Search results for: joint probability

Authors: Farid Khosravikia, Patricia Clayton

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The main objective of this work is to evaluate the advantages and disadvantages of various machine learning techniques in two key steps of seismic hazard and risk assessment of different types of structures. The first step is the development of ground-motion models, which are used for forecasting ground-motion intensity measures (IM) given source characteristics, source-to-site distance, and local site condition for future events. IMs such as peak ground acceleration and velocity (PGA and PGV, respectively) as well as 5% damped elastic pseudospectral accelerations at different periods (PSA), are indicators of the strength of shaking at the ground surface. Typically, linear regression-based models, with pre-defined equations and coefficients, are used in ground motion prediction. However, due to the restrictions of the linear regression methods, such models may not capture more complex nonlinear behaviors that exist in the data. Thus, this study comparatively investigates potential benefits from employing other machine learning techniques as statistical method in ground motion prediction such as Artificial Neural Network, Random Forest, and Support Vector Machine. The results indicate the algorithms satisfy some physically sound characteristics such as magnitude scaling distance dependency without requiring pre-defined equations or coefficients. Moreover, it is shown that, when sufficient data is available, all the alternative algorithms tend to provide more accurate estimates compared to the conventional linear regression-based method, and particularly, Random Forest outperforms the other algorithms. However, the conventional method is a better tool when limited data is available. Second, it is investigated how machine learning techniques could be beneficial for developing probabilistic seismic demand models (PSDMs), which provide the relationship between the structural demand responses (e.g., component deformations, accelerations, internal forces, etc.) and the ground motion IMs. In the risk framework, such models are used to develop fragility curves estimating exceeding probability of damage for pre-defined limit states, and therefore, control the reliability of the predictions in the risk assessment. In this study, machine learning algorithms like artificial neural network, random forest, and support vector machine are adopted and trained on the demand parameters to derive PSDMs for them. It is observed that such models can provide more accurate estimates of prediction in relatively shorter about of time compared to conventional methods. Moreover, they can be used for sensitivity analysis of fragility curves with respect to many modeling parameters without necessarily requiring more intense numerical response-history analysis.

Keywords: artificial neural network, machine learning, random forest, seismic risk analysis, seismic hazard analysis, support vector machine

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Authors: Mohamed Hendawy Mousa, Warda Youssef Mohamed Morsy

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Background: Sepsis is a major cause of mortality and morbidity in trauma patients. Body mass index as an indicator of nutritional status was reported as a predictor of injury pattern and complications among critically ill injured patients. Aim: The aim of this study is to investigate the relationship between body mass index and the development of sepsis, systemic inflammatory response syndrome among adult trauma patients at emergency hospital - Cairo University. Research design: Descriptive correlational research design was utilized in the current study. Research questions: Q1. What is the body mass index profile of adult trauma patients admitted to the emergency hospital at Cairo University over a period of 6 months?, Q2. What is the frequency of systemic inflammatory response syndrome and sepsis among adult trauma patients admitted to the emergency hospital at Cairo University over a period of 6 months?, and Q3. What is the relationship between the development of sepsis, systemic inflammatory response syndrome and body mass index among adult trauma patients admitted to the emergency hospital at Cairo University over a period of 6 months?. Sample: A purposive sample of 52 adult male and female trauma patients with revised trauma score 10 to 12. Setting: The Emergency Hospital affiliated to Cairo University. Tools: Four tools were utilized to collect data pertinent to the study: Socio demographic and medical data tool, Systemic inflammatory response syndrome assessment tool, Revised Trauma Score tool, and Sequential organ failure assessment tool. Results: The current study revealed that, (61.5 %) of the studied subjects had normal body mass index, (25 %) were overweight, and (13.5 %) were underweight. 84.6% of the studied subjects had systemic inflammatory response syndrome and 92.3% were suffering from mild sepsis. No significant statistical relationship was found between body mass index and occurrence of Systemic inflammatory response syndrome (2= 2.89 & P = 0.23). However, Sequential organ failure assessment scores were affected significantly by body mass index was found mean of initial and last Sequential organ failure assessment score for underweight, normal and obese where t= 7.24 at p = 0.000, t= 16.49 at p = 0.000 and t= 9.80 at p = 0.000 respectively. Conclusion: Underweight trauma patients showed significantly higher rate of developing sepsis as compared to patients with normal body weight and obese. Recommendations: based on finding of this study the following are recommended: replication of the study on a larger probability sample from different geographical locations in Egypt; Carrying out of further studies in order to assess the other risk factors influencing trauma outcome and incidence of its complications; Establishment of standardized guidelines for managing underweight traumatized patients with sepsis.

Keywords: body mass index, sepsis, systemic inflammatory response syndrome, adult trauma

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Authors: Ali Ahmed Ali Al-Juboori, H. Zhu, D. Wexler, H. Li, C. Lu, J. McLeod, S. Pannila, J. Barnes

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A number of studies have focused on the formation mechanics of white etching layer and its origin in the railway operation. Until recently, the following hypotheses consider the precise mechanics of WELs formation: (i) WELs are the result of thermal process caused by wheel slip; (ii) WELs are mechanically induced by severe plastic deformation; (iii) WELs are caused by a combination of thermo-mechanical process. The mechanisms discussed above lead to occurrence of white etching layers on the area of wheel and rail contact. This is because the contact patch which is the active point of the wheel on the rail is exposed to highest shear stresses which result in localised severe plastic deformation; and highest rate of heat caused by wheel slipe during excessive traction or braking effort. However, if the WELs are not on the running band area, it would suggest that there is another cause of WELs formation. In railway system, particularly electrified railway, arcing phenomenon has been occurring more often and regularly on the rails. In electrified railway, the current is delivered to the train traction motor via contact wires and then returned to the station via the contact between the wheel and the rail. If the contact between the wheel and the rail is temporarily losing, due to dynamic vibration, entrapped dirt or water, lubricant effect or oxidation occurrences, high current can jump through the gap and results in arcing. The other resources of arcing also include the wheel passage the insulated joint and lightning on a train during bad weather. During the arcing, an extensive heat is generated and speared over a large area of top surface of rail. Thus, arcing is considered another heat source in the rail head (rather than wheel slipe) that results in microstructural changes and white etching layer formation. A head hardened (HH) rail steel, cut from a curved rail truck was used for the investigation. Samples were sectioned from a depth of 10 mm below the rail surface, where the material is considered to be still within the hardened layer but away from any microstructural changes on the top surface layer caused by train passage. These samples were subjected to electrical discharges by using Gas Tungsten Arc Welding (GTAW) machine. The arc current was controlled and moved along the samples surface in the direction of travel, as indicated by an arrow. Five different conditions were applied on the surface of the samples. Samples containing pre-existed WELs, taken from ex-service rail surface, were also considered in this study for comparison. Both simulated and ex-serviced WELs were characterised by advanced methods including SEM, TEM, TKD, EDS, XRD. Samples for TEM and TKFD were prepared by Focused Ion Beam (FIB) milling. The results showed that both simulated WELs by electrical arcing and ex-service WEL comprise similar microstructure. Brown etching layer was found with WELs and likely induced by a concurrent tempering process. This study provided a clear understanding of new formation mechanics of WELs which contributes to track maintenance procedure.

Keywords: white etching layer, arcing, brown etching layer, material characterisation

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Authors: Ning Chang, Zelong Yuan, Yunpeng Wang, Jianchun Wang

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Large eddy simulation (LES) has been extensively used in the investigation of turbulence. LES calculates the grid-resolved large-scale motions and leaves small scales modeled by sublfilterscale (SFS) models. Among the existing SFS models, the deconvolution model has been used successfully in the LES of the engineering flows and geophysical flows. Despite the wide application of deconvolution models, the effects of subfilter scale dynamics and filter anisotropy on the accuracy of SFS modeling have not been investigated in depth. The results of LES are highly sensitive to the selection of filters and the anisotropy of the grid, which has been overlooked in previous research. In the current study, two critical aspects of LES are investigated. Firstly, we analyze the influence of sub-filter scale (SFS) dynamics on the accuracy of direct deconvolution models (DDM) at varying filter-to-grid ratios (FGR) in isotropic turbulence. An array of invertible filters are employed, encompassing Gaussian, Helmholtz I and II, Butterworth, Chebyshev I and II, Cauchy, Pao, and rapidly decaying filters. The significance of FGR becomes evident, as it acts as a pivotal factor in error control for precise SFS stress prediction. When FGR is set to 1, the DDM models cannot accurately reconstruct the SFS stress due to the insufficient resolution of SFS dynamics. Notably, prediction capabilities are enhanced at an FGR of 2, resulting in accurate SFS stress reconstruction, except for cases involving Helmholtz I and II filters. A remarkable precision close to 100% is achieved at an FGR of 4 for all DDM models. Additionally, the further exploration extends to the filter anisotropy to address its impact on the SFS dynamics and LES accuracy. By employing dynamic Smagorinsky model (DSM), dynamic mixed model (DMM), and direct deconvolution model (DDM) with the anisotropic filter, aspect ratios (AR) ranging from 1 to 16 in LES filters are evaluated. The findings highlight the DDM's proficiency in accurately predicting SFS stresses under highly anisotropic filtering conditions. High correlation coefficients exceeding 90% are observed in the a priori study for the DDM's reconstructed SFS stresses, surpassing those of the DSM and DMM models. However, these correlations tend to decrease as lter anisotropy increases. In the a posteriori studies, the DDM model consistently outperforms the DSM and DMM models across various turbulence statistics, encompassing velocity spectra, probability density functions related to vorticity, SFS energy flux, velocity increments, strain-rate tensors, and SFS stress. It is observed that as filter anisotropy intensify, the results of DSM and DMM become worse, while the DDM continues to deliver satisfactory results across all filter-anisotropy scenarios. The findings emphasize the DDM framework's potential as a valuable tool for advancing the development of sophisticated SFS models for LES of turbulence.

Keywords: deconvolution model, large eddy simulation, subfilter scale modeling, turbulence

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Authors: Elias Jemal Abdella

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The Blue Nile River is an important shared resource of Ethiopia, Sudan and also, because it is the major contributor of water to the main Nile River, Egypt. Despite the potential benefits of regional cooperation and integrated joint basin management, all three countries continue to pursue unilateral plans for development. Besides, there is great uncertainty about the likely impacts of climate change in water availability for existing as well as proposed irrigation and hydropower projects in the Blue Nile Basin. The main objective of this study is to quantitatively assess the impact of climate change on the hydrological regime of the upper Blue Nile basin, western Ethiopia. Three models were combined, a dynamic Coordinated Regional Climate Downscaling Experiment (CORDEX) regional climate model (RCM) that is used to determine climate projections for the Upper Blue Nile basin for Representative Concentration Pathways (RCPs) 4.5 and 8.5 greenhouse gas emissions scenarios for the period 2021-2050. The outputs generated from multimodel ensemble of four (4) CORDEX-RCMs (i.e., rainfall and temperature) were used as input to a Soil and Water Assessment Tool (SWAT) hydrological model which was setup, calibrated and validated with observed climate and hydrological data. The outputs from the SWAT model (i.e., projections in river flow) were used as input to a Water Evaluation and Planning (WEAP) water resources model which was used to determine the water resources implications of the changes in climate. The WEAP model was set-up to simulate three development scenarios. Current Development scenario was the existing water resource development situation, Medium-term Development scenario was planned water resource development that is expected to be commissioned (i.e. before 2025) and Long-term full Development scenario were all planned water resource development likely to be commissioned (i.e. before 2050). The projected change of mean annual temperature for period (2021 – 2050) in most of the basin are warmer than the baseline (1982 -2005) average in the range of 1 to 1.4oC, implying that an increase in evapotranspiration loss. Subbasins which already distressed from drought may endure to face even greater challenges in the future. Projected mean annual precipitation varies from subbasin to subbasin; in the Eastern, North Eastern and South western highland of the basin a likely increase of mean annual precipitation up to 7% whereas in the western lowland part of the basin mean annual precipitation projected to decrease by 3%. The water use simulation indicates that currently irrigation demand in the basin is 1.29 Bm3y-1 for 122,765 ha of irrigation area. By 2025, with new schemes being developed, irrigation demand is estimated to increase to 2.5 Bm3y-1 for 277,779 ha. By 2050, irrigation demand in the basin is estimated to increase to 3.4 Bm3y-1 for 372,779 ha. The hydropower generation simulation indicates that 98 % of hydroelectricity potential could be produced if all planned dams are constructed.

Keywords: Blue Nile River, climate change, hydropower, SWAT, WEAP

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Authors: Parichehr Sharifi, Konrad Reschke, Hans-Liudger Dienel

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Psychological intervention generally targets changes in attitudes and behavior. Working with DUIs is part of traffic psychologists’ work. The primary goal of this field is to reduce the probability of re-conspicuous of the delinquent driver. One of these measurements in Germany is IFT courses for DUI s. The IFT course was designed by the Institute for Therapy Research. Participants are drivers who have fallen several times or once with a blood alcohol concentration of 1.6 per mill and who have completed a medical-psychological assessment (MPU) with the result of the course recommendation. The course covers four sessions of 3.5 hours each (1 hour / 60 m) and in a period of 3 to 4 weeks in the group discussion. This work analyzes interventions for the rehabilitation of DUI (Drunk Drivers offenders) offenders in groups under the aspect of activating psychological resources. From the aspect of sustainability, they should also have long-term consequences for the maintenance of unproblematic driving behavior in terms of the activation of resources. It is also addressing a selected consistency-theory-based intervention effect, activating psychological resources. So far, this has only been considered in the psychotherapeutic field but never in the field of traffic psychology. The methodology of this survey is one qualitative and three quantitative. In four sub-studies, it will be examined which measurements can determine the resources and how traffic psychological interventions can strengthen resources. The results of the studies have the following implications for traffic psychology research and practice: (1) In the field of traffic psychology intervention for the restoration of driving fitness, it can be stated that aspects of resource activation in this work have been investigated for the first time by qualitative and quantitative methods. (2) The resource activation could be confirmed based on the determined results as an effective factor of traffic psychological intervention. (3) Two sub-studies show a range of resources and resource activation options that must be given greater emphasis in traffic psychology interventions: - Social resource activation - improvement of the life skills of participants - Reactivation of existing social support options - Re-experiencing self-esteem, self-assurance, and acceptance of traffic-related behaviors. (4) In revising the IFT-§70 course, as well as other courses on recreating aptitude for DUI, new traffic-specific resource-enabling interventions against alcohol abuse should be developed to further enhance the courses through motivational, cognitive, and behavioral effects of resource activation, Resource-activating interventions can not only be integrated into behavioral group interventions but can also be applied in psychodynamic, psychodynamic (individual psychological) and other contexts of individual traffic psychology. The results are indicative but clearly show that personal resources can be strengthened through traffic psychology interventions. In the research, practice, training, and further education of traffic psychology, the aspect of primary resource activation (Grawe, 1999), therefore, always deserves the greatest attention for the rehabilitation of DUIs and Traffic safety.

Keywords: traffic safety, psychological resources, activating of resources, intervention programs for alcohol offenders, empowerment

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Authors: Helen Bartsch, Markus Feldmann

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The dimensioning of steel structures subject to fatigue loads, such as wind turbines, bridges, masts and towers, crane runways and weirs or components in crane construction, is often dominated by fatigue verification. The fatigue details defined by the welded connections, such as butt or cruciform joints, longitudinal welds, welded-on or welded-in stiffeners, etc., are decisive. In Europe, the verification is usually carried out according to EN 1993-1-9 on a nominal stress basis. The basis is the detailed catalog, which specifies the fatigue strength of the various weld and construction details according to fatigue classes. Until now, a relation between fatigue classes and weld imperfection sizes is not included. Quality levels for imperfections in fusion-welded joints in steel, nickel, titanium and their alloys are regulated in EN ISO 5817, which, however, doesn’t contain direct correlations to fatigue resistances. The question arises whether some imperfections might be tolerable to a certain extent since they may be present in the test data used for detail classifications dating back decades ago. Although current standardization requires proof of satisfying limits of imperfection sizes, it would also be possible to tolerate welds with certain irregularities if these can be reliably quantified by non-destructive testing. Fabricators would be prepared to undertake carefully and sustained weld inspection in view of the significant economic consequences of such unfavorable fatigue classes. This paper presents investigations on the fatigue behavior of common welded details containing imperfections. In contrast to the common nominal stress concept, local fatigue concepts were used to consider the true stress increase, i.e., local stresses at the weld toe and root. The actual shape of a weld comprising imperfections, e.g., gaps or undercuts, can be incorporated into the fatigue evaluation, usually on a numerical basis. With the help of the effective notch stress concept, the fatigue resistance of detailed local weld shapes is assessed. Validated numerical models serve to investigate notch factors of fatigue details with different geometries. By utilizing parametrized ABAQUS routines, detailed numerical studies have been performed. Depending on the shape and size of different weld irregularities, fatigue classes can be defined. As well load-carrying welded details, such as the cruciform joint, as non-load carrying welded details, e.g., welded-on or welded-in stiffeners, are regarded. The investigated imperfections include, among others, undercuts, excessive convexity, incorrect weld toe, excessive asymmetry and insufficient or excessive throat thickness. Comparisons of the impact of different imperfections on the different types of fatigue details are made. Moreover, the influence of a combination of crucial weld imperfections on the fatigue resistance is analyzed. With regard to the trend of increasing efficiency in steel construction, the overall aim of the investigations is to include a more economical differentiation of fatigue details with regard to tolerance sizes. In the long term, the harmonization of design standards, execution standards and regulations of weld imperfections is intended.

Keywords: effective notch stress, fatigue, fatigue design, weld imperfections

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Authors: K. S. Vimal, D. Bodhini, K. Ramya, N. Lakshmipriya, R. M. Anjana, V. Sudha, J. A. Lovegrove, V. Mohan, V. Radha

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Gene-lifestyle interaction studies have been carried out in various populations. However, to date there are no studies in an Asian Indian population. Hence, we examined whether lifestyle factors such as diet and physical activity modify the association between fat mass and obesity–associated (FTO) gene variants and obesity and type 2 diabetes (T2D) in an Asian Indian population. We studied 734 unrelated T2D and 884 normal glucose-tolerant (NGT) participants randomly selected from the Chennai Urban Rural Epidemiology Study (CURES) in Southern India. Obesity was defined according to the World Health Organization Asia Pacific Guidelines (non-obese, BMI < 25 kg/m2; obese, BMI ≥ 25 kg/m2). Six single nucleotide polymorphisms (SNPs) in the FTO gene (rs9940128, rs7193144, rs8050136, rs918031, rs1588413 and rs11076023) identified from recent genome-wide association studies for T2D were genotyped by polymerase chain reaction-restriction fragment length polymorphism and direct sequencing. Dietary assessment was carried out using a validated food frequency questionnaire and physical activity was based upon the self-report. Interaction analyses were performed by including the interaction terms in the model. A joint likelihood ratio test of the main SNP effects and the SNP-diet/physical activity interaction effects was used in the linear regression analyses to maximize statistical power. Statistical analyses were performed using STATA version 13. There was a significant interaction between FTO SNP rs8050136 and carbohydrate energy percentage (Pinteraction=0.04) on obesity, where the ‘A’ allele carriers of the SNP rs8050136 had 2.46 times higher risk of obesity than those with ‘CC’ genotype (P=3.0x10-5) among individuals in the highest tertile of carbohydrate energy percentage. Furthermore, among those who had lower levels of physical activity, the ‘A’ allele carriers of the SNP rs8050136 had 1.89 times higher risk of obesity than those with ‘CC’ genotype (P=4.0x10-5). We also found a borderline interaction between SNP rs11076023 and carbohydrate energy percentage (Pinteraction=0.08) on T2D, where the ‘A’ allele carriers in the highest tertile of carbohydrate energy percentage, had 1.57 times higher risk of T2D than those with ‘TT’ genotype (P=0.002). There was also a significant interaction between SNP rs11076023 and physical activity (Pinteraction=0.03) on T2D. No further significant interactions between SNPs and macronutrient intake or physical activity on obesity and T2D were observed. In conclusion, this is the first study to provide evidence for a gene-diet and gene-physical activity interaction on obesity and T2D in an Asian Indian population. These findings suggest that the association between FTO gene variants and obesity and T2D is influenced by carbohydrate intake and physical activity levels. Greater understanding of how FTO gene influences obesity and T2D through dietary and exercise interventions will advance the development of behavioral intervention and personalised lifestyle strategies predicted to reduce the development of metabolic diseases in ‘A’ allele carriers of both SNPs in this Asian Indian population.

Keywords: dietary intake, FTO, obesity, physical activity, type 2 diabetes, Asian Indian.

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Authors: V. Schmidt, L. Janovák, N. Wiegand, B. Patczai, K. Turzó

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Large bone defects are not able to heal spontaneously. Bioactive glasses seem to be appropriate (bio)materials for bone reconstruction. Bioactive glasses are osteoconductive and osteoinductive, therefore, play a useful role in bony regeneration and repair. Because of their not optimal mechanical properties (e.g., brittleness, low bending strength, and fracture toughness), their applications are limited. Bioactive glass can be used as a coating material applied on metal surfaces. In this way -when using them as implants- the excellent mechanical properties of metals and the biocompatibility and bioactivity of glasses will be utilized. Furthermore, ion release effects of bioactive glasses regarding osteogenic and angiogenic responses have been shown. Silicate bioactive glasses (45S5 Bioglass) induce the release and exchange of soluble Si, Ca, P, and Na ions on the material surface. This will lead to special cellular responses inducing bone formation, which is favorable in the biointegration of the orthopedic prosthesis. The incorporation of other additional elements in the silicate network such as fluorine, magnesium, iron, silver, potassium, or zinc has been shown, as the local delivery of these ions is able to enhance specific cell functions. Although hip and knee prostheses present a high success rate, bacterial infections -mainly implant associated- are serious and frequent complications. Infection can also develop after implantation of hip prostheses, the elimination of which means more surgeries for the patient and additional costs for the clinic. Prosthesis-related infection is a severe complication of orthopedic surgery, which often causes prolonged illness, pain, and functional loss. While international efforts are made to reduce the risk of these infections, orthopedic surgical infections (SSIs) continue to occur in high numbers. It is currently estimated that up to 2.5% of primary hip and knee surgeries and up to 20% of revision arthroplasties are complicated by periprosthetic joint infection (PJIs). According to some authors, these numbers are underestimated, and they are also increasing. Staphylococcus aureus is the leading cause of both SSIs and PJIs, and the prevalence of methicillin-resistant S. aureus (MRSA) is on the rise, particularly in the United States. These deep infections lead to implant removal and consequently increase morbidity and mortality. The study targets this clinical problem using our experience so far with the Ag-doped polymer coatings on Titanium implants. Non-modified or modified (e.g., doped with antibacterial agents, like Ag) bioactive glasses could play a role in the prevention of infections or the therapy of infected tissues. Bioactive glasses have excellent biocompatibility, proved by in vitro cell culture studies of human osteoblast-like MG-63 cells. Ag-doped bioactive glass-scaffold has a good antibacterial ability against Escherichia coli and other bacteria. It may be concluded that these scaffolds have great potential in the prevention and therapy of implant-associated bone infection.

Keywords: antibacterial agents, bioactive glass, hip and knee prosthesis, medical implants

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Authors: Lia Marchi, Ernesto Antonini

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The impact of industrial sites on people’s living environment both involves detrimental effects on the ecosystem and perceptual-aesthetic interferences with the scenery. These, in turn, affect the economic and social value of the landscape, as well as the wellbeing of workers and local communities. Given the diffusion of the phenomenon and the relevance of its effects, it emerges the need for a joint approach to assess and thus mitigate the impact of factories on the landscape –being this latest assumed as the result of the action and interaction of natural and human factors. However, the impact assessment tools suitable for the purpose are quite heterogeneous and mostly monodisciplinary. On the one hand, green building rating systems (GBRSs) are increasingly used to evaluate the performance of manufacturing sites, mainly by quantitative indicators focused on environmental issues. On the other hand, methods to detect the visual and social impact of factories on the landscape are gradually emerging in the literature, but they generally adopt only qualitative gauges. The research addresses the integration of the environmental impact assessment and the perceptual-aesthetic interferences of factories on the landscape. The GBRSs model is assumed as a reference since it is adequate to simultaneously investigate different topics which affect sustainability, returning a global score. A critical analysis of GBRSs relevant to industrial facilities has led to select the U.S. GBC LEED protocol as the most suitable to the scope. A revision of LEED v4 Building Design+Construction has then been provided by including specific indicators to measure the interferences of manufacturing sites with the perceptual-aesthetic and social aspects of the territory. To this end, a new impact category was defined, namely ‘PA - Perceptual-aesthetic aspects’, comprising eight new credits which are specifically designed to assess how much the buildings are in harmony with their surroundings: these investigate, for example the morphological and chromatic harmonization of the facility with the scenery or the site receptiveness and attractiveness. The credits weighting table was consequently revised, according to the LEED points allocation system. As all LEED credits, each new PA credit is thoroughly described in a sheet setting its aim, requirements, and the available options to gauge the interference and get a score. Lastly, each credit is related to mitigation tactics, which are drawn from a catalogue of exemplary case studies, it also developed by the research. The result is a modified LEED scheme which includes compatibility with the landscape within the sustainability assessment of the industrial sites. The whole system consists of 10 evaluation categories, which contain in total 62 credits. Lastly, a test of the tool on an Italian factory was performed, allowing the comparison of three mitigation scenarios with increasing compatibility level. The study proposes a holistic and viable approach to the environmental impact assessment of factories by a tool which integrates the multiple involved aspects within a worldwide recognized rating protocol.

Keywords: environmental impact, GBRS, landscape, LEED, sustainable factory

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Authors: Mylena McCoggle, Shyra Wilson, Andrea Rivera, Rocio Alba-Flores

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This work introduces the use of EMGs (electromyography) from muscle sensors to develop an Artificial Neural Network (ANN) for pattern recognition to control a small unmanned aerial vehicle. The objective of this endeavor exhibits interfacing drone applications beyond manual control directly. MyoWare Muscle sensor contains three EMG electrodes (dual and single type) used to collect signals from the posterior (extensor) and anterior (flexor) forearm and the bicep. Collection of raw voltages from each sensor were connected to an Arduino Uno and a data processing algorithm was developed with the purpose of interpreting the voltage signals given when performing flexing, resting, and motion of the arm. Each sensor collected eight values over a two-second period for the duration of one minute, per assessment. During each two-second interval, the movements were alternating between a resting reference class and an active motion class, resulting in controlling the motion of the drone with left and right movements. This paper further investigated adding up to three sensors to differentiate between hand gestures to control the principal motions of the drone (left, right, up, and land). The hand gestures chosen to execute these movements were: a resting position, a thumbs up, a hand swipe right motion, and a flexing position. The MATLAB software was utilized to collect, process, and analyze the signals from the sensors. The protocol (machine learning tool) was used to classify the hand gestures. To generate the input vector to the ANN, the mean, root means squared, and standard deviation was processed for every two-second interval of the hand gestures. The neuromuscular information was then trained using an artificial neural network with one hidden layer of 10 neurons to categorize the four targets, one for each hand gesture. Once the machine learning training was completed, the resulting network interpreted the processed inputs and returned the probabilities of each class. Based on the resultant probability of the application process, once an output was greater or equal to 80% of matching a specific target class, the drone would perform the motion expected. Afterward, each movement was sent from the computer to the drone through a Wi-Fi network connection. These procedures have been successfully tested and integrated into trial flights, where the drone has responded successfully in real-time to predefined command inputs with the machine learning algorithm through the MyoWare sensor interface. The full paper will describe in detail the database of the hand gestures, the details of the ANN architecture, and confusion matrices results.

Keywords: artificial neural network, biosensors, electromyography, machine learning, MyoWare muscle sensors, Arduino

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Authors: Tesfaldet Mekonnen Estifanos, Chen Hui, Afewerki Weldezgi

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Background: Intimate partner violence (hereafter IPV) is a major global public health challenge that tortures and disables women in the place where they are ought to be most secure within their own families. The fact that the family unit is commonly viewed as a private circle, violent acts towards women remains undermined. There are limited research and knowledge about the influencing factors linked to IPV in Sierra Leone. This study, therefore, estimates the prevalence rate and the predicting factors associated with IPV. Methods: Data were taken from Sierra-Leone Demographic and Health Survey (SDHS, 2013): the first in its form to incorporate information on domestic violence. Multistage cluster sampling research design was used, and information was gathered by a standard questionnaire. A total of 5185 respondents selected were interviewed, out of whom 870 were never been in union, thus excluded. To analyze the two dependent variables: experience of IPV, ‘ever’ and 'last 12 months prior to the survey', a total of 4315 (currently or formerly married) and 4029 women (currently in union) were included respectively. These dependent variables were constructed from the three forms of violence namely physical, emotional and sexual. Data analysis was applied using SPSS version 23, comprising three-step process. First, descriptive statistics were used to show the frequency distribution of both the outcome and explanatory variables. Second, bivariate analysis adopting chi-square test was applied to assess the individual relationship between the outcome and explanatory variables. Third, multivariate logistic regression analysis was undertaken using hierarchical modeling strategy to identify the influence of the explanatory variables on the outcome variables. Odds ratio (OR) and 95% confidence interval (CI) were utilized to examine the association of the variables considering p-values less than 0.05 statistically significant. Results: The prevalence of lifetime IPV among ever married women was 48.4%, while 39.8% of those currently married experienced IPV in the previous year preceding the survey. Women having 1 to 4 and more than 5 number of ever born babies were almost certain to encounter lifetime IPV. However, women who own a property, and those who referenced 3-5 reasons for which wife-beating is acceptable were less probably to experience lifetime IPV. Attesting parental violence, partner’s dominant marital behavior, and women afraid of their partner were the variables related to both experience of IPV ‘ever’ and ‘the previous year prior to the survey’. Respondents who concur that wife-beating is sensible in certain situations and occupations under the professional category had diminished chances of revealing IPV in the year prior to the data collection. Conclusion: This study indicated that factors significantly correlated with IPV in Sierra-Leone are mostly linked with husband related factors specifically, marital controlling behaviors. Addressing IPV in Sierra-Leone requires joint efforts that target men raise awareness to address controlling behavior and empower security in affiliations.

Keywords: husband behavior, married women, partner violence, Sierra Leone

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Authors: Klaus Peter Scherer, Daniel Knöll, Constantin Rieder

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Problem and Purpose: Intelligent systems are available and helpful to support the human being decision process, especially when complex surgical eye interventions are necessary and must be performed. Normally, such a decision support system consists of a knowledge-based module, which is responsible for the real assistance power, given by an explanation and logical reasoning processes. The interview based acquisition and generation of the complex knowledge itself is very crucial, because there are different correlations between the complex parameters. So, in this project (semi)automated self-learning methods are researched and developed for an enhancement of the quality of such a decision support system. Methods: For ophthalmic data sets of real patients in a hospital, advanced data mining procedures seem to be very helpful. Especially subgroup analysis methods are developed, extended and used to analyze and find out the correlations and conditional dependencies between the structured patient data. After finding causal dependencies, a ranking must be performed for the generation of rule-based representations. For this, anonymous patient data are transformed into a special machine language format. The imported data are used as input for algorithms of conditioned probability methods to calculate the parameter distributions concerning a special given goal parameter. Results: In the field of knowledge discovery advanced methods and applications could be performed to produce operation and patient related correlations. So, new knowledge was generated by finding causal relations between the operational equipment, the medical instances and patient specific history by a dependency ranking process. After transformation in association rules logically based representations were available for the clinical experts to evaluate the new knowledge. The structured data sets take account of about 80 parameters as special characteristic features per patient. For different extended patient groups (100, 300, 500), as well one target value as well multi-target values were set for the subgroup analysis. So the newly generated hypotheses could be interpreted regarding the dependency or independency of patient number. Conclusions: The aim and the advantage of such a semi-automatically self-learning process are the extensions of the knowledge base by finding new parameter correlations. The discovered knowledge is transformed into association rules and serves as rule-based representation of the knowledge in the knowledge base. Even more, than one goal parameter of interest can be considered by the semi-automated learning process. With ranking procedures, the most strong premises and also conjunctive associated conditions can be found to conclude the interested goal parameter. So the knowledge, hidden in structured tables or lists can be extracted as rule-based representation. This is a real assistance power for the communication with the clinical experts.

Keywords: an expert system, knowledge-based support, ophthalmic decision support, self-learning methods

Procedia PDF Downloads 250

Authors: Fong-Zuo Lee, Jihn-Sung Lai, Yung-Bin Lin, Xiaoqin Liu, Kuo-Chun Chang, Zhi-Xian Yang, Wen-Dar Guo, Jian-Hao Hong

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In recent years, climate change is a major factor to increase rainfall intensity and extreme rainfall frequency. The increased rainfall intensity and extreme rainfall frequency will increase the probability of flash flood with abundant sediment transport in a river basin. The floods caused by heavy rainfall may cause damages to the bridge, embankment, hydraulic works, and the other disasters. Therefore, the foundation scouring of bridge pier, embankment and spur dike caused by floods has been a severe problem in the worldwide. This severe problem has happened in many East Asian countries such as Taiwan and Japan because of these areas are suffered in typhoons, earthquakes, and flood events every year. Results from the complex interaction between fluid flow patterns caused by hydraulic works and the sediment transportation leading to the formation of river morphology, it is extremely difficult to develop a reliable and durable sensor to measure river bed degradation and bridge pier scouring. Therefore, an innovative scour monitoring sensor using vibration-based Micro-Electro Mechanical Systems (MEMS) was developed. This vibration-based MEMS sensor was packaged inside a stainless sphere with the proper protection of the full-filled resin, which can measure free vibration signals to detect scouring/deposition processes at the bridge pier. In addition, a friendly operational system includes rainfall runoff model, one-dimensional and two-dimensional numerical model, and the applicability of sediment transport equation and local scour formulas of bridge pier are included in this research. The friendly operational system carries out the simulation results of flood events that includes the elevation changes of river bed erosion near the specified bridge pier and the erosion depth around bridge piers. In addition, the system is developed with easy operation and integrated interface, the system can supplies users to calibrate and verify numerical model and display simulation results through the interface comparing to the scour monitoring sensors. To achieve the forecast of the erosion depth of river bed and main bridge pier in the study area, the system also connects the rainfall forecast data from Taiwan Typhoon and Flood Research Institute. The results can be provided available information for the management unit of river and bridge engineering in advance.

Keywords: flash flood, river bed degradation, bridge pier scouring, a friendly operational system

Procedia PDF Downloads 188

Authors: Shotiros Protong

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The incidents of sudden landslides in Thailand during the past decade have occurred frequently and more severely. It is necessary to focus on the principal parameters used for analysis such as land cover land use, rainfall values, characteristic of soil and digital elevation model (DEM). The combination of intense rainfall and severe monsoons is increasing due to global climate change. Landslide occurrences rapidly increase during intense rainfall especially in the rainy season in Thailand which usually starts around mid-May and ends in the middle of October. The rain-triggered landslide hazard analysis is the focus of this research. The combination of geotechnical and hydrological data are used to determine permeability, conductivity, bedding orientation, overburden and presence of loose blocks. The regional landslide hazard mapping is developed using the Slope Stability Index SINMAP model supported on Arc GIS software version 10.1. Geological and land use data are used to define the probability of landslide occurrences in terms of geotechnical data. The geological data can indicate the shear strength and the angle of friction values for soils above given rock types, which leads to the general applicability of the approach for landslide hazard analysis. To address the research objectives, the methods are described in this study: setup and calibration of the SINMAP model, sensitivity of the SINMAP model, geotechnical laboratory, landslide assessment at present calibration and landslide assessment under future climate simulation scenario A2 and B2. In terms of hydrological data, the millimetres/twenty-four hours of average rainfall data are used to assess the rain triggered landslide hazard analysis in slope stability mapping. During 1954-2012 period, is used for the baseline of rainfall data at the present calibration. The climate change in Thailand, the future of climate scenarios are simulated by spatial and temporal scales. The precipitation impact is need to predict for the climate future, Statistical Downscaling Model (SDSM) version 4.2, is used to assess the simulation scenario of future change between latitude 16o 26’ and 18o 37’ north and between longitude 98o 52’ and 103o 05’ east by SDSM software. The research allows the mapping of risk parameters for landslide dynamics, and indicates the spatial and time trends of landslide occurrences. Thus, regional landslide hazard mapping under present-day climatic conditions from 1954 to 2012 and simulations of climate change based on GCM scenarios A2 and B2 from 2013 to 2099 related to the threshold rainfall values for the selected the study area in Uttaradit province in the northern part of Thailand. Finally, the landslide hazard mapping will be compared and shown by areas (km2 ) in both the present and the future under climate simulation scenarios A2 and B2 in Uttaradit province.

Keywords: landslide hazard, GIS, slope stability index (SINMAP), landslides, Thailand

Procedia PDF Downloads 552

Authors: Sayyed Mostafa Ahmadi, Neda Raeesi

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Background and Objectives: Cervical spondylosis is a common problem that affects the adult spine and is the most common cause of radiculopathy and myelopathy in older patients. Anterior discectomy and fusion is a well-known technique in degenerative cervical disc disease. However, one of the late undesirable complications is adjacent disc degeneration, which affects about 91% of patients in ten years. Many factors can be effective in causing this complication, but some are still debatable. Discovering these risk factors and eliminating them can improve the quality of life. Methods: This is a retrospective cohort study. All patients who underwent anterior discectomy and fusion surgery in the neurosurgery ward of Imam Khomeini Hospital between 2013 and 2016 were evaluated. Their demographic information was collected. All patients were visited and examined for radiculopathy, myelopathy, and muscular force. At the same visit, all patients were asked to have a facelift, and neck profile, as well as a neck MRI(General Tesla 3). Preoperative graphs were used to measure the diameter of the cervical canal(Pavlov ratio) and to evaluate sagittal alignment(Cobb Angle). Preoperative MRI of patients was reviewed for anterior and posterior longitudinal ligament calcification. Result: In this study, 57 patients were studied. The mean age of patients was 50.63 years, and 49.1% were male. Only 3.5% of patients had anterior and posterior longitudinal ligament calcification. Symptomatic ASD was observed in 26.6%. The X-rays and MRIs showed evidence of 80.7% radiological ASD. Among patients who underwent one-level surgery, 20% had symptomatic ASD, but among patients who underwent two-level surgery, the rate of ASD was 50%.In other words, the higher the number of surfaces that are operated and fused, the higher the probability of symptomatic ASD(P-value <0.05). The X-rays and MRIs showed 80.7% of radiological ASD. Among patients who underwent surgery at one level, 78% had radiological ASD, and this number was 92% among patients who underwent two-level surgery(P-value> 0.05). Demographic variables such as age, sex, height, weight, and BMI did not have a significant effect on the incidence of radiological ASD(P-value> 0.05), but sex and height were two influential factors on symptomatic ASD(P-value <0.05). Other related variables such as family history, smoking and exercise also have no significant effect(P-value> 0.05). Radiographic variables such as Pavlov ratio and sagittal alignment were also unaffected by the incidence of radiological and symptomatic ASD(P-value> 0.05). The number of surgical surfaces and the incidence of anterior and posterior longitudinal ligament calcification before surgery also had no statistically significant effect(P-value> 0.05). In the study of the ability of the neck to move in different directions, none of these variables are statistically significant in the two groups with radiological and symptomatic ASD and the non-affected group(P-value> 0.05). Conclusion: According to the findings of this study, this disease is considered to be a multifactorial disease. The incidence of radiological ASD is much higher than symptomatic ASD (80.7% vs. 26.3%) and sex, height and number of fused surfaces are the only factors influencing the incidence of symptomatic ASD and no variable influences radiological ASD.

Keywords: risk factors, anterior neck disectomy and fusion, adjucent segment degeneration, complication

Procedia PDF Downloads 53

Authors: Ivelise M. Strozberg, Lucas O. Vale, Maria V. V. Morais

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Expansive soils are characterized by their significant volumetric variations, tending to suffer an increase of this volume when added water in their voids and a decrease of volume when this water is removed. The parameters of resistance (especially the angle of friction, cohesion and specific weight) of expansive or non-expansive soils of the same field present differences, as found in laboratory tests. What is expected is that, through this research, demonstrate that this variation directly affects the results of the calculation of factors of safety for slope stability. The expansibility due to specific clay minerals such as montmorillonites and vermiculites is the most common form of expansion of soils or rocks, causing expansion pressures. These pressures can become an aggravating problem in regions across the globe that, when not previously studied, may present high risks to the enterprise, such as cracks, fissures, movements in structures, breaking of retaining walls, drilling of wells, among others. The study provides results based on analyzes carried out in the Slide 2018 software belonging to the Rocsience group, where the software is a two-dimensional equilibrium slope stability program that calculates the factor of safety or probability of failure of certain surfaces composed of soils or rocks (or both, depending on the situation), - through the methods of: Bishop simplified, Fellenius and Janbu corrected. This research compares the factors of safety of a homogeneous earthfill dam geometry, analysed for operation and end-of-construction situations, having a height of approximately 35 meters, with a slope of 1.5: 1 in the slope downstream and 2: 1 on the upstream slope. As the water level is 32.73m high and the water table is drawn automatically by the Slide program using the finite element method for the operating situation, considering two hypotheses for the use of materials - the first with soils with characteristics of expansion and the second with soils without expansibility. For this purpose, soil samples were collected from the region of São Bento do Una - Pernambuco, Brazil and taken to the soil mechanics laboratory to characterize and determine the percentage of expansibility. There were found 2 types of soils in that area: 1 site of expansive soils (8%) and another with non- expansive ones. Based on the results found, the analysis of the values of factors of safety indicated, both upstream and downstream slopes, the highest values were obtained in the case where there is no presence of materials with expansibility resulting, for one of the situations, values of 1.353 (Fellenius), 1,295 (Janbu corrected) and 1,409 (Bishop simplified). There is a considerable drop in safety factors in cases where soils are potentially expansive, resulting in values for the same situation of 0.859 (Fellenius), 0.809 (Janbu corrected) and 0.842 (Bishop simplified), in the case of higher expansibility (8 %). This shows that the expansibility is a determinant factor in the fall of resistance of soil, determined by the factors of cohesion and angle of friction.

Keywords: dam. slope. software. swelling soil

Procedia PDF Downloads 113

Authors: Iliuta Cumpanasu, Veronica Oana Cumpanasu

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This paper focuses on studying the conjunction between the new emerged theory of “Memory Effect” in Irregular Migration and Related Criminality and the notion of securitization, and its impact on border management, bringing about a scientific advancement in the field by identifying the patterns corresponding to the linkage of the two concepts, for the first time, and developing a theoretical explanation, with respect to the effects of the non-military threats on border security. Over recent years, irregular migration has experienced a significant increase worldwide. The U.N.'s refugee agency reports that the number of displaced people is at its highest ever - surpassing even post-World War II numbers when the world was struggling to come to terms with the most devastating event in history. This is also the fresh reality within the core studied coordinate, the Balkan Route of Irregular Migration, which starts from Asia and Africa and continues to Turkey, Greece, North Macedonia or Bulgaria, Serbia, and ends in Romania, where thousands of migrants find themselves in an irregular situation concerning their entry to the European Union, with its important consequences concerning the related criminality. The data from the past six years was collected by making use of semi-structured interviews with experts in the field of migration and desk research within some organisations involved in border security, pursuing the gathering of genuine insights from the aforementioned field, which was constantly addressed the existing literature and subsequently subjected to the mixed methods of analysis, including the use of the Vector Auto-Regression estimates model. Thereafter, the analysis of the data followed the processes and outcomes in Grounded Theory, and a new Substantive Theory emerged, explaining how the phenomena of irregular migration and cross-border criminality are the decisive impetus for implementing the concept of securitization in border management by using the proposed pattern. The findings of the study are therefore able to capture an area that has not yet benefitted from a comprehensive approach in the scientific community, such as the seasonality, stationarity, dynamics, predictions, or the pull and push factors in Irregular Migration, also highlighting how the recent ‘Pandemic’ interfered with border security. Therefore, the research uses an inductive revelatory theoretical approach which aims at offering a new theory in order to explain a phenomenon, triggering a practically handy contribution for the scientific community, research institutes or Academia and also usefulness to organizational practitioners in the field, among which UN, IOM, UNHCR, Frontex, Interpol, Europol, or national agencies specialized in border security. The scientific outcomes of this study were validated on June 30, 2021, when the author defended his dissertation for the European Joint Master’s in Strategic Border Management, a two years prestigious program supported by the European Commission and Frontex Agency and a Consortium of six European Universities and is currently one of the research objectives of his pending PhD research at the West University Timisoara.

Keywords: migration, border, security, memory effect

Procedia PDF Downloads 84

Authors: Roberto M. G. Velásquez, Jonas R. Gazoli, Nelson Ponce Jr, Valério L. Borges, Alessandro Sete, Fernanda M. C. Tomé, Julian D. Hunt, Heitor C. Lira, Cristiano L. de Souza, Fabio T. Bindemann, Wilmar Wounnsoscky

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Nowadays, society is working toward reducing energy losses and greenhouse gas emissions, as well as seeking clean energy sources, as a result of the constant increase in energy demand and emissions. Energy loss occurs in the gas pressure reduction stations at the delivery points in natural gas distribution systems (city gates). Installing pressure reduction turbines (PRT) parallel to the static reduction valves at the city gates enhances the energy efficiency of the system by recovering the enthalpy of the pressurized natural gas, obtaining in the pressure-lowering process shaft work and generating electrical power. Currently, the Brazilian natural gas transportation network has 9,409 km in extension, while the system has 16 national and 3 international natural gas processing plants, including more than 143 delivery points to final consumers. Thus, the potential of installing PRT in Brazil is 66 MW of power, which could yearly avoid the emission of 235,800 tons of CO2 and generate 333 GWh/year of electricity. On the other hand, an economic viability analysis of these energy efficiency projects is commonly carried out based on estimates of the project's cash flow obtained from several variables forecast. Usually, the cash flow analysis is performed using representative values of these variables, obtaining a deterministic set of financial indicators associated with the project. However, in most cases, these variables cannot be predicted with sufficient accuracy, resulting in the need to consider, to a greater or lesser degree, the risk associated with the calculated financial return. This paper presents an approach applied to the technical-economic viability analysis of PRTs projects that explicitly considers the uncertainties associated with the input parameters for the financial model, such as gas pressure at the delivery point, amount of energy generated by TRP, the future price of energy, among others, using sensitivity analysis techniques, scenario analysis, and Monte Carlo methods. In the latter case, estimates of several financial risk indicators, as well as their empirical probability distributions, can be obtained. This is a methodology for the financial risk analysis of PRT projects. The results of this paper allow a more accurate assessment of the potential PRT project's financial feasibility in Brazil. This methodology will be tested at the Cuiabá thermoelectric plant, located in the state of Mato Grosso, Brazil, and can be applied to study the potential in other countries.

Keywords: pressure reduction turbine, natural gas pressure drop station, energy efficiency, electricity generation, monte carlo methods

Procedia PDF Downloads 108

Authors: M. Bukowski, K. Kreissl

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Social and environmental pressures in our times bear threats that often cross-border in scale, such as climate change, poverty-driven migration, demographic change as well as socio-economic developments. One of the hot topics is prevailing in many societies across Europe and worldwide, concerns 'affordable housing' and poverty-driven international and domestic migration (including displacements through gentrification processes), focusing here on the urban and regional context. The right to adequate housing and shelter is one of the recognized in the Universal Declaration of Human rights and International Covenant on Economic, Social and Cultural Rights, and as such considered as a human right of the second generation. The decreasing supply of affordable housing, especially in urban areas, has reached dimensions that have led to an increasing 'housing crisis'. This crisis, which has even reached middle-income homes, has an even more devastating impact on low income and poor households raising poverty levels. Therefore, the understanding of the connection between housing and poverty is vital to integrate and support the different stakeholders in order to tackle poverty. When it comes to issues of inequalities and poverty within the SDG framework, multi-faceted stakeholders with different claims, distribution of resources and interactions with other development goals (spill-over and trade-offs) account for a highly complex context. To contribute to a sustainable and fair society and hence to support the UN Sustainable Development Goals, the University of Salzburg participates in the Austrian-wide universities' network 'UniNEtZ'. Our joint target is to develop an options report for the Austrian Government regarding the seventeen SDGs, so far hosted by 18 Austrian universities. In this vein, the University of Salzburg; i.e., the Centre for Ethics and Poverty Research, the departments of Geography and Geology and the Department of Sociology and Political Science are focusing on the SDG 1 (No Poverty) and SDG 10 (Reduced Inequalities). Our target and research focus is to assess and evaluate the status of SDG 1 and 10 in Austria, to find possible solutions and to support stakeholders' integration. We aim at generating and deducing appropriate options as scientific support, from interdisciplinary research studies to 'Sustainability Developing Goals and their Targets' in action. For this reason, and to deal with the complexity of the Agenda 2030, we have developed a special Model for Inequalities and Poverty Assessment (IPAM). Through the example of 'affordable housing' we provide insight into the situation focusing on sustainable outcomes, including ethical and justice perceptions. The IPAM has proven to be a helpful tool in detecting the different imponderables on the Agenda 2030, assessing the situation, showing gaps and options for ethical SDG actions combining different SDG targets. Supported by expert and expert group interviews, this assessment allows different stakeholders to overview a complex and dynamic SDG challenge (here housing) which is necessary to be involved in an action finding process.

Keywords: affordable housing, inequality, poverty, sustainable development goals

Procedia PDF Downloads 99

Authors: Binder Hans

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Cancer is no longer seen as solely a genetic disease where genetic defects such as mutations and copy number variations affect gene regulation and eventually lead to aberrant cell functioning which can be monitored by transcriptome analysis. It has become obvious that epigenetic alterations represent a further important layer of (de-)regulation of gene activity. For example, aberrant DNA methylation is a hallmark of many cancer types, and methylation patterns were successfully used to subtype cancer heterogeneity. Hence, unraveling the interplay between different omics levels such as genome, transcriptome and epigenome is inevitable for a mechanistic understanding of molecular deregulation causing complex diseases such as cancer. This objective requires powerful downstream integrative bioinformatics methods as an essential prerequisite to discover the whole genome mutational, transcriptome and epigenome landscapes of cancer specimen and to discover cancer genesis, progression and heterogeneity. Basic challenges and tasks arise ‘beyond sequencing’ because of the big size of the data, their complexity, the need to search for hidden structures in the data, for knowledge mining to discover biological function and also systems biology conceptual models to deduce developmental interrelations between different cancer states. These tasks are tightly related to cancer biology as an (epi-)genetic disease giving rise to aberrant genomic regulation under micro-environmental control and clonal evolution which leads to heterogeneous cellular states. Machine learning algorithms such as self organizing maps (SOM) represent one interesting option to tackle these bioinformatics tasks. The SOMmethod enables recognizing complex patterns in large-scale data generated by highthroughput omics technologies. It portrays molecular phenotypes by generating individualized, easy to interpret images of the data landscape in combination with comprehensive analysis options. Our image-based, reductionist machine learning methods provide one interesting perspective how to deal with massive data in the discovery of complex diseases, gliomas, melanomas and colon cancer on molecular level. As an important new challenge, we address the combined portrayal of different omics data such as genome-wide genomic, transcriptomic and methylomic ones. The integrative-omics portrayal approach is based on the joint training of the data and it provides separate personalized data portraits for each patient and data type which can be analyzed by visual inspection as one option. The new method enables an integrative genome-wide view on the omics data types and the underlying regulatory modes. It is applied to high and low-grade gliomas and to melanomas where it disentangles transversal and longitudinal molecular heterogeneity in terms of distinct molecular subtypes and progression paths with prognostic impact.

Keywords: integrative bioinformatics, machine learning, molecular mechanisms of cancer, gliomas and melanomas

Procedia PDF Downloads 146

Authors: Noam Markovitz

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People with physical disabilities constitute a very large and simultaneously a diverse group of general population, as the term physical disabilities is extensive and covers a wide range of disabilities. Therefore, individuals with physical disabilities are often faced with a new, threatening and stressful reality leading possibly to a multi-crisis in their lives due to the great changes they experience in somatic, socio-economic, occupational and psychological level. The current study seeks to advance understanding of the complex adaptation to physical disabilities by expanding the dynamic-adaptational model of the pursuit of happiness in a hostile world with a new conception of physical self-integrity. Physical self-integrity incorporates an objective dimension, namely physical self-functioning (PSF), and a subjective dimension, namely physical self-concept (PSC). Both of these dimensions constitute an experience of wholeness in the individual’s identification with her or his physical body. The model guiding this work is dialectical in nature and depicts two systems in the individual’s sense of happiness: subjective well-being (SWB) and meaning in life (MIL). Both systems serve as self-adaptive agents that moderate the complementary system of the hostile-world scenario (HWS), which integrates one’s perceived threats to one’s integrity. Thus, in situations of increased HWS, the moderation may take a form of joint activity in which SWB and MIL are amplified or a form of compensation in which one system produces a stronger effect while the other system produces a weaker effect. The current study investigated PSC in relations to SWB and MIL through pleasantness and meanings that are physically or metaphorically grounded in one’s body. In parallel, PSC also relates to HWS by activating representations of inappropriateness, deformation and vulnerability. In view of possibly dialectical positions of opposing and complementary forces within the current model, the current field study that aims to explore PSC as appearing in an independent, cross-sectional, design addressing the model’s variables in a focal group of people with physical disabilities. This study delineated the participation of the PSC in the adaptational functions of SWB and MIL vis-à-vis HWS-related life adversities. The findings showed that PSC could fully complement the main variables of the pursuit of happiness in a hostile world model. The assumed dialectics in the form of a stronger relationship between SWB and MIL in the face of physical disabilities was not supported. However, it was found that when HWS increased, PSC and MIL were strongly linked, whereas PSC and SWB were weakly linked. This highlights the compensatory role of MIL. From a conceptual viewpoint, the current investigation may clarify the role of PSC as an adaptational agent of the individual’s positive health in complementary senses of bodily wholeness. Methodologically, the advantage of the current investigation is the application of an integrative, model-based approach within a specially focused design with a particular relevance to PSC. Moreover, from an applicative viewpoint, the current investigation may suggest how an innovative model may be translated to therapeutic interventions used by clinicians, counselors and practitioners in improving wellness and psychological well-being, particularly among people with physical disabilities.

Keywords: older adults, physical disabilities, physical self-concept, pursuit of happiness in a hostile-world

Procedia PDF Downloads 145

Authors: Elisa Santana-Monagas, Juan L. Núñez, Jaime León, Samuel Falcón, Celia Fernández, Rocío P. Solís

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Students’ emotional experiences have been a widely discussed theme among researchers, proving a central role on students’ outcomes. Yet, up to now, far too little attention has been paid to teaching practices that negatively relate with students’ negative emotions in the higher education. The present work aims to examine the relationship between teachers’ teaching practices (i.e., students’ evaluations of teaching and autonomy support), the students’ feelings of boredom and agentic engagement and motivation in the higher education context. To do so, the present study incorporates one of the most popular tools in natural processing language to address students’ evaluations of teaching: sentiment analysis. Whereas most research has focused on the creation of SA models and assessing students’ satisfaction regarding teachers and courses to the author’s best knowledge, no research before has included results from SA into an explanatory model. A total of 225 university students (Mean age = 26.16, SD = 7.4, 78.7 % women) participated in the study. Students were enrolled in degree and masters’ studies at the faculty of Education of a public university of Spain. Data was collected using an online questionnaire students could access through a QR code they completed during a teaching period where the assessed teacher was not present. To assess students’ sentiments towards their teachers’ teaching, we asked them the following open-ended question: “If you had to explain a peer who doesn't know your teacher how he or she communicates in class, what would you tell them?”. Sentiment analysis was performed with Microsoft's pre-trained model. For this study, we relied on the probability of the students answer belonging to the negative category. To assess the reliability of the measure, inter-rater agreement between this NLP tool and one of the researchers, who independently coded all answers, was examined. The average pairwise percent agreement and the Cohen’s kappa were calculated with ReCal2. The agreement reached was of 90.8% and Cohen’s kappa .68, both considered satisfactory. To test the hypothesis relations a structural equation model (SEM) was estimated. Results showed that the model fit indices displayed a good fit to the data; χ² (134) = 351.129, p < .001, RMSEA = .07, SRMR = .09, TLI = .91, CFI = .92. Specifically, results show that boredom was negatively predicted by autonomy support practices (β = -.47[-.61, -.33]), whereas for the negative sentiment extracted from SET, this relation was positive (β = .23[.16, .30]). In other words, when students’ opinion towards their instructors’ teaching practices was negative, it was more likely for them to feel bored. Regarding the relations among boredom and student outcomes, results showed a negative predictive value of boredom on students’ motivation to study (β = -.46[-.63, -.29]) and agentic engagement (β = -.24[-.33, -.15]). Altogether, results show a promising future for sentiment analysis techniques in the field of education as they proved the usefulness of this tool when evaluating relations among teaching practices and student outcomes.

Keywords: sentiment analysis, boredom, motivation, agentic engagement

Procedia PDF Downloads 90

Authors: Johns Paul, Santhosh J. Nalluveettil, P. Purushothaman, M. Premdas

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Lunar landing is one of the most critical phases of lunar mission. The lander is provided with a soft landing system to prevent structural damage of lunar module by absorbing the landing shock and also assure stability during landing. Presently available software are not capable to simulate the rigid body dynamics coupled with contact simulation and elastic/plastic deformation analysis. Hence a separate mathematical model has been generated for studying the dynamics of a typical lunar soft lander. Parameters used in the analysis includes lunar surface slope, coefficient of friction, initial touchdown velocity (vertical and horizontal), mass and moment of inertia of lander, crushing force due to energy absorbing material in the legs, number of legs and geometry of lander. The mathematical model is capable to simulate plastic and elastic deformation of honey comb, frictional force between landing leg and lunar soil, surface contact simulation, lunar gravitational force, rigid body dynamics and linkage dynamics of inverted tripod landing gear. The non linear differential equations generated for studying the dynamics of lunar lander is solved by numerical method. Matlab programme has been used as a computer tool for solving the numerical equations. The position of each kinematic joint is defined by mathematical equations for the generation of equation of motion. All hinged locations are defined by position vectors with respect to body fixed coordinate. The vehicle rigid body rotations and motions about body coordinate are only due to the external forces and moments arise from footpad reaction force due to impact, footpad frictional force and weight of vehicle. All these force are mathematically simulated for the generation of equation of motion. The validation of mathematical model is done by two different phases. First phase is the validation of plastic deformation of crushable elements by employing conservation of energy principle. The second phase is the validation of rigid body dynamics of model by simulating a lander model in ADAMS software after replacing the crushable elements to elastic spring element. Simulation of plastic deformation along with rigid body dynamics and contact force cannot be modeled in ADAMS. Hence plastic element of primary strut is replaced with a spring element and analysis is carried out in ADAMS software. The same analysis is also carried out using the mathematical model where the simulation of honeycomb crushing is replaced by elastic spring deformation and compared the results with ADAMS analysis. The rotational motion of linkages and 6 degree of freedom motion of lunar Lander about its CG can be validated by ADAMS software by replacing crushing element to spring element. The model is also validated by the drop test results of 4 leg lunar lander. This paper presents the details of mathematical model generated and its validation.

Keywords: honeycomb, landing leg tripod, lunar lander, primary link, secondary link

Procedia PDF Downloads 347

Authors: Natalia V. Naryzhnaya, Alexandr V. Mukhomedzyanov, Ivan A. Derkachev, Boris K. Kurbatov, Leonid N. Maslov

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Background: Techniques of adaptation to hypoxia and remote postconditioning (RPost) have great prospects for use in the clinic. However, recent studies have shown low efficacy of remote postconditioning in patients with AMI. We hypothesize that the reasons for this inefficiency may be metabolic disorders, which are very common, especially in patients with cardiovascular disease, and age of patients. The purpose of the study was to reveal the effectiveness of adaptation to chronic hypoxia and RPost. To determine the possible relationship between the decrease in the effectiveness of projective impacts and disorders of carbohydrate and lipid metabolism. Design: The study was carried out on Wistar rats 60 day old. MetS was induced by high-carbohydrate, high-fat diet (HСHFD). Modeling MS led to the formation of obesity, hypertension, impaired lipid and carbohydrate metabolism, hyperleptinemia, and moderate stress. Groups with adaptation to chronic hypoxia were subjected to hypoxia for 21 days at 12% O2 and 0.3% CO2 after complete of HСHFD. All animals were subjected to 45 min coronary occlusion and 120 min reperfusion. Groups with RPost, immediately after the end of ischemia, tourniquets were applied to the hind limbs in the area of the hip joint (3 times in the mode of 5 min ischemia, 5 min reperfusion). Results: RPost led to a twofold reduction of infarct size in rats with intact metabolism (р < 0.0001), while in rats with MetS, a decrease in infarct size during RPost was 25 % (p = 0.00003). A direct correlation was found between of infarct size during RPost and the serum leptin level of rats with MetC (r = 0.85). The presented data suggested that a decrease in the efficiency of remote postconditioning in rats with diet-induced metabolic syndrome depends on serum leptin. Chronic hypoxia resulted in a 38% reduced in infarct size in metabolically intact rats. The decrease of cardioprotection was observed in rats with chronic hypoxia and MetS. Infarct size showed a direct correlation with impaired glucose tolerance (AUC, glucose tolerance test, r = 0.034) and serum triglyceride levels (r = 0.39). Our study showed the dependence of cardioprotection in rats with metabolic syndrome during chronic hypoxia and DPost on opioids in the blood serum and myocardium, protein kinase C and NO synthase activity. Conclusion: The results obtained showed that the infarct-limiting efficiency of adaptation to hypoxia and remote postconditioning is reduced or completely absent in animals with metabolic syndrome. The increase in the infarction, in this case, directly depends on the disturbances in carbohydrate. lipid metabolism and opioids signaling. Funding: Investigation of effectiveness of chronic hypoxia at the metabolic syndrome was carried out within the support of Russian Science Foundation Grant 22-15-00048. Studies of the mechanisms of arterial hypertension in induced metabolic syndrome were carried out within the framework of the state assignment (122020300042-4). The work was performed using the Center for Collective Use "Medical Genomics".

Keywords: chronic hypoxia, opioids, remote postconditioning, metabolic syndrome

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Authors: Ye Zhang, Chuanjun Liu

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In-service aircraft is exposed to different types of threaten, e.g. bird strike, ground vehicle impact, and run-way debris, or even lightning strike, etc. To satisfy the aircraft damage tolerance design requirements, the designer has to understand the threatening level for different types of the aircraft structures, either metallic or composite. Exposing to low-velocity impacts may produce very serious internal damages such as delaminations and matrix cracks without leaving visible mark onto the impacted surfaces for composite structures. This internal damage can cause significant reduction in the load carrying capacity of structures. The semi-probabilistic method provides a practical and proper approximation to establish the impact-threat based energy cut-off level for the damage tolerance evaluation of the aircraft components. Thus, the probabilistic distribution of impact threat and the realistic impact energy level cut-offs are the essential establishments required for the certification of aircraft composite structures. A new survey of impact threat to civil aircraft in-service has recently been carried out based on field records concerning around 500 civil aircrafts (mainly single aisles) and more than 4.8 million flight hours. In total 1,006 damages caused by low-velocity impact events had been screened out from more than 8,000 records including impact dents, scratches, corrosions, delaminations, cracks etc. The impact threat dependency on the location of the aircraft structures and structural configuration was analyzed. Although the survey was mainly focusing on the metallic structures, the resulting low-energy impact data are believed likely representative to general civil aircraft, since the service environments and the maintenance operations are independent of the materials of the structures. The probability of impact damage occurrence (Po) and impact energy exceedance (Pe) are the two key parameters for describing the statistic distribution of impact threat. With the impact damage events from the survey, Po can be estimated as 2.1x10-4 per flight hour. Concerning the calculation of Pe, a numerical model was developed using the commercial FEA software ABAQUS to backward estimate the impact energy based on the visible damage characteristics. The relationship between the visible dent depth and impact energy was established and validated by drop-weight impact experiments. Based on survey results, Pe was calculated and assumed having a log-linear relationship versus the impact energy. As the product of two aforementioned probabilities, Po and Pe, it is reasonable and conservative to assume Pa=PoxPe=10-5, which indicates that the low-velocity impact events are similarly likely as the Limit Load events. Combing Pa with two probabilities Po and Pe obtained based on the field survey, the cutoff level of realistic impact energy was estimated and valued as 34 J. In summary, a new survey was recently done on field records of civil aircraft to investigate the probabilistic distribution of impact threat. Based on the data, two probabilities, Po and Pe, were obtained. Considering a conservative assumption of Pa, the cutoff energy level for the realistic impact energy has been determined, which provides potential applicability in damage tolerance certification of future civil aircraft.

Keywords: composite structure, damage tolerance, impact threat, probabilistic

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Authors: Nanteza Rachel

Abstract:

Background: Worldwide, there were 36.7 million people living with Human Immunodeficiency Virus (HIV) in 2015, up from 35 million at the end of 2013. Wakiso district is one of the hotspots for the Human Immunodeficiency Virus (HIV)/ Acquired Immune Deficiency Syndrome (AIDS) infection in Uganda, with the prevalence of 8.1 %. Herbal medicine has gained popularity among Human Immunodeficiency Virus (HIV)/ Acquired Immune Deficiency Syndrome (AIDS) patients as adjuvant therapy to reduce the adverse effects of ART. Regardless of the subsidized and physical availability of the Anti-Retroviral Therapy (ART), majority of Africans living with Human Immunodeficiency Virus (HIV)/ Acquired Immune Deficiency Syndrome (AIDS) resort to adding to their ART traditional medicine. Result found out from a pilot observation made by the PI that indicate 13 out of 30 People Living with AIDS(PLWA) who are attending Human Immunodeficiency Virus (HIV) clinics in Wakiso district reported to be using herbal preparations despite the fact that they were taking Anti Retro Viral (ARVs) this prompted this study to be done. Purpose of the study: To determine the prevalence and factors associated with concurrent use of herbal medicine and anti-retroviral therapy among HIV/AIDS patients attending selected HIV clinics in Wakiso district. Methodology: This was a cross sectional study with both quantitative data collection (use of a questionnaire) and qualitative data collection (key informants’ interviews). A mixed method of sampling was used, that is, purposive and random sampling. Purposive sampling was based on the location in the district and used to select 7 health facilities basing on the 7 health sub districts from Wakiso. Simple random sampling was used to select one HIV clinic from each of the 7 health sub districts. Furthermore, the study units were enrolled in to the study as they entered into the HIV clinics, and 105 respondents were interviewed. Both manual and computer packages (SPSS) were used to analyze the data Results: The prevalence of concurrent use of herbal medicine and ART was 38 (36.2%). Commonly HIV symptom treated with herbs was fever 27(71.1%), diarrhea 3(7.9%) and cough 2(5.3%). Commonly used herbs for fever (Omululuza (Vernonica amydalina), Ekigagi (Aloe sp), Nalongo (Justicia betonica Linn) while for diarrhea was Ntwatwa. The side effects also included; too much pain, itchy pain of HIV, aneamia,felt sick, loss/gain appetite, joint pain and bad dreams. Herbs used to sooth the side effects were; for aneamia was avocado leaves Parea Americana mill The significant factors associated with concurrent use of herbal medicine were being familiar with herbs and conventional medicine for management HIV symptoms being expensive. The other significant factor was exhibiting hostility to patients by health personnel providing HIV care. Conclusion: Herbal medicine is widely used by clients in HIV/AIDS care. Patients being familiar with herbs and conventional medicine being expensive were associated with concurrent use of herbal medicine and ART. The exhibition of hostility to the HIV/AIDS patients by the health care providers was also associated with concurrent use of herbal medicine and ART among HIV/AIDS patients.

Keywords: HIV patients, herbal medicine, antiretroviral therapy, factors associated

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Authors: Danny Barash

Abstract:

Riboswitches are RNA genetic control elements that were originally discovered in bacteria and provide a unique mechanism of gene regulation. They work without the participation of proteins and are believed to represent ancient regulatory systems in the evolutionary timescale. One of the biggest challenges in riboswitch research is that many are found in prokaryotes but only a small percentage of known riboswitches have been found in certain eukaryotic organisms. The few examples of eukaryotic riboswitches were identified using sequence-based bioinformatics search methods that include some slight structural considerations. These pattern-matching methods were the first ones to be applied for the purpose of riboswitch detection and they can also be programmed very efficiently using a data structure called affix arrays, making them suitable for genome-wide searches of riboswitch patterns. However, they are limited by their ability to detect harder to find riboswitches that deviate from the known patterns. Several methods have been developed since then to tackle this problem. The most commonly used by practitioners is Infernal that relies on Hidden Markov Models (HMMs) and Covariance Models (CMs). Profile Hidden Markov Models were also carried out in the pHMM Riboswitch Scanner web application, independently from Infernal. Other computational approaches that have been developed include RMDetect by the use of 3D structural modules and RNAbor that utilizes Boltzmann probability of structural neighbors. We have tried to incorporate more sophisticated secondary structure considerations based on RNA folding prediction using several strategies. The first idea was to utilize window-based methods in conjunction with folding predictions by energy minimization. The moving window approach is heavily geared towards secondary structure consideration relative to sequence that is treated as a constraint. However, the method cannot be used genome-wide due to its high cost because each folding prediction by energy minimization in the moving window is computationally expensive, enabling to scan only at the vicinity of genes of interest. The second idea was to remedy the inefficiency of the previous approach by constructing a pipeline that consists of inverse RNA folding considering RNA secondary structure, followed by a BLAST search that is sequence-based and highly efficient. This approach, which relies on inverse RNA folding in general and our own in-house fragment-based inverse RNA folding program called RNAfbinv in particular, shows capability to find attractive candidates that are missed by Infernal and other standard methods being used for riboswitch detection. We demonstrate attractive candidates found by both the moving-window approach and the inverse RNA folding approach performed together with BLAST. We conclude that structure-based methods like the two strategies outlined above hold considerable promise in detecting riboswitches and other conserved RNAs of functional importance in a variety of organisms.

Keywords: riboswitches, RNA folding prediction, RNA structure, structure-based methods

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Authors: Kalpana Adhikari, Mandip Subedi, Keshab Sharma, Indra P. Acharya

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The Gorkha Nepal earthquake of moment magnitude (Mw) 7.8 struck the central region of Nepal on April 25, 2015 with the epicenter about 77 km northwest of Kathmandu Valley . Peak ground acceleration observed during the earthquake was 0.18g. This motion induced several geotechnical effects such as landslides, foundation failures liquefaction, lateral spreading and settlement, and local amplification. An aftershock of moment magnitude (Mw) 7.3 hit northeast of Kathmandu on May 12 after 17 days of main shock caused additional damages. Kathmandu is the largest city in Nepal, have a population over four million. As the Kathmandu Valley deposits are composed mainly of sand, silt and clay layers with a shallow ground water table, liquefaction is highly anticipated. Extensive liquefaction was also observed in Kathmandu Valley during the 1934 Nepal-Bihar earthquake. Field investigations were carried out in Kathmandu Valley immediately after Mw 7.8, April 25 main shock and Mw 7.3, May 12 aftershock. Geotechnical investigation of both liquefied and non-liquefied sites were conducted after the earthquake. This paper presents observations of liquefaction and liquefaction induced damage, and the liquefaction potential assessment based on Standard Penetration Tests (SPT) for liquefied and non-liquefied sites. SPT based semi-empirical approach has been used for evaluating liquefaction potential of the soil and Liquefaction Potential Index (LPI) has been used to determine liquefaction probability. Recorded ground motions from the event are presented. Geological aspect of Kathmandu Valley and local site effect on the occurrence of liquefaction is described briefly. Observed liquefaction case studies are described briefly. Typically, these are sand boils formed by freshly ejected sand forced out of over-pressurized sub-strata. At most site, sand was ejected to agricultural fields forming deposits that varied from millimetres to a few centimeters thick. Liquefaction-induced damage to structures in these areas was not significant except buildings on some places tilted slightly. Boiled soils at liquefied sites were collected and the particle size distributions of ejected soils were analyzed. SPT blow counts and the soil profiles at ten liquefied and non-liquefied sites were obtained. The factors of safety against liquefaction with depth and liquefaction potential index of the ten sites were estimated and compared with observed liquefaction after 2015 Gorkha earthquake. The liquefaction potential indices obtained from the analysis were found to be consistent with the field observation. The field observations along with results from liquefaction assessment were compared with the existing liquefaction hazard map. It was found that the existing hazard maps are unrepresentative and underestimate the liquefaction susceptibility in Kathmandu Valley. The lessons learned from the liquefaction during this earthquake are also summarized in this paper. Some recommendations are also made to the seismic liquefaction mitigation in the Kathmandu Valley.

Keywords: factor of safety, geotechnical investigation, liquefaction, Nepal earthquake

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Authors: Akbar Gharbali, Ali Abbasian Ardekani, Afshin Mohammadi

Abstract:

Introduction: Thyroid nodules have an incidence of 33-68% in the general population. More than 5-15% of these nodules are malignant. Early detection and treatment of thyroid nodules increase the cure rate and provide optimal treatment. Between the medical imaging methods, Ultrasound is the chosen imaging technique for assessment of thyroid nodules. The confirming of the diagnosis usually demands repeated fine-needle aspiration biopsy (FNAB). So, current management has morbidity and non-zero mortality. Objective: To explore diagnostic potential of automatic texture analysis (TA) methods in differentiation benign and malignant thyroid nodules by ultrasound imaging in order to help for reliable diagnosis and monitoring of the thyroid nodules in their early stages with no need biopsy. Material and Methods: The thyroid US image database consists of 70 patients (26 benign and 44 malignant) which were reported by Radiologist and proven by the biopsy. Two slices per patient were loaded in Mazda Software version 4.6 for automatic texture analysis. Regions of interests (ROIs) were defined within the abnormal part of the thyroid nodules ultrasound images. Gray levels within an ROI normalized according to three normalization schemes: N1: default or original gray levels, N2: +/- 3 Sigma or dynamic intensity limited to µ+/- 3σ, and N3: present intensity limited to 1% - 99%. Up to 270 multiscale texture features parameters per ROIs per each normalization schemes were computed from well-known statistical methods employed in Mazda software. From the statistical point of view, all calculated texture features parameters are not useful for texture analysis. So, the features based on maximum Fisher coefficient and the minimum probability of classification error and average correlation coefficients (POE+ACC) eliminated to 10 best and most effective features per normalization schemes. We analyze this feature under two standardization states (standard (S) and non-standard (NS)) with Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA) and Non-Linear Discriminant Analysis (NDA). The 1NN classifier was performed to distinguish between benign and malignant tumors. The confusion matrix and Receiver operating characteristic (ROC) curve analysis were used for the formulation of more reliable criteria of the performance of employed texture analysis methods. Results: The results demonstrated the influence of the normalization schemes and reduction methods on the effectiveness of the obtained features as a descriptor on discrimination power and classification results. The selected subset features under 1%-99% normalization, POE+ACC reduction and NDA texture analysis yielded a high discrimination performance with the area under the ROC curve (Az) of 0.9722, in distinguishing Benign from Malignant Thyroid Nodules which correspond to sensitivity of 94.45%, specificity of 100%, and accuracy of 97.14%. Conclusions: Our results indicate computer-aided diagnosis is a reliable method, and can provide useful information to help radiologists in the detection and classification of benign and malignant thyroid nodules.

Keywords: ultrasound imaging, thyroid nodules, computer aided diagnosis, texture analysis, PCA, LDA, NDA

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