Lorentzian Curve Research Articles

WATER-RICH MELT INCLUSION AS "FROZEN" SAMPLES OF THE SUPERCRITICAL STATE IN GRANITES AND PEGMATITES REVEAL EXTREME ELEMENT ENRICHMENT RESULTING UNDER NON-EQUILIBRIUM CONDITIONS

In this contribution, we show that in miarolitic pegmatites during the crystallization of water-rich melts, samples of these mineral-forming melts were trapped in the form of water-rich melt inclusions, preserved primarily in quartz. The bulk concentration of water and the temperature are the system-determining parameters since from their analysis it follows that these melt inclusions depict pseudo-binary solvus curves in the coordinates of temperature and water concentration. Furthermore, using reduced coordinates (H2O/H2Ocrit vs. T/Tcrit) most melt inclusions of the studied pegmatites plot very well in a standardized and reduced solvus curve. The existence and formation of such uniform solvus curves is an expression of crystallization processes under nearly equilibrium conditions. However, many trace and some principal elements of the melt inclusions trapped near the solvus crest [H2O/H2Ocrit from 0.5 to 1.5 and T/Tcrit > 0.95] show unusual distributions, with very well-defined Gaussian and/or Lorentzian curves, characterized by defined area, width, offset, and height. This has been shown in many natural examples obtained from pegmatites. Only the offset values represent near-equilibrium conditions and corresponding element concentrations, which are equivalent to the regional Clarke number (Clarke number or Clark is the relative abundance of a chemical element, typically in the Earth's crust). We interpret these distributions as explanation for some extraordinary-chemical properties in this critical region: principally extremely high diffusion rates, low dynamic viscosity and extremely low surface tension. Near the critical point, we have both space and time-related non-equilibrium and equilibrium processes close together. Furthermore, we can show that the Gaussian and Lorentzian distribution are first approximations of the specific element distribution because at the critical point the enrichment of some elements reaches such an extent that the Gaussian and/or Lorentzian curves degenerate into a vertical line (are asymptotic to the concentration axis), which is determined by the maximum solubility of a species in the supercritical melt-water system. The highest concentration of Be, as an example, was observed in Ehrenfriedersdorf melt inclusions: 71490 ppm Be.

A Method for Identifying Channeling Paths in Low-Permeability Fractured Reservoirs

Often oilfield fractured horizontal wells produce water flowing in multiple directions. In this study, a method to identify such channeling paths is developed. The dual-medium model is based on the principle of inter-well connectivity and considers the flow characteristics and related channeling terms. The Lorentz curve is drawn to qualitatively discern the geological type of the low-permeability fractured reservoir and determine the channeling direction and size. The practical application of such an approach to a sample oilfield shows that it can accurately identify the channeling paths of the considered low-permeability fractured reservoir and predict production performances according to the inter-well connectivity model. As a result, early detection of water channeling becomes possible, paving the way to real-time production system optimization in low-permeability fractured reservoirs.

INCOME AND ECONOMIC INEQUALITY

The “Lorentz curve”, reflecting the inequality of income distribution is considered. The equation of this curve is derived and it is shown how to calculate the level of subsidies to the population based on it.

The influence of modulated magnetic field on light absorption in SERF atomic magnetometer.

A single-beam spin-exchange relaxation-free atomic magnetometer is ultra-sensitive in the zero field, which has great potential for the detection of a magnetoencephalogram. The addition of a modulated magnetic field is an important approach to achieve high sensitivity for devices of this kind. In this study, we discovered that the amplitude and frequency of the modulated magnetic field (modulation index0-3) both influence the light absorption. We defined this effect into a function by combining theoretical analysis and the results of experiments. It is discovered that the transmission intensity decreases with an increase in the modulation index. This effect is weakened under the application of a high modulation index. In addition, the transmission intensity and bias magnetic field no longer follow a strict Lorentz curve, while a high degree of fit can be achieved by applying the numerical solution of the Bloch function. A compact magnetometer with a volume of 10 cm3 and a sensitivity of 20 fT/Hz is developed based on the single beam scheme for the proof of concept. Our study is crucial in two aspects: (1) Obtaining high sensitivity through a short measurement period and (2) alignment of the scale factor of the individual magnetometer in a detection array, which further pave the way for improvement in a magnetometer's performance under a variety of optics platforms.

Cultivated Land Fragmentation and Its Influencing Factors Detection: A Case Study in Huaihe River Basin, China.

The booming population and accelerating urbanization in the Huaihe River Basin have sped up the land use transformation and the cultivated land fragmentation (CLF), seriously impeded the advancement of agricultural modernization, and threatened regional stability and national food security as well. The analysis of CLF degree and its spatiotemporal distribution characteristics, along with the influencing factors in the Huaihe River Basin, is of great significance for promoting the intensive and efficient utilization of cultivated land resources and maintaining food security. Previous studies lack the measurement and cause analysis of CLF in Huaihe River Basin. To bridge the gap, this study introduces Fragstats4.2 and ArcGIS10.3 to analyze the spatiotemporal characteristics of CLF in county units in the Huaihe River Basin from 2000 to 2018 through the Lorentz curve, entropy method, and spatial auto-correlation method while the causes of the spatiotemporal differentiation of CLF in the basin were explored with the help of a geographic detector. The results show that the spatial distribution of cultivated land in the Huaihe River Basin is relatively balanced, and the Gini coefficients of cultivated land from 2000 to 2018 were 0.105, 0.108, and 0.113, respectively. More than 56% of the counties in the basin have a location entropy greater than 1. the percentage of landscape, area-weighted mean patch area, patch cohesion index, and aggregation index decrease year by year while the patch density and splitting index show an upward trend. The landscape pattern of cultivated land is highly complex, and the overall fragmentation degree is increasing. The county distribution pattern of the CLF degree with random and agglomeration is generally stable. The spatiotemporal differentiation of CLF in the Huaihe River Basin is affected by multiple factors, among which the influences of the normalized difference vegetation index, per capita cultivated land area, and intensity of human activity obviously stronger than other factors, and the contribution rate of the factors reached more than 0.4. The interaction effect among the factors is stronger than that of single factor, with dual-factor enhancement and nonlinear enhancement dominating. The results of this study have important implications for optimizing the agricultural structure in the Huaihe River Basin and alleviating the CLF in important grain production areas.

Physical factors affecting the propagation length of Bloch surface modes in one-dimensional photonic crystals

In this work we present a detailed study of the propagation length of Bloch modes along the surface between a bulk medium and a one-dimensional truncated photonic crystal and how this quantity is affected by different parameters like the number of periods composing the photonic crystal, absorption of materials, the leak of energy due to the intrinsic structure of the system, and the roughness of involved surfaces that is inherently present depending on the manufacturing method and the materials themselves. To analyze the influence of different factors affecting the propagation length, we use essentially three different methods: the characteristic matrix for systems composed of smooth surfaces, along with the numerical fitting of a Lorentz curve around the resonance; the boundary integral method based on the Green function for two-dimensional systems that include random rough surfaces; and the numerical analysis of the energy propagation along the surface when a Gaussian beam impinges on it. We have found that the propagation length can vary from a few nanometers to some millimeters depending on the different mentioned factors, along with the relative position of the modes within the bandgaps. Bloch modes located at the center of bandgaps propagate longer distances than those residing near the edges. Absorption and roughness provoke a drastic decreasing of the propagation length as they increase at small rates. Finally, the number of periods composing the structure also produces an increase of the propagation length reaching a maximum and then dropping almost suddenly to zero when it grows at a constant pace.

Highly Discriminative Physiological Parameters for Thermal Pattern Classification.

Infrared Thermography (IRT) is a non-contact, non-intrusive, and non-ionizing radiation tool used for detecting breast lesions. This paper analyzes the surface temperature distribution (STD) on an optimal Region of Interest (RoI) for extraction of suitable internal heat source parameters. The physiological parameters are estimated through the inverse solution of the bio-heat equation and the STD of suspicious areas related to the hottest spots of the RoI. To reach these values, the STD is analyzed by means: the Depth-Intensity-Radius (D-I-R) measurement model and the fitting method of Lorentz curve. A highly discriminative pattern vector composed of the extracted physiological parameters is proposed to classify normal and abnormal breast thermograms. A well-defined RoI is delimited at a radial distance, determined by the Support Vector Machines (SVM). Nevertheless, this distance is less than or equal to cm due to the maximum temperature location close to the boundary image. The methodology is applied to 87 breast thermograms that belong to the Database for Mastology Research with Infrared Image (-). This methodology does not apply any image enhancements or normalization of input data. At an optimal position, the three-dimensional scattergrams show a correct separation between normal and abnormal thermograms. In other cases, the feature vectors are highly correlated. According to our experimental results, the proposed pattern vector extracted at optimal position cm reaches the highest sensitivity, specificity, and accuracy. Even more, the proposed technique utilizes a reduced number of physiological parameters to obtain a Correct Rate Classification (CRC) of 100%. The precision assessment confirms the performance superiority of the proposed method compared with other techniques for the breast thermogram classification of the -.

Fairness of the Distribution of Public Medical and Health Resources.

The fairness of health services is an important indicator of the World Health Organization's performance evaluation of health services, and the fairness of health resource allocation is the prerequisite for the fairness of health services. The research in this article aims to explore how to use health and medical resources fairly and effectively to allocate health resources in different fields, populations and projects, in order to achieve the maximization of social and economic benefits of health and medical resources. In the study of the distribution and equity of public health and medical resources, we comprehensively apply Gini coefficient, Theil index, Lorentz curve and difference index, based on the theory of health resource allocation and the theory of health equity, the province's health service resources have been researched and evaluated, combined with regional health planning theories and public health theories, a variety of scientific methods were used to analyze community health service resources at all levels across the country. At the same time, we reviewed the journal literature about the treatment of patients and children, and analyzed the patients admitted to medical institutions in various regions. The research in this paper found that from 2016 to 2020, the Gini coefficient of the province's health institutions according to population distribution has been fluctuating between 0.14 and 0.17. During this 5-year period, the Gini coefficient of the distribution of medical and health expenditures by population shows a downward trend year by year. From 2019, reach below 0.1, this shows that the fairness of the allocation of health resources according to population has a clear trend of improvement.

COMBINED NEURAL NETWORK METHOD FOR DETERMINING THE BRILLOUIN SPECTRUM MAXIMUM IN DISTRIBUTED FIBER-OPTIC SENSORS

Distributed fiber-optic sensors are becoming an increasingly common solution for monitoring and diagnosing extended information transmission lines, industrial devices, buildings and devices. One of the directions – Brillouin reflectometry, which allows diagnosing a fiber line for changes in ambient temperature or mechanical deformation, is becoming increasingly popular for engineers and researchers. However, modern standards impose increasingly strict requirements on diagnostic systems in terms of the accuracy of determined parameters. For Brillouin reflectometry, where the value of the environmental parameters is determined by the position of the maximum of the Brillouin gain spectrum, the task of more accurately determining this maximum becomes the main one. The paper considers modern computer-computational methods for detecting the maximum of the Brillouin gain spectrum in an optical fiber. The authors note that imperfections in the shape of the optical spectrum, such as the signal-to-noise ratio, as well as possible digital defects that occur during digitization, can significantly impair the accuracy of the system. The authors consider three approaches to detecting the maximum of the spectrum: the classical method of Lorentz curve fitting, the method of cross-correlation with the ideal Lorentzian function, as well as the method of inverse correlation developed by the authors earlier. To combine the results of the work of the three methods, a neural network model was developed that accepts the input data of each method, together with the parameters of noise and distortion of the spectrum. The model is presented in the form of a four-layer perceptron with two hidden layers. As a result, the authors achieved an increase in the accuracy of determining the position of the maximum of the spectrum by 10% on the model data.

Effects of deposition time on growth of Ir buffer layer on MgO(1 0 0) support layer by magnetron sputtering

The effects of deposition time of Ir buffer layer on MgO(100) support layer were investigated during the fabrication of the Ir/MgO compliant substrates with the use of the magnetron sputtering technique. It was observed that the XRD FWHM of Ir(200) decreases rapidly at first and then slowly with increasing deposition time, and the XRD FWHM data versus the deposition time can be fitted into the Logistic curve. For the surface roughness Ra of the Ir buffer layer, it increases firstly and then declines with increasing deposition time; the experimental data of Ra versus the deposition time can be fitted to the Lorentz curve. And the fitting functions corresponding to the two curves can be used for the determination of the deposition time of desired Ir buffer layer quality easily and conveniently, which provides a solid foundation for subsequent heteroepitaxy of high-quality diamond films on the Ir/MgO compliant substrate.

Indices for exploring information in Lorentz curve of daily precipitation and their application in natural disaster risk assessment

The concentration index (CI) based on the Lorenz curve has been widely used to analyse the temporal structure of daily precipitation. However, two different Lorenz curves may have the same CI, while indicating different distribution information of precipitation. Previous studies have proposed Lorentz asymmetry coefficient, the value of which concentrated around 0.9 without significant distinction. Additional indicators are thus in need to investigate the complete information in Lorenz curves besides CI. In this study, six geometrical indices are defined to characterize a Lorenz curve. Together with the CI, any one of the proposed indices can help determine a unique Lorenz curve. An analysis of the daily precipitation over the Qinghai–Tibet Plateau derived five groups of meteorological stations with identical CIs, but completely different Lorenz curves. The correlation analysis between the CI and proposed indices indicated that there are two parameters independent of the CI, representing the contribution of heavy rain and the position of the transaction point, respectively, thus introducing relatively new information on precipitation beyond the CI. Within the stations with high CIs, these two indices were used to further identify areas in the Qinghai–Tibet Plateau at a high risk for natural disasters, such as rainstorms, debris flows, and aridity, the derived results were consistent with the debris flow prone areas in China designated by China Meteorological Administration. The proposed indices can not only help CI to describe the Lorentz curve of daily rainfall, but can also help identify areas at a high risk for natural disasters.

Coupling between energy efficiency and industrial structure: An urban agglomeration case

Understanding the interactions between energy efficiency and industrial structure is conducive to sustainable urban development. The coupling mechanism in between remains to be unraveled in depth for forming a positive cycle. With the Yangtze River Delta (YRD) urban agglomeration as the empirical target, first the total-factor energy efficiency (TFEE) of the 26 cities of the YRD urban agglomeration during 2010–2017 is estimated by slacks-based measure model. The redefined Theil index, industrial advancement index and Lorentz curve statistics are then adopted to quantify industrial reasonability, industrial advancement and industrial concentration of cities. Finally, a coupling coordination degree model is employed to measure the comprehensive coupling level between energy efficiency and industrial structure. The results indicate that the TFEE of cities has great differences. Observed overall, the industrial reasonability and industrial advancement of cities reach a high level, while the industrial concentration is at a middle-lower level. In 2017, the comprehensive coupling of all cities is at high coordination running-in level and above. The results are expected to offer decision-making support on energy efficiency improvement and industrial restructuring for the YRD region, as well as other urban agglomerations in similar conditions.

Green Stereoregular Polymerization of Poly(methyl methacrylate)s Through Vesicular Catalysis

Green Stereoregular Polymerization of Poly(methyl methacrylate)s Through Vesicular Catalysis

Time-Efficient Convolutional Neural Network-Assisted Brillouin Optical Frequency Domain Analysis.

To our knowledge, this is the first report on a machine-learning-assisted Brillouin optical frequency domain analysis (BOFDA) for time-efficient temperature measurements. We propose a convolutional neural network (CNN)-based signal post-processing method that, compared to the conventional Lorentzian curve fitting approach, facilitates temperature extraction. Due to its robustness against noise, it can enhance the performance of the system. The CNN-assisted BOFDA is expected to shorten the measurement time by more than nine times and open the way for applications, where faster monitoring is essential.

X-ray Photoelectron Spectroscopy Analysis of Chitosan-Graphene Oxide-Based Composite Thin Films for Potential Optical Sensing Applications.

In this study, X-ray photoelectron spectroscopy (XPS) was used to study chitosan–graphene oxide (chitosan–GO) incorporated with 4-(2-pyridylazo)resorcinol (PAR) and cadmium sulfide quantum dot (CdS QD) composite thin films for the potential optical sensing of cobalt ions (Co2+). From the XPS results, it was confirmed that carbon, oxygen, and nitrogen elements existed on the PAR–chitosan–GO thin film, while for CdS QD–chitosan–GO, the existence of carbon, oxygen, cadmium, nitrogen, and sulfur were confirmed. Further deconvolution of each element using the Gaussian–Lorentzian curve fitting program revealed the sub-peak component of each element and hence the corresponding functional group was identified. Next, investigation using surface plasmon resonance (SPR) optical sensor proved that both chitosan–GO-based thin films were able to detect Co2+ as low as 0.01 ppm for both composite thin films, while the PAR had the higher binding affinity. The interaction of the Co2+ with the thin films was characterized again using XPS to confirm the functional group involved during the reaction. The XPS results proved that primary amino in the PAR–chitosan–GO thin film contributed more important role for the reaction with Co2+, as in agreement with the SPR results.

INEQUALITY IN THE HOUSEHOLD INCOME DISTRIBUTION IN UKRAINE

Currently Ukrainian economy is characterized by an unstable situation caused by the political and economic situation in the country, as well as a by the pandemic, which led to irregularity in the population income distribution, which further affected consumption and its volume. The article examines irregularity in the distribution of household’s incomes. The research analysis reveals that there have been positive changes in the structure of cumulative income of urban and rural households in Ukraine recently. To put it more precisely, there is an increase in the share of wages, transfer payments in the form of benefits and subsidies and income from business activities along with the specific natural incomes and pensions decrease. However, factual statistical information contradicts the realities of our lives. Their structure in 2020 was analyzed and the share of wages in the household incomes formation is calculated. Indicators of socio–economic irregularity (Lorentz curve, Gini coefficient, decile coefficient) were studied. Compared to the developed world countries, the general level of Ukrainians’ income remains low. The main part of Ukrainian citizens’ income is spent on consumption since they have no opportunity to save. Recently, there has been a decrease in the book income from hired labor, and, therefore, most households conceal their income, which affects living standards and reduces revenues to the state budget. The dynamics of income and expenditure of urban and rural households in 2020 was also analyzed. It was found out that the vast majority of urban and rural households in the country spend their income on consumption and they have no ability to save. The main ways to reduce income inequality are indicated, namely: ending the war in the east of the country; increasing the tax burden for big business and the wealthiest sections of the population; deprivation of the oligarchs’ influence on the government, increase in wages; reducing unemployment; employment growth; reducing the level of corruption; development of small and medium business, creating equal opportunities for all sections of the population in education and health care.

ASSESSMENT OF INEQUALITY OF THE POPULATION OF UKRAINE BY SOURCES OF INCOME

Purpose. The aim of the article is the analysis of inequality of the population of Ukraine by sources of income. Methodology of research. A set of general scientific and specific methods of economic research was used in the course of the research, in particular, methods of theoretical generalizations: analysis, abstract and logical method (at substantiation of modern tendencies of inequality of the population of Ukraine on incomes); economic and statistical methods (in assessing the dynamics of inequality of the population of Ukraine in terms of monetary income); methods of mathematical statistics (when calculating the Gini index and the decomposition of income); methods of graphic display of the received results of research. Findings. The Gini index was calculated using the spline interpolation method to construct the Lorentz function. The Gini index is compared with known calculation methods, the description of the extended method of decomposition of the Gini index is carried out, and also this method is applied on statistical data of distribution of households of Ukraine on the level of monetary incomes. The influence of changes in sources of income on the general level of differentiation is analysed. According to the results of the study, the main factors influencing the level of income distribution and the possibility of reducing the level of stratification of the population of Ukraine were identified. Originality. It is proposed to use the spline interpolation method to construct the Lorentz function, which involves the calculation of the Gini index. The method of the Gini index decomposition identifies the sources of income that have the greatest impact on the growth of income inequality in Ukraine in the period 2014-2020. Practical value. The obtained results of the research are useful in the study of determining the reasons for the influence of certain factors on the level of income distribution and the possibility of reducing the level of stratification of the population of Ukraine. Key words: population inequality, Lorentz curve, Gini index, Gini index decomposition, spline interpolation.

Analysis of income distribution as prevention of environmental damage in agribusiness management of cassava in Bengawan Solo watershed, Wonogiri regency

This research was conducted with the aim of 1) knowing the income distribution or income gap among cassava farmers, 2) looking for solutions to increase cultural values in preventing environmental damage related to the management of cassava agribusiness in the Bengawan Solo Wonogiri watershed, which indicates environmental damage in land degradation and erosion which leads to silting of the Wonogiri Reservoir. This research used a survey approach with cross-sectional data, with a questionnaire research instrument. Data were analyzed with income analysis and income distribution analysis by looking for the Gini Index value and depicted by the Lorentz curve. The results showed that the level of income gap was quite high with the Gini Index number reaching 0.40 in the management of cassava agribusiness. It is recommended to strengthen cultural values through increasing the capacity of farmers’ human resources in social empathy.

An Empirical Study Based on the Impact of Smart Sensor System on Rural Relative Poverty

Solving the problem of rural poverty is a difficult problem for the country to enter a well‐off society in an all‐round way. Therefore, this paper conducts an experimental analysis based on the impact of smart sensor systems on the relative poverty in rural areas. This article is aimed at studying the related factors of rural poverty and improving relative poverty in rural areas. In this regard, this article proposes an intelligent processing function based on smart sensors. Multiple sensors work together to process relatively complex things. Then, through the experimental analysis of GH efficiency, the data collected in the experimental area is used as the data. Combining the Lorentz curve and Gini coefficient analysis to determine the influencing factors of rural relative poverty. This article also selected 10 areas for experimentation. The experimental results show that the proportion of middle school education from 2014 to 2020 is between 24.3% and 34%, and the number of poor people has also declined, indicating that education level is a factor affecting rural poverty. Therefore, based on the intelligent sensor system, the factors of relative poverty in rural areas can be found, and related measures can be analyzed. By implementing the rural poverty alleviation strategy, the relative poverty situation in rural areas can be effectively improved.

Structuring advertising campaign costs considering the asymmetry of users’ interests

This work is devoted to the highly topical problem of structuring costs for contextual and targeted advertising on the Internet. The choice of the ad campaign financing structure is considered from the point of view of violating the principle of symmetry of user interest in ads. The purpose of this work is to develop a methodology for structuring advertising campaign costs based on cluster analysis, taking into account the asymmetry of user interest in advertising. The key feature of the research is the description of the possibility of using the asymmetry of user interest in application solutions, such as online advertising. The Gini coefficient is used as an indicator of the degree of imbalance in the manifestation of a feature in clustering, and the features of using the lift coefficient and the Lorentz curve to evaluate the effectiveness of contextual and targeted advertising for various groups of customers are also considered. Using the Gini index and cluster analysis, you can analyze the possibilities of increasing ad revenue and compare it with the absence of any policy for structuring advertising costs. Identifying such patterns in consumer groups allows you to identify the main directions of product development and customer interest in it. The method described here should be used to improve the effectiveness of banner advertising and clustering algorithms. This approach does not improve banner clickability, but allows you to implement an individual approach to advertising products with the current number of clicks and more effectively structure the cost of various types of advertising.