Statistical Modeling for PM10, PM2.5 and PM1 at Gangneung Affected by Local Meteorological Variables and PM10 and PM2.5 at Beijing for Non- and Dust Periods

Multiple statistical prediction modeling of PM10, PM2.5 and PM1 at Gangneung city, Korea, was performed in association with local meteorological parameters (air temperature, wind speed and relative humidity) and PM10 and PM2.5 concentrations of an upwind site in Beijing, China, in the transport route of Chinese yellow dusts which originated from the Gobi Desert and passed through Beijing to the city from 18 March to 27 March 2015. Before and after the dust periods, the PM10, PM2.5 and PM1 concentrations showed as being very high at 09:00 LST (the morning rush hour) by the increasing emitted pollutants from vehicles and flying dust from the road and their maxima occurred at 20:00 to 22:00 LST (the evening departure time) from the additional pollutants from resident heating boilers. During the dust period, these peak trends were not found due to the persistent accumulation of dust in the city from the Gobi Desert through Beijing, China, as shown in real-time COMS-AI satellite images. Multiple correlation coefficients among PM10, PM2.5 and PM1 at Gangneung were in the range of 0.916 to 0.998. Multiple statistical models were devised to predict each PM concentration, and the significant levels through multi-regression analyses were p < 0.001, showing all the coefficients to be significant. The observed and calculated PM concentrations were compared, and new linear regression models were sequentially suggested to reproduce the original observed PM values with improved correlation coefficients, to some extent.

Estimating biological age by hematological blood parameters

For the estimation of the biological age (BA) of people based on hematological parameters of the clinical blood test there were used MLR and Deep Neural Networks. In the archive of the Institute of Gerontology NAMS of Ukraine there were selected people aged from 20 up to 90 years (440 men and 504 women), who had all hematological parameters within normal limits. When using the MLR method, the multiple correlation coefficients (R) have low values for both men (0.37) and women (0.38). The use of Deep Neural Networks has given good results. The values of the correlation coefficients between BA and chronological age were 0.92 for men and 0.79 for women. The average absolute error in determining BA was 3.68 years for the men and 6.55 years for the women. The developed method for assessing hematological age can be used in clinical practice to identify people with the risk of developing hematological pathology, as well as in population researches. Keywords: biological age, hematological blood parameters, deep neural network

Genotype screening of Cannabis sativa L. based on the specifics of minor cannabinoids manifestation

Analysis of hemp collection samples based on the content of minor (rare) non-psychotropic cannabinoids, such as cannabichromene (CBC), cannabidivarin (CBDV), and cannabinol (CBN); determination of correlation relationships between them and common compounds; selection of valuable breeding genotypes. Methods. Field, biochemical (gas chromatography of cannabinoid compounds), and statistical (pair, partial, and multiple linear correlations). Results. Quantitative analysis of 210 samp­les of various ecological-geographical and genetic origin (local and wild forms, self-filing lines, hybrids, varieties, synthetic populations, polyploids) with a tetrahydrocannabinol (THC) content of less than 0.08% in dried plants showed the level of manifestation of the trait from its absence within the sensitivity of the gas chromatograph up to 0.6838% CBC, 0.1719% CBC and 0.3274% CBN. In the studied hemp samples, a medium negative relationship was found between the signs of the CBC and cannabidiol (CBD) contents (r = –0.53), a weak negative relationship between CBC and CBDV contents (r = –0.35), medium positive relationships between the signs of CBC and THC contents (r = 0.57) and CBC and CBN contents (r = 0.59). A medium positive correlation (r = 0.57) was found between the signs of CBDV and CBD contents, while CBN had a strong positive relationship with THC (r = 0.82). There is almost no correlation between cannabigerol (CBG) and the minor cannabinoids under study. The biosynthesis of minor cannabinoid compounds is quite complex. Signs manifestation is affected by many genetic and external factors. Partial correlation coefficients (given that one of the three signs is eliminated) and multiple correlation coefficients (given that the relationship of one sign is determined and two other signs are combined) give grounds to state that the gene for CBCA-synthase affects the production of CBD and, in particular THC. Conclusions. The closeness of the linear relationships between minor cannabinoids and common components allows selecting valuable hemp samples with a high content of one or several compounds under the absence or low content of psychotropic THC.

Automatic Estimation of Multidimensional Personality From a Single Sound-Symbolic Word

Researchers typically use the “big five” traits (Extroversion, Agreeableness, Conscientiousness, Neuroticism, and Openness) as a standard way to describe personality. Evaluation of personality is generally conducted using self-report questionnaires that require participants to respond to a large number of test items. To minimize the burden on participants, this paper proposes an alternative method of estimating multidimensional personality traits from only a single word. We constructed a system that can convert a sound-symbolic word (SSW) that intuitively expresses personality traits into information expressed by 50 personality-related adjective pairs. This system can obtain information equivalent to the adjective scales using only a single word instead of asking many direct questions. To achieve this, we focused on SSWs in Japanese that have the association between linguistic sounds and meanings and express diverse and complex aspects of personality traits. We evaluated the prediction accuracy of the system and found that the multiple correlation coefficients for 48 personality-related adjective pairs exceeded 0.75, indicating that the model could explain more than half of the variations in the data. In addition, we conducted an evaluation experiment in which participants rated the appropriateness of the system output using a seven-point scale (with −3 as absolutely inappropriate and +3 as completely appropriate). The average score for 50 personality-related adjective pairs was 1.25. Thus, we believe that this system can contribute to the field of personality computing, particularly in terms of personality evaluation and communication.

Investigating the relationship between self-esteem and stress coping styles with students’ procrastination

The aim of this study is to investigate the relationship between self-esteem and stress coping styles with students’ procrastination. The statistical population of the study is all high school female students in Mashhad City in the academic year of 2018-2019. Due to the high volume of the population, using the Karajsi and Morgan (1970), the sample size was 384. Subjects answered three questionnaires that are: Rosenberg Self-Esteem Scale (1965), Andler and Parker's Stress Dealing Styles (1990), and Solomon and Rothblum Academic Procrastination (1984). Pearson Multiple Correlation coefficients were used for analyzing the data. The results showed that between self-esteem with procrastination and avoidance coping style with procrastination, is a significant relationship (p

Multiply Regression Analysis as An Integrated Approach in the TB Indicators Assessment in the Republic of Crimea

The use of multiply regression analysis for the TB indicators assessment and prediction in the Republic of Crimea is discussed. Basic TB indicators in the Republic of Crimea for the period 2014-2018 were studied using Pearson correlation coefficient and step-by-step multiply linear regression analysis. During paired correlation analysis, dependable association with an average and high degree is identified for the most indicators of interest. The multiple correlation coefficients were higher than the paired correlation coefficients, which demonstrated the greater significance of the group conditionality of the indicators. For key epidemiological TB indicators the regression equations are constructed and the most relevant predictors are found using stepwise multiply regression analysis. The regression equations for TB incidence, prevalence and mortality rates are proposed for practical applying to predict epidemiological situation.

PENGARUH STRUKTUR AKTIVA DAN LIKUIDITAS TERHADAP STRUKTUR MODAL

This study aims to determine the effect of asset structure and liquidity on capital structure at PT. INDOFOOD SUKSES MAKMUR Tbk. The population in this study is all data from PT. Indofood Sukses Makmur Tbk from the first listing on the Indonesia Stock Exchange in 1994 for 24 years, from 1994 to 2018 with the sample used for 6 years, from 2013 to 2018. The sampling technique used is purposive sampling. Data analysis techniques used are the classical assumption test, multiple linear regression, multiple correlation coefficients, coefficient of determination and hypothesis testing (t-test and f-test). The results of this study prove that the Asset Structure has a partially significant effect on the Capital Structure,because the larger the asset structure, the greater the capital structure, it is due to the existence of a large debt obtained can be large. Liquidity has no significant effect partially on the Capital Structure,where company liquidity does not affect the size of the capital structure, and simultaneously the Asset Structure and Liquidity have significant effect on the Capital Structure at PT. Indofood Sukses Makmur tbk.

Pengaruh Kompetensi Manajerial Kepala Sekolah dan Budaya Kerja Terhadap Disiplin Guru di SD Islam Al-Ikhlas Cipete Jakarta Selatan

This study aims to determine and examine empirical data related to the influence of principals' managerial competencies and work culture on teacher discipline separately or simultaneously. In this study, the authors used a survey method with a correlational and regression approach to the quantitative data obtained from the object of research, namely teachers at SD Islam Al-Ikhlas Cipete South Jakarta. The sample of this study was 66 respondents from 66 populations. The data collection is done by using questionnaire / questionnaire techniques, observation, and documentation. The type of analysis used is the regression analysis which is described descriptively. The results of this study are: 1) There is a positive relationship, which is quite strong and significant between principals' managerial competencies and teacher discipline, which is shown by a simple correlation coefficient (ry.1) is 0.408 (the correlation is quite strong) and the determination coefficient (R2) = 0.166, which means that Principal's managerial competence contributes to teacher discipline by 16.6% and the remaining 84.4% is determined by other factors. 2) There is a positive relationship, quite strong and significant between work culture and teacher discipline, which is shown by a simple correlation coefficient (ry.2) is 0.321 (the correlation is quite strong) and the determination coefficient (R2) = 0.103, which means that work culture provides contribution to teacher discipline is 10.3% and the remaining 89.7% is determined by other factors. 3) There is a positive, strong and significant relationship between principals' managerial competencies and work culture together with teacher discipline, which is indicated by multiple correlation coefficients (Ry. 1.2) is 0.470 (quite strong correlation) and coefficient of determination (R2) = 0.221, which means that principals' managerial competencies and work culture together contribute to teacher discipline by 22.1% and the rest 77.9% is determined by other factors.

Possibilities of Determination of Risk Elements in Alluvial Agriculture Soils in the Mže and Otava River Basins by X-Ray Fluorescence Spectrometry

The undesirable, hazardous, and risk elements are introduced into all environmental parts through human activities. They enter the soil and aquatic environment by atmospheric deposition, or by application of sewage sludge, pesticides, mineral and organic fertilisers, and by organic manures. Heavy metals (HMs) and risk elements can be determined in the soil by a wide range of analytical methods that differ in terms of time and financial costs, and the demands on service. One of the methods is the use of a portable XRF spectrometer under lab conditions, offering relatively fast determination of the concentration of chemical elements in the soil. In the presented study we evaluated the accuracy and the precision of the XRF device for analysis of the concentration of heavy metals (Pb, Zn, As, Mn, Cu, and Ni) in alluvial soils from the Mže and Otava river basins (Czech Republic), and validated and compared obtained results with the conventional lab method (ICP-OES). The soil samples (n = 502) were taken at 43 sampling sites at depths of 0 – 30, 30 – 60, and 60 – 90 cm, mainly in floodplains with Fluvisol soil type (N-year flow rates = Q100 m3/s). The multiple correlation coefficients R values ranged from 0.81 to 0.99. The R2 determination coefficients for individual HMs, measured by XRF, were determined as follows: Pb – 0.98, Zn – 0.97, Cu – 0.80, Mn – 0.79, As – 0.78, Ni – 0.66. According to our results, 66 – 98% points fit the designed models. The Pb and Zn have the best dependency (relationship tightness), and regression models are excellent. Cu, Mn, and As have a slightly worse dependency (tightness of the relationship), but the regression model is still very well suitable for agriculture practice, or for the purposes of environmental monitoring.

Financial support as a determinant of small and medium-sized enterprises economic growth

European Union integration and revitalization of economy after the global economic crisis require small and medium-sized enterprises in Republic of Serbia to face more complex and dynamic environment which requires greater competitiveness in terms of improved quality, efficiency and management practices. However, the competitiveness of the regional SMEs is still at a much lower level compared to other European SMEs. Pointing out to the characteristics of small and medium enterprises, a logical conclusion can be drawn that state support for this sector is important. When forming the support modalities, the sector should not be viewed as a uniform whole. This paper analyses the importance of financial and non financial support for SMEs in terms of organizational capability and competiveness. Roy's test, Pearson's coefficient of contingency (ch), and multiple correlation coefficients (R) are applied as univariate statistical procedures. MANOVA and discriminant analysis show a difference and clearly defined boundary between other forms of support and financial forms of support in all the analyzed units. The findings also indicate that the financial forms of SME support influence the SMEs organization capability and competitiveness, given that in most cases the benefits of state institutions are viewed through forms of financial support.