Journal articles on the topic 'Restrictive correlation Model'
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Guo, Jianqiao, Yang Sun, Yunxia Hao, Ligang Cui, and Gexue Ren. "A mass-flowing muscle model with shape restrictive soft tissues: correlation with sonoelastography." Biomechanics and Modeling in Mechanobiology 19, no. 3 (December 18, 2019): 911–26. http://dx.doi.org/10.1007/s10237-019-01260-z.
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McAleer, Michael, Felix Chan, Suhejla Hoti, and Offer Lieberman. "GENERALIZED AUTOREGRESSIVE CONDITIONAL CORRELATION." Econometric Theory 24, no. 6 (July 9, 2008): 1554–83. http://dx.doi.org/10.1017/s0266466608080614.
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This paper develops a generalized autoregressive conditional correlation (GARCC) model when the standardized residuals follow a random coefficient vector autoregressive process. As a multivariate generalization of the Tsay (1987, Journal of the American Statistical Association 82, 590–604) random coefficient autoregressive (RCA) model, the GARCC model provides a motivation for the conditional correlations to be time varying. GARCC is also more general than the Engle (2002, Journal of Business & Economic Statistics 20, 339–350) dynamic conditional correlation (DCC) and the Tse and Tsui (2002, Journal of Business & Economic Statistics 20, 351–362) varying conditional correlation (VCC) models and does not impose unduly restrictive conditions on the parameters of the DCC model. The structural properties of the GARCC model, specifically, the analytical forms of the regularity conditions, are derived, and the asymptotic theory is established. The Baba, Engle, Kraft, and Kroner (BEKK) model of Engle and Kroner (1995, Econometric Theory 11, 122–150) is demonstrated to be a special case of a multivariate RCA process. A likelihood ratio test is proposed for several special cases of GARCC. The empirical usefulness of GARCC and the practicality of the likelihood ratio test are demonstrated for the daily returns of the Standard and Poor's 500, Nikkei, and Hang Seng indexes.
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Yue, Yu, Bo Zhang, and Zheng Liang Xue. "Study on Desulfurization Kinetics Model of LF Refining." Advanced Materials Research 690-693 (May 2013): 246–51. http://dx.doi.org/10.4028/www.scientific.net/amr.690-693.246.
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The desulphurization kinetics in ladle refining was analyzed, and the restrictive link for the desulfurization was selected based on previous research. Then the kinetics of desulfurization model in LF refining was developed and the empirical formula of sulfur ratio was summarized. The result by calculated shows that there is a good linear correlation between desulfurization rate and time, and the mass transfer coefficient D=3.79x10-5m/min.
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Cimiotti, Diana, Heidi Budde, Roua Hassoun, and Kornelia Jaquet. "Genetic Restrictive Cardiomyopathy: Causes and Consequences—An Integrative Approach." International Journal of Molecular Sciences 22, no. 2 (January 8, 2021): 558. http://dx.doi.org/10.3390/ijms22020558.
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The sarcomere as the smallest contractile unit is prone to alterations in its functional, structural and associated proteins. Sarcomeric dysfunction leads to heart failure or cardiomyopathies like hypertrophic (HCM) or restrictive cardiomyopathy (RCM) etc. Genetic based RCM, a very rare but severe disease with a high mortality rate, might be induced by mutations in genes of non-sarcomeric, sarcomeric and sarcomere associated proteins. In this review, we discuss the functional effects in correlation to the phenotype and present an integrated model for the development of genetic RCM.
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Cimiotti, Diana, Heidi Budde, Roua Hassoun, and Kornelia Jaquet. "Genetic Restrictive Cardiomyopathy: Causes and Consequences—An Integrative Approach." International Journal of Molecular Sciences 22, no. 2 (January 8, 2021): 558. http://dx.doi.org/10.3390/ijms22020558.
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The sarcomere as the smallest contractile unit is prone to alterations in its functional, structural and associated proteins. Sarcomeric dysfunction leads to heart failure or cardiomyopathies like hypertrophic (HCM) or restrictive cardiomyopathy (RCM) etc. Genetic based RCM, a very rare but severe disease with a high mortality rate, might be induced by mutations in genes of non-sarcomeric, sarcomeric and sarcomere associated proteins. In this review, we discuss the functional effects in correlation to the phenotype and present an integrated model for the development of genetic RCM.
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Tsidik, L. I. "CLINICAL VALIDATION OF THE SCALES OF EXPANSIVENESS, RESTRICTIVE CONTROL, CORRECTION AND PHOBIC FEARS OF THE MODIFIED VARIANT OF THE NEUROTIC DISORDERS QUESTIONNAIRE." Journal of the Grodno State Medical University 18, no. 6 (December 31, 2020): 681–86. http://dx.doi.org/10.25298/2221-8785-2020-18-6-681-686.
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Background. On the basis of the statements of the questionnaire of neurotic disorders within the framework of the Rush model, which is a kind of modern test theory, 13 scales with proven psychometric properties were formed. This article evaluates the clinical effectiveness of four of them. Purpose of the study. To carry out clinical validation of scales of expansiveness, restrictive control, correction and phobic fears of the modified version of the neurotic disorders questionnaire. Material and methods. A total of 296 people were examined, among them 167 women and 129 men. Statistical methods of research included factor analysis of standardized residuals, ROC-analysis, and correlation analysis. Results. The scales under study have a homogeneous structure. With the help of ROC-analysis, moderate differentiating properties of the scales were revealed, and cutoff values were calculated, which were the criteria for interpretation. Correlation analysis of the total indicator revealed statistically significant correlations between the studied scales and the MMPI scores, the QIDS-SR16 questionnaire and the Hamilton Anxiety Rating Scale (HADS). Conclusions. The scales of expansiveness, restrictive control, correction and phobic fears of the modified version of the neurotic disorders questionnaire are clinically valid and can be used to solve various practical problems.
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Cao, Shulei, Maria Dainotti, and Bharat Ratra. "Standardizing Platinum Dainotti-correlated gamma-ray bursts, and using them with standardized Amati-correlated gamma-ray bursts to constrain cosmological model parameters." Monthly Notices of the Royal Astronomical Society 512, no. 1 (February 24, 2022): 439–54. http://dx.doi.org/10.1093/mnras/stac517.
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ABSTRACT We show that the Platinum gamma-ray burst (GRB) data compilation, probing the redshift range 0.553 ≤ z ≤ 5.0, obeys a cosmological-model-independent three-parameter Fundamental Plane (Dainotti) correlation and so is standardizable. While they probe the largely unexplored z ∼ 2.3–5 part of cosmological redshift space, the GRB cosmological parameter constraints are consistent with, but less precise than, those from a combination of baryon acoustic oscillation (BAO) and Hubble parameter [H(z)] data. In order to increase the precision of GRB-only cosmological constraints, we exclude common GRBs from the larger Amati-correlated A118 data set composed of 118 GRBs and jointly analyse the remaining 101 Amati-correlated GRBs with the 50 Platinum GRBs. This joint 151 GRB data set probes the largely unexplored z ∼ 2.3–8.2 region; the resulting GRB-only cosmological constraints are more restrictive, and consistent with, but less precise than, those from H(z) + BAO data.
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Lebedev, Valery V., and Konstantin V. Lebedev. "On Assessing the Impact of Coronavirus Epidemic in Russia on Population Incomes." Economics of Contemporary Russia, no. 1 (March 29, 2021): 116–33. http://dx.doi.org/10.33293/1609-1442-2021-1(92)-116-133.
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The paper discusses an approach to assessing the impact of the coronavirus epidemic in Russia on economic efficiency and, as a result, on the monetary income of the country's population. The approach used is based on the application of the methodology of mathematical modeling. Based on the analysis of statistical information, it is shown that there is a correlation between the dynamics of the average per capita income of the population and GDP. To assess the dynamics of GDP, a dynamic model of the impact of restrictive measures aimed at curbing the spread of the coronavirus epidemic on macroeconomic efficiency is constructed. The main hypothesis of the model is that the main factor affecting the efficiency of the economy is the productivity of workers who create GDP. In the constructed model, all employees are divided into three groups. The first group – workers whose activities were not affected by the coronavirus; the second group-workers whose productivity decreased due to the coronavirus; the third group-workers whose productivity fully or partially recovered after the easing of restrictive measures. As a result, the dynamics of GDP is determined by a system of three ordinary differential equations with parameters depended on the epidemiological situation. To assess the indicators that characterize the spread of infection and affect the parameters of the macroeconomic efficiency model, a discrete modification of the classical SIR-model of the epidemic with piecewise constant parameters is constructed. This model allowed us to estimate the dynamics of the average for the four day values of the basic reproductive numbers and other indicators of spread of infection through the use of official statistical information in the base period, and to perform scenario calculations for the development of the epidemic in Moscow and beyond until July 2021 Developed modification of the SIR model allows for its clarification with regard to the influence of vaccination on the dynamics of epidemiological process.
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Knezevic, Aleksandar, and Vera Gligorijevic. "The ethno-demographic context of declining birth rates and birth control in Eastern Serbia - an example of an atypical demographic transition." Bulletin de l'Institut etnographique 71, no. 1 (2023): 267–98. http://dx.doi.org/10.2298/gei2301267k.
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The restrictive reproductive model in Eastern Serbia, which appeared in pre- industrial rural society and without of sufficient development potential that would lead to the redefinition of ethical and general social norms, was in many ways similar to industrialized and urbanized societies. The expansive spread of the restricted model of reproduction was atypical in relation to the verme, place and conditions in which it appeared, and beyond all the theoretical postulates of the demographic transition. The paper analyzes the dynamics of change in both components of the natural population movement at the end of the 19th and the beginning of the 20th century and considers the ethnodemographic, ecocultural and socioeconomic context of birth and mortality, which interrelationship indicates the stages of the demographic transition. In addition to objective problems related to the quality of statistical data, the regional demographic differentiation of changes in birth mortality rates indicates a certain correlation between the intensity of the decline in birth and the ethnic structure of the population.
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Bozo, N. V., and O. T. Shipkova. "Interregional Differentiation and Heterogeneity of the Consequences of Pandemic Restrictions in Russia." Voprosy statistiki 30, no. 2 (April 16, 2023): 43–52. http://dx.doi.org/10.34023/2313-6383-2023-30-2-43-52.
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The purpose of the study is to analyze the features of the economic development of Russian regions under the influence of various socio-economic factors and the differentiation of region groups depending on the implementation of state regulation of economic activity measures in them during the pandemic period. The analysis was carried out using statistical methods (primarily methods of statistical groupings and correlation-regression analysis). The conceptual and methodological principles for assessing changes in economic activity in Russian regions after the introduction of restrictive measures of different levels of severity are outlined based on the study of Russian and foreign scientific publications on the issues under consideration. A regression model uses to identify the influence of the studied factors. To identify the impact of the studied factors, the authors built a regression model that included the following statistical indicators: index of industrial production, unemployment rate, share of the urban population, share of the region's gross value added (GVA), number of small and medium-sized enterprises (excluding micro-enterprises) per 10,000 population, share of the region in the production of all Russian mining enterprises, region openness coefficient, average per capita monetary income of the population, poverty level. The final part of the article presents the results of the study indicating that pandemic restrictions, depending on the degree of their severity, had a different impact on the economy of the regions. The authors emphasize the heterogeneity of changes in the factors determining the economic activity of regions under the influence of restrictive measures on the part of governments, particularly regional authorities.
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de Azevedo Barbosa, Petterson, Maurício Guimarães Bergerman, Elisabeth da Fonseca, and Rogerio Kwitko-Ribeiro. "Determination of Abrasiveness in Copper-Gold Sulfide Ores: A Contribution to the Geometallurgical Model of the Sossego Deposit." Minerals 11, no. 12 (December 16, 2021): 1427. http://dx.doi.org/10.3390/min11121427.
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The geological context of this study is established in the iron oxide-copper-gold (IOCG) deposit of Sossego (Canaã dos Carajás, Brazil), where hydrothermal alterations in shear zones concentrated the metals of interest and added new characteristics to the metavolcanic-sedimentary and granite rocks. The mineral transformation of rocks by hypersaline fluids enriched in metals and silica also modifies some metallurgical properties, such as abrasiveness. Special bench tests on rock drill cores are used in mapping the abrasiveness of rocks, with the Bond abrasion test being more commonly used in the mining industry, but it has a restrictive sampling protocol and mass requirement for geometallurgical studies. As a counterpoint, the test of the Laboratoire Central des Ponts et Chaussées/Central Laboratory of Bridges and Roads (LCPC) requires a smaller amount of fine material and a finer granulometric range. The study on the use of LCPC was implemented in 40 samples, using Bond Ai as a reference. The results showed a strong correlation between both methodologies (R2 = 95%), validating the use of LCPC to quantify abrasiveness in the Sossego mine. It was also possible to classify the most abrasive lithologies.
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Kavitha, U., E. Kayalvizhi, K. Revathy, T. R. Brindha, R. Muthulakshmi, and M. Chandrasekar. "A systematic review on Valproate induced rat model of autism: Pathophysiology, treatment, developmental and neurobehavioral assessment of rat offsprings." Biomedicine 41, no. 1 (April 2, 2021): 9–15. http://dx.doi.org/10.51248/.v41i1.526.
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Autism Spectrum disorder (ASD) is charecterised by certain degrees of disabilities in social communication, restrictive repetitive behaviour and altered motor and sensory perception. Translational research is carried out by creating animal models of autism to find out the correlation between behavioural changes and the pathology of brain tissue and for clinical trials of newer therapeutic formulations. Valproate induced animal model of autism has significant validity to demonstrate ASD manifestations. An early appreciation of ASD symptoms is needed for a better prognosis. So assessment of behavioural abnormalities and development stones in the first month of animal life are much important to study ASD.An extensive literature search was done on different databases. (PUBMED-MeSH, PMC, Webof Science, Google scholar and Research Gate). Original articles reported between the years 2000-2020 were selected. PRISMA protocol was followed. There are good quantities of studies on behavioural assessment of valproate induced animal model. This review explains the pathophysiology and various treatment modalities tried in valporate induced animal model and it also enlists the developmental and behavioural assessment methods of rat off springs. It will be useful to demonstrate all signs of autism.
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Latu, M. N., A. А. Levit, and M. B. Gavrilova. "Static Polycode Text Modeling Using Network Analysis (Demotivator Dedicated to Problems of Self-Isolation)." Nauchnyi dialog 11, no. 3 (April 28, 2022): 62–77. http://dx.doi.org/10.24224/2227-1295-2022-11-3-62-77.
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The features of modeling a graphic-verbal polycode text, including a static image and an accompanying inscription, are considered. The study was conducted on the example of a demotivator dedicated to the problems of mass self-isolation at the very beginning of the pandemic and the introduction of restrictive measures. Significant semantic components, represented as part of only the iconic component, only the verbal component, and also as part of the verbal and iconic components at the same time are established. The semantic relations between the selected semantic components are revealed, the types of these links, revealing the different nature of their correlation are determined. On the basis of the data obtained, a network model of the considered static polycode text in the form of a semantic network was built. Cases of semantic components correlation are considered, reflecting the generally objective aspects of the situation and unrealistic ideas based on irony and hyperbole to create a comic effect. Based on quantitative analysis, representative semantic relations were established: “partitive”, “localization (in)”, “attributive”, “subject-object”. Non-representative semantic relations between the semantic components in the analyzed polycode text are revealed: “coincidence”, “localization (on)”, “temporal”, “subject-instrument”, “subject-result”.
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Choi, Youn Hee, and Ying Sun. "Modeling and Simulation of Baroreflex Regulation of Heart Rate in Response to Respiratory Fluctuations in Arterial Pressure." Key Engineering Materials 277-279 (January 2005): 28–32. http://dx.doi.org/10.4028/www.scientific.net/kem.277-279.28.
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Autonomic derangement can be assessed by depressed baroreflex sensitivity in a restrictive left ventricular diastolic filling pattern. However, it is unclear how reflex or other compensations affect the inspiratory fall of systolic arterial pressure (IFSAP) during acute airway obstruction. In an in-vivo situation, it is particularly difficult to isolate individual effects of heart rate, vascular tone, pleural pressure variation, and ventricular interdependence. For this reason, a computer model study was undertaken. A previously validated computer model of the cardiopulmonary system was adapted for this study, relating mechanisms such as baroreflex regulation of heart rate to IFSAP. The model provided time-course simulations of hemodynamics by numerically integrating 28 nonlinear, time-varying differential equations. Two models for baroreflex gain were tested, including a simple 1st-order relationship between systolic arterial pressure (SAP) and R-R interval (RRI) and the autoregressive moving average (ARMA) model reported in literature. The ARMA model predicted the next RRI based on SAP from several previous cardiac cycles and previous RRI predictions. Experimental data were obtained retrospectively from 22 patients with chronic airway obstruction before and during breathing through an external resistance. The computer model provided good fits to arterial pressure waveforms: correlation coefficients (r) ranging from 0.71 to 0.96 (mean±SD: 0.87±0.06) with a simple 1st-order SAP-RRI model. The ARMA model did not improve the goodness of fit.
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Silva, Wanderson Roberto da, Patrícia Angélica Teixeira, João Marôco, Eric Batista Ferreira, Micaela Aparecida Teodoro, and Juliana Alvares Duarte Bonini Campos. "Relationship between Attention to Body Shape, Social Physique Anxiety, and Personal Characteristics of Brazilians: A Structural Equation Model." International Journal of Environmental Research and Public Health 19, no. 22 (November 10, 2022): 14802. http://dx.doi.org/10.3390/ijerph192214802.
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People can develop eating disorders due to excessive body image concerns. The primary objective of this study was to examine the relationship between attention to body shape, social physique anxiety, and personal characteristics in a sample of Brazilians. The secondary objective was to evaluate the correlation of the constructs with the participants’ body composition. First, 1795 individuals (70% female; Mage = 25.5 ± 6.6 years) completed the Attention to Body Shape Scale, the Social Physique Anxiety Scale, and a sociodemographic questionnaire. Then, 286 participants (58% female; Mage = 25.3 ± 5.7 years) underwent a bioimpedance exam to identify body composition. Structural equation modeling was used to estimate the relationship between the variables. The greater the attention to body shape, the greater the expectations of negative physical evaluation and the less comfort with physical presentation. Younger age, female gender, consumption of supplements/substances for body change, restrictive diets, physical inactivity, poor self-assessment of food quality, and overweight/obesity were related to negative body concerns. An expectation of negative physical evaluation was positively correlated with body fat and negatively with muscle mass. Comfort with physical presentation was negatively correlated with fat and positively with muscle. These results can support preventive strategies aimed at reducing eating disorders resulting from body image concerns.
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Rio, Daniel E., Robert R. Rawlings, Lawrence A. Woltz, Jodi Gilman, and Daniel W. Hommer. "Development of the Complex General Linear Model in the Fourier Domain: Application to fMRI Multiple Input-Output Evoked Responses for Single Subjects." Computational and Mathematical Methods in Medicine 2013 (2013): 1–16. http://dx.doi.org/10.1155/2013/645043.
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A linear time-invariant model based on statistical time series analysis in the Fourier domain for single subjects is further developed and applied to functional MRI (fMRI) blood-oxygen level-dependent (BOLD) multivariate data. This methodology was originally developed to analyze multiple stimulus input evoked response BOLD data. However, to analyze clinical data generated using a repeated measures experimental design, the model has been extended to handle multivariate time series data and demonstrated on control and alcoholic subjects taken from data previously analyzed in the temporal domain. Analysis of BOLD data is typically carried out in the time domain where the data has a high temporal correlation. These analyses generally employ parametric models of the hemodynamic response function (HRF) where prewhitening of the data is attempted using autoregressive (AR) models for the noise. However, this data can be analyzed in the Fourier domain. Here, assumptions made on the noise structure are less restrictive, and hypothesis tests can be constructed based on voxel-specific nonparametric estimates of the hemodynamic transfer function (HRF in the Fourier domain). This is especially important for experimental designs involving multiple states (either stimulus or drug induced) that may alter the form of the response function.
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Hall, Peter, and Inge Koch. "On continuous image models and image analysis in the presence of correlated noise." Advances in Applied Probability 22, no. 2 (June 1990): 332–49. http://dx.doi.org/10.2307/1427539.
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Most theoretical studies of image processing employ discrete image models. While that might be a good approximation to digital analysis, it severely restricts the class of tractable models for the blur component of image degradation, and concentrates excessive attention on specialized features of the pixel lattice. It is analogous to modelling all real statistical data using discrete distributions, which is clearly unnecessary. In this paper we study a continuous model for image analysis, in the presence of systematic degradation via a point spread function and stochastic degradation by a second-order stationary random field. Thus, we depart from the restrictive white-noise models which are commonly used in the theory of image analysis. We establish a general result which describes the performance of optimal image processing methods when the noise process has short-range dependence. Concise limits to resolution are derived, depending on image type, point spread function and noise correlation. These results are developed in important special cases, giving explicit formulae for optimal smoothing sets and convergence rates.
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Hall, Peter, and Inge Koch. "On continuous image models and image analysis in the presence of correlated noise." Advances in Applied Probability 22, no. 02 (June 1990): 332–49. http://dx.doi.org/10.1017/s0001867800019601.
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Most theoretical studies of image processing employ discrete image models. While that might be a good approximation to digital analysis, it severely restricts the class of tractable models for the blur component of image degradation, and concentrates excessive attention on specialized features of the pixel lattice. It is analogous to modelling all real statistical data using discrete distributions, which is clearly unnecessary. In this paper we study a continuous model for image analysis, in the presence of systematic degradation via a point spread function and stochastic degradation by a second-order stationary random field. Thus, we depart from the restrictive white-noise models which are commonly used in the theory of image analysis. We establish a general result which describes the performance of optimal image processing methods when the noise process has short-range dependence. Concise limits to resolution are derived, depending on image type, point spread function and noise correlation. These results are developed in important special cases, giving explicit formulae for optimal smoothing sets and convergence rates.
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Rex, John H., Page W. Nelson, Victor L. Paetznick, Mario Lozano-Chiu, A. Espinel-Ingroff, and Elias J. Anaissie. "Optimizing the Correlation between Results of Testing In Vitro and Therapeutic Outcome In Vivo for Fluconazole by Testing Critical Isolates in a Murine Model of Invasive Candidiasis." Antimicrobial Agents and Chemotherapy 42, no. 1 (January 1, 1998): 129–34. http://dx.doi.org/10.1128/aac.42.1.129.
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ABSTRACT The trailing growth phenomenon seen when determining the susceptibilities of Candida isolates to the azole antifungal agents makes consistent endpoint determination difficult, and the M27-A method of the National Committee for Clinical Laboratory Standards addresses this problem by requiring an 80% reduction in growth after 48 h of incubation. For some isolates, however, minor variations of this endpoint criterion can produce up to 128-fold variations in the resulting MIC. To investigate the significance of this effect, isolates of Candida that exhibited various forms of trailing growth when tested against fluconazole were identified. The isolates were examined in a murine model of invasive candidiasis and were ranked by their relative response to fluconazole by using both improvement in survival and reduction in fungal burden in the kidney. The resulting rank order of in vivo response did not match the MICs obtained by using the M27-A criterion, and these MICs significantly overestimated the resistance of three of the six isolates tested. However, if the MIC was determined after 24 h of incubation and the endpoint required a less restrictive 50% reduction in growth, MICs which better matched the in vivo response pattern could be obtained. Minor variations in the M27-A endpoint criterion are thus required to optimize the in vitro-in vivo correlation for isolates that demonstrate significant trailing growth when tested against fluconazole.
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Commerford, Benjamin P., Richard C. Hatfield, and Richard W. Houston. "The Effect of Real Earnings Management on Auditor Scrutiny of Management's Other Financial Reporting Decisions." Accounting Review 93, no. 5 (January 1, 2018): 145–63. http://dx.doi.org/10.2308/accr-52032.
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ABSTRACT Recent research reveals that accruals-based earnings management (AEM) is decreasing while real earnings management (REM) is increasing, suggesting the correlation is due to regulatory scrutiny. However, based on Correspondent Inference Theory, we predict and find that when management uses REM, auditors are more restrictive of management's subjective estimates, making it more difficult for management to use income-increasing AEM. Our experiment manipulates the presence versus absence of REM, and whether the audit difference potentially impacts the client's ability to meet an earnings target. Using a serial mediation model, we find that when auditors observe REM, they perceive these operating decisions as aggressive, leading them to perceive management as aggressive, ultimately causing greater proposed adjustments on an unrelated audit difference. We contribute to the literature by demonstrating that when auditors observe REM, their altered perceptions about management can cascade, affecting how they respond to management estimates in unrelated financial statement accounts.
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Wu, Shiwen, Yanfang Shen, Yujie Geng, Tinggui Chen, and Lei Xi. "Consumer Panic Buying Behavior and Supply Distribution Strategy in a Multiregional Network after a Sudden Disaster." Systems 11, no. 2 (February 20, 2023): 110. http://dx.doi.org/10.3390/systems11020110.
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Panic buying is now a frequent occurrence in many countries, leading to stockouts and supply chain disruptions. This paper highlights consumers’ panic buying behavior in different types of regions and the impact of different replenishment strategies after an emergency supply disruption. Panic buying behavior occurs when consumers try to mitigate the negative impact of a supply disruption. Therefore, this paper develops a consumer-based agency model to study the correlation between public opinion and panic buying and simulates the influence of consumers’ panic buying behavior under different situations in a complex network. The results show that the spread of panic feelings can lead to panic buying behavior among consumers, which then shocks the retailer market. The distribution of supplies according to the type of city and the number of people can have an impact on consumer panic buying behavior, and when the government adopts a restrictive strategy, implementing a quota policy or uniform rationing is very effective in reducing the number of consumers participating in panic buying.
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Cardosi, Joshua David, Herman Shen, Jonathan I. Groner, Megan Armstrong, and Henry Xiang. "Machine learning for outcome predictions of patients with trauma during emergency department care." BMJ Health & Care Informatics 28, no. 1 (October 2021): e100407. http://dx.doi.org/10.1136/bmjhci-2021-100407.
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ObjectivesTo develop and evaluate a machine learning model for predicting patient with trauma mortality within the US emergency departments.MethodsThis was a retrospective prognostic study using deidentified patient visit data from years 2007 to 2014 of the National Trauma Data Bank. The predictive model intelligence building process is designed based on patient demographics, vital signs, comorbid conditions, arrival mode and hospital transfer status. The mortality prediction model was evaluated on its sensitivity, specificity, area under receiver operating curve (AUC), positive and negative predictive value, and Matthews correlation coefficient.ResultsOur final dataset consisted of 2 007 485 patient visits (36.45% female, mean age of 45), 8198 (0.4%) of which resulted in mortality. Our model achieved AUC and sensitivity-specificity gap of 0.86 (95% CI 0.85 to 0.87), 0.44 for children and 0.85 (95% CI 0.85 to 0.85), 0.44 for adults. The all ages model characteristics indicate it generalised, with an AUC and gap of 0.85 (95% CI 0.85 to 0.85), 0.45. Excluding fall injuries weakened the child model (AUC 0.85, 95% CI 0.84 to 0.86) but strengthened adult (AUC 0.87, 95% CI 0.87 to 0.87) and all ages (AUC 0.86, 95% CI 0.86 to 0.86) models.ConclusionsOur machine learning model demonstrates similar performance to contemporary machine learning models without requiring restrictive criteria or extensive medical expertise. These results suggest that machine learning models for trauma outcome prediction can generalise to patients with trauma across the USA and may be able to provide decision support to medical providers in any healthcare setting.
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Zhang, Zhiqiang, Ling Li, and Qiuyu Guo. "The Interactive Relationships between the Tourism-Transportation-Ecological Environment System of Provinces along the ‘Silk Road Economic Belt’ in China." Sustainability 14, no. 5 (March 5, 2022): 3050. http://dx.doi.org/10.3390/su14053050.
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Taking nine provinces and cities along the ‘Silk Road Economic Belt’ as an example, this paper constructs an evaluation index system of the coupling coordination degree of the tourism–transportation–ecological environment system (TTE system), analyzes the spatial–temporal evolution and regional differences of the coupling coordination level of the TTE system from 2004 to 2016 using the mean square error index model and the scissor difference model, and uses the EKC curve model to further verify the interactive relationship between the tourism economy and the ecological environment. The results show the following. (1) The comprehensive evaluation values of the tourism subsystem and transportation subsystem are on an overall upward trend and the comprehensive evaluation value of the ecological environment subsystem is in constant flux. (2) The coupling coordination degree of the TTE system generally develops in a good coordination direction, but the conversion rate of the coupling coordination degree of each province is different. (3) Regarding the north–south region divergence, the degree of coupling and coordination within the region is “strong in the south and weak in the north”. (4) The tourism subsystem and the transportation subsystem are interdependent and mutually restrictive. (5) There is a strong correlation between tourism, economic growth, and environmental quality, but in most provinces, the relationship between them does not accord with the inverted U-shaped environmental Kuznets curve.
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Li, Wenjing, Zhuoyang Sun, Mehdi Makvandi, Qingchang Chen, Jiayan Fu, Lei Gong, and Philip F. Yuan. "The Use of Normative Energy Calculation beyond the Optimum Retrofit Solutions in Primary Design: A Case Study of Existing Buildings on a Campus." Sustainability 15, no. 9 (April 23, 2023): 7094. http://dx.doi.org/10.3390/su15097094.
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There are significant differences between expectations and fulfillment in the building delivery process. Many researchers have emphasized the need for design strategies that establish a direct correlation between design proposals and building performance. One of the main objectives is to support performance-driven primary design, which occurs before the design performance modeling (DPM) phase. To achieve this, a case study of retrofitting existing buildings on campus is presented. A normative calculation approach is used to identify the optimal combinations of a dozen retrofit strategies based on the Energy Performance Calculator (EPC) model. This approach reduces or eliminates the impact of parametric uncertainties on modeling assumptions and simplifies calculations, particularly in restrictive studies. These retrofit solutions involve structural and functional zoning renovation, meaning that disparity between expectations and fulfilments is considered, and a timely related information feedback route to architects is achieved. In the first step of the narrative development of the EPC model, EPC-Calib was used to find the optimal combination of input variables in the model that satisfies the desired target and complies with the problem constraints. Secondly, the retrofit study was implemented with EPC-TechOpt, and 16 retrofit solutions for three design performance models were examined based on the local climatic conditions, building features, and retrofit costs. Finally, design schemes were determined, and the cost-optimal mix of the measures was desired with a 40% energy saving.
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Qiao, Mingzhe, Saihong Chen, and Shiwei Xu. "Equity incentive contract characteristics and company operational performance—An empirical study of Chinese listed companies." PLOS ONE 18, no. 2 (February 6, 2023): e0281244. http://dx.doi.org/10.1371/journal.pone.0281244.
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Equity incentive, as an institutional arrangement for the coordination of the interests of shareholders and managers, has been widely implemented by public companies in developed capital markets throughout Europe and America. However, does it work and/or when might it be more effective in emerging market economies such as China? We aimed to understand the effects of equity incentive plans implemented by listed companies in China and the potential influence of the general characteristics of contracts on the effectiveness of equity incentive plans. Based on behavioral decision theory, this paper adopts a multivariate linear regression model to analyze the 1695 equity incentive plans implemented in Chinese listed companies between 2010 and 2018 with their two-year lagged performance data. The empirical results show that the operational performance of companies after implementing equity incentive plans shows a trend of polarization. In the 95% confidence interval, the effect of restrictive stock incentive and exercise-constrained variables is not significant, while the validity period has a significant positive correlation and incentive intensity has a significantly negative correlation with the company’s operational performance. Furthermore, the negative effects mentioned above become more obvious with a longer plan implementation period. Based on these conclusions, we suggest that companies could adopt equity incentive plans with a relatively longer validity period and more reasonable incentive intensity. Additionally, it would be better for companies to select non-restricted stocks as incentive tools if there is no obvious preference.
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Bonavera, L., J. González-Nuevo, M. M. Cueli, T. Ronconi, M. Migliaccio, L. Dunne, A. Lapi, S. J. Maddox, and M. Negrello. "Cosmology with the submillimetre galaxies magnification bias: Proof of concept." Astronomy & Astrophysics 639 (July 2020): A128. http://dx.doi.org/10.1051/0004-6361/202038050.
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Context. As recently demonstrated, high-z submillimetre galaxies (SMGs) are the perfect background sample for tracing the mass density profiles of galaxies and clusters (baryonic and dark matter) and their time-evolution through gravitational lensing. Their magnification bias, a weak gravitational lensing effect, is a powerful tool for constraining the free parameters of a halo occupation distribution (HOD) model and potentially also some of the main cosmological parameters. Aims. The aim of this work is to test the capability of the magnification bias produced on high-z SMGs as a cosmological probe. We exploit cross-correlation data to constrain not only astrophysical parameters (Mmin, M1, and α), but also some of the cosmological ones (Ωm, σ8, and H0) for this proof of concept. Methods. The measured cross-correlation function between a foreground sample of GAMA galaxies with spectroscopic redshifts in the range 0.2 < z < 0.8 and a background sample of H-ATLAS galaxies with photometric redshifts > 1.2 is modelled using the traditional halo model description that depends on HOD and cosmological parameters. These parameters are then estimated by performing a Markov chain Monte Carlo analysis using different sets of priors to test the robustness of the results and to study the performance of this novel observable with the current set of data. Results. With our current results, Ωm and H0 cannot be well constrained. However, we can set a lower limit of > 0.24 at 95% confidence level (CL) on Ωm and we see a slight trend towards H0 > 70 values. For our constraints on σ8 we obtain only a tentative peak around 0.75, but an interesting upper limit of σ8 ≲ 1 at 95% CL. We also study the possibility to derive better constraints by imposing more restrictive priors on the astrophysical parameters.
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García-Carnero, Laura C., Diana M. Clavijo-Giraldo, Manuela Gómez-Gaviria, Nancy E. Lozoya-Pérez, Alma K. Tamez-Castrellón, Luz A. López-Ramírez, and Héctor M. Mora-Montes. "Early Virulence Predictors during the Candida Species–Galleria mellonella Interaction." Journal of Fungi 6, no. 3 (August 27, 2020): 152. http://dx.doi.org/10.3390/jof6030152.
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Fungal infections are a serious and increasing threat for human health, and one of the most frequent etiological agents for systemic mycoses is Candida spp. The gold standard to assess Candida virulence is the mouse model of systemic candidiasis, a restrictive, expensive, and time-consuming approach; therefore, invertebrate models have been proposed as alternatives. Galleria mellonella larvae have several traits that make them good candidates to study the fungal virulence. Here, we showed that a reduction in circulating hemocytes, increased melanin production, phenoloxidase, and lactate dehydrogenase activities were observed at 12 and 24 h postinoculation of highly virulent Candidatropicalis strains, while minimal changes in these parameters were observed in low-virulent strains. Similarly, the most virulent species Candida albicans, Candida tropicalis, Candida auris, Candida parapsilosis, and Candida orthopsilosis have led to significant changes in those parameters; while the low virulent species Candida guilliermondii, Candida krusei, and Candida metapsilosis induced modest variations in these immunological and cytotoxicity parameters. Since changes in circulating hemocytes, melanin production, phenoloxidase and lactate dehydrogenase activities showed a correlation with the larval median survival rates at 12 and 24 h postinoculation, we proposed them as candidates for early virulence predictors in G. mellonella.
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Fiems, Dieter, Eline De Cuypere, Koen De Turck, and Dieter Claeys. "Performance Analysis of Hybrid MTS/MTO Systems with Stochastic Demand and Production." Mathematics 8, no. 11 (November 2, 2020): 1925. http://dx.doi.org/10.3390/math8111925.
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We present a comprehensive numerical approach with reasonably light complexity in terms of implementation and computation for assessing the performance of hybrid make-to-stock (MTS)/make-to-order (MTO) systems. In such hybrid systems, semi-finished products are produced up front and stored in a decoupling inventory. When an order arrives, the products are completed and possibly customised. We study this system in a stochastic setting: demand and production are modelled by random processes. In particular, our model includes two coupled Markovian queues: one queue represents the decoupling inventory and the other the order backlog. These queues are coupled as order processing can only occur when both queues are non-empty. We rely on matrix analytic techniques to study the performance of the MTO/MTS system under non-restrictive stochastic assumptions. In particular, we allow for arrival correlation and non-exponential setup and MTS and MTO processing times, while the hybrid MTS/MTO system is managed by an (s,S)-type threshold policy that governs switching from MTO to MTS and back. By some numerical examples, we assess the impact of inventory control, irregular order arrivals, setup and order processing times on inventory levels and lead times.
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van Noord, JA, J. Clement, M. Cauberghs, I. Mertens, KP Van de Woestijne, and M. Demedts. "Total respiratory resistance and reactance in patients with diffuse interstitial lung disease." European Respiratory Journal 2, no. 9 (October 1, 1989): 846–52. http://dx.doi.org/10.1183/09031936.93.02090846.
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In 54 patients with interstitial lung diseases and no signs of airway obstruction we measured lung volumes, maximal expiratory flows, diffusing capacity (DLCO), total respiratory resistance (Rrs) and reactance (Xrs) between 4 and 26 Hz by means of the forced oscillation technique. In all patients DLCO was less than 75% of the expected value. Patients were classified into two groups depending on total lung capacity (TLC): group A with TLC less than 80% of expected, and group B with TLC of 80% or more. Group A demonstrated a decrease of Xrs especially at low frequencies, with small, not significant changes in Rrs. In the patients in this group with the lowest values of TLC (less than 50%), we observed an increase of Rrs at low frequencies causing a negative frequency dependence of Rrs. In group B no distinct changes of Rrs and Xrs occurred. Canonical correlation analysis between routine lung function data and forced oscillation parameters, showed tight correlations between TLC in absolute value or VC in percent of the predicted value on the one hand and average level of Xrs and average slope of Xrs (and Rrs) vs frequency curves on the other hand. Measurements of lung mechanics in five additional patients and comparison with a model of the respiratory system suggest that the changes of Rrs and Xrs are not explained totally by the observed increase in lung tissue resistance and decrease in lung compliance. The observed changes in Rrs and Xrs are not specific for restrictive lung disorders; similar changes are met also in moderately advanced obstructive diseases.
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Liu, Haitao, Haibo Gong, Shenjun Zheng, Yujuan Cao, Yong Hong, Yongle Hu, Zuo Liu, and Hao Dai. "A Practical R&D Expenditure Statistic and Management Method Based on Spatial-Temporal Representation of Multi-factors and Data Twin Technology." International Journal of Innovation, Management and Technology 14, no. 2 (2023): 59–63. http://dx.doi.org/10.18178/ijimt.2023.14.2.938.
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Nowadays, R&D Expenditure plays an important role in more and more creative activities of enterprises and other entities, especially in research activities and programs of society. However there still have a big problem that is how to collect and classify R&D Expenditure accurately. In this paper, after analyzing the restrictive collection factors on R&D Expenditure statistically, a practical scheme was provided that including R&D Expenditure Feature Vector and “Object Wood” concept were defined firstly, intelligent receipt recognizing model (IRPM), intelligent receipt persona model (IRRM) based on spatial-temporal representation of multi-factors and R&D expenditure data Twin(REDT) based on data multi relationship were developed creatively. Besides, intelligence carrier-class R&D expenditure management system (REMS) was developed based on above novel technologies and deployed on cloud with SaaS mode. For calling advantageously and updating conveniently, API standard interface and Full Stack Security Mechanism were also improved and used in REMS. Meanwhile, it was proved that REMS had better performance on assisting enterprise in collecting and using their R&D Expenditure after REMS employed by 50 industrial enterprises at first batch in practical over a period of time. There also have better economic benefits and social benefits after REMS was used by 211 enterprises in practically. Next, REMS would be utilized and tested in more scope of important entities so that the correlation technologies could be tested, iterated and optimized forward in the future. Actually, REMS is becoming R&D Expenditure industrial promoted by investor and market. Eventually, REMS would become one of the best R&D Expenditure collecting and using tools, it would not only promote R&D Expenditure increase but also become a industrial correlating with R&D Expenditure.
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Lutoshkin, I. V., and M. S. Rybina. "Modelling of Regional Economic Management in Conditions of Mass Diseases." Economy of Regions 19, no. 2 (2023): 299–313. http://dx.doi.org/10.17059/ekon.reg.2023-2-1.
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Economic globalisation, logistics intensification, world population growth and increasing mobility lead to the emergence of mass diseases, determining the behaviour of various economic agents. The article offers a new tool for analysing regional economic management in conditions of mass diseases, which combines both socio-biological and economic factors in one economic and mathematical model. The proposed model is based on the description of disease dynamics among various population groups (SIR or SIER compartmental models) and corresponding socio-economic changes. Investments in the improvement of hospital beds, in the construction of new hospitals, and in information campaigns to combat the disease are considered as control actions on the economic system. Thus, the regional management system can apply this tool to quantify and compare possible management decisions, taking into account the mutual influence of biological and socio-economic factors. Mathematical models in population biology and epidemiology were analysed in order to construct the tool and assess its parameters by the methods of regression correlation analysis, simulation modelling, and numerical analysis of the differential equation system. In particular, statistical information on the COVID-19 pandemic in Russia and Ulyanovsk oblast for 2020 was examined during the research. The developed software package was utilised to model the presence or absence of restrictive measures during the reviewed period; then, a comparative analysis of these strategies was conducted. The described tool can be adapted to assess the management strategies of various economic agents. It can be further supplemented with quality criteria and appropriate algorithms for selecting optimal strategies to manage regional economy in conditions of mass diseases.
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Motta, Giovanni, Darlin Soto, and Márcio Catelan. "Periodic Variable Stars Modulated by Time-varying Parameters." Astrophysical Journal 925, no. 1 (January 1, 2022): 73. http://dx.doi.org/10.3847/1538-4357/ac3833.
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Abstract Many astrophysical phenomena are time-varying, in the sense that their brightness changes over time. In the case of periodic stars, previous approaches assumed that changes in period, amplitude, and phase are well described by either parametric or piecewise-constant functions. With this paper, we introduce a new mathematical model for the description of the so-called modulated light curves, as found in periodic variable stars that exhibit smoothly time-varying parameters such as amplitude, frequency, and/or phase. Our model accounts for a smoothly time-varying trend and a harmonic sum with smoothly time-varying weights. In this sense, our approach is flexible because it avoids restrictive assumptions (parametric or piecewise-constant) about the functional form of the trend and amplitudes. We apply our methodology to the light curve of a pulsating RR Lyrae star characterized by the Blazhko effect. To estimate the time-varying parameters of our model, we develop a semi-parametric method for unequally spaced time series. The estimation of our time-varying curves translates into the estimation of time-invariant parameters that can be performed by ordinary least squares, with the following two advantages: modeling and forecasting can be implemented in a parametric fashion, and we are able to cope with missing observations. To detect serial correlation in the residuals of our fitted model, we derive the mathematical definition of the spectral density for unequally spaced time series. The proposed method is designed to estimate smoothly time-varying trends and amplitudes, as well as the spectral density function of the errors. We provide simulation results and applications to real data.
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Vasin, Sergey Mikhailovich. "Comparative Analysis of Socioeconomic Models in COVID-19 Pandemic." Economies 10, no. 11 (November 8, 2022): 278. http://dx.doi.org/10.3390/economies10110278.
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Certain features of socioeconomic models can be distinctly determined in different countries and regions. However, such models are quite flexible under external and internal influences. Their changes can be observed under the impact of unpredictable factors, the COVID-19 pandemic being one. The aim of the work is to identify differences in the structure of socioeconomic models under the influence of the pandemic. The object of the study is the socioeconomic models of various states. The subject of the study is the transformation of socioeconomic models at different stages of the pandemic. Research methods include analysis of statistical data, correlation and comparative analysis, and graphical methods of presenting results. A comparison of data from the most well-known socioeconomic models was carried out for the first time. It is determined that the countries of the Chinese model adopted restrictive measures of high Stringency Index. The countries of the Japanese model used unique crowd management methods, and the countries of the Scandinavian, German and Anglo-Saxon models resorted to unprecedented monetary injections into the social and economic spheres. It was revealed that quarantine measures eventually cost countries less than monetary injections. It was shown that a decrease in the Pandemic Uncertainty Index stabilized the economic behavior of the population and businesses and increased the volume of export-import operations. It was found that the pandemic affected the economy indirectly through the level of uncertainty and rigidity of preventive measures. It is assumed that the intensity and severity of measures could be influenced by global trends leading to certain types of preventive measures rather than by the COVID-19 statistics of a particular country.
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Rezaie, Javad, Jo Eidsvik, and Tapan Mukerji. "Value of information analysis and Bayesian inversion for closed skew-normal distributions: Applications to seismic amplitude variation with offset data." GEOPHYSICS 79, no. 4 (July 1, 2014): R151—R163. http://dx.doi.org/10.1190/geo2013-0048.1.
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Information analysis can be used in the context of reservoir decisions under uncertainty to evaluate whether additional data (e.g., seismic data) are likely to be useful in impacting the decision. Such evaluation of geophysical information sources depends on input modeling assumptions. We studied results for Bayesian inversion and value of information analysis when the input distributions are skewed and non-Gaussian. Reservoir parameters and seismic amplitudes are often skewed and using models that capture the skewness of distributions, the input assumptions are less restrictive and the results are more reliable. We examined the general methodology for value of information analysis using closed skew normal (SN) distributions. As an example, we found a numerical case with porosity and saturation as reservoir variables and computed the value of information for seismic amplitude variation with offset intercept and gradient, all modeled with closed SN distributions. Sensitivity of the value of information analysis to skewness, mean values, accuracy, and correlation parameters is performed. Simulation results showed that fewer degrees of freedom in the reservoir model results in higher value of information, and seismic data are less valuable when seismic measurements are spatially correlated. In our test, the value of information was approximately eight times larger for a spatial-dependent reservoir variable compared with the independent case.
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Ma, Lizheng, Congzhi Zhang, Kai Lisa Lo, and Xiangyan Meng. "Can Stringent Government Initiatives Lead to Global Economic Recovery Rapidly during the COVID-19 Epidemic?" International Journal of Environmental Research and Public Health 20, no. 6 (March 12, 2023): 4993. http://dx.doi.org/10.3390/ijerph20064993.
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This paper investigates the effectiveness of government measures implemented against COVID-19 and the factors influencing a country’s economic growth from a global perspective. With the help of the data of the Government Response Stringency Index (GRSI), Google mobility, and confirmed COVID-19 daily cases, we conducted a panel model for 105 countries and regions from 11 March 2020 to 31 June 2021 to explore the effects of response policies in different countries against the pandemic. First, the results showed that staying in residential places had the strongest correlation with confirmed cases. Second, in countries with higher government stringency, stay-at-home policies carried out in the early spread of the pandemic had the most effective the impact. In addition, the results have also been strictly robustly analyzed by applying the propensity score matching (PSM) method. Third, after reconstructing a panel data of 47 OECD countries, we further concluded that governments should take stricter restrictive measures in response to COVID-19. Even though it may also cause a shock to the market in the short term, this may not be sustainable. As long as the policy response is justified, it will moderate the negative effect on the economy over time, and finally have a positive effect.
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Velojic-Golubovic, Milena, Dragan Dimic, Slobodan Antic, Sasa Radenkovic, Boris Djindjic, and Miodrag Jovanovic. "Relationship of adipokine to insulin sensitivity and glycemic regulation in obese women: The effect of body weight reduction by caloric restriction." Vojnosanitetski pregled 70, no. 3 (2013): 284–91. http://dx.doi.org/10.2298/vsp1303284v.
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Bacground/Aim. Visceral fat is highly active metabolic and endocrine tissue which secretes many adipokines that act both on local and systemic level. It is believed that adipokines and "low-grade inflammatory state" represent a potential link between obesity, metabolic syndrome, insulin resistance and cardiovascular disease. Leptin and adiponectin are considered to be the most important adipokines with the potential metabolic and cardiovascular effects. Body weight loss improves insulin sensitivity and decreases risk for most complications associated with obesity. The aim of this study was to determine the effects of moderate loss of body weight on the level of leptin and adiponectin, insulin sensitivity and abnormalities of glycoregulation in obese women, to determine whether and to what extent the secretory products of adipose tissue, leptin and adiponectin contribute to insulin sensitivity, as well as to assess their relationship and influence on glycemia and insulinemia during the period of losing body weight using a calorie restricted diet. Methods. The study involved 90 obese female subjects (BMI ?? 30 kg/m2) of different age with weight loss no less than 5% during a six-month period by application of restricted dietary regime. The calorie range was between 1,100-1,350 kcal. Serum levels of leptin and adiponectin, fasting glucose, fasting insulinemia, and Homeostasis Model Assessment of Insulin Resistance (HOMA-R) index were determined in all the subjects initially and after weight reduction. The presence of glycemic disorders was assessed on the basis of oral glucose tolerance test - OGTT. Results. Applying a 6-month restrictive dietary regime the subjects achieved an average weight loss of 8.73 ? 1.98 kg and 8.64 ? 1.96%, which led to the reduction of fasting glycemia, fasting insulinemia and HOMA-R index at the maximum level of statistical significance (p < 0.001). The achieved reduction led to a statistically significant decrease of leptin level and increase of adiponectin level (p < 0.001). The correction of the established pre-diabetic disorders of glycoregulation was not statistically significant. There was a statistically significant correlation between the anthropometric parameters, leptin, adiponectin, fasting glycemia, fasting insulinemia and HOMA-R index. There was a positive correlation between leptin, fasting insulinemia and HOMA-R, as well as a statistically significant negative correlation between adiponectin, fasting insulinemia and HOMA-R index (p < 0.01). Conclusion. Body weight increase and central fat accumulation lead to changes in serum levels of leptin and adiponectin, reduction of insulin sensitivity and development of glycemic dysregulation. Secretory products of adipose tissue, leptin and adiponectin contribute to the genesis of these disorders. The obtained results show that the effect of adiponectin on insulin sensitivity is more significant. The analysis of the effects of weight loss on the investigated parameters shows that moderate weight reduction by restrictive dietary regime lead to changes of investigated parameters at the maximum level of statistical significance. Such results emphasize the importance of weight reduction in obese persons, as well as the need for consistent implementation of restricted dietary regime in the process of treatment of obesity.
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He, Xi, Aoxue Li, Junhong Li, and Youbo Zhuang. "Conservation and Development: Spatial Identification of Relative Poverty Areas Affected by Protected Areas in China and Its Spatiotemporal Evolutionary Characteristics." Land 11, no. 7 (July 11, 2022): 1048. http://dx.doi.org/10.3390/land11071048.
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Currently, biodiversity conservation and the achievement of common prosperity are important challenges. China bid farewell to “absolute poverty” in 2020 but continues to face challenges, such as relative multidimensional poverty, especially in regions of protected areas (PA). The correlation between poverty and the natural environment leads to further research on the distribution and spatiotemporal evolutionary characteristics of relative poverty regions affected by the restrictive policies of PA. Quantitative research on these regions helps researchers formalize ecological indemnification policies based on the condition of different regions, thereby stabilizing efforts toward poverty alleviation. Through a study on relative poverty areas in 489 county-level administrative regions in China influenced by 477 national nature reserves, this study formulated a multidimensional integrated poverty index model that comprises three systems, namely, natural environment, economy, and society and 13 indicators. Using the comprehensive index, spatial analysis, and cluster analysis to investigate the evolutionary characteristics and driving factors of poverty from 2014 to 2019, the study created a distribution map of relative poverty regions affected by PA. The results indicated the following. (i) Relative poverty regions are mainly concentrated in provinces on the northwest side of the Hu Line with strong spatial correlation between these regions. Among them, the relatively poor areas with persistent deterioration become the keystone to stabilizing poverty alleviation and promoting green development. (ii) Poverty alleviation focuses on the economic dimension, whereas the environmental and social dimensions lack engagement. (iii) Conservation areas overlap with relative poverty regions. However, the increase in PA does not necessarily lead to the aggravation of the poverty in counties. The results offer a valuable reference for decision makers in formulating targeted policies and measures for areas affected by PA to facilitate green development and common prosperity.
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Golovanov, Oleg. "Impact of the COVID-19 pandemic on the socio-economic development of the region." Economics and the Mathematical Methods 59, no. 2 (2023): 54. http://dx.doi.org/10.31857/s042473880022737-9.
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The article presents an analysis of the consequences of economic instability caused by the COVID‑19 pandemic for the socio‑economic development of the region. The study was carried on the example of the Sverdlovsk region according to the Federal State Statistics Service. The article sets and solves three research problems. First, to assess how the overall socio‑economic condition of the region has changed because of the COVID‑19 pandemic. Second, to identify the impact of the COVID‑19 pandemic on the nature and structure of the relationship between the socio‑economic indicators of the region. Third, to analyze the impact of the COVID‑19 pandemic on the trends in the socio‑economic indicators of the region, considering their possible delay and seasonal fluctuations. The first task is solved using statistical methods of pattern recognition, the second task — by methods of multivariate correlation analysis, and for the third task stochastic time series models are used. The largest contribution to the division into clusters was made by the number of births, the turnover of public catering and the volume of goods, works and services performed on their own; their dynamics most clearly traces the impact of the COVID‑19 pandemic in the Sverdlovsk region. Multidimensional correlation analysis established that because of the introduction of restrictive and supportive measures, multidirectional trends in the socio‑economic indicators of the region were formed, which violated the previously established relationships between them. Based on the obtained coefficients of the autoregressive model, one can find a certain pattern consisting in the growth of the influence of short‑term (lag 1 and 3 months) and the decrease of the long‑term influence (lag 12 months) change in indicators. According to the calculations obtained, the economy of the Sverdlovsk region during the analyzed period failed to overcome the destabilizing effect of the consequences of the COVID‑19 pandemic.
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Vollbrecht, E., L. Reiser, and S. Hake. "Shoot meristem size is dependent on inbred background and presence of the maize homeobox gene, knotted1." Development 127, no. 14 (July 15, 2000): 3161–72. http://dx.doi.org/10.1242/dev.127.14.3161.
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The knotted1 (kn1) gene of maize is expressed in meristems and is absent from leaves, including the site of leaf initiation within the meristem. Recessive mutations of kn1 have been described that limit the capacity to make branches and result in extra carpels. Dominant mutations suggest that kn1 function plays a role in maintaining cells in an undifferentiated state. We took advantage of a Ds-induced dominant allele in order to screen for additional recessive alleles resulting from mobilization of the Ds element. Analysis of one such allele revealed a novel embryonic shoot phenotype in which the shoot initiated zero to few organs after the cotyledon was made, resulting in plants that arrested as seedlings. We refer to this phenotype as a limited shoot. The limited shoot phenotype reflected loss of kn1 function, but its penetrance was background dependent. We examined meristem size and found that plants lacking kn1 function had shorter meristems than non-mutant siblings. Furthermore, meristems of restrictive inbreds were significantly shorter than meristems of permissive inbreds, implying a correlation between meristem height and kn1 gene function in the embryo. Analysis of limited shoot plants during embryogenesis indicated a role for kn1 in shoot meristem maintenance. We discuss a model for kn1 in maintenance of the morphogenetic zone of the shoot apical meristem.
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Zhao, Rui, and Kening Wu. "Soil Health Evaluation of Farmland Based on Functional Soil Management—A Case Study of Yixing City, Jiangsu Province, China." Agriculture 11, no. 7 (June 24, 2021): 583. http://dx.doi.org/10.3390/agriculture11070583.
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Given that farmland serves as a strategic resource to ensure national food security, blind emphasis on the improvement of food production capacity can lead to soil overutilization and impair other soil functions. Hence, the evaluation of soil health (SH) should comprehensively take soil productivity and ecological environmental effects into account. In this study, five functions from the perspective of functional soil management were summarized, including primary productivity, provision and cycling of nutrients, the provision of functional and intrinsic biodiversity, water purification and regulation, and carbon sequestration and regulation. For each soil function, in view of the natural and ameliorable conditions affecting SH, basic indicators were selected from the two aspects of inherent and dynamic properties, and restrictive indicators were chosen considering the external properties or environmental elements, with the minimum limiting factor method coupled with weighted linear model. The new evaluation system was tested and verified in Yixing City, China. The healthy and optimally functional soils were concentrated in the northeast and mid-west of Yixing City, whereas unhealthy soils were predominant in the south and around Taihu Lake. The main limitations to SH improvement included cation exchange capacity, nutrient elements, and soluble carbon. The SH evaluation method was verified using the crop performance validation method, and a positive correlation was noted between food production stability index and soil health index, indicating that the evaluation system is reasonable.
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CORDISCO, POTITO, and CHIARA BISAGNI. "DESIGN, TESTING AND VALIDATION OF A COMPOSITE BOX UNDER COMBINED LOADING UP TO COLLAPSE." International Journal of Structural Stability and Dynamics 10, no. 04 (October 2010): 853–69. http://dx.doi.org/10.1142/s0219455410003774.
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This paper presents part of the activities performed by Politecnico di Milano within the European research project COCOMAT, consisting of the design, testing and validation of a closed box structure made up of CFRP stringer-stiffened curved panels. The design phase is carried out using ABAQUS/Explicit with the purpose of obtaining a structure with a ratio between the collapse and the buckling load that is greater than 3 under axial compression and greater than 2 under torque. The box is manufactured by Agusta/Westland and tested at Politecnico di Milano. The first test results are used to validate the FE model, removing some restrictive hypothesis formulated during the design process. Finally, a comparison between the results under combined axial compression and torque loads obtained in the collapse test and in the FE analysis reproducing the collapse is shown. A good correlation is obtained, both in the buckling and postbuckling behavior and in the collapse modality, demonstrating the capability of the dynamic explicit analyses to capture the highly nonlinear response of the aeronautical panels. The results also show the possibility of CFRP structures working deeply in the postbuckling region if properly designed and, consequently, the possibility of a weight reduction of aerospace structures thanks to the possibility of moving up the ultimate load toward the collapse load without any loss in the structural safety.
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Anzulović Šanta, Željka, Anja Ognjenović, Frane Božić, Boška Hrvačić, Ines Glojnarić, Snježana Čužić, and Maja Antolić. "Retrospektivna procjena učinka nintedaniba u mišjem modelu plućne fibroze." Veterinarska stanica 54, no. 4 (December 30, 2022): 395–406. http://dx.doi.org/10.46419/vs.54.4.4.
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Pulmonary function tests (PFTs) routinely implemented in clinics are the first step in the diagnosis of idiopathic pulmonary fibrosis. Evaluation of PFTs in the mouse model of pulmonary fibrosis accompanied by histological readouts may improve the clinical predictability of new therapeutic candidates. Forced vital capacity (FVC) is considered the most predictive of restrictive pulmonary disorders. This study aimed to test the improvement of PFT in mice lung fibrosis induced by treatment with an approved substance nintedanib, considered the gold standard. The hypothesis that treatment in animal models will demonstrate similar effects as in humans in the most relevant clinical outcomes was tested. Two experimental designs were enrolled in this study, a preventive regimen, with treatment initiation from the day of the challenge; and a therapeutic regimen, starting on day 7 postchallenge when fibrotic changes are present in the lungs. Experiments were terminated at two different time points, at 14 and 21 days postchallenge. C57BL/6 mice were administered with bleomycin (BLM) intranasally and treated with nintedanib from day 0 to day 14 or from day 7 until day 21. Fourteen or 21 days after the BLM challenge, PFTs were assessed using the in vivo invasive lung function measurement system Buxco® Pulmonary Function Test (PFT) (DSI™, New Brighton, USA). Histological evaluation was performed as a modified Ashcroft score. The bleomycin challenge induced a significant decrease of FVC in both experiments. However, nintedanib treatment given in both regimens significantly improved lung functionality. These findings were confirmed with histological analysis of the Ashcroft scoring system, modified by Matsuse. In conclusion, a good correlation between functional test parameters and the clinical effect of nintedanib was shown in both experiments: the preventive regimen was sampled 14 days post-challenge and the therapeutic regimen 21 days post-challenge. Based on these findings, the implementation of PFTs could be a good platform to increase the translational value of the model and potential new treatments.
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Ihou, Koffi Eddy, Manar Amayri, and Nizar Bouguila. "Stochastic Variational Optimization of a Hierarchical Dirichlet Process Latent Beta-Liouville Topic Model." ACM Transactions on Knowledge Discovery from Data 16, no. 5 (October 31, 2022): 1–48. http://dx.doi.org/10.1145/3502727.
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In topic models, collections are organized as documents where they arise as mixtures over latent clusters called topics. A topic is a distribution over the vocabulary. In large-scale applications, parametric or finite topic mixture models such as LDA (latent Dirichlet allocation) and its variants are very restrictive in performance due to their reduced hypothesis space. In this article, we address the problem related to model selection and sharing ability of topics across multiple documents in standard parametric topic models. We propose as an alternative a BNP (Bayesian nonparametric) topic model where the HDP (hierarchical Dirichlet process) prior models documents topic mixtures through their multinomials on infinite simplex. We, therefore, propose asymmetric BL (Beta-Liouville) as a diffuse base measure at the corpus level DP (Dirichlet process) over a measurable space. This step illustrates the highly heterogeneous structure in the set of all topics that describes the corpus probability measure. For consistency in posterior inference and predictive distributions, we efficiently characterize random probability measures whose limits are the global and local DPs to approximate the HDP from the stick-breaking formulation with the GEM (Griffiths-Engen-McCloskey) random variables. Due to the diffuse measure with the BL prior as conjugate to the count data distribution, we obtain an improved version of the standard HDP that is usually based on symmetric Dirichlet (Dir). In addition, to improve coordinate ascent framework while taking advantage of its deterministic nature, our model implements an online optimization method based on stochastic, at document level, variational inference to accommodate fast topic learning when processing large collections of text documents with natural gradient. The high value in the predictive likelihood per document obtained when compared to the performance of its competitors is also consistent with the robustness of our fully asymmetric BL-based HDP. While insuring the predictive accuracy of the model using the probability of the held-out documents, we also added a combination of metrics such as the topic coherence and topic diversity to improve the quality and interpretability of the topics discovered. We also compared the performance of our model using these metrics against the standard symmetric LDA. We show that online HDP-LBLA (Latent BL Allocation)’s performance is the asymptote for parametric topic models. The accuracy in the results (improved predictive distributions of the held out) is a product of the model’s ability to efficiently characterize dependency between documents (topic correlation) as now they can easily share topics, resulting in a much robust and realistic compression algorithm for information modeling.
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О.Д., ГОРОХОВА,, and РОМАНОВА, Е.В. "Impact of the Coronavirus Pandemic on the Unemployment and Pay Relationship." Vestnik of North-Eastern Federal University. Series "Economics. Sociology. Culturology", no. 4(28) (December 25, 2022): 24–32. http://dx.doi.org/10.25587/svfu.2022.40.49.003.
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Изучение вопросов влияния факторов на изменение уровня заработной платы, как основного источника доходов населения, является актуальным не только в условиях развития рыночной экономики, но и в условиях развития эпидемиологической ситуации, связанной с возникновением и развитием коронавирусной инфекции COVID-19. Распространение и развитие коронавирусной инфекции в России привело к введению ряда ограничительных и профилактичских мер: введение локдауна, перевод на дистанционный формат работы, вакцинация населения и др. В результате ограничительных мер ряд хозяйствующих субъектов были вынуждены либо остановить, либо прекратить свою деятельность, что привело к росту безработицы практически во всех регионах нашей страны и, как следствие, снижению уровня доходов и заработной платы населения. Основной гипотезой исследования является влияние эпидемиологического фактора (развитие коронавирусной инфекции Covid-19) на характер взаимосвязи между показателями уровня безработицы и заработной платы. В качестве эмпирической базы исследования послужили данные по показателям уровня безработицы и средней заработной платы по регионам федеральных округов России за период 2018‒2020 гг. Основными методами исследования послужили инструменты корреляционного анализа, которые позволили выявить направление и тесноту связи между изучаемыми показателями. Использование критерия Стьюдента подтвердило с вероятностью 0,95 статистическую значимость и надежность коэффициента корреляции только по показателям 2020 г. По результатам корреляционного анализа выдвинутая гипотеза о влиянии пандемии на характер взаимосвязи между показателями безработицы и заработной платы подтвердилась. В период развития пандемии увеличение темпов роста безработицы приводило к замедлению темпов роста заработной платы, что соответствует концепции кривой Филлипса. Корреляционный анализ выявил обратное направление связи между показателями. Теснота связи увеличилась именно в период развития пандемии и наиболее ярко она наблюдалась в двух федеральных округах: Уральском и Сибирском. Материалы исследования могут использоваться органами государственного управления в части разработки эффективных механизмов развития экономики под влиянием эпидемиологических факторов воздействия на экономику государства. Studying the influence of certain factors on the change in the level of pay, as the main source of income for the population, is relevant in the context of a developing market economy; moreover, it is of significance in the context of the occurrence of the epidemiological situation due to the emergence and spread of the coronavirus infection COVID-19. The spread of the coronavirus infection in Russia has led to a number of restrictive and preventive measures: the introduction of a lockdown, transfer to a remote work model, organization of vaccination, etc. The restrictive measures forced a number of businesses to either suspend or stop their activities, which led to increased unemployment rates in almost all regions of our country and, as a result, decreased levels of income and pay. The main hypothesis of the study is the influence of the epidemiological factor (spread of Covid-19 coronavirus infection) on the nature of the relationship between unemployment and pay. The empirical base of the study was data on unemployment rates and average salaries and wages by regions of the federal districts of Russia in the period 2018-2020. Correlation analysis tools served as the main research methods, which allowed us to identify the direction and closeness of the relationship between the studied indicators. The use of Student’s t-test confirmed with a probability of 0.95 the statistical significance and reliability of the correlation coefficient only for 2020 indicators. The correlation analysis confirmed the hypothesis about the impact of the pandemic on the nature of the relationship between unemployment and pay. During the spread of the pandemic, an increased rate of growth in unemployment led to a slowdown in pay growth, which corresponds to the concept of the Phillips curve. The correlation analysis revealed the reverse direction of the relationship between the indicators. The closeness of communication increased precisely during the spread of the pandemic, and it was most clearly observed in two federal districts: the Urals and the Siberian ones. The research materials can be used by government bodies for designing effective mechanisms for economic development under the epidemiological factors influencing the state economy.
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Rogowska, Aleksandra M., Aleksandra Kwaśnicka, and Dominika Ochnik. "Development and Validation of the Test of Orthorexia Nervosa (TON-17)." Journal of Clinical Medicine 10, no. 8 (April 12, 2021): 1637. http://dx.doi.org/10.3390/jcm10081637.
Full textAbstract:
This study aims to develop and validate a new self-report questionnaire to measure orthorexia nervosa (ON). Based on a current review of the scientific literature and interviews with people at risk of orthorexia, 40 items were selected to test orthorexia nervosa (TON-40). A total sample of 767 individuals (M = 26.49, SD = 9.66, 56.98% women) participated in the study. The exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and composite construct analysis (CCA) were performed to find an appropriate model of sufficient reliability and validity and stable construction. Convergent validation was performed regarding the correlation of the TON-17 with another measure of ON (ORTO-15), eating disorders (the EAT-26 and DEAS), healthy behavior (the HBI), quality of life (the Brief WHOQOL), physical health (the GRSH), anxiety (the GAD-7), depression (the PHQ-9), and obsessive-compulsive disorder (the OCI-R). Gender, Body Mass Index (BMI), and the medical reasons for a restrictive diet were also examined. As a result of the structural analyses, the number of items was reduced from 40 to 17. The best fit indices of the TON-17 were found for the hierarchical bi-factor model, with three lower-order factors (Control of food quality, Fixation of health and healthy diet, and Disorder symptoms) and one general higher-order factor (Orthorexia). According to the 95th percentile method of estimation, the prevalence of ON was 5.5% for the TON-17 total score. The TON-17 scale and subscales showed good psychometric properties, stability, reliability, and construct validity. The TON-17 indicated a positive relationship with the ORTO-15, EAT-26, DEAS, HBI, OCI-R, GAD-7, and PHQ-9. TON-17 can be considered as a useful tool for assessing the risk of ON.
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Sebastianelli, Alessandro, Francesco Mauro, Gianluca Di Cosmo, Fabrizio Passarini, Marco Carminati, and Silvia Liberata Ullo. "AIRSENSE-TO-ACT: A Concept Paper for COVID-19 Countermeasures Based on Artificial Intelligence Algorithms and Multi-Source Data Processing." ISPRS International Journal of Geo-Information 10, no. 1 (January 14, 2021): 34. http://dx.doi.org/10.3390/ijgi10010034.
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The aim of this concept paper is the description of a new tool to support institutions in the implementation of targeted countermeasures, based on quantitative and multi-scale elements, for the fight and prevention of emergencies, such as the current COVID-19 pandemic. The tool is a cloud-based centralized system; a multi-user platform that relies on artificial intelligence (AI) algorithms for the processing of heterogeneous data, which can produce as an output the level of risk. The model includes a specific neural network which is first trained to learn the correlations between selected inputs, related to the case of interest: environmental variables (chemical–physical, such as meteorological), human activity (such as traffic and crowding), level of pollution (in particular the concentration of particulate matter) and epidemiological variables related to the evolution of the contagion. The tool realized in the first phase of the project will serve later both as a decision support system (DSS) with predictive capacity, when fed by the actual measured data, and as a simulation bench performing the tuning of certain input values, to identify which of them led to a decrease in the degree of risk. In this way, we aimed to design different scenarios to compare different restrictive strategies and the actual expected benefits, to adopt measures sized to the actual needs, adapted to the specific areas of analysis and useful for safeguarding human health; and we compared the economic and social impacts of the choices. Although ours is a concept paper, some preliminary analyses have been shown, and two different case studies are presented, whose results have highlighted a correlation between NO2, mobility and COVID-19 data. However, given the complexity of the virus diffusion mechanism, linked to air pollutants but also to many other factors, these preliminary studies confirmed the need, on the one hand, to carry out more in-depth analyses, and on the other, to use AI algorithms to capture the hidden relationships among the huge amounts of data to process.
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Walkowiak, Jaroslaw, Edyta Mądry, Aleksandra Lisowska, Anna Szaflarska-Popławska, Marian Grzymisławski, Hanna Stankowiak-Kulpa, and Juliusz Przysławski. "Adaptive changes of pancreatic protease secretion to a short-term vegan diet: influence of reduced intake and modification of protein." British Journal of Nutrition 107, no. 2 (July 13, 2011): 272–76. http://dx.doi.org/10.1017/s0007114511002923.
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In our previous study, we demonstrated that abstaining from meat, for 1 month, by healthy omnivores (lacto-ovovegetarian model) resulted in a statistical decrease in pancreatic secretion as measured by faecal elastase-1 output. However, no correlation between relative and non-relative changes of energy and nutrient consumption and pancreatic secretion was documented. Therefore, in the present study, we aimed to assess the changes of exocrine pancreatic secretion with a more restrictive dietetic modification, by applying a vegan diet. A total of twenty-one healthy omnivores (sixteen females and five males) participated in the prospective study lasting for 6 weeks. The nutrient intake and faecal output of pancreatic enzymes (elastase-1, chymotrypsin and lipase) were assessed twice during the study. Each assessment period lasted for 7 d: the first before the transition to the vegan diet (omnivore diet) and the second during the last week of the study (vegan diet). The dietary modification resulted in a significant decrease in faecal elastase-1 (P < 0·05) and chymotrypsin output (P < 0·04). The lipase excretion remained unchanged. The decrease in proteolytic enzymes was documented to be positively correlated with a decreased protein intake (P < 0·05). In addition, elastase-1 and chymotrypsin outputs were also related to the changes of protein type, plantv.animal (P < 0·04 andP < 0·03, respectively). It was concluded that significant reduction and modification of protein intake due to a short-term vegan diet resulted in an adaptation of pancreatic protease secretion in healthy volunteers.
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Bai, Min. "An Empirical Study on the Relationship between Stock Price Information and Enterprise Innovation Management Based on Information Learning Mechanism." Computational Intelligence and Neuroscience 2022 (May 17, 2022): 1–10. http://dx.doi.org/10.1155/2022/9425405.
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The capital market economy had created a good environment for the development of enterprises, and innovation had brought great impetus to the sustainable development of enterprises. However, the research on the relationship between stock market and enterprise innovation was not deep enough. Therefore, this paper proposed an empirical study on the relationship between stock price information and enterprise innovation management based on information learning mechanism, in order to provide reference for enterprise innovation and development. Firstly, taking the A-share listed enterprises from 2005 to 2020 as the research sample, this paper analyzed the factors that may affect the innovation behavior of enterprises, such as enterprise stock price information, peer stock price information, and IPO, and put forward relevant assumptions. Secondly, according to various factors that restrict the innovation behavior of enterprises, this paper defined relevant indicators to reflect the change law of enterprise stock price information, peer stock price information, and IPO and described the restrictive relationship between exploratory innovation and developmental innovation with different influencing factors by constructing a correlation regression model. Finally, through empirical analysis, the results show that exploratory innovation and developmental innovation are not affected by the enterprise’s own stock price information, but with the increase of peer stock price information, enterprise exploratory innovation becomes more sensitive to peer stock price information. Although the share price information of peers has no significant impact on enterprise development and innovation, after IPO, enterprises are more sensitive to the share price information of peers in exploratory innovation and developmental innovation. However, with the passage of time, the impact of peer stock price information on enterprise developmental innovation is gradually weakened.
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Kascha, Mariya, Maksym Palienko, and Roman Marchenko. "Forecast of COVID-19 progress considering the seasonal fluctuations." Health Economics and Management Review 2, no. 2 (2021): 71–82. http://dx.doi.org/10.21272/hem.2021.2-07.
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This study aims to analyze the course of the COVID-19 disease and forecast its progress. Systematization of scientific background concerning the issues under investigation indicated the snowballing growth of scientific publications devoted to COVID-19. The urgency of the research rests on the negative influence of the SARS-CoV-2 virus on all spheres that deepen the global economic crisis. The forecast of the COVID-19 progress in Ukraine was carried out in the following logical sequence: 1) collection and analysis of statistical data; 2) testing stationarity and periodicity of the time series, using software Statistica (portable); 3) constructing the trend component 4) detecting the seasonal component by the fast Fourier transformation under excluded trend; 5) building the general model, checking its quality and adequacy; 6) forecast and elaboration on the recommendations. The methodological tools of the study were the regression and correlation analysis, the Dickie-Fuller test, decomposition of the additive model into cyclic and trend components, and the fast Fourier transformation, using software MathCAD(portable). The empirical research was conducted based on panel data from 22 January 2020 to 2 May 2021. The object of the study was selected the population of Ukraine who were infected with coronavirus during the study period. The study empirically confirmed and theoretically proved that if the pandemic tendency persists and the absence of carefully planned COVID-19 preventive work in Ukraine, a new wave of the disease may occur from mid-August to early September. Besides, the growth of the load on the medical sector and the increase in COVID-19 deaths among the population may lead to the introduction of new restrictive quarantine measures. In turn, it would result in an economic shutdown and the decline of small and medium businesses. Therefore, it is necessary to direct the Government’s policy to eliminate the myths about vaccination, to increase confidence in vaccination among the population, which will avoid the next wave of diseases.
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Liu, Erin Y., and Anne TM Konkle. "Extreme Male Brain Theory of Autism." Revue interdisciplinaire des sciences de la santé - Interdisciplinary Journal of Health Sciences 2, no. 1 (March 10, 2011): 32. http://dx.doi.org/10.18192/riss-ijhs.v2i1.1525.
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Autism spectrum conditions (ASCs) are a category of neurodevelopmental disorders with symptoms of communication and social impairment, and the exhibition of restrictive and repetitive behaviours. Their occurrence is greater in males than females and this sex difference has played an important part in hypothesizing their etiology. The Extreme Male Brain (EMB) theory is a cognitive model proposed by Simon Baron-Cohen to explain the aforementioned sex differences and potential cause of ASCs. It is based upon his Empathizing Systemizing theory, which classifies individuals into one of five cognitive profiles (Type S, Type E, Type B, Extreme Type S and Extreme Type E). These cognitive profiles determine an individual’s ability to systemize and empathize. Systemizing is the ability to understand and derive the rules of a system, and requires deductive and analytical skills. Empathizing relates to understanding human emotion and behaviour, thus requires social and communication skills. Males tend to systemize better than empathize while females have an opposite profile. Based upon the EMB theory, autistic individuals would possess an Extreme Type S profile as their impairments in social communication can be explained by a deficit in empathizing, while their preoccupation with patterns and detail-oriented behaviour can be related to their high systemizing. Together, these cognitive models have resulted in the Foetal Testosterone (fT) Theory, which implicates high prenatal testosterone as a risk factor for the associated hypermasculinized cognitive profile of individuals with ASCs. This review paper assesses the validity of the EMB and fT theories by reviewing the literature relating fT with autistic traits in the general population. The seven studies confirmed a correlation between higher fT levels and an increase in autistic traits, but limitations need to be considered when generalizing this information to an ASC sample.