Distribution Of Values Research Articles

A-165 Value Of Monocyte Distribution Width In Bacteremia Assessment In Emergency Department Patients

Abstract Background Monocyte distribution width (MDW) is an immune response biomarker and part of a CBC differential. MDW is derived from the distribution of monocyte volumes and elevated MDW values correlate with severe infections and sepsis in Emergency Department (ED) adult patients. Neutrophil to lymphocyte ratio (NLR) is predictive of infections and inflammatory stress. Evaluating these biomarkers could be valuable in bacteremia risk assessment. Bacteremia is the presence of viable bacteria in the bloodstream and is present in up to 20% of septic patients. Blood cultures establish pathogen identity but require culture time, potentially delaying appropriate treatment. Our goal was to characterize MDW and NLR clinical performance in ED patients with suspected bacteremia. Methods This was an observational cohort study of ED patients 18 years and older with CBC differential and blood cultures obtained. MDW values ≥20 is the published cut-off for increased infection risk. Clinical literature suggests that NLR ≥3 is abnormal. We assessed the diagnostic performance of MDW and NLR for positive blood cultures using SPSS Version 25. Results From 07/2021-09/2023, 9,400 blood cultures were ordered and 5174 patients had differential CBCs. The overall blood culture positivity rate was 14.4%. MDW and NLR performance for positive blood cultures is shown in Table 1. Conclusions Our analysis provides evidence that MDW and NLR may be useful for early recognition of bacteremia in ED patients. CBC differential results are reported sooner than culture results. MDW is directly reported, NLR can be readily calculated from the differential. Therefore both could contribute to earlier risk stratification and our findings suggest potentially distinct information from MDW and NLR. Combining MDW with other CBC parameters may provide additional diagnostic advantage. Further analysis will incorporate added clinical data for enhanced decision support in interpreting MDW values in the context of pending blood culture results.

On the phase consistency of apical organ of Corti vibrations

Low-frequency hearing is critically important for speech and music perception. However, technical and anatomical limitations previously made it difficult to study the mechanics of the low-frequency parts of the cochlea, but this changed with the introduction of optical coherence tomography vibrometry. With this technique, sound-evoked vibration can be measured from the apex of a fully intact cochlea. Results of such measurements generated controversy because conventional traveling waves, the hallmark of which is longer group delay closer to the helicotrema, were absent within the apical 20% of the guinea pig cochlea (Burwood et al, Science Advances 8:eabq2773, 2022). The validity of this result was questioned, primarily because group delays were calculated from phase values averaged across many points within the organ of Corti. Here we show that variations in phase across the organ of Corti are minor and does not affect the group delay significantly. We also assess the precision of phase measurements with optical coherence tomography. An artificial target with reflectivity similar to the organ of Corti was used. These measurements revealed that a commonly used commercial optical coherence tomography system produces half-cycle errors in 1-5% of pixels, leading to a bimodal distribution of phase values. This problem can be easily addressed by using medians when computing averages, as was done by Burwood et al (2022). Hence, neither averaging across pixels nor technical factors can explain the apparent lack of conventional traveling waves at the apex of the guinea pig cochlea at low stimulus levels. The physiological mechanisms that operate at the apex apparently differ from other cochlear regions.

Validating the Vegetable Variety Navigator Decision-support Tool Using Recent On-farm Variety Trial Data

Local variety trial data are necessary for informing growers how a specific variety might perform on their farm but there is a growing deficiency in these data, particularly for specialty crops. To address this issue, an online decision-support tool named the Vegetable Variety Navigator (VVN) was developed in 2020 to compile, analyze, and visually communicate publicly available broccoli (Brassica oleracea var. italica), cucumber (Cucumis sativus), and sweet pepper (Capsicum annuum) variety trial data. To validate the accuracy and predictive potential of the VVN, we conducted 16 on-farm variety trials for broccoli, cucumber, and sweet pepper between 2020 and 2022. Yield of each variety in a trial was compared with the mean of all other varieties in the same trial to calculate a mean relative yield (MRY). The difference between observed relative yield in the field and predicted relative yield from the VVN (ΔMRY) was used to assess the accuracy of three different VVN prediction strategies. Strategies included using data from the following: 1) the single geographically nearest trial, 2) the mean of the three geographically nearest trials, or 3) the mean of all available trial data regardless of location. Compared with random predictions of MRY for each variety (from within a normal distribution of MRY values in the VVN database), the VVN predictions reduced ΔMRY and improved the accuracy of relative yield predictions across varieties by up to 21% in broccoli, 51% in cucumber (depending on strategy), and 51% in sweet pepper. Results confirm the value of the VVN as a decision-support tool for growers facing an ever-increasing number of crop variety options with less variety trial data. Future research and development are needed to improve the accuracy of the VVN by accounting for possible effects of crop types, management, and location on relative yield and quality.

Surface geochemistry as a key to understanding the petroleum system in regions of complex geology - Polish Outer Carpathians

The goal of the study is to investigate the relationships between soil gas composition and geological structures in a structurally complex area of the Carpathian fold and thrust belt. Surface geochemical surveys, aimed at determining the molecular and isotopic composition of soil gas samples, were carried out in the central part of the Polish Outer Carpathians in two major tectonic units, the Magura Unit and the Fore-Magura Group of units, which outcrop at the front of the former and within it as a tectonic window (the so-called Mszana Dolna Tectonic Window, MDTW). The tectonic structure of the area has numerous deformations, such as folds, thrusts, and strike-slip faults, that are accompanied by broad zones of mélange. In all 572 soil gas samples, the concentrations of light alkanes, gaseous alkenes as well as non-hydrocarbon (e.g. hydrogen) components were determined, and part of the samples were analysed to test the carbon isotope composition of methane and carbon dioxide.The results of the surface geochemical survey showed significant differences in the recorded microconcentrations of hydrocarbons within the tectonic units of the Outer Carpathians. Significantly higher concentrations of total alkanes C2-C5 were mainly recorded in the MDTW, although the distribution of total alkane values within the Window shows strong connections with the arrangement of strata and the strike of faults and thrusts. Generally, the sealing is insufficient within the MDTW to support the existence of conventional economically viable hydrocarbon accumulations. Our data confirms the sealing role of the Magura Unit in the Carpathian oil system. Therefore, hydrocarbon sources (i.e. potential hydrocarbon accumulations) may be expected within the Fore-Magura Group beneath the cover of the Magura Unit.Our results are also of key importance for the interpretation of surface geochemistry data in other oil and gas provinces with a complex geological structure.

Antimicrobial susceptibility of Clostridium botulinum group III field strains isolated in Europe from animal outbreaks

Neurotoxins produced by Clostridium (C.) botulinum group III are responsible for the majority of botulism outbreaks occurring in animals and in this study we report the drug susceptibility of 71 field strains.The minimum inhibitory concentration (MIC) of 13 antimicrobials was established through the agar dilution method. The MIC50 matched or differed for one or two dilutions from MIC90 of the same antimicrobial, showing a unimodal distribution of the MIC values, irrespective of the geographical origin, the animal source and the toxinotype of the strain. Beta-lactams and rifampin showed the lowest MIC values, while gentamicin, polymyxin B and sulfamethoxazole showed the highest MICs. As for similar studies conducted in human botulism, the results could be helpful to avoid the administration of antimicrobials that could worsen the health condition of the affected animals and to develop selective media for the isolation of these fastidious anaerobes. Indeed, the isolation of the strain from affected animals and from environmental samples is important to perform epidemiological studies based on the genetic characterization and to produce tailor-made vaccines.

Analysis of subsurface Resistivity Structures in Relation to the Level of Damage Caused by Earthquakes Using the Audio-Magnetotelluric (AMT) Method (Case study: the 2006 Yogyakarta Earthquake)

Abstract The 2006 Yogyakarta Earthquake had caused a disaster in Bantul area. Although the magnitude reached only Mw = 6.4, it left more than 6,000 fatalities and up to 1,000,000 homeless. The earthquakes that occur in this area is shallow earthquakes that originate on land (Opak fault) and triggers quite high surface damage. This damage includes damage to buildings and infrastructure that support community activities. The main objective of this research is to determine the subsurface structure and be able to identify soft layers based on the distribution of resistivity values that can be correlated to the value of the amplification factor. The Audio-Magnetotelluric (AMT) method was conducted in this area using five components of electric and magnetic fields. The Audio-Magnetotelluric (AMT) method utilizes electromagnetic waves with a frequency of 1 Hz to 100KHz. Based on the one-dimensional (1-D) inversion result calculated from 3 sites show that there is a low resistivity value (10 - 70 Ωm) from the surface to the depth of 1000 m. This ticked conductive zone interpreted as a sediment layer that can triggers the high amplification factor values.

Analysis of the annual number of tropical cyclones over Japan using the extreme value theory

We predicted the extreme value of the annual number of typhoons, tropical cyclones over the western North Pacific, approaching typhoons, and landing typhoons for 1951–2019 over Japan and the minimum central pressure for 1987–2020 using the extreme value theory. The generalized extreme value (GEV) distribution was used to fit the extreme indices. Various diagnostic plots for assessing the accuracy of the GEV model fitted to the annual number of typhoons, approaching typhoons, and landing typhoons are shown, and all four diagnostic plots support the fitted GEV model. The shape parameter ξ for the annual number of typhoons and approaching typhoons is negative, and the number of typhoons has a finite upper limit. The calculated upper limits were 44.5 and 23.2 for the annual number of typhoons and approaching typhoons, respectively. However, ξ in the number of landing typhoons was zero; therefore, the number of landing typhoons did not have a finite upper limit, and there was a possibility that a significant risk would occur. The number of typhoons increased for 1951–2019. The minimum central pressure of typhoons estimated using geostationary satellite images decreased for 1987–2020, and the number of strong typhoons increased. The annual number of violent typhoons ( 54 m/s) increased in the 2010s. The calculated limit of the minimum central pressure of the typhoon is 877 hPa. When the Pacific Decadal Oscillation (PDO) index is positive, more violent typhoons tend to occur.

Integrating heterogeneous information for modeling non-stationarity of extreme precipitation in the Yangtze River Basin

Extreme precipitation exhibits non-stationary characteristics due to climate change and land use/cover change in recent years. In the literature, probability distributions with varying parameters associated with covariates have been applied to describe the non-stationarity of extreme precipitation. However, there is no consensus on the optimal distributions and the number and type of covariates for constructing non-stationary models. This study comprehensively investigates and determines the optimal distribution models, the type of covariates, and the number of covariates to best characterize the non-stationarity of extreme precipitation, using the Yangtze River Basin as the study area. The time series of four indices representing extreme precipitation of different durations and intensities are fitted by stationary and non-stationary Generalized Additive Models for Location, Scale, and Shape. The models are constructed using seven distributions and four types (time, global climate, local climate, and land cover) of covariates. Each model incorporates one to three covariates simultaneously. The results show that the most preferred distribution is the Generalized Extreme Value distribution for very wet-day precipitation, while the Log-Normal distribution is more suitable for other extreme precipitation indices. For the type of covariates, when using a single covariate, the proportion of stations using a global climate covariate as the best covariate (22.3 %–33.2 % of 193 stations) is close to that using a local climate covariate as the best covariate (22.3 %–27.5 %). The proportion of stations using land cover as the best covariate is much lower (7.3 %–10.9 %), while that using time as the best covariate is the lowest (1.6 %–4.1 %). When using multiple covariates, the models with both global and local climate covariates are mostly selected (8.3 % to 17.6 %) for all extreme precipitation indices. For the number of covariates, one or two covariates are enough to describe the non-stationary behaviors of all extreme precipitation indices. This study emphasizes the necessity to use non-stationary models for extreme precipitation frequency analysis with careful consideration and selection of distributions and covariates.

Development of diesel combustion with low cooling loss and high dispersion spray using two-dimensional optical measurements

In this study, a novel, high-efficiency, and clean combustion concept utilizing low cooling loss and high dispersion spray is proposed. The research aims to validate the objectives of this concept through spatiotemporal analysis of phenomena when key variables such as combustion chamber shape, spray parameters, and swirl are modified. This new combustion approach focuses on achieving low heat loss by using smaller nozzle diameters, multi-hole nozzles, and reduced swirl compared to conventional combustion. The combustion chamber is designed with an increased cavity diameter and an expanded taper diameter to enhance upward spray dispersion, thereby reducing fuel spray penetration into the cavity and decreasing cooling loss. This configuration reduces the fuel spray penetration in cavity, achieving a reduction in cooling heat loss. Furthermore, to increase the volume in the lower part of the combustion chamber, a corner-bottom shape is employed. Additionally, by causing spray impingement through the corner bottom shape, the strategy aimed to prevent the return of the mail injections to the central part of the combustion chamber. These parameters were evaluated using two-dimensional optical measurements, which calculated thermal flux, temperature, velocity, and KL value distributions. The impact of cavity diameter on internal cooling loss is significant, and preventing flame stagnation from a smoke perspective is crucial. An increase in taper diameter reduces squish velocity, achieving heat losses reduction, while necessitating spray dispersion into the squish area. The influence of swirl ratio on heat losses is more pronounced in the squish and taper areas than inside the cavity, necessitating consideration of flame temperature reduction within the cavity when reducing swirl ratios. The implementation of double after injection influences low heat losses and avoids flame stagnation, enabling soot reduction. The corner bottom shape combustion chamber proved effective in reducing heat losses and particulate matter (PM) at medium and high loads.

POLARIZATION-CORRELATION MAPPING OF MICROSCOPIC IMAGES OF BIOLOGICAL TISSUES OF DIFFERENT MORPHOLOGICAL STRUCTURE

The results of polarization-correlation mapping of the fourth parameter of the two-point Stokes vector of microscopic images of histological sections of biological tissues with different architectonics of the optically anisotropic polycrystalline component are presented. The coordinate distributions of randomly generated values representing the modulus of the fourth parameter of the polarization-correlation vector from microscopic images of histological sections of fibrillar tissues (such as skin dermis) and parenchymal tissues (like spleen) have been replicated. The statistical analysis results of algorithmically generated coordinate distributions of random values representing the modulus of the fourth parameter of the polarization-correlation vector from microscopic images of histological sections of biological tissues with varying morphological structures are provided.

Experimental study of shielding gas concentration on mechanical properties of stainless steel alloy parts using wire and arc additive manufacturing

Wire Arc Additive Manufacturing (WAAM) is an emerging three-dimensional fabrication technology that enables higher deposition rate, material savings, and near net-shape. In this study, various shielding gas concentration (SGC) of argon (Ar) and carbon-di-oxide (CO2) was employed to fabricate 316L using Cold Metal Transfer (CMT) WAAM process. Microstructure characteristics and mechanical properties of thick-walled parts were studied. Microstructure studies show a combination of columnar and equiaxed grains in various regions. Microhardness results exhibit the uneven distribution of hardness value from bottom to top region along the building direction and the values are ranging between185 and 240 HV. Tensile studies indicates the both horizontal and vertical direction samples secures the higher ultimate tensile strength (UTS), yield strength (YS) and elongation (EL) values and confirmed the isotropic properties. Fractography studies prove ductile fracture with the evidence of dimples and enough plastic deformation. From the experimental results, the SGC-2 possesses finer solidification structure and higher mechanical properties than the other samples. The as-fabricated WAAM parts possess higher mechanical properties than the 316L parts fabricated via casting and wrought parts.

TWO-DIMENSIONAL HYPERCHAOTIC MAP FOR CHAOTIC OSCILLATIONS

This manuscript explores a two-dimensional hyperchaotic map for generating chaotic oscillations. Hyperchaotic maps are finding increasing applications in various scientific and technological fields due to the unique properties of their generated oscillations. The studied map, based on two interconnected piecewise-linear functions, is one of the simplest for generating oscillations with a predetermined distribution of values across a continuous parameter space. This simplicity allows for wide applicability in various contexts. The paper presents simulation results demonstrating control over the parameters of the dynamic modes. Building upon these modeling results, a two-dimensional hyperchaotic system is implemented using an electric circuit. The chosen map is attractive due to its inherent simplicity and ease of parameter control. By adjusting these parameters, the distribution of the generated signal's values can be manipulated. The circuit consists of two symmetrical sections connected via feedback loops, employing four amplifiers with variable gain. The gain values act as the circuit's implementation of the control parameters. Chaotic oscillations are generated by applying a delayed clock signal from an external square wave generator to circuit elements. The obtained experimental results exhibit excellent agreement with the simulation data.

THE INFLUENCE OF CORPORATE SUSTAINABILITY ON TAX DISTRIBUTION AND DIVIDEND DISTRIBUTION

This study investigates the impact of corporate sustainability on effective tax rates and dividend payout ratios among companies listed in the LQ45 index over the period from 2018 to 2022. Corporate sustainability is increasingly recognized as a crucial aspect of business strategy, influencing financial structures and shareholder value distribution. Utilizing a panel data analysis taken from Bloomberg, we explore how sustainability growth rate affect their tax strategies and dividend policies. Our findings reveal a nuanced interaction between corporate sustainability and fiscal obligations. Specifically, the study indicates that higher levels of corporate sustainability correlate with a lower effective tax rate; however, this relationship is statistically insignificant. This suggests that while sustainable practices may influence tax-related decisions, other factors such as changes in tax legislation, profitability, and tax planning strategies might play more pivotal roles in determining the effective tax rate. Conversely, the impact of corporate sustainability on dividend payout ratios is both negative and statistically significant. Companies with robust sustainability practices tend to reinvest a greater portion of their earnings back into the business to support sustainable growth and long-term value creation, leading to lower dividend distributions. This finding highlights the prioritization of capital retention over immediate shareholder returns among sustainably focused firms in the LQ45 index. This research contributes to the understanding of how sustainability initiatives intersect with financial policies within Indonesian listed companies. The insights provided could help investors and policymakers better understand the financial implications of sustainability growth rate, particularly in emerging markets where such practices are gaining momentum. The results also suggest areas for further research, particularly in exploring the indirect pathways through which sustainability might influence corporate financial policies.

Revisiting design wind speed and cyclonic factor for east coast of India

It is very much challenging to estimate the accurate design wind speed for engineering structures of India, those experiencing extreme wind events such as cyclones. However, there are different categories of structures based on their importance level and a trade-off always exists between structural safety and economy. Indian code IS15498 specifies uniform cyclonic factors. However, a wide variation has been found while considering different return periods and threshold wind speeds above which cyclones have been modelled. Accordingly, a cyclonic factor (k4) has been calculated using three distinct approaches. These include the Gumbel distribution with the Generalized Least Squares Method (GLSM), the Generalized Extreme Value distribution with the Least Squares Method, and the Peaks over Threshold approach employing the De Haan method. These methods were applied to the dataset of peak values from all cyclone events to determine the design wind speed and, subsequently, the cyclonic factor. The analysis shows that Gumbel distribution with GLSM provides the best results with 1.03 value of cyclonic factor. Reverse Weibull can also be used to fit the extreme wind speed data. The outcomes from all approaches consistently underscore the necessity of a cyclonic factor for the east coast of India.

Строение центральной части палеопротерозойского Лосевского террейна по данным плотностного моделирования

The results of detailed three-dimensional density modeling of the upper crust of the central part of the Losevsky terrane located in the northern part of the Voronezh crystal massif are considered. The distribution of absolute crustal density values of to a depth of 16 km was obtained as a result of the inversion of local anomalies of the gravitational field in the Bouguer reduction. The solution of the inverse problem of gravimetry was implemented within the framework of the initial model, which was formed using digital geological and geophysical data from the study area: the regional density model of the East European Platform lithosphere and its corresponding regional gravity field; the field of local gravity anomalies, representing the difference between the observed and regional fields of the lithosphere model; generalized information on the density of sedimentary cover rocks and the crystal basement; the thickness scheme of the «gravity-active» layer, obtained on the basis of statistical analysis of the anomalous field; geological and topographic information. Quantitative interpretation of the gravimetry data allowed us to obtain fundamentally new information about the geological structure of the upper crust of the study area. The reliability of the obtained results is confirmed by the consistency of a priori data and the correspondence of the total model (local plus regional) and observed gravitational fields.

Machine Learning-Assisted Prediction of Stress Corrosion Crack Growth Rate in Stainless Steel

Stainless-steel is extensively utilized in the key structural components of the main equipment in the nuclear island of pressurized water reactor nuclear power plants. The operational experience of nuclear power plants demonstrates that stress corrosion is one of the significant factors influencing the long-term safe operation of stainless steel in the high-temperature water of pressurized water reactor nuclear power plants. This study is based on the stress corrosion crack growth rate data of 316SS and 304SS stainless steel in the simulated primary water environment of pressurized water reactor nuclear power plants. Data mining and modeling were conducted using multiple machine learning algorithms, including Random Forest (RF), eXtreme Gradient Boosting (XGBoost), Support Vector Regression (SVR), and Gaussian Process Regression (GPR), and the Sharpley Additive explanation (SHAP) method was employed to analyze the interpretability of the model. The results indicate that the stress corrosion crack growth rate prediction model based on XGBoost outperforms other models in all assessment indicators. Compared with empirical equations, XGBoost exhibits high flexibility and excellent data-driven learning capabilities. In the test set, 90% of the prediction errors are within the range of experimental values, with the maximum error multiple being 2.5, which significantly improves the prediction accuracy. Moreover, the distribution of SHAP values is consistent with the theoretical study of the stress corrosion behavior of stainless-steel, effectively reflecting the impact of cold working, temperature, and stress intensity factor on the stress corrosion crack growth rate, thereby proving the reliability of the model’s prediction results. The achievements of this study hold significant reference value and application prospects for the prediction of the stress corrosion behavior of stainless-steel in a high-temperature and high-pressure water environment of pressurized water reactor nuclear power plants.

Value distribution of a pair of meromorphic functions

The well-known Picard theorem shows only what happens on the Picard exceptional value of a meromorphic function f. In this paper, we mainly consider what happens on the common or different Picard exceptional values of two or three meromorphic functions with certain types. For instance, we will provide some new results and discussions for the generalized Picard exceptional values or small functions of a pair of meromorphic functions fng(k) and gmf(k), these two functions are the crossed variants of the complex differential polynomials in Hayman's conjecture, where n, m are positive integers and k≥0. We give more details on the case that fg′ and gf′ when f and g are exponential polynomials in particular.

Simulation and Measurement of Strain Waveform under Vibration Using Fiber Bragg Gratings.

The work is devoted to the consideration of methods for determining the strain of objects using fiber Bragg gratings under a high-frequency vibration or pulsed mechanical action, which is difficult to perform using widespread methods and devices. The methods are based on numerical processing of the time dependence of the radiation power reflected from the fiber Bragg grating at various wavelengths, which makes it possible to measure strain parameters in a wide range of magnitude and frequencies. The efficiency of the proposed methods is demonstrated by numerical simulation. It is shown that it is possible to restore the strain dependence on time in the range ±1000 μϵ or more from simultaneously measured power dependencies reflected by the fiber Bragg grating using common fiber-optic components. The case of sequential registration of reflected radiation power at different wavelengths to determine the probability density of the distribution of the strain values is also considered. The results of signal processing obtained both by numerical simulation and experimentally for the case of a linear vibration are presented. The technical problems of using the proposed methods are discussed.

Continuity of long-term climate data series after the transition from manual to automatic weather station

In climatology, transitioning from conventional manual weather stations (MWS) to automatic weather stations (AWS) presents challenges in maintaining the homogeneity of long-term data series. At the Skalnaté Pleso Observatory (1778 m a.s.l., High Tatras), manual meteorological measurements have been conducted since 1943 using the same methods and devices at the same location. In 2014, the AWS Physicus was installed to record meteorological data parallelly with manual measurements. This study processed six years of parallel measurements (2017–2022) to derive corrections for AWS monthly atmospheric precipitation totals and maximum (Tmax), minimum (Tmin) and mean air temperatures (Tmean) measured in 2023. Two correction approaches were proposed: monthly regressions (MR) and cumulative distribution functions (CDF), including Generalized Extreme Value (GEV) distribution, normal distribution (GAUSS), and Gamma distribution (GAMMA). Analyses of monthly data revealed an underestimation of precipitation totals in AWS data, with a mean bias error (MBE) of −6.8 mm and a root mean squared error (RMSE) of 20.0 mm. The most suitable correction method was the MR, which decreased MBE to 1.5 mm and RMSE to 11.1 mm. AWS monthly air temperature data were overestimated by 0.1 °C, 0.3 °C, and 0.1 °C for Tmax, Tmin, and Tmean, respectively. For Tmax, correction using the MR and GEV methods reduced the MBE to 0.0 °C and achieved RMSE of 0.1 °C for both. After applying GAUSS, MBE and RMSE decreased to 0.1 °C. The most appropriate correction method for Tmin was the MR resulting in MBE of 0.0 °C and RMSE of 0.3 °C. For Tmean, the MR and GEV methods reduced the MBE to 0.0 °C and the RMSE to 0.1 °C for both methods. These results demonstrate that AWS monthly data, when corrected using the presented methods, have the potential to maintain the continuity of historical climate data series at Skalnaté Pleso.

Research on the Influence of Matrix Shape on Percolation Threshold Values for Current Flow Conducted Using the Monte Carlo Simulation Method

In this study, in order to determine the effect of matrices’ shape on the percolation threshold values, computer simulations were performed using the Monte Carlo method for a 200 × 200 square-shaped matrix and rectangular matrices containing the same number of nodes as the square matrix. Based on the simulations, the average values of the percolation thresholds and standard deviations for the current flow along and across the matrices were determined. It was determined that for a square-shaped matrix, the average values of the percolation thresholds in both directions of the current flow were the same. Extending the rectangular matrix while reducing its height causes the average value of the percolation threshold in the direction of the current flow along the matrix to increase from 0.592740 to 0.759847, while in the transverse direction, it decreases from 0.592664 to 0.403614. The values of the classical asymmetry coefficients of the probability distributions of the percolation thresholds for both directions of the current flow were determined. Histograms of the probability distributions of the percolation threshold values for a square-shaped matrix and rectangular matrices were made and compared with the normal distributions. It was found that the occurrence of two percolation thresholds in rectangular layers should be considered when analyzing the electrical conductivity measurements of nanocomposite thin films.