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The purpose of this paper is to construct a grey incidence model for panel data that can reflect the incidence direction and degree between indicators.

Firstly, this paper introduces the concept of a negative matrix and preprocesses the data of each indicator matrix to eliminate differences in dimensions and magnitudes between indicators. Then a model is constructed to measure the incidence direction and degree between indicators, and the properties of the model are studied. Finally, the model is applied to a practical problem.

The grey-directed incidence degree is 1 if and only if corresponding elements between the feature indicator matrix and the factor indicator matrix have a positive linear relationship. This degree is −1 if and only if corresponding elements between the feature indicator matrix and the factor indicator matrix have a negative linear relationship.

The example shows the number of days with good air quality is negatively correlated with the annual average concentration of each pollutant index. PM_2.5, PM₁₀ and O₃ are the main pollutants affecting air quality in northern Henan.

This paper introduces the negative matrix and constructs a model from the holistic perspective to measure the incidence direction and level between indicators. This model can effectively measure the incidence between the feature indicator and factor indicator by integrating information from the point, row, column and matrix.

This paper sets out to solve a common and crucial fundamental theoretical problem of gray incidence cluster analysis: to [X]={X|ρ(X,Y)≥1−ε0} constitute an approximate classification, it must first be proven that [X]={X|ρ(X,Y)=1} constitutes a rigorous classification.

This paper does not study the concrete expressions of various incidence degrees but rather the perfect correlation essence of such incidence degrees, that is, sufficient and necessary conditions.

For any order difference incidence degree, the similarity incidence degree, the direct proportion incidence degree, the parallel incidence degree and the nearness incidence degree, it is proven that the perfect correlation relation is an equivalence relation. The set composed of all sequences Y that are equivalent to sequences X is studied, that is, the equivalence class of X. The structure and mutual relations of these equivalence classes are discussed, and the topological homeomorphism concept of incidence degree is introduced. The conclusion is obtained that the equivalence classes of the two incidence degrees must be the same when the topological homeomorphism is obtained.

In this paper, only the perfect correlation relation of any order difference incidence degree, the similarity incidence degree, the direct proportion incidence degree, the parallel incidence degree and the nearness incidence degree are studied as equivalent relations.

Not only are the research results of several incidence degrees involved in this paper original but also many other effective incidence degrees have not done this basic research, so this paper opens up a research direction with theoretical significance.

With the use of the grey incidence analysis (GIA), indicators such as the absolute degree of grey incidence (ε_ij), relative degree of grey incidence (r_ij) or synthetic degree of grey incidence (ρ_ij) are calculated. However, it seems that some assumptions made to calculate them are arguable, which may also have a material impact on the reliability of test results. In this paper, the authors analyse one of the indicators of the GIA, namely the relative degree of grey incidence. The aim of the article was to verify the hypothesis: in determining the relative degree of grey incidence, the method of standardisation of elements in a series significantly affects the test results.

To achieve the purpose of the article, the authors used the numerical simulation method and the logical analysis method (in order to draw conclusions from our tests).

It turned out that the applied method of standardising elements in series when calculating the relative degree of grey incidence significantly affects the test results. Moreover, the manner of standardisation used in the original method (which involves dividing all elements by the first element) is not the best. Much more reliable results are obtained by a standardisation that involves dividing all elements by their arithmetic mean.

Limitations of the conducted evaluation involve in particular the limited scope of inference. This is since the obtained results referred to only one of the indicators classified into the GIA.

In this article, the authors have evaluated the model of GIA in which the relative degree of grey incidence is determined. As a result of the research, the authors have proposed a recommendation regarding a change in the method of standardising variables, which will contribute to obtaining more reliable results in relational tests using the grey system theory.

This study aims to simultaneously and stochastically maximize autonomous flight performance of a variable wing incidence angle having an unmanned aerial vehicle (UAV) and its flight control system (FCS) design.

A small UAV is produced in Iskenderun Technical University Drone Laboratory. Its wing incidence angle is able to change before UAV flight. FCS parameters and wing incidence angle are simultaneously and stochastically designed to maximize autonomous flight performance using an optimization method named simultaneous perturbation stochastic approximation. Obtained results are also benefitted during UAV flight simulations.

Applying simultaneous and stochastic design approach for a UAV having passively morphing wing incidence angle and its flight control system, autonomous flight performance is maximized.

Permission of the Directorate General of Civil Aviation in Turkish Republic is necessary for real-time flights.

Simultaneous stochastic variable wing incidence angle having UAV and its flight control system design approach is so useful for maximizing UAV autonomous flight performance.

Simultaneous stochastic variable wing incidence angle having UAV and its flight control system design methodology succeeds confidence, excellent autonomous performance index and practical service interests of UAV users.

Creating an innovative method to recover autonomous flight performance of a UAV and generating an innovative procedure carrying out simultaneous stochastic variable wing incidence angle having UAV and its flight control system design idea.

The brain drain challenge has become a cankerworm confronting not only the public health-care sector in Nigeria but almost all sectors of the national economy. This study aims to explore the push factors responsible for brain drain incidence among the migrated, JAPA, physicians to other global work environments. The study investigates the mediating role of capacity development among migrated, JAPA, physicians between the health-care infrastructural deficit and brain drain syndrome.

This study used a survey cross-sectional research design to examine the 214 migrated physicians in four notable perceived countries (UK, USA, Canada and Australia). The study used a probability sampling strategy to survey a self-administered online research instrument. The study adapted a battery of scales from several authors to measure the relevant constructs of this study. Hierarchical multiple regression was used to examine factors that provoke the incidence of brain drain burden among the JAPA Physicians. While Macro Hayes Process was used to investigate the mediating role of capacity development among migrated physicians.

The study revealed from the “JAPA” physicians that working conditions are turbulent and utterly poor which led to the incidence of brain drain. The study indicated that poor remuneration and benefits are the predominant reason for JAPA physicians to European countries and USA/UK. The findings of the study demonstrated that restricted opportunities and poor standard of living in the country were additional factors responsible for the brain drain of Nigerian physicians to other international countries. The outcome of the study also illustrated that inadequate infrastructure and facilities are the dominant variables that pushed physicians to foreign nations. It was revealed that there is a toxic mix of several issues that led to a brain drain albatross among the migrated physicians from Nigeria. The last part of the study indicated that physicians’ capacity development was a game changer that would discourage brain drain incidence and establish motivation for working in Nigeria's public health-care sector.

The study has given a direction for providing succinct solutions to the cankerworm of brain drain that has depleted the Nigerian public health-care industry. It has proffered a possible trajectory that will reverse the JAPA syndrome among the professional health-care workforce. This will not only benefit the public health-care personnel but also be significant for all the human capital across all the sectors of the national economy of Nigeria.

This study assesses the relevance of foreign aid to the incidence of capital flight and unemployment in 20 countries in sub-Saharan Africa.

The study is for the period 1996–2018, and the empirical evidence is based on interactive quantile regressions in order to assess the nexuses throughout the conditional distribution of the unemployment outcome variable.

From the findings, capital flight has a positive unconditional incidence on unemployment, while foreign aid dampens the underlying positive unconditional nexus. Moreover, in order for the positive incidence of capital flight to be completely dampened, foreign aid thresholds of 2.230 and 3.964 (% of GDP) are needed at the 10th and 25th quantiles, respectively, of the conditional distribution of unemployment. It follows that the relevance of foreign aid in crowding out the unfavourable incidence of capital flight on unemployment is significantly apparent only in the lowest quantiles or countries with below-median levels of unemployment. The policy implications are discussed.

The study complements the extant literature by assessing the importance of development assistance in how capital flight affects unemployment in sub-Saharan Africa.

This systematic review paper aims to investigate seasonal ambient change’s impact on the incidence of falls among older adults.

The population, exposure, outcome (PEO) structured framework was used to frame the research question prior to using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis framework. Three databases were searched, and a total of 12 studies were found for inclusion, and quality appraisal was carried out. Data extraction was performed, and narrative analysis was carried out.

Of the 12 studies, 2 found no link between seasonality and fall incidence. One study found fall rates increased during warmer months, and 9 of the 12 studies found that winter months and their associated seasonal changes led to an increase in the incidence in falls. The overall result was that cooler temperatures typically seen during winter months carried an increased risk of falling for older adults.

Additional research is needed, most likely examining the climate one lives in. However, the findings are relevant and can be used to inform health-care providers and older adults of the increased risk of falling during the winter.

This paper aims to study the impact of pyro-electricity, moisture and temperature diffusivity on the energy distribution of plane waves at the free surface of an orthotropic piezo-hygro-thermo-elastic medium.

This study presents the novel creation of governing equations for an anisotropic piezothermoelastic medium with moisture impact, which is a significant contribution of this paper.

In addition to providing numerical data for the amplitude ratios and energy ratios of reflected waves, this study identifies five different kinds of coupled reflected plane waves, namely, quasi-longitudinal P wave, quasi-thermal wave, quasi-transverse wave, quasi-moisture wave and electric potential wave.

The graphical analysis examines the impact of various factors, such as the angle of incidence, moisture and temperature diffusivity, pyro-electricity and frequency, on energy distribution.

This paper's results significantly impact the development of more efficient piezoelectric materials and their applications in geophysics.

The authors of the submitted document initiated and produced it collectively, with equal contributions from all members.

The purpose of the current manuscript is to investigate the reflection of plane waves in a rotating, two-dimensional homogeneous, initially stressed, nonlocal orthotropic thermoelastic solid half-space based on dual-phase-lag model.

The reflection phenomenon has been utilized to study the effects of initial stress, rotation and nonlocal parameter on the amplitude ratios. During the reflection phenomenon three coupled waves, namely quasi displacement primary wave (qP), quasi thermal wave (qT) and quasi displacement secondary wave (qSV) have been observed in the medium, propagating with distinct velocities. After imposing the suitable boundary conditions, amplitude and energy ratios of the reflected waves are obtained in explicit form.

With the support of MATLAB programming, the amplitude ratios and energy ratios are plotted graphically to display the effects of rotation, initial stress and nonlocal parameters. Moreover, the impact of anisotropy and phase lags is also observed on the reflection coefficients of the propagating waves.

In the current work, we have considered rotation and nonlocality parameters in an initially stressed orthotropic thermoelastic half-space, which is lacking in the published literature in this field. The introduction of these parameters in a nonlocal orthotropic thermoelastic medium provides a more realistic model for these studies. The present work is valuable for the analysis of orthotropic thermoelastic problems involving rotation, initial stress and nonlocality parameters.

This paper investigates one of the potential costs of rising segregation in American cities by evaluating empirically the extent at which ethnic-based segregation contributes to the onset and the speed of propagation of the COVID-19 pandemic.

Regression analysis based on matched data on early incidence of COVID-19 cases, segregation and covariates. Identification resorts on variations in segregation across MSAs and heterogeneity in the geography and timing of stay-at-home orders.

One cross-MSA standard deviation increase in segregation leads to a significant and robust rise of COVID-19 cases of 8.7 per 100,000 residents across urban counties.

Combines spatial data on COVID-19 cases and segregation; use of a new segregation measure; focus on early incidence of the pandemic and its drivers.