Graphic Correlation Research Articles

A palynological zonation for the Neogene of the Solimões/Amazon Basin, northwestern Amazonia

The tropical rainforests of northwestern Amazonia possess the highest plant diversity of any biome in the world. Understanding their origin, development, maintenance, and future in the face of ongoing global warming requires study of the plant fossil record and a predictive time framework. In this region, palynology is the best biostratigraphic tool because palynomorphs are the most abundant fossils. To construct a biostratigraphic zonation for the Neogene of the Solimões/Amazon basin in northwestern Amazonia, we analyzed palynological information from 25 sections, a total of 143,411 palynomorph grains from 622 samples. Using graphic correlation, we propose seven palynological zones that comprise the Miocene and a portion of the Pleistocene—the Pliocene is absent in the region. We then calibrated these zones against the geological timescale through correlation with a previously calibrated zonation and U/Pb geochronology.

RGrapCor: a tool for graphic correlation

Graphic correlation is a well-known biostratigraphical method that has been widely used for more than 40 years. During the 1980s, Kenneth Hood developed the program GraphCor, which was designed to run graphic correlation projects. However, the software was developed using DOS and it is no longer compatible with modern operating systems. To solve this issue, we developed rGraphCor, an open-source, free, and user-friendly application built within the R-for-computing environment and enhanced with the package Shiny, ensuring compatibility with Linux, macOS, and Windows operating systems. rGraphCor can use information from diverse sources including cores, ditch-cuttings, and outcrops to perform graphic correlation. The interactive nature of rGraphCor allows real-time updates, providing immediate feedback on correlation results. Additional R functions assist users in formatting their data, optimizing the analysis, and reducing errors. To demonstrate rGraphCor’s capabilities, we generated a randomized simulation of fossil data, representing hypothetical species across four sites with varying sampling patterns. This simulation showed the flexibility in handling diverse data sets and the robustness of its correlation capabilities. rGraphCor is available for public use, promoting transparency and collaboration in the biostratigraphic community.

INNOVATIVE STRATEGIES IN RISK MANAGEMENT AND CRISIS RESPONSE IN BUSINESS

The growth and sustainable development of companies depend on their ability to adequately and effectively identify and utilize innovative strategies. The aim of the study is to determine the results of the innovative strategy of international small and medium-sized enterprises (SMEs) in times of economic crisis. The research involved 360 owners and managers of international SMEs in the European Union. The study used tabular and graphical methods, surveys, questionnaires, and correlation and regression analysis. It was found that 82.7% of SMEs improved their production processes, while 62.8% implemented innovations by acquiring new products or equipment. It was established that 82% of enterprises implemented innovative strategies in the commercial or trade sector, 73.2% in the service sector, and 77.7% in other sectors. The models developed in the study contribute to the modern development of the economy since they analyze the relationship between innovative strategies and determinants affecting their successful implementation and implementation. Prospects for further research include analyzing the types of innovative strategies that prevail in the activities of international SMEs, as well as their size and sectors of activity.

Seed yield limitations of coriander (Coriandrum sativum L.) based on plant structure analysis

The present study describes the dependencies of key productivity and growth indicators of coriander plants on sowing rate and fertilization parameters. The aim of the research was to establish the patterns of coriander yield formation through the prism of plant structure considering modifications in nutrient conditions and sowing rates. Graphical models and correlation matrices were developed for three coriander varieties with similar morphological features (Oksanit, Nectar, Caribe). Data from field studies conducted in 2013–2015 in the Forest-Steppe zone of Ukraine serve as the basis for model construction. Two variable technological elements were studied (sowing rate of seeds; fertilization system) to determine the dependencies of biometric indicators for each variety. 3D graphical models of dependency for structural elements showed advantages over linear models. Seed yield of coriander in the study ranged from 1.24 t/ha with the lowest sowing rate to 1.91 t/ha with a sowing rate of 2.5 million seeds/ha. Maximum essential oil yield for cv. Oksanit was 46.4 kg/ha with a seed yield of 2.16 tons/ha. Cv. Nectar forms 45.6 kg/ha of essential oil with a seed yield of 2.01 tons/ha, and cv. Caribe forms 40.6 kg/ha with a seed yield of 2.06 tons/ha. Absence of statistically significant correlation between seed yield and essential oil output points to the peculiarities of the experiment. Research factors have opposing effects on the formation of essential oil, and consequently, its yield from the seed yield. The value of the results lies in the potential application of this approach in practice and the implementation of findings in the humid zone. The development of productivity models (like 3D plots) across a range of multiple factors simultaneously, based on crop structure indicators, allows for the prediction of target crop parameters, enabling the efficient utilization of available resources.

The connections between meteorological conditions and the health status of the population of Suceava municipality. A case study on respiratory afflictions throughout the years 2019-2020 in Suceava

Background: The present study addresses the real necessity of covering the gaps related to the actual understanding of the relationships established between weather patterns and the health status of the population. The urban area of Suceava is representative of medium-sized cities in Romania. Methods: Respiratory pathologies manifest with a temporal offset when compared to intervals with severe weather conditions. The consultation program is one that does not take into account the severity of weather conditions. Through statistical and graphical correlations, strong direct or inverse proportional relationships were identified between meteorological elements, the multitude of meteorological elements represented by bioclimatic indices, and the number of consultations provided to patients with respiratory afflictions. Results: In the winter season when t°C, THI, and TPr have minimum values and Pr has maximum values, the number of consultations for respiratory conditions is at an all-time high. The value of the coefficient of determination R2 between the monthly values of t°C and THI, respectively, the number of consultations for respiratory conditions exceeds the threshold of 0.7, and between the monthly values of Pr and the number of consultations for respiratory afflictions was 0.66. On days when t°C was ≤ 0°C, the average number of consultations for respiratory conditions was 6.1, decreasing to 3 on days when t°C was > 23°C. Conclusions: Respiratory diseases have the most favorable temporal framework for occurrence in the months of the cold season. In winter in Suceava, respiratory conditions affect twice as many people as in summer. Keywords: respiratory afflictions, meteorological elements, bioclimatic indices THI, Pr, and TPr

A Sensor-Based Application for Eco-Driving Management in Short-Term Car Rentals

How to reduce fuel consumption to mitigate CO2 emissions to the atmosphere and improve road safety is one of the priorities to be addressed in the field of transport in the European Union. Considering the trend towards more frequent car rentals, it seems important to encourage drivers to change their driving style to a more ecological and economic one. This can be achieved by a system (built of a sensor located in the car, analytical software in the cloud and a mobile application for displaying results) that analyzes driving style and tells the driver how to drive better. Solutions such as the car bus PCB, GSM/GPS modem and 3D sensors were used in the development of the sensor. The validation of the sensor and the development of the analytical system are based on tests carried out in road conditions and in a closed area. Graphical methods (box-plot charts), correlation analysis and testing statistical hypotheses using the Mann–Whitney method were used in the analysis of the test results. The developed sensor and the analytical system allow for identifying the driving style of drivers. This system, through the use of a sensor that allows for downloading data not only from the car’s CAN bus but also the forces acting on the vehicle, permits the checking of 14 driving parameters used to interpret the driver’s driving style.

Simulation Modeling Using Markovian Decision Theory on Cash Flow Analysis of Central Bank of Nigeria

This research aims to investigate the cash flow analysis of the Central Bank of Nigeria using Markovian decision theory. The specific objectives include determining the (i) cash flow solvency ratio, (ii) cash flow adequacy ratio, (iii) sufficiency ratio, (iv) cash flow profitability ratio, and (v) estimating the optimal policy of cash flow ratios performance in CBN. The identified problems are the effects of (i) insolvency, (ii) inadequacy, (iii) insufficiency, and (v) Unprofitability on Central Bank of Nigeria (CBN) cash flows performance.The methodology involves a research design tailored toward collecting, arranging, and determining cash flow data for model prediction and optimization. The Markov chain is introduced as an operator to evaluate the distribution of cash flow ratios in the long term, using initial state vectors and state transition probabilities for forecasting behavior. Data validation is performed using graphical and Pearson moment correlation coefficient methods. The pre-model analysis of CBN cash flows problem during the period of January 2012 to December 2017 identifies six finite current states. State-2012 cash flows performance was exceptional (above the zero line), reflecting 100%, while State-2013 and 2015 reflect 75%, and State-2014, 2016 & 2017 reflect 50% healthy cash flows status. The model results introduce the Markovian Cash Flow Ratios Monitoring Curve (MCFRMC), specifying the minimum values for healthy status. The research explores the present status of cash flow ratios, presenting forecasted ratios in the form of an optimum policy or solution. Pearson moment correlation coefficient validation of the prototype and model results in a coefficient of 1.0, indicating a 100% higher performance of the model. Further research reveals strategic cash inflows policy allocation to the cash flows indicators, with (i) operational activity receiving 24%, (ii) investment active e

Untangling the biotic stress in the late Maastrichtian Deccan-benchmark interval of Bidart (France)

The late Maastrichtian witnessed substantial surges in Deccan volcanism, prompting the hypothesis that these voluminous pulses may have instigated repeated episodes of ocean acidification during this period. The Cretaceous-Palaeogene (K/Pg) boundary at Bidart (France) is preceded by a ∼0.5 m thick interval with geochemical and taphonomic vestiges of an ocean acidification event linked with Deccan volcanism. New planktic foraminifera census and morphometric data now confirm biotic stress conditions related to acidification in the Deccan benchmark interval. The absolute abundance data of larger (>150 μm) heavily calcified planktic morphogroups show fluctuating populations throughout zone CF1 (spanning the final ∼225 ky), lowest peaks within the Deccan benchmark, and a demographic collapse (>90%) at the K/Pg boundary. The analyzed species are generally reduced in size, with thinner test walls in this ∼0.5 m interval, indicating the likelihood of calcification stress as a contributor to the overall biotic stress. At the K/Pg boundary, maximum biotic stress is recorded in all the tested faunal proxies. A preliminary graphic correlation of zone CF1 at Bidart with the auxiliary GSSP at Elles (Tunisia) constrains the Deccan benchmark interval of high biotic stress to the final ∼58 ky of the late Maastrichtian, culminating in the K/Pg mass extinction. The volcanogenic Hg peaks coincident with faunal and taphonomic evidence of ocean acidification strengthen the Deccan-related ocean acidification hypothesis.

Quantitative biostratigraphy of the Miocene-Pleistocene succession in Sapphire field, offshore Nile Delta, Egypt

A high-resolution quantitative nannoplankton biostratigraphy has been established in four wells based on a total of 1241 subsurface samples to understand and improve hydrocarbon exploration and recovery in the offshore Nile Delta. Ninety-two nannofossil species were used to delineate stages/ages boundaries of the Miocene-Pleistocene succession and to construct the age-depth model. Empirical, semi-quantitative (Graphic Correlation), and quantitative (Unitary Associations ‘UA’) methods retained comparable results, suggesting that the data quality is a master variable in the biostratigraphic resolution of the studied sequence. The UA method retained a sequence of 22 UAs, which exceeded the empirical zones (15; CNM6-CNPL9 = NN4-NN19). However, these UAs were merged into 14 zones (UAZ) to enable correlation among sections. Age-depth models and the nannofossil abundance were used to estimate the sedimentation rates and identify the system tracts within the depositional cycles. The variation in sedimentation rate was attributed to the interplay between the sea level and Nile flooding, which controlled the terrigenous influx. Furthermore, the nannofossil diversity was linked to the sequence stratigraphic framework, where seven 3rd order sequences were identified and correlated with the Global Tethyan sequences. Moreover, the extinction rate has increased after the Messinian and is attributed to the Pliocene-Pleistocene sea-level highstand and invasion of deeper water rich in nutrients from the upwelling zone.

An empirical analysis of inflation's influence on income inequality in Lithuania

Income inequality is a growing problem worldwide, especially in developed countries, with adverse social, economic, political and health consequences. In 2017, the goal of reducing poverty and inequality was included in the United Nations' seventeen Sustainable Development Goals list. Despite this, governments are not paying enough attention to tackling the problem, and inequality continues to rise. To take appropriate measures to reduce income inequality, it is essential first to understand the underlying causes, as this can help to tackle the problem at its root. Many different factors have been identified as impacting income inequality, one of which is inflation. Inflation is currently at an all-time high in the country, reaching as high as 19.7% in 2022. This makes it particularly difficult for low-income earners to make ends meet, as buying necessities is becoming harder and harder. Given that rising inflation, due to geopolitical factors, is also an issue in Lithuania and throughout Europe, it is essential to analyse the relationship between income inequality, as this can help us make the right decisions in tackling both problems. This study aims to identify the impact of inflation on income inequality in Lithuania. The research methods used to achieve the objective were graphical analysis, literature analysis, correlation analysis and regression analysis. The study shows a linear relationship between the Gini coefficient and inflation, as measured by the change in the GDP deflator, in Lithuania over 2008-2021, but that the impact of inflation on inequality is observed after one year. Similarly, a parabolic relationship is found when examining the impact of a change in inflation, as measured by the change in the GICP, on income inequality. However, changes in producer prices significantly impact income inequality only after three years. An analysis of the impact of changes in the prices of different commodities on income inequality reveals that, over the period analysed, the main contributors to inequality have been increases in the prices of oil, gas, food, and non-alcoholic beverages. Inflation directly impacts income inequality in Lithuania, so policymakers should consider it when formulating social policy.

ENVIRONMENTAL AUDIT IN ASSESSING THE IMPACT OF REAGENTS ON SUSTAINABLE DEVELOPMENT IN LATVIA

Sustainable development in the environmental sector is a priority direction in Latvia, as in all EU countries. However, the use of different approaches does not provide effective results to achieve the SDG. The purpose of the research is to develop a model for carrying out an ecological audit based on the principle of inter-industrial assessment on the use of reagents on the country’s roads. The authors suggest using an environmental audit for a comprehensive assessment of the influence of reagents on the environment. Subject of research: model of environmental audit in assessing the use of reagents. The object of the study is the Latvian approach to the use of reagents. The research methodology applied for this research study is qualitative and quantitative research methods. The monographic method and the method of deduction were used to analyze the corresponding theoretical concepts, the statistical method, the method of graphic analysis, correlation and regression analysis, Student’s distribution were used for the evidence base of the research. Conclusion of the study: in the research the authors identified the following pattern: with the growth of income of the population of Latvia, the number of cars in the country increases (correlation 0.999, R = 0.754), however, there is also an increase in road accidents (correlation 0.946, R = 0.728), which leads to an increase in car repairs. In auto repair work, an anti-corrosion coating is used that releases non-methane volatile compounds. When conducting an environmental audit, it is necessary to take into account anti-corrosion coatings. As part of the research, the identified pattern was based on the use of the principle of intersectoral assessment. According to the authors, conducting an environmental audit according to the model proposed by the authors will lead to the identification of sources of environmental pollution, and subsequently to the development of a program to reduce or eliminate it. Regression equation analysis will make it possible to predict the expected number of accidents and will allow non-methane volatile compounds to be taken into account in environmental audits.

Retrospective Study on the Incidence of Tuberculosis Cases in Pakistan

Tuberculosis (TB) is a serious infection or disease that directly affects the lungs. Pakistan stands 5th ranks amongst the high burden countries in the world. This study addresses the relationships between different tuberculosis cases in the province of Pakistan. The study is used to find which province reported high tuberculosis cases like (bacteriologically confirmed, clinically diagnosed, extra pulmonary and retreated tuberculosis). The main objective of this study is to know which tuberculosis case has significant effect among the provinces. For this purpose, we find the mean difference among the province of Pakistan with concern to tuberculosis cases in this study. The secondary data is used in this study. Further we find the correlation between tuberculosis cases and then used factor analysis. The dataset is taken by the website of the national TB data and Pakistan bureau of statistics. The dataset includes four different cases of tuberculosis (bacteriologically confirmed, clinically diagnosed, extra pulmonary and retreated tuberculosis) in provinces of Pakistan during the period of 2019. For achieving the objectives of the study, different techniques are used such as graphical representation, descriptive statistics, two-way ANOVA, LSD Test, correlation matrix, and factor analysis. The study shows highly significant results and concluded that the highest numbers of cases and deaths are reported in Punjab. Correlation matrix shows strong positive correlation between the four cases of tuberculosis. From factor analysis, there is only one factor is extracted that explains 82.872% of the total variation and all the cases have strong correlation with the factor.

Deconstructing the Gerber statistic

The Gerber Statistic is a recently proposed co-movement measure. The measure is a conditional statistic and due to conditioning bias, will naturally differ from full-sample measures. This contribution makes use of an intuitive two-asset simulation framework to better elucidate the statistical behaviour of the Gerber Statistic, across its three proposed forms. Using graphical correlation profiles, we explore the measure's behaviour across return conditioning threshold, sample size and market distribution, detailing its mechanisms of performance but also demonstrating several caveats around its understanding and use. We conclude that while interesting, the Gerber Statistic is best viewed as an imperfect conditional dependence metric.

An Optimization Method for CNC Laser Combination Cutting of Irregular Plate Remainders

The key research question in this study is how to cut pieces in irregular plate remainders, because there are many irregular plate leftovers created during the CNC (Computer Numerical Control) process. This will increase material utilization and allow plate leftovers to be reused. One of the issues being researched is how to arrange plate remainders on the surface of the CNC machine; this issue is known as combination layout optimization. The other issue being researched is combination cutting-path optimization of plate remainders, which aims to determine the cutting path of parts of plate remainders. A genetic algorithm based on the gravity-center NFP (No-Fit Polygon) method was applied to optimize the layout pattern, and then the geometric coordinates of a part included in one plate remainder after packing were obtained by geometric transformation with the help of a three-layer graphic data correlation model, which quickly identified the inside and outside contours of parts. A colony algorithm based on the mathematical model of cutting-path optimization was used to optimize the cutting path of the parts in the plate remainders. Finally, some simulation tests were performed to illustrate the feasibility and effectiveness of the proposed method. The results of the algorithm for packing irregular shapes for some instances show that our algorithm outperforms the other algorithms. On most instances, the average plate utilization ratio using our algorithm, after running 20 times, is improved by 1% to 9% in comparison to the best plate utilization ratio using the tree search algorithm. The best idle travel of an example achieved by the algorithm in this paper is 7632 mm after running the cutting-path optimization algorithm 20 times, while that of the traditional equivalent TSP (Traveling Salesman Problem) algorithm is 11,625 mm, which significantly demonstrates the efficiency of the algorithm.

On the Bivariate Generalized Gamma-Lindley Distribution

ABSTRACT In this research paper, we propose a new class of bivariate distributions called Bivariate Generalized Gamma-Lindley (BGGL) distribution with four parameters. This model is a mixture of independent Gamma random variables and bivariate generalized Lindley distribution. We investigate various properties of the new bivariate distribution such as graphical representation, joint moments and correlation. Furthermore, we derive a measure of entropy of this bivariate distribution. We also derive the distributions of the random variables X 1 + X 2, X 1/(X 1 + X 2), X 1/X 2 and X 1 X 2 as well as the corresponding moment properties when X 1 and X 2 follow the BGGL distribution. Additionally, we address two approximations of the product of the proposed model and assess their goodness of fit. Next, we elaborate the expectation maximization (E.M) algorithm in order to estimate the BGGL model parameters. Finally, we provide two concrete examples to demonstrate the applicability of the results.

Integrating graphic correlation and similarity matrix of the Early Paleogene rock units in South Sinai, Egypt

This article aims to provide a simple and applicable method of measuring the rock accumulation rate and recording the depositional events based on the application of graphic correlation and similarity matrix of the Paleogene planktonic foraminifera in two surface sections in South Sinai. Fifteen continuous biozones and subzones were recorded spanning from P0 to E3. The average RAR of the Beida Formation was somewhat equal to that recorded for the Dakhla Formation, however, the Selandian‐Ypresian Garra Formation was more than twice that recorded for the Esna Formation. On the other hand, the Thebes Formation represents a reverse setting which is relatively higher in the south than the north. Seven (T1‐T7) and twelve (T1‐T12) terraces were recorded at different stratigraphic positions. The terraces diverged in the Palaeocene and converged in the Eocene, whereas they lengthen in the Palaeocene and shortened in the Eocene. Breaks identified in the SM support many of the poorly constrained terraces on the GC, however, the SM technique efficiently recorded around 60% of the terraces recorded by GC. For confirming the terraces identified, field and faunal parameters confirm all the recorded events, however, a further correlation with their equivalent in and outside Egypt has been made which confirms another support of the technique applied. Therefore, the integration between these techniques in recognizing the depositional events and sedimentation breaks supports further depositional and palaeobathymetical studies and regional correlation as well.

Simulation of Rotor-Rotor Interaction and Noise of an Axial Counter-Rotating Fan

The Counter-Rotating Fan (CRF) offers higher aerodynamic performance, in terms of pressure head and aerodynamic efficiency, compared to the single rotor fan, thus making it an attractive solution for equipment cooling and ventilation of mines and tunnels. Nevertheless, further investigations are required to understand the flow interactions between the front rotor (FR) and the rear rotor (RR), as these interactions are sources of noise emission. This numerical study used the Unsteady Reynolds Average Navier-Stokes (URANS) flow simulations and the Fast Fourier transformation (FFT) to analyse the rotor-rotor interactions and consequences on the aero-acoustic performance. The static pressure fluctuations were recorded at several locations and analysed by FFT to reveal the mechanisms of flow interactions and the effects of axial inter-distance between the two rotors. The inter-distance seems to influence the aerodynamic loading of RR more than that of FR and the total-to-static isentropic efficiency tends to drop. Over one chord distance, the noise level decreases but at the expense of isentropic efficiency. The balanced performance does not seem to improve for an inter-distance greater than 1.5 chords, considered the optimum distance in this study. Finally, a graphical correlation which can be used to estimate the Sound Pressure Level (SPL) is developed for this category of CRF.

Data Integration for Investigating Drivers of Water Quality Variability in the Banja Reservoir Watershed

It is increasingly important to know the water quality of a reservoir, given the prospect of an environment poor in water reserves, which are based on intense and short-lived precipitation events. In this work, vegetation indices (NDVI, EVI) and bio-physical parameters of the vegetation (LAI, FC), meteorological variables, and hydrological data are considered as possible drivers of the spatial and temporal variability of water quality (WQ) of the Banja reservoir (Albania). Sentinel-2 and Landsat 8/9 images are analyzed to derive WQ parameters and vegetation properties, while the HYPE model provides hydrological variables. Timeseries of the considered variables are examined using graphical and statistical methods and correlations among the variables are computed for a five-year period (2016–2022). The added-value of integrating earth observation derived data is demonstrated in the analysis of specific time periods or precipitation events. Significant positive correlations are found between water turbidity and hydrological parameters such as river discharge or runoff (0.55 and 0.40, respectively), while negative correlations are found between water turbidity and vegetation descriptors (−0.48 to −0.56). The possibility of having easy-to-use tools (e.g., web portal) for the analysis of multi-source data in an interactive way, facilitates the planning of hydroelectric plants management operations.

Inferred networks, machine learning, and health data.

This paper presents a network science approach to investigate a health information dataset, the Sexual Acquisition and Transmission of HIV Cooperative Agreement Program (SATHCAP), to uncover hidden relationships that can be used to suggest targeted health interventions. From the data, four key target variables are chosen: HIV status, injecting drug use, homelessness, and insurance status. These target variables are converted to a graph format using four separate graph inference techniques: graphical lasso, Meinshausen Bühlmann (MB), k-Nearest Neighbors (kNN), and correlation thresholding (CT). The graphs are then clustered using four clustering methods: Louvain, Leiden, and NBR-Clust with VAT and integrity. Promising clusters are chosen using internal evaluation measures and are visualized and analyzed to identify marker attributes and key relationships. The kNN and CT inference methods are shown to give useful results when combined with NBR-Clust clustering. Examples of cluster analysis indicate that the methodology produces results that will be relevant to the public health community.

Removal of Phenol from Sour Water by Poly(vinyl Alcohol)/Polyamide‐Reverse Osmosis Membranes

AbstractA commercial thin‐film membrane (unmodified) of polyamide improved by poly(vinyl alcohol) (PVA)‐coated membranes (modified) was investigated for separating phenol in sour water by reverse osmosis. Dependences of pressure and pore surface area on flux and phenol rejection were tested. A graphical correlation was found between the relative flux decline and phenol concentration decrease in the feed. The modified membrane provided rejection of 86 % at 2 bar with the highest permeate flux of 8.46 L m−2h−1. The average contact angle for the former membrane was 58.4°, while that for the modified membrane was 49.1°. The reduction in contact angle enhances the surface hydrophilicity of the membrane leading to the antifouling effect. The modified membrane provides 95.4 % flux recovery compared to the unmodified membrane that provides only 66.2 %.