Calculated Correlation Coefficients Research Articles

УПРАВЛЕНИЕ ЗАТРАТАМИ, ПРИБЫЛЬЮ И БЕЗУБЫТОЧНОСТЬЮ ТРАНСПОРТНОЙ КОМПАНИИ

To manage the financial stability of the company, working capital, current activities, business risk and solvency, CVP analysis, the value of the break-even point plays an important role, as well as the degree of excess of sales volumes over the critical point, which determines the company's stability margin. The article analyzes the income and expenses of the company, the analysis of the volume of production, cost and profit, the analysis of break-even and the relationship between the income and the number of flight hours of the studied company of Air Astana JSC, which revealed a strong relationship between the indicators based on the calculated correlation coefficient (0.9527), as well as a direct dependence of the income (90.75%) of the company on the flight hours based on the coefficient of determination. The analysis of the influence of various factors on the critical sales volume and break-even points is carried out.

Abstract P212: Comparison Of Vascular Risk Factors And Serum Fatty Acids At Admission Between Intracerebral Hemorrhage And Acute Ischemic Stroke

Introduction: Dietary triglycerides influence fatty acid (FA) serum concentrations and weight percentages (wt%), which may be associated with the onset of intracerebral hemorrhage (ICH) or acute ischemic stroke (AIS). Hypothesis: There are significant differences between FAs at the admission of ICH and AIS. Methods: We included patients admitted between 2016 and 2019 within 24 h of ICH or AIS onset and calculated correlation coefficients between their ages, serum FA concentrations, and FA wt% values. We evaluated differences in age, average blood pressure (ABP), glucose, A1c, serum lipids, and FAs between two groups. Excluding variables with multicollinearity, we performed multiple logistic regression (MLR) analysis to identify independent variables distinguishing ICH from AIS. We estimated the threshold values of independent variables using the area under the curve values derived from the receiver operating characteristic (ROC) curves. Results: Our inclusion criteria were met by 141 of ICH patients and 525 of AIS patients. In the ICH group, age, A1c, and eicosapentaenoic acid (EPA) levels were smaller than those in the AIS group. ABP, high-density lipoprotein cholesterol (HDL-C), myristic acid (MyA), linoleic acid (LiA) concentrations, and MyA wt% were higher than those in the AIS group. MLR analysis between two groups indicated that age, ABP, A1c, HDL-C were independent variables. Serum FA levels were not independent. ROC curves showed that the threshold values of age, ABP, A1c, and HDL-C for ICH onset were ≤ 69 years, ≥ 126.6 mmHg, ≤ 6.0%, and ≥ 1.62 mmol/L, respectively. In 27 patients with age ≤ 69 , ABP ≥ 126.6, A1c ≤ 6.0%, and HDL-C ≥ 1.62 and 87 patients with age > 69 , ABP< 126.6, A1c > 6.0, and HDL-C < 1.62, there were 19 (70.4%) and 9 (10.3%) patients with ICH, the MyA concentrations were 108 and 73 μmol/L (p < 0.001), the LiA concentration were 2,900 and 2,410μmol/L (p < 0.001), and the EPA wt% were 1.4 and 2.0% (p=0.059), respectively. Conclusions: Younger patients with higher ABP, lower A1c, and higher HDL-C suffered from not AIS but ICH, and their MyA and LiA concentrations were higher than older patients without them.

Фактори розвитку харчової гіперчутливості у дітей раннього віку

Food hypersensitivity is a reaction to the food consumed, regardless of the pathogenetic mechanisms that cause the symptoms. It is an actual and controversial problem in pediatric practice. Nowadays there is an active search for the causes of disease progression, a large role is given to the study of genetic and external factors (food, environmental, social). This disease arises many questions due to the similarity of the clinical representation in different kinds of food hypersensitivity and in different pathogenetic mechanisms, which are involved. The purpose of the study is to perform the analysis of factors, which cause appearance of food hypersensitivity in toddlers. Materials and methods. A study of the number of children with food intolerance was conducted using a specially compiled questionnaire. Thus, 4,500 questionnaires were distributed in pre-school and medical establishments to question parents. Results and discussion. Analysis of 3,214 questionnaires was conducted, which enabled to obtain information from parents on anamnesis and living conditions of toddlers. Values of 56 factors were analyzed, calculating correlation coefficients with a formation of food hypersensitivity for each of them. Statistical analysis allowed distinguishing 15 signs among these factors, which significantly correlated with the formation of food hypersensitivity in young children. The investigation enabled not only to detect factors that affect formation of food hypersensitivity in young children, but also to suggest a mathematical model of individual calculation of risk factors for this pathology. Data of conducted mathematical analysis can be used for elaboration of a complex of prophylaxis measures on development of food hypersensitivity in toddlers. Conclusion. The formation of hypersensitivity to cow's milk in children is provoked by the presence of contact reactions in the child, adverse reactions after medication, positive family history (bronchial asthma in relatives, skin diseases in parents (father and / or mother)), smoking in the family, living in the city; at the same time, preventive factors are living in an apartment, in a new building, in a dry apartment. The formation of food hypersensitivity in young children is generally provoked by a positive family history (bronchial asthma, hay fever, urticaria, diseases of the stomach and duodenum in relatives, skin diseases in parents), smoking in the family; frequent consumption of food in a mass catering points; living in the city plays a preventive role

Deep learning for ionospheric TEC forecasting at mid-latitude stations in Turkey

Earth's ionosphere is an important medium for navigation, communication, and radio wave transmission. The inadequate advances in technology do not allow enough realization of ionosphere monitoring systems globally, and most research is still limited to local research in certain parts of the world. However, new methods developed in the field of forecasting and calculation contribute to the solution of such problems. One of the methods developed is artificial neural networks-based deep learning method (DLM), which has become widespread in many areas recently and aimed to forecast ionospheric GPS-TEC variations with DLM. In this study, hourly resolution GPS-TEC values were obtained from five permanent GNSS stations in Turkey. DLM model is created by using the TEC variations and 9 different SWC index values between the years 2016 and 2018. The forecasting process (daily, three-daily, weekly, monthly, quarterly, and semi-annual) was carried out for the prediction of the TEC variations that occurred in the first half-year of 2019. The findings show that the proposed deep learning-based long short-term memory architecture reveals changes in ionospheric TEC estimation under 1–5 TECU. The calculated correlation coefficient and R2 values between the forecasted GPS-TEC values and the test values are higher than 0.94.

Pretreatment Apparent Diffusion Coefficient Cannot Predict Histopathological Features and Response to Neoadjuvant Radiochemotherapy in Rectal Cancer: A Meta-Analysis

Aim: Our purpose was to perform a systemic literature review and meta-analysis regarding use of apparent diffusion coefficient (ADC) for prediction of histopathological features in rectal cancer (RC) and to prove if ADC can predict treatment response to neoadjuvant radiochemotherapy (NARC) in RC. Methods: MEDLINE library, EMBASE, Cochrane, and SCOPUS database were screened for associations between ADC and histopathology and/or treatment response in RC up to June 2020. Authors, year of publication, study design, number of patients, mean value, and standard deviation of ADC were acquired. The methodological quality of the collected studies was checked according to the Quality Assessment of Diagnostic Studies instrument. The meta-analysis was undertaken by using the RevMan 5.3 software. DerSimonian and Laird random-effects models with inverse-variance weights were used to account the heterogeneity between the studies. Mean ADC values including 95% confidence intervals were calculated. Results: Overall, 37 items (2,015 patients) were included. ADC values of tumors with different T and N stages and grades overlapped strongly. ADC cannot distinguish RC with a high- and low-carcinoembryonic antigen level. Regarding KRAS status, ADC cannot discriminate mutated and wild-type RC. ADC did not correlate significantly with expression of vascular endothelial growth factor and hypoxia-inducible factor 1a. ADC correlates with Ki 67, with the calculated correlation coefficient: −0.52. The ADC values in responders and nonresponders overlapped significantly. Conclusion: ADC correlates moderately with expression of Ki 67 in RC. ADC cannot discriminate tumor stages, grades, and KRAS status in RC. ADC cannot predict therapy response to NARC in RC.

Influence of solar activity on ambient dose equivalent H*(10) measured with thermoluminescent dosimeters in Slovenia

Ambient dose equivalent H *(10) is measured to assess general population exposure to ionising radiation. From its spatial and time variations it is possible to identify sources of exposure. In Slovenia, semi-annual H *(10) is measured routinely with thermoluminescence dosimeters at 66 locations around the Nuclear Power Plant (NPP) Krško and at 50 other locations covering the rest of Slovenian territory. Since the Chernobyl accident contamination had ceased to contribute to ambient dose equivalents, we have been calculating correlation coefficients between annual mean number of sunspots and annual H *(10). These correlation coefficients were calculated for five locations in western Slovenia and for five annual H *(10) extracted from measurements around NPP Krško. Their ranges between –0.64 and –0.38 suggest a clear negative correlation between solar activity and H *(10). Mean annual H *(10) averted by solar activity in the past two solar maxima reached 0.070 mSv around NPP Krško (155 m.a.s.l.) and 0.132 mSv and 0.180 mSv at Kredarica (2515 m.a.s.l.). Quantifying the influence of the solar activity on the ambient dose equivalent helps us to better understand exposure of the general population to ionising radiation.

Temporal Correlation and Long-Term Average Performance Analysis of Multiple UAV-Aided Networks

In multiple unmanned aerial vehicles (UAVs)-aided networks, the time-varying channel caused by the impact of the line of sight (LOS) and nonline of sight (NLOS) leads to signal fluctuations; moreover, the UAV's agility and the constraint of the spatial distribution of blind areas on the UAV's deployment result in interference topology fluctuations. Accordingly, the instantaneous signal-to-interference ratio is fluctuant and cannot accurately reflect network performance. Considering a multi-UAV-aided network with UAV spatial dependence, this article derives the semiclosed expression of long-term average throughput considering the fluctuations of the channel and topology, which are measured by calculating correlation coefficients of the signal and interference. Specifically, the time-varying channel is characterized by incorporating the link-state conversions and randomness of small-scale fading into channel gains, the time-varying network topology is quantified by considering the effect of distance variation caused by mobility on interference topology. In addition, considering multiple UAVs are clustered in corresponding blind areas, UAV networks are modeled as matern cluster processes (MCP), and time-averaged performances at intracluster and extracluster are analyzed, respectively. The numerical results show the effects of clustering parameters and deployment parameters on temporal correlation and long-term average network performance.

Sorption dynamics, geochemical fraction and driving factors in phosphorus transport at large basin scale

The transport and deposition of phosphorus (P) in large-scale basin are closely associated with the spatial distribution characteristics and nutritional status of river sediments. Samples of surface water (SW), suspended sediment (SS), bed sediment (BS), and sediment cores from the Yellow River (YR) were collected. The different fractions including total phosphorus (TP), organic P (OP), inorganic P (IP), HCl–P and NaOH–P were determined by standard measurement and testing method. The results showed that upper, middle, and downstream sedimentary texture exhibit spatial heterogeneity. Pearson correlation analysis and redundancy analysis revealed that medium grain size (Mz) is the most negative factor that influence P and fractions, indicating the importance of silt content. Additionally, TP and HCl–P content were positively and significantly correlated, and the calculated correlation coefficient was 0.96 (p < 0.05). Fe oxides had the greatest positive effect on the absorption of NaOH–P in sediments, followed by Al and Mn oxides. From the sediment cores perspective, the rose figure and logistic regression curve showed that significant growth trend, which indicates that vertical pollution status becomes more severe with increasing silt content. Overall, due to the strong adsorption ability of finer particle as silt that driving the P distribution, this study suggests a greater focus on the effects of fine sediment particles transport for the diffuse pollution control towards the whole basin.

Examining Sex-Differentiated Genetic Effects Across Neuropsychiatric and Behavioral Traits

BackgroundThe origin of sex differences in prevalence and presentation of neuropsychiatric and behavioral traits is largely unknown. Given established genetic contributions and correlations, we tested for a sex-differentiated genetic architecture within and between traits. MethodsUsing European ancestry genome-wide association summary statistics for 20 neuropsychiatric and behavioral traits, we tested for sex differences in single nucleotide polymorphism (SNP)-based heritability and genetic correlation (rg < 1). For each trait, we computed per-SNP z scores from sex-stratified regression coefficients and identified genes with sex-differentiated effects using a gene-based approach. We calculated correlation coefficients between z scores to test for shared sex-differentiated effects. Finally, we tested for sex differences in across-trait genetic correlations. ResultsWe observed no consistent sex differences in SNP-based heritability. Between-sex, within-trait genetic correlations were high, although <1 for educational attainment and risk-taking behavior. We identified 4 genes with significant sex-differentiated effects across 3 traits. Several trait pairs shared sex-differentiated effects. The top genes with sex-differentiated effects were enriched for multiple gene sets, including neuron- and synapse-related sets. Most between-trait genetic correlation estimates were not significantly different between sexes, with exceptions (educational attainment and risk-taking behavior). ConclusionsSex differences in the common autosomal genetic architecture of neuropsychiatric and behavioral phenotypes are small and polygenic and unlikely to fully account for observed sex-differentiated attributes. Larger sample sizes are needed to identify sex-differentiated effects for most traits. For well-powered studies, we identified genes with sex-differentiated effects that were enriched for neuron-related and other biological functions. This work motivates further investigation of genetic and environmental influences on sex differences.

Decrypting healed fault zones: how gouge production reduces the influence of fault roughness

SUMMARY Two key parameters control the localization of deformation and seismicity along and surrounding crustal faults: the strength and roughness of the pre-existing fault surface. Using 3-D discrete element method simulations, we investigate how the anisotropy and amplitude of roughness control the mechanical behaviour of healed faults within granite blocks during quasi-static triaxial compression. We focus on models in which the uniaxial compressive strength of the healed faults is about 25 per cent of that strength of the surrounding host rock. These models provide insights into the evolution of fracture network localization, fault roughness, gouge production, fault slip and stress concentrations along initially healed faults of varying roughness. In contrast to expectations, the uniaxial compressive strengths of models that host faults with root-mean-squared roughness amplitudes of 0.2–1.4 mm do not vary more than the change produced by variations in particle packing. To assess if this lack of influence arises from the evolving roughness of the faults, we track the roughness amplitudes parallel and perpendicular to the downdip direction throughout fault failure and slip. The de facto roughness does not provide an explanation for the lack of influence of roughness on compressive strength because the roughness of the faults does not evolve to similar values with slip. Rather, smoother faults remain smoother than rougher faults throughout the simulation. However, the rougher faults produce larger volumes of gouge than the smoother faults. The gouge lubricates the fault and thereby reduces the influence of roughness on compressive strength. These observations suggest that fault topography and the asperities that build this topography do not exert a significant impact on deformation. To quantify the influence of asperities on slip, we calculate correlation coefficients between the fault surface topography and components of the slip vectors. The observed negative correlation coefficients between the fault topography and fault-plane parallel slip quantify the degree to which asperities slow slip in the downdip direction. The observed positive correlation coefficients between the topography and fault-plane perpendicular movement quantify the degree to which asperities promote opening. Thus, this analysis shows how asperities control slip by acting as speed bumps that hinder fault-plane parallel slip and promote fault-plane normal opening as the healed faults slide. The asperities do not significantly control fault movement during the unlocking and failure of the healed faults, but only following the peak axial stress as the faults slide and damage zones develop. These models thus provide unparalleled access to the dynamics of reactivated healed faults.

Application of four different models for predicting the high-temperature flow behavior of TG6 titanium alloy

The high-temperature flow behavior of TG6 titanium alloy at strain rates from 0.001 to 10 s−1 and temperatures from 850 to 1050 ℃ was systematically studied by Gleeble-3500 thermal simulation compressor, and four different constitutive equations (classical Arrhenius (AR) model, modified Johnson-Cook (MJC) model, modified Zerilli–Armstrong (MZA) model, artificial neural network (ANN) model) were derived. EBSD results show that the deformation behavior of TG6 titanium alloy has flow softening characteristics. Furthermore, the calculated correlation coefficient (R) and average absolute relative error (AARE) are used to make an error analysis of the fit accuracy of the above models to evaluate the predictive ability of the TG6 titanium alloy flow behavior. The results of the comprehensive analysis are as follows: on the one hand, it is revealed that different predictive capabilities of the high-temperature flow behavior of TG6 titanium alloy by all the four models based on the meticulous experimental comparison and validation (AR model: R2 is 97.376 % and AARE is 14.16 %; MJC model: R2 is 97.42 % and AARE is 18.5 %; MZA model: R2 is 90.598 % and AARE is 19.32 %; ANN model: R2 is 99.94 % and AARE is 2.14 %), but MZA model is a special case. On the other hand, the MJC and AR model can be considered as the best choices for relatively accurate description and prediction of the flow stress behavior of TG6 titanium alloy when the predictability of the model and the material parameters to be considered.

Analysis of factors causing appearance of food hypersensitivity in young children in Lviv oblast

Food hypersensitivity in young children is a topical issue, since it encompasses a wide range of clinical symptoms and requires a personified approach in diagnostic, therapeutic and preventive measures. A progressive increase in different forms of food hypersensitivity is associated with many factors, particularly malnutrition and harmful ecological conditions. Epigenetic and genetic factors, which potentially can be related to food hypersensitivity and allergy, are being thoroughly studied. In this complex situation, the detection of risk factors for disease development is important for offering patients proper recommendations on diet, living conditions and lifestyle. Aim of the research: to perform analysis of factors, which cause appearance of food hypersensitivity in young children in Lviv oblast. Materials and methods. A study of the number of children with food intolerance was conducted using a specially compiled questionnaire. Thus, 4500 questionnaires were distributed in pre-school and medical establishments to question parents. The questionnaire had 34 questions that were grouped into four parts: general information and detailed information in parts A, B, and C. The general information part of the questionnaire included questions about the region where the child lived, passport data of the child (age, gender) and presence of serious disease (either past or present). Part A had questions about serious diseases that a child had suffered; part B asked about the child’s genealogical and medical history and presence of harmful habits in the family; part C had questions about the environment and living conditions of the child, as well as nutrition and its relation to the development of clinical symptoms of disease. Results. Analysis of 3214 questionnaires was conducted, which enabled to obtain information from parents on anamnesis and living conditions of young children. Values of 56 factors were analyzed, calculating correlation coefficients with a formation of food hypersensitivity for each of them. Statistical analysis allowed distinguishing 15 signs among these factors, which significantly correlated with the formation of food hypersensitivity in young children. Conclusions. The investigation enabled not only to detect factors that affect formation of food hypersensitivity in young children, but also to suggest a mathematical model of individual calculation of risk factors for this pathology. Data of conducted mathematical analysis can be used for elaboration of a complex of prophylaxis measures on development of food hypersensitivity in young children in Lviv oblast.

Correlation between the levels of digitalization and economic indicators in Russian regions

This article is dedicated to examination of the questions of interinfluence of digital and traditional economy in the regions of the Russian Federation. On the one hand, digital economy stimulates the development of traditional economy; while on the other hand, digitalization requires acquisition of equipment, digital communication services, software, and recruitment of qualified personnel. The interaction of digital and traditional economies differs in the regions with commodity sector, industrial regions, mixed economy regions, metropolitan areas, and territories with low population density. The growing importance of digital economy in the overall development of the regions and the country requires comprehensive examination of digitalization processes with regards to both, economy and society. The scientific novelty consists in the use of big data for tracing correlations between the available indicators of development of digital economy and various aspects of traditional economy established in the Russian region. Based on the database of the Unified Interdepartmental Information Statistical System, the author constructed scatter diagrams, calculated correlation coefficients and trend lines to determine the interdependence of these indicators. The article examined the link between the number of personal computers in the region, level of public access to the Internet, GRP, cost of labor, and users of satellite communication systems. The author determines the instances of positive and negative interinfluence, and discusses the probable causes their different vector.

Examining the Relationship between Altmetric Score and Traditional Bibliometrics in the Ophthalmology Literature for 2013 and 2016 Cohorts.

Background In this study, we reviewed a select sample of ophthalmology literature to determine if there was a correlation between Altimetric and traditional citation-based and impact factor metrics. We hypothesized that Altmetric score would more closely correlate with impact factor and citations in 2016. Methods Journal Citation Reports for the year 2013 was used to find the 15 highest impact factor ophthalmology journals in 2013. Then Elsevier's Scopus was used to identify the 10 most cited articles from each journal for the years 2013 and 2016. Metrics for all identified articles were collected using the Altmetric Bookmarklet, and date of Twitter account creation was noted for journals with such an account. Altmetric scores, impact factor, and citation counts were tabulated for each article. Pearson's correlation coefficient ( r ) determined correlation of independent variables (number of citations or impact factor) with dependent variable (Altmetric score). For our Twitter analysis, account age was the independent variable and calculated correlation coefficients ( r ) were the dependent variable. Proportion of variance was determined with a coefficient of determination ( R 2 ). Results This study included 300 articles, evenly split between 2013 and 2016. Within the 2013 cohort, three journals had significant positive correlations between citation count and Altmetric score. For the 2016 cohort, both Altmetric score and citation count ( r = 0.583, p < 0.001) and Altmetric score and impact factor ( r = 0.183, p = 0.025) revealed significant positive correlations. In 2016, two journals were found to have significant correlations between Altmetric score and citation number. Neither year revealed a significant correlation between the age of a journal's Twitter profile and the relationship between Altmetric score and citation count. In each year, Twitter accounted for the highest number of mentions. Conclusion The findings suggest that correlation between Altmetric score and traditional quality metric scores may be increasing. Altmetric score was correlated with impact factor and number of citations in 2016 but not 2013. At this time, Altmetrics are best used as an adjunct that is complementary but not an alternative to traditional bibliometrics for assessing academic productivity and impact.

Формирование структуры каолина, обработанного давлением

To form the technological properties of clays, various methods of their activation have been developed, the essence of which is that when processing clays, their structure (defectiveness) changes, which forms the energy potential of clay particles, and the latter is realized in the form of "specified" physicochemical properties of clays. In this regard, the effect of stress pressure on the change in the defectiveness of structural elements of kaolin was studied. Experimental studies showed that the pressure value P = 150 MPa was the boundary value at which different conditions for the formation of defectiveness of structural elements of kaolin were observed. High pressure has a multidirectional effect on the defectiveness formation of the kaolin structural elements: a package, a mineral, a colloid and an aggregate. In a package of kaolinite mineral, the defectiveness increases with increasing pressure. Defects are formed due to the removal of Al, Fe, Mg, Si ions from the octahedral and tetrahedral sheets. Al ions are the most sensitive to pressure. The removal of ions entails deformation of the packet and the formation of "hole" energy centers. Pressure up to 0–150 MPa has a greater effect on the formation of defectiveness (calculated correlation coefficient rс = 0.86) than in the range 150–800 MPa (rс = 0.82). In the kaolinite mineral at pressures up to 150 MPa, a decrease in defectiveness is observed due to the ordering of the structure under pressure (rс = 0.67). At pressures above 150 MPa, an increase in the defectiveness of the kaolinite mineral (rс = –0.72) is observed due to the destruction of hydrogen bonds between the packets, which entails the sliding and rotation of the structural packets among themselves. In a colloid (particle), with an increase in pressure to 150 MPa, the structural defect decreases due to an increase in the colloid density (rс = 0.67). In the pressure range of 150–800 MPa, it is rather difficult to reveal the effect of pressure on the formation of defectiveness (rс = 0.37). In the aggregate, with an increase in pressure to 150 MPa, the defectiveness of the structure increases due to crushing of particles, sliding and displacement of particles among themselves (rс = 0.95). In the pressure range of 150–800 MPa, it is rather difficult to reveal the influence of pressure on the formation of defectiveness (rс = 0.58), although the tendency increases with increasing pressure, the defectiveness of the aggregate remains.

ECONOMIC AND MATHEMATICAL MODELING OF THE LEVEL OF MOTIVATION IN AGRICULTURAL ENTERPRISES

Introduction. To date, the high turnover of staff, their aging and declining productivity in enterprises of the agricultural sector of the economy are studied. There is a need to assess the effectiveness and feasibility of the existing system of intangible incentives in terms of its importance to stabilize personnel policy, as well as identify areas for improvement of this system, offer tools for diagnosing staff motivation, build an econometric model, substantiate recommendations for improving intangible resources. Purpose. The aim of the article is to analyze publications that consider methods of motivating personnel of enterprises, the use of mathematical apparatus to calculate the integrated assessment of motivation of personnel of enterprises, construction and analysis of econometric model of intangible methods of motivating labor resources of agricultural enterprises of Dnepropetrovsk region. Method (methodology). The article uses the results of a survey of employees of agro-industrial enterprises; methods of correlation-regression analysis are used for the calculation of results as one of the main methods of scientific research; methods of mathematical modeling. Results. An econometric multifactor regression model of the indicator of integrated assessment of labor resources motivation of agro-industrial enterprises is constructed as a result of the research. There is a direct relationship between the state of the indicator and the assessments of employees on the components of intangible methods of motivation. The results of the calculations allowed us to conclude: an increase in the assessment of employees on the possibility of professional training by 1 point indicates an increase in the integrated assessment of the indicator by 0.998; the rise of the assessment of the possibility of career growth by 1 point enlarges the integrated assessment on 0.846; an increase in the score on the provision of soft loans by 1 point provides the going up in the integrated score by 0.587; increasing the assessment by the method of leisure incentives leads to the grow of the integrated assessment by 0.518; the rising assessment of employees for the provision of discounted meals by 1 point increases the integrated estimation by 0.605; increasing the scores on transport support and the possibility of recovery at the expense of the company by 1 point also brings up the integrated score by 0.471 and 0.603, respectively. The calculated correlation coefficients between each of the factors and the integrated indicator demonstrate a significant correlation and the influence of each factor on the integrated indicator. In this regard, it is necessary to continue to apply the methods of mathematical modeling, which allow to estimate not only the level of motivation, but also to develop and implement an effective mechanism for further development of labor resources in agricultural enterprises.

Some new Pythagorean fuzzy correlation techniques via statistical viewpoint with applications to decision-making problems

Pythagorean fuzzy set is a reliable technique for soft computing because of its ability to curb indeterminate data when compare to intuitionistic fuzzy set. Among the several measuring tools in Pythagorean fuzzy environment, correlation coefficient is very vital since it has the capacity to measure interdependency and interrelationship between any two arbitrary Pythagorean fuzzy sets (PFSs). In Pythagorean fuzzy correlation coefficient, some techniques of calculating correlation coefficient of PFSs (CCPFSs) via statistical perspective have been proposed, however, with some limitations namely; (i) failure to incorporate all parameters of PFSs which lead to information loss, (ii) imprecise results, and (iii) less performance indexes. Sequel, this paper introduces some new statistical techniques of computing CCPFSs by using Pythagorean fuzzy variance and covariance which resolve the limitations with better performance indexes. The new techniques incorporate the three parameters of PFSs and defined within the range [-1, 1] to show the power of correlation between the PFSs and to indicate whether the PFSs under consideration are negatively or positively related. The validity of the new statistical techniques of computing CCPFSs is tested by considering some numerical examples, wherein the new techniques show superior performance indexes in contrast to the similar existing ones. To demonstrate the applicability of the new statistical techniques of computing CCPFSs, some multi-criteria decision-making problems (MCDM) involving medical diagnosis and pattern recognition problems are determined via the new techniques.

Profitability determinants of Nepalese commercial banks

Purpose- The purpose of this study is to examine the the key determinants of profitability of Nepalese commercial banks. Methodology- This study employs descriptive statistics to describe the profitability of Nepalese banks and its determinants. Further, the degree of correlation among different indicators of profitability and its determinants has been assessed by calculating correlation coefficient. Finally, this study has adopted a panel data regression model (Fixed Effect Model and Random Effect Model) to investigate the determinants and their impact on profitability of Nepalese commercial banks. Findings- The analysis reveals that the bank pofitability measured by ROA of Nepalese commercial banks is significantly affected by concentration ratio, banking sector development, GDP growth, inflation and exchange rate significantly in opposite direction rather it is not significantly affected by the internal factors like bank size, capital base, deposit, loan, off-balance sheet activities and number of branches. Another indicator of bank profitability; NIM is significantly affected only by capital adequacy, absolute number of branches and inflation rate. Conclusion- This study concluded that the profitability of Nepalese commercial banks measured by return on assets is significantly influenced by the external factors. Among external factors, industry specific factors have high degree of impact on return on assets whereas macroeconomic variables have quite a weak degree but significant impact on profitability of Nepalese commercial banks as measured by return on assets. Further, the profitability measured by net interest margin (NIM) is significantly influenced only by capital adequacy, absolute number of branches and annual inflation rate.

Effect of the Acoustic Impedance Mismatch at the Bone-Soft Tissue Interface as a Function of Frequency in Transcranial Ultrasound: A Simulation and In Vitro Experimental Study.

The transcranial Doppler (TCD) ultrasound is a method that uses a handheld low-frequency (2-2.5 MHz), pulsed Doppler phased array probe to measure blood velocity within the arteries located inside the brain. The problem with TCD lies in the low ultrasonic energy penetrating inside the brain through the skull, which leads to a low signal-to-noise ratio. This is due to several effects, including phase aberration, variations in the speed of sound in the skull, scattering, the acoustic impedance mismatch, and absorption of the three-layer medium constituted by soft tissues, the skull, and the brain. The goal of this article is to study the effect of transmission losses due to the acoustic impedance mismatch on the transmitted energies as a function of frequency. To do so, wave propagation was modeled from the ultrasonic transducer into the brain. This model calculates transmission coefficients inside the brain, leading to a frequency-dependent transmission coefficient for a given skin and bone thickness. This approach was validated experimentally by comparing the analytical results with measurements obtained from a bone phantom plate mimicking the skull. The average position error of the occurrence of the maximum amplitude between the experiment and analytical result was equivalent to a 0.06-mm error on the skin thickness given a fixed bone thickness. The similarity between the experimental and analytical results was also demonstrated by calculating correlation coefficients. The average correlation between the experimental and analytical results came out to be 0.50 for a high-frequency probe and 0.78 for a low-frequency probe. Further analysis of the simulation showed that an optimized excitation frequency can be chosen based on skin and bone thicknesses, thereby offering an opportunity to improve the image quality of TCD.

THE VARIABILITY OF SOME CHARACTERS AND THEIR CORRELATIONS WITH THE YIELD OF AN EXTENSIVE ASSORTMENT OF AUTUMN WHEAT VARIETIES, TESTED ON THE CHERNOZEM FROM ARDS CARACAL

In 2021 year, 120 cultivars of winter wheat were tested on the Caracal chernozem in microplots. The following traits were determined: yield, thousand kernel weight, test weight, days from 01.01 to heading date. The variability of the characters was studied by the method of boxplots and variability coefficients. The obtained yield registered values between 12306 kg / ha for the Romanian cultivar Ursita and 5803 kg / ha for the KWS Marvel cultivar. The plant height had values between 110 cm for the Kapitol cultivar and 69 cm for the Avenue cultivar. The test weight showed values in the range 78 kg / hl (Apexus) - 64.2 kg / hl (Atuan). The thousand kernel weight recorded values between 47.2 g for the SY Starlord cultivar and 29.29 g for the Amburgo cultivar. The period from 01.01 to heading date lasted between 143 days (Sophie and Lennox) and 123 days (Tata Mata and Felix). The highest coefficient of variability was presented by the yield, this being over 10%. The lowest variability was registered by the test weight and the period from 01.01 to heading date, the values being around 3%. The analysis of the variability of the yield by the boxplot method highlighted a negative outlier (KWS Marvel cultivar). From the point of view of plant height, by the same method, three positive outliers were observed - Kapitol, Bezostaia and Exotic. Their height - 110, 109, and 108 cm, respectively, is significantly larger than that of all other cultivars. The values of the calculated correlation coefficients suggested that in the climatic conditions of 2020-2021 agricultural year, the yield was not correlated with any of the studied characters, the coefficients being below Analele Universităţii din Craiova, seria Agricultură – Montanologie – Cadastru (Annals of the University of Craiova - Agriculture, Montanology, Cadastre Series) Vol. 51/1/2021 245 0.21 (the value from which the correlation could be considered significant at P = 5%).