Search results for: breast cancer detection

Authors: Saad M. Darwish, Magda M. Madbouly, Murad B. Khorsheed

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Sign Languages (SL) are the most accomplished forms of gestural communication. Therefore, their automatic analysis is a real challenge, which is interestingly implied to their lexical and syntactic organization levels. Hidden Markov models (HMM’s) have been used prominently and successfully in speech recognition and, more recently, in handwriting recognition. Consequently, they seem ideal for visual recognition of complex, structured hand gestures such as are found in sign language. In this paper, several results concerning static hand gesture recognition using an algorithm based on Type-2 Fuzzy HMM (T2FHMM) are presented. The features used as observables in the training as well as in the recognition phases are based on Singular Value Decomposition (SVD). SVD is an extension of Eigen decomposition to suit non-square matrices to reduce multi attribute hand gesture data to feature vectors. SVD optimally exposes the geometric structure of a matrix. In our approach, we replace the basic HMM arithmetic operators by some adequate Type-2 fuzzy operators that permits us to relax the additive constraint of probability measures. Therefore, T2FHMMs are able to handle both random and fuzzy uncertainties existing universally in the sequential data. Experimental results show that T2FHMMs can effectively handle noise and dialect uncertainties in hand signals besides a better classification performance than the classical HMMs. The recognition rate of the proposed system is 100% for uniform hand images and 86.21% for cluttered hand images.

Keywords: hand gesture recognition, hand detection, type-2 fuzzy logic, hidden Markov Model

Procedia PDF Downloads 427

Authors: Ediati Budi Cahyono, Triana Hertiani, Nauval Arrazy Asawimanda, Wahyu Puji Pratomo

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Background: Doxorubicin is widely used as a chemotherapeutic drug despite having many side effects. It may cause macrophage dysfunction and decreasing proliferation of lymphocyte. Noni (Morinda citrifolia) fruit which has rich of polysaccharide content has potential as antitumor and immunostimulant effect. The isolation of polysaccharide from Noni fruit has been optimized according to four different methods based on macrophage and lymphocyte activities. We found the highest polysaccharide content from one of the four methods isolation. A method of polysaccharide isolation which has the highest immunostimulant effect was used for further observation as co-chemotherapy. The aim of the study: was to evaluate the isolated polysaccharide from the method of choice as co-chemotherapy of doxorubicin for the growth of Vero, He-La, and T47D cell lines in vitro. The method: in vitro growth assay of Vero, He-La, and T47D cell lines was done using MTT-reduction method, and apoptosis test was done by double staining method to evaluate the induction apoptotic effect of the combination. Every group was treated with doxorubicin and isolated polysaccharide from method of choice with 4 variances of concentrations (25 µg/ml, 50 µg/ml, 100 µg/ml and 200 µg/ml) a long with negative control (doxorubicin only) and normal control (without doxorubicin or polysaccharide administration). Results: The combination of polysaccharide fraction in the concentration of 100μg/ml with 2μmol of doxorubicin against He-La and T47D cell lines influenced the highest cytotoxic effect by suppressing cell viability comparing with doxorubicin only. The combination of polysaccharide fraction in the concentration of 100μg/ml with 2μmol of doxorubicin-induced apoptotic effect the He-La cell line comparing with doxorubicin only. The result of the study: it can be concluded that the combination of polysaccharide fraction and doxorubicin effect more selective toward He-La and T47D cell lines than to Vero cell line. It can be suggested isolated polysaccharide from the method of choice has co-chemotherapy activity against doxorubicin.

Keywords: polysaccharide, noni fruit, doxorubicin, cancer cell lines, vero cell line

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Authors: Beng Yew Low, Cher Liang Cha, Cheng Yong Teoh

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Due to a lack of continual assessment or grade related data, identifying first-year engineering students in a polytechnic education at risk of failing is challenging. Our experience over the years tells us that there is no strong correlation between having good entry grades in Mathematics and the Sciences and excelling in hardcore engineering subjects. Hence, identifying students at risk of failure cannot be on the basis of entry grades in Mathematics and the Sciences alone. These factors compound the difficulty of early identification and intervention. This paper describes the development of a predictive analytics model in the early detection of students at risk of failing and evaluates its effectiveness. Data from continual assessments conducted in term one, supplemented by data of student psychological profiles such as interests and study habits, were used. Three classification techniques, namely Logistic Regression, K Nearest Neighbour, and Random Forest, were used in our predictive model. Based on our findings, Random Forest was determined to be the strongest predictor with an Area Under the Curve (AUC) value of 0.994. Correspondingly, the Accuracy, Precision, Recall, and F-Score were also highest among these three classifiers. Using this Random Forest Classification technique, students at risk of failure could be identified at the end of term one. They could then be assigned to a Learning Support Programme at the beginning of term two. This paper gathers the results of our findings. It also proposes further improvements that can be made to the model.

Keywords: continual assessment, predictive analytics, random forest, student psychological profile

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Authors: Sanjeev Kumar Raghuwanshi, Yadvendra Singh

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The objective of this paper is to develop and optimize the Fiber Bragg (FBG) grating based Surface Plasmon Resonance (SPR) sensor for monitoring the hazardous toxic chemicals and gases in underground mines or any industrial area. A fully cladded telecommunication standard FBG is proposed to develop to produce surface plasmon resonance. A thin few nm gold/silver film (subject to optimization) is proposed to apply over the FBG sensing head using e-beam deposition method. Sensitivity enhancement of the sensor will be done by adding a composite nanostructured Graphene Oxide (GO) sensing layer using the spin coating method. Both sensor configurations suppose to demonstrate high responsiveness towards the changes in resonance wavelength. The GO enhanced sensor may show increased sensitivity of many fold compared to the gold coated traditional fibre optic sensor. Our work is focused on to optimize GO, multilayer structure and to develop fibre coating techniques that will serve well for sensitive and multifunctional detection of hazardous chemicals. This research proposal shows great potential towards future development of optical fiber sensors using readily available components such as Bragg gratings as highly sensitive chemical sensors in areas such as environmental sensing.

Keywords: surface plasmon resonance, fibre Bragg grating, sensitivity, toxic gases, MATRIX method

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Authors: Maysoon Khalil Askar

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The delineation of possible areas of corrosion along the external face of an underground oil pipeline in Trunk line of Al- Garraf oil field was investigated using the horizontal electrical resistivity profiling technique and study the contribution of pH, Moisture Content in Soil and Presence chlorides, sulfates and total dissolve salts in soil and water. The test sites represent a physical and chemical properties of soils. The hydrogen-ion concentration of soil and groundwater range from 7.2 to 9.6, and the resistivity values of the soil along the pipeline were obtained using the YH302B model resistivity meter having values between 1588 and 720 Ohm-cm. the chloride concentration in soil and groundwater is high (more than 1000 ppm), total soulable salt is more than 5000 ppm, and sulphate range from 0.17% and 0.98% in soil and more than 600 ppm in groundwater. The soil is poor aeration, the soil texture is fine (clay and silt soil), the water content is high (the groundwater is close to surface), the chloride and sulphate is high in the soil and groundwater, the total soulable salt is high in ground water and finally the soil electric resistivity is low that the soil is very corrosive and there is the possibility of the pipeline failure. These methods applied in the study are quick, economic and efficient for detecting along buried pipelines which need to be protected. Routine electrical geophysical investigations along buried oil pipelines should be undertaken for the early detection and prevention of pipeline failure with its attendant environmental, human and economic consequences.

Keywords: soil resistivity, corrosion, cathodic protection, chloride concentration, water content

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Authors: B. Nageshwar Rao

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Urinary tract infection (UTI) represents the most commonly acquired bacterial infection worldwide, with substantial morbidity, mortality, and economic burden. The objective of the study is to characterize the microbial profiles of uropathogenic in the obstetric population by RTPCR. Study design: An observational cross-sectional study was performed at a single tertiary health care hospital among 50 pregnant women with UTIs, including asymptomatic and symptomatic patients attending the outpatient department and inpatient department of Obstetrics and Gynaecology.Methods: Serotyping and genes detection of various uropathogens were studied using RTPCR. Pulse filed gel electrophoresis methods were used to determine the various genetic profiles. Results: The present study shows that CsgD protein, involved in biofilm formation in Escherichia coli, VIM1, IMP1 genes for Klebsiella were identified by using the RTPCR method. Our results showed that the prevalence of VIM1 and IMP1 genes and CsgD protein in E.coli showed a significant relationship between strong biofilm formation, and this may be due to the prevalence of specific genes. Finally, the genetic identification of RTPCR results for both bacteria was correlated with each other and concluded that the above uropathogens were common isolates in producing Biofilm in the pregnant woman suffering from urinary tract infection in our hospital observational study.

Keywords: biofilms, Klebsiella, E.coli, urinary tract infection

Procedia PDF Downloads 87

Authors: Abdolamir Allameh, Seyyed Mortaza Haghgoo, Adnan Khosravi, Esmaeil Mortaz, Mihan Pourabdollah-Toutkaboni, Sharareh Seifi

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Non-Small Cell Lung Carcinoma (NSCLC) is associated with a number of gene mutations in epidermal growth factor receptor (EGFR). The prognostic significance of mutations in exons 19 and 21, together with serum levels of EGFR, amphiregulin (AR), and Transforming Growth Factor-alpha (TGF-α) are implicated in diagnosis and treatment. The aim of this study was to examine the relationship of EGFR mutations in selected exons with the expression of relevant ligands in sera samples of NSCLC patients. For this, a group of NSCLC patients (n=98) referred to the hospital for lung surgery with a mean age of 59±10.5 were enrolled (M/F: 75/23). Blood specimen was collected from each patient. Besides, formalin fixed paraffin embedded tissues were processed for DNA extraction. Gene mutations in exons 19 and 21 were detected by direct sequencing, following DNA amplification which was done by PCR (Polymerase Chain Reaction). Also, serum levels of EGFR, AR, and TGF-α were measured by ELISA. The results of our study show that EGFR mutations were present in 37% of Iranian NSCLC patients. The most frequently identified mutations were deletions in exon 19 (72.2%) and substitutions in exon 21 (27.8%). The most frequently identified alteration, which is considered as a rare mutation, was the E872K mutation in exon 21, which was found in 90% (9 out of 10) cases. EGFR mutation detected in exon 21 was significantly (P<0.05) correlated with the levels of its ligands, EGFR and TGF-α in serum samples. Furthermore, it was found that increased serum AR (>3pg/ml) and TGF-α (>10.5 pg/ml) were associated with shorter overall survival (P<0.05). The results clearly showed a close relationship between EGFR mutations and serum EGFR and serum TGF-α. Increased serum EGFR was associated with TGF-α and AR and linked to poor prognosis of NSCLC. These findings are implicated in clinical decision-making related to EGFR-Tyrosine kinase inhibitors (TKIs).

Keywords: lung cancer, Iranian patients, epidermal growth factor, mutation, prognosis

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Authors: Behnaz Moradijamei, Michael Higgins

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Identifying community structure is a critical task in analyzing social media data sets often modeled by networks. Statistical models such as the stochastic block model have proven to explain the structure of communities in real-world network data. In this work, we develop a goodness-of-fit test to examine community structure's existence by using a distinguishing property in networks: cyclic structures are more prevalent within communities than across them. To better understand how communities are shaped by the cyclic structure of the network rather than just the number of edges, we introduce a novel method for deciding on the existence of communities. We utilize these structures by using renewal non-backtracking random walk (RNBRW) to the existing goodness-of-fit test. RNBRW is an important variant of random walk in which the walk is prohibited from returning back to a node in exactly two steps and terminates and restarts once it completes a cycle. We investigate the use of RNBRW to improve the performance of existing goodness-of-fit tests for community detection algorithms based on the spectral properties of the adjacency matrix. Our proposed test on community structure is based on the probability distribution of eigenvalues of the normalized retracing probability matrix derived by RNBRW. We attempt to make the best use of asymptotic results on such a distribution when there is no community structure, i.e., asymptotic distribution under the null hypothesis. Moreover, we provide a theoretical foundation for our statistic by obtaining the true mean and a tight lower bound for RNBRW edge weights variance.

Keywords: hypothesis testing, RNBRW, network inference, community structure

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Authors: Luca Collini, Michele Antolotti, Diego Schiavi

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At present, complex geometries within production time shrinkage, rapidly increasing demand, and high-quality standard requirement make the non-destructive (ND) control of additively manufactured components indispensable means. On the other hand, a technology gap and the lack of standards regulating the methods and the acceptance criteria indicate the NDT of these components a stimulating field to be still fully explored. Up to date, penetrant testing, acoustic wave, tomography, radiography, and semi-automated ultrasound methods have been tested on metal powder based products so far. External defects, distortion, surface porosity, roughness, texture, internal porosity, and inclusions are the typical defects in the focus of testing. Detection of density and layers compactness are also been tried on stainless steels by the ultrasonic scattering method. In this work, the authors want to present and discuss the radiographic and the ultrasound ND testing on additively manufactured Ti₆Al₄V and inconel parts obtained by the selective laser melting (SLM) technology. In order to test the possibilities given by the radiographic method, both X-Rays and γ-Rays are tried on a set of specifically designed specimens realized by the SLM. The specimens contain a family of defectology, which represent the most commonly found, as cracks and lack of fusion. The tests are also applied to real parts of various complexity and thickness. A set of practical indications and of acceptance criteria is finally drawn.

Keywords: non-destructive testing, selective laser melting, radiography, UT method

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Authors: Sahar Ehsani, David James, Vernon Hodge

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In this experimental study, total selenium in solution was measured with Graphite Furnace Atomic Absorption Spectroscopy, GFAAS, then chemical reactions with sodium borohydride were used to reduce selenite to hydrogen selenide. Hydrogen selenide was then stripped from the solution by purging the solution with nitrogen gas. Since the two main speciations in oxic waters are usually selenite, Se(IV) and selenate, Se(VI), it was assumed that after Se(IV) is removed, the remaining total selenium was Se(VI). Total selenium measured after stripping gave Se(VI) concentration, and the difference of total selenium measured before and after stripping gave Se(IV) concentration. An additional step of reducing Se(VI) to Se(IV) was performed by boiling the stripped solution under acidic conditions, then removing Se(IV) by a chemical reaction with sodium borohydride. This additional procedure of removing Se(VI) from the solution is useful in rare cases where the water sample is reducing and contains selenide speciation. In this study, once Se(IV) and Se(VI) were both removed from the water sample, the remaining total selenium concentration was zero. The method was tested to determine Se(IV) and Se(VI) in both purified water and synthetic irrigation water spiked with Se(IV) and Se(VI). Average recovery of spiked samples of diluted synthetic irrigation water was 99% for Se(IV) and 97% for Se(VI). Detection limits of the method were 0.11 µg L⁻¹ and 0.32 µg L⁻¹ for Se(IV) and Se(VI), respectively.

Keywords: Analytical Method, Graphite Furnace Atomic Absorption Spectroscopy, Selenate, Selenite, Selenium Speciations

Procedia PDF Downloads 103

Authors: Felipe A. Guth, Shane Ward, Kevin McDonnell

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The assessment of disease levels in crop fields is an important and time-consuming task that generally relies on expert knowledge of trained individuals. Image classification in agriculture problems historically has been based on classical machine learning strategies that make use of hand-engineered features in the top of a classification algorithm. This approach tends to not produce results with high accuracy and generalization to the classes classified by the system when the nature of the elements has a significant variability. The advent of deep convolutional neural networks has revolutionized the field of machine learning, especially in computer vision tasks. These networks have great resourcefulness of learning and have been applied successfully to image classification and object detection tasks in the last years. The objective of this work was to propose a new method based on deep learning convolutional neural networks towards the task of disease level monitoring. Common RGB images of winter wheat were obtained during a growing season. Five categories of disease levels presence were produced, in collaboration with agronomists, for the algorithm classification. Disease level tasks performed by experts provided ground truth data for the disease score of the same winter wheat plots were RGB images were acquired. The system had an overall accuracy of 84% on the discrimination of the disease level classes.

Keywords: crop disease assessment, deep learning, precision agriculture, residual neural networks

Procedia PDF Downloads 291

Authors: Muñiz-Lino Marcos Agustín, Vazquez Borbolla Jessica, Licéaga-Escalera Carlos

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The ectomesenchymal tissues involved in tooth development and their remnants are the origin of different odontogenic lesions, including tumors and cysts of the jaws, with a wide range of clinical behaviors. Dentigerous cyst (DC) represents approximately 20% of all cases of odontogenic cysts, and it has been demonstrated that it can develop benign and malignant odontogenic tumors. DC is characterized by bone destruction of the area surrounding the crown of a tooth which has not erupted and it contain is liquid. The treatment of odontogenic tumors and cysts usually are partial or total removal of the jaw, causing important secondary co-morbidities. However, molecules implicated in DC pathogenesis as well in its development to odontogenic tumors remains unknown. A cellular model may be useful to study these molecules, but that model has not been established yet. Here, we reported the establishment of a cell culture derived from a dentigerous cyst. This cell line was named DeCy-1. In spite of its ectomesenchymal morphology, DeCy-1 cells express epithelial markers such as cytokeratins 5, 6, and 8. Furthermore, these cells express the ODAM protein, which is present in odontogenesis and in dental follicle, indicating that DeCy-1 cells derived from odontogenic epithelium. Analysis by electron microscopy of this cell line showed that it has a high vesicular activity, suggesting that DeCy-1 could secrete molecules that may be involved in DC pathogenesis. Thus, secreted proteins were analyzed by PAGE-SDS, where we observed approximately 11 bands. In addition, the capacity of these secretions to degrade proteins was analyzed by gelatin substrate zymography. A degradation band of about 62 kDa was found in these assays. Western blot assays suggested that the matrix metalloproteinase 2 (MMP-2) is responsible of this protease activity. Thus, our results indicate that the establishment of a cell line derived from DC is a useful in vitro model to study the biology of this odontogenic lesion and its participation in the development of odontogenic tumors.

Keywords: dentigerous cyst, MMP20, cancer, cell culture

Procedia PDF Downloads 109

Authors: Subir Gupta, Subhas Ganguly

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In this paper, we demonstrate the new area of application of image processing in metallurgical images to develop the more opportunity for structure-property correlation based approaches of alloy design. The present exercise focuses on the development of image processing tools suitable for phrase segmentation, grain boundary detection and recognition of micro-constituents in SEM micrographs of ferrite and pearlite steels. A comprehensive data of micrographs have been experimentally developed encompassing the variation of ferrite and pearlite volume fractions and taking images at different magnification (500X, 1000X, 15000X, 2000X, 3000X and 5000X) under scanning electron microscope. The variation in the volume fraction has been achieved using four different plain carbon steel containing 0.1, 0.22, 0.35 and 0.48 wt% C heat treated under annealing and normalizing treatments. The obtained data pool of micrographs arbitrarily divided into two parts to developing training and testing sets of micrographs. The statistical recognition features for ferrite and pearlite constituents have been developed by learning from training set of micrographs. The obtained features for microstructure pattern recognition are applied to test set of micrographs. The analysis of the result shows that the developed strategy can successfully detect the micro constitutes across the wide range of magnification and variation of volume fractions of the constituents in the structure with an accuracy of about +/- 5%.

Keywords: SEM micrograph, metallurgical image processing, ferrite pearlite steel, microstructure

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Authors: C. Catalina Zapata, Z. Claudia Montoya

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Transplant from hematopoietic parents (THP) or medulla (MT) is a procedure used to replace the medulla that does not work as part of a disease or when it is destroyed either by a treatment of high medication doses against cancer or by radiation. The transplant process has three stages, a stage prior to transplant, during and after the transplant. It is held with the help of an interdisciplinary team, including nursing, carrying out mainly educative procedures to warrant the adhesion and the changes in lifestyles needed to whom will undergo this procedure. The aim of the study was to assess the results of an educative procedure by nursing, on adult patients subjected to a transplant from hematopoietic parents at a high complexity institution of Medellin city, Colombia. This study had an observational longitudinal design. According to the rules of protocol, the educative activity must be held on all patients joining the procedure. Four instruments were designed in order to collect all the information. One of them to measure the sociodemographic variables, another one to measure self-care practices, another one to measure transplant knowledge and its cares and the other one to measure the 30-day post-transplant complications. The last three instruments were applied before and after the educative procedure. A univaried analysis was carried out but the bivaried analysis was not carried out since there were not statistically meaningful differences before and after. Within the results, ten patients were evaluated. The average age was 38.2 (13.38 SD – standard deviation), 8/10 were men. Some self-care practices such us having pets and plants and consuming some specific food as well as little use of UV protection are all present in this type of patients and are not modified after the procedure. In measuring the knowledge, something stands out among the answers. It is the fact that some patients do not know what the medulla is, the nature of separating wastes at home and the need to consult about vomit and nausea. The most frequent complications during the first thirty days were: nausea, vomit, fever, and rash. They are considered to be expected within this period. Patients do not exhibit differences in their level of knowledge before and after the educative procedure by nursing. The patients’ self-care practices do not involve all the necessary ones to avoid complications. During the first 30 days, most of the complications are typical of the transplant process from hematopoietic parents.

Keywords: bone marrow transplant, education, family, nursing, patients, Transplantation of hematopoietic progenitors

Procedia PDF Downloads 93

Authors: Zhipeng Yan, Janice Wing-Tung Kwong, Ching-Lung Lai

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Background: Advanced melanoma accounts for the majority of skin cancer death due to its poor prognosis. Nivolumab and ipilimumab are monoclonal antibodies targeting programmed cell death protein 1 (PD-1) and cytotoxic T-lymphocytes antigen 4 (CTLA-4). Nivolumab and ipilimumab combination therapy has been proven to be effective for advanced melanoma. This systematic review and meta-analysis are to evaluate its clinical efficacy and adverse events. Method: A systematic search was done on databases (Pubmed, Embase, Medline, Cochrane) on 21 June 2020. Search keywords were nivolumab, ipilimumab, melanoma, and randomised controlled trials. Clinical trials fulfilling the inclusion criteria were selected to evaluate the efficacy of combination therapy in terms of prolongation of progression-free survival (PFS), overall survival (OS), and objective response rate (ORR). The odd ratios and distributions of grade 3 or above adverse events were documented. Subgroup analysis was performed based on PD-L1 expression-status and BRAF-mutation status. Results: Compared with nivolumab monotherapy, the hazard ratios of PFS, OS and odd ratio of ORR in combination therapy were 0.64 (95% CI, 0.48-0.85; p=0.002), 0.84 (95% CI, 0.74-0.95; p=0.007) and 1.76 (95% CI, 1.51-2.06; p < 0.001), respectively. Compared with ipilimumab monotherapy, the hazard ratios of PFS, OS and odd ratio of ORR were 0.46 (95% CI, 0.37-0.57; p < 0.001), 0.54 (95% CI, 0.48-0.61; p < 0.001) and 6.18 (95% CI, 5.19-7.36; p < 0.001), respectively. In combination therapy, the odds ratios of grade 3 or above adverse events were 4.71 (95% CI, 3.57-6.22; p < 0.001) compared with nivolumab monotherapy, and 3.44 (95% CI, 2.49-4.74; p < 0.001) compared with ipilimumab monotherapy, respectively. High PD-L1 expression level and BRAF mutation were associated with better clinical outcomes in patients receiving combination therapy. Conclusion: Combination therapy is effective for the treatment of advanced melanoma. Adverse events were common but manageable. Better clinical outcomes were observed in patients with high PD-L1 expression levels and positive BRAF-mutation.

Keywords: nivolumab, ipilimumab, advanced melanoma, systematic review, meta-analysis

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Authors: Mst Ilme Faridatul, Bo Wu

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Multi-temporal urban land cover mapping is of paramount importance for monitoring urban sprawl and managing the ecological environment. For diversified urban activities, it is challenging to map land covers in a complex urban environment. Spectral indices have proved to be effective for mapping urban land covers. To improve multi-temporal urban land cover classification and mapping, we evaluate the performance of three spectral indices, e.g. modified normalized difference bare-land index (MNDBI), tasseled cap water and vegetation index (TCWVI) and shadow index (ShDI). The MNDBI is developed to evaluate its performance of enhancing urban impervious areas by separating bare lands. A tasseled cap index, TCWVI is developed to evaluate its competence to detect vegetation and water simultaneously. The ShDI is developed to maximize the spectral difference between shadows of skyscrapers and water and enhance water detection. First, this paper presents a comparative analysis of three spectral indices using Landsat Enhanced Thematic Mapper (ETM), Thematic Mapper (TM) and Operational Land Imager (OLI) data. Second, optimized thresholds of the spectral indices are imputed to classify land covers, and finally, their performance of enhancing multi-temporal urban land cover mapping is assessed. The results indicate that the spectral indices are competent to enhance multi-temporal urban land cover mapping and achieves an overall classification accuracy of 93-96%.

Keywords: land cover, mapping, multi-temporal, spectral indices

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Authors: Markus Feufel, Friederike Kendel, Caren Hilger, Selamawit Woldai

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Since the corona pandemic, the use of video consultation has increased remarkably. For vulnerable groups such as oncological patients, the advantages seem obvious. But how does video consultation potentially change the doctor-patient relationship compared to face-to-face consultation? Which barriers may hinder the effective use of this consultation format in practice? We are presenting first results from a mixed-methods field study, funded by Federal Ministry of Health, which will provide the basis for a hands-on guide for both physicians and patients on how to improve the quality of video consultations. We use a quasi-experimental design to analyze qualitative and quantitative differences between face-to-face and video consultations based on video recordings of N = 64 actual counseling sessions (n = 32 for each consultation format). Data will be recorded from n = 32 gynecological and n = 32 urological cancer patients at two clinics. After the consultation, all patients will be asked to fill out a questionnaire about their consultation experience. For quantitative analyses, the counseling sessions will be systematically compared in terms of verbal and nonverbal communication patterns. Relative frequencies of eye contact and the information exchanged will be compared using 𝝌2 -tests. The validated questionnaire MAPPIN'Obsdyad will be used to assess the expression of shared decision-making parameters. In addition, semi-structured interviews will be conducted with n = 10 physicians and n = 10 patients experienced with video consultation, for which a qualitative content analysis will be conducted. We will elaborate the comprehensive methodological approach we used to compare video vs. face-to-face consultations and present first evidence on how video consultations change the doctor-patient interaction. We will also outline possible barriers of video consultations and best practices on how they may be overcome. Based on the results, we will present and discuss recommendations outlining best practices for how to prepare and conduct high-quality video consultations from the perspective of both physicians and patients.

Keywords: video consultation, patient-doctor-relationship, digital applications, technical barriers

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Authors: P. S. Jain, K. D. Bobade, S. J. Surana

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A simple, selective, precise and Stability-indicating High-performance thin-layer chromatographic method for analysis of Naftopidil both in a bulk and in pharmaceutical formulation has been developed and validated. The method employed, HPTLC aluminium plates precoated with silica gel as the stationary phase. The solvent system consisted of hexane: ethyl acetate: glacial acetic acid (4:4:2 v/v). The system was found to give compact spot for Naftopidil (Rf value of 0.43±0.02). Densitometric analysis of Naftopidil was carried out in the absorbance mode at 253 nm. The linear regression analysis data for the calibration plots showed good linear relationship with r2=0.999±0.0001 with respect to peak area in the concentration range 200-1200 ng per spot. The method was validated for precision, recovery and robustness. The limits of detection and quantification were 20.35 and 61.68 ng per spot, respectively. Naftopidil was subjected to acid and alkali hydrolysis, oxidation and thermal degradation. The drug undergoes degradation under acidic, basic, oxidation and thermal conditions. This indicates that the drug is susceptible to acid, base, oxidation and thermal conditions. The degraded product was well resolved from the pure drug with significantly different Rf value. Statistical analysis proves that the method is repeatable, selective and accurate for the estimation of investigated drug. The proposed developed HPTLC method can be applied for identification and quantitative determination of Naftopidil in bulk drug and pharmaceutical formulation.

Keywords: naftopidil, HPTLC, validation, stability, degradation

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Authors: Magdalena Bury-Kaminska, Aneta Szudy-Szczyrek, Aleksandra Nowaczynska, Olga Jankowska-Lecka, Marek Hus, Klaudia Kot

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Introduction: The aim of the research was to determine the changes in cognitive functioning in patients with plasma cell myeloma by comparing patients’ state before the treatment and during chemotherapy as well as to determine the biological factors that can be used to predict patients’ cognitive state. Methods: The patients underwent the research procedure twice: before chemotherapy and after 4-6 treatment cycles. A psychological test and measurement of the following biological variables were carried out: TNF-α (tumor necrosis factor), IL-6 (interleukin 6), IL-10 (interleukin 10), BDNF (brain-derived neurotrophic factor). The following research methods were implemented: the Montreal Cognitive Assessment (MoCA), Battery of Tests for Assessing Cognitive Functions PU1, experimental and clinical trials based on the Choynowski’s Memory Scale, Stroop Color-Word Interference Test (SCWT), depression measurement questionnaire. Results: The analysis of the research showed better cognitive functions of patients during chemotherapy in comparison to the phase before it. Moreover, neurotrophin BDNF allows to predict the level of selected cognitive functions (semantic fluency and execution control) already at the diagnosis stage. After 4-6 cycles, it is also possible to draw conclusions concerning the extent of working memory based on the level of BDNF. Cytokine TNF-α allows us to predict the level of letter fluency during anti-cancer treatment. Conclusions: It is possible to presume that BDNF has a protective influence on patients’ cognitive functions and working memory and that cytokine TNF-α co-occurs with a diminished execution control and better material grouping in terms of phonological fluency. Acknowledgment: This work was funded by the National Science Center in Poland [grant no. 2017/27/N/HS6/02057.

Keywords: chemobrain, cognitive impairment, non−central nervous system cancers, hematologic diseases

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Authors: Janmejoy Gupta, Arnab Paul, Manjari Chakraborty

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Jharkhand is a state located in the eastern part of India. The Tropic of Cancer (23.5 degree North latitude line) passes through Ranchi district in Jharkhand. Mud huts with burnt clay tiled roofs in Jharkhand are an integral component of the state’s vernacular architecture. They come in various shapes, with a number of them having a courtyard type of plan. In general, it has been stated that designing dwellings with courtyards in them is a climate-responsive strategy in composite climate. The truth behind this hypothesis is investigated in this paper. In this paper, three types of mud huts with courtyards situated in Ranchi district in Jharkhand are taken as a study and through temperature measurements in the south-side rooms and courtyards, in addition to Autodesk Ecotect (Version 2011) software simulations, their thermal performance throughout the year are observed. Temperature measurements are specifically taken during the peak of summer and winter and the average temperatures in the rooms and courtyards during seven day-periods in peak of summer and peak of winter are plotted graphically. Thereafter, on the basis of the study and software simulations, the hypothesis is verified and the thermally better performing dwelling types in summer and winter identified among the three sub-types studied. Certain recommendations with respect to increasing thermal comfort in courtyard type mud huts in general are also made. It is found that all courtyard type dwellings do not necessarily show better thermal performance in summer and winter in composite climate. The U shaped dwelling with open courtyard on southern side offers maximum amount of thermal-comfort inside the rooms in the hotter part of the year and the square hut with a central courtyard, with the courtyard being closed from all sides, shows superior thermal performance in winter. The courtyards in all the three case-studies are found to get excessively heated up during summer.

Keywords: courtyard, mud huts, simulations, temperature measurements, thermal performance

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Authors: Beier Zhu, Rui Zhang, Qi Song

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Text contained within fixed-layout documents can be of great semantic value and so requires a high localization accuracy, such as ID cards, invoices, cheques, and passports. Recently, algorithms based on deep convolutional networks achieve high performance on text detection tasks. However, for text localization in fixed-layout documents, such algorithms detect word bounding boxes individually, which ignores the layout information. This paper presents a novel architecture built on convolutional neural networks (CNNs). A global text localization network and a regional bounding-box regression network are introduced to tackle the problem in a coarse-to-fine manner. The text localization network simultaneously locates word bounding points, which takes the layout information into account. The bounding-box regression network inputs the features pooled from arbitrarily sized RoIs and refine the localizations. These two networks share their convolutional features and are trained jointly. A typical type of fixed-layout documents: ID cards, is selected to evaluate the effectiveness of the proposed system. These networks are trained on data cropped from nature scene images, and synthetic data produced by a synthetic text generation engine. Experiments show that our approach locates high accuracy word bounding boxes and achieves state-of-the-art performance.

Keywords: bounding box regression, convolutional networks, fixed-layout documents, text localization

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Authors: Alexander Wachtel, Michael T. Franzen, Walter F. Tichy

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Programming requires years of training. With natural language and end user development methods, programming could become available to everyone. It enables end users to program their own devices and extend the functionality of the existing system without any knowledge of programming languages. In this paper, we describe an Interactive Spreadsheet Processing Module (ISPM), a natural language interface to spreadsheets that allows users to address ranges within the spreadsheet based on inferred table schema. Using the ISPM, end users are able to search for values in the schema of the table and to address the data in spreadsheets implicitly. Furthermore, it enables them to select and sort the spreadsheet data by using natural language. ISPM uses a machine learning technique to automatically infer areas within a spreadsheet, including different kinds of headers and data ranges. Since ranges can be identified from natural language queries, the end users can query the data using natural language. During the evaluation 12 undergraduate students were asked to perform operations (sum, sort, group and select) using the system and also Excel without ISPM interface, and the time taken for task completion was compared across the two systems. Only for the selection task did users take less time in Excel (since they directly selected the cells using the mouse) than in ISPM, by using natural language for end user software engineering, to overcome the present bottleneck of professional developers.

Keywords: natural language processing, natural language interfaces, human computer interaction, end user development, dialog systems, data recognition, spreadsheet

Procedia PDF Downloads 274

Authors: Jaturong Som-ard

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The heavy rainfall from 3rd to 22th January 2017 had swamped much area of Ranot district in southern Thailand. Due to heavy rainfall, the district was flooded which had a lot of effects on economy and social loss. The major objective of this study is to detect flooding extent using Sentinel-1A data and identify a number of damaged buildings over there. The data were collected in two stages as pre-flooding and during flood event. Calibration, speckle filtering, geometric correction, and histogram thresholding were performed with the data, based on intensity spectral values to classify thematic maps. The maps were used to identify flooding extent using change detection, along with the buildings digitized and collected on JOSM desktop. The numbers of damaged buildings were counted within the flooding extent with respect to building data. The total flooded areas were observed as 181.45 sq.km. These areas were mostly occurred at Ban khao, Ranot, Takhria, and Phang Yang sub-districts, respectively. The Ban khao sub-district had more occurrence than the others because this area is located at lower altitude and close to Thale Noi and Thale Luang lakes than others. The numbers of damaged buildings were high in Khlong Daen (726 features), Tha Bon (645 features), and Ranot sub-district (604 features), respectively. The final flood extent map might be very useful for the plan, prevention and management of flood occurrence area. The map of building damage can be used for the quick response, recovery and mitigation to the affected areas for different concern organization.

Keywords: flooding extent, Sentinel-1A data, JOSM desktop, damaged buildings

Procedia PDF Downloads 158

Authors: Upasana Bhumbla

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Background: Hepatitis C virus is a major cause of chronic hepatitis, which can further lead to cirrhosis of the liver and hepatocellular carcinoma. Worldwide the burden of Hepatitis C infection has become a serious threat to the human race. Hepatitis C virus (HCV) has population-specific genotypes and provides valuable epidemiological and therapeutic information. Genotyping and assessment of viral load in HCV patients are important for planning the therapeutic strategies. The aim of the study is to study the changing trends of prevalence and genotypic distribution of hepatitis C virus in a tertiary care hospital in Western India. Methods: It is a retrospective study; blood samples were collected and tested for anti HCV antibodies by ELISA in Dept. of Microbiology. In seropositive Hepatitis C patients, quantification of HCV-RNA was done by real-time PCR and in HCV-RNA positive samples, genotyping was conducted. Results: A total of 114 patients who were seropositive for Anti HCV were recruited in the study, out of which 79 (69.29%) were HCV-RNA positive. Out of these positive samples, 54 were further subjected to genotype determination using real-time PCR. Genotype was not detected in 24 samples due to low viral load; 30 samples were positive for genotype. Conclusion: Knowledge of genotype is crucial for the management of HCV infection and prediction of prognosis. Patients infected with HCV genotype 1 and 4 will have to receive Interferon and Ribavirin for 48 weeks. Patients with these genotypes show a poor sustained viral response when tested 24 weeks after completion of therapy. On the contrary, patients infected with HCV genotype 2 and 3 are reported to have a better response to therapy.

Keywords: hepatocellular, genotype, ribavarin, seropositive

Procedia PDF Downloads 99

Authors: Shalini Rankawat, Mansi Rankawat, Rahul Dubey, Mazad Zaveri

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Physiological signals such as electrocardiogram (ECG) and arterial blood pressure (ABP) in the intensive care unit (ICU) are often seriously corrupted by noise, artifacts, and missing data, which lead to errors in the estimation of heart rate (HR) and incidences of false alarm from ICU monitors. Clinical support in ICU requires most reliable heart rate estimation. Cardiac activity, because of its relatively high electrical energy, may introduce artifacts in Electroencephalogram (EEG), Electrooculogram (EOG), and Electromyogram (EMG) recordings. This paper presents a robust heart rate estimation method by detection of R-peaks of ECG artifacts in EEG, EMG & EOG signals, using energy-based function and a novel Signal Quality Index (SQI) assessment technique. SQIs of physiological signals (EEG, EMG, & EOG) were obtained by correlation of nonlinear energy operator (teager energy) of these signals with either ECG or ABP signal. HR is estimated from ECG, ABP, EEG, EMG, and EOG signals from separate Kalman filter based upon individual SQIs. Data fusion of each HR estimate was then performed by weighing each estimate by the Kalman filters’ SQI modified innovations. The fused signal HR estimate is more accurate and robust than any of the individual HR estimate. This method was evaluated on MIMIC II data base of PhysioNet from bedside monitors of ICU patients. The method provides an accurate HR estimate even in the presence of noise and artifacts.

Keywords: ECG, ABP, EEG, EMG, EOG, ECG artifacts, Teager-Kaiser energy, heart rate, signal quality index, Kalman filter, data fusion

Procedia PDF Downloads 665

Authors: Chiang-Lead Woo

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In reply to serious environmental problems, the Taiwan government quickly adjusted some articles to suit the needs of environmental protection recently, such as the amendment to article 190-1 of the Taiwan Criminal Code. The transfer of legislation comes as an improvement which canceled the limitation of ‘endangering public safety’. At the same time, the article 190-1 goes from accumulative concrete offense to abstract crime of danger. Thus, the public looks forward to whether environmental crime following the imposition of fines or penalties works efficiently in anti-pollution by the deterrent effects. However, according to the addition to article 38-2 of the Taiwan Criminal Code, the confiscation system seems controversial legislation to restrain ill-gotten gains. Most prior studies focused on comparisons with the Administrative Penalty Law and the Criminal Code in environmental issue in Taiwan; recently, more and more studies emphasize calculations on ill-gotten gains. Hence, this paper try to examine the deterrent effect in environmental crime by economic analysis of law and environmental economics perspective. This analysis shows that only if there is an extremely high probability (equal to 100 percent) of an environmental crime case being prosecuted criminally by Taiwan Environmental Protection Agency, the deterrent effects will work. Therefore, this paper suggests deliberating the confiscation system from supplementing the System of Environmental and Economic Accounting, reasonable deterrent fines, input management, real-time system for detection of pollution, and whistleblower system, environmental education, and modernization of law.

Keywords: confiscation, ecosystem services, environmental crime, ill-gotten gains, the deterrent effect, the system of environmental and economic accounting

Procedia PDF Downloads 135

Authors: Azizollah Khodakaram- Tafti, Ali Mohammadi, Ghasem Farjanikish

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Bovine viral diarrhea virus (BVDV) is one of the most important viral pathogens of cattle worldwide caused by Pestivirus genus, Flaviviridae family.The aim of the present study was to comparison several diagnostic methods and determine the prevalence of BVDV infection for the first time in dairy herds of Fars province, Iran. For initial screening, a total of 400 blood samples were randomly collected from 12 industrial dairy herds and analyzed using reverse transcription (RT)-PCR on the buffy coat. In the second step, blood samples and also ear notch biopsies were collected from 100 cattle of infected farms and tested by antigen capture ELISA (ACE), RT-PCR and immunohistochemistry (IHC). The results of nested RT-PCR (outer primers 0I100/1400R and inner primers BD1/BD2) was successful in 16 out of 400 buffy coat samples (4%) as acute infection in initial screening. Also, 8 out of 100 samples (2%) were positive as persistent infection (PI) by all of the diagnostic tests similarly including RT-PCR, ACE and IHC on buffy coat, serum and skin samples, respectively. Immunoreactivity for bovine BVDV antigen as brown, coarsely to finely granular was observed within the cytoplasm of epithelial cells of epidermis and hair follicles and also subcutaneous stromal cells. These findings confirm the importance of monitoring BVDV infection in cattle of this region and suggest detection and elimination of PI calves for controlling and eradication of this disease.

Keywords: antigen capture ELISA, bovine viral diarrhea virus, immunohistochemistry, RT-PCR, cattle

Procedia PDF Downloads 334

Authors: Jai Prakash, Promod Kumar, Chantel Swart, J. H. Neethling, A. Janse van Vuuren, H. C. Swart

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Ag nanoparticles (NPs) have been used as functional nanomaterials due to their optical and antibacterial properties. Similarly, TiO2 photocatalysts have also been used as suitable nanomaterials for killing cancer cells, viruses and bacteria. Here, we report on multifunctional plasmonic Ag-TiO2 nano-biocomposite synthesized by the sol-gel technique and their optical, surface enhanced Raman scattering (SERS) and antibacterial activities. The as-prepared composites of Ag–TiO2 with different silver content and TiO2 nanopowder were characterized by X-ray diffraction, scanning electron microscopy, high-resolution transmission electron microscopy, energy-dispersed X-ray analysis (EDX), UV-vis and Raman spectroscopy. The Ag NPs were found to be uniformly distributed and strongly attached to the TiO2 matrix. The novel optical response of the Ag-TiO2 nanocomposites is due to the strong electric field from the surface plasmon excitation of the Ag NPs. The Raman spectrum of Ag-TiO2 nanocomposite was found to be enhanced as compared to TiO2. The enhancement of the low frequency band is evident. This indicates the SERS effect of the TiO2 NPs in close vicinity of Ag NPs. In addition, nanocomposites showed enhancement in the SERS signals of methyl orange (MO) dye molecules with increasing Ag content. The localized electromagnetic field from the surface plasmon excitation of the Ag NPs was responsible for the SERS signals of the TiO2 NPs and MO molecules. The antimicrobial effect of the Ag–TiO2 nanocomposites with different silver content and TiO2 nanopowder were carried out against the bacterium Staphylococcus aureus. The Ag–TiO2 composites showed antibacterial activity towards S. aureus with increasing Ag content as compared to the TiO2 nanopowder. These results foresee promising applications of the functional plasmonic metal−semiconductor based nanobiocomposites for both chemical and biological samples.

Keywords: metal-Semiconductor, nano-Biocomposites, anti-microbial activity, surface enhanced Raman scattering

Procedia PDF Downloads 206

Authors: Phang Moon Leng

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Automated Early Warning Scores is a newly developed clinical decision tool that is used to streamline and improve the process of obtaining a patient’s vital signs so a clinical decision can be made at an earlier stage to prevent the patient from further deterioration. This technology provides immediate update on the score and clinical decision to be taken based on the outcome. This paper aims to study the use of an automated early warning score system on whether the technology has assisted the hospital in early detection and escalation of clinical condition and improve patient outcome. The hospital adopted the Modified Early Warning Scores (MEWS) Scoring System and MEWS Clinical Response into Philips IntelliVue Guardian Automated Early Warning Score equipment and studied whether the process has been leaned, whether the use of technology improved the usage & experience of the nurses, and whether the technology has improved patient care and outcome. It was found the steps required to obtain vital signs has been significantly reduced and is used more frequently to obtain patient vital signs. The number of deaths, and length of stay has significantly decreased as clinical decisions can be made and escalated more quickly with the Automated EWS. The automated early warning score equipment has helped improve work efficiency by removing the need for documenting into patient’s EMR. The technology streamlines clinical decision-making and allows faster care and intervention to be carried out and improves overall patient outcome which translates to better care for patient.

Keywords: automated early warning score, clinical quality and safety, patient safety, medical technology

Procedia PDF Downloads 147

Authors: Ankit Sinha, Soham Banerjee, Pratik Chattopadhyay

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Automated product recognition in retail stores is an important real-world application in the domain of Computer Vision and Pattern Recognition. In this paper, we consider the problem of automatically identifying the classes of the products placed on racks in retail stores from an image of the rack and information about the query/product images. We improve upon the existing approaches in terms of effectiveness and memory requirement by developing a two-stage object detection and recognition pipeline comprising of a Faster-RCNN-based object localizer that detects the object regions in the rack image and a ResNet-18-based image encoder that classifies the detected regions into the appropriate classes. Each of the models is fine-tuned using appropriate data sets for better prediction and data augmentation is performed on each query image to prepare an extensive gallery set for fine-tuning the ResNet-18-based product recognition model. This encoder is trained using a triplet loss function following the strategy of online-hard-negative-mining for improved prediction. The proposed models are lightweight and can be connected in an end-to-end manner during deployment to automatically identify each product object placed in a rack image. Extensive experiments using Grozi-32k and GP-180 data sets verify the effectiveness of the proposed model.

Keywords: retail stores, faster-RCNN, object localization, ResNet-18, triplet loss, data augmentation, product recognition

Procedia PDF Downloads 114