Smooth Regression Model Research Articles

Testing Forecasting Properties of Different Approaches to Interval Forecasting (Using the Example of Inflation in Russia)

The paper contains the main results of the study of the quality of interval forecasts based on quantile regression and smooth quantile regression models relative to interval forecasts based on OLS models for Russian inflation. All models in the work were built from the logic of the possibility of forecasting in real-time, in connection with which the authors used inflation that was not cleared of seasonality in the expression month to the same month of the previous year. For each forecast horizon, the authors developed a separate model from lagged values of inflation and regressors so that the known values of lagged variables were always used on the right side of the equation.The authors tested a wide range of specifications – from very compact autoregressive models with one or two lags to wide ones with three additional regressors in addition to inflation lags. The best quality from the point of view of CRPS (Continuous Ranked Probability Score) metrics typical for such a task were the specifications that included the only additional variable – the USD/RUB exchange rate. As the confidence interval narrowed and at longer horizons, quantile and smooth quantile models became increasingly better relative to OLS models according to the CRPS metric.According to the authors, in the presence of inflation targeting, qualitative inflation forecasts can be used by the Bank of Russia in conducting monetary policy when forecasting future inflation dynamics and stress-testing the Russian economy. In general, this can help increase the economic agents’ confidence in the Bank of Russia within the concept of rational expectations

Association of crown-root ratio and tooth survival in Chinese patients with advanced periodontitis: An 11-year retrospective cohort study

IntroductionPeriodontitis is a chronic multifactorial inflammatory disease which eventually lead to tooth loss (TL). Therefore, a retrospective study was conducted to evaluate the status of tooth survival within 11 years after non-surgical periodontal treatment (NSPT) and to analyze the risk factors especially crown-root ratio (CRR) that affected TL in Chinese with advanced periodontitis. Methods3481 teeth of 131 subjects who underwent NSPT were examined retrospectively within a mean follow-up period of 11.6 years. The association of risk factors including clinical and radiographic parameters with TL was assessed using univariate and multivariate Cox regression analyses. Smooth curve fitting and segmented regression model were conducted to show the nonlinear relationship and the threshold effect between CRR and the risk of TL. Results347 teeth were lost in 97 patients in this study. Male, diabetes mellitus, heavy-smoker, molar, probing depth (PD), attachment loss (AL), bleeding on probing (BOP), tooth mobility, and radiographic bone loss were significantly associated with tooth loss (P < 0.05). A nonlinear relationship between CRR and the risk of TL was found, with different turning point values between molars and non-molars (1.9 vs. 2.76). ConclusionsThe findings based on practice-based clinical and radiographic data do suggest a nonlinear relationship between CRR and the survival of teeth, and provide evidence to help clinicians to determine the prognosis of teeth for patients with advanced periodontitis. Clinical SignificanceBased on clinical and radiographic data, this study provides an individualized basis for clinicians to judge the dental prognosis of patients with advanced periodontitis according to the different tooth sites.

Gender differences in the relationship between the triglyceride-glucose index and serum Klotho concentrations among the middle-aged and elderly: a cross-sectional analysis

BackgroundThe triglyceride-glucose (TyG) index is recognized as a robust indicator for evaluating insulin resistance (IR). Despite the well-documented anti-aging biological functions of Klotho protein, its correlation with the TyG index remains unexplored.MethodsA cross-sectional analysis was conducted involving participants from the National Health and Nutrition Examination Surveys (NHANES) 2007–2016. The TyG index was computed using laboratory data, while serum Klotho concentrations was determined using ELISA kit. After adjusting potential confounding variables, multivariate regression models were employed to evaluate the association between the TyG index and Klotho protein levels among middle-aged and elderly females and males separately. Additionally, smooth curve fitting and segmented regression model were applied to investigate potential threshold effects and identify the inflection point.ResultsA total of 6,573 adults qualified for inclusion, comprising 3,147 (47.88%) males and 3,426 (52.12%) females. Multivariate regression analysis revealed that females with a higher TyG index exhibited significantly lower serum Klotho concentrations (β=-83.41, 95% CI: -124.23 to -42.60, P < 0.0001). This association was not statistically significant in males (β = 15.40, 95% CI: -19.16 to 49.95, P = 0.3827). Subgroup analyses revealed a significant interaction effect by diabetes status in females (P-interaction = 0.0121), where non-diabetic females showed a stronger negative association between TyG index and serum Klotho levels compared to diabetic females. In the female group, when TyG index was divided into quartiles, individuals in the highest quartile of TyG index exhibited reduced levels of Klotho protein (Q4: -88.77 pg/ml) compared to those in the lowest quartile (Q1) after full adjustment (P = 0.0041). Segmented regression analysis indicated a turning point value of 9.4 in females. Notably, a 1-unit increase in TyG index was significantly associated with a decrease in Klotho levels by -111.43 pg/ml (95% CI: -157.34 to -65.52, P < 0.0001) when TyG index was below 9.4, while above this threshold, the association was not significant (Log likelihood ratio test: 0.009).ConclusionsThe findings highlight a non-linear correlation between the TyG index and serum Klotho concentrations among females, indicative of a saturation effect. This relationship was particularly pronounced in non-diabetic women. In contrast, no statistically significant association was observed in male participants.

Behavioral Modeling and Digital Predistortion for Power Amplifier Based on the Sparse Smooth Twin Support Vector Regression Method

In this paper, a sparse smooth twin support vector regression (Sparse‐STSVR) model for power amplifier (PA) behavioral modeling is obtained by pruning the kernel matrix based on Cholesky decomposition. Based on the primal smooth twin support vector regression (STSVR) model, the Nystrom approximate matrix of the kernel matrix is found to replace the original kernel matrix, thus simplifying the Newton iterative parameter extraction process of the primal STSVR model and accelerating the convergence of the algorithm. In addition, the new rank approximation kernel matrix has the characteristic of sparse parameters, which further reduces the computational complexity of the feedforward link of the digital predistorter. The 100 MHz 5G New Radio (NR) signal is used for verify the effect of PA modeling and digital predistortion (DPD) experiment. The results show that the proposed method can improve the normalized mean square error (NMSE) by about 2 ~ 3 dB with fewer coefficients compared with the previously proposed machine learning model, and the predistortion linearization effect improves by nearly 3 dB on the adjacent channel power ratio (ACPR), which achieves a good trade‐off between model performance and computational complexity. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

Exploring non-linear causal nexus between economic growth and energy consumption across various R&D regimes: Cross-country evidence from a PSTR model

PurposeThis study endeavors to elucidate the divergent conclusions encountered in empirical research regarding the interplay of Economic Growth (EG) and Energy Consumption (EC). Design/methodology/approachFor this purpose, we employ the Panel Smooth Threshold Regression (PSTR) model to intricately examine the non-linear impacts of independent variables on EC and EG within a dataset encompassing 46 countries over the period from 1996 to 2021. FindingsThe outcomes of our investigation can be summarized as follows: First, the findings underscore the positive impact of the logarithm of net capital formation on EG. This impact is particularly pronounced at low levels of Research and Development (R&D), gradually waning beyond a certain threshold. Second, the ratio of capital to labor exhibits a negative influence on EC at lower R&D levels. Notably, these detrimental impacts become more pronounced as R&D levels increase. Third, trade openness contributes positively to EG, particularly evident at low R&D levels. However, with increasing R&D levels, the incremental benefits from trade diminish. Finally, our findings lend support to the feedback hypothesis. Nevertheless, the impact of R&D expenditures in countries moderates these positive effects. Practical implicationsPolicymakers should strategically balance resource allocation between capital formation and research endeavors, considering diminishing returns at elevated levels of R&D spending, to ensure sustained EG.

U-SHAPED ASSOCIATION BETWEEN SERUM CALCIUM LEVELS AND 28-DAY MORTALITY IN PATIENTS WITH SEPSIS: A RETROSPECTIVE ANALYSIS OF THE MIMIC-III DATABASE.

Background: Serum calcium levels disorder have been reported to be associated with poor prognosis in different diseases. Studies on the association between serum calcium and outcomes of septic patients remained limited. The aim of this study is to investigate the association between serum calcium and 28-day mortality in septic patients. Method: Patients diagnosed with sepsis in the Medical Information Mart for Intensive Care III database were included. Patients were divided into five groups according to the quintiles of serum calcium levels, and their baseline characteristics were compared. Multivariate Cox regression models were used to assess the association between serum calcium and 28-day mortality. Smooth curve fitting and segmented regression models were used to visualize the association between serum calcium levels and 28-day mortality risk. The 28-day survival probability between five groups was analyzed using Kaplan-Meier curves. Results: A total of 3,016 patients with sepsis were enrolled, and the 28-day mortality rate was 35.64%. After adjusting for confounders, compared with the reference quintile (Q4: 9.00-9.50), the lowest serum calcium level quintile (Q1: 5.70-8.20) was independently associated with an increased risk of 28-day mortality (hazard ratio [HR], 2.12; 95% CI, 1.76-2.56). Smooth spline fitting revealed a U-shaped association between serum calcium and 28-day mortality. When serum calcium was <9.0 mg/dL, 28-day mortality risk increased by 58% per unit decrease in serum calcium (HR, 0.42; 95% CI, 0.37-0.48). When serum calcium was >9.0 mg/dL, the 28-day mortality risk increased by 12% per unit increase in serum calcium (HR, 1.12; 95% CI, 1.04-1.20). Conclusion: A U-shaped association was observed between serum calcium levels and 28-day mortality in septic patients. Lower or higher serum calcium levels were associated with increased risk of 28-day mortality in septic patients.

The effects of plasma to red blood cells transfusion ratio on in-hospital mortality in patients with acute type A aortic dissection.

Blood transfusion is a frequent and necessary practice in acute type A aortic dissection (AAAD) patients, but the effect of plasma/red blood cells (RBCs) ratio on mortality remains unclear. The aim of this study is to investigate the association between plasma/RBCs transfusion ratio and in-hospital mortality in patients with AAAD. Patients were admitted to Xiangya Hospital of Central South University from January 1, 2016 to December 31, 2021. Clinical parameters were recorded. Multivariate Cox regression model was used to analyze the association between transfusion and in-hospital mortality. We used the smooth curve fitting and segmented regression model to assess the threshold effect between plasma/RBCs transfusion ratio and in-hospital mortality in patients with AAAD. The volumes of RBCs [14.00 (10.12-20.50) unit] and plasma [19.25 (14.72-28.15) unit] transfused in non-survivors were significantly higher than in survivors [RBCs: 8.00 (5.50-12.00) unit]; plasma: [10.35 (6.50-15.22) unit]. Multivariate Cox regression analysis showed plasma transfusion was an independent risk factor of in-hospital mortality. Adjusted HR was 1.03 (95% CI: 0.96-1.11) for RBCs transfusion and 1.08 (95% CI: 1.03-1.13) for plasma transfusion. In the spline smoothing plot, mortality risk increased with plasma/RBCs transfusion ratio leveling up to the turning point 1. Optimal plasma/RBCs transfusion ratio with least mortality risk was 1. When the plasma/RBCs ratio was <1 (adjusted HR per 0.1 ratio: 0.28, 95% CI per 0.1 ratio: 0.17-0.45), mortality risk decreased with the increase of ratio. When the plasma/RBCs ratio was 1-1.5 (adjusted HR per 0.1 ratio: 2.73, 95% CI per 0.1 ratio:1.13-6.62), mortality risk increased rapidly with the increase of ratio. When the plasma/RBCs ratio was >1.5 (adjusted HR per 0.1 ratio: 1.09, 95% CI per 0.1 ratio:0.97-1.23), mortality risk tended to reach saturation, and increased non-significantly with the increase of ratio. A 1:1 plasma/RBCs ratio was associated with the lowest mortality in the patients with AAAD. And non-linear relationship existed between plasma/RBCs ratio and mortality.

Revisiting the Environmental Kuznets Curve hypothesis in OECD during 1970–2016: Panel smooth transition regression

The examination of the Environmental Kuznets Curve (EKC) hypothesis is revisited in the OECD countries during 1970–2016. This paper focuses on some OECD countries with a high economic level and a high concentration of air pollution monitoring. In this examination, we propose a Panel smooth transition kink regression (PSTKR) model to examine the inverted U-shaped nexus between economic development and air quality and define the turning point of this relationship. This model allows the slope of the independent variable to be changed after the kink point, leading us to capture the nonlinear relationship between the dependent and independent variables. This study uses the GDP per capita and Sulfur dioxide emissions as economic and development indicators, respectively. Our finding reveals the existence of the EKC hypothesis in the OECD countries. Furthermore, we find the heterogeneous impacts of economic growth on air quality. There is evidence of the positive effects of economic growth on air pollution when the GDP per capita is less than 26,338.84 USD, while it turns out to be harmful when the GDP per capita is more than 26,338.84 USD. In sum, our model confirms the presence of EKC in the OECD countries.

Financial development, foreign trade, regional economic development level and carbon emissions

Drawing on balanced panel data of 30 Chinese provinces in 2000–2020, this paper uses the Panel Smooth Transformation Regression (PSTR) model to explore the impact of financial development and foreign trade on carbon emissions under different regional economic development levels. The empirical results show that: 1) Financial development and foreign trade have a non-linear impact on carbon emissions under different economic development levels; 2) As the level of economic development exceeds the threshold, the positive effect of financial development on carbon emissions will weaken, while the effect of foreign trade on carbon emissions will change from negative to positive; 3) The sub-sample estimates further found that the impact on carbon emissions in southern and northern regions are different. The threshold in the south is lower than that in the north, but all the conversion speed is faster.

Threshold effects of board gender diversity on firm performance: panel smooth transition regression model

PurposeThis study aims to investigate whether threshold effects exist in the relationship between board gender diversity and firm performance.Design/methodology/approachThis study applies the panel smooth threshold regression model (PSTR) to a sample of 284 non-financial French firms listed on Euronext Paris over the period 2009–2017. Firm performance proxies are Tobin’s Q and return on assets (ROA). The board gender diversity is measured by the percentage of women participation in board.FindingsThreshold effects in the relationships between board gender diversity and firm performance measures are found. For Tobin’s Q, the model has one threshold at the 34.17% of women directors’ appointment on boards. Similarly, for ROA, the model has one threshold at the 38.28% of women presence in the board. The results show that above the estimated threshold, women directorship has a positive impact on firm performance. However, below the threshold, there is a neutral relationship. The findings support the critical mass view that a minimum of one third women representation in board is compulsory to achieve the desired effect of gender diversity.Practical implicationsThis study’s finding provides useful insights to managers, investors and policymakers. Managers and investors can identify the adequate board gender diversity levels that enhance firm performance. Policymakers are divided on whether mandatory or voluntary board gender quota should be adopted. This study suggests that a quota of one third can be used in policy implementation.Originality/valueUnlike prior studies that consider the relationship between firm performance and board gender diversity as linear, to the best of the authors’ knowledge, this study is the first to investigate the threshold effects in this relationship using a new econometric approach.

J-shaped relationship between serum zinc levels and the severity of hepatic necro-inflammation in patients with MAFLD

Background and aimsZinc is an essential trace element that plays an important role in maintaining health, and affecting gene expression, signal transduction and regulation of apoptosis. It is uncertain whether serum zinc levels are altered in patients with metabolic dysfunction-associated fatty liver disease (MAFLD). We aimed to investigate the association between serum zinc levels and the severity of hepatic necro-inflammation (HN) in patients with MAFLD. Methods and resultsLiver disease severity was graded histologically using the NAFLD activity score. HN was defined as the sum of ballooning and lobular inflammation. We used a smooth function regression model to analyze the relationship between serum zinc levels and HN. A total of 561 (76.5% men) patients with biopsy-confirmed MAFLD were enrolled. They had a mean age of 41.3 years, and a mean serum zinc level of 17.0 ± 4.1 μmol/L. Compared to those with mild hepatic necro-inflammation (MHN, grades 0–2; n = 286), patients with severe hepatic necro-inflammation (SHN, grades 3–5; n = 275) had lower serum zinc concentrations (16.3 ± 4.2 vs. 17.6 ± 4.0 μmol/L; p < 0.001). However, a threshold saturation effect analysis showed that there was an inflection in serum zinc levels at 24 μmol/L. After adjustment for potential confounders, serum zinc levels <24 μmol/L were inversely associated with SHN (adjusted-odds ratio 0.88, 95%CI 0.83–0.93; p < 0.001), whereas serum zinc levels >24 μmol/L were positively associated with SHN (adjusted-odds ratio 1.42, 95%CI: 1.03–1.97; p = 0.035). ConclusionsThere is a J-shaped relationship between serum zinc levels and the severity of hepatic necro-inflammation in patients with biopsy-proven MAFLD.

The effect of the quality of institutions on the relationship between public health expenditure and the infant mortality rate: evidence from the PVAR (X) and PSTR approaches

Infant mortality is a major health problem in developing countries. It is an important indicator of a country's public health as it goes hand in hand with socio-economic conditions and many others. Public health spending has been committed to reducing this scourge. This has led to the completion of numerous studies which have yielded mixed results. The main objective of this study is to test the effect of public health expenditure (% GDP) on the infant mortality rate, taking into account the role that institutional quality can play. To achieve this, we use two approaches which are the autoregressive vector panel model with exogenous variables (PVAR (X)) and the smooth threshold regression model (PSTR) on annual data covering the period 2002-2016 and covering 37 African countries. Sub-Saharan. Our main results through the PVAR (X) reveal that in the absence of institutional variables, public health expenditure has a negative and significant effect on the infant mortality rate, whereas, in the presence of the various institutional variables, this effect is still negative but is no longer significant. Our results show that the presence of institutions halves the weight of public health expenditure in explaining the infant mortality rate. In addition, our results show through the PSTR that there is a certain level of institutional qualities that these countries must achieve for public health expenditure to positively affect infant mortality rates. These thresholds oscillate for all the institutional variables around 7%. Taking institutional variables into account will help reduce infant mortality in Sub-Saharan African countries.

Research on the Correlation Between WTI Crude Oil Futures Price and European Carbon Futures Price

In recent years, the rapid increase in CO2 concentration has accelerated global warming. As a result, sea levels rise, glaciers melt, extreme weather occurs, and species become extinct. As the world’s largest CO2 emission rights trading market, EU Emissions Trading System (EU-ETS) has reached 1.855 billion tons of quotas by 2019, influencing the development of the global carbon emission market. Crude oil, as one of the major fossil energy sources in the world, its price fluctuation is bound to affect the price of carbon emission rights. Therefore, this paper aims to reveal the correlation between crude oil futures prices and carbon emission rights futures prices by studying the price fluctuation. In this paper, the linkage between West Texas Intermediate (WTI) crude oil futures prices and European carbon futures prices was investigated. In addition, this paper selects continuous data of WTI crude oil futures prices and spot prices with European carbon futures prices from January 8, 2018 to November 27, 2020, and builds a smooth transformation regression (STR) model. The relationship between crude oil futures and carbon futures prices is studied in both forward and reversal linkage through empirical analysis. The results show that crude oil futures prices and carbon futures prices have a mutual effect on each other, and both linear and nonlinear correlations between the two prices exist. Based on the results of this research, some suggestions are provided.

An improved nonlinear smooth twin support vector regression based‐behavioral model for joint compensation of frequency‐dependent transmitter nonlinearities

In this article, an improved nonlinear smooth twin support vector regression (NSTSVR) model is proposed for the modeling and compensating of the transmitter nonlinearities jointly. The proposed model is an improved version of the twin support vector regression (TSVR) model by introducing a smooth function to replace the loss function of TSVR, which can change the dual space solution to the original space solution and speed up the solving solution. In addition, in order to solve the problem of long training time for large sample data in traditional SVR or TSVR model, the new algorithm further adopts the model pruning techniques, such as deleting the kernel matrix and finding sparse diagonal matrices, to reduce the size of the Hessian matrix in the fast Newton iteration process. To verify the performance of the proposed model, two transmitters based on single-device gallium nitride (GaN) PA with IQ imbalance and GaN Doherty PA with modulator imperfections are used for experimental verification and analysis. The experimental results show that the proposed model is superior to the conventional support vector regression and TSVR machine learning models in terms of modeling effect and linearization ability. Furthermore, the proposed model can achieve the improved compensation performance for transmitter impairments compared with some popular Volterra series-based I/Q imbalance models.

Effects of political institutions on the external debt-economic growth nexus in Africa

The main contribution of this study is the determination of an endogenous threshold of institutional quality, beyond which external debt would affect economic growth differently. The focus is on 14 countries of the African Franc zone over the period 1985-2015. Based on the panel Smooth Threshold Regression model, the results reveal that the relationship between external debt and economic growth is based on institutional quality. It is found that the level of indebtedness at which the effect of external debt on economic growth becomes negative is higher in countries with lower levels of corruption and high levels of democracy. This means that poor institutional quality prevents a country from taking full advantage of its credit opportunities. Thus, the more countries become democratic, the more debt helps finance economic growth. These results are robust to sensitivity analysis and Generalized Method of Moments estimation.

Piecewise modeling of the associations between dry period length and milk, fat, and protein yield changes in the subsequent lactation

Our objective was to develop predictive models of 305-d mature-equivalent milk, fat, and protein yields in the subsequent lactation as continuous functions of the number of days dry (DD) in the current lactation. In this retrospective cohort study with field data, we obtained DHIA milk recording lactation records with the last DD in 2014 or 2015. Cows included had DD from 21 to 100 d. After editing, 1,030,141 records from cows in 7,044 herds remained. Three parity groups of adjacent (current, subsequent) lactations were constructed. We conducted all analyses by parity group and yield component. We first applied control models to pre-adjust the yields in the subsequent lactation for potentially confounding effects. Control models included the covariates mature-equivalent yield, days open, somatic cell score at 180 d pregnant, daily yield at 180 d pregnant, and a herd-season random effect, all observed in the current lactation. Days dry was not included. Second, we modeled residuals from control models with smooth piecewise regression models consisting of a simple linear, quadratic, and another simple linear equation depending on DD. Yield deviations were calculated as differences from predicted mature-equivalent yield at 50 DD. For validation, predictions of yield deviations from piecewise models by DD were compared with predictions from local regression for the DHIA field records and yield deviations reported in 38 experimental and field studies found in the literature. Control models reduced the average root mean squared prediction error by approximately 21%. Yield deviations were increasingly more negative for DD shorter than 50 d, indicating lower yields in the subsequent lactation. For short DD, the decrease in 305-d mature-equivalent milk yield ranged from 43 to 53 kg per DD. For mature-equivalent fat and protein yields, decreases were between 1.28 and 1.71 kg per DD, and 1.06 and 1.50 kg per DD, respectively. Yield deviations often were marginally positive and increasing for DD >50, so that the highest yield in the subsequent lactation was predicted for 100 DD. For long DD, the 305-d mature-equivalent milk yield increased at most 4.18 kg per DD. Patterns in deviations for fat and protein yield were similar to those for milk yield deviations. Predictions from piecewise models and local regressions were very similar, which supports the chosen functional form of the piecewise models. Yield deviations from field studies in the literature typically were decreasing when DD were longer, likely because of insufficient control for confounding effects. In conclusion, piecewise models of mature-equivalent milk, fat, and protein yield deviations as continuous functions of DD fit the observed data well and may be useful for decision support on the optimal dry period length for individual cows.

Investigating the direct and indirect linkages between economic development and CO2 emissions: a PSTR analysis.

This paper re-assesses the relationship between economic growth and pollution emissions using a large panel of 146 economies over the period 1990-2016. For our empirical investigation, we rely upon a panel smooth threshold regression (PSTR) model which is a more flexible method for appraising cross-country heterogeneity and time instability. Furthermore, we analyze additional non-linearities in the income-pollution nexus coming from trade openness and financial development channels. Our empirical findings support the existence of environmental Kuznets curve hypothesis for the global sample as well as for income-specific sub-samples. Our sub-sample results show stark differences in the threshold points and the latter increase with the level of economic development. Finally, our investigation of the indirect channels reveals that both trade openness and financial development mediate the adverse effects of income on the pollution emissions of the selected countries. These findings enable us to advance some very important policy implication for the sample economies.

Does ownership structure affect the optimal capital structure? A PSTR model for China

AbstractIn the context of Chinese enterprises' privatization reforms, the relationships between ownership structure and optimal capital structure and between ownership structure and firm performance are worth attention. Using data on listed companies in China, this article uses the panel smooth transfer regression (PSTR) model and multiple regression models to test the nonlinear relationship between capital structure and firm performance. The optimal capital structure is calculated using the partial correlation function of the PSTR model, and the ownership structure–optimal capital structure relationship is analysed. This research found that (a) the effect of the debt‐to‐asset ratio on firm performance shows a nonlinear relationship with sudden changes in characteristics, and a debt‐to‐asset ratio interval exists that can significantly improve firm performance; (b) under the premise of the effect of ownership checks and balances, an increase in ownership concentration can improve the optimal capital structure; thus, enterprises can achieve effective operations with higher debt; (c) the promotion effect of ownership concentration on firm performance varies depending on a company's debt‐to‐asset ratio; and (d) different industries have different optimal capital structures. The raw materials industry has a high optimal capital structure. A series of robustness tests verify the robustness of these conclusions. This research enriches the theoretical interpretation of the optimal capital structure and provides new insights into the relationship between ownership structure and firm performance. The conclusions drawn by this article are helpful to enterprises making corresponding financial decisions and the government in formulating corresponding capital market systems.

Elevated neutrophil-to-lymphocyte ratio but not platelet-to-lymphocyte ratio is associated with generalized aggressive periodontitis in a Chinese population.

Host inflammatory mediators are associated with tissue destruction in patients suffering from generalized aggressive periodontitis (GAgP). However, the correlations between neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) with GAgP remain unknown. Periodontal clinical parameters, including probing depth (PD), bleeding index (BI) and attachment loss (AL) were collected from patients with GAgP and healthy controls. Complete blood cells analyses were obtained; further, NLR and PLR were calculated using neutrophil, platelet, and lymphocyte counts. Smooth curve fitting and segmented regression models were used to analyze the roles and predictive value of NLR with GAgP. In total, 505 participants from a Chinese population were recruited, including 133 healthy controls and 372 patients with GAgP. Periodontal clinical parameters, NLR, and neutrophil counts were significantly higher in patients with GAgP than the control group. Moreover, NLR was positively correlated with the risk and clinical parameters of GAgP. When NLR<3, the risk of GAgP increased by 20.6% for each 0.1 increase in NLR, reaching saturation when NLR>3. An increase in NLR equivalent to 1 was associated with an increase in PD, BI, and AL by 0.41mm, 0.26, and 0.57mm, respectively. Notably, PLR did not show obvious correlations with GAgP. NLR but not PLR may be a potential marker to identify GAgP in healthy individuals, particularly in a Chinese population.

Re-Examination of the Relationship between Agricultural Economic Growth and Non-Point Source Pollution in China: Evidence from the Threshold Model of Financial Development

The coordinated development of agricultural economic growth and non-point source (NPS) pollution is an important task in enhancing pollution prevention. Significantly, agricultural economic growth and NPS pollution are interrelated, and their mechanism will be affected by financial development. For this reason, the current study established a panel smooth transformation regression (PSTR) model to reveal the mechanical evolution under different financial development levels. It was found that the impact of agricultural economic growth on NPS pollution was significantly positive in the low level of financial development, which is manifested as an “intensification effect”. Fortunately, when the level of financial development reaches the medium and high thresholds, agricultural economic growth will inhibit agricultural NPS pollution. At the same time it was also found that the impact of agricultural economic growth on NPS pollution is manifested as an “inhibition effect” at the overall level, but presenting significant structural differences. Specifically, the impact on the eastern and central regions of China is manifested as an “inhibition effect”, whereas the impact in the western region of China is characterized as an “intensification effect”. Finally, the elasticity analysis showed that the influence of financial development on agricultural NPS pollution was significantly positive, and that its intensification effect is ubiquitous.