Search results for: multivariate exponentially weighted moving average

Authors: Christos E. Lampropoulos, Maria Konsta, Tamta Sirbilatze, Ifigenia Apostolou, Vicky Dradaki, Konstantina Panouria, Irini Dri, Christina Kordali, Vaggelis Lambas, Georgios Mavras

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Objectives: Full Mini Nutritional Assessment (MNA) questionnaire is one of the most useful tools in diagnosis of malnutrition in hospitalized patients, which is related to increased morbidity and mortality. The purpose of our study was to assess the nutritional status of elderly, hospitalized patients and examine the hypothesis that MNA may predict mortality and extension of hospitalization. Methods: One hundred fifty patients (78 men, 72 women, mean age 80±8.2) were included in this cross-sectional study. The following data were taken into account in analysis: anthropometric and laboratory data, physical activity (International Physical Activity Questionnaires, IPAQ), smoking status, dietary habits, cause and duration of current admission, medical history (co-morbidities, previous admissions). Primary endpoints were mortality (from admission until 6 months afterwards) and duration of admission. The latter was compared to national guidelines for closed consolidated medical expenses. Logistic regression and linear regression analysis were performed in order to identify independent predictors for mortality and extended hospitalization respectively. Results: According to MNA, nutrition was normal in 54/150 (36%) of patients, 46/150 (30.7%) of them were at risk of malnutrition and the rest 50/150 (33.3%) were malnourished. After performing multivariate logistic regression analysis we found that the odds of death decreased 20% per each unit increase of full MNA score (OR=0.8, 95% CI 0.74-0.89, p < 0.0001). Patients who admitted due to cancer were 23 times more likely to die, compared to those with infection (OR=23, 95% CI 3.8-141.6, p=0.001). Similarly, patients who admitted due to stroke were 7 times more likely to die (OR=7, 95% CI 1.4-34.5, p=0.02), while these with all other causes of admission were less likely (OR=0.2, 95% CI 0.06-0.8, p=0.03), compared to patients with infection. According to multivariate linear regression analysis, each increase of unit of full MNA, decreased the admission duration on average 0.3 days (b:-0.3, 95% CI -0.45 - -0.15, p < 0.0001). Patients admitted due to cancer had on average 6.8 days higher extension of hospitalization, compared to those admitted for infection (b:6.8, 95% CI 3.2-10.3, p < 0.0001). Conclusion: Mortality and extension of hospitalization is significantly increased in elderly, malnourished patients. Full MNA score is a useful diagnostic tool of malnutrition.

Keywords: duration of admission, malnutrition, mini nutritional assessment score, prognostic factors for mortality

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Authors: Negin Mohammadrezaee Larki

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Cloud Computing is a popular solution that has been used in recent years to cooperate and collaborate among distributed applications over networks. Moving successfully into cloud computing requires an architecture that will support the new cloud capabilities. Many business leaders and analysts agree that moving to cloud requires having a solid, service-oriented architecture to provide the infrastructure needed for successful cloud implementation.

Keywords: Service Oriented Architecture (SOA), Service Oriented Cloud Computing Architecture (SOCCA), cloud computing, cloud computing architecture

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Authors: Jose Flores, Nadia Gamboa

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A proper water quality management requires the establishment of a monitoring network. Therefore, evaluation of the efficiency of water quality monitoring networks is needed to ensure high-quality data collection of critical quality chemical parameters. Unfortunately, in some Latin American countries water quality monitoring programs are not sustainable in terms of recording historical data or environmentally representative sites wasting time, money and valuable information. In this study, multivariate statistical techniques, such as principal components analysis (PCA) and hierarchical cluster analysis (HCA), are applied for identifying the most significant monitoring sites as well as critical water quality parameters in the monitoring network of the Jequetepeque River basin, in northern Peru. The Jequetepeque River basin, like others in Peru, shows socio-environmental conflicts due to economical activities developed in this area. Water pollution by trace elements in the upper part of the basin is mainly related with mining activity, and agricultural land lost due to salinization is caused by the extensive use of groundwater in the lower part of the basin. Since the 1980s, the water quality in the basin has been non-continuously assessed by public and private organizations, and recently the National Water Authority had established permanent water quality networks in 45 basins in Peru. Despite many countries use multivariate statistical techniques for assessing water quality monitoring networks, those instruments have never been applied for that purpose in Peru. For this reason, the main contribution of this study is to demonstrate that application of the multivariate statistical techniques could serve as an instrument that allows the optimization of monitoring networks using least number of monitoring sites as well as the most significant water quality parameters, which would reduce costs concerns and improve the water quality management in Peru. Main socio-economical activities developed and the principal stakeholders related to the water management in the basin are also identified. Finally, water quality management programs will also be discussed in terms of their efficiency and sustainability.

Keywords: PCA, HCA, Jequetepeque, multivariate statistical

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Authors: Visar Baxhuku, Halil Demolli, Alishukri Shkodra

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This paper presents the monitoring of vehicle movement, namely the developing of speed of vehicles during movement in a certain twist. The basic geometry data of twist are measured with the purpose of calculating the slide in border speed. During the research, measuring developed speed of passenger vehicles for the real conditions of the road surface, dry road with average damage, was realised. After setting values, the analysis was done in function security of movement in twist.

Keywords: critical sliding velocity, moving velocity, curve, passenger vehicles

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Authors: Achut Manandhar, Kenneth D. Morton, Peter A. Torrione, Leslie M. Collins

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The current trends in affect recognition research are to consider continuous observations from spontaneous natural interactions in people using multiple feature modalities, and to represent affect in terms of continuous dimensions, incorporate spatio-temporal correlation among affect dimensions, and provide fast affect predictions. These research efforts have been propelled by a growing effort to develop affect recognition system that can be implemented to enable seamless real-time human-computer interaction in a wide variety of applications. Motivated by these desired attributes of an affect recognition system, in this work a multi-dimensional affect prediction approach is proposed by integrating multivariate Relevance Vector Machine (MVRVM) with a recently developed Output-associative Relevance Vector Machine (OARVM) approach. The resulting approach can provide fast continuous affect predictions by jointly modeling the multiple affect dimensions and their correlations. Experiments on the RECOLA database show that the proposed approach performs competitively with the OARVM while providing faster predictions during testing.

Keywords: dimensional affect prediction, output-associative RVM, multivariate regression, fast testing

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Authors: Ishapathik Das

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The purpose of this article is to find a method of comparing designs for ordinal regression models using quantile dispersion graphs in the presence of linear predictor misspecification. The true relationship between response variable and the corresponding control variables are usually unknown. Experimenter assumes certain form of the linear predictor of the ordinal regression models. The assumed form of the linear predictor may not be correct always. Thus, the maximum likelihood estimates (MLE) of the unknown parameters of the model may be biased due to misspecification of the linear predictor. In this article, the uncertainty in the linear predictor is represented by an unknown function. An algorithm is provided to estimate the unknown function at the design points where observations are available. The unknown function is estimated at all points in the design region using multivariate parametric kriging. The comparison of the designs are based on a scalar valued function of the mean squared error of prediction (MSEP) matrix, which incorporates both variance and bias of the prediction caused by the misspecification in the linear predictor. The designs are compared using quantile dispersion graphs approach. The graphs also visually depict the robustness of the designs on the changes in the parameter values. Numerical examples are presented to illustrate the proposed methodology.

Keywords: model misspecification, multivariate kriging, multivariate logistic link, ordinal response models, quantile dispersion graphs

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Authors: Bencharif Meriem, Sersar Ibrahim, Djaafri Zineb

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Introduction and purpose of the study: Education plays a fundamental role in the lives of young people, but what about their physical well-being as they spend long hours sitting at school? School inactivity is a problem that deserves particular attention because it can have significant repercussions on the health and development of students. The aim of this study was to describe and evaluate the physical activity of students in different practices in class, at recess and in the canteen. Material and methods: A physical activity diary and an anthropometric measurement sheet (weight, height) were provided to 123 school-aged adolescents. The measurements were carried out according to international recommendations. The statistical tests were carried out with the R software. 3.2.4. The significance threshold retained was 0.05. Results and Statistical Analysis: One hundred and twenty-three students agreed to participate in the study. Their average age was 16.5±1.60 years. Overweight was present in 8.13% and obesity in 4.06%. For the practice of physical activity, during physical education and sports classes, all students played sports with an average of 1.94±1.00 hours/week, of which 74.00% sweated or were out of breath during these hours of physical activity. It was also noted that boys practiced sports more than girls (p<0.0001). Each day, on average, students spent 39.78±37.85 min walking or running during recess. On the other hand, they spent, on average 4.25±2.65 hours sitting per day in class, at recess, in the canteen, etc., without counting the time spent in front of a screen. The increasing use of screens has become a major concern for parents and educators. On average, students spent approximately 42.90±38.41 min per day using screens in class, at recess, in the canteen and at home. (computer, tablet, telephone, video games, etc.) and therefore to a prolonged sedentary lifestyle. On average, students sat for more than 1.5 hours without moving for at least 2 minutes in a row approximately 1.72±0.71 times per day. Conclusion: These students spent many hours sitting at school. This prolonged inactivity can have negative consequences on their health, including problems with posture and cardiovascular health. It is crucial that schools, educators and parents collaborate to promote more active learning environments where students can move more and thus contribute to their overall well-being. It's time to rethink how we approach education and student health to give them a healthier, more active future.

Keywords: physical acivity, sedentarity, adolescents, school

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Authors: Aisyah Rahmatul Laily

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Indonesia Ministry of Health is increasing their awareness on non communicable diseases. From the top ten causes of death, two of them are non communicable diseases. Diabetes Mellitus is one of the two non communicable diseases above that have the increasing number of patient from year to year. From that problem, this research is made to determine the correlation between education, food intake, exercise, and the medication obedience with the average of blood sugar. In this research, the researchers used observational and cross-sectional studies. The sample that used in this research were 50 patients in Puskesmas Gamping I Yogyakarta who have suffered from Diabetes Mellitus in long period. The researcher doing anamnesis by using questionnaire to collect the data, then analyzed it with Chi Square to determine the correlation between each variable. The dependent variable in this research is the average of blood sugar, whereas the independent variables are education, food intake, do exercise, and the obedience of medication. The result shows a relation between education and average blood sugar level (p=0.029), a relation between food intake and average blood sugar level (p=0.009), and a relation between exercise and average blood sugar level (p=0.023). There is also a relation between the medication obedience with the average of blood sugar (p=0,002). The conclusion is that the positive correlations exist between education and average blood sugar level, between food intake and average blood sugar level, and between medication obedience and average blood sugar level.

Keywords: average of blood sugar, education, exercise, food intake, medication obedience

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Authors: A. Shirazibeheshti, T. Radwan, A. Ettefaghian, G. Wilson, C. Luca, Farbod Khanizadeh

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Anticholinergic medication has been associated with events such as falls, delirium, and cognitive impairment in older patients. To further assess this, anticholinergic burden scores have been developed to quantify risk. A risk model based on clustering was deployed in a healthcare management system to cluster patients into multiple risk groups according to anticholinergic burden scores of multiple medicines prescribed to patients to facilitate clinical decision-making. To do so, anticholinergic burden scores of drugs were extracted from the literature, which categorizes the risk on a scale of 1 to 3. Given the patients’ prescription data on the healthcare database, a weighted anticholinergic risk score was derived per patient based on the prescription of multiple anticholinergic drugs. This study was conducted on over 300,000 records of patients currently registered with a major regional UK-based healthcare provider. The weighted risk scores were used as inputs to an unsupervised learning algorithm (mean-shift clustering) that groups patients into clusters that represent different levels of anticholinergic risk. To further evaluate the performance of the model, any association between the average risk score within each group and other factors such as socioeconomic status (i.e., Index of Multiple Deprivation) and an index of health and disability were investigated. The clustering identifies a group of 15 patients at the highest risk from multiple anticholinergic medication. Our findings also show that this group of patients is located within more deprived areas of London compared to the population of other risk groups. Furthermore, the prescription of anticholinergic medicines is more skewed to female than male patients, indicating that females are more at risk from this kind of multiple medications. The risk may be monitored and controlled in well artificial intelligence-equipped healthcare management systems.

Keywords: anticholinergic medicines, clustering, deprivation, socioeconomic status

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Authors: Chris Suma, Yingcai Xiao

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This paper presents Parallel Coordinates on a Spiral Surface (PCoSS), a parallel coordinate based interactive visualization method for high-dimensional data, and a test implementation of the method. Plots generated by the test system are compared with those generated by XDAT, a software implementing traditional parallel coordinates. Traditional parallel coordinate plots can be cluttered when the number of data points is large or when the dimensionality of the data is high. PCoSS plots display multivariate data on a 3D spiral surface and allow users to see the whole picture of high-dimensional data with less cluttering. Taking advantage of the 3D display environment in PCoSS, users can further reduce cluttering by zooming into an axis of interest for a closer view or by moving vantage points and by reorienting the viewing angle to obtain a desired view of the plots.

Keywords: human computer interaction, parallel coordinates, spiral surface, visualization

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Authors: Prozorkevitch D., Mishurov A., Sokolov K., Karsakov L., Pestrikova L.

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The current body of knowledge about the marine environment and the dynamics of marine ecosystems includes a huge amount of heterogeneous data collected over decades. It generally includes a wide range of hydrological, biological and fishery data. Marine researchers collect these data and analyze how and why the ecosystem changes from past to present. Based on these historical records and linkages between the processes it is possible to predict future changes. Multivariate analysis of trends and their interconnection in the marine ecosystem may be used as an instrument for predicting further ecosystem evolution. A wide range of information about the components of the marine ecosystem for more than 50 years needs to be used to investigate how these arrays can help to predict the future.

Keywords: barents sea ecosystem, abiotic, biotic, data sets, trends, prediction

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Authors: E. M. Rifqi Wilda Pradana, Bagus Bayu Prabowo, Meida Riski Pujiyati, Efraim Maykhel Hagana Ginting, Virgiawan Arya Hangga Reksa

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The VLF (Very Low Frequency) method is an electromagnetic method that uses low frequencies between 10-30 KHz which results in a fairly deep penetration. In this study, the VLF method was used for zonation of disaster-prone areas by identifying geological structures in the form of faults. Data acquisition was carried out in Trimulyo Region, Jetis District, Bantul Regency, Special Region of Yogyakarta, Indonesia with 8 measurement paths. This study uses wave transmitters from Japan and Australia to obtain Tilt and Elipt values that can be used to create RAE (Rapat Arus Ekuivalen or Current Density) sections that can be used to identify areas that are easily crossed by electric current. This section will indicate the existence of a geological structure in the form of faults in the study area which is characterized by a high RAE value. In data processing of VLF method, it is obtained Tilt vs Elliptical graph and Moving Average (MA) Tilt vs Moving Average (MA) Elipt graph of each path that shows a fluctuating pattern and does not show any intersection at all. Data processing uses Matlab software and obtained areas with low RAE values that are 0%-6% which shows medium with low conductivity and high resistivity and can be interpreted as sandstone, claystone, and tuff lithology which is part of the Semilir Formation. Whereas a high RAE value of 10% -16% which shows a medium with high conductivity and low resistivity can be interpreted as a fault zone filled with fluid. The existence of the fault zone is strengthened by the discovery of a normal fault on the surface with strike N550W and dip 630E at coordinates X= 433256 and Y= 9127722 so that the activities of residents in the zone such as housing, mining activities and other activities can be avoided to reduce the risk of natural disasters.

Keywords: current density, faults, very low frequency, zonation

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Authors: Azadeh Golshan, Craig Evans, Phillip Geary, Abigail Morrow, Zoe Rogers, Marcel Maeder

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22 physicochemical variables have been determined in water samples collected weekly from January to December in 2013 from three sampling stations located within a major drinking water reservoir. Classical Multivariate Curve Resolution Alternating Least Squares (MCR-ALS) analysis was used to investigate the environmental factors associated with the physico-chemical variability of the water samples at each of the sampling stations. Matrix augmentation MCR-ALS (MA-MCR-ALS) was also applied, and the two sets of results were compared for interpretative clarity. Links between these factors, reservoir inflows and catchment land-uses were investigated and interpreted in relation to chemical composition of the water and their resolved geographical distribution profiles. The results suggested that the major factors affecting reservoir water quality were those associated with agricultural runoff, with evidence of influence on algal photosynthesis within the water column. Water quality variability within the reservoir was also found to be strongly linked to physical parameters such as water temperature and the occurrence of thermal stratification. The two methods applied (MCR-ALS and MA-MCR-ALS) led to similar conclusions; however, MA-MCR-ALS appeared to provide results more amenable to interpretation of temporal and geological variation than those obtained through classical MCR-ALS.

Keywords: drinking water reservoir, multivariate analysis, physico-chemical parameters, water quality

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Authors: Nida Rizvi, Deeksha Katyal, Varun Joshi

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River Hindon is an important river catering the demand of highly populated rural and industrial cluster of western Uttar Pradesh, India. Water quality of river Hindon is deteriorating at an alarming rate due to various industrial, municipal and agricultural activities. The present study aimed at identifying the pollution sources and quantifying the degree to which these sources are responsible for the deteriorating water quality of the river. Various water quality parameters, like pH, temperature, electrical conductivity, total dissolved solids, total hardness, calcium, chloride, nitrate, sulphate, biological oxygen demand, chemical oxygen demand and total alkalinity were assessed. Water quality data obtained from eight study sites for one year has been subjected to the two multivariate techniques, namely, principal component analysis and cluster analysis. Principal component analysis was applied with the aim to find out spatial variability and to identify the sources responsible for the water quality of the river. Three Varifactors were obtained after varimax rotation of initial principal components using principal component analysis. Cluster analysis was carried out to classify sampling stations of certain similarity, which grouped eight different sites into two clusters. The study reveals that the anthropogenic influence (municipal, industrial, waste water and agricultural runoff) was the major source of river water pollution. Thus, this study illustrates the utility of multivariate statistical techniques for analysis and elucidation of multifaceted data sets, recognition of pollution sources/factors and understanding temporal/spatial variations in water quality for effective river water quality management.

Keywords: cluster analysis, multivariate statistical techniques, river Hindon, water quality

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Authors: O. Poleshchuk, E. Komarov

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This paper presents a regression model for interval type-2 fuzzy sets based on the least squares estimation technique. Unknown coefficients are assumed to be triangular fuzzy numbers. The basic idea is to determine aggregation intervals for type-1 fuzzy sets, membership functions of whose are low membership function and upper membership function of interval type-2 fuzzy set. These aggregation intervals were called weighted intervals. Low and upper membership functions of input and output interval type-2 fuzzy sets for developed regression models are considered as piecewise linear functions.

Keywords: interval type-2 fuzzy sets, fuzzy regression, weighted interval

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Authors: Faramarz Khosravi, Gokhan Izbirak

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A weighted statistical stochastic based Analytical Hierarchy Process (AHP) model for modeling the potential barriers and enablers of sustainability for measuring and assessing the sustainability level is proposed. For context-dependent potential barriers and enablers, the proposed model takes the basis of the properties of the variables describing the sustainability functions and was developed into a realistic analytical model for the sustainable behavior of an organization. This thus serves as a means for measuring the sustainability of the organization. The main focus of this paper was the application of the AHP tool in a statistically-based model for measuring sustainability. Hence a strong weighted stochastic AHP based procedure was achieved. A case study scenario of a widely reported major Canadian electric utility was adopted to demonstrate the applicability of the developed model and comparatively examined its results with those of an equal-weighted model method. Variations in the sustainability of a company, as fluctuations, were figured out during the time. In the results obtained, sustainability index for successive years changed form 73.12%, 79.02%, 74.31%, 76.65%, 80.49%, 79.81%, 79.83% to more exact values 73.32%, 77.72%, 76.76%, 79.41%, 81.93%, 79.72%, and 80,45% according to priorities of factors that have found by expert views, respectively. By obtaining relatively necessary informative measurement indicators, the model can practically and effectively evaluate the sustainability extent of any organization and also to determine fluctuations in the organization over time.

Keywords: AHP, sustainability fluctuation, environmental indicators, performance measurement

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Authors: Zdeněk Veselý, Milan Honner, Jiří Mach

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The aim of the performed work is to establish the 2D and 3D model of direct unsteady task of sample heat treatment by moving source employing computer model on the basis of finite element method. The complex boundary condition on heat loaded sample surface is the essential feature of the task. Computer model describes heat treatment of the sample during heat source movement over the sample surface. It is started from the 2D task of sample cross section as a basic model. Possibilities of extension from 2D to 3D task are discussed. The effect of the addition of third model dimension on the temperature distribution in the sample is showed. Comparison of various model parameters on the sample temperatures is observed. Influence of heat source motion on the depth of material heat treatment is shown for several velocities of the movement. Presented computer model is prepared for the utilization in laser treatment of machine parts.

Keywords: computer simulation, unsteady model, heat treatment, complex boundary condition, moving heat source

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Authors: Susanne Fridsten, Kristina Hellman, Anders Sundin, Lennart Blomqvist

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Background: Patients diagnosed with locally advanced cervical carcinoma are treated with definitive concomitant chemo-radiotherapy. Treatment failure occurs in 30-50% of patients with very poor prognoses. The treatment is standardized with risk for both over-and undertreatment. Consequently, there is a great need for biomarkers able to predict therapy outcomes to allow for individualized treatment. Aim: To explore the role of T2- and diffusion-weighted magnetic resonance imaging (MRI) for early prediction of therapy outcome and the optimal time point for assessment. Methods: A pilot study including 15 patients with cervical carcinoma stage IIB-IIIB (FIGO 2009) undergoing definitive chemoradiotherapy. All patients underwent MRI four times, at baseline, 3 weeks, 5 weeks, and 12 weeks after treatment started. Tumour size, size change (∆size), visibility on diffusion-weighted imaging (DWI), apparent diffusion coefficient (ADC) and change of ADC (∆ADC) at the different time points were recorded. Results: 7/15 patients relapsed during the study period, referred to as "poor prognosis", PP, and the remaining eight patients are referred to "good prognosis", GP. The tumor size was larger at all time points for PP than for GP. The ∆size between any of the four-time points was the same for PP and GP patients. The sensitivity and specificity to predict prognostic group depending on a remaining tumor on DWI were highest at 5 weeks and 83% (5/6) and 63% (5/8), respectively. The combination of tumor size at baseline and remaining tumor on DWI at 5 weeks in ROC analysis reached an area under the curve (AUC) of 0.83. After 12 weeks, no remaining tumor was seen on DWI among patients with GP, as opposed to 2/7 PP patients. Adding ADC to the tumor size measurements did not improve the predictive value at any time point. Conclusion: A large tumor at baseline MRI combined with a remaining tumor on DWI at 5 weeks predicted a poor prognosis.

Keywords: chemoradiotherapy, diffusion-weighted imaging, magnetic resonance imaging, uterine cervical carcinoma

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Authors: S. da Costa, D. Páez, E. Martínez, A. Torres, M. Beramendi, D. Hermosilla, M. Muratori

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This study examined the association between creative performance, organizational climate and leadership, affectivity, shared flow, and group decision making. The sample consisted of 315 cadets of a military academic unit of South America. Satisfaction with the decision-making process during a creative task was associated with the usefulness and effectiveness of the ideas generated by the teams with a weighted average correlation of r = .18. Organizational emotional climate, positive and innovation leadership were associated with this group decision-making process r = .25, with shared flow, r = .29 and with positive affect felt during the performance of the creative task, r = .12. In a sequential mediational analysis positive organizational leadership styles were significantly associated with decision-making process and trough cohesion with utility and efficacy of the solution of a creative task. Satisfactory decision-making was related to shared flow during the creative task at collective or group level, and positive affect with flow at individual level.This study examined the association between creative performance, organizational climate and leadership, affectivity, shared flow, and group decision making. The sample consisted of 315 cadets of a military academic unit of South America. Satisfaction with the decision-making process during a creative task was associated with the usefulness and effectiveness of the ideas generated by the teams with a weighted average correlation of r = .18. Organizational emotional climate, positive and innovation leadership were associated with this group decision-making process r = .25, with shared flow, r = .29 and with positive affect felt during the performance of the creative task, r = .12. In a sequential mediational analysis positive organizational leadership styles were significantly associated with decision-making process and trough cohesion with utility and efficacy of the solution of a creative task. Satisfactory decision-making was related to shared flow during the creative task at collective or group level, and positive affect with flow at individual level.

Keywords: creativity, innovation, military, organization, teams

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Authors: Naiara de Almeida Rios

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The environmental education, from Tbilisi, is signaled as an important instrument for conservation and environmental management. However, the social, economic, political and environmental aspects of each place require an environmental management that corresponds to the reality to which they are inserted, as well as environmental education practices. The city of Belém, the capital of the State of Pará, is one of the most important cities in the Amazon Region, and its vast water dimension requires that its watersheds take a careful look at their socio-environmental management. The Estrada Nova Hydrographic Basin is considered as one of the most critical river basins in the city due to flooding, lack of basic sanitation and degradation of water bodies. In this context, environmental education is understood as one of the necessary conditions to reduce environmental degradation. Environmental education presents itself as an instrument of social transformation and conservation of natural resources (especially water resources), where thinking about the sustainability of natural resources is moving towards dialogue on the importance of building an environmental awareness. The commitment that environmental education proposes covers all spheres of society, since the main objective of the same is the transformation of thought and attitudes from the understanding of reality. Therefore, to analyze how the government is managing the basin, as well as the environmental education practices developed in it, is fundamental, so that government can be charged with improvements for the population and for the natural environment. Therefore, the objective of this study is to analyze the influence of environmental education actions developed by local public authorities in the management of the Estrada Nova Hydrographic Basin, Belém/PA. For the accomplishment of this study, some methodological procedures will be used, like documentary analysis, bibliographical survey and fieldwork. If the multivariate statistical method is used to analyze the results obtained in the field. Unfortunately, public policies in the area of ​environmental education in Belém are still moving in short steps, since government interests have had very little dialogue with the socio-environmental problems that affect the Estrada Nova Hydrographic Basin. Both formal and informal environmental education has been poorly developed, hampering the continuous process proposed by water resources management.

Keywords: environmental education, environmental management, hydrographic basin, water resources

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Authors: Reza Babajanivalashedi, Stefania Lo Feudo, Jean-Luc Dion

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Liquid sloshing is a crucial problem for the dynamic of moving containers in the packaging industries. Sloshing issues have been so far mainly modeled within the framework of fluid dynamics or by using equivalent mechanical models with different kinds of movements and shapes of containers. Nevertheless, these approaches do not allow to determinate the shape of the free surface of the liquid in case of the irregular shape of the moving containers, so that experimental measurements may be required. If there is too much slosh in the moving tank, the liquid can be splashed out on the packages. So, the free surface oscillation must be controlled/reduced to eliminate the splashing. The purpose of this research is to propose an optimization algorithm for finding an optimum command law to reduce surface elevation. In the first step, the free surface of the liquid is simulated based on the separation variable and weak formulation models. Then Genetic and Gradient algorithms are developed for finding the optimum command law. The optimum command law is compared with existing command laws, and the results show that there is a significant difference in surface oscillation between optimum and existing command laws. This algorithm is applicable for different varieties of bottles in case of using the camera for detecting the liquid elevation, and it can produce new command laws for different kinds of tanks to reduce the surface oscillation and remove the splashing phenomenon.

Keywords: sloshing phenomenon, separation variables, weak formulation, optimization algorithm, command law

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Authors: Azza Gaber Farag, Yasser Atta Shehata, Sara Elsayed Elghazouly, Mustafa Elsayed Elshaib, Nesreen Gamal Elden Elhelbawy

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Background: Androgen receptor (AR) polymorphism in cytosine adenineguanine (CAG) repeat has an effect on the functional capacity of AR in males. However, little researches in this field are available regarding female sexual function. Aim: To investigate the possible link between polymorphism in the CAG repeat of AR gene and female sexual function in a sample of the Egyptian population. Materials and methods: 500 Egyptian married females completed a questionnaire regarding sociodemographic, reproductive, and sexual data. AR CAG repeat length was analyzed for those having female sexual dysfunctions (FSD) using real-time PCR. Results: The most sensitive domain to AR CAG repeat length was the orgasm domain that showed significant positive correlations with short allele (p=0.001), long allele (p=.015), biallellic mean (p=.000), and X weighted biallelic mean (p=.000). The satisfaction domain had significant positive correlations with the biallelic mean (p=.035), and the X weighted biallelic mean (p=. 032). However, the pain domain was of significant negative correlations with AR polymorphism of short allele (p=.002), biallelic mean (p=.013), and X weighted biallelic mean (p = . 011). Conclusions: AR polymorphism could represent a non-negligible aspect in female sexual function. The lower AR CAG repeat polymorphism was of significant impact on FSD, affecting mainly female orgasm followed by pain disorders that finally reflected On her sexual satisfaction.

Keywords: female sexual dysfunction, androgen receptor, CAG repeat polymorphism, androgen

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Authors: B. G. Abiona, O. E. Fapojuwo, T. Akinlawon

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This study assessed the influence of human resource management practices on agricultural employees’ behavior. Data were collected from 75 randomly selected respondents using a well-structured questionnaire. The mean age of the employees’ was 43.2 years. Major human resource management practices that influence employees behaviors were: In-service training are given to employees on a regular basis (average value of x=3.44), management reward employees who are committed to their job (average value of x =3.41) and reward are designed to encourage wide participation and activity (average value of x=3.41). Also, major employees’ behavior include: Managers and employees’ wants to create better job performance (average value of x=3.13) and administrator provides praise and recognition for effective performance and show appreciation for special effort (average value of x=3.05). Major factors affecting employees’ behavior were: inadequate training (average value of x=2.93), inadequate local and international training (average value of x=2.87), inadequate grants for training programmes (average value of x= 2.81). A significant relationship was found between gender (χ2 = 37.204, P<0.05), educational qualification (χ2 = 59.093, P<0.05), income (r =0.122, P<0.05) and human resource management practices (r = 0.573, P< 0.05) of the respondents and employees’ behavior. Management should encourage employees who are committed to their job through awards and recognition.

Keywords: human resources management, agricultural employees, behaviour research institutes, Nigeria

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Authors: Morteza Raminnia

Abstract:

In this study, dynamic analysis of functionally graded nano-composite pipe reinforced by single-walled carbon nano-tubes (SWCNTs) with simply supported boundary condition subjected to moving mechanical loads is investigated. The material properties of functionally graded carbon nano tube-reinforced composites (FG-CNTRCs) are assumed to be graded in the thickness direction and are estimated through a micro-mechanical model. In this paper polymeric matrix considered as isotropic material and for the CNTRC, uniform distribution (UD) and three types of FG distribution patterns of SWCNT reinforcements are considered. The system equation of motion is derived by using Hamilton's principle under the assumptions of first order shear deformation theory (FSDT).The thin piezoelectric layers embedded on inner and outer surfaces of FG-CNTRC layer are acted as distributed sensor and actuator to control dynamic characteristics of the FG-CNTRC laminated pipe. The modal analysis technique and Newmark's integration method are used to calculate the displacement and dynamic stress of the pipe subjected to moving loads. The effects of various material distribution and velocity of moving loads on dynamic behavior of the pipe is presented. This present approach is validated by comparing the numerical results with the published numerical results in literature. The results show that the above-mentioned effects play very important role on dynamic behavior of the pipe .This present work shows that some meaningful results that which are interest to scientific and engineering community in the field of FGM nano-structures.

Keywords: nano-composite, functionally garded material, moving load, active control, PZT layers

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Authors: Zichun Guo

Abstract:

Guangzhou's house price has long been lower than the other three major cities; with the gradual increase in Guangzhou's house price, the influencing factors of house price have gradually been paid attention to; this paper tries to use house price data and POI (Point of Interest) data, and explores the distribution of house price and influencing factors by applying the Kriging spatial interpolation method and geographically weighted regression model in ArcGIS. The results show that the interpolation result of house price has a significant relationship with the economic development and development potential of the region and that different POI types have different impacts on the growth of house prices in different regions.

Keywords: POI, house price, spatial heterogeneity, Guangzhou

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Authors: Muhammad Tarmidzi, Reza M. G. Gani, Andri Luthfi

Abstract:

The purpose of this study is to identify rock zone containing hydrocarbons with calculating rock property includes volume shale, total porosity, effective porosity and water saturation. Identification method rock property based on GR log, resistivity log, neutron log and density rock. Zoning is based on sequence stratigraphic markers that are sequence boundary (SB), transgressive surface (TS) and flooding surface (FS) which correlating ten well log in blok “M”. The results of sequence stratigraphic correlation consist of eight zone that are two LST zone, three TST zone and three HST zone. The result of rock property calculation in each zone is showing two LST zone containing hydrocarbons. LST-1 zone has average volume shale (Vsh) 25%, average total porosity (PHIT) 14%, average effective porosity (PHIE) 11% and average water saturation 0,83. LST-2 zone has average volume shale (Vsh) 19%, average total porosity (PHIT) 21%, average effective porosity (PHIE) 17% and average water saturation 0,82.

Keywords: hydrocarbons zone, petrophysic, rock property, sequence stratigraphic

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Authors: Rishikesh Yadav, Ramakanta Meher, Vishnu Narayan Mishra

Abstract:

The main aim of this article is to investigate the statistical convergence of the summation of integral type operators and to obtain the weighted statistical convergence. The rate of statistical convergence by means of modulus of continuity and function belonging to the Lipschitz class are also studied. We discuss the convergence of the defined operators by graphical representation and put a better rate of convergence than the Szasz-Mirakjan-Kantorovich operators. In the last section, we extend said operators into bivariate operators to study about the rate of convergence in sense of modulus of continuity and by means of Lipschitz class by using function of two variables.

Keywords: The Szasz-Mirakjan-Kantorovich operators, statistical convergence, modulus of continuity, Peeters K-functional, weighted modulus of continuity

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Authors: Plessen Mogens Graf

Abstract:

Within the context of multivariate time series segmentation, this paper proposes a method inspired by a posteriori optimal trading. After a normalization step, time series are treated channelwise as surrogate stock prices that can be traded optimally a posteriori in a virtual portfolio holding either stock or cash. Linear transaction costs are interpreted as hyperparameters for noise filtering. Trading signals, as well as trading signals obtained on the reversed time series, are used for unsupervised channelwise labeling before a consensus over all channels is reached that determines the final segmentation time instants. The method is model-free such that no model prescriptions for segments are made. Benefits of proposed approach include simplicity, computational efficiency, and adaptability to a wide range of different shapes of time series. Performance is demonstrated on synthetic and real-world data, including a large-scale dataset comprising a multivariate time series of dimension 1000 and length 2709. Proposed method is compared to a popular model-based bottom-up approach fitting piecewise affine models and to a recent model-based top-down approach fitting Gaussian models and found to be consistently faster while producing more intuitive results in the sense of segmenting time series at peaks and valleys.

Keywords: time series segmentation, model-free, trading-inspired, multivariate data

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Authors: Lu Lin

Abstract:

Urbanization has reshaped physical environment, energy consumption and carbon emission of the urban area. China is a typical developing country under a rapid urbanization process and is the world largest carbon emission country. This study aims to explore the correlation between urban form and carbon emission caused by urban energy consumption in China. 287 provincial-level and prefecture-level cities are studied in 2000, 2005, and 2010. Compact ratio index, shape index, and fractal dimension index are used to quantify urban form. Geographically weighted regression (GWR) model is employed to explore the relationship between urban form, energy consumption, and related carbon emission. The results show the average compact ratio index decreased from 2000 to 2010 which indicates urban in China sprawled. The average fractal dimension index increases by 3%, indicating the spatial layouts of China's cities were more complicated. The results by the GWR model show that shape index and fractal dimension index had a non-significant relationship with carbon emission by urban energy consumption. However, compact urban form reduced carbon emission. The findings of this study will help policy-makers make sustainable urban planning and reduce urban carbon emission.

Keywords: carbon emission, GWR model, urban energy consumption, urban form

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Authors: Mekni Sabrine, Nouira Mariem

Abstract:

Background and aim: Allogeneic hematopoietic stem cell transplantation is a curative treatment for several hematological diseases; however, it has a non-negligible morbidity and mortality depending on several prognostic factors, including pre-transplant hyperferritinemia. The aim of our study was to estimate the impact of hyperferritinemia on survivals and on the occurrence of post-transplant complications. Methods: It was a longitudinal study conducted over 8 years and including all patients who had a first allograft. The impact of pretransplant hyperferritinemia (ferritinemia ≥1500) on survivals was studied using the Kaplan Meier method and the COX model for uni- and multivariate analysis. The Khi-deux test and binary logistic regression were used to study the association between pretransplant ferritinemia and post-transplant complications. Results: One hundred forty patients were included with an average age of 26.6 years and a sex ratio (M/F)=1.4. Hyperferritinemia was found in 33% of patients. It had no significant impact on either overall survival (p=0.9) or event -free survival (p=0.6). In multivariate analysis, only the type of disease was independently associated with overall survival (p=0.04) and event-free survival (p=0.002). For post-allograft complications: The occurrence of early documented infections was independently associated with pretransplant hyperferritinemia (p=0.02) and the presence of acute graft versus host disease( GVHD) (p<10-3). The occurrence of acute GVHD was associated with early documented infection (p=0.002) and Cytomegalovirus reactivation (p<10-3). The occurrence of chronic GVHD was associated with the presence of Cytomegalovirus reactivation (p=0.006) and graft source (p=0.009). Conclusion: Our study showed the significant impact of pre-transplant hyperferritinemia on the occurrence of early infections but not on survivals. Early and more accurate assessment iron overload by other tests such as liver magnetic resonance imaging with initiation of chelating treatment could prevent the occurrence of such complications after transplantation.

Keywords: allogeneic, transplants, ferritin, survival

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