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Dental defects are relatively common in long-distance pipeline engineering and can lead to permanent plastic deformation of the pipeline, compromising its structural integrity. To clarify the evolution process of the dented pipelines in engineering practice, this paper puts forward the method of combining the whole and local calculation to analyze the mechanical behavior of pipeline indentations. Based on the combination of whole and local method, the influence of concentration, bending and internal pressure load on the indentation deformation of long-distance oil and gas pipelines under typical scenarios is explored. The research found that the simulated values of indentation depth largely coincided with the measured values. The Mises stress, equivalent plastic strain, and indentation depth reached their maximum values at the contact edges between the pipeline and the supports, making the contact edge between the pipeline and the support the most unfavorable position. In the significance analysis of loads, it is found that the stress change of the pipeline was significant under concentrated loads. As the internal pressure gradually increased, the pipeline stress exhibited a trend of first decreasing and then increasing. When the internal pressure load is 4 MPa, the Mises stress reached its minimum value. During the service stage of the pipeline, low-load conditions can lead to the elastic recovery of indentation deformation in the pipeline, but high-load conditions will exacerbate the indentation deformation, which is detrimental to the continued service of the pipeline. In this study, the mechanical analysis of long-distance oil and gas pipeline is carried out by combining the whole and local, which provides a new technical idea and guarantee for the development of long-distance oil and gas pipeline mechanical analysis industry. [ABSTRACT FROM AUTHOR]

Background: Chronic low-grade inflammation is recognized as a significant factor in various health outcomes, including the development and progression of breast cancer. The Systemic Immune-Inflammation Index (SII), a novel marker derived from routine blood counts, has been suggested as a predictor of all-cause mortality and cardiovascular mortality. However, its predictive value in a nationwide representative population, particularly for breast cancer incidence and mortality, is not well-established. Methods: This study aimed to assess the association of SII and the risk of breast cancer incidence and all-cause mortality in breast cancer patients within the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2018. SII was calculated from complete blood count parameters. We used multifactor regression models to examine the associations between SII and the outcomes of interest. Results: A total of 21,058 female participants were included in the study, of which 557 (2.7%) were identified as having breast cancer. After adjusting for multiple potential confounders, the relationship between SII and the incidence of breast cancer revealed an inverse L-shaped association. The optimal inflection point for SII/100 was determined to be 5.09. Below this threshold, there was a significant increase in the risk of breast cancer (OR=1.05, 95% CI: 1.02-1.09). Within the breast cancer population, SII exhibited a J-shaped relationship with all-cause mortality. The optimal inflection point for SII/100 in this context was 5.22, and above this threshold, there was a marked escalation in all-cause mortality (HR=1.09, 95% CI: 1.04-1.14). Conclusion: The SII, as a novel inflammatory composite index, is significantly associated with the risk of breast cancer incidence and all-cause mortality in breast cancer patients. These findings highlight the importance of monitoring systemic inflammation and suggest that SII could serve as a valuable prognostic tool. [ABSTRACT FROM AUTHOR]

Purpose: NHHR, the ratio of non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol, is a novel lipid marker associated with the risk of heart diseases and various health conditions. However, there is limited evidence regarding the relationship between NHHR and the onset of hypertension and heart diseases. The aim of this study was to investigate the association between NHHR and the new-onset hypertension and heart diseases among the Chinese middle-aged and older general population. Methods: This prospective cohort study utilized data from a nationally representative sample of Chinese residents aged 45 and older, sourced from the China Health and Retirement Longitudinal Study (CHARLS). The primary outcomes of the study were new-onset hypertension and heart diseases. To investigate the relationship between the NHHR and the risk of new-onset hypertension and heart diseases, multivariate logistic regression models and the restricted cubic spline (RCS) method were employed. Additionally, the mediating effects of hypertension on the association between NHHR and heart diseases were assessed using the bootstrap method. Results: A total of 5349 participants were included in the final analysis and three groups of NHHR were identified, including low-stable, medium-stable, and high-stable NHHR. By 2020, 1,631 participants (30.5%) had been newly diagnosed with hypertension, while 1233 (23.1%) developed heart diseases. Compared to those with a low-stable NHHR, individuals in the other two groups showed a significantly increased risk of developing hypertension and heart diseases. The findings remained consistent across various sensitivity analyses. According to the RCS analysis, a partial U-shaped relationship existed between the NHHR and the risk of developing hypertension and heart diseases (P for nonlinear < 0.001). Furthermore, hypertension was found to partially mediate the association between NHHR and heart diseases. Conclusion: The NHHR was closely associated with an increased risk of developing hypertension and heart diseases. In addition, the NHHR partially mediated the development of heart diseases by promoting hypertension progression. In the prevention and treatment of heart diseases, managing both lipid levels and blood pressure is crucial. [ABSTRACT FROM AUTHOR]

The aim of our study is to explore the relationship between remnant cholesterol (RC) levels and visceral adipose tissue (VAT) in the US adult population. This cross-sectional study utilized data from 5301 participants aged 20 to 59 years gathered by the National Health and Nutrition Examination Survey (NHANES). RC was determined by deducting both high-density lipoprotein cholesterol (HDL-c) and low-density lipoprotein cholesterol (LDL-c) from total cholesterol (TC), and VAT was measured using dual-energy X-ray absorptiometry. Visceral obesity is defined as a VAT area ≥ 100 cm 2. With increasing quartiles of RC levels, the prevalence of visceral obesity rises (16.51% vs. 36.11% vs. 55.66% vs. 74.48%, p<0.001). After adjusting for confounders, RC levels positively correlate with visceral obesity risk (OR=1.039, 95% CI 1.031–1.048, p<0.001). Additionally, individuals with low LDL-c/high RC and those with high LDL-c/low RC showed 2.908-fold (95% CI 1.995–4.241) and 1.310-fold (95% CI 1.022–1.680) higher risk of visceral obesity, respectively, compared to those with low LDL-c/low RC. Receiver Operating Characteristic (ROC) and Decision Curve Analysis (DCA) show RC's superior predictive ability over other lipid markers. Subgroup analysis showed that the relationship between RC and visceral obesity was more ronounced in those with cardiovascular disease. Smooth curve fitting indicated a nonlinear relationship between RC levels and VAT area. Our study highlights that elevated levels of RC are associated with adverse accumulation of VAT. However, the causal relationship between RC and visceral obesity requires additional investigation. [ABSTRACT FROM AUTHOR]

In this study, numerical simulations of centrifugal compressors are carried out using ANSYS-CFX software. The focus lies in investigating the impact of the inlet tip-clearance (ITC) on the characteristics of the internal complex flow and the aerodynamic performance of centrifugal compressors. Specifically, the paper mainly emphasizes the influence of ITC on the polytropic efficiency and total pressure ratio of a centrifugal compressor, as well as the variations in velocity and pressure at the blade tip, the spatiotemporal evolution of the tip-leakage vortex (TLV), and fluctuations in pressure and velocity downstream of the passage near the blade surface. Analysis of tip-leakage flow (TLF) and TLV motion patterns at rated operating conditions reveals the spatiotemporal evolution within one revolution. Results from Fast Fourier Transform (FFT) spectrum analysis indicate that the TLV motion pattern may be affected by the ITC size. The fluid flow resistance and backflow in the blade tip region are gradually reduced, the flow field stability is effectively enhanced, and the reflux vortex at the volute outlet is eliminated, thereby the working range of the centrifugal compressor is effectively extended by decreasing the ITC. The aerodynamic performance of the centrifugal compressor is effectively increased in the range of the medium and high flow rates by decreasing ITC. Additionally, it is observed that pressure, velocity, and load in the blade tip region do not exhibit a linear relationship with ITC, resulting in a nonlinear change in aerodynamic performance concerning ITC. Pressure and velocity spectrum analysis suggests that the effect of TLF is stronger at the top of the flow passage compared to the middle. Moreover, with the increase of ITC, the effect of TLF decreases at the middle and top of the pressure side (PS) while increasing at the bottom of PS and the suction side (SS). [ABSTRACT FROM AUTHOR]

Exploring the nonlinear relationship between air pollution and precursor emissions in Qingdao, eastern China is crucial for improving air quality. We simulated 32 emission reduction scenarios based on different volatile organic compound (VOC) and nitrogen oxide (NOx) emission reduction ratios using the Weather Research and Forecasting-Comprehensive Air Quality Model Extensions model. The emission reduction of VOCs was beneficial for reducing fine particulate matter (PM2.5) concentration in January and ozone (O3) concentration in June. However, NOx must be reduced by at least 48% and 70% to decrease PM2.5 and O3 concentrations, respectively, when VOCs are not reduced. The responses of PM2.5 and O3 concentrations to emission reductions from different sources were also evaluated. The reduction in VOC emissions from different sources decreased the PM2.5 concentration in January, and O3 concertation in June, while NOx reduction resulted in an increase. Controlling VOC emissions from industry has a positive effect on improving local PM2.5 and O3, while the emission reductions of NOx from transportation and industry are not conducive to reducing PM2.5 and O3 concentrations. The synergistic emission reduction pathways for NOx and VOCs during PM2.5 and O3 combined pollution were also analyzed. The VOC and NOx emission reductions were beneficial for reducing the comprehensive Air Quality Index (sAQI) values. When the NOx emission reduction was large, the sAQI improvement gradually exceeded that of VOCs. A collaborative optimization path should be adopted that focuses on controlling VOCs first, and further control of combined pollution should depend on the deep reduction of NOx. [ABSTRACT FROM AUTHOR]

We extend the growth at risk (GaR) of Adrian et al. (2019) by considering the nonlinear nexus between macro-financial environment indexes and economic growth. In this extension, we use the threshold quantile regression model to investigate the nonlinear impact of five constructed macro-financial environment indexes on economic growth and measure China's GaR from 2021Q1 to 2021Q4. The empirical results show that the threshold effect does exist. Incorporating this nonlinear relationship significantly improves the accuracy of China's GaR measure in terms of smaller prediction loss. [ABSTRACT FROM AUTHOR]

In the age of stock planning, urban vitality is a key indication of a city's health and vitality. Using the central city of Tianjin as an example, the study uses multi-source data, such as Weibo check-ins, points of interest, etc., to quantify urban vitality. The Light GBM-SHAP model is chosen to measure the non-linear effects of each indicator on urban vitality in four dimensions: crowd vitality, economic vitality, facility vitality, and environmental vitality. The study also applies spatial visualization and spatial statistical analysis to analyze the vitality of the central city of Tianjin in terms of time and space scales. The findings indicate that: (1) There is clear temporal and geographical variation in the vitality distribution in Tianjin's core urban region. Over time, spring, particularly April, is marked by a surge of vitality brought on by the tourist season and holiday effects; there is a double-peak time in the morning and evening, and the nighttime vitality is particularly strong; and, in terms of space, urban vitality tends to decline from the Heping District outward. (2) Public facility density, living facility density, and building density are the three indicators that most strongly influence urban vitality; each indication has a negligible impact on the temporal dimension of urban vitality. (3) The indicators in Tianjin's core urban region have a substantial impact on urban vitality. Their threshold effect and non-linear influence are evident, and managing the indicators within a suitable range may effectively promote urban vitality. The study's findings might serve as a foundation for Tianjin's core city's urban planning and design. [ABSTRACT FROM AUTHOR]

Patients with atrial fibrillation (AF) are linked to an increased risk of cognitive dysfunction, and serum uric acid levels play an important factor in cognitive dysfunction. However, the optimal serum uric acid level in patients with AF remains unclear. Therefore, we aimed to explore the relationship between serum uric acid and cognitive dysfunction. 583 patients were conducted in the Affiliated Hospital of Jining Medical University. Cognitive dysfunction was assessed by the Montreal Cognitive Assessment (MoCA). The relationship between serum uric acid levels and the risk of cognitive dysfunction in patients with AF was analyzed using the smoothing spline fitting model and threshold analysis. The average serum uric acid level was (383.26 ± 110.11) μmol/L, and the incidence of cognitive dysfunction was 79.76%. There was a non‐linear relationship between serum uric acid levels and the risk of cognitive dysfunction in patients with AF, and the inflection point was 352 μmol/L. At the left of the inflection point, the relationship was significant (OR = 1.02, 95% CI = 1.00–1.04). At the right of the inflection point, there was no statistical difference (p = 0.101). When serum uric acid levels are less than 352 μmol/L, the risk of cognitive dysfunction increases by 2% for each unit increase in serum uric acid levels in patients with AF. The study provides evidence for the treatment of serum uric acid levels in patients with AF. [ABSTRACT FROM AUTHOR]

Studies on the relationship between serum sex hormone-binding globulin (SHBG) levels and chronic kidney disease (CKD) remain limited and inconclusive. Therefore, this study aims to evaluate the effects of SHBG on CKD in a nationally representative population. We included a total of 7713 adults from the National Health and Nutrition Examination Survey (NHANES) conducted between 2013 and 2016. Multivariate logistic regression models were utilized to evaluate the association between SHBG levels and CKD, and odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. Additionally, we employed a restricted cubic-spline regression model to explore potential dose-response associations. Among the participants, 4030 (52.2%) were women, and CKD was observed in 13.50% (1043/7713). After adjusting for various variables, SHBG levels were found to be associated with the risk of CKD (OR: 1.24; 95% CI: 1.11–1.38), indicating a 24% higher risk of CKD for SHBG levels (log2-transformed). A comparison between the highest quartile (Q4) and the lowest quartile (Q1) of SHBG levels revealed an OR of 1.51 (95% CI: 1.17–1.95) for CKD prevalence. Notably, while the association between SHBG and the risk of CKD disappeared when SHBG levels were <46.1 nmol/l, it existed when SHBG levels exceeded 46.1 nmol/l. Taken together, these findings indicate nonlinear correlations between serum SHBG levels and CKD, with the inflection point occurring at approximately 46.1 nmol/l, which suggest that SHBG levels could serve as a useful marker for assessing CKD risk, with potential applications in early detection and management strategies. [ABSTRACT FROM AUTHOR]

Remnant cholesterol (RC) is closely related to metabolic diseases. Our study aims to explore the relationship between RC and hyperuricemia. This cross-sectional study included 14 568 adults aged 20 years or older from the National Health and Nutrition Examination Survey (NHANES) conducted between 2007 and 2018 in the United States. RC is calculated by subtracting high-density lipoprotein cholesterol (HDL-c) and low-density lipoprotein cholesterol (LDL-c) from total cholesterol (TC). Hyperuricemia is defined by serum uric acid (SUA) levels≥7 mg/dl in men and≥6 mg/dl in women. The independent association between RC and hyperuricemia was evaluated. As the quartile range of RC levels increases, the prevalence of hyperuricemia also rises (7.84% vs. 13.71% vs. 18.61% vs. 26.24%, p<0.001). After adjusting for confounding factors, the fourth quartile of RC was associated with an increased risk of hyperuricemia compared with the first quartile (OR=2.942, 95% CI 2.473–3.502, p<0.001). Receiver Operating Characteristic (ROC) analysis shows that RC outperforms other single lipid indices in hyperuricemia. Further Restricted Cubic Splines (RCS) analysis suggests a nonlinear relationship between RC levels and hyperuricemia. Elevated RC levels were found to be linked to hyperuricemia. Further studies on RC hold promise for both preventing and addressing hyperuricemia. [ABSTRACT FROM AUTHOR]

Against the background of ecological civilization construction, optimizing the control of territorial spatial zoning has become an important issue in maintaining regional ecological security. Clarifying different ecological processes and mechanisms within and among different ecological functional zones is of great practical significance for formulating refined spatial ecological management strategies. So far, research studies have focused on delineating ecological functional zones and analyzing linear processes and mechanisms within them, with little discussion on the differences in internal mechanisms and nonlinear characteristics of different ecological functional zones. Thus, it is necessary to elucidate key differences in the internal mechanisms and nonlinear threshold effects among different ecological functional zones to provide a scientific basis for establishing a territorial spatial zoning management system. In this study, the Integrated Valuation of Ecosystem Services and Trade-Offs model was used to evaluate ecosystem services in the Pearl River Delta region. Toward this, a self-organizing map was used to identify ecosystem service bundles, and geographically weighted regression and restrictive cubic spline analysis were used to clarify the key differences in trade-off/synergy networks and nonlinear thresholds among different ecosystem service bundles. Based on the results, suggestions for refined zoning and control of ecological spaces in the Pearl River Delta region are proposed. The results showed that: (1) In the Pearl River Delta, five different types of ecosystem service bundles are distributed in a circular pattern in space from the central to the surrounding areas: the urban-ecological, ecological-scarcity, agricultural-ecological, ecological-cooling, and ecological-conservation types. The ecological-conservation type accounted for 45.38% (the largest proportion), ecological-cooling for 32.80%, and ecological-scarcity for 10.73% of ecosystem service bundles; whereas neither the agricultural-ecological nor urban-ecological types accounted for more than 10%. (2) In the trade-off/synergy network of different ecosystem service bundles, the synergistic relationship between carbon storage and urban cooling remained stable, whereas the relationships between other ecosystem services showed significant differences. Among the five bundles, the trade-off/synergy interaction of the urban-ecological type was the strongest, followed by that of the agricultural-ecological and ecologicalconservation types, whereas that of the ecological-cooling and ecological-scarcity types were relatively weak. (3) There were significant differences in the nonlinear threshold effects between the Multiple Ecosystem Services Landscape Index (MESLI) and six identified driving factors in the different ecosystem service bundles. In the ecological conservation and ecological scarcity types, the MESLI exhibited nonlinear relationships with all six factors and clear critical thresholds. The MESLIs of the agricultural ecological and ecological cooling types exhibited nonlinear relationships with elevation, night light, gross domestic product density, and population density, whereas that of the urban ecological type only exhibited nonlinear relationships with elevation and population density. (4) We suggest that decision makers use nonlinear thresholds as references to demarcate key control areas for each ecosystem service bundle, clarify their dominant mechanisms based on trade-off/synergy networks, and develop different control indicators in a targeted manner. In conclusion. this study identified key differences in trade-off/synergy networks and nonlinear threshold effects among different ecosystem service bundles and explored different ecological zoning and control strategies for the Pearl River Delta region, providing a theoretical basis and indicator references for refined management of territorial spaces in urban agglomeration areas. [ABSTRACT FROM AUTHOR]

More efficient use of renewable energy to reduce carbon emission requires a more comprehensive understanding of the impact of renewable energy on carbon emissions. To this end, this work investigates the linear and nonlinear relationship between renewable energy consumption and carbon emissions in 130 countries from the new perspective of resource capital factors (total natural resources rents) and human capital (human capital index). The results are given that from a global perspective, the increase in the proportion of renewable energy consumption can accelerate the reduction of per capita carbon emissions before reaching a particular threshold value of total natural resources rents. When a specific natural threshold value is reached, the increase in the proportion of renewable energy consumption will reduce the rate of per capita carbon emissions. Another interesting finding is that the greater the human factor, the lower the reduction rate of per capita carbon dioxide emissions. To explain the above phenomenon, all countries are divided into four different income levels for further heterogeneity research. When the threshold variables are different, the impact on carbon emissions in various income countries is heterogeneous, which is further analyzed in the article. Furthermore, a meaningful discovery shows that whether the threshold variable is natural or human factor, low-income countries benefit the most from the carbon reduction effect brought by the increase in the proportion of renewable energy consumption, followed by lower-middle income and upper-middle income countries, and the lowest is higher-income countries. [ABSTRACT FROM AUTHOR]

Key message: We propose an improved exponential equation for the nonlinear dependence of cell measurements on the seasonal cell production in conifer wood. These changes shall simplify the model towards ease in understanding, interpretation and analysis. With methodological development, quantitative parameters of wood cellular structure have featured as dendroclimatic indicators in various studies. But to disentangle climatic impacts in different wood anatomical characteristics, relationships between them have to be described quantitatively and extricated. This study investigates exponential description of the non-linear dependences of conifer wood cell measurements on their seasonal production in cambial zone. Improvement to the equation of exponential model was suggested, simplifying the interpretation and analysis and providing biological meaning to all numerical parameters of the model. This new equation was demonstrated for 630 tree rings from 20 to 40-year-old trees of Siberian spruce (Picea obovata Ledeb.) in Siberia, collected at the experimental plantation, as well as for its subsets from plots of various planting density, demonstrating plausible value of the new proposed numerical parameter of model and dependence of the other parameter on the stand density, probably based on the tree height. Limitation for successful fitting of this exponential model was demonstrated, based on representativity of wide and narrow rings within sample; we proposed possible way to overcome it in certain cases. [ABSTRACT FROM AUTHOR]

Abstract In the age of stock planning, urban vitality is a key indication of a city’s health and vitality. Using the central city of Tianjin as an example, the study uses multi-source data, such as Weibo check-ins, points of interest, etc., to quantify urban vitality. The Light GBM-SHAP model is chosen to measure the non-linear effects of each indicator on urban vitality in four dimensions: crowd vitality, economic vitality, facility vitality, and environmental vitality. The study also applies spatial visualization and spatial statistical analysis to analyze the vitality of the central city of Tianjin in terms of time and space scales. The findings indicate that: (1) There is clear temporal and geographical variation in the vitality distribution in Tianjin’s core urban region. Over time, spring, particularly April, is marked by a surge of vitality brought on by the tourist season and holiday effects; there is a double-peak time in the morning and evening, and the nighttime vitality is particularly strong; and, in terms of space, urban vitality tends to decline from the Heping District outward. (2) Public facility density, living facility density, and building density are the three indicators that most strongly influence urban vitality; each indication has a negligible impact on the temporal dimension of urban vitality. (3) The indicators in Tianjin’s core urban region have a substantial impact on urban vitality. Their threshold effect and non-linear influence are evident, and managing the indicators within a suitable range may effectively promote urban vitality. The study’s findings might serve as a foundation for Tianjin’s core city’s urban planning and design.

Abstract To investigate the non-linear relationship between diabetes mellitus (DM) duration and the development of diabetic retinopathy (DR). By investigating the association between these variables, our goal is to contribute to the existing knowledge regarding the impact of DM duration on the development and severity of DR. A retrospective cross-sectional study was conducted on 420 patients in the Department of Endocrinology at Guangdong Provincial People’s Hospital, who had undergone ophthalmic consultations from December 2017 to November 2018. The analysis of DM duration and DR utilized a generalized additive model to identify both linear and non-linear connections. The threshold effect was determined using a two-piece regression model. The study included a total of 420 patients, with a mean age of 58.7 years. Of these, 56.9% (239/420) were male. The prevalence of DR was 38.33% (161/420). After adjusting for confounding factors, a nonlinear relationship between DM duration and DR was observed, with a turning point at 8 years. On the left side of the turning point, the prevalence increased by 24% per 1-year increase in DM duration (OR: 1.24; 95% CI: 1.11–1.38; P

Abstract The paper analyzes the relationship between urbanization rates, the growing reliance on renewable electricity production, and CO2 emissions per capita. It further examines the economic impact of these urbanization and renewable electricity production variables on GDP per capita using threshold regression and annual data from Jordan covering the period from 1990 to 2022. The objective is to determine whether Jordan can reduce CO2 emissions despite high urbanization rates by increasing the share of renewable energy in electricity production. The fundamental assumption is that the relationship between CO2 emissions and urbanization rates varies according to the share of renewable energy production. Results from the estimated threshold regression model indicate a decline in CO2 emissions per capita during the period from 2004 to 2018, when urbanization rates ranged between 0.78 and 0.91. During this time, the compound growth rate of renewable energy share in electricity production was 24% in regime 2 (2004–2018). In contrast, CO2 emissions per capita increased both before and after this period, suggesting a nonlinear relationship between urbanization rates and CO2 emissions. This nonlinearity implies that Jordan can manage the conflicting goals of the Sustainable Development Goals (SDGs)—sustainable urbanization and low CO2 emissions—by enhancing the share of renewables in electricity production. Additionally, the results demonstrate a positive effect of urbanization rates and renewable energy shares on economic growth.

In this study, numerical simulations of centrifugal compressors are carried out using ANSYS-CFX software. The focus lies in investigating the impact of the inlet tip-clearance (ITC) on the characteristics of the internal complex flow and the aerodynamic performance of centrifugal compressors. Specifically, the paper mainly emphasizes the influence of ITC on the polytropic efficiency and total pressure ratio of a centrifugal compressor, as well as the variations in velocity and pressure at the blade tip, the spatiotemporal evolution of the tip-leakage vortex (TLV), and fluctuations in pressure and velocity downstream of the passage near the blade surface. Analysis of tip-leakage flow (TLF) and TLV motion patterns at rated operating conditions reveals the spatiotemporal evolution within one revolution. Results from Fast Fourier Transform (FFT) spectrum analysis indicate that the TLV motion pattern may be affected by the ITC size. The fluid flow resistance and backflow in the blade tip region are gradually reduced, the flow field stability is effectively enhanced, and the reflux vortex at the volute outlet is eliminated, thereby the working range of the centrifugal compressor is effectively extended by decreasing the ITC. The aerodynamic performance of the centrifugal compressor is effectively increased in the range of the medium and high flow rates by decreasing ITC. Additionally, it is observed that pressure, velocity, and load in the blade tip region do not exhibit a linear relationship with ITC, resulting in a nonlinear change in aerodynamic performance concerning ITC. Pressure and velocity spectrum analysis suggests that the effect of TLF is stronger at the top of the flow passage compared to the middle. Moreover, with the increase of ITC, the effect of TLF decreases at the middle and top of the pressure side (PS) while increasing at the bottom of PS and the suction side (SS).

Background While the connection between monounsaturated fatty acid (MUFA) intake and non-alcoholic fatty liver disease (NAFLD) has received attention, research in Chinese populations remains scarce. Objective This study aims to evaluate the association between daily MUFA intake and the prevalence of NAFLD in a Chinese population and to estimate the probable threshold of MUFA intake for NAFLD risk. Methods This case-control study employed data from the Dryad database (https://doi.org/10.5061/dryad.8nn2j46), complying with Dryad's terms of service. We collected data from 534 NAFLD patients and 534 healthy controls who underwent medical tests at the First Hospital of Nanping Affiliated to Fujian Medical University between April 2015 and August 2017. A semi-quantitative food frequency questionnaire (SQFFQ) was used to collect individuals' typical food consumption information, and daily MUFA intake was computed. A thorough analytical technique, including baseline characteristics, multivariate statistics, non-linear relationship analysis, and subgroup research, was applied to study the correlation between daily MUFA intake and NAFLD prevalence. Multiple confounding factors, such as age, sex, lifestyle, and other dietary components, were evaluated to estimate the theoretical threshold of MUFA intake for NAFLD risk. Results In the adjusted model, daily MUFA intake was a significant risk factor for NAFLD (OR=1.04, 95%CI=1.02-1.07, P

Abstract Contradictory to conventional economic theory, which foresees any increase in the size of government as inflationary, this article provides evidence that the reaction of price levels to changes in the size of government is nonlinear. The price levels do not necessarily increase in response to a rise in the size of the government but only up to a certain threshold or optimal level. Accordingly, this paper utilizes the dynamic panel threshold model to examine the threshold effects of government size (measured as government final consumption expenditure as a proportion of GDP) on inflation using a sample of 10 selected MENA countries from 1980 to 2019. The findings of this study stand out in several ways. First, the results support the nonlinear relationship between government size and inflation in the study area. Second, the government size’s estimated threshold level is equivalent to 12.46%. Third, government size negatively impacts inflation in the regime of small governments up to the threshold level. The impact turns positive once the government size goes beyond the threshold level in a regime of large size of government. These findings have ramifications for the conduct of fiscal policy. Policymakers in the MENA region can increase the size of government till it reaches the threshold level without exerting any upward pressure on price levels.

Abstract Purpose Muscle Quality Index (MQI), defined as the muscle strength per unit of muscle mass, is considered an emerging indicator of health and physical function. This study aims to explore the relationship between MQI and the risk of depression among non-elderly US adults. Methods This cross-sectional study collected data from participants aged between 20 and 59 years old, utilizing the National Health and Nutrition Examination Survey (NHANES) from 2011 to 2014. The MQI was calculated by dividing the handgrip strength (HGS, kg) by the arm and appendicular skeletal muscle mass (ASM, kg). Depression assessments were conducted using the Patient Health Questionnaire (PHQ-9). The relationship between MQI and the risk of depression was explored by weighted logistic regression, smooth curve fitting, and subgroup analyses. Results A total of 4773 participants were included in this study. After adjusting for confounding factors, low MQI levels were identified as an independent risk factor for depression (OR = 0.800, 95%CI:0.668–0.957, P = 0.015). Smooth curve fitting analysis indicated a nonlinear relationship. Subgroup analysis did not identify any specific populations. Conclusions Higher MQI levels were closely associated with a lower risk of depression among non-elderly US adults. MQI could enhance our understanding of the link between muscle and depression and might serve as a simple functional measure for evaluating and predicting depression.

Yifei Lu,1,&ast; Minhua Ye,2,&ast; Dehua Ma,2 Yu Chen2 1Department of Cardiology, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Linhai, People’s Republic of China; 2Department of Thoracic Surgery, Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, Linhai, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Yu Chen; Dehua Ma, Email chenyu5835@126.com; madh@enzemed.comObjective: To explore the association between survival status and the number of resected lymph nodes in node-negative esophageal squamous cell carcinoma(ESCC) after surgical treatment.Methods: This was a retrospective observational cohort study and data were obtained from the Surveillance, Epidemiology, and End Results program (SEER) and TaiZhou hospital in China. The data for subjects with negative lymph nodes and no distant metastasis (pN0M0) after post-operative pathology were screened. The nonlinear relationship between resected lymph node number and survival status in node-negative ESCC was conducted using restricted cubic spline regression analysis. The association between the number of resected lymph nodes and survival status in node-negative ESCC was evaluated by Cox proportional hazards regression models. Subgroup analysis based on different subgroups was also performed.Results: A total of 999 subjects were included in the study. Restricted cubic spline regression was used to show a U shaped association between the number of resected lymph nodes and survival status in node-negative ESCC, with low count associated with a decreased survival. To elucidate the association, we adjusted for age, sex, race, T stage, TNM (tumor node metastasis classification), location, grade, chemotherapy, and radiotherapy. As the resected lymph node number increased by one node, the survival status was improved by 2% (Hazard ratio(HR) = 0.98, 95% confidence interval (CI) 0.98– 0.99). Sensitivity analysis indicate that the effect size and direction in different subgroups are consistent, the results is stability in SEER.Conclusion: A low count of resected lymph nodes correlated with reduced survival in patients with ESCC, where resecting 25 to 28 or more nodes is considered optimal. Larger prospective studies are warranted to confirm these findings.Keywords: number of lymph node resection, survival status, cohort study, nonlinear relationship, node-negative esophageal squamous cell carcinoma

Abstract Metabolic dysfunction associated fatty liver disease (MAFLD) is a common cause of liver disease in children and adolescents. The relationship between insulin resistance (IR) and MAFLD in children with short stature remains largely unknown. The present study was to investigate the relationship between the triglyceride–glucose (TyG) index and alanine aminotransferase (ALT) levels in children with short stature. A total of 1754 children with short stature were enrolled. Anthropometric, biochemical and hormonal indexes were collected through physical measurement examinations and laboratory tests. A nonlinear association was found between the TyG index and ALT. The inflection point of the curve was at a TyG index of 8.24. In multivariate piecewise linear regression, only when the TyG index was greater than 8.24 was there a significant positive association between the TyG index and ALT (β 5.75, 95% CI 3.30, 8.19; P < 0.001). However, when the TyG index was less than 8.24, there was no significant association between the TyG index and ALT (β −0.57, 95% CI −1.84, 0.71; P = 0.382). This study demonstrated a nonlinear relationship between TyG index and ALT in children with short stature. This finding suggests that a high TyG index is associated with elevated ALT in children with short stature.

Abstract In the process of penicillin fermentation, there is a strong nonlinear relationship between the input eigenvector and multiple output vectors, which makes the prediction accuracy of the existing model difficult to meet the requirements of chemical production. Therefore, a local selective ensemble learning multi-objective soft sensing modeling strategy is proposed in this study. Firstly, a localization method based on transfer entropy and k-means is proposed to reconstruct the sample set. Then, based on the reconstructed local samples, the local soft sensing model is established by the multi-objective support vector regression method, and the selective ensemble of sub-models and the adaptive calculation of prediction weights are realized. At the same time, to reduce the adverse effects caused by improper selection of model parameters, the sparrow search algorithm is used to realize the tuning of the mentioned model parameters. Finally, the proposed modeling strategy is simulated. The results show that, compared with other methods, the proposed local selective ensemble learning multi-objective soft sensing modeling strategy has better prediction performance.

The calculation method for negative skin friction of a single pile has not been unified yet. To improve the design and calculation level of the single pile under vertical load considering negative skin friction, the threshold limit value of pile skin friction was determined based on the effective stress method. The effects of relative displacement of pile-soil and pile depth on pile skin friction were analyzed, and a nonlinear calculation model for pile skin friction was established. The pile skin friction was divided into elastic and plastic states. In the elastic range, the friction is a quadratic function with the depth of the pile body; while in the plastic range, the friction is distributed linearly along the pile body, and the slope is the product of the effective weight of the soil around the pile and the negative friction coefficient. Consequently, the analytical solution of the pile skin friction for the corresponding pile section was acquired. Based on the theory of pile axial force calculation, a formula for calculating the axial force of a single pile under different distribution forms of pile lateral friction was obtained. The reliability, applicability, and practicality of this model were verified by measured data. Based on the calculated pile shaft axial force, the axial force of single pile with different distributions of skin friction was analyzed. This study has practical significance for fully utilizing the performance of pile foundations and improving the level of pile foundation design.

Abstract Implementing the strongly coupled data assimilation (SCDA) in coupled earth system models remains big challenging, primarily due to accurately estimating the coupled cross background-error covariance. In this work, through simplified two-variable one-dimensional assimilation experiments focusing on the air–sea interactions over the tropical pacific, we aim to clarify that SCDA based on the variance–covariance correlation, such as the ensemble-based SCDA, is limited in handling the inherent nonlinear relations between cross-sphere variables and provides a background matrix containing linear information only. These limitations also lead to the analysis distributions deviating from the truth and miscalculating the strength of rare extreme events. However, free from linear or Gaussian assumptions, the application of the data-driven machine learning (ML) method, such as multilayer perceptron, on SCDA circumvents the expensive matrix operations by avoiding the explicit calculation of background matrix. This strategy presents comprehensively superior performance than the conventional ensemble-based assimilation strategy, particularly in representing the strongly nonlinear relationships between cross-sphere variables and reproducing long-tailed distributions, which help capture the occurrence of small probability events. It is also demonstrated to be cost-effective and has great potential to generate a more accurate initial condition for coupled models, especially in facilitating prediction tasks of the extreme events.

Abstract This study addresses the relationship between platelet count and 30-day in-hospital mortality in End-Stage Kidney Disease (ESRD) patients in the intensive care unit (ICU), a topic with limited existing evidence. Utilizing data from the US eICU-CRD v2.0 database (2014–2015), a retrospective cohort study was conducted involving 3700 ICU ESRD patients. We employed binary logistic regression, smooth curve fitting, and subgroup analyses to explore the association between platelet count and 30-day in-hospital mortality. The 30-day in-hospital mortality rate was 13.27% (491/3700), with a median platelet count of 188 × 109/L. After adjusting for covariates, we observed a relationship between platelet count and 30-day in-hospital mortality (OR = 0.98, 95% CI 0.97, 0.99). Subgroup analyses supported these findings. More importantly, a nonlinear association was detected, with an inflection point at 222 × 109/L. The effect sizes (OR) on the left and right sides of the inflection point were 0.94 (0.92, 0.96) and 1.03 (1.00, 1.05), respectively. The most significant finding of this study is the revelation of a nonlinear relationship between baseline platelet count and 30-day in-hospital mortality in ICU patients with ESRD. This discovery explicitly suggests that when ESRD patients are admitted to the ICU, a platelet level closer to 222 × 10⁹/L may predict a lower 30-day in-hospital mortality risk.

The paper analyzes the relationship between urbanization rates, the growing reliance on renewable electricity production, and CO2 emissions per capita. It further examines the economic impact of these urbanization and renewable electricity production variables on GDP per capita using threshold regression and annual data from Jordan covering the period from 1990 to 2022. The objective is to determine whether Jordan can reduce CO2 emissions despite high urbanization rates by increasing the share of renewable energy in electricity production. The fundamental assumption is that the relationship between CO2 emissions and urbanization rates varies according to the share of renewable energy production. Results from the estimated threshold regression model indicate a decline in CO2 emissions per capita during the period from 2004 to 2018, when urbanization rates ranged between 0.78 and 0.91. During this time, the compound growth rate of renewable energy share in electricity production was 24% in regime 2 (2004–2018). In contrast, CO2 emissions per capita increased both before and after this period, suggesting a nonlinear relationship between urbanization rates and CO2 emissions. This nonlinearity implies that Jordan can manage the conflicting goals of the Sustainable Development Goals (SDGs)—sustainable urbanization and low CO2 emissions—by enhancing the share of renewables in electricity production. Additionally, the results demonstrate a positive effect of urbanization rates and renewable energy shares on economic growth. [ABSTRACT FROM AUTHOR]

The arrangement and design of urban streets have a profound impact on the thermal conditions within cities, including the mitigation of excessive street land surface temperatures (LSTs). However, previous research has mainly addressed the linear relationships between the physical spatial elements of streets and LST. There has been limited exploration of potential nonlinear relationships and the influence of population density variations. This study explores multi-dimensional street composition indicators obtained from street-view imagery and applies generalized additive models (GAMs) and geographically weighted regression (GWR) to evaluate the indicators' impact on LST in areas with various population densities. The results indicate the following: (1) The six indicators—green space index (GSI), tree canopy index (TCI), sky open index (SOI), spatial enclosure index (SEI), road width index (RWI), and street walking index (SWI)—all have significant nonlinear effects on summer daytime LST. (2) Among all categories, the GSI negatively affects LST. Moreover, the TCI's impact on LST shifts from negative to positive as its value increases. The SOI and SWI positively affect LST in all categories. The SEI's effect on LST changes from negative to positive in the total and high-population (HP) categories, and it remains negative in the low-population (LP) category. The RWI positively affects LST in the total category, shifts from negative to positive in the LP category, and remains negative in the HP category. (3) The influence ranking is GSI > SEI > SWI > SOI > TCI > RWI, with GSI being the most significant factor. These findings provide key insights for mitigating street LSTs through design interventions, contributing to sustainable urban development. [ABSTRACT FROM AUTHOR]

The study conducted by Cai et al. examines the relationship between metacognitive strategy use and English achievement among university students in China. Four distinct profiles of strategy use were identified, ranging from low to extremely high. The research suggests a nonlinear relationship between metacognitive strategies and English achievement, with a ceiling effect observed in high and extremely high strategy profiles. The findings offer valuable insights for tailored support to enhance metacognitive strategy use among students at different proficiency levels, contributing to pedagogical practices in the context of L2 acquisition. [Extracted from the article]

The COVID-19 pandemic and similar public health emergencies have significantly impacted global travel patterns. Analyzing the recovery characteristics of subway station-level passenger flow during the pandemic recovery phase can offer unique insights into public transportation operations and guide practical planning efforts. This pioneering study constructs a station-level passenger flow recovery resilience (PFRR) index during the rapid recovery phase using subway AFC system swipe data. Additionally, it develops an analytical framework based on a multiscale geographically weighted regression (MGWR) model, the improved gray wolf optimization with Levy flight (LGWO), and light gradient boosting machine (LightGBM) regression to analyze passenger flow resilience on weekdays and weekends in relation to land use-related built environment types. Finally, SHAP attribution analysis is used to study the nonlinear relationships between built environment variables and PFRR index. The results show significant spatial heterogeneity in the impact of commercial, recreational, and residential land, as well as POI (points of interest) of leisure and shopping on PFRR. On weekdays, the most relevant built environment variables for PFRR are POI of enterprises and shopping numbers. In contrast, the contribution of built environment variables affecting PFRR of weekend is more balanced, reflecting the recovery of non-essential travel on weekends. Most land use-related built environment variables exhibit nonlinear associations with PFRR values. The proposed analytical framework shows significant performance advantages over other baseline models. This study provides unique insights into subway passenger flow characteristics and surrounding land use-related development layouts under the impact of public health emergencies. [ABSTRACT FROM AUTHOR]

When using the Transformer model for wind power prediction, the presence of noise in wind power data and the model's final layer relying solely on a simple linear output reduces the model's ability to capture nonlinear relationships, leading to a decrease in prediction accuracy. To address these issues, this paper proposes an ultrashort-term wind power prediction model based on exponential weighted moving average (EWMA) data processing and Kolmogorov–Arnold Network (KAN)-Transformer. First, multiple variable features are smoothed using EWMA, which suppresses noise while preserving the original data trends. Then, the EWMA-processed data is input into the Encoder and Decoder modules of the Transformer model to extract features. The output from the Decoder layer is then passed through the KAN layer, built using a cubic B-spline function, to enhance the model's ability to capture nonlinear relationships, thereby improving the prediction accuracy of the Transformer model for wind power. Finally, experimental analysis is conducted, and it shows that the proposed model achieves the highest prediction accuracy, with a mean absolute error of 4.38 MW, a root mean squared error of 7.37 MW, and a coefficient of determination of 98.73%. [ABSTRACT FROM AUTHOR]