devices.Keywords: β phase, minimally invasive surgery, piezoelectricity, PVDF-TrFE, tactile sensor
Procedia PDF Downloads 122529 The Use of Correlation Difference for the Prediction of Leakage in Pipeline Networks
Authors: Mabel Usunobun Olanipekun, Henry Ogbemudia Omoregbee
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Anomalies such as water pipeline and hydraulic or petrochemical pipeline network leakages and bursts have significant implications for economic conditions and the environment. In order to ensure pipeline systems are reliable, they must be efficiently controlled. Wireless Sensor Networks (WSNs) have become a powerful network with critical infrastructure monitoring systems for water, oil and gas pipelines. The loss of water, oil and gas is inevitable and is strongly linked to financial costs and environmental problems, and its avoidance often leads to saving of economic resources. Substantial repair costs and the loss of precious natural resources are part of the financial impact of leaking pipes. Pipeline systems experts have implemented various methodologies in recent decades to identify and locate leakages in water, oil and gas supply networks. These methodologies include, among others, the use of acoustic sensors, measurements, abrupt statistical analysis etc. The issue of leak quantification is to estimate, given some observations about that network, the size and location of one or more leaks in a water pipeline network. In detecting background leakage, however, there is a greater uncertainty in using these methodologies since their output is not so reliable. In this work, we are presenting a scalable concept and simulation where a pressure-driven model (PDM) was used to determine water pipeline leakage in a system network. These pressure data were collected with the use of acoustic sensors located at various node points after a predetermined distance apart. We were able to determine with the use of correlation difference to determine the leakage point locally introduced at a predetermined point between two consecutive nodes, causing a substantial pressure difference between in a pipeline network. After de-noising the signal from the sensors at the nodes, we successfully obtained the exact point where we introduced the local leakage using the correlation difference model we developed.Keywords: leakage detection, acoustic signals, pipeline network, correlation, wireless sensor networks (WSNs)
Procedia PDF Downloads 109528 Investigation of Fumaric Acid Radiolysis Using Gamma Irradiation
Authors: Wafa Jahouach-Rabai, Khouloud Ouerghi, Zohra Azzouz-Berriche, Faouzi Hosni
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Widely used organic products in the pharmaceutical industry have been detected in environmental systems, essentially carboxylic acids. In this purpose, the degradation efficiency of these contaminants was evaluated using an advanced oxidation process (AOP), namely ionization process as an alternative to conventional water treatment technologies. This process permitted the generation of radical reactions to directly degrade organic pollutants in wastewater. In fact, gamma irradiation of aqueous solutions produces several reactive radicals, essentially hydroxyl radical (OH), to destroy recalcitrant pollutants. Different concentrations of aqueous solutions of Fumaric acid (FA) were considered in this study (0.1-1 mmol/L), which were treated by irradiation doses from 1 to 15 kGy with 6.1 kGy/h rate by ionizing system in pilot scale (⁶⁰Co irradiator). Variations of main parameters influencing degradation efficiency versus absorbed doses were released in the aim to optimize total mineralization of considered pollutants. Preliminary degradation pathway until complete mineralization into CO₂ has been suggested based on detection of residual degradation derivatives using different techniques, namely high performance liquid chromatography (HPLC) and electron paramagnetic resonance spectroscopy (EPR). Results revealed total destruction of treated compound, which improve the efficiency of this process in water remediation. We investigated the reactivity of hydroxyl radicals generated by irradiation on dicarboxylic acid (FA) in aqueous solutions, leading to its degradation into other smaller molecules. In fact, gamma irradiation of FA leads to the formation of hydroxylated intermediates such as hydroxycarbonyl radical which were identified by EPR spectroscopy. Finally, pilot plant irradiation facilities improved the applicability of radiation technology on large scale.Keywords: AOP, radiolysis, fumaric acid, gamma irradiation, hydroxyl radical, EPR, HPLC
Procedia PDF Downloads 173527 Sensory Evaluation and Microbiological Properties of Gouda Cheese Affected by Bunium persicum (Boiss.) Essential Oil
Authors: N. Noori, P. Taherkhani, A. Akhondzadeh Basti, H. Gandomi, M. Alimohammadi
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Research on natural antimicrobial agents, especially of plant origin, highly noticed in recent years and evaluation of antimicrobial effects of native plants such as Bunium persicum Boiss. is especially important. In the present study, sensory characteristics and microbiological properties of Gouda cheese affected by different concentrations of Bunium persicum Boiss. essential oil were investigated. Extraction of the essential oil was performed by hydro distillation. The oil was analyzed by GC using flame ionization (FID) and GC/ MS for detection. The antimicrobial effects were determined against various microbial groups (aerobic mesophilic bacteria, enterococci, mesophilic lactobacilli, enterobacteriaceae, lactococcus and yeasts). Microbial groups were counted during ripening period using plate count on specific culture media. Organoleptic evaluation including teture, flavor, odor, color and total acceptability were determined at the end of aging. According to results, the essential oil yield was 4/1 % ( W/ W). Twenty- six compounds were identified in the oil that concluded 99.7 % of the total oil. The major components of Bunium persicum Boiss. essential oil were γ- terpinene- 7- al (26.9 %) and cuminaldehyde (23.3 %). Generally, the increase of Black Cumin essential oil concentration led to reduction in microbial counts in different groups. The maximum antimicrobial effect was seen in yeast that reduced by 2 log compared to the control group at EO concentration of 4µl/ ml at day 90.The minimum reduction was observed in enterobacteriaceae that showed only 0.75 log decreese compared to the control at the same concentration of EO. Addition of EO improved organoleptic properties of Gouda cheese especially in the case of flavor and odor characteristic. However, no significant differences were observed in texture and color between treatment and control groups. Bunium persicum Boiss. essential oil could be used as preservative material and flavoring agent in some kinds of food such as cheese and also could be provided consumers health.Keywords: Bunium persicum Boiss. essential oil, Microbiological properties, sensory evaluation, gouda cheese
Procedia PDF Downloads 325526 Zinc Nanoparticles Modified Electrode as an Insulin Sensor
Authors: Radka Gorejova, Ivana Sisolakova, Jana Shepa, Frederika Chovancova, Renata Orinakova
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Diabetes mellitus (DM) is a serious metabolic disease characterized by chronic hyperglycemia. Often, the symptoms are not sufficiently observable at early stages, and so hyperglycemia causes pathological and functional changes before the diagnosis of the DM. Therefore, the development of an electrochemical sensor that will be fast, accurate, and instrumentally undemanding is currently needful. Screen-printed carbon electrodes (SPCEs) can be considered as the most suitable matrix material for insulin sensors because of the small size of the working electrode. It leads to the analyst's volume reduction to only 50 µl for each measurement. The surface of bare SPCE was modified by a combination of chitosan, multi-walled carbon nanotubes (MWCNTs), and zinc nanoparticles (ZnNPs) to obtain better electrocatalytic activity towards insulin oxidation. ZnNPs were electrochemically deposited on the chitosan-MWCNTs/SPCE surface using the pulse deposition method. Thereafter, insulin was determined on the prepared electrode using chronoamperometry and electrochemical impedance spectroscopy (EIS). The chronoamperometric measurement was performed by adding a constant amount of insulin in 0.1 M NaOH and PBS (2 μl) with the concentration of 2 μM, and the current response of the system was monitored after a gradual increase in concentration. Subsequently, the limit of detection (LOD) of the prepared electrode was determined via the Randles-Ševčík equation. The LOD was 0.47 µM. Prepared electrodes were studied also as the impedimetric sensors for insulin determination. Therefore, various insulin concentrations were determined via EIS. Based on the performed measurements, the ZnNPs/chitosan-MWCNTs/SPCE can be considered as a potential candidate for novel electrochemical sensor for insulin determination. Acknowledgments: This work has been supported by the projects Visegradfund project number 22020140, VEGA 1/0095/21 of the Slovak Scientific Grant Agency, and APVV-PP-COVID-20-0036 of the Slovak Research and Development Agency.Keywords: zinc nanoparticles, insulin, chronoamperometry, electrochemical impedance spectroscopy
Procedia PDF Downloads 122525 A Web Service Based Sensor Data Management System
Authors: Rose A. Yemson, Ping Jiang, Oyedeji L. Inumoh
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The deployment of wireless sensor network has rapidly increased, however with the increased capacity and diversity of sensors, and applications ranging from biological, environmental, military etc. generates tremendous volume of data’s where more attention is placed on the distributed sensing and little on how to manage, analyze, retrieve and understand the data generated. This makes it more quite difficult to process live sensor data, run concurrent control and update because sensor data are either heavyweight, complex, and slow. This work will focus on developing a web service platform for automatic detection of sensors, acquisition of sensor data, storage of sensor data into a database, processing of sensor data using reconfigurable software components. This work will also create a web service based sensor data management system to monitor physical movement of an individual wearing wireless network sensor technology (SunSPOT). The sensor will detect movement of that individual by sensing the acceleration in the direction of X, Y and Z axes accordingly and then send the sensed reading to a database that will be interfaced with an internet platform. The collected sensed data will determine the posture of the person such as standing, sitting and lying down. The system is designed using the Unified Modeling Language (UML) and implemented using Java, JavaScript, html and MySQL. This system allows real time monitoring an individual closely and obtain their physical activity details without been physically presence for in-situ measurement which enables you to work remotely instead of the time consuming check of an individual. These details can help in evaluating an individual’s physical activity and generate feedback on medication. It can also help in keeping track of any mandatory physical activities required to be done by the individuals. These evaluations and feedback can help in maintaining a better health status of the individual and providing improved health care.Keywords: HTML, java, javascript, MySQL, sunspot, UML, web-based, wireless network sensor
Procedia PDF Downloads 212524 Ecological Risk Assessment of Informal E-Waste Processing in Alaba International Market, Lagos, Nigeria
Authors: A. A. Adebayo, O. Osibanjo
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Informal electronic waste (e-waste) processing is a crude method of recycling, which is on the increase in Nigeria. The release of hazardous substances such as heavy metals (HMs) into the environment during informal e-waste processing has been a major concern. However, there is insufficient information on environmental contamination from e-waste recycling, associated ecological risk in Alaba International Market, a major electronic market in Lagos, Nigeria. The aims of this study were to determine the levels of HMs in soil, resulting from the e-waste recycling; and also assess associated ecological risks in Alaba international market. Samples of soils (334) were randomly collected seasonally for three years from fourteen selected e-waste activity points and two control sites. The samples were digested using standard methods and HMs analysed by inductive coupled plasma optical emission. Ecological risk was estimated using Ecological Risk index (ER), Potential Ecological Risk index (RI), Index of geoaccumulation (Igeo), Contamination factor (Cf) and degree of contamination factor (Cdeg). The concentrations range of HMs (mg/kg) in soil were: 16.7-11200.0 (Pb); 14.3-22600.0 (Cu); 1.90-6280.0 (Ni), 39.5-4570.0 (Zn); 0.79-12300.0 (Sn); 0.02-138.0 (Cd); 12.7-1710.0 (Ba); 0.18-131.0 (Cr); 0.07-28.0 (V), while As was below detection limit. Concentrations range in control soils were 1.36-9.70 (Pb), 2.06-7.60 (Cu), 1.25-5.11 (Ni), 3.62-15.9 (Zn), BDL-0.56 (Sn), BDL-0.01 (Cd), 14.6-47.6 (Ba), 0.21–12.2 (Cr) and 0.22-22.2 (V). The trend in ecological risk index was in the order Cu > Pb > Ni > Zn > Cr > Cd > Ba > V. The potential ecological risk index with respect to informal e-waste activities were: burning > dismantling > disposal > stockpiling. The index of geo accumulation indices revealed that soils were extremely polluted with Cd, Cu, Pb, Zn and Ni. The contamination factor indicated that 93% of the studied areas have very high contamination status for Pb, Cu, Ba, Sn and Co while Cr and Cd were in the moderately contaminated status. The degree of contamination decreased in the order of Sn > Cu > Pb >> Zn > Ba > Co > Ni > V > Cr > Cd. Heavy metal contamination of Alaba international market environment resulting from informal e-waste processing was established. Proper management of e-waste and remediation of the market environment are recommended to minimize the ecological risks.Keywords: Alaba international market, ecological risk, electronic waste, heavy metal contamination
Procedia PDF Downloads 197523 A Cross-Sectional Study of Parents’ Knowledge, Attitude, and Health-Seeking Behaviour Towards Childhood Tuberculosis during COVID-19 Pandemic: Lessons Learned from Indonesia
Authors: Windy Rakhmawati, Suryani Suryani, Sri Hendrawati, Nenden Nur Asriyani Maryam
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Tuberculosis (TB) is one of the leading causes of death in the world. Fear of COVID-19 has made people reluctant to visit health facilities, leading to disruptions to childhood TB control programs, which may increase household transmission and delay diagnosis and treatment. This study aimed to describe parents' knowledge, attitudes, and health-seeking behaviour towards childhood TB during the COVID-19 pandemic. This cross-sectional study was performed on 392 parents with TB children in three provinces with the highest proportion of TB cases in Indonesia. This study was conducted from February to December 2022. The inclusion criteria of respondents were parents with a child aged 0-14 years old with TB diagnosis who live with their parents. Data were collected using the Knowledge, Attitude, and Practice (KAP) survey guidelines from the World Health Organization and analyzed descriptively, as well as Spearman’s correlation. Overall, 392 parents of children with TB had poor knowledge (51.8%) including about causes, risk factors, transmission, symptoms, treatment, and prevention, which about 52.3%, 55.1%, 61.2%, 69.6%, 100%, 59.2%, respectively. Parents' health service-seeking behaviour towards Child TB was not normally distributed (P < 0.05) with knowledge test results (.000) and Seeking Health Services (.000). Health-seeking behaviour of parents in pediatric TB care was self-medication or self-treatment (86.2%), Traditional health seeking behaviour (4.8%), and modern health seeking behaviour (8.9%). The correlation between knowledge and seeking health services (Sig= .609) means there is no correlation between knowledge about TB and parents' health-seeking behaviour. Furthermore, 60.2% of the respondents would be shocked if their child had TB. More than half of the families in this study have poor knowledge and did self-medication or self-treatment regarding health-seeking behaviour for TB disease. Therefore, health workers, especially nurses, must provide TB-related education and health promotion and emphasize the importance of early detection. Health workers can also optimize their role in caring for and providing care to patients by increasing their trust in health workers, which will impact health-seeking behaviour in the future.Keywords: attitude, child, health seeking behaviour, knowledge, tuberculosis
Procedia PDF Downloads 67522 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
Procedia PDF Downloads 198521 Prenatal Exposure to Organophosphate Pesticide and Fetal Growth
Authors: Yi-Shuan ShaoShao, Yen-An Tsai, Chia-Huang Chang, Kai-Wei Liao, Ming-Song Tsai, Mei-Lien Chen
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Organophosphate pesticides (OPs) is an environmental hormone with proven endocrine-disrupting effects that may affect the growth and development in human. A large amount of organophosphate pesticides (OPs) is used throughout Taiwan, and human may be exposed through dietary intake or residential use. During pregnancy, OPs can be transferred to the blood stream reaching the fetus through the placenta. The aim of this study was to explore the association between maternal OPs exposure levels and fetal developments and birth outcomes. A birth cohort was follow-up. Maternal urine sample were collected at the first, second, and third gestational trimester. Fetal growth characteristics were measured by ultrasonic scan and birth outcomes were assessed by pediatrician. Urinary metabolite of organophosphate pesticides were assessed using gas chromatography-mass spectrometry. The analytes included dimethylphosphate (DMP), dimethylthiophosphate (DMTP), dimethyldithiophosphates (DMDTP), diethylphosphate (DEP), diethylthiophosphate (DETP), and diethyldithiophosphate (DEDTP). We found that all of urine samples in each trimester were detected at least one metabolite for dialkyl phosphate (DAP). The detection rate range of OP urinary metabolites were from the lowest 22% DEDTP to the highest 100% DMP and DMTP. And to compared geometric means (GM) of urinary metabolites with three trimesters, that third trimester had the highest concentration for DMPs, DEPs, and DAPs in pregnant women were 368.01, 169.85 and 543.75 nmol/g creatinine, respectively. We observed that DAPs concentration in first and second trimester were significantly negative association with head circumference. DMPs in first trimester was significantly negative association with thoracic circumference (p=0.05) by spearman correlation. Our results support associations with prenatal OPs exposure with fetal head circumference and thoracic circumference. It provided that maternal OPs exposure might affect birth outcomes. Thus, prenatal exposure to OPs and health risk worthy of attention and concern.Keywords: DAPs, birth outcomes, organophosphate pesticides, prenatal
Procedia PDF Downloads 340520 Source Identification Model Based on Label Propagation and Graph Ordinary Differential Equations
Authors: Fuyuan Ma, Yuhan Wang, Junhe Zhang, Ying Wang
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Identifying the sources of information dissemination is a pivotal task in the study of collective behaviors in networks, enabling us to discern and intercept the critical pathways through which information propagates from its origins. This allows for the control of the information’s dissemination impact in its early stages. Numerous methods for source detection rely on pre-existing, underlying propagation models as prior knowledge. Current models that eschew prior knowledge attempt to harness label propagation algorithms to model the statistical characteristics of propagation states or employ Graph Neural Networks (GNNs) for deep reverse modeling of the diffusion process. These approaches are either deficient in modeling the propagation patterns of information or are constrained by the over-smoothing problem inherent in GNNs, which limits the stacking of sufficient model depth to excavate global propagation patterns. Consequently, we introduce the ODESI model. Initially, the model employs a label propagation algorithm to delineate the distribution density of infected states within a graph structure and extends the representation of infected states from integers to state vectors, which serve as the initial states of nodes. Subsequently, the model constructs a deep architecture based on GNNs-coupled Ordinary Differential Equations (ODEs) to model the global propagation patterns of continuous propagation processes. Addressing the challenges associated with solving ODEs on graphs, we approximate the analytical solutions to reduce computational costs. Finally, we conduct simulation experiments on two real-world social network datasets, and the results affirm the efficacy of our proposed ODESI model in source identification tasks.Keywords: source identification, ordinary differential equations, label propagation, complex networks
Procedia PDF Downloads 20519 Competitive DNA Calibrators as Quality Reference Standards (QRS™) for Germline and Somatic Copy Number Variations/Variant Allelic Frequencies Analyses
Authors: Eirini Konstanta, Cedric Gouedard, Aggeliki Delimitsou, Stefania Patera, Samuel Murray
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Introduction: Quality reference DNA standards (QRS) for molecular testing by next-generation sequencing (NGS) are essential for accurate quantitation of copy number variations (CNV) for germline and variant allelic frequencies (VAF) for somatic analyses. Objectives: Presently, several molecular analytics for oncology patients are reliant upon quantitative metrics. Test validation and standardisation are also reliant upon the availability of surrogate control materials allowing for understanding test LOD (limit of detection), sensitivity, specificity. We have developed a dual calibration platform allowing for QRS pairs to be included in analysed DNA samples, allowing for accurate quantitation of CNV and VAF metrics within and between patient samples. Methods: QRS™ blocks up to 500nt were designed for common NGS panel targets incorporating ≥ 2 identification tags (IDTDNA.com). These were analysed upon spiking into gDNA, somatic, and ctDNA using a proprietary CalSuite™ platform adaptable to common LIMS. Results: We demonstrate QRS™ calibration reproducibility spiked to 5–25% at ± 2.5% in gDNA and ctDNA. Furthermore, we demonstrate CNV and VAF within and between samples (gDNA and ctDNA) with the same reproducibility (± 2.5%) in a clinical sample of lung cancer and HBOC (EGFR and BRCA1, respectively). CNV analytics was performed with similar accuracy using a single pair of QRS calibrators when using multiple single targeted sequencing controls. Conclusion: Dual paired QRS™ calibrators allow for accurate and reproducible quantitative analyses of CNV, VAF, intrinsic sample allele measurement, inter and intra-sample measure not only simplifying NGS analytics but allowing for monitoring clinically relevant biomarker VAF across patient ctDNA samples with improved accuracy.Keywords: calibrator, CNV, gene copy number, VAF
Procedia PDF Downloads 152518 New Test Algorithm to Detect Acute and Chronic HIV Infection Using a 4th Generation Combo Test
Authors: Barun K. De
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Acquired immunodeficiency syndrome (AIDS) is caused by two types of human immunodeficiency viruses, collectively designated HIV. HIV infection is spreading globally particularly in developing countries. Before an individual is diagnosed with HIV, the disease goes through different phases. First there is an acute early phase that is followed by an established or chronic phase. Subsequently, there is a latency period after which the individual becomes immunodeficient. It is in the acute phase that an individual is highly infectious due to a high viral load. Presently, HIV diagnosis involves use of tests that do not detect the acute phase infection during which both the viral RNA and p24 antigen are expressed. Instead, these less sensitive tests detect antibodies to viral antigens which are typically sero-converted later in the disease process following acute infection. These antibodies are detected in both asymptomatic HIV-infected individuals as well as AIDS patients. Studies indicate that early diagnosis and treatment of HIV infection can reduce medical costs, improve survival, and reduce spreading of infection to new uninfected partners. Newer 4th generation combination antigen/antibody tests are highly sensitive and specific for detection of acute and established HIV infection (HIV1 and HIV2) enabling immediate linkage to care. The CDC (Center of Disease Control, USA) recently recommended an algorithm involving three different tests to screen and diagnose acute and established infections of HIV-1 and HIV-2 in a general population. Initially a 4th generation combo test detects a viral antigen p24 and specific antibodies against HIV -1 and HIV-2 envelope proteins. If the test is positive it is followed by a second test known as a differentiation assay which detects antibodies against specific HIV-1 and HIV-2 envelope proteins confirming established infection of HIV-1 or HIV-2. However if it is negative then another test is performed that measures viral load confirming an acute HIV-1 infection. Screening results of a Phoenix area population detected 0.3% new HIV infections among which 32.4% were acute cases. Studies in the U.S. indicate that this algorithm effectively reduces HIV infection through immediate treatment and education following diagnosis.Keywords: new algorithm, HIV, diagnosis, infection
Procedia PDF Downloads 410517 In-vitro Metabolic Fingerprinting Using Plasmonic Chips by Laser Desorption/Ionization Mass Spectrometry
Authors: Vadanasundari Vedarethinam, Kun Qian
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The metabolic analysis is more distal over proteomics and genomics engaging in clinics and needs rationally distinct techniques, designed materials, and device for clinical diagnosis. Conventional techniques such as spectroscopic techniques, biochemical analyzers, and electrochemical have been used for metabolic diagnosis. Currently, there are four major challenges including (I) long-term process in sample pretreatment; (II) difficulties in direct metabolic analysis of biosamples due to complexity (III) low molecular weight metabolite detection with accuracy and (IV) construction of diagnostic tools by materials and device-based platforms for real case application in biomedical applications. Development of chips with nanomaterial is promising to address these critical issues. Mass spectroscopy (MS) has displayed high sensitivity and accuracy, throughput, reproducibility, and resolution for molecular analysis. Particularly laser desorption/ ionization mass spectrometry (LDI MS) combined with devices affords desirable speed for mass measurement in seconds and high sensitivity with low cost towards large scale uses. We developed a plasmonic chip for clinical metabolic fingerprinting as a hot carrier in LDI MS by series of chips with gold nanoshells on the surface through controlled particle synthesis, dip-coating, and gold sputtering for mass production. We integrated the optimized chip with microarrays for laboratory automation and nanoscaled experiments, which afforded direct high-performance metabolic fingerprinting by LDI MS using 500 nL of serum, urine, cerebrospinal fluids (CSF) and exosomes. Further, we demonstrated on-chip direct in-vitro metabolic diagnosis of early-stage lung cancer patients using serum and exosomes without any pretreatment or purifications. To our best knowledge, this work initiates a bionanotechnology based platform for advanced metabolic analysis toward large-scale diagnostic use.Keywords: plasmonic chip, metabolic fingerprinting, LDI MS, in-vitro diagnostics
Procedia PDF Downloads 162