Search results for: average causal effect

Authors: Javad Sarvestan, Zdenek Svoboda

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Force-time (F-T) curvature characteristics are globally referenced as the main indicators of athletic jump performance. Nevertheless, to the best of authors’ knowledge, no investigation tried to deeply study the relationship between F-T curve variables and real-game jump performance among elite volleyball players. To this end, this study was designated to investigate the association between F-T curve variables, including movement timings, force, velocity, power, rate of force development (RFD), modified reactive strength index (RSImod), and net impulse with spike jump height during real-game circumstances. Twelve young elite volleyball players performed 3 countermovement jump (CMJ) and 3 spike jump in real-game circumstances with 1-minute rest intervals to prevent fatigue. Shapiro-Wilk statistical test illustrated the normality of data distribution, and Pearson’s product correlation test portrayed a significant correlation between CMJ height and peak RFD (0.85), average RFD (r=0.81), RSImod (r=0.88) and concentric net impulse (r=0.98), and also significant correlation between spike jump height and peak RFD (0.73), average RFD (r=0.80), RSImod (r=0.62) and concentric net impulse (r=0.71). Multiple regression analysis also reported that these factors have a strong contribution in predicting of CMJ (98%) and spike jump (77%) heights. Outcomes of this study confirm that the RFD, concentric net impulse, and RSImod values could precisely monitor and track the volleyball attackers’ explosive strength, muscular stretch-shortening cycle function efficiency, and ultimate spike jump height. To this effect, volleyball coaches and trainers are advised to have an in-depth focus on their athletes’ progression or the impacts of strength trainings by observing and chasing the F-T curve variables such as RFD, net impulse, and RSImod.

Keywords: net impulse, reactive strength index, rate of force development, stretch-shortening cycle

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Authors: Ivory A. Rulona, Jarungchai Anton S. Vatanagul

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Background: Depression is common after stroke with quoted rates ranging from 18% to 61%. 8 Mood disturbance is common after stroke and may present as depression or anxiety. Psychological mood disturbance is associated with higher rates of mortality, long term disability, and hospital readmission. Objectives: To investigate the incidence of post-stroke depression in a tertiary hospital in Cebu City, Philippines and to determine its associated factors. The study is designed to be prospective, descriptive, cross-sectional survey. Participants: Adult patients seen and diagnosed to have stroke either infarct or hemorrhage within the period of January 1 to July 31, 2014. Results: A total of 100 patients with stroke were interviewed using the 17-item Hamilton Depression Rating Scale (HDRS) questionnaire. The average age of the respondents was 60.50 years old ±1.18, majority were males (55%), 83% were married, and 81% were employed. The most common co-morbidity was hypertension 78% followed by diabetes mellitus at 50%. Moreover, 39% of these patients had stroke in months, 26% in years, and 18% in weeks. The average functional capacity based on Modified Rankin Scale was 2.14+/-0.14. Among 100 patients, a total of 30 patients (30%) had depression: 2 (2%) very severe, 5 (5%) moderate and 23 (23%) had mild depression while 70 patients (70%) had no depression. Stroke located at the dominant hemisphere was not associated with severe depression (p=0.102). A similar trend was also noted among those with stroke at the right side (p=0.183), pons (p=0.634), bilateral (p=0.776), and midbrain (p=0.336). Conclusion: This study showed that majority of stroke patients were males with average age of 60.50 years. Hypertension was the most common co-morbidity. There was no association between stroke location and depression. The incidence of PSD was 30%.

Keywords: post-stroke depression, co-morbidity, disturbance, bilateral

Procedia PDF Downloads 294

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

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Authors: S. L. Tulasi Devi, Shivam Azad

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The primary objective of this study is to analyze the impact of green bond issuance on the stock prices of respective Indian companies. An event study methodology has been employed to study the effect of green bond issuance. For in-depth study and analysis, this paper used different window frames, including 15-15 days, 10-10 days, 7-7days, 6-6 days, and 5-5 days. Further, for better clarity, this paper also used an uneven window period of 7-5 days. The period of study covered all the companies which issued green bonds during the period of 2017-2022; Adani Green Energy, State Bank of India, Power Finance Corporation, Jain Irrigation, and Rural Electrification Corporation, except Indian Renewable Energy Development Agency and Indian Railway Finance Corporation, because of data unavailability. The paper used all three event study methods as discussed in earlier literature; 1) constant return model, 2) market-adjusted model, and 3) capital asset pricing model. For the fruitful comparison between results, the study considered cumulative average return (CAR) and buy and hold average return (BHAR) methodology. For checking the statistical significance, a two-tailed t-statistic has been used. All the statistical calculations have been performed in Microsoft Excel 2016. The study found that all other companies have shown positive returns on the event day except for the State Bank of India. The results demonstrated that constant return model outperformed compared to the market-adjusted model and CAPM. The p-value derived from all the methods has shown an almost insignificant impact of the issuance of green bonds on the stock prices of respective companies. The overall analysis states that there’s not much improvement in the market efficiency of the Indian Stock Markets.

Keywords: green bonds, event study methodology, constant return model, market-adjusted model, CAPM

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Authors: Abdallah Touaibia, Nachida Kasbadji Merzouk, Mustapha Merzouk, Ryma Belarbi

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accuracy assessment and a better understand of the wind resource distribution are the most important tasks for decision making before installing wind energy operating systems in a given region, there where our interest come to the Algerian coastline and its Mediterranean sea area. Despite its large coastline overlooking the border of Mediterranean Sea, there is still no strategy encouraging the development of offshore wind farms in Algerian waters. The present work aims to estimate the offshore wind fields for the Algerian Mediterranean Sea based on wind data measurements ranging from 1995 to 2018 provided of 24 years of measurement by seven observation stations focusing on three coastline cities in Algeria under a different measurement time step recorded from 30 min, 60 min, and 180 min variate from one to each other, two stations in Spain, two other ones in Italy and three in the coast of Algeria from the east Annaba, at the center Algiers, and to Oran taken place at the west of it. The idea behind consists to have multiple measurement points that helping to characterize this area in terms of wind potential by the use of interpolation method of their average wind speed values between these available data to achieve the approximate values of others locations where aren’t any available measurement because of the difficulties against the implementation of masts within the deep depth water. This study is organized as follow: first, a brief description of the studied area and its climatic characteristics were done. After that, the statistical properties of the recorded data were checked by evaluating wind histograms, direction roses, and average speeds using MatLab programs. Finally, ArcGIS and MapInfo soft-wares were used to establish offshore wind maps for better understanding the wind resource distribution, as well as to identify windy sites for wind farm installation and power management. The study pointed out that Cap Carbonara is the windiest site with an average wind speed of 7.26 m/s at 10 m, inducing a power density of 902 W/m², then the site of Cap Caccia with 4.88 m/s inducing a power density of 282 W/m². The average wind speed of 4.83 m/s is occurred for the site of Oran, inducing a power density of 230 W/m². The results indicated also that the dominant wind direction where the frequencies are highest for the site of Cap Carbonara is the West with 34%, an average wind speed of 9.49 m/s, and a power density of 1722 W/m². Then comes the site of Cap Caccia, where the prevailing wind direction is the North-west, about 20% and 5.82 m/s occurring a power density of 452 W/m². The site of Oran comes in third place with the North dominant direction with 32% inducing an average wind speed of 4.59 m/s and power density of 189 W/m². It also shown that the proposed method is either crucial in understanding wind resource distribution for revealing windy sites over a large area and more effective for wind turbines micro-siting.

Keywords: wind ressources, mediterranean sea, offshore, arcGIS, mapInfo, wind maps, wind farms

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Authors: Kevin Wongleedee

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This research paper was aimed to examine the reasons associated with hotel employees’ loyalty. This was a case study of 200 hotel employees in Bangkok, Thailand. The population of this study included all hotel employees who were working in Bangkok during January to March, 2014. Based on 200 respondents who answered the questionnaire, the data were complied by using SPSS. Mean and standard deviation were utilized in analyzing the data. The findings revealed that the average mean of importance was 4.40, with 0.7585 of standard deviation. Moreover, the mean average can be used to rank the level of importance from each factor as follows: 1) salary, service charge cut, and benefits, 2) career development and possible advancement, 3) freedom of working, thinking, and ability to use my initiative, 4) training opportunities, 5) social involvement and positive environment, 6) fair treatment in the workplace and fair evaluation of job performance, and 7) personal satisfaction, participation, and recognition.

Keywords: hotel employees, loyalty, reasons, case study

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Authors: Feng Ji Mervin Goh, Edmund Chee Jian Pua, Stuart Alexander Cook

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Dilated cardiomyopathy (DCM) is a common cause of heart failure. Genetic mutations account for 50% of DCM cases with TTN mutations being the most common, accounting for up to 25% of DCM cases. However, the genetic architecture underlying Asian DCM patients is unknown. We evaluated 68 patients (female= 17) with DCM who underwent follow-up at the National Heart Centre, Singapore from 2013 through 2014. Clinical data were obtained and analyzed retrospectively. Genomic DNA was subjected to next-generation targeted sequencing. Nextera Rapid Capture Enrichment was used to capture the exons of a panel of 169 cardiac genes. DNA libraries were sequenced as paired-end 150-bp reads on Illumina MiSeq. Raw sequence reads were processed and analysed using standard bioinformatics techniques. The average age of onset of DCM was 46.1±10.21 years old. The average left ventricular ejection fraction (LVEF), left ventricular diastolic internal diameter (LVIDd), left ventricular systolic internal diameter (LVIDs) were 26.1±11.2%, 6.20±0.83cm, and 5.23±0.92cm respectively. The frequencies of mutations in major DCM-associated genes were as follows TTN (5.88% vs published frequency of 20%), LMNA (4.41% vs 6%), MYH7 (5.88% vs 4%), MYH6 (5.88% vs 4%), and SCN5a (4.41% vs 3%). The average callability at 10 times coverage of each major gene were: TTN (99.7%), LMNA (87.1%), MYH7 (94.8%), MYH6 (95.5%), and SCN5a (94.3%). In conclusion, TTN mutations are not common in Singaporean DCM patients. The frequencies of other major DCM-associated genes are comparable to frequencies published in the current literature.

Keywords: heart failure, dilated cardiomyopathy, genetics, next-generation sequencing

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Authors: M. Lloret-Climent, J. Nescolarde-Selva

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The aim of this paper is to propose a mathematical model to determine invariant sets, set covering, orbits and, in particular, attractors in the set of tourism variables. Analysis was carried out based on a pre-designed algorithm and applying our interpretation of chaos theory developed in the context of General Systems Theory. This article sets out the causal relationships associated with tourist flows in order to enable the formulation of appropriate strategies. Our results can be applied to numerous cases. For example, in the analysis of tourist flows, these findings can be used to determine whether the behaviour of certain groups affects that of other groups and to analyse tourist behaviour in terms of the most relevant variables. Unlike statistical analyses that merely provide information on current data, our method uses orbit analysis to forecast, if attractors are found, the behaviour of tourist variables in the immediate future.

Keywords: attractor, invariant set, tourist flows, orbits, social responsibility, tourism, tourist variables

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Authors: Tanakom Potjanapitak, Kevin Wongleedee

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The purpose of this research study was to study the level of satisfaction of the faculty members who participated in the ASEAN camp which aimed to prepare them for the readiness of AEC 2015. The population of this study included all the faculty members who participated in the activities of the ASEAN camp during April, 2014. Based on the survey of 120 faculty members who answered the questionnaire, the data was complied by using SPSS. Mean and standard deviation were utilized in analyzing the data. The findings revealed that the average mean of satisfaction was 4.41, and standard deviation was 0.7188. Moreover, the average mean can be used to rank the level of satisfaction from each of the following factors: helpful knowledge, understandable knowledge, proper materials, suitable knowledge, schedule of activities, staff, and advertising.

Keywords: ASEAN camp, training, satisfaction, human resources

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Authors: Xu Wang

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This research builds linear regressions of U.S. macroeconomic condition and volatility measures in the investment grade and high yield Credit Default Swap index spreads using monthly data from March 2009 to July 2016, to study the relationship between different dimensions of macroeconomy and overall credit risk quality. The most significant contribution of this research is systematically examining individual and joint effects of macroeconomic condition and volatility on CDX spreads by including macroeconomic time series that captures different dimensions of the U.S. economy. The industrial production index growth, non-farm payroll growth, consumer price index growth, 3-month treasury rate and consumer sentiment are introduced to capture the condition of real economic activity, employment, inflation, monetary policy and risk aversion respectively. The conditional variance of the macroeconomic series is constructed using ARMA-GARCH model and is used to measure macroeconomic volatility. The linear regression model is conducted to capture relationships between monthly average CDX spreads and macroeconomic variables. The Newey–West estimator is used to control for autocorrelation and heteroskedasticity in error terms. Furthermore, the sensitivity factor analysis and standardized coefficients analysis are conducted to compare the sensitivity of CDX spreads to different macroeconomic variables and to compare relative effects of macroeconomic condition versus macroeconomic uncertainty respectively. This research shows that macroeconomic condition can have a negative effect on CDX spread while macroeconomic volatility has a positive effect on determining CDX spread. Macroeconomic condition and volatility variables can jointly explain more than 70% of the whole variation of the CDX spread. In addition, sensitivity factor analysis shows that the CDX spread is the most sensitive to Consumer Sentiment index. Finally, the standardized coefficients analysis shows that both macroeconomic condition and volatility variables are important in determining CDX spread but macroeconomic condition category of variables have more relative importance in determining CDX spread than macroeconomic volatility category of variables. This research shows that the CDX spread can reflect the individual and joint effects of macroeconomic condition and volatility, which suggests that individual investors or government should carefully regard CDX spread as a measure of overall credit risk because the CDX spread is influenced by macroeconomy. In addition, the significance of macroeconomic condition and volatility variables, such as Non-farm Payroll growth rate and Industrial Production Index growth volatility suggests that the government, should pay more attention to the overall credit quality in the market when macroecnomy is low or volatile.

Keywords: autoregressive moving average model, credit spread puzzle, credit default swap spread, generalized autoregressive conditional heteroskedasticity model, macroeconomic conditions, macroeconomic uncertainty

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Authors: Hamid Reza Goshayeshi

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The effect of ɑ(alpha) Fe2O3 and ɤ(gamma)Fe2O3 particles on the heat transfer performance of an oscillating heat pipe was investigated experimentally. Kerosene was used as the base fluid for the OHP. Six size particles with average diameters of 10 nm, 20 nm, and 30 nm ɑFe2O3 and ɤFe2O3 were investigated, respectively. Experimental results show that the ɤFe2O3 particles added in the OHP significantly affect the heat transfer performance. When the OHP was charged with kerosene and 20 nm ɤ Fe2O3 particles, the OHP can achieve the best heat transfer performance among six particles investigated in this research.

Keywords: copper oscillating heat pipe, heat transfer, flow, comparison of ɑ(alpha)Fe2O3 and ɤ(gamma)Fe2O3, increase heat transfer

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Authors: Michael B. C. Khoo, J. L. Khoo, W. C. Yeong, W. L. Teoh

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The Shewhart Xbar control chart is a useful process monitoring tool in manufacturing industries to detect the presence of assignable causes. However, it is insensitive in detecting small process shifts. To circumvent this problem, adaptive control charts are suggested. An adaptive chart enables at least one of the chart’s parameters to be adjusted to increase the chart’s sensitivity. Two common adaptive charts that exist in the literature are the double sampling (DS) Xbar and variable sampling interval (VSI) Xbar charts. This paper compares the performances of the DS and VSI Xbar charts, based on the average time to signal (ATS) criterion. The ATS profiles of the DS Xbar and VSI Xbar charts are obtained using the Mathematica and Statistical Analysis System (SAS) programs, respectively. The results show that the VSI Xbar chart is generally superior to the DS Xbar chart.

Keywords: adaptive charts, average time to signal, double sampling, charts, variable sampling interval

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Authors: Charline David, Alexandre Blondin Massé, Arnaud Zinflou

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In 2016, Clements, Hurn, and Li proposed a multiple equation time series approach for the short-term load forecasting, reporting an average mean absolute percentage error (MAPE) of 1.36% on an 11-years dataset for the Queensland region in Australia. We present an adaptation of their model to the electrical power load consumption for the whole Quebec province in Canada. More precisely, we take into account two additional meteorological variables — cloudiness and wind speed — on top of temperature, as well as the use of multiple meteorological measurements taken at different locations on the territory. We also consider other minor improvements. Our final model shows an average MAPE score of 1:79% over an 8-years dataset.

Keywords: short-term load forecasting, special days, time series, multiple equations, parallelization, clustering

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Authors: A. Bentley, A. Prost, N. Daruwalla, D. Osrin

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Background: This study aims to investigate the relationship between experiences of violence against women in the family, and levels of self-esteem in women residing in informal settlement (slum) areas of Mumbai, India. The authors hypothesise that violence against women in Indian households extends beyond that of intimate partner violence (IPV), to include other members of the family and that experiences of violence are associated with lower levels of self-esteem. Methods: Experiences of violence were assessed through a cross-sectional survey of 598 women, including questions about specific acts of emotional, economic, physical and sexual violence across different time points, and the main perpetrator of each. Self-esteem was assessed using the Rosenberg self-esteem questionnaire. A global score for self-esteem was calculated and the relationship between violence in the past year and Rosenberg self-esteem score was assessed using multivariable linear regression models, adjusted for years of education completed, and clustering using robust standard errors. Results: 482 (81%) women consented to interview. On average, they were 28.5 years old, had completed 6 years of education and had been married 9.5 years. 88% were Muslim and 46% lived in joint families. 44% of women had experienced at least one act of violence in their lifetime (33% emotional, 22% economic, 24% physical, 12% sexual). Of the women who experienced violence after marriage, 70% cited a perpetrator other than the husband for at least one of the acts. 5% had low self-esteem (Rosenberg score < 15). For women who experienced emotional violence in the past year, the Rosenberg score was 2.6 points lower (p < 0.001). It was 1.2 points lower (p = 0.03) for women who experienced economic violence. For physical or sexual violence in the past year, no statistically significant relationship with Rosenberg score was seen. However, for a one-unit increase in the number of different acts of each type of violence experienced in the past year, a decrease in Rosenberg score was seen (-0.62 for emotional, -0.76 for economic, -0.53 for physical and -0.47 for sexual; p < 0.05 for all). Discussion: The high prevalence of violence experiences across the lifetime was likely due to the detailed assessment of violence and the inclusion of perpetrators within the family other than the husband. Experiences of emotional or economic violence in the past year were associated with lower Rosenberg scores and therefore lower self-esteem, but no relationship was seen between experiences of physical or sexual violence and Rosenberg score overall. For all types of violence in the past year, a greater number of different acts were associated with a decrease in Rosenberg score. Emotional violence showed the strongest relationship with self-esteem, but for all types of violence the more complex the pattern of perpetration with different methods used, the lower the levels of self-esteem. Due to the cross-sectional nature of the study causal directionality cannot be attributed. Further work to investigate the relationship between severity of violence and self-esteem and whether self-esteem mediates relationships between violence and poorer mental health would be beneficial.

Keywords: family violence, India, informal settlements, Rosenberg self-esteem scale, self-esteem, violence against women

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Authors: Zahra Khoshnood, Mehdi Kazaie, Sajedeh Neisi

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In 2013, 24 fish samples were taken from two fishery regions in the north of Persian Gulf near the Iranian coastal lines. The two flatfishes were Yellofin seabream (Acanthopagrus latus) and Longtail tuna (Thannus tonggol). We analyzed total Hg concentration of liver and muscle tissues by Mercury Analyzer (model LECO AMA 254). The average concentration of total Hg in edible Muscle tissue of deep-Flounder was measured in Bandar-Abbas and was found to be 18.92 and it was 10.19 µg.g-1 in Bandar-Lengeh. The corresponding values for Oriental sole were 8.47 and 0.08 µg.g-1. The average concentration of Hg in liver tissue of deep-Flounder, in Bandar-Abbas was 25.49 and that in Bandar-Lengeh was 12.52 µg.g-1.the values for Oriental sole were 11.88 and 3.2 µg.g-1 in Bandar-Abbas and Bandar-Lengeh, respectively.

Keywords: mercury, Acanthopagrus latus, Thannus tonggol, Persian Gulf

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Authors: Mohsen Varzande

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Translators’ professional and academic characteristics may directly influence their translation quality. The present study aimed at investigating whether translators’ degree in translation and years of professional experience predict their translation quality. Following a causal-comparative study, a sample of one hundred professional translators was selected using purposive sampling method. The participants were divided into two groups each containing individuals with and without a degree in translation, respectively. The participants were asked to translate a paragraph to assess their translation quality. For data analysis, appropriate statistical procedures including correlation and regression were used. Results showed that both degree in translation and years of professional experience significantly predict translation quality. Also, the interaction of translators’ years of professional experience and degree in translation significantly affect their translation quality. An implication could be that besides providing translators with academic knowledge and theories, practical training in translation is necessary as a prerequisite for a competent translator.

Keywords: translation, degree in translation, translation quality, professional experience

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Authors: Singh Deepeshwar, N. K. Manjunath, M. Avinash

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Meditation is a self-regulated conscious process associated with improved awareness, perception, attention and overall performance. Different traditional origin of meditation technique may have different effects on autonomic activity and brain functions. Based on this quest, the present study evaluated the effect of Tai-Chi Chuan (TCC, a Chines movement based meditation technique) and Cyclic Meditation (CM, an Indian traditional based stimulation and relaxation meditation technique) on the hemodynamic responses of the prefrontal cortex (PFC) and autonomic functions (such as R-R interval of heart rate variability and respiration). These two meditation practices were compared with simple walking. Employing 64 channel near infrared spectroscopy (NIRS), we measured hemoglobin concentration change (i.e., Oxyhemoglobin [ΔHbO], Deoxyhemoglobin [ΔHbR] and Total hemoglobin change [ΔTHC]) in the bilateral PFC before and after TCC, CM and Walking in young college students (n=25; average mean age ± SD; 23.4 ± 3.1 years). We observed the left PFC activity predominantly modulates sympathetic activity effects during the Tai-Chi whereas CM showed changes on right PFC with vagal dominance. However, the changes in oxyhemoglobin and total blood volume change after Tai-Chi was significant higher (p < 0.05, spam t-maps) on the left hemisphere, whereas after CM, there was a significant increase in oxyhemoglobin (p < 0.01) with a decrease in deoxyhemoglobin (p < 0.05) on right PFC. The normal walking showed decrease in Oxyhemoglobin with an increase in deoxyhemoglobin on left PFC. The autonomic functions result showed a significant increase in RR- interval (p < 0.05) along with significant reductions in HR (p < 0.05) in CM, whereas Tai-chi session showed significant increase in HR (p < 0.05) when compared to walking session. Within a group analysis showed a significant reduction in RR-I and significant increase in HR both in Tai-chi and walking sessions. The CM showed there were a significant improvement in the RR - interval of HRV (p < 0.01) with the reduction of heart rate and breath rate (p < 0.05). The result suggested that Tai-Chi and CM both have a positive effect on left and right prefrontal cortex and increase sympathovagal balance (alertful rest) in autonomic nervous system activity.

Keywords: brain, hemodynamic responses, yoga, meditation, Tai-Chi Chuan (TCC), walking, heart rate variability (HRV)

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Authors: Enikő Bene

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Our sowing date experiment took place in the Demonstration Garden of Institution of Plant Sciences, Agricultural Center of University of Debrecen, in 2012-2014. The thesis contains data of test year 2014. Our purpose, besides several other examinations, was to observe how sowing date influences leaf area index and activity of photosynthesis of maize hybrids, and how those factors affect fruiting. In the experiment we monitored the change of the leaf area index and the photosynthesis of hybrids with four different growing seasons. The results obtained confirm that not only the environmental and agricultural factors in the growing season have effect on the yield, but also other factors like the leaf area index and the photosynthesis are determinative parameters, and all those factors together, modifying effects of each other, develop average yields

Keywords: sowing date, hybrid, leaf area index, photosynthetic capacity

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Authors: A. Swetha

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This study aims to prioritize and explore critical risks in construction project assessment, employing the Weighted Average Index method and Principal Component Analysis (PCA). Through extensive literature review and expert interviews, project assessment risk factors were identified across Budget and Cost Management Risk, Schedule and Time Management Risk, Scope and Planning Risk, Safety and Regulatory Compliance Risk, Resource Management Risk, Communication and Stakeholder Management Risk, and Environmental and Sustainability Risk domains. A questionnaire was distributed to stakeholders involved in construction activities in Hyderabad, India, with 180 completed responses analyzed using the Weighted Average Index method to prioritize risk factors. Subsequently, PCA was used to understand relationships between these factors and uncover underlying patterns. Results highlighted dependencies on critical resources, inadequate risk assessment, cash flow constraints, and safety concerns as top priorities, while factors like currency exchange rate fluctuations and delayed information dissemination ranked lower but remained significant. These insights offer valuable guidance for stakeholders to mitigate risks effectively and enhance project outcomes. By adopting systematic risk assessment and management approaches, construction projects in Hyderabad and beyond can navigate challenges more efficiently, ensuring long-term viability and resilience.

Keywords: construction project assessment risk factor, risk prioritization, weighted average index, principal component analysis, project risk factors

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Authors: Eyyup Murat Karakurt, Yan Huang, Mehmet Kaya, Huseyin Demirtas

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In this study, the effect of the porosity effect of Ti-20Zr alloy produced by powder metallurgy as a biomaterial was investigated experimentally. The Ti based alloys (Ti-20%Zr (at.) were produced under 300 MPa, for 6 h at 1200 °C. Afterward, the microstructure of the Ti-based alloys was analyzed by optical analysis, scanning electron microscopy, energy dispersive spectrometry. Moreover, compression tests were applied to determine the mechanical behaviour of samples. As a result, highly porous Ti-20Zr alloys exhibited an elastic modulus close to human bone. The results later were compared theoretically and experimentally.

Keywords: porosity effect, Ti based alloys, elastic modulus, compression test

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Authors: A. A. Azab

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In this work, Sm0.6Sr0.4CoxMn1-xO3 (x=0, 0.1, 0.2 and 0.3) was synthesized by sol-gel method for magnetocaloric effect (MCE) applications. XRD analysis confirmed formation of the required orthorhombic phase of perovskite, and there is crystallographic phase transition as a result of substitution. Maxwell-Wagner interfacial polarisation and Koops phenomenological theory were used to investigate and analyze the temperature and frequency dependency of the dielectric permittivity. The phase transition from the ferromagnetic to the paramagnetic state was demonstrated to be second order. Based on the isothermal magnetization curves obtained at various temperatures, the magnetic entropy change was calculated. A magnetocaloric effect (MCE) over a wide temperature range was studied by determining DSM and the relative cooling power (RCP).

Keywords: magnetocaloric effect, pperovskite, magnetic phase transition, dielectric permittivity

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Authors: Sharmili Routray, Kishor Chandra Biswal

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The use of corrosion resistant fiber reinforced polymer (FRP) reinforcement is beneficial in structures particularly those exposed to deicing salts, and/or located in highly corrosive environment. Generally Glass, Carbon and Aramid fibers are used for the strengthening purpose of the structures. Due to the necessities of low weight and high strength materials, it is required to find out the suitable substitute with low cost. Recent developments in fiber production technology allow the strengthening of structures using Basalt fiber which is made from basalt rock. Basalt fiber has good range of thermal performance, high tensile strength, resistance to acids, good electro‐magnetic properties, inert nature, resistance to corrosion, radiation and UV light, vibration and impact loading. This investigation focuses on the effect of fibre content and fiber orientation of basalt fibre on mechanical properties of the fabricated composites. Specimen prepared with unidirectional Basalt fabric as reinforcing materials and epoxy resin as a matrix in polymer composite. In this investigation different fiber orientation are taken and the fabrication is done by hand lay-up process. The variation of the properties with the increasing number of plies of fiber in the composites is also studied. Specimens are subjected to tensile strength test and the failure of the composite is examined with the help of INSTRON universal testing Machine (SATEC) of 600 kN capacities. The average tensile strength and modulus of elasticity of BFRP plates are determined from the test Program.

Keywords: BFRP, fabrication, Fiber Reinforced Polymer (FRP), strengthening

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Authors: Abiodun M. Adeola, Hannes Rautenbach, Gbenga J. Abiodun, Thabo E. Makgoale, Joel O. Botai, Omolola M. Adisa, Christina M. Botai

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There was a surge in malaria morbidity as well as mortality in 2016/2017 malaria season in malaria-endemic regions of South Africa. Rainfall is a major climatic driver of malaria transmission and has potential use for predicting malaria. Annual and seasonal trends and cross-correlation analyses were performed on time series of monthly total rainfall (derived from interpolated weather station data) and monthly malaria cases in five districts of Limpopo Province for the period of 1998 to 2017. The time series analysis indicated that an average of 629.5mm of rainfall was received over the period of study. The rainfall has an annual variation of about 0.46%. Rainfall amount varies among the five districts, with the north-eastern part receiving more rainfall. Spearman’s correlation analysis indicated that total monthly rainfall with one to two months lagged effect is significant in malaria transmission in all the five districts. The strongest correlation is noticed in Mopani (r=0.54; p-value = < 0.001), Vhembe (r=0.53; p-value = < 0.001), Waterberg (r=0.40; p-value = < 0.001), Capricorn (r=0.37; p-value = < 0.001) and lowest in Sekhukhune (r=0.36; p-value = < 0.001). More particularly, malaria morbidity showed a strong relationship with an episode of rainfall above 5-year running means of rainfall of 400 mm. Both annual and seasonal analyses showed that the effect of rainfall on malaria varied across the districts and it is seasonally dependent. Adequate understanding of climatic variables dynamics annually and seasonally is imperative in seeking answers to malaria morbidity among other factors, particularly in the wake of the sudden spike of the disease in the province.

Keywords: correlation, malaria, rainfall, seasonal, trends

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Authors: Suzan Arslanturk, Mohammad-Reza Siadat, Theophilus Ogunyemi, Ananias Diokno

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Missing data is a common challenge in statistical analyses of most clinical survey datasets. A variety of methods have been developed to enable analysis of survey data to deal with missing values. Imputation is the most commonly used among the above methods. However, in order to minimize the bias introduced due to imputation, one must choose the right imputation technique and apply it to the correct type of missing data. In this paper, we have identified different types of missing values: missing data due to skip pattern (SPMD), undetermined missing data (UMD), and genuine missing data (GMD) and applied rough set imputation on only the GMD portion of the missing data. We have used rough set imputation to evaluate the effect of such imputation on prediction by generating several simulation datasets based on an existing epidemiological dataset (MESA). To measure how well each dataset lends itself to the prediction model (logistic regression), we have used p-values from the Wald test. To evaluate the accuracy of the prediction, we have considered the width of 95% confidence interval for the probability of incontinence. Both imputed and non-imputed simulation datasets were fit to the prediction model, and they both turned out to be significant (p-value < 0.05). However, the Wald score shows a better fit for the imputed compared to non-imputed datasets (28.7 vs. 23.4). The average confidence interval width was decreased by 10.4% when the imputed dataset was used, meaning higher precision. The results show that using the rough set method for missing data imputation on GMD data improve the predictive capability of the logistic regression. Further studies are required to generalize this conclusion to other clinical survey datasets.

Keywords: rough set, imputation, clinical survey data simulation, genuine missing data, predictive index

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Authors: Zakaria Boual, Abdellah Kemassi, Toufik Chouana, Philippe Michaud, Mohammed Didi Ould El Hadj

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In order to investigate the prebiotic potential of oligosaccharides prepared by chemical hydrolysis of water-soluble polysaccharides (WSP) from Zizyphus lotus leaves, the effect of oligosaccharides on bacterial growth was studied. The chemical composition of WSP was evaluated by colorimetric assays revealed the average values: 7.05±0.73% proteins and 86.21±0.74% carbohydrates, among them 64.81±0.42% are neutral sugar and the rest 16.25±1.62% are uronic acids. The characterization of monosaccharides was determined by high performance anion exchange chromatography with pulsed amperometric detection (HPAEC-PAD) was found to be composed of galactose (23.95%), glucose (21.30%), rhamnose (20.28%), arabinose (9.55%), and glucuronic acid (22.95%). The effects of oligosaccharides on the growth of lactic acid bacteria were compared with those of fructo-oligosaccharide (RP95). The oligosaccharides concentration was 1g/L of man rogosa sharpe broth. Bacterial growth was assessed during 2, 4.5, 6.5, 9, 12, 16 and 24 h by measuring the optical density of the cultures at 600 nm (OD600) and pH values. During fermentation, pH in broth cultures decreased from 6.7 to 5.87±0.15. The enumeration of lactic acid bacteria indicated that oligosaccharides led to a significant increase in bacteria (P≤0.05) compared to the control. The fermentative metabolism appeared to be faster on RP95 than on oligosaccharides from Zizyphus lotus leaves. Both RP95 and oligosaccharides showed clear prebiotic effects, but had differences in fermentation kinetics because of to the different degree of polymerization. This study shows the prebiotic effectiveness of oligosaccharides, and provides proof for the selection of leaves of Zizyphus lotus for use as functional food ingredients.

Keywords: Zizyphus lotus, polysaccharides, characterization, prebiotic effects

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Authors: Tsetsegmaa A., Bayarsuren B., Altantsetseg Ts.

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To make the best decision on reducing harmful emissions from buses, we need to have a clear understanding of the current state of their actual emissions. The emissions from city buses running on high sulfur fuel, particularly particulate matter (PM) and nitrogen oxides (NOx) from the exhaust gases of conventional diesel engines, have been studied and measured with and without diesel particulate filter (DPF) in Ulaanbaatar city. The study was conducted by using the PEMS (Portable Emissions Measurement System) and gravimetric method in real traffic conditions. The obtained data were used to determine the actual emission rates and to evaluate the effectiveness of the selected particulate filters. Actual road and daily PM emissions from city buses were determined during the warm and cold seasons. A bus with an average daily mileage of 242 km was found to emit 166.155 g of PM into the city's atmosphere on average per day, with 141.3 g in summer and 175.8 g in winter. The actual PM of the city bus is 0.6866 g/km. The concentration of NOx in the exhaust gas averages 1410.94 ppm. The use of DPF reduced the exhaust gas opacity of 24 buses by an average of 97% and filtered a total of 340.4 kg of soot from these buses over a period of six months. Retrofitting an old conventional diesel engine with cassette-type silicon carbide (SiC) DPF, despite the laboriousness of cleaning, can significantly reduce particulate matter emissions. Innovation: First comprehensive road PM and NOx emission dataset and actual road emissions from public buses have been identified. PM and NOx mathematical model equations have been estimated as a function of the bus technical speed and engine revolution with and without DPF.

Keywords: conventional diesel, silicon carbide, real-time onboard measurements, particulate matter, diesel retrofit, fuel sulphur

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Authors: A. Gharaei, R. Karami

Abstract:

Rutilus frisii Kutum was exposed to various concentrations of mercuric chloride in water to determine its acute toxicity and bioaccumulation. We carried out ten treatments with three replicates and one control for each of the chemicals using the static O. E. C. D. method in 55-liter-tanks each containing 14 fingerlings. During the experiments, the average pH was recorded as 7.8, total hardness was measured to be 255 mg/l, the average water temperature was 27±1 degrees centigrade and dissolved oxygen was 7.2 mg/l. Mean LC50 values of Hgcl2 for juvenile R. frisii kutum with mean weight 1±0.2 gr were 0.102 and 0.86 mgHg/l at 24h and 96h, respectively. The bioaccumulation values during 24h in tissue, kidney, and gill were 1.55, 16.1, and 22.7 mgHg/l, respectively. So, these values during 96h were 2.8, 16.8, and 26.65 mgHg/l, respectively. The bioconcentration factors in tissue, kidney, and gill during 24h were 14.75, 153.39, and 216.11 and so during 96h were 33.8, 198.1, and 313.5 times. These results show that bioaccumulation was highest in the gill and then kidney and tissue, respectively. This study suggested that between mercury concentrations of water with bioaccumulation in tissue more than kidney and gill.

Keywords: HgCl2, LC5096h, bioaccumulation, Rutilus frisii Kutum, Caspian Sea

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Authors: Amit Kumar, Jaikumar V, Pradeep AG, Shivakumar Bhavi

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Reducing sloshing is one of the major challenges in industries where transporting of liquid involved. The present study investigates the sloshing effect for different liquid levels 25%, 50%, and 75% of the tank capacity. CFD simulation for three different liquid levels has been carried out using a time-based multiphase Volume of fluid (VOF) scheme. Baffles were introduced to examine the sloshing effect inside the tank. Results were compared against the baseline case to assess the effectiveness of baffles. Maximum liquid height over the period of the simulation was considered as the parameter for measuring the sloshing effect inside the tank. It was found that the addition of baffles reduced the sloshing effect inside the tank as compared to the baseline model.

Keywords: sloshing, CFD, VOF, baffles

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Authors: Ross Guest, Bjarne Jensen

Abstract:

This paper analyses a potentially new consumption dividend from lower fertility arising from imperfect labour substitution by age. A smaller proportion of young workers relative to older workers raises relative youth wages given imperfect labour substitution by age. Discounted lifetime labour income rises which provides a consumption dividend. Simulation results are reported for the four Scandinavian countries, adopting a simple overlapping generations model. Imperfect labour substitution is modelled using a CRESH functional form of an aggregate labour index. The magnitudes of this new consumption dividend from a Low fertility projection compared with a high fertility projection are found to be approximately 4 percent annually, on average over the Scandinavian countries in the very long run, but somewhat lower in the short term. There is some sensitivity to the interest rate and the degree of consumption smoothing.

Keywords: fertility, consumption, productivity, labour substitution

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Authors: Siwanit Autthawuttikul, Prakob Koraneekid, Sayamon Insa-ard

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The purposes of this research were to development creatively integrated teaching skills using Information and Communication Technology (ICT) for professional teacher in schools under the education area of the basic education commission, ministry of education both schools under the office of primary education and those under The office of secondary education in eight western region provinces of Thailand. This is useful in defining a vision for the school strategy and restructuring schools in addition, teachers will have developed skills in teaching creative integrated ICT. The research methodology comprises quantitative and qualitative data collection. The Baseline Survey, focus group for discussions and then the model was developed creatively integrated teaching skills using ICT. The findings showed that 7 elements were important: (1) Academy Transformation (2) Information Technology Infrastructure (3) Personal Development (4) Supervision, Monitoring and Evaluation (5) Motivating and Rewarding (6) Important factor affecting the success of teaching integrated with ICT were knowledge, skills, attitudes and (7) The role of the individual concerned. The comparison creatively integrated teaching skills before and after participating in the overall shows that the average creatively integrated teaching skills using ICT after attending the event is 3.27, and standard deviation was 0.56, higher than before which is 2.60 and the standard deviation was 0.56. There are significant differences significant statistically level of .05. The final average score of the evaluation plan design creatively integrated teaching skills using ICT teachers' average score was 26.94 at the high levels.

Keywords: integrated curriculum, information and communications technology, teachers in the western region, schools

Procedia PDF Downloads 440