Search Results (35)

Climate warming leads to earlier onset and shortened duration of the freeze–thaw period in the eastern Tibetan Plateau, which has complex effects on vegetation growth. We assessed the spatiotemporal changes in the freeze–thaw period, evaluated its relationship with Normalized Difference Vegetation Index (NDVI from remotely sensed data), used the Panel Smooth Threshold Regression (PSTR) model to quantify the nonlinear impacts and identify critical thresholds, and applied ridge regression to explore the dominant mechanisms under different climatic conditions. The results showed the following: (1) The duration of the freeze–thaw transition period showed strong latitudinal zonality, with stronger spring disturbances than autumn ones. The trend of soil freeze–thaw status in high-altitude areas is the most significant, with a significant increase in the complete thaw period (CTP) and a significant decrease in the complete freeze period (CFP). (2) The earlier onset of the spring freeze–thaw period (SFTTP) and the CTP benefits vegetation growth in both early and late seasons. The delayed autumn freeze–thaw period (AFTTP) benefits early-season vegetation growth but is less favorable for late-season growth. The delayed CFP is beneficial for vegetation growth throughout the year. (3) The CTP’s boost to NDVI collapses at an onset date of 110 days and duration of 190 days. The AFTTP’s benefit peaks at an onset date of 300 days. (4) Temperature and the CTP are key drivers of NDVI changes, especially in the mid-to-late growing season. Arid areas respond strongly to freeze–thaw disturbances, while moderate precipitation areas are less affected. This study is the first to quantitatively analyze the nonlinear mechanism of the freeze–thaw–vegetation relationship, offering a new theoretical basis. Full article

Under the “dual carbon” targets, the influence of environmental regulation on carbon emissions is critical, and the moderating role of environmental decentralization should not be overlooked. Using provincial panel data from China, this study builds a Panel Smooth Transition Regression Model (PSTR) with environmental decentralization as the threshold variable to examine the nonlinear relationship between environmental regulation and carbon emissions. The study finds that when environmental decentralization is below the threshold, raising the intensity of environmental regulation leads to a significant reduction in carbon emissions; however, once decentralization surpasses the threshold, strengthened environmental regulation may result in a rise in carbon emissions. Three subcategories of decentralization exhibit similar threshold effects, but their direct emission reduction effects are heterogeneous. This research offers empirical evidence supporting the optimization of the distribution of environmental responsibilities across central and local governments, as well as for formulating regionally differentiated emission reduction policies. Full article

Water resources are an important foundation for sustainable socioeconomic development. Revealing water use efficiency, the change in water use trends, and their driving mechanisms is essential for facilitating the scientific and reasonable prediction of water demand, thereby guiding the scientific planning and management of water resources. This study utilizes socioeconomic and water usage data from 65 countries spanning the years 1970 to 2020, employing the panel smooth transfer regression (PSTR) model to analyze the relationship between per capita total water withdrawal and per capita GDP. Additionally, Random Forest (RF) methods and empirical statistical analyses are implemented to identify the driving factors, control variables, and critical thresholds of water use trends in countries with different levels of development. The results show that: (1) there exists a nonlinear relationship between per capita total water withdrawal and per capita GDP on a global scale, with 70% of the countries exhibiting an inverted U-type trend in water usage; (2) the observed decline in per capita total water withdrawal in relation to per capita GDP is primarily driven by technological advancements and the optimization and enhancement of production structure; (3) common characteristics of OECD (Organization for Economic Cooperation and Development) countries that have reached their peak water usage include a service sector contribution to GDP exceeding 60%, urbanization levels at 70%, and per capita GDP surpassing USD 20,000. The observed changes in water use trends and the characteristic indicators associated with peak water usage, under conditions devoid of engineering interventions and resources constraints, can serve as valuable references for medium- and long-term water resources planning and water demand management in developing nations. Full article

Background: In this study, we examined and compared ex vivo mechanical properties of aortic walls in patients with bicuspid (BAV) and tricuspid (TAV) aortic valve aortopathy to investigate if the anatomical peculiarities in the BAV group are related to an increased frailty of the aortic wall and, therefore, if a different surgical cutoff point for ascending aortic replacement could be reasonable in such patients. Methods: Ultimate stress tests were performed on fresh aortic wall specimens harvested during elective aortic surgery in BAV (n. 33) and TAV (n. 77) patients. Three mechanical parameters were evaluated at the failure point, under both longitudinal and circumferential forces: the peak strain (Pstr), peak stress (PS), and maximum elastic modulus (EM). The relationships between the three mechanical parameters and preoperative characteristics were evaluated, with a special focus on evaluating potential risk factors for severely impaired mechanical properties, cumulatively and comparatively (BAV vs. TAV groups). Results: The patient populations were inhomogeneous, as BAV patients reached surgical indication, according to the maximum aortic dilatation, at a younger age (58 ± 15 vs. 64 ± 13; p = 0.0294). The extent of the maximum aortic dilatation was, conversely, similar in the two groups (52 ± 4 vs. 54 ± 7; p = 0.2331), as well as the incidences of different phenotypes of aortic dilatation (with the ascending aorta phenotype being the most frequent in 81% and 66% of the BAV and TAV patients, respectively (p = 0.1134). Cumulatively, the mechanical properties of the aortic wall were influenced mainly by the orientation of the force applied, as both PS and EM were impaired under longitudinal stress. An age of >66 and a maximum dilatation of >52 mm were shown to predict severe Pstr reduction in the overall population. Comparative analysis revealed a trend of increased mechanical properties in the BAV group, regardless of the position, the force orientation, and the phenotype of the aortic dilatation. Conclusions: BAV aortopathy is not correlated with impaired mechanical properties of the aortic wall as such. Different surgical cutoff points for BAV aortopathy, therefore, seem to be unjustified. An age of >66 and a maximum aortic dilatation of >52 mm, however, seem to significantly influence the mechanical properties of the aortic wall in both groups. These findings, therefore, could suggest the need for more accurate monitoring and evaluation in such conditions. Full article

As one of the important driving forces of sustainable development in coastal areas, foreign direct investment (FDI) has provided new ideas for exploring optimal strategies. This analysis explores the linear impact of FDI on sustainable development in coastal areas with 53 cities in China from 2012 to 2020. Accordingly, a dynamic panel smoothed transition regression (PSTR) model is used to analyze the non-linear impact of FDI on sustainable development, with transition mechanisms of industrial structure and technological innovation level. The findings reveal that the non-linear effect of FDI on the sustainable development of coastal areas is obvious. When the coastal area’s industrial structure is more optimized, and the level of technological innovation is higher, the promotion effect of FDI on sustainable development is more obvious. Further, the threshold effect of industrial structure and technological innovation is different. The threshold conversion rate of industrial structure is faster, but the threshold effect of technological innovation is stronger. Regionally, the impact of FDI on the sustainable development of coastal adjacent areas is significant, but not on the sustainable development of inland areas due to the few FDI inflows. This analysis offers guidance for policymakers to further develop the tertiary industry, increase financial investment in innovation in coastal areas and encourage enterprises to improve their independent innovation capacity. Full article

Phyllotreta striolata, the striped flea beetle, is one of the most destructive pests in Brassicaceae plants worldwide. Given the drawbacks associated with long-term use of chemical insecticides, green strategies based on chemical ecology are an effective alternative for beetle control. However, the lack of information on beetle ecology has hindered the development of effective biocontrol strategies. In this report, we identified two odorants, (S)-cis-verbenol and (−)-verbenone, which displayed significant attraction for P. striolata (p < 0.05), indicating their great potential for P. striolata management. Using the Drosophila “empty neuron” system, an antenna-biased odorant receptor, PstrOR17, was identified as responsible for the detection of (−)-verbenone and (S)-cis-verbenol. Furthermore, the interactions between PstrOR17 and (−)-verbenone or (S)-cis-verbenol were predicted via modeling and molecular docking. Finally, we used RNAi to confirm that PstrOR17 is essential for the detection of (−)-verbenone and (S)-cis-verbenol to elicit an attraction effect. Our results not only lay a foundation for the development of new and effective nonchemical insecticide strategies based on (S)-cis-verbenol and (−)-verbenone, but also provide new insight into the molecular basis of odorant recognition in P. striolata. Full article

This work focuses on the extraction and analysis of large-scale data from the Internet, specifically using panel data consisting of 273 prefecture-level cities spanning the period from 2011 to 2021. The data are processed using both the panel fixed-effect model and the panel smooth transformation model (PSTR). This study examines the relationship between public environmental concern and urban air pollution, as well as the impact of various city area divisions on public environmental concern and urban ambient air pollution. The regression analysis reveals several key findings: (1) It is observed that the impact of public participation in environmental pollution control on suppressing air pollution exhibits a lag of approximately three periods. This implies that it takes some time for the power of public participation to manifest its effect in reducing air pollution. (2) The study finds that urban public environmental concern, as measured by the Baidu Index, has a suppressive effect on air pollution once it surpasses a threshold value of 20,455.36. (3) This effect is found to be strengthened as the level of public concern increases. Lastly, it is noted that public environmental concern exhibits regional heterogeneity, which can be attributed to factors such as economic development and scientific and technological advancements. These factors influence the level of public environmental concern in different regions. The findings may be succinctly summarized as follows: geographical variations in public environmental concern can be attributed to the impact of economic growth and advancements in science and technology. Regional variability may arise from several sources, including economic growth, scientific and technical advancements, and other influences, all of which impact public environmental concerns. Full article

Environmental regulation (ER) is a crucial tool used by governments to intervene in the environmental practices of enterprises, and it is recognized as a significant avenue to impact industrial ecological efficiency (IEE). This study uses the superefficiency SBM model to determine provincial IEE scores. Then, a panel smooth transition regression (PSTR) model is used to explore the effects of ER on IEE transition at different stages of economic growth. The main findings are as follows: Firstly, China’s IEE showed an overall upward trend, with small increments over the past two decades. Regions with higher IEE were mainly located in the east, while those with lower IEE were mostly in the less economically developed west. Secondly, the PSTR model revealed that ER had varying impacts on IEE at different stages of economic growth. ER positively influenced IEE in the early stages of economic growth. However, after surpassing the threshold of economic growth, ER began to contribute to reducing IEE scores. In addition to these findings, this study proposes a series of policy recommendations to strengthen IEE. Full article

Tandem repeats in proteins are patterns of residues repeated directly adjacent to each other. The evolution of these repeats can be assessed by using groups of homologous sequences, which can help pointing to events of unit duplication or deletion. High pressure in a protein family for variation of a given type of repeat might point to their function. Here, we propose the analysis of protein families to calculate protein short tandem repeats (pSTRs) in each protein sequence and assess their variability within the family in terms of number of units. To facilitate this analysis, we developed the pSTR tool, a method to analyze the evolution of protein short tandem repeats in a given protein family by pairwise comparisons between evolutionarily related protein sequences. We evaluated pSTR unit number variation in protein families of 12 complete metazoan proteomes. We hypothesize that families with more dynamic ensembles of repeats could reflect particular roles of these repeats in processes that require more adaptability. Full article

This paper analyzes the linear and non-linear relationship between non-performing loans and bank profitability measured by the Net Interest Margin for a sample of 74 Middle Eastern and North African banks over the period of 2005–2020. We used the System Generalized Method of Moments (SGMM) as a linear approach and the Panel Smooth Transition Regression (PSTR) model as a non-linear approach. The empirical results of the SGMM approach indicated that the ratio of NPLs negatively affects bank profitability. The findings of the non-linear relationship based on the PSTR model confirmed the existence of a threshold effect. We found that below the threshold of 4.42%, the effect of NPLs is negative but not significant, while after surpassing this threshold, the effect becomes negative and significant. As for bank specifics, we revealed that bank size is positively and significantly associated with bank profitability. For industry factors, we found that more bank concentration decreases bank profitability. Regarding the financial environment, we concluded that the global financial crisis exerted a negative impact on bank profitability. Moreover, we revealed a positive and significant impact of GDP on bank profitability as well as a negative impact of inflation on bank profitability. This study has some limitations regarding the social, economic, and financial differences of the whole sample, which includes banks from the Middle East and others from North Africa. Hence, decomposing the whole sample into two sub-samples could improve the results of this paper. Full article

Forensic DNA profiles are established by multiplex PCR amplification of a set of highly variable short tandem repeat (STR) loci followed by capillary electrophoresis (CE) as a means to assign alleles to PCR products of differential length. Recently, CE analysis of STR amplicons has been supplemented by high-throughput next generation sequencing (NGS) techniques that are able to detect isoalleles bearing sequence polymorphisms and allow for an improved analysis of degraded DNA. Several such assays have been commercialised and validated for forensic applications. However, these systems are cost-effective only when applied to high numbers of samples. We report here an alternative, cost-efficient shallow-sequence output NGS assay called maSTR assay that, in conjunction with a dedicated bioinformatics pipeline called SNiPSTR, can be implemented with standard NGS instrumentation. In a back-to-back comparison with a CE-based, commercial forensic STR kit, we find that for samples with low DNA content, with mixed DNA from different individuals, or containing PCR inhibitors, the maSTR assay performs equally well, and with degraded DNA is superior to CE-based analysis. Thus, the maSTR assay is a simple, robust and cost-efficient NGS-based STR typing method applicable for human identification in forensic and biomedical contexts. Full article

Purpose: This paper empirically investigated the impact of high government debt on economic growth, using a panel data of 12 developing countries in Africa for the period between 1991 and 2020. Furthermore, it sought to find the existence of nonlinearity between government debt and economic growth. The study used a cross-country panel data approach estimated through the panel smooth transition regression to find the threshold effect. The results reveal a threshold of 60.5% of government debt on economic growth, suggesting an inverted U-shaped relationship between government debt and economic growth for the whole sample. After this threshold, additional government debt starts impeding economic growth. The estimated slope parameter of 18.11 supports the smoothness of government debt from a low regime to a high regime of debt. In the lower debt regime, government debt boosts economic growth; however as the level of debt growth surpasses the peak point, economic growth decreases. By implication, policymakers should have strict debt management policies in place to keep the level of government debt low, and be able to respond robustly to an economic shock. While resorting to borrowing to finance public spending, especially during economic crises, may be an imperative, it should be done in a circumspect manner so that the borrowings are kept at tolerable levels and reduced and/or repaid when there is a recovery in the economy. Full article

Since China has put forward the Belt and Road Initiative in 2013, research on the BRI-related countries along the Belt and Road has sprung up. With the advent of the era of carbon peak and carbon neutralization, environmental regulation, as one of the important methods to control carbon emissions, is becoming increasingly prominent. Research on the impact pathway of environmental regulation of countries along the Belt and Road on carbon emissions has important implications for environmental protection and carbon emission reduction. Based on the panel data of 38 countries along the Belt and Road from 2005 to 2018, this research applied linear Tobit model and nonlinear dynamic panel regression model (PSTR) to evaluate the direct impacts on carbon emissions from environmental regulation of countries along the Belt and Road, and to analyze the different impacts of environmental regulation on carbon emissions in terms of technical innovation, industrial structure, and energy intensity. We found that (1) the direct impact of environmental regulation on carbon emissions in the countries along the Belt and Road is positive, with slight differences between the Silk Road Economic Belt and 21st Century Maritime Silk Road (2) when technical innovation is at a low level, environmental regulation promotes carbon emissions, while at a high level, environmental regulation significantly inhibits carbon emissions. (3) When industrial structure is at both a low and high level, environmental regulation inhibits carbon emissions, with a stronger degree of inhibition at a higher level. (4) When energy intensity is at a low level, environmental regulation promotes carbon emissions, while at a high level, environmental regulation inhibits carbon emissions. Accordingly, we suggest that countries along the Belt and Road follow the road of sustainable and low-carbon development, which should further enhance their focus on environment protection, improve their environmental awareness, and take environmental regulation measures rationally to reduce carbon emissions. Meanwhile, relevant adjustments should be done on technical innovation, industrial structure, and energy intensity to achieve carbon emission reduction. Full article

The contradiction between financial development and environmental pollution has become increasingly prominent with economic development. The discovery of the link between financial development and carbon dioxide emissions will aid in the development of solutions to this problem. This paper uses a panel smooth transition regression (PSTR) model to examine the impact of financial development on carbon dioxide emissions using panel data from 28 Chinese provinces from 2005 to 2021. The PSTR model can solve the problem of minimizing potential outliers ignored in the previous literature, while taking into account the endogeneity and heterogeneity of the model and obtaining more reliable results. According to the findings, financial development has a nonlinear effect on carbon dioxide emissions. Furthermore, the positive effect of financial development on carbon dioxide emissions occurs via the scale and structural effects, while the negative effect occurs via the technological effect, which takes up more space. Moreover, financial added value and the financial scale demonstrate a smooth transition, while financial efficiency and foreign direct investment demonstrate a positive influence. Full article

In the context of climate change and high-quality economic growth, the penetration of green innovation is crucial for attaining sustainable economic development. However, the economic growth and carbon emissions nexus has not been fully investigated from the green innovation perspective. Using green innovation as the transition variable, this research employs the panel smooth transition regression model to examine the influence of economic growth on carbon emissions in 30 Chinese provinces over the period 2000–2019. The empirical results indicate that economic growth and carbon emissions have a substantially nonlinear nexus. The promoting influence of economic growth on carbon emissions is offset and even transformed into an inhibiting effect as green innovation degree rises; that is, green innovation alters the economic growth and carbon emissions nexus and plays a considerable part in carbon reduction for China. Additionally, the temporal variations analysis indicates that the positive nexus economic growth effect exerted on carbon emissions decreases gradually as time goes on. In terms of spatial variations, economic growth in the eastern area with higher levels of green innovation exerts the least positive impacts on carbon emissions. The research findings indicate that it is crucial for the Chinese government to lay down effective environmental protection policies to stimulate the enthusiasm of green innovation for social entities. Full article