Search results for: salinity indices

Authors: Hamed A. El-Serehy, Khaled A. Al-Rasheid, Fahad A. Al-Misned

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The composition and distribution of the benthic meiofauna assemblages of the Egyptian coasts along the Red Sea are described in relation to abiotic variables. Sediment samples were collected seasonally from twelve stations chosen along the northern part of the Red Sea to observe the meiofaunal community structure, its temporal distribution and horizontal fluctuation in relation to environmental conditions of the Red Sea marine ecosystem. The meiofaunal assemblage in the area of study was well diversified including 140 taxa. The temperature, salinity, pH, dissolved oxygen, and redox potential were measured at the time of collection. The water content of the sediments, total organic matters and chlorophyll a values were determined, and sediment samples were subjected to granulometric analysis. A total of 10 meiofauna taxa were identified, with the meiofauna being primarily represented by nematodes (on annual average from 42% to 84%), harpacticoids, polycheates and ostracodes; and the meiofauna abundances ranging from 41- to 167 ind. / 10 cm2. The meiofaunal population density fluctuated seasonally with a peak of 192.52 ind. / 10 cm2 during summer at station II. The vertical zonation in the distribution of meiofaunal community was significantly correlated with interstitial water, chlorophyll a and total organic matter values. The present study indicates that the existing of well diversified meiofaunal group which can serve as food for higher trophic levels in the Red Sea interstitial environment.

Keywords: benthos, diversity, meiofauna, Red Sea

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Authors: Nasrin Akter, Prem Chhetri, Shams Rahman

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The present study tested Ajzen’s Theory of Planned Behavior (TPB) model to explain the formation of business customers’ intention to use 3PL services in Bangladesh. The findings show that the TPB model has a good fit to the data. Based on theoretical support and suggested modification indices, a refined TPB model was developed afterwards which provides a better predictive power for intention. Consistent with the theory, the results of a structural equation analysis revealed that the intention to use 3PL services is predicted by attitude and subjective norms but not by perceived behavioral control. Further investigation indicated that the paths between (attitude and intention) and (subjective norms and intention) did not statistically differ between 3PL user and non-user. Findings of this research provide an evidence base to formulate business strategies to increase the use of 3PL services in Bangladesh to enhance productivity and to gain economic efficiency.

Keywords: Bangladesh, intention, third-party logistics, Theory of Planned Behavior

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Authors: Gona Ayuba, Isiaka Mohammed, Kotom Mohammed Baba, Mohammed Aabubakar Maikasuwa

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The study examined the technical efficiency and its determinants of cattle fattening enterprises in Kebbi state, Nigeria. Data were collected from a sample of 160 fatteners between June 2010 and June 2011 using the multistage random sampling technique. Translog stochastic frontier production function was employed for the analysis. Results of the analysis show that technical efficiency indices varied from 0.74 to 0.98%, with a mean of 0.90%, indicating that there was no wide gap between the efficiency of best technical efficient fatteners and that of the average fattener. The result also showed that fattening experience and herd size influenced the level of technical efficiency at 1% levels. It is recommended that credit agencies should ensure that credit made available to the fatteners is monitored to ensure appropriate utilization.

Keywords: technical efficiency, determinants, cattle, fattening enterprises

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Authors: Aisami A., Z. A. Adamu, Lawan Bulama

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Due to growing issues of crude oil pollution in both marine and terrestrial environments, Billions to Trillions of US Dollars were spent over the years for the treatment of this spill. There is an urgent need for effective bioremediation strategies. This current study focuses on the isolation and characterization of a crude oil-degrading bacterium from hydrocarbon-contaminated soil samples. Soil samples were collected from an oil spill site and subjected to enrichment culture techniques in a mineral salt medium supplemented with crude oil as the singular carbon source. The isolates were screened for their crude oil-degrading capabilities using gravimetric analysis. The most efficient isolation was identified through 16S rRNA gene sequencing. Cultural and physical conditions such pH, temperature salinity and crude oil concentrations were optimized. The isolates showed significant crude oil degradation efficiency, reducing oil concentration (2.5%) by 75% within 15 days of incubation. The strain was identified as Providencia sp. through molecular characterization, the sequence was deposited at the NCBI Genbank with accession number MN880494. The bacterium exhibited optimal growth at 32.5°C, pH 7.0 to 7.5, and in the presence of 1.5% (w/v) NaCl. The isolated Providencia sp. shows encouraging potential for bioremediation of crude oil-contaminated environments. This study successfully isolated and characterized a crude oil-degrading Providencia sp., highlighting its potential in bioremediation.

Keywords: crude oil degradation, providencia sp., bioremediation, hydrocarbon utilization, environmental pollution.

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Authors: Hyun-Woo Cho

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For ensuring the safety of a manufacturing process one should quickly identify an assignable cause of a fault in an on-line basis. To this end, many statistical techniques including linear and nonlinear methods have been frequently utilized. However, such methods possessed a major problem of small sample size, which is mostly attributed to the characteristics of empirical models used for reference models. This work presents a new method to overcome the insufficiency of measurement data in the monitoring and diagnosis tasks. Some quasi-measurement data are generated from existing data based on the two indices of similarity and importance. The performance of the method is demonstrated using a real data set. The results turn out that the presented methods are able to handle the insufficiency problem successfully. In addition, it is shown to be quite efficient in terms of computational speed and memory usage, and thus on-line implementation of the method is straightforward for monitoring and diagnosis purposes.

Keywords: data analysis, diagnosis, monitoring, process data, quality control

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Authors: Jayeola Olabisi, T. Olawale Oladunjoye, Ademola A. Adewumi

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The study empirically examines the relationship that exists between the economic environment and entrepreneurial development in Nigeria. A structured questionnaire is administered on the study and data collected are analysed using Analysis of Variance and Regression. The following variables are indices of determination; Interest Rate (IR); Income Tax (IT). The results of the study show that there is a significant relationship between IR and ED in Nigeria (p < 0.5) with a positive correlation (r=0.526, r2=0.276). Also, there is a significant relationship between IT and ED in Nigeria (p < 0.05), with a positive association (r=0.546; r2=0.299). The study concludes that the emergence of the higher level of the stable economic environment is critical to entrepreneurial development in Nigeria. Therefore, government involvement in public private partnership for infrastructural development, enlargement of productive, judicious and transparent use of funds collected from income tax and affordable interest rate will galvanise the inward sourcing of raw materials that boost entrepreneurial development in Nigeria.

Keywords: interest rate, income tax, business environment and entrepreneurial development

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Authors: Mohamad H. Atyeh, Wael Alrashed, Steven Telford

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The main objective of this research is to measure if there have been any notable changes in the trading actives of the Kuwait stock Exchange (KSE) after the privatization process that took place on the 25th of April 2016. The data that are used to test if there is any change in the KSE market performance are the daily indices for the period from the 25th of April 2016 till the 24th of October 2016 (after privatization) and a similar six months period before the date of the privatization from the 24th of October 2015 till the 24th of April 2016. In addition, as a control, the study included a period that is a period parallel to the six months period after the privatization. The results indicate that privatization is associated with lower variability for the majority of variables, but that the observed switch in slope direction is not actually a product of privatization, but rather one of serial correlation.

Keywords: privatization, Kuwait stock exchange (KSE), market capitalization (MCAP), capital markets authority (CMA), Boursa Kuwait securities company (BKSC)

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Authors: Maruska Vizek, Josip Glaurdic, Marina Tkalec, Goran Vuksic

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We empirically explore whether and how taxation affects bilateral real exchange rates in the euro area – relative unit labor costs and relative consumer price indices. We find that employers’ social security contributions and the value added tax changes have the expected effects put forward in the fiscal devaluation literature and simulations. Increases in employers’ contributions appreciate the relative unit labor costs in the short- and the long-run, while value added tax hike appreciates the relative consumer prices. Somewhat surprisingly, for personal income tax increases, we find a short-run depreciating impact on the relative unit labor costs, while increases in employees’ contributions depreciate both measures of real exchange rates in the short-run.

Keywords: sovereign bonds, European Union, developing countries, political determinants

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Authors: Reshma Raskar-Phule, Abhay Shinde, Manesh Konkani, Rohit Nighot, Shrirang Mahajan, Viraj Thorat

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Sustainability in construction projects can be considered from three dimensions - environment, economy and society. Key concepts of sustainable construction include the protection of the natural environment, choice of non-toxic materials, reduction and reuse of resources, waste minimization, and life cycle analysis. The present paper attempts to identify and analyze the use of sustainable construction materials for a new college hostel building in terms of sustainability development indices (SDIs). Low SDI materials, say as composite fiberglass reinforcement (SDI 4074.96), compressed earth blocks (SDI 0.47), and fiber-reinforced doors (SDI 0.13) are the proposed sustainable materials for the hostel building. Indian Green Building Certification (IGBC) is applied for the hostel building and it earns 5 points out of total 16 points for criterion 5 – Building Materials and Resources of IGBC.

Keywords: sustainable development, construction materials, IGBC, hostel building

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Authors: Subhash Chandra Sharma, Mohammad Soleimani

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Selection of the correct lubricant for the top of rail application is a complex process. In this paper, the selection of the proper lubricant for a Top-Of-Rail (TOR) lubrication system based on graph theory and matrix approach has been developed. Attributes influencing the selection process and their influence on each other has been represented through a digraph and an equivalent matrix. A matrix function which is called the Permanent Function is derived. By substituting the level of inherent contribution of the influencing parameters and their influence on each other qualitatively, a criterion called Suitability Index is derived. Based on these indices, lubricants can be ranked for their suitability. The proposed model can be useful for maintenance engineers in selecting the best lubricant for a TOR application. The proposed methodology is illustrated step–by-step through an example.

Keywords: lubricant selection, top of rail lubrication, graph-theory, Ranking of lubricants

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Authors: Lidia Sanchis-Marco, Antonio Rubia

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In this paper we analyze the state-dependent risk-spillover in different economic areas. To this end, we apply the quantile regression-based methodology developed in Adams, Füss and Gropp approach to examine the spillover in conditional tails of daily returns of indices of the banking industry in the US, BRICs, Peripheral EMU, Core EMU, Scandinavia, the UK and Emerging Markets. This methodology allow us to characterize size, direction and strength of financial contagion in a network of bilateral exposures to address cross-border vulnerabilities under different states of the economy. The general evidence shows as the spillover effects are higher and more significant in volatile periods than in tranquil ones. There is evidence of tail spillovers of which much is attributable to a spillover from the US on the rest of the analyzed regions, specially on European countries. In sharp contrast, the US banking system show more financial resilience against foreign shocks.

Keywords: spillover effects, Bank Contagion, SDSVaR, expected shortfall, VaR, expectiles

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Authors: Ofelia Loani Elvir Lazo, Roya Yumul, Sevan Komshian, Ruby Wang, Jun Tang

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Background: Monitoring the anti-nociceptive drug effect is useful because a sudden and strong nociceptive stimulus may result in untoward autonomic responses and muscular reflex movements. Monitoring the anti-nociceptive effects of perioperative medications has long been desiredas a way to provide anesthesiologists information regarding a patient’s level of antinociception and preclude any untoward autonomic responses and reflexive muscular movements from painful stimuli intraoperatively.To this end, electroencephalogram (EEG) based tools includingBIS and qCON were designed to provide information about the depth of sedation whileqNOXwas produced to informon the degree of antinociception.The goal of this study was to compare the reliability of qCON/qNOX to BIS asspecific indicators of response to nociceptive stimulation. Methods: Sixty-two patients undergoing general anesthesia with LMA were included in this study. Institutional Review Board(IRB) approval was obtained, and informed consent was acquired prior to patient enrollment. Inclusion criteria included American Society of Anesthesiologists (ASA) class I-III, 18 to 80 years of age, and either gender. Exclusion criteria included the inability to consent. Withdrawal criteria included conversion to endotracheal tube and EEG malfunction. BIS and qCON/qNOX electrodes were simultaneously placed o62n all patientsprior to induction of anesthesia and were monitored throughout the case, along with other perioperative data, including patient response to noxious stimuli. All intraoperative decisions were made by the primary anesthesiologist without influence from qCON/qNOX. Student’s t-distribution, prediction probability (PK), and ANOVA were used to statistically compare the relative ability to detect nociceptive stimuli for each index. Twenty patients were included for the preliminary analysis. Results: A comparison of overall intraoperative BIS, qCON and qNOX indices demonstrated no significant difference between the three measures (N=62, p> 0.05). Meanwhile, index values for qNOX (62±18) were significantly higher than those for BIS (46±14) and qCON (54±19) immediately preceding patient responses to nociceptive stimulation in a preliminary analysis (N=20, * p= 0.0408). Notably, certain hemodynamic measurements demonstrated a significant increase in response to painful stimuli (MAP increased from74±13 mm Hg at baseline to 84± 18 mm Hg during noxious stimuli [p= 0.032] and HR from 76±12 BPM at baseline to 80±13BPM during noxious stimuli[p=0.078] respectively). Conclusion: In this observational study, BIS and qCON/qNOX provided comparable information on patients’ level of sedation throughout the course of an anesthetic. Meanwhile, increases in qNOX values demonstrated a superior correlation to an imminent response to stimulation relative to all other indices.

Keywords: antinociception, bispectral index (BIS), general anesthesia, laryngeal mask airway, qCON/qNOX

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Authors: Elham Koohi, Silvio Jose Gumiere, Hossein Bonakdari, Saeid Homayouni

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Water used in agricultural crops can be managed by irrigation scheduling based on soil moisture levels and plant water stress thresholds. Automated irrigation scheduling limits crop physiological damage and yield reduction. Knowledge of crop water stress monitoring approaches can be effective in optimizing the use of agricultural water. Understanding the physiological mechanisms of crop responding and adapting to water deficit ensures sustainable agricultural management and food supply. This aim could be achieved by analyzing and diagnosing crop characteristics and their interlinkage with the surrounding environment. Assessments of plant functional types (e.g., leaf area and structure, tree height, rate of evapotranspiration, rate of photosynthesis), controlling changes, and irrigated areas mapping. Calculating thresholds of soil water content parameters, crop water use efficiency, and Nitrogen status make irrigation scheduling decisions more accurate by preventing water limitations between irrigations. Combining Remote Sensing (RS), the Internet of Things (IoT), Artificial Intelligence (AI), and Machine Learning Algorithms (MLAs) can improve measurement accuracies and automate irrigation scheduling. This paper is a review structured by surveying about 100 recent research studies to analyze varied approaches in terms of providing high spatial and temporal resolution mapping, sensor-based Variable Rate Application (VRA) mapping, the relation between spectral and thermal reflectance and different features of crop and soil. The other objective is to assess RS indices formed by choosing specific reflectance bands and identifying the correct spectral band to optimize classification techniques and analyze Proximal Optical Sensors (POSs) to control changes. The innovation of this paper can be defined as categorizing evaluation methodologies of precision irrigation (applying the right practice, at the right place, at the right time, with the right quantity) controlled by soil moisture levels and sensitiveness of crops to water stress, into pre-processing, processing (retrieval algorithms), and post-processing parts. Then, the main idea of this research is to analyze the error reasons and/or values in employing different approaches in three proposed parts reported by recent studies. Additionally, as an overview conclusion tried to decompose different approaches to optimizing indices, calibration methods for the sensors, thresholding and prediction models prone to errors, and improvements in classification accuracy for mapping changes.

Keywords: agricultural crops, crop water stress detection, irrigation scheduling, precision agriculture, remote sensing

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Authors: Leila Khosravi

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A major part of the drinking water in North West of Iran is supplied from Mahabad reservoir 80 km northwest of Mahabad. This reservoir collects water from 750 km-catchment which is undergoing accelerated changes due to deforestation and urbanization. The main objective of this study is to develop a catchment modeling platform which translates ongoing land-use changes, soil data, precipitation and evaporation into surface runoff of the river discharging into the reservoir: Soil and Water Assessment Tool, SWAT, model along with hydro -meteorological records of 1997–2011. A variety of statistical indices were used to evaluate the simulation results for both calibration and validation periods; among them, the robust Nash–Sutcliffe coefficients were found to be 0.52 and 0.62 in the calibration and validation periods, respectively. This project has developed a reliable modeling platform with the benchmark land physical conditions of the Mahabad dam basin.

Keywords: simulation, surface runoff, Mahabad dam, SWAT model

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Authors: Htet Khaing Lin

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This study explores the relationship between a diverse set of variables, encompassing both environmental and socio-economic factors, and poverty levels in the Philippines for the years 2012, 2015, and 2018. Employing Ordinary Least Squares (OLS), Spatial Lag Models (SLM), and Spatial Error Models (SEM), this study delves into the dynamics of key indicators, including daytime and nighttime land surface temperature, cropland surface, urban land surface, rainfall, population size, normalized difference water, vegetation, and drought indices. The findings reveal consistent patterns and unexpected correlations, highlighting the need for nuanced policies that address the multifaceted challenges arising from the interplay of environmental and socio-economic factors.

Keywords: poverty analysis, OLS, spatial lag models, spatial error models, Philippines, google earth engine, satellite data, environmental dynamics, socio-economic factors

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Authors: Mona Rezaei, Habib Honari, Mehrzad Hamidi, Fatemeh Kiani

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Make strong brands has become a priority for many organizations in marketing. Brand is an important indicator of marketing status. Brand Strength is in kept customer, profit, brand development and gain competitive advantage and In fact it is a concept that was created from a consumer perspective. It is assumed that the creation of a strong brand is creating numerous marketing benefits. The purpose of this study was to evaluate the psychometric characteristics of the questionnaire the most strong sports brands in the consumer society. Questionnaire was conducted to a sample of 340 customers of sports brands. Psychometric parameters were determined by using appropriate statistical methods. The results of the factor analysis and Varimax rotation revealed five factors of strong brands. The results confirms that questionnaire structure have acceptable associated to the data and confirmed all indicators of the model. Reliability (859/0) was satisfactory. According to calculated psychometric indices, this questionnaire could be appropriate to assess the most strong sports brands.

Keywords: reliability, strong brand, sport brands, psychometric

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Authors: Aslam Faheem, Hunjra Ahmed Imran, Tayachi Tahar, Verhoeven Peter, Tariq Yasir

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We investigate the evidence of three risk-adjusted calendar anomalies in eight frontier markets. Our sample consists of the daily closing prices of their stock indices for the period of January 2006 to September 2019. We categorize the data with respect to day-of-the-week, Lunar calendar and Islamic calendar. Using Morgan Stanley Capital International (MSCI) eight Markets Index as our proxy of the market portfolio, most of the frontier markets tested exhibit calendar seasonality. We confirm that systematic risk varies with respect to day-of-the-week, Lunar months and Islamic months. After consideration of time-varying risk and applying Bonferroni correction, few frontier markets exhibit profitable investment opportunities from calendar return anomalies for active investment managers.

Keywords: asset pricing, frontier markets, market efficiency, Islamic calendar effects, Islamic stock markets

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Authors: Onder Aldemir, Ercan Ceyhan

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The research was conducted to determine effects of salt concentrations on emergence and seedling development of chickpea genotypes. Trials were performed during the year of 2013 on the laboratory and greenhouse of Agricultural Faculty, Selcuk University. Emergency trial was set up according to ‘Randomized Plots Design’ by two factors and four replications; greenhouse trial was also set up according to ‘Randomized Plots Design’ by two factors with three replications. The chickpea genotypes; CA119, CA132, CA149, CA150, CA215, CA222, CA235, CA261, Bozkır and Gokce were used as material for both of the trials. Effects of the five doses of salt concentrations (control, 30 mM, 60 mM, 90 mM and 120 mM) on the ratio of emergency, speed of emergency, average time for emergency, index of sensibility, length of shoot and root, fresh weight of shoot and root, dry weight of shoot and root, index of salt tolerance were evaluated. Responses of the chickpea genotypes for salt concentrations were found different. Comparing to the control, all of the investigated characteristics on the chickpea genotypes showed significant reduction by depending on the increasing salt level. According to the effects of salt application, the chickpea genotypes Gokce, CA215 and CA222 were the most tolerant in respect to plant dry weights while the chickpea genotypes CA149 and CA150 were the most sensitive.

Keywords: chickpea, emergence, salt tolerant, seedling development

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Authors: Mustafa M. Donma, Orkide Donma

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Obesity is a low-grade inflammatory state. Childhood obesity is a multisystem disease, which is associated with a number of complications as well as potentially negative consequences. Gender is an important universal risk factor for many diseases. Hematological indices differ significantly by gender. This should be considered during the evaluation of obese children. The aim of this study is to detect hematologic indices that differ by gender in morbid obese (MO) children. A total of 134 MO children took part in this study. The parents filled an informed consent form and the approval from the Ethics Committee of Namik Kemal University was obtained. Subjects were divided into two groups based on their genders (64 females aged 10.2±3.1 years and 70 males aged 9.8±2.2 years; p ≥ 0.05). Waist-to-hip as well as head-to-neck ratios and body mass index (BMI) values were calculated. The children, whose WHO BMI-for age and sex percentile values were > 99 percentile, were defined as MO. Hematological parameters [haemoglobin, hematocrit, erythrocyte count, mean corpuscular volume, mean corpuscular haemoglobin, mean corpuscular haemoglobin concentration, red blood cell distribution width, leukocyte count, neutrophil %, lymphocyte %, monocyte %, eosinophil %, basophil %, platelet count, platelet distribution width, mean platelet volume] were determined by the automatic hematology analyzer. SPSS was used for statistical analyses. P ≤ 0.05 was the degree for statistical significance. The groups included children having mean±SD value of BMI as 26.9±3.4 kg/m² for males and 27.7±4.4 kg/m² for females (p ≥ 0.05). There was no significant difference between ages of females and males (p ≥ 0.05). Males had significantly increased waist-to-hip ratios (0.95±0.08 vs 0.91±0.08; p=0.005) and mean corpuscular hemoglobin concentration values (33.6±0.92 vs 33.1±0.83; p=0.001) compared to those of females. Significantly elevated neutrophil (4.69±1.59 vs 4.02±1.42; p=0.011) and neutrophil-to-lymphocyte ratios (1.70±0.71 vs 1.39±0.48; p=0.004) were detected in females. There was no statistically significant difference between groups in terms of C-reactive protein values (p ≥ 0.05). Adipose tissue plays important roles during the development of obesity and associated diseases such as metabolic syndrom and cardiovascular diseases (CVDs). These diseases may cause changes in complete blood cell count parameters. These alterations are even more important during childhood. Significant gender effects on the changes of neutrophils, one of the white blood cell subsets, were observed. The findings of the study demonstrate the importance of considering gender in clinical studies. The males and females may have distinct leukocyte-trafficking profiles in inflammation. Female children had more circulating neutrophils, which may be the indicator of an increased risk of CVDs, than male children within this age range during the late stage of obesity. In recent years, females represent about half of deaths from CVDs; therefore, our findings may be the indicator of the increasing tendency of this risk in females starting from childhood.

Keywords: children, gender, morbid obesity, neutrophil-to-lymphocyte ratio

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Authors: Mike Tsionas

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The paper develops new indices of financial stability based on an explicit model of expected utility maximization by financial institutions subject to the classical technology restrictions of neoclassical production theory. The model can be estimated using standard econometric techniques, like GMM for dynamic panel data and latent factor analysis for the estimation of co-variance matrices. An explicit functional form for the utility function is not needed and we show how measures of risk aversion and prudence (downside risk aversion) can be derived and estimated from the model. The model is estimated using data for Eurozone countries and we focus particularly on (i) the use of the modeling approach as an “early warning mechanism”, (ii) the bank- and country-specific estimates of risk aversion and prudence (downside risk aversion), and (iii) the derivation of a generalized measure of risk that relies on loan-price uncertainty.

Keywords: financial stability, banking, expected utility maximization, sub-prime crisis, financial crisis, eurozone, PIIGS

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Authors: Parvaneh Ziviar Pardehei, Esmaeil Hossinnejad

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In this research, the tourism climate index Miczcofski (TCI) and to assess climate Trjvng Piranshahr city tourism is discussed. The index is a systematic way to evaluate the climatic conditions for tourism. To calculate the parameters of mean monthly maximum temperature, minimum relative humidity, average daily relative humidity, rainfall, sunshine and the wind speed are used. In the months of April, July, August and September of comfort there in December, January, February and March, the nerve is cold comfort factor. Baker calculation method showed that during spring and summer cooling environment, mild, pleasant, and comfortable Byvklymay there. TCI results suggest that the months of April to July are top rated and best climatic conditions in terms of comfort to the tourists. In general, indices used in this paper show that the months of April to October is the best time for tourism in the city Piranshahr.

Keywords: tourism, climate, Piranshahr city, TCI indicators and trjvng

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Authors: Reza Rezaeipour Honarmandzad

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In this paper we propose an ANN for detection and localization of fatigue damage in aircraft structures. We used network of piezoelectric transducers for Lamb-wave measurements in order to calculate damage indices. Data gathered by the sensors was given to neural network classifier. A set of neural network electors of different architecture cooperates to achieve consensus concerning the state of each monitored path. Sensed signal variations in the ROI, detected by the networks at each path, were used to assess the state of the structure as well as to localize detected damage and to filter out ambient changes. The classifier has been extensively tested on large data sets acquired in the tests of specimens with artificially introduced notches as well as the results of numerous fatigue experiments. Effect of the classifier structure and test data used for training on the results was evaluated.

Keywords: ANN, fatigue damage, aircraft structures, piezoelectric transducers, lamb-wave measurements

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Authors: M. Shahina, K. Fakruddin, C. M. Subhan, S. Rangappa

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In this work, two mixtures with equal concentrations of 1) 4ꞌ-(6-(4-(pentylamino) methyl)-3-hydroxyphenoxy) hexyloxy) biphenyl-4-carbonitrile+-4-((4-(hexyloxy) benzylidene) amino) phenyl 4-butoxy benzoate and 2) 4ꞌ - (6-(4-(hexylamino) methyl)-3-hydroxyphenoxy) hexyloxy) biphenyl-4-carbonitrile+-4-((4-(octyloxy) benzylidene) amino) phenyl 4-butoxy benzoate, have been prepared. The transition temperature and optical texture are observed by using thermal microscopy. Density and birefringence studies are carried out on the above liquid crystalline mixtures. Using density and refractive indices data, the molecular polarizabilities are evaluated by using well-known Vuks and Neugebauer models. The molecular polarizability is also evaluated theoretically by Lippincott δ function model. The results reveal that the polarizability values are same in both experimental and theoretical methods.

Keywords: liquid crystals, optical textures, transition temperature, birefringence, polarizability

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Authors: Alexander Peikos, Carole Binsfeld

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The aim of this paper is to determine a thermally comfortable air temperature in an automated living room. This calculated temperature should serve as input for a user-specific and dynamic heating control in such a living space. In addition to the usual physical factors (air temperature, humidity, air velocity, and radiation temperature), individual clothing and activity should be taken into account. The calculation of such a temperature is based on different methods and indices which are usually used for the evaluation of the thermal comfort. The thermal insulation of the worn clothing is determined with a Radio Frequency Identification system. The activity performed is only taken into account indirectly through the generated heart rate. All these methods are ultimately very well suited for use in temperature regulation in an automated home, but still require further research and extensive evaluation.

Keywords: smart home, thermal comfort, predicted mean vote, radio frequency identification

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Authors: Roberta Ranielle M. de Freitas, Vagner R. Botaro

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The relationship between biodegradation and mechanical behavior is fundamental for studies of the application of cellulose acetate films as a possible material for biodegradable packaging. In this work, the biodegradation of cellulose acetate (CA) with DS 2.5 was analyzed in simulated soil. CA films were prepared by casting and buried in the simulated soil. Samples were taken monthly and analyzed, the total time of biodegradation was 6 months. To characterize the biodegradable CA, the DMA technique was employed. The main result showed that the time of exposure to the simulated soil affects the mechanical properties of the films and the values of crystallinity. By DMA analysis, it was possible to conclude that as the CA is biodegraded, its mechanical properties were altered, for example, storage modulus has increased with biodegradation and the modulus of loss has decreased. Analyzes of DSC, XRD, and FTIR were also carried out to characterize the biodegradation of CA, which corroborated with the results of DMA. The observation of the carbonyl band by FTIR and crystalline indices obtained by XRD were important to evaluate the degradation of CA during the exposure time.

Keywords: biodegradation, cellulose acetate, DMA, simulated soil

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Authors: Emad A. Mohammed

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Utilizing the capabilities of Data Mining and Artificial Intelligence in the prediction of the minimum miscibility pressure (MMP) required for multi-contact miscible (MCM) displacement of reservoir petroleum by hydrocarbon gas flooding using Fuzzy Logic models and Artificial Neural Network models will help a lot in giving accurate results. The factors affecting the (MMP) as it is proved from the literature and from the dataset are as follows: XC2-6: Intermediate composition in the oil-containing C2-6, CO2 and H2S, in mole %, XC1: Amount of methane in the oil (%),T: Temperature (°C), MwC7+: Molecular weight of C7+ (g/mol), YC2+: Mole percent of C2+ composition in injected gas (%), MwC2+: Molecular weight of C2+ in injected gas. Fuzzy Logic and Neural Networks have been used widely in prediction and classification, with relatively high accuracy, in different fields of study. It is well known that the Fuzzy Inference system can handle uncertainty within the inputs such as in our case. The results of this work showed that our proposed models perform better with higher performance indices than other emprical correlations.

Keywords: MMP, gas flooding, artificial intelligence, correlation

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Authors: Kaoutar Abbahaddou, Mohammed Salah Chiadmi

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The need to find a relevant way to predict the next-day price of a stock index is a real concern for many financial stakeholders and researchers. We have known across years the proliferation of several methods. Nevertheless, among all these methods, the most controversial one is a machine learning algorithm that claims to be reliable, namely neural networks. Thus, the purpose of this article is to study the prediction power of neural networks in the particular case of Islamic finance as it is an under-looked area. In this article, we will first briefly present a review of the literature regarding neural networks and Islamic finance. Next, we present the architecture and principles of artificial neural networks most commonly used in finance. Then, we will show its empirical application on two Islamic stock indexes. The accuracy rate would be used to measure the performance of the algorithm in predicting the right price the next day. As a result, we can conclude that artificial neural networks are a reliable method to predict the next-day price for Islamic indices as it is claimed for conventional ones.

Keywords: Islamic finance, stock price prediction, artificial neural networks, machine learning

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Authors: Ikenna Charles Onyema, Tolut Prince Bako

Abstract:

A study was carried out in the Atlantic Ocean off the Lighthouse Beach, Lagos. There were monthly and spatial variations in physical and chemical characteristics of the neritic ocean (August - December, 2014). Mean and standard deviation values for air temperature were 27. 67, ± 2.98 °C, water temperature (28.37 ± 1.88), pH (7.85 ± 0.17), conductivity (44738.75 ± 6262.76 µS/cm), total dissolved solids (29236.71 ± 4273.30 mg/L), salinity (27.11 ± 3.91 ‰), alkalinity (126.99 ± 42.81 mg/L) and chloride (15056. 67 ± 2165.78 mg/L). Higher estimates were recorded in the dry than wet months for these characteristics. On the other hand, reducing values were recorded for acidity (2.34 ± 0.63 mg/L), total hardness (4711.98 ± 691.50 mg/L), phosphate (1.1 ± 0.78 mg/L), sulphate (2601.99 ± 447.04 mg/L) and nitrate (0.12 ± 0.06 mg/L). Values for total suspended solids and biological oxygen demand values were low (<1mg/L). Twenty-one species of phytoplankton were recorded. Diatoms recorded 80.92% and were the dominant group. Hemidiscus cuneiformis, Coscinodiscus centralis, Coscinodiscus lineatus, Coscinodiscus radiatus and Oscillatoria limosa were more frequently occurring species. Biddulphia sinensis and four species of Ceratium, were representatives of the dry season. The dry season also recorded comparatively higher individuals of phytoplankton than the wet season. Spirogyra sp. (green algae) appeared only in the wet season. Species abundance (N) was highest in December at Station 1 (13.15%) (dry season) and lowest in August (wet season) at Station 3 (2.96%). The physico-chemical factors and phytoplankton reflected a tropical unpolluted neritic oceanic environment.

Keywords: sea, physico-chemistry, lighthouse beach, microalgae

Procedia PDF Downloads 186

Authors: Ikenna Charles Onyema, Prince Tolut Bako

Abstract:

A study was carried out in the Atlantic Ocean off the Lighthouse Beach, Lagos. There were monthly and spatial variations in physical and chemical characteristics of the neritic ocean (August-December, 2014). Mean and standard deviation values for air temperature were 27. 67, ± 2.98 oC, water temperature (28.37 ± 1.88), pH (7.85 ± 0.17), Conductivity (44738.75 ± 6262.76 µS/cm), Total dissolved solids (29236.71 ± 4273.30 mg/L), Salinity (27.11 ± 3.91 ‰), Alkalinity (126.99 ± 42.81 mg/L) and Chloride (15056. 67 ± 2165.78 mg/L). Higher estimates were recorded in the dry than wet months for these characteristics. On the other hand, reducing values were recorded for Acidity (2.34 ± 0.63 mg/L), Total hardness (4711.98 ± 691.50 mg/L), Phosphate (1.1 ± 0.78 mg/L), Sulphate (2601.99 ± 447.04 mg/L) and Nitrate (0.12 ± 0.06 mg/L). Values for Total suspended solids and Biological oxygen demand values were low ( < 1mg/L). Twenty-one species of phytoplankton were recorded. Diatoms recorded 80.92% and were the dominant group. Hemidiscus cuneiformis, Coscinodiscus centralis, Coscinodiscus lineatus, Coscinodiscus radiatus and Oscillatoria limosa were more frequently occurring species. Biddulphia sinensis and four species of Ceratium, were representatives of the dry season. The dry season also recorded comparatively higher individuals of phytoplankton than the wet season. Spirogyra sp. (green algae) appeared only in the wet season. Species abundance (N) was highest in December at Station 1 (13.15%) (dry season) and lowest in August (wet season) at Station 3 (2.96%). The physico-chemical factors and phytoplankton reflected a tropical unpolluted neritic oceanic environment.

Keywords: sea, physico-chemistry, micro-algae, lighthouse beach

Procedia PDF Downloads 223

Authors: Shreemoyee Sarkar, Vikhyat Chadha

Abstract:

In this paper, the local fractal properties and chaotic properties of financial time series are investigated by calculating two exponents, the Local Hurst Exponent: LHE and Lyapunov Exponent in a moving time window of a financial series.y. For the purpose of this paper, the Dow Jones Industrial Average (DIJA) and S&P 500, two of the major indices of United States have been considered. The behaviour of the above-mentioned exponents prior to some major crashes (1998 and 2008 crashes in S&P 500 and 2002 and 2008 crashes in DIJA) is discussed. Also, the optimal length of the window for obtaining the best possible results is decided. Based on the outcomes of the above, an attempt is made to predict the crashes and accuracy of such an algorithm is decided.

Keywords: local hurst exponent, lyapunov exponent, market crash prediction, time series chaos, time series local fractal properties

Procedia PDF Downloads 150