Relationships between water quality of a long-distance inter-basin water diversion project and air pollution emissions along the canal: Distributions, lag effects, and nonlinear responses.

Understanding and quantifying the influences and contributions of air pollution emissions on water quality variations is critically important for surface water quality protection and management. To address this, we created a five-year daily data matrix of six water quality indicators-permanganate index (CODMn), NH3-N, pH, turbidity, conductivity, and dissolved organic matter (DOM)-and six air pollution indicators-O3, CO, NO2, SO2, 2.5 µm particulate matter (PM2.5), and inhalable particles (PM10)-using data from seven national monitoring stations along the world's longest water-diversion project, the Middle Route of the South-to-North Water Diversion Project in China (MR-SNWD). Multivariate techniques (Mann-Kendall, Spearman's correlation, lag correlation, and Generalized Additive Models [GAMs]) were applied to examine the nonlinear relationships and lag effects of air pollution on water quality. Air pollution and water quality exhibited marked spatial heterogeneity along the MR-SNWD, with all water quality parameters meeting Class I or II national standards and the air pollution indicators exceeding those thresholds. Except for CODMn and DOM, the other water quality and air pollution indicators exhibited significant seasonal differences. Air pollution exhibited significant lag effects on water quality at the northern stations, with NO2, SO2, PM2.5, and PM10 being highly correlated with changes in pH, with an average lag of 17 d. Based on the GAMs, lag effects enhanced the significant nonlinear relationships between air pollution and water quality, increasing the average deviance explained for CODMn, NH3-N, and pH by 93%, 24%, and 41%, respectively. These findings provide a scientific basis for protecting water quality along the long-distance inter-basin water-diversion project under anthropogenic air pollution.

Leveraging Random Effects in Cistrome-Wide Association Studies for Decoding the Genetic Determinants of Prostate Cancer.

Cistrome-wide association studies (CWAS) are pivotal for identifying genetic determinants of diseases by correlating genetically regulated cistrome states with phenotypes. Traditional CWAS typically develops a model based on cistrome and genotype data to associate predicted cistrome states with phenotypes. The random effect cistrome-wide association study (RECWAS), reevaluates the necessity of cistrome state prediction in CWAS. RECWAS utilizes either a linear model or marginal effect for initial feature selection, followed by kernel-based feature aggregation for association testing is introduced. Through simulations and analysis of prostate cancer data, a thorough evaluation of CWAS and RECWAS is conducted. The results suggest that RECWAS offers improved power compared to traditional CWAS, identifying additional genomic regions associated with prostate cancer. CWAS identified 102 significant regions, while RECWAS found 50 additional significant regions compared to CWAS, many of which are validated. Validation encompassed a range of biological evidence, including risk signals from the GWAS catalog, susceptibility genes from the DisGeNET database, and enhancer-domain scores. RECWAS consistently demonstrated improved performance over traditional CWAS in identifying genomic regions associated with prostate cancer. These findings demonstrate the benefits of incorporating kernel methods into CWAS and provide new insights for genetic discovery in complex diseases.

How can green finance effectively promote low-carbon cities? Evidence from 237 cities in China.

Urban areas contribute 85% of China's CO2 emissions. Green finance is an important means to support green energy development and achieve the low-carbon transformation of high-energy-consuming industries. The motivation of this article is to investigate the impact and mechanism of green finance on urban carbon intensity. Most existing literature uses linear models to investigate urban carbon intensity, ignoring the nonlinear relationships between economic variables. The nonparametric models can fill the inherent shortcomings of linear models and effectively simulate the nonlinear nexus between economic variables. Based on the 2011-2021 panel data of 237 cities in China, this paper applies the nonparametric additive model to survey the influence of green finance on urban carbon intensity. Empirical findings exhibit that green finance exerts an inverted U-shaped effect on urban carbon intensity, indicating that the carbon reduction effect of green finance has gradually shifted from inconspicuous in the early stages to prominent in the later stages. Then, from the perspectives of region, city size, and carbon intensity, this article conducts heterogeneity analysis. The results show that the impact of green finance on various carbon intensities all exhibits obvious nonlinear feature. Furthermore, this article employs a mediation effect model to conduct mechanism analysis. The results display that technological progress and industrial structure are two important mediating variables, both of which produce an inverted U-shaped nonlinear impact on urban carbon intensity.

Nonlinear effects of agricultural drought on vegetation productivity in the Yellow River Basin, China.

Agricultural drought (AD) is the main environmental factor affecting vegetation productivity (VP) in the Yellow River Basin (YRB). In recent years, the nonlinear effects of AD on VP in the YRB have attracted much attention. However, it is still unclear whether fluctuating AD will have complex nonlinear effects on VP in the YRB, and there are scant previous studies at large scale on whether there is a threshold for nonlinear effects of AD on VP in the YRB. Therefore, this study used a newly developed agricultural drought index to explore nonlinear effects on VP revealing the nonlinear effects of AD on VP in the YRB. First, we developed a kernel temperature vegetation drought index (kTVDI) based on kernel normalized difference vegetation index (kNDVI) and land surface temperature data to study the spatiotemporal variation of AD in the YRB. Second, we used GPP data from solar-induced chlorophyll fluorescence inversion as an indicator to explore the spatiotemporal variation of VP in the YRB. Finally, we used several statistical indicators and a distributed lag nonlinear model (DLNM) to analyze the nonlinear effect of AD on VP in the YRB. The results showed that AD decreased significantly during 2000-2020, mainly in the southeast of the Loess Plateau, while GPP increased significantly in 80.93 % of the YRB. Meanwhile, moderate and severe AD stress limited VP growth, with the negative effects gradually decreasing, while mild AD had an increasingly positive promoting effect on VP. AD stress resulted in a VP decrease of 69.78 %, and severe AD stress resulted in a VP decrease of 65.52 %, mainly distributed in the northern Loess and Ordos Plateau. AD had significant nonlinear effects on VP. The effects of moderate and severe AD on the sustained nonlinear lag of vegetation were more obvious, and those of moderate and severe AD on the nonlinear lag of VP were the largest when the lag was approximately 1 month and 7 months. The effect of AD on the nonlinear hysteresis of VP in YRB was significantly different under different vegetation types, and forests were more able to withstand longer and more severe droughts than grasslands and croplands. The results of the study provide a theoretical basis for evaluating AD and analyzing the nonlinear impact of AD on VP. This will provide scientific basis for studying the mechanism of drought effect on vegetation in other regions.

The burden of disease and economic growth: The nonlinear effect of population age structure.

This study aims to detangle the impact of health on economic growth as empirical evidence shows a mixture of findings. We use data on the Burden of Disease (BoD) from the Institute of Health Metric Evaluation (IHME) to measure health capital and the economic data of 87 countries from 1990 to 2018. Using panel threshold regression, this study shows that the old dependency ratio is a good measure of the threshold variable, which divides the country groups into four. The BoD, whether it comes from communicable diseases (CD), non-communicable diseases (NCD), or injuries, has a negative impact on economic growth. However, the negative relation is somewhat diminished as the population gets older, demonstrating that the BoD's impact on economic growth is less pronounced for the older population than the younger population.

Influence mechanism of the temporal duration of laser irradiation on photoacoustic technique: a review.

Significance: In the photoacoustic (PA) technique, the laser irradiation in the time domain (i.e., laser pulse duration) governs the characteristics of PA imaging-it plays a crucial role in the optical-acoustic interaction, the generation of PA signals, and the PA imaging performance. Aim: We aim to provide a comprehensive analysis of the impact of laser pulse duration on various aspects of PA imaging, encompassing the signal-to-noise ratio, the spatial resolution of PA imaging, the acoustic frequency spectrum of the acoustic wave, the initiation of specific physical phenomena, and the photothermal-PA (PT-PA) interaction/conversion. Approach: By surveying and reviewing the state-of-the-art investigations, we discuss the effects of laser pulse duration on the generation of PA signals in the context of biomedical PA imaging with respect to the aforementioned aspects. Results: First, we discuss the impact of laser pulse duration on the PA signal amplitude and its correlation with the lateral resolution of PA imaging. Subsequently, the relationship between the axial resolution of PA imaging and the laser pulse duration is analyzed with consideration of the acoustic frequency spectrum. Furthermore, we examine the manipulation of the pulse duration to trigger physical phenomena and its relevant applications. In addition, we elaborate on the tuning of the pulse duration to manipulate the conversion process and ratio from the PT to PA effect. Conclusions: We contribute to the understanding of the physical mechanisms governing pulse-width-dependent PA techniques. By gaining insight into the mechanism behind the influence of the laser pulse, we can trigger the pulse-with-dependent physical phenomena for specific PA applications, enhance PA imaging performance in biomedical imaging scenarios, and modulate PT-PA conversion by tuning the pulse duration precisely.

Carbon emission reduction effect of renewable energy technology innovation: a nonlinear investigation from China's city level.

There has always been controversy over how renewable energy technologies can play a role in reducing carbon emissions. Based on the energy patent data and the economic data of 244 prefecture-level cities from 2007 to 2017 in China, we explore the carbon reduction effect of renewable energy technology and its mechanism from the perspective of energy production, conservation, and management. The two-way fixed effect, instrumental variable, spatial Durbin, and mediation effect models are employed to explore empirical results. We found that (1) the impact of renewable energy technologies on carbon emissions is nonlinear, with an inverted U shape. However, this inverted U-shaped relationship only exists locally in cities and there are uncertainties in adjacent cities, which indicates that cross-regional cooperation in renewable energy technology needs to be improved. (2) The mechanism analysis shows that industrial agglomeration and energy consumption scale are the channels that renewable energy technologies affect carbon emissions. Thus, the implicit carbon emissions generated by industrial agglomeration and the failure to green upgrade energy consumption are the main reasons for the inverted U-shaped relationship. (3) The carbon reduction effect of renewable energy technologies of conservation type takes effect first, and renewable energy technologies of production type do not reduce carbon emissions in non-eastern cities, which means that non-eastern cities are likely to become pollution havens. This study provides evidence for renewable energy technologies to achieve efficient carbon emission reduction and cross-regional technical cooperation.

The nonlinear effects of digital economy on the low-carbon green total factor productivity: Evidence from China.

The production process has undergone significant changes due to the exponential expansion of digital economy, leading to implications for carbon emissions. This study aims to establish the digital economy (DE) index and measures low-carbon green total factor productivity (CTFP) in 30 Chinese provinces between 2011 and 2020. Utilizing the panel fixed-effects model and the spatial model, it examines the nonlinear effects of DE on CTFP and investigates its underlying mechanism. The results reveal the following findings: (1) CTFP has experienced a decline over the past decade, while DE has exhibited significant growth. (2) the contribution of DE to CTFP follows a U-shaped pattern, indicating that CTFP experiences a significant increase once DE reaches a specific turning point. (3) DE affects CTFP by influencing technological innovation progress. (4) The impact of DE on CTFP exhibits regional heterogeneity, with the eastern region experiencing a spatial spillover effect. These rigorous empirical findings provide valuable insights for national policymakers, emphasizing the importance of prioritizing the digital economy and technological innovation when formulating policies to facilitate sustainable economic growth and reduce carbon emissions.

Testing for quadratic impact of industrial robots on environmental performance and reaction to green technology and environmental cost.

Industrial robots play a crucial role in enhancing productivity but their impact on the environment has produced debates. Some researchers have focused on the relation between industrial robots and energy efficiency (or environmental performance), such as Huang et al. (Energy Econ 107:105837, 2022) and Luan et al. (Sustain Prod Consum 30:870-888, 2022). However, their arguments mainly depend on the assumption of linear relationship between the two. This study infers that there is a nonlinear relationship between them from the theories of energy-saving effect, rebound effect, and scale effect. Our research, using data from 74 countries and regions worldwide between 1997 and 2020, reveals an inverted U-shaped relationship between the use of robots and their environmental impact. This means that the environment benefits from robot use up to a certain point, beyond which it starts to incur damage. Two moderating factors, green technology and environmental cost, are analyzed and tested. Our findings suggest that the high-green-tech left shifts and steepens the inverted U-shaped relationship whereas the high cost right shifts and flattens the relationship. This study explains the influencing mechanism of industrial robots on environmental performance by integrating the energy-saving effect, the rebound effect, and the scale effect. Our findings enrich the understanding of the robot-environment nexus and emphasize the importance of government in balancing robot use and environmental protection.

Efficient label-free in vivo photoacoustic imaging of melanoma cells using a condensed NIR-I spectral window.

In this paper, we propose an efficient label-free in vivo photoacoustic (PA) imaging of melanoma using a condensed near infrared-I (NIR-I) supercontinuum light source. Although NIR-II spectral window is advantageous such as longer penetration depth compared to the NIR-I region, supercontinuum light sources emitting both NIR-I and NIR-II region could lower the efficiency to target melanoma because of low optical power density in the melanoma's absorption spectra. To exploit efficient in vivo PA imaging of melanoma, we demonstrated the light source emitting from visible (532-600 nm) to NIR-I (600-1000 nm) by optimizing stimulated Raman scattering induced supercontinuum generation. The melanoma's structure is successfully differentiated from blood vessels at a high pulse energy of 2.5 µJ and a flexible pulse repetition rate (PRR) of 5-50 kHz. The proposed light source with the microjoules energies and tens of kHz of PRR can potentially accelerate clinical trials such as early diagnosis of melanoma.

Exploring the Nonlinear and Threshold Effects of Travel Distance on the Travel Mode Choice across Different Groups: An Empirical Study of Guiyang, China.

Examining how travel distance is associated with travel mode choice is essential for understanding traveler travel patterns and the potential mechanisms of behavioral changes. Although existing studies have explored the effect of travel distance on travel mode choice, most overlook their non-linear relationship and the heterogeneity between groups. In this study, the correlation between travel distance and travel mode choice is explored by applying the random forest model based on resident travel survey data in Guiyang, China. The results show that travel distance is far more important than other determinants for understanding the mechanism of travel mode choice. Travel distance contributes to 42.28% of explanation power for predicting travel mode choice and even 63.24% for walking. Significant nonlinear associations and threshold effects are found between travel distance and travel mode choice, and such nonlinear associations vary significantly across different socioeconomic groups. Policymakers are recommended to understand the group heterogeneity of travel mode choice behavior and to make targeted interventions for different groups with different travel distances. These results can provide beneficial guidance for optimizing the spatial layout of transportation infrastructure and improving the operational efficiency of low-carbon transportation systems.

Digital Economy, Environmental Regulation and Corporate Green Technology Innovation: Evidence from China.

Background: As human beings enter the digital age, the impact of the digital economy on environmental regulation and corporate green technology innovation (CGTI) is expanding. In order to effectively strengthen the efficacy of environmental regulation and improve the green technology innovation ability of corporate, this paper conducts in-depth research on the influence process of the digital economy and environmental regulation on the CGTI. Methods: Based on the mediating variable environmental regulation, this paper explores the influence process of the digital economy on CGTI. Combined with empirical analysis methods such as the fixed-effect model, mediating effect model, spatial model and regression analysis, the authors reveal the influence process of the digital economy on CGTI. Results: The digital economy can directly promote the improvement of the green technology innovation level of CGTI. The digital economy can indirectly affect the CGTI through the mediating variable of environmental regulation, marginal effect and spatial spillover effect. Conclusions: The digital economy and CGTI had a significant spatial correlation among different regions in China. In different regions of China, there are significant differences in the relationship between the digital economy, environmental regulation and CGTI.

An N-Shaped Association between Population Density and Abdominal Obesity.

Abdominal obesity is a threat to public health and healthy cities. Densification may reduce abdominal obesity, but current evidence of the relationship between population density and abdominal obesity is not conclusive. The aim of this study was to disentangle the nonlinear association between population density and abdominal obesity. Data came from the 2004-2015 China Health and Nutrition Survey, which included 36,422 adults aged between 18 and 65 years. Generalized additive models (GAMs) were applied to explore how population density was associated with objectively measured waist circumference (WC) and waist-to-height ratio (WHtR), after controlling for other built environmental attributes, socioeconomic characteristics, and regional and year fixed effects. We found that population density had N-shaped associations with both WC and WHtR, and the two turning points were 12,000 and 50,000 people/km2. In particular, population density was positively correlated with abdominal obesity when it was below 12,000 people/km2. Population density was negatively associated with abdominal obesity when it was between 12,000 and 50,000 people/km2. Population density was also positively related to abdominal obesity when it was greater than 50,000 people/km2. Therefore, densification is not always useful to reduce abdominal obesity. Policy-makers need to pay more attention to local density contexts before adopting densification strategies.

Nonlinear Effects of Pulsed Ion Beam in Ultra-High Resolution Material Removal.

Ion beam sputtering is widely utilized in the area of ultra-high precision fabrication, coating, and discovering the microworld. A pulsed ion beam (PIB) can achieve higher material removal resolution while maintaining traditional ion beam removal performance and macro removal efficiency. In this paper, a 0.01 s pulse width beam is used to sputter atom layer deposition (ALD) coated samples. The nano-scale phenomenon is observed by high-resolution TEM. The results show that when the cumulative sputtering time is less than 1.7 s, the sputtering removal of solid by ion beam is accompanied by a nonlinear effect. Furthermore, the shortest time (0.05 s) and lowest thickness (0.35 nm) necessary to remove a uniform layer of material were established. The definition of its nonlinear effect under a very small removal amount guides industrial ultra-high precision machining. It reveals that PIB not only has high removal resolution on nanoscale, but can also realize high volume removal efficiency and large processing diameter at the same time. These features make PIB promising in the manufacturing of high power/energy laser optics, lithography objective lens, MEMS, and other ultra-high precision elements.

The nonlinear effect of land freight structure on carbon emission intensity: new evidence from road and rail freight in China.

The extensive literature has debated the varying effects of factors on carbon dioxide (CO2) emissions. However, it has paid little attention to land freight structure (FS), including road and rail freight share, which may have different effects on CO2 emissions. Based on the data from 6 eastern provinces in China during 2005-2019, the panel threshold model is used to explore the dynamic influence mechanism of road and rail freight share on transport carbon emission intensity (CE), respectively. The results show different nonlinear relationships between the share of road and rail freight and transport carbon emission intensity. First, the effect of road freight share on carbon emission intensity is all positive across different stages of trade openness, while such effect goes through a process of increasing and then decreasing with the level of trade openness improving. Second, the driving effect of rail freight share on carbon emission intensity exhibits a "negative-positive-negative" feature as the level of trade openness increases. Third, trade openness generates a double-threshold effect on carbon emission intensity. The differentiated nonlinear effects provide significant evidence of the modal shift from road to rail freight, which would be effective to alleviate transport CO2 emissions.

Infant mortality and death clustering at the district level in India: A Bayesian approach.

This study assessed the clustering of and spatial variations in infant mortality between districts in selected states of India using a Bayesian geoadditive model. The study utilized 10 years of retrospective birth history of women from the fourth round of NFHS-4 (2015-16). Findings suggest, except Kerala, there was a significant amount of clustering of infant deaths in families in the selected Indian states. The maximum impact of clustering was observed in Assam, followed by Madhya Pradesh, Bihar, Uttarakhand, and Uttar Pradesh. The estimated residual spatial effect was statistically significant in all the states, with the maximum effect being in Assam and Chhattisgarh. The risk of infant death in Assam was higher in the north-eastern districts and lower in the southern districts of the state. Mother's age at child birth had a nonlinear effect on infant death in all the states, although significant effects were observed only in Bihar and Assam. In both of these states, mother's age at child birth had a "U-shape," showing that the risk of infant death was higher at both earlier and later ages of mother's reproductive period. With the exception of Kerala, all the other selected states in the study had an "elongated L shaped" pattern, showing that in the early ages of the reproductive period, the risk of infant death was very high and that it gradually decreased with age and remained constant thereafter. In Kerala, mother's age at child birth was a straight line, implying that the risk of infant death was constant across the reproductive age of women. In order to keep infant mortality at a low level and to achieve better maternal and child health outcomes, the government needs to target families experiencing multiple infant deaths. In addition, programs must take into consideration the prevailing state-specific spatial heterogeneity in infant deaths and factors like mother's age at child birth.

Observation of Hyperpositive Non-Linear Effect in Asymmetric Organozinc Alkylation in Presence of N-Pyrrolidinyl Norephedrine.

Phenomena related to asymmetric amplification are considered to be key to understanding the emergence of homochirality in life. In asymmetric catalysis, theoretical and experimental models have been studied to understand such chiral amplification, in particular based on non-linear effects. Three decades after the theoretical demonstration that a chiral catalyst, when not enantiopure, could be more enantioselective than its enantiopure counterpart, we show here a new experimental example of nonlinear hyperpositive effect. We report here our investigations in the enantioselective zinc-catalyzed alkylation of benzaldehyde with N-pyrrolidinyl norephedrine as partially resolved chiral ligand, which shows a significant hyperpositive non-linear effect. A study of the underlying mechanism was conducted, which allows us to confirm a mechanism that implies a monomeric and a dimeric complex both catalyzing the reaction at a steady state and giving different enantioselectivities.

Joint Error Estimation and Calibration Method of Memory Nonlinear Mismatch for a Four-Channel 16-Bit TIADC System.

Memory nonlinear error greatly reduces the performance of analog-to-digital converters (ADCs), and this effect is more serious in a time-interleaved analog-to-digital converter (TIADC) system. In this study, the sinusoidal wave fitting method was adopted and a joint error estimation method was proposed to address the memory nonlinear mismatch problem of the current TIADC system. This method divides the nonlinear error estimation method into two steps: the nonlinear mismatch error is coarsely estimated offline using the least squares (LS) method, and then accurately estimated online using the recursive least squares (RLS) method. After the estimation, digital post-compensation method is adopted. The obtained error parameters are used to reconstruct the error and then the reconstructed error is reduced at the output. This study used a four-channel 16-bit TIADC system with an effective number of bits (ENOB) value of 10.06 bits after the introduction of a memory nonlinearity error, which was increased to 15.42 bits after calibration by the joint error estimation method. As a result, the spurious-free dynamic range (SFDR) increased by 36.22 dB. This error estimation method can improve the error estimation accuracy and reduce the hardware complexity of implementing the error estimation system using a field programmable gate array (FPGA).

An Impact Asymmetry Analysis of Small Urban Green Space Attributes to Enhance Visitor Satisfaction.

Urban green spaces have beneficial effects on the health and well-being of citizens. Understanding the factors influencing visitor satisfaction with urban green spaces contributes to making more informed policies. Prior studies on green spaces satisfaction primarily focused on the linear correlation between small urban green space attributes and satisfaction. In this manuscript, we presented a study aimed to (1) identify the attributes of SUGS as frustrators, dissatisfiers, hybrids, satisfiers, and delighters; (2) prioritize attributes for effective satisfaction management; (3) assist managers in drafting guidelines for operational management decisions. We gathered a range of information about the users to nine SUGS in Shanghai, in 2020, via a questionnaire, and we found that safety, noise, and social interaction are improvement priorities. Squares and visitors' behavior should not be ignored in SUGS management. Moreover, managers should carefully monitor SUGS attributes of the social environment to meet users' expectations. The findings of this study have implications for SUGS management and future research.

Detection of weak optical absorption by optical-resolution photoacoustic microscopy.

Optical-resolution photoacoustic microscopy (OR-PAM) is one of the major implementations of photoacoustic (PA) imaging. With tightly focused optical illumination and high-frequency ultrasound detection, OR-PAM provides micrometer-level resolutions as well as high sensitivity to optical absorption contrast. Traditionally, it is assumed that the detected PA signal in OR-PAM has a linear dependence on the target's optical absorption coefficient, which is the basis for quantitative functional and molecular PA imaging. In this paper, we demonstrate that, due to the limited detection bandwidth and detection view, OR-PAM can have a strong nonlinear dependence on the optical absorption, especially for weak optical absorption (<10 cm-1). We have investigated the nonlinear dependence in OR-PAM using numerical simulations, analyzed the underlining mechanisms, proposed potential solutions, and experimentally confirmed the results on phantoms. This work may correct a traditional misunderstanding of the OR-PAM signals and improve quantitative accuracy for functional and molecular applications.