Search results for: normalized Laplacian eigenvalues
126 Using Hyperspectral Sensor and Machine Learning to Predict Water Potentials of Wild Blueberries during Drought Treatment
Authors: Yongjiang Zhang, Kallol Barai, Umesh R. Hodeghatta, Trang Tran, Vikas Dhiman
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Detecting water stress on crops early and accurately is crucial to minimize its impact. This study aims to measure water stress in wild blueberry crops non-destructively by analyzing proximal hyperspectral data. The data collection took place in the summer growing season of 2022. A drought experiment was conducted on wild blueberries in the randomized block design in the greenhouse, incorporating various genotypes and irrigation treatments. Hyperspectral data ( spectral range: 400-1000 nm) using a handheld spectroradiometer and leaf water potential data using a pressure chamber were collected from wild blueberry plants. Machine learning techniques, including multiple regression analysis and random forest models, were employed to predict leaf water potential (MPa). We explored the optimal wavelength bands for simple differences (RY1-R Y2), simple ratios (RY1/RY2), and normalized differences (|RY1-R Y2|/ (RY1-R Y2)). NDWI ((R857 - R1241)/(R857 + R1241)), SD (R2188 – R2245), and SR (R1752 / R1756) emerged as top predictors for predicting leaf water potential, significantly contributing to the highest model performance. The base learner models achieved an R-squared value of approximately 0.81, indicating their capacity to explain 81% of the variance. Research is underway to develop a neural vegetation index (NVI) that automates the process of index development by searching for specific wavelengths in the space ratio of linear functions of reflectance. The NVI framework could work across species and predict different physiological parameters.Keywords: hyperspectral reflectance, water potential, spectral indices, machine learning, wild blueberries, optimal bands
Procedia PDF Downloads 67125 Monitoring Deforestation Using Remote Sensing And GIS
Authors: Tejaswi Agarwal, Amritansh Agarwal
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Forest ecosystem plays very important role in the global carbon cycle. It stores about 80% of all above ground and 40% of all below ground terrestrial organic carbon. There is much interest in the extent of tropical forests and their rates of deforestation for two reasons: greenhouse gas contributions and the impact of profoundly negative biodiversity. Deforestation has many ecological, social and economic consequences, one of which is the loss of biological diversity. The rapid deployment of remote sensing (RS) satellites and development of RS analysis techniques in the past three decades have provided a reliable, effective, and practical way to characterize terrestrial ecosystem properties. Global estimates of tropical deforestation vary widely and range from 50,000 to 170,000km2 /yr Recent FAO tropical deforestation estimates for 1990–1995 cite 116,756km2 / yr globally. Remote Sensing can prove to be a very useful tool in monitoring of forests and associated deforestation to a sufficient level of accuracy without the need of physically surveying the forest areas as many of them are physically inaccessible. The methodology for the assessment of forest cover using digital image processing (ERDAS) has been followed. The satellite data for the study was procured from Indian institute of remote Sensing (IIRS), Dehradoon in the digital format. While procuring the satellite data, care was taken to ensure that the data was cloud free and did not belong to dry and leafless season. The Normalized Difference Vegetation Index (NDVI) has been used as a numerical indicator of the reduction in ground biomass. NDVI = (near I.R - Red)/ (near I.R + Red). After calculating the NDVI variations and associated mean, we have analysed the change in ground biomass. Through this paper, we have tried to indicate the rate of deforestation over a given period of time by comparing the forest cover at different time intervals. With the help of remote sensing and GIS techniques, it is clearly shown that the total forest cover is continuously degrading and transforming into various land use/land cover category.Keywords: remote sensing, deforestation, supervised classification, NDVI, change detection
Procedia PDF Downloads 1202124 The New Far-Right: The Social Construction of Hatred against the Contemporary Islamic Community in Multicultural Australia
Authors: Angel Adams
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In Australia, the contemporary social construction of hatred against the Islamic community was facilitated through the mainstream media. Australian public figures who have depicted Muslims and Islam not only as potential terrorists but also as incompatible with the country’s values and identities have helped to increase the level of fear against the Islamic community, leading sympathetic far-right movements to shift discussions towards anti-Islamic and anti-Muslim rhetoric. Political opportunities combined with a socially constructed narrative of fear of the ‘other’, introduced during the White Australia Policy of 1901, has allowed extreme and radical far-right movements to justify hate against the contemporary Australian Islamic community. This study aims to answer the following question: How does Australia’s founding provide a fertile environment to the spread of hatred against the contemporary Islamic community? The paper demonstrates that a forged social construct of grievances concerning the Islamic community in Australia has led to a surge in supply of far-right activism to combat what has become a perceived ‘national threat’. In essence, Australia’s history of a fear of the ‘other’ brings challenges to a multicultural society, and can potentially lead to a more unstable socio-political environment where abuse and violence are normalized and more likely to develop. Furthermore, the paper aims to bring a more nuanced understanding of what is considered ‘new far-right’ discourses with shared anti-Islam and anti-Muslim agendas in Australia. The political opportunity structures theory was the mechanism used to determine how new forms of far-right groups have become more mainstream in Australia. Previous studies on far-right groups in Australia have relied on qualitative data, but further empirical research in this area is sorely needed. Above all, this paper clarifies how hatred against minorities can have a negative impact on wider communities and allow a global narrative of ‘us’ versus ‘them’ to erupt from the fringes of society in Australia.Keywords: Australia, Islamophobia, far-right, nationalism, political opportunity structures, political violence, social construction
Procedia PDF Downloads 130123 NDVI as a Measure of Change in Forest Biomass
Authors: Amritansh Agarwal, Tejaswi Agarwal
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Forest ecosystem plays very important role in the global carbon cycle. It stores about 80% of all above ground and 40% of all below ground terrestrial organic carbon. There is much interest in the extent of tropical forests and their rates of deforestation for two reasons: greenhouse gas contributions and the impact of profoundly negative biodiversity. Deforestation has many ecological, social and economic consequences, one of which is the loss of biological diversity. The rapid deployment of remote sensing (RS) satellites and development of RS analysis techniques in the past three decades have provided a reliable, effective, and practical way to characterize terrestrial ecosystem properties. Global estimates of tropical deforestation vary widely and range from 50,000 to 170,000 km2 /yr Recent FAO tropical deforestation estimates for 1990–1995 cite 116,756km2 / yr globally. Remote Sensing can prove to be a very useful tool in monitoring of forests and associated deforestation to a sufficient level of accuracy without the need of physically surveying the forest areas as many of them are physically inaccessible. The methodology for the assessment of forest cover using digital image processing (ERDAS) has been followed. The satellite data for the study was procured from USGS website in the digital format. While procuring the satellite data, care was taken to ensure that the data was cloud and aerosol free by making using of FLAASH atmospheric correction technique. The Normalized Difference Vegetation Index (NDVI) has been used as a numerical indicator of the reduction in ground biomass. NDVI = (near I.R - Red)/ (near I.R + Red). After calculating the NDVI variations and associated mean we have analysed the change in ground biomass. Through this paper we have tried to indicate the rate of deforestation over a given period of time by comparing the forest cover at different time intervals. With the help of remote sensing and GIS techniques it is clearly shows that the total forest cover is continuously degrading and transforming into various land use/land cover category.Keywords: remote sensing, deforestation, supervised classification, NDVI change detection
Procedia PDF Downloads 402122 Geostatistical Models to Correct Salinity of Soils from Landsat Satellite Sensor: Application to the Oran Region, Algeria
Authors: Dehni Abdellatif, Lounis Mourad
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The new approach of applied spatial geostatistics in materials sciences, agriculture accuracy, agricultural statistics, permitted an apprehension of managing and monitoring the water and groundwater qualities in a relationship with salt-affected soil. The anterior experiences concerning data acquisition, spatial-preparation studies on optical and multispectral data has facilitated the integration of correction models of electrical conductivity related with soils temperature (horizons of soils). For tomography apprehension, this physical parameter has been extracted from calibration of the thermal band (LANDSAT ETM+6) with a radiometric correction. Our study area is Oran region (Northern West of Algeria). Different spectral indices are determined such as salinity and sodicity index, the Combined Spectral Reflectance Index (CSRI), Normalized Difference Vegetation Index (NDVI), emissivity, Albedo, and Sodium Adsorption Ratio (SAR). The approach of geostatistical modeling of electrical conductivity (salinity), appears to be a useful decision support system for estimating corrected electrical resistivity related to the temperature of surface soils, according to the conversion models by substitution, the reference temperature at 25°C (where hydrochemical data are collected with this constraint). The Brightness temperatures extracted from satellite reflectance (LANDSAT ETM+) are used in consistency models to estimate electrical resistivity. The confusions that arise from the effects of salt stress and water stress removed followed by seasonal application of the geostatistical analysis in Geographic Information System (GIS) techniques investigation and monitoring the variation of the electrical conductivity in the alluvial aquifer of Es-Sénia for the salt-affected soil.Keywords: geostatistical modelling, landsat, brightness temperature, conductivity
Procedia PDF Downloads 440121 Unveiling the Truth of Female Reproductive Health: The Tied Shackles of Authoritative Knowledge and Domestic Violence: An Ethnographic Study on an Urban Slum of Dhaka City
Authors: Saba Nuzhat
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The present ethnographic study examines how domestic violence and authoritative knowledge affect the reproductive health of females; in terms of contraceptive behavior and induced abortion. This qualitative study has been conducted by collecting in depth informal interviews and case studies of 12 female respondents living in an urban slum of Keraniganj, located Dhaka city. The study depicts how multivariable factors are linked to a woman’s ability to contracept and make abortion decisions in a cultural context where being a wife infers to submission, limited mobility, sexual availability, and restricted autonomy on her own reproduction health. This study shows how violence is being normalized and socially acceptable, every time women do not adhere to go through expected gender roles. The study primarily explores the subjective experiences and perceptions of the females about contraceptive behavior as well as abortions from a medical anthropological perspective. A number of salient examples are highlighted into this paper where women who go through abortion or adopt various measures of contraceptives get highly influenced by authoritative knowledge or under the pressure of male dominance. The lack of female autonomy or prevalence of domestic violence challenges the gender equality of Bangladeshi society and female sovereignty in accessing sexual or reproductive rights. This paper remarks the significance of medical anthropological research that helps to understand the intricate interrelationship between authoritative knowledge and male dominance with female reproductive health in order to reduce women’s risk of experiencing domestic violence and to promote reproductive health autonomy for themselves for espousing contraceptive behaviors and abortion decisions.Keywords: abortion, authoritative knowledge, contraception, domestic violence, reproductive health
Procedia PDF Downloads 140120 Elastodynamic Response of Shear Wave Dispersion in a Multi-Layered Concentric Cylinders Composed of Reinforced and Piezo-Materials
Authors: Sunita Kumawat, Sumit Kumar Vishwakarma
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The present study fundamentally focuses on analyzing the limitations and transference of horizontally polarized Shear waves(SH waves) in a four-layered compounded cylinder. The geometrical structure comprises of concentric cylinders of infinite length composed of self-reinforced (SR), fibre-reinforced (FR), piezo-magnetic (PM), and piezo-electric(PE) materials. The entire structure is assumed to be pre stressed along the azimuthal direction. In order to make the structure sensitive to the application pertaining to sensors and actuators, the PM and PE cylinders have been categorically placed in the outer part of the geometry. Whereas in order to provide stiffness and stability to the structure, the inner part consists of self-reinforced and fibre-reinforced media. The common boundary between each of the cylinders has been essentially considered as imperfectly bounded. At the interface of PE and PM media, mechanical, electrical, magnetic, and inter-coupled types of imperfections have been exhibited. The closed-form of dispersion relation has been deduced for two contrast cases i.e. electrically open magnetically short(EOMS) and electrically short and magnetically open ESMO circuit conditions. Dispersion curves have been plotted to illustrate the salient features of parameters like normalized imperfect interface parameters, initial stresses, and radii of the concentric cylinders. The comparative effect of each one of these parameters on the phase velocity of the wave has been enlisted and marked individually. Every graph has been presented with two consecutive modes in succession for a comprehensive understanding. This theoretical study may be implemented to improvise the performance of surface acoustic wave (SAW) sensors and actuators consisting of piezo-electric quartz and piezo-composite concentric cylinders.Keywords: self-reinforced, fibre-reinforced, piezo-electric, piezo-magnetic, interfacial imperfection
Procedia PDF Downloads 109119 House Price Index Predicts a Larger Impact of Habitat Loss than Primary Productivity on the Biodiversity of North American Avian Communities
Authors: Marlen Acosta Alamo, Lisa Manne, Richard Veit
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Habitat loss due to land use change is one of the leading causes of biodiversity loss worldwide. This form of habitat loss is a non-random phenomenon since the same environmental factors that make an area suitable for supporting high local biodiversity overlap with those that make it attractive for urban development. We aimed to compare the effect of two non-random habitat loss predictors on the richness, abundance, and rarity of nature-affiliated and human-affiliated North American breeding birds. For each group of birds, we simulated the non-random habitat loss using two predictors: the House Price Index as a measure of the attractiveness of an area for humans and the Normalized Difference Vegetation Index as a proxy for primary productivity. We compared the results of the two non-random simulation sets and one set of random habitat loss simulations using an analysis of variance and followed up with a Tukey-Kramer test when appropriate. The attractiveness of an area for humans predicted estimates of richness loss and increase of rarity higher than primary productivity and random habitat loss for nature-affiliated and human-affiliated birds. For example, at 50% of habitat loss, the attractiveness of an area for humans produced estimates of richness at least 5% lower and of a rarity at least 40% higher than primary productivity and random habitat loss for both groups of birds. Only for the species abundance of nature-affiliated birds, the attractiveness of an area for humans did not outperform primary productivity as a predictor of biodiversity following habitat loss. We demonstrated the value of the House Price Index, which can be used in conservation assessments as an index of the risks of habitat loss for natural communities. Thus, our results have relevant implications for sustainable urban land-use planning practices and can guide stakeholders and developers in their efforts to conserve local biodiversity.Keywords: biodiversity loss, bird biodiversity, house price index, non-random habitat loss
Procedia PDF Downloads 86118 A Convolution Neural Network Approach to Predict Pes-Planus Using Plantar Pressure Mapping Images
Authors: Adel Khorramrouz, Monireh Ahmadi Bani, Ehsan Norouzi, Morvarid Lalenoor
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Background: Plantar pressure distribution measurement has been used for a long time to assess foot disorders. Plantar pressure is an important component affecting the foot and ankle function and Changes in plantar pressure distribution could indicate various foot and ankle disorders. Morphologic and mechanical properties of the foot may be important factors affecting the plantar pressure distribution. Accurate and early measurement may help to reduce the prevalence of pes planus. With recent developments in technology, new techniques such as machine learning have been used to assist clinicians in predicting patients with foot disorders. Significance of the study: This study proposes a neural network learning-based flat foot classification methodology using static foot pressure distribution. Methodologies: Data were collected from 895 patients who were referred to a foot clinic due to foot disorders. Patients with pes planus were labeled by an experienced physician based on clinical examination. Then all subjects (with and without pes planus) were evaluated for static plantar pressures distribution. Patients who were diagnosed with the flat foot in both feet were included in the study. In the next step, the leg length was normalized and the network was trained for plantar pressure mapping images. Findings: From a total of 895 image data, 581 were labeled as pes planus. A computational neural network (CNN) ran to evaluate the performance of the proposed model. The prediction accuracy of the basic CNN-based model was performed and the prediction model was derived through the proposed methodology. In the basic CNN model, the training accuracy was 79.14%, and the test accuracy was 72.09%. Conclusion: This model can be easily and simply used by patients with pes planus and doctors to predict the classification of pes planus and prescreen for possible musculoskeletal disorders related to this condition. However, more models need to be considered and compared for higher accuracy.Keywords: foot disorder, machine learning, neural network, pes planus
Procedia PDF Downloads 360117 Agile Software Effort Estimation Using Regression Techniques
Authors: Mikiyas Adugna
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Effort estimation is among the activities carried out in software development processes. An accurate model of estimation leads to project success. The method of agile effort estimation is a complex task because of the dynamic nature of software development. Researchers are still conducting studies on agile effort estimation to enhance prediction accuracy. Due to these reasons, we investigated and proposed a model on LASSO and Elastic Net regression to enhance estimation accuracy. The proposed model has major components: preprocessing, train-test split, training with default parameters, and cross-validation. During the preprocessing phase, the entire dataset is normalized. After normalization, a train-test split is performed on the dataset, setting training at 80% and testing set to 20%. We chose two different phases for training the two algorithms (Elastic Net and LASSO) regression following the train-test-split. In the first phase, the two algorithms are trained using their default parameters and evaluated on the testing data. In the second phase, the grid search technique (the grid is used to search for tuning and select optimum parameters) and 5-fold cross-validation to get the final trained model. Finally, the final trained model is evaluated using the testing set. The experimental work is applied to the agile story point dataset of 21 software projects collected from six firms. The results show that both Elastic Net and LASSO regression outperformed the compared ones. Compared to the proposed algorithms, LASSO regression achieved better predictive performance and has acquired PRED (8%) and PRED (25%) results of 100.0, MMRE of 0.0491, MMER of 0.0551, MdMRE of 0.0593, MdMER of 0.063, and MSE of 0.0007. The result implies LASSO regression algorithm trained model is the most acceptable, and higher estimation performance exists in the literature.Keywords: agile software development, effort estimation, elastic net regression, LASSO
Procedia PDF Downloads 71116 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 144115 Effect of Loop Diameter, Height and Insulation on a High Temperature CO2 Based Natural Circulation Loop
Authors: S. Sadhu, M. Ramgopal, S. Bhattacharyya
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Natural circulation loops (NCLs) are buoyancy driven flow systems without any moving components. NCLs have vast applications in geothermal, solar and nuclear power industry where reliability and safety are of foremost concern. Due to certain favorable thermophysical properties, especially near supercritical regions, carbon dioxide can be considered as an ideal loop fluid in many applications. In the present work, a high temperature NCL that uses supercritical carbon dioxide as loop fluid is analysed. The effects of relevant design and operating variables on loop performance are studied. The system operating under steady state is modelled taking into account the axial conduction through loop fluid and loop wall, and heat transfer with surroundings. The heat source is considered to be a heater with controlled heat flux and heat sink is modelled as an end heat exchanger with water as the external cold fluid. The governing equations for mass, momentum and energy conservation are normalized and are solved numerically using finite volume method. Results are obtained for a loop pressure of 90 bar with the power input varying from 0.5 kW to 6.0 kW. The numerical results are validated against the experimental results reported in the literature in terms of the modified Grashof number (Grm) and Reynolds number (Re). Based on the results, buoyancy and friction dominated regions are identified for a given loop. Parametric analysis has been done to show the effect of loop diameter, loop height, ambient temperature and insulation. The results show that for the high temperature loop, heat loss to surroundings affects the loop performance significantly. Hence this conjugate heat transfer between the loop and surroundings has to be considered in the analysis of high temperature NCLs.Keywords: conjugate heat transfer, heat loss, natural circulation loop, supercritical carbon dioxide
Procedia PDF Downloads 241114 Evaluation of Anti-Typhoid Effects of Azadirachta indica L. Fractions
Authors: A. Adetutu, T. M. Awodugba, O. A. Owoade
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The development of resistance to currently known conventional anti-typhoid drugs has necessitated search into cheap, more potent and less toxic anti-typhoid drugs of plant origin. Therefore, this study investigated the anti-typhoid activity of fractions of A. indica in Salmonella typhi infected rats. Leaves of A. indica were extracted in methanol and fractionated into n-hexane, chloroform, ethyl-acetate, and aqueous fractions. The anti-salmonella potentials of fractions of A. indica were assessed via in-vitro inhibition of S. typhi using agar well diffusion, Minimum Inhibitory Concentration (MIC), Minimum Bactericidal Concentration (MBC) and biofilm assays. The biochemical and haematological parameters were determined by spectrophotometric methods. The histological analysis was performed using Haematoxylin and Eosin staining methods. Data analysis was performed by one-way ANOVA. Results of this study showed that S. typhi was sensitive to aqueous and chloroform fractions of A. indica, and the fractions showed biofilm inhibition at concentrations of 12.50, 1.562, and 0.39 mg/mL. In the in-vivo study, the extract and chloroform fraction had significant (p < 0.05) effects on the number of viable S. typhi recovered from the blood and stopped salmonellosis after 6 days of treatment of rats at 500 mg/kg b.w. Treatments of infected rats with chloroform and aqueous fractions of A. indica normalized the haematological parameters in the animals. Similarly, treatment with fractions of the plants sustained a normal antioxidant status when compared with the normal control group. Chloroform and ethyl-acetate fractions of A. indica reversed the liver and intestinal degeneration induced by S. typhi infection in rats. The present investigation indicated that the aqueous and chloroform fractions of A. indica showed the potential to provide an effective treatment for salmonellosis, including typhoid fever. The results of the study may justify the ethno-medicinal use of the extract in traditional medicine for the treatment of typhoid and salmonella infections.Keywords: Azadirachta indica L, salmonella, typhoid, leave fractions
Procedia PDF Downloads 132113 Evaluation and Selection of Contractors in Construction Projects with a View Supply Chain Management and Utilization of Promthee
Authors: Sara Najiazarpour, Mahsa Najiazarpour
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There are many problems in contracting projects and their performance. At each project stage and due to different reasons, these problems affect cost, time and overall project quality. Hence, in order to increase the efficiency and performance in all levels of the chain and with supply chain management approach, there will be a coordination from the beginning of a project (contractor selection) to the end of project (handover of project). Contractor selection is the foremost part of construction projects which in this multi-criteria decision-making, the best contractor is determined by expert judgment, different variables and their priorities. In this paper for selecting the best contractor, numerous criteria were collected by asking from adept experts and then among them, 16 criteria with highest frequency were considered for questionnaire. This questionnaire was distributed between experts. Cronbach's alpha coefficient was obtained as 72%. Then based on Borda's function 12 important criteria was selected which was categorized in four main criteria and related sub-criteria as follow: Environmental factors and physical equipment: procurement and materials (supplier), company's machines, contractor’s proposed cost estimate - financial capacity: bank turnover and company's assets, the income of tax declaration in last year, Ability to compensate for losses or delays - past performance- records and technical expertise: experts and key personnel, the past technical backgrounds and experiences, employer satisfaction of previous contracts, the number of similar projects was done - standards: rank and field of expertise which company is qualified for and its validity, availability and number of permitted projects done. Then with PROMTHEE method, the criteria were normalized and monitored, finally the best alternative was selected. In this research, qualitative criteria of each company is became a quantitative criteria. Finally, information of some companies was evaluated and the best contractor was selected based on all criteria and their priorities.Keywords: contractor evaluation and selection, project development, supply chain management, PROMTHEE method
Procedia PDF Downloads 72112 Assessment of Soil Quality Indicators in Rice Soil of Tamil Nadu
Authors: Kaleeswari R. K., Seevagan L .
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Soil quality in an agroecosystem is influenced by the cropping system, water and soil fertility management. A valid soil quality index would help to assess the soil and crop management practices for desired productivity and soil health. The soil quality indices also provide an early indication of soil degradation and needy remedial and rehabilitation measures. Imbalanced fertilization and inadequate organic carbon dynamics deteriorate soil quality in an intensive cropping system. The rice soil ecosystem is different from other arable systems since rice is grown under submergence, which requires a different set of key soil attributes for enhancing soil quality and productivity. Assessment of the soil quality index involves indicator selection, indicator scoring and comprehensive score into one index. The most appropriate indicator to evaluate soil quality can be selected by establishing the minimum data set, which can be screened by linear and multiple regression factor analysis and score function. This investigation was carried out in intensive rice cultivating regions (having >1.0 lakh hectares) of Tamil Nadu viz., Thanjavur, Thiruvarur, Nagapattinam, Villupuram, Thiruvannamalai, Cuddalore and Ramanathapuram districts. In each district, intensive rice growing block was identified. In each block, two sampling grids (10 x 10 sq.km) were used with a sampling depth of 10 – 15 cm. Using GIS coordinates, and soil sampling was carried out at various locations in the study area. The number of soil sampling points were 41, 28, 28, 32, 37, 29 and 29 in Thanjavur, Thiruvarur, Nagapattinam, Cuddalore, Villupuram, Thiruvannamalai and Ramanathapuram districts, respectively. Principal Component Analysis is a data reduction tool to select some of the potential indicators. Principal Component is a linear combination of different variables that represents the maximum variance of the dataset. Principal Component that has eigenvalues equal or higher than 1.0 was taken as the minimum data set. Principal Component Analysis was used to select the representative soil quality indicators in rice soils based on factor loading values and contribution percent values. Variables having significant differences within the production system were used for the preparation of the minimum data set. Each Principal Component explained a certain amount of variation (%) in the total dataset. This percentage provided the weight for variables. The final Principal Component Analysis based soil quality equation is SQI = ∑ i=1 (W ᵢ x S ᵢ); where S- score for the subscripted variable; W-weighing factor derived from PCA. Higher index scores meant better soil quality. Soil respiration, Soil available Nitrogen and Potentially Mineralizable Nitrogen were assessed as soil quality indicators in rice soil of the Cauvery Delta zone covering Thanjavur, Thiruvavur and Nagapattinam districts. Soil available phosphorus could be used as a soil quality indicator of rice soils in the Cuddalore district. In rain-fed rice ecosystems of coastal sandy soil, DTPA – Zn could be used as an effective soil quality indicator. Among the soil parameters selected from Principal Component Analysis, Microbial Biomass Nitrogen could be used quality indicator for rice soils of the Villupuram district. Cauvery Delta zone has better SQI as compared with other intensive rice growing zone of Tamil Nadu.Keywords: soil quality index, soil attributes, soil mapping, and rice soil
Procedia PDF Downloads 86111 Chemopreventive and Therapeutic Efficacy of Salsola inermis Extract against N-Nitrosodiethylamine-Initiated and Phenobarbital-Promoted Hepatocellular Carcinogenesis in Wistar Rats
Authors: Ahlam H. Mahmoud, Samir F. Zohny, Ibrahim H. Boraia, Faten S. Bayoumic, Eman Eissa
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Hepatocellular carcinoma is one of the most common cancers worldwide and is known to be resistant to conventional chemotherapy. Therefore, we aimed to assess the Salsola inermis extract as a novel chemopreventive and/or therapeutic agent against N-nitrosodiethylamine (DNE)/phenobarbital (PB)-induced hepatocarcinogenesis in rats. Adult male Wistar albino rats were divided into five groups: group1 rats were served as normal controls; group 2 rats were injected intraperitoneally with S. inermis extract (100 mg/kg body weight/day) for 20 weeks; group 3 rats were subjected to two-phase hepatocarcinogenic regimen (initiation of hepatocarcinogenesis was performed by a single intraperitoneal injection of DEN at a dose of 200 mg/kg body weight, 2 weeks later, the carcinogenic effect was promoted by supplementation of rats with 0.05% PB for 16 weeks); group 4 rats were injected intraperitoneally with S. inermis extract 2 weeks prior to the injection of DEN, the daily injection of S. inermis extract was then continued for 18 weeks along with two-phase hepatocarcinogenic regimen (chemoprevention group); and group 5 rats were subjected to the two-phase hepatocarcinogenic regimen, and then, the animals were injected intraperitoneally with S. inermis extract for 4 weeks (treatment group). The activities of serum liver enzymes and levels of total bilirubin, conjugated bilirubin, α-fetoprotein, vascular endothelial growth factor (VEGF) and soluble intercellular adhesion molecule-1 (sICAM-1) in serum were decreased in chemopreventive and treated rats compared with DEN/PB-administered rats. Interestingly, the serum levels of total protein and albumin were normalized in chemopreventive and treated rats. Moreover, the majority of chemopreventive and treated rats showed an almost normal histological pattern of liver. In conclusion, S. inermis extract possessed chemopreventive and therapeutic activities against hepatocarcinogenesis in rats partially through the inhibition of VEGF and sICAM-1.Keywords: Salsola inermis extract, hepatocarcinogenesis, α–fetoprotein, VEGF, sICAM-1
Procedia PDF Downloads 369110 In vivo Antidiabetic and Antioxidant Potential of Pseudovaria macrophylla Extract
Authors: Aditya Arya, Hairin Taha, Ataul Karim Khan, Nayiar Shahid, Hapipah Mohd Ali, Mustafa Ali Mohd
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This study has investigated the antidiabetic and antioxidant potential of Pseudovaria macrophylla bark extract on streptozotocin–nicotinamide induced type 2 diabetic rats. LCMS-QTOF and NMR experiments were done to determine the chemical composition in the methanolic bark extract. For in vivo experiments, the STZ (60 mg/kg/b.w, 15 min after 120 mg/kg/1 nicotinamide, i.p.) induced diabetic rats were treated with methanolic extract of Pseuduvaria macrophylla (200 and 400 mg/kg∙bw) and glibenclamide (2.5 mg/kg) as positive control respectively. Biochemical parameters were assayed in the blood samples of all groups of rats. The pro-inflammatory cytokines, antioxidant status and plasma transforming growth factor βeta-1 (TGF-β1) were evaluated. The histological study of the pancreas was examined and its expression level of insulin was observed by immunohistochemistry. In addition, the expression of glucose transporters (GLUT 1, 2 and 4) were assessed in pancreas tissue by western blot analysis. The outcomes of the study displayed that the bark methanol extract of Pseuduvaria macrophylla has potentially normalized the elevated blood glucose levels and improved serum insulin and C-peptide levels with significant increase in the antioxidant enzyme, reduced glutathione (GSH) and decrease in the level of lipid peroxidation (LPO). Additionally, the extract has markedly decreased the levels of serum pro-inflammatory cytokines and transforming growth factor beta-1 (TGF-β1). Histopathology analysis demonstrated that Pseuduvaria macrophylla has the potential to protect the pancreas of diabetic rats against peroxidation damage by downregulating oxidative stress and elevated hyperglycaemia. Furthermore, the expression of insulin protein, GLUT-1, GLUT-2 and GLUT-4 in pancreatic cells was enhanced. The findings of this study support the anti-diabetic claims of Pseudovaria macrophylla bark.Keywords: diabetes mellitus, Pseuduvaria macrophylla, alkaloids, caffeic acid
Procedia PDF Downloads 357109 Antagonist Coactivation in Athletes Following Anterior Cruciate Ligament Reconstruction
Authors: Milad Pirali, Sohrab Keyhani, Mohhamad Ali Sanjari, Ali Ashraf Jamshidi
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Purpose: The effect of hamstring antagonist activity on the knee extensors torque of the Anterior Cruciate Ligament reconstruction (ACLR) is not clear and persistent muscle weakness is common after ACLR. Hamstring activation when acting as antagonist is considered very important for knee strengths. Therefore the purpose of this study was to examine hamstring antagonist coactivation during maximal effort of the isokinetic knee extension in ACLR athletes with hamstring autograft. Materials and Methods: We enrolled 20 professional athletes who underwent primary ACLR (hamstring tendon autograft)with 6-24 months postoperative and 20 healthy subjects as control group. Each subjects performed maximal effort isokinetic knee extension and flexion in 60/˚ s and 180/˚ s velocities for the involved and uninvolved limb. Synchronously, surface electromyography (EMG) was recorded of vastus medialis (VM), vastus lateralis (VL), rectus femoris (RF) and biceps femoris (BF). The antagonist integrated EMG (IEMG) values were normalized to the IEMG of the same muscle during maximal isokinetic eccentric effort at the same velocities and ROM. Results: A one-way analysis of variance designs shows significantly greater IEMG coactivation of hamstring and decreased activation of Vm in ACLR when compared to uninvolved and control group leg in 60/˚ s and 180/˚ s velocities. Likewise peak torque to body weight was decreased in ACLR compared to uninvolved and control group during knee extension in both velocities (p < 0.05). Conclusions: Decreased extensors moment caused by decreased quadriceps inhibition and increased hamstring coactivation. In addition, these result indicated to decrease of motor unit recruitment in the VM (as a kinesiologicmonitore of the knee). It is appearing that strengthening of the quadriceps to be an important for rehabilitation program after ACLR for preparation in athletes endeavors. Therefore, we suggest that having more emphasis and focus on quadriceps strength and less emphasis on hamstring following ACLR.Keywords: ACLR-coactivation, dynamometry, electromyography, isokinetic
Procedia PDF Downloads 254108 A Single Feature Probability-Object Based Image Analysis for Assessing Urban Landcover Change: A Case Study of Muscat Governorate in Oman
Authors: Salim H. Al Salmani, Kevin Tansey, Mohammed S. Ozigis
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The study of the growth of built-up areas and settlement expansion is a major exercise that city managers seek to undertake to establish previous and current developmental trends. This is to ensure that there is an equal match of settlement expansion needs to the appropriate levels of services and infrastructure required. This research aims at demonstrating the potential of satellite image processing technique, harnessing the utility of single feature probability-object based image analysis technique in assessing the urban growth dynamics of the Muscat Governorate in Oman for the period 1990, 2002 and 2013. This need is fueled by the continuous expansion of the Muscat Governorate beyond predicted levels of infrastructural provision. Landsat Images of the years 1990, 2002 and 2013 were downloaded and preprocessed to forestall appropriate radiometric and geometric standards. A novel approach of probability filtering of the target feature segment was implemented to derive the spatial extent of the final Built-Up Area of the Muscat governorate for the three years period. This however proved to be a useful technique as high accuracy assessment results of 55%, 70%, and 71% were recorded for the Urban Landcover of 1990, 2002 and 2013 respectively. Furthermore, the Normalized Differential Built – Up Index for the various images were derived and used to consolidate the results of the SFP-OBIA through a linear regression model and visual comparison. The result obtained showed various hotspots where urbanization have sporadically taken place. Specifically, settlement in the districts (Wilayat) of AL-Amarat, Muscat, and Qurayyat experienced tremendous change between 1990 and 2002, while the districts (Wilayat) of AL-Seeb, Bawshar, and Muttrah experienced more sporadic changes between 2002 and 2013.Keywords: urban growth, single feature probability, object based image analysis, landcover change
Procedia PDF Downloads 274107 Changes in Forest Cover Regulate Streamflow in Central Nigerian Gallery Forests
Authors: Rahila Yilangai, Sonali Saha, Amartya Saha, Augustine Ezealor
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Gallery forests in sub-Saharan Africa are drastically disappearing due to intensive anthropogenic activities thus reducing ecosystem services, one of which is water provisioning. The role played by forest cover in regulating streamflow and water yield is not well understood, especially in West Africa. This pioneering 2-year study investigated the interrelationships between plant cover and hydrology in protected and unprotected gallery forests. Rainfall, streamflow, and evapotranspiration (ET) measurements/estimates over 2015-2016 were obtained to form a water balance for both catchments. In addition, transpiration in the protected gallery forest with high vegetation cover was calculated from stomatal conductance readings of selected species chosen from plot level data of plant diversity and abundance. Results showed that annual streamflow was significantly higher in the unprotected site than the protected site, even when normalized by catchment area. However, streamflow commenced earlier and lasted longer in the protected site than the degraded unprotected site, suggesting regulation by the greater tree density in the protected site. Streamflow correlated strongly with rainfall with the highest peak in August. As expected, transpiration measurements were less than potential evapotranspiration estimates, while rainfall exceeded ET in the water cycle. The water balance partitioning suggests that the lower vegetation cover in the unprotected catchment leads to a larger runoff in the rainy season and less infiltration, thereby leading to streams drying up earlier, than in the protected catchment. This baseline information is important in understanding the contribution of plants in water cycle regulation, for modeling integrative water management in applied research and natural resource management in sustaining water resources with changing the land cover and climate uncertainties in this data-poor region.Keywords: evapotranspiration, gallery forest, rainfall, streamflow, transpiration
Procedia PDF Downloads 172106 Neural Network and Support Vector Machine for Prediction of Foot Disorders Based on Foot Analysis
Authors: Monireh Ahmadi Bani, Adel Khorramrouz, Lalenoor Morvarid, Bagheri Mahtab
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Background:- Foot disorders are common in musculoskeletal problems. Plantar pressure distribution measurement is one the most important part of foot disorders diagnosis for quantitative analysis. However, the association of plantar pressure and foot disorders is not clear. With the growth of dataset and machine learning methods, the relationship between foot disorders and plantar pressures can be detected. Significance of the study:- The purpose of this study was to predict the probability of common foot disorders based on peak plantar pressure distribution and center of pressure during walking. Methodologies:- 2323 participants were assessed in a foot therapy clinic between 2015 and 2021. Foot disorders were diagnosed by an experienced physician and then they were asked to walk on a force plate scanner. After the data preprocessing, due to the difference in walking time and foot size, we normalized the samples based on time and foot size. Some of force plate variables were selected as input to a deep neural network (DNN), and the probability of any each foot disorder was measured. In next step, we used support vector machine (SVM) and run dataset for each foot disorder (classification of yes or no). We compared DNN and SVM for foot disorders prediction based on plantar pressure distributions and center of pressure. Findings:- The results demonstrated that the accuracy of deep learning architecture is sufficient for most clinical and research applications in the study population. In addition, the SVM approach has more accuracy for predictions, enabling applications for foot disorders diagnosis. The detection accuracy was 71% by the deep learning algorithm and 78% by the SVM algorithm. Moreover, when we worked with peak plantar pressure distribution, it was more accurate than center of pressure dataset. Conclusion:- Both algorithms- deep learning and SVM will help therapist and patients to improve the data pool and enhance foot disorders prediction with less expense and error after removing some restrictions properly.Keywords: deep neural network, foot disorder, plantar pressure, support vector machine
Procedia PDF Downloads 357105 Determination of Rare Earth Element Patterns in Uranium Matrix for Nuclear Forensics Application: Method Development for Inductively Coupled Plasma Mass Spectrometry (ICP-MS) Measurements
Authors: Bernadett Henn, Katalin Tálos, Éva Kováss Széles
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During the last 50 years, the worldwide permeation of the nuclear techniques induces several new problems in the environmental and in the human life. Nowadays, due to the increasing of the risk of terrorism worldwide, the potential occurrence of terrorist attacks using also weapon of mass destruction containing radioactive or nuclear materials as e.g. dirty bombs, is a real threat. For instance, the uranium pellets are one of the potential nuclear materials which are suitable for making special weapons. The nuclear forensics mainly focuses on the determination of the origin of the confiscated or found nuclear and other radioactive materials, which could be used for making any radioactive dispersive device. One of the most important signatures in nuclear forensics to find the origin of the material is the determination of the rare earth element patterns (REE) in the seized or found radioactive or nuclear samples. The concentration and the normalized pattern of the REE can be used as an evidence of uranium origin. The REE are the fourteen Lanthanides in addition scandium and yttrium what are mostly found together and really low concentration in uranium pellets. The problems of the REE determination using ICP-MS technique are the uranium matrix (high concentration of uranium) and the interferences among Lanthanides. In this work, our aim was to develop an effective chemical sample preparation process using extraction chromatography for separation the uranium matrix and the rare earth elements from each other following some publications can be found in the literature and modified them. Secondly, our purpose was the optimization of the ICP-MS measuring process for REE concentration. During method development, in the first step, a REE model solution was used in two different types of extraction chromatographic resins (LN® and TRU®) and different acidic media for environmental testing the Lanthanides separation. Uranium matrix was added to the model solution and was proved in the same conditions. Methods were tested and validated using REE UOC (uranium ore concentrate) reference materials. Samples were analyzed by sector field mass spectrometer (ICP-SFMS).Keywords: extraction chromatography, nuclear forensics, rare earth elements, uranium
Procedia PDF Downloads 307104 Computational Fluid Dynamicsfd Simulations of Air Pollutant Dispersion: Validation of Fire Dynamic Simulator Against the Cute Experiments of the Cost ES1006 Action
Authors: Virginie Hergault, Siham Chebbah, Bertrand Frere
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Following in-house objectives, Central laboratory of Paris police Prefecture conducted a general review on models and Computational Fluid Dynamics (CFD) codes used to simulate pollutant dispersion in the atmosphere. Starting from that review and considering main features of Large Eddy Simulation, Central Laboratory Of Paris Police Prefecture (LCPP) postulates that the Fire Dynamics Simulator (FDS) model, from National Institute of Standards and Technology (NIST), should be well suited for air pollutant dispersion modeling. This paper focuses on the implementation and the evaluation of FDS in the frame of the European COST ES1006 Action. This action aimed at quantifying the performance of modeling approaches. In this paper, the CUTE dataset carried out in the city of Hamburg, and its mock-up has been used. We have performed a comparison of FDS results with wind tunnel measurements from CUTE trials on the one hand, and, on the other, with the models results involved in the COST Action. The most time-consuming part of creating input data for simulations is the transfer of obstacle geometry information to the format required by SDS. Thus, we have developed Python codes to convert automatically building and topographic data to the FDS input file. In order to evaluate the predictions of FDS with observations, statistical performance measures have been used. These metrics include the fractional bias (FB), the normalized mean square error (NMSE) and the fraction of predictions within a factor of two of observations (FAC2). As well as the CFD models tested in the COST Action, FDS results demonstrate a good agreement with measured concentrations. Furthermore, the metrics assessment indicate that FB and NMSE meet the tolerance acceptable.Keywords: numerical simulations, atmospheric dispersion, cost ES1006 action, CFD model, cute experiments, wind tunnel data, numerical results
Procedia PDF Downloads 133103 Geospatial Analysis of Hydrological Response to Forest Fires in Small Mediterranean Catchments
Authors: Bojana Horvat, Barbara Karleusa, Goran Volf, Nevenka Ozanic, Ivica Kisic
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Forest fire is a major threat in many regions in Croatia, especially in coastal areas. Although they are often caused by natural processes, the most common cause is the human factor, intentional or unintentional. Forest fires drastically transform landscapes and influence natural processes. The main goal of the presented research is to analyse and quantify the impact of the forest fire on hydrological processes and propose the model that best describes changes in hydrological patterns in the analysed catchments. Keeping in mind the spatial component of the processes, geospatial analysis is performed to gain better insight into the spatial variability of the hydrological response to disastrous events. In that respect, two catchments that experienced severe forest fire were delineated, and various hydrological and meteorological data were collected both attribute and spatial. The major drawback is certainly the lack of hydrological data, common in small torrential karstic streams; hence modelling results should be validated with the data collected in the catchment that has similar characteristics and established hydrological monitoring. The event chosen for the modelling is the forest fire that occurred in July 2019 and burned nearly 10% of the analysed area. Surface (land use/land cover) conditions before and after the event were derived from the two Sentinel-2 images. The mapping of the burnt area is based on a comparison of the Normalized Burn Index (NBR) computed from both images. To estimate and compare hydrological behaviour before and after the event, curve number (CN) values are assigned to the land use/land cover classes derived from the satellite images. Hydrological modelling resulted in surface runoff generation and hence prediction of hydrological responses in the catchments to a forest fire event. The research was supported by the Croatian Science Foundation through the project 'Influence of Open Fires on Water and Soil Quality' (IP-2018-01-1645).Keywords: Croatia, forest fire, geospatial analysis, hydrological response
Procedia PDF Downloads 136102 Exploration of the Nonlinear Viscoelastic Behavior of Yogurt Using Lissajous Curves
Authors: Hugo Espinosa-Andrews
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Introduction: Yogurt is widely accepted worldwide due to its high nutritional value, consistency, and texture. Their rheological properties play a significant role in consumer acceptance and are related to the manufacturing process and formulation. Typically, the viscoelastic characteristics of yogurts are studied using the small amplitude oscillatory shear test; however, the initial stages of flow and oral processing are described in the nonlinear zone, in which a large amplitude oscillatory stress test is applied. The objective of this work was to analyze the nonlinear viscoelastic behavior of commercial yogurts using Lissajous curves. Methods: Two commercial yogurts were purchased in a local store in Guadalajara Jalisco Mexico: a natural Greek-style yogurt and a low-fat traditional yogurt. Viscoelastic properties were evaluated using a large amplitude oscillatory stress procedure (LAOS). A crosshatch geometry of 40 mm and a truncation of 1000 µm were used. Stress sweeps were performed at 6.28 rad/s from 1 to 250 Pa at 5°C. The nonlinear viscoelastic properties were analyzed using the Lissajous curves. Results: The yogurts showed strain-viscoelastic behavior related to deformation-dependent materials. In the low-strain region, the elastic modulus predominated over the viscous modulus, showing gel-elastic properties. The sol-gel transitions were observed at approximately 66.5 Pa for the Greek yogurt, double that detected for traditional yogurt. The viscoelastic behavior of the yogurts was characteristic of weak excess deformation: behavior indicating a stable molecular structure at rest, and moderate structure at medium shear-forces. The normalized Lissajous curves characterized viscoelastic transitions of the yogurt as the stress increased. Greater viscoelasticity deformation was observed in Greek yogurt than in traditional yogurt, which is related to the presence of a protein network with a greater degree of crosslinking. Conclusions: The yogurt composition influences the viscoelastic properties of the material. Yogurt with the higher percentage of protein has greater viscoelastic and viscous properties, which describe a product of greater consistency and creaminess.Keywords: yogurt, viscoelastic properties, LAOS, elastic modulus
Procedia PDF Downloads 21101 Creating a Dementia-Friendly Community
Authors: Annika Kjallman Alm, Ove Hellzen, Malin Rising-Homlstrom
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The concept of dementia‐friendly communities focuses on the lived experience of people who have dementia and is most relevant to addressing their needs and the needs of those people who live with and provide support for them. The goal of communities becoming dementia‐friendly is for dementia to be normalized and recognized as a disabling condition. People with dementia find being connected to self, to others, and to the environment by meaningful activities as important. According to the concept underlying dementia-friendly communities, people with dementia or cognitive decline can continue to live in the community if their residential community has sufficiently strong social capital. The aim of this study is to explore staff and leaders’ experiences in implementing interventions to enhance a more inclusive dementia-friendly community. A municipality in northern Sweden with a population of approx. 100 000 inhabitants decided to create a dementia friendly municipality. As part of the initiative, a Centre for support was established. The Centre offered support for both individuals and groups, did home visits, and provided information about Dementia. Interviews were conducted with staff who had undergone training in a structured form of multidimensional support, the PER-model®, and worked at the Centre for support. The staff consisted of registered nurses, occupational therapists, and specialized nurses who had worked there for more than five years, and all had training in dementia. All interviews were audio-recorded and transcribed verbatim. The transcribed data were analyzed using qualitative content analysis. Results suggest that implementing the PER-model® of support for persons in the early stages of dementia and their next of kin added a much-needed form of support and perceived possibilities to enhance daily life in the early stages of dementia. The staff appreciated that the structure of PER-model® was evidenced based. They also realized that they never even considered that the person with dementia also needed support in the early stages but that they now had tools for that as well. Creating a dementia friendly municipality offering different kinds of support for all stages of dementia is a challenge. However, evidence-based tools and a broad spectrum of different types of support, whether individual or group, are needed to tailor to everyone’s needs. A conviction that all citizens are equal and should all be involved in the community is a strong motivator.Keywords: dementia, dementia-friendly, municipality, support
Procedia PDF Downloads 178100 Surface Motion of Anisotropic Half Space Containing an Anisotropic Inclusion under SH Wave
Authors: Yuanda Ma, Zhiyong Zhang, Zailin Yang, Guanxixi Jiang
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Anisotropy is very common in underground media, such as rock, sand, and soil. Hence, the dynamic response of anisotropy medium under elastic waves is significantly different from the isotropic one. Moreover, underground heterogeneities and structures, such as pipelines, cylinders, or tunnels, are usually made by composite materials, leading to the anisotropy of these heterogeneities and structures. Both the anisotropy of the underground medium and the heterogeneities have an effect on the surface motion of the ground. Aiming at providing theoretical references for earthquake engineering and seismology, the surface motion of anisotropic half-space with a cylindrical anisotropic inclusion embedded under the SH wave is investigated in this work. Considering the anisotropy of the underground medium, the governing equation with three elastic parameters of SH wave propagation is introduced. Then, based on the complex function method and multipolar coordinates system, the governing equation in the complex plane is obtained. With the help of a pair of transformation, the governing equation is transformed into a standard form. By means of the same methods, the governing equation of SH wave propagation in the cylindrical inclusion with another three elastic parameters is normalized as well. Subsequently, the scattering wave in the half-space and the standing wave in the inclusion is deduced. Different incident wave angle and anisotropy are considered to obtain the reflected wave. Then the unknown coefficients in scattering wave and standing wave are solved by utilizing the continuous condition at the boundary of the inclusion. Through truncating finite terms of the scattering wave and standing wave, the equation of boundary conditions can be calculated by programs. After verifying the convergence and the precision of the calculation, the validity of the calculation is verified by degrading the model of the problem as well. Some parameters which influence the surface displacement of the half-space is considered: dimensionless wave number, dimensionless depth of the inclusion, anisotropic parameters, wave number ratio, shear modulus ratio. Finally, surface displacement amplitude of the half space with different parameters is calculated and discussed.Keywords: anisotropy, complex function method, sh wave, surface displacement amplitude
Procedia PDF Downloads 11999 Organ Dose Calculator for Fetus Undergoing Computed Tomography
Authors: Choonsik Lee, Les Folio
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Pregnant patients may undergo CT in emergencies unrelated with pregnancy, and potential risk to the developing fetus is of concern. It is critical to accurately estimate fetal organ doses in CT scans. We developed a fetal organ dose calculation tool using pregnancy-specific computational phantoms combined with Monte Carlo radiation transport techniques. We adopted a series of pregnancy computational phantoms developed at the University of Florida at the gestational ages of 8, 10, 15, 20, 25, 30, 35, and 38 weeks (Maynard et al. 2011). More than 30 organs and tissues and 20 skeletal sites are defined in each fetus model. We calculated fetal organ dose-normalized by CTDIvol to derive organ dose conversion coefficients (mGy/mGy) for the eight fetuses for consequential slice locations ranging from the top to the bottom of the pregnancy phantoms with 1 cm slice thickness. Organ dose from helical scans was approximated by the summation of doses from multiple axial slices included in the given scan range of interest. We then compared dose conversion coefficients for major fetal organs in the abdominal-pelvis CT scan of pregnancy phantoms with the uterine dose of a non-pregnant adult female computational phantom. A comprehensive library of organ conversion coefficients was established for the eight developing fetuses undergoing CT. They were implemented into an in-house graphical user interface-based computer program for convenient estimation of fetal organ doses by inputting CT technical parameters as well as the age of the fetus. We found that the esophagus received the least dose, whereas the kidneys received the greatest dose in all fetuses in AP scans of the pregnancy phantoms. We also found that when the uterine dose of a non-pregnant adult female phantom is used as a surrogate for fetal organ doses, root-mean-square-error ranged from 0.08 mGy (8 weeks) to 0.38 mGy (38 weeks). The uterine dose was up to 1.7-fold greater than the esophagus dose of the 38-week fetus model. The calculation tool should be useful in cases requiring fetal organ dose in emergency CT scans as well as patient dose monitoring.Keywords: computed tomography, fetal dose, pregnant women, radiation dose
Procedia PDF Downloads 14098 A Normalized Non-Stationary Wavelet Based Analysis Approach for a Computer Assisted Classification of Laryngoscopic High-Speed Video Recordings
Authors: Mona K. Fehling, Jakob Unger, Dietmar J. Hecker, Bernhard Schick, Joerg Lohscheller
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Voice disorders origin from disturbances of the vibration patterns of the two vocal folds located within the human larynx. Consequently, the visual examination of vocal fold vibrations is an integral part within the clinical diagnostic process. For an objective analysis of the vocal fold vibration patterns, the two-dimensional vocal fold dynamics are captured during sustained phonation using an endoscopic high-speed camera. In this work, we present an approach allowing a fully automatic analysis of the high-speed video data including a computerized classification of healthy and pathological voices. The approach bases on a wavelet-based analysis of so-called phonovibrograms (PVG), which are extracted from the high-speed videos and comprise the entire two-dimensional vibration pattern of each vocal fold individually. Using a principal component analysis (PCA) strategy a low-dimensional feature set is computed from each phonovibrogram. From the PCA-space clinically relevant measures can be derived that quantify objectively vibration abnormalities. In the first part of the work it will be shown that, using a machine learning approach, the derived measures are suitable to distinguish automatically between healthy and pathological voices. Within the approach the formation of the PCA-space and consequently the extracted quantitative measures depend on the clinical data, which were used to compute the principle components. Therefore, in the second part of the work we proposed a strategy to achieve a normalization of the PCA-space by registering the PCA-space to a coordinate system using a set of synthetically generated vibration patterns. The results show that owing to the normalization step potential ambiguousness of the parameter space can be eliminated. The normalization further allows a direct comparison of research results, which bases on PCA-spaces obtained from different clinical subjects.Keywords: Wavelet-based analysis, Multiscale product, normalization, computer assisted classification, high-speed laryngoscopy, vocal fold analysis, phonovibrogram
Procedia PDF Downloads 26597 The MicroRNA-2110 Suppressed Cell Proliferation and Migration Capacity in Hepatocellular Carcinoma Cells
Authors: Pelin Balcik Ercin
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Introduction: ZEB transcription factor family member ZEB2, has a role in epithelial to mesenchymal transition during development and metastasis. The altered circulating extracellular miRNAs expression is observed in diseases, and extracellular miRNAs have an important role in cancer cell microenvironment. In ChIP-Seq study, the expression of miR-2110 was found to be regulated by ZEB2. In this study, the effects of miR2110 on cell proliferation and migration of hepatocellular carcinoma (HCC) cells were examined. Material and Methods: SNU398 cells transfected with mimic miR2110 (20nM) (HMI0375, Sigma-Aldrich) and negative control miR (HMC0002, Sigma-Aldrich). MicroRNA isolation was accomplished with miRVANA isolation kit according to manufacturer instructions. cDNA synthesis was performed expression, respectively, and calibrated with Ct of controls. The real-time quantitative PCR (RT-qPCR) reaction was performed using the TaqMan Fast Advanced Master Mix (Thermo Sci.). Ct values of miR2110 were normalized to miR-186-5p and miR16-5p for the intracellular gene. Cell proliferation analysis was analyzed with the xCELLigence RTCA System. Wound healing assay was analyzed with the ImageJ program and relative fold change calculated. Results: The mimic-miR-2110 transfected SNU398 cells nearly nine-fold (log2) more miR-2110 expressed compared to negative control transfected cells. The mimic-miR-2110 transfected HCC cell proliferation significantly inhibited compared to the negative control cells. Furthermore, miR-2110-SNU398 cell migration capacity was relatively four-fold decreased compared to negative control-miR-SNU398 cells. Conclusion: Our results suggest the miR-2110 inhibited cell proliferation and also miR-2110 negatively affect cell migration compared to control groups in HCC cells. These data suggest the complexity of microRNA EMT transcription factors regulation. These initial results are pointed out the predictive biomarker capacity of miR-2110 in HCC.Keywords: epithelial to mesenchymal transition, EMT, hepatocellular carcinoma cells, micro-RNA-2110, ZEB2
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