Development and validation of a machine learning-based readmission risk prediction model for non-ST elevation myocardial infarction patients after percutaneous coronary intervention.

To investigate the factors that influence readmissions in patients with acute non-ST elevation myocardial infarction (NSTEMI) after percutaneous coronary intervention (PCI) by using multiple machine learning (ML) methods to establish a predictive model. In this study, 1576 NSTEMI patients who were hospitalized at the Affiliated Hospital of North Sichuan Medical College were selected as the research subjects. They were divided into two groups: the readmitted group and the non-readmitted group. The division was based on whether the patients experienced complications or another incident of myocardial infarction within one year after undergoing PCI. Common variables selected by univariate and multivariate logistic regression, LASSO regression, and random forest were used as independent influencing factors for NSTEMI patients' readmissions after PCI. Six different ML models were constructed using these common variables. The area under the ROC curve, accuracy, sensitivity, and specificity were used to evaluate the performance of the six ML models. Finally, the optimal model was selected, and a nomogram was created to visually represent its clinical effectiveness. Three different methods were used to select seven representative common variables. These variables were then utilized to construct six different ML models, which were subsequently compared. The findings indicated that the LR model exhibited the most optimal performance in terms of AUC, accuracy, sensitivity, and specificity. The outcome, admission mode (walking and non-walking), communication ability, CRP, TC, HDL, and LDL were identified as independent predicators of readmissions in NSTEMI patients after PCI. The prediction model constructed by the LR algorithm was the best. The established column graph model established proved to be effective in identifying high-risk groups with high accuracy and differentiation. It holds a specific predictive value for the occurrence of readmissions after direct PCI in NSTEMI patients.

The environmental impact assessment of China's ecological migration from a social-ecological perspective.

When accounting for the social-ecological impact of an ecological restoration program, both objective environmental contexts and people's subjective perceptions are required. While this kind of environmental impact assessment lacks a comprehensive perspective. We use the difference-in-differences model to evaluate the effect of the greenness of the landscape after ecological migration in the Qilian Mountains in China; and analysis of variance and fixed effects models are used to evaluate the effects of such ecological restoration programs on local people's perceptions. The results show that the ecological migration program in the Qilian Mountains has been successful at not only significantly improving remotely sensed greenness at the landscape scale, but also at enhancing immigrants' environmental perceptions. These findings demonstrate the environmental impacts of ecological migration from a social-ecological perspective, and can provide methodological implications for landscape planning to support a better understanding of ecological restoration programs in the drylands.

Declined terrestrial ecosystem resilience.

Terrestrial ecosystem resilience is crucial for maintaining the structural and functional stability of ecosystems following disturbances. However, changes in resilience over the past few decades and the risk of future resilience loss under ongoing climate change are unclear. Here, we identified resilience trends using two remotely sensed vegetation indices, analyzed the relative importance of potential driving factors to resilience changes, and finally assessed the risk of future resilience loss based on the output data of eight models from CMIP6. The results revealed that more than 60% of the ecosystems experienced a conversion from an increased trend to a declined trend in resilience. Attribution analysis showed that the most important driving factors of declined resilience varied regionally. The declined trends in resilience were associated with increased precipitation variability in the tropics, decreased vegetation cover in arid region, increased temperature variability in temperate regions, and increased average temperature in cold regions. CMIP6 reveals that terrestrial ecosystems under SPP585 are expected to experience more intense declines in resilience than those under SSP126 and SSP245, particularly in cold regions. These results highlight the risk of continued degradation of ecosystem resilience in the future and the urgency of climate mitigation actions.

Interannual precipitation variability dominates the growth of alpine grassland above-ground biomass at high elevations on the Tibetan Plateau.

The impact of global climate change on mountainous regions with significant elevational gaps is complex and often unpredictable. In particular, alpine grassland ecosystems, are experiencing changes in their spatial patterns along elevational gradients, which increases their vulnerability to degradation. Therefore, a more detailed understanding of spatiotemporal changes in alpine grassland productivity along elevational gradients and an elevation-dependent characterization of the effects of climatic variables on grassland productivity dynamics are essential. Thus, we conducted a study in the Tibetan Plateau, where we collected 2251 above-ground biomass (AGB) observations collected from 1986 to 2020. Mean annual temperature (TMP), annual precipitation (PRE), interannual precipitation variability (CVP), and snowmelt (SNMM) were chosen as influential variables. Using the Random Forest algorithm, we generated an AGB raster dataset covering the period 1989-2020 based on earth observation data at 30 m resolution to examine the dynamics of alpine grasslands and their response to climate change with respect to elevation. The results showed that the AGB of alpine grassland on the Tibetan Plateau was 49.17 g/m2. We observed an increasing trend in grassland AGB at high elevations, with a growth rate of about 0.28 g/m2 per year within the interval of 3100-4800 m. However, above the elevation of approximately 4400-4600 m, we observed a decoupling trend between grassland AGB and TMP. Moreover, at most elevations, the proportion of maximum partial correlation coefficients for CVP, PRE, and SNMM surpassed that of TMP. We found the dominant role of precipitation variability on grassland AGB dynamics, with 22.80 % and 18.86 % for CVP+ and CVP-, respectively. The proportion of CVP+ did not vary much at different elevations, whereas the proportion of CVP- increased with elevation, varying between 12.85 and 30.25 %. In the future, precipitation on the Tibetan plateau is expected to increase, potentially reversing its original positive impact.

Differentiated impacts of environmental contexts on residents' environmental attitudes towards ecological restoration programs of China's drylands.

Residents' environmental attitudes (EAs) towards ecological restoration programs are vital for evaluating program effectiveness and promoting environmental management. However, most local studies have neglected the indirect environmental contextual influences on residents' EAs, and have omitted the regional variations in the environmental contextual influences. To investigate the multilevel factors affecting residents' EAs, we conducted a transect survey that included the eastern, middle, and western regions in northern China's drylands, where have experienced ecological restoration. Multilevel linear models (MLMs) were applied to analyse the direct and indirect impacts of environmental contexts and individual characteristics on rural residents' EAs. The results showed the environmental context can indirectly impact EAs by amplifying the influence of individual characteristics such as family structure and income on EAs. The EAs are influenced by different local environmental contexts among the east, middle and west of China's drylands. The humidity attitude was influenced by precipitation only in the highly arid western and middle regions, while precipitation attitude is strongly influenced by land surface temperature and humidity in eastern China's drylands. These findings hold important implications for understanding the cross-scale impact of environmental contexts on EAs in drylands.

The relationship between childhood socioeconomic status and depression level in older adults: the mediating role of adult socioeconomic status and subjective well-being.

BACKGROUND: There is a causal link between childhood socioeconomic status and health status in adulthood and beyond. It's vital to comprehend the relationship between childhood socioeconomic status and mental health among older Chinese individuals from the current generation who have undergone significant social changes in China. This understanding is critical to foster healthy demographic and social development in China. METHODS: Using data from the 2020 China Family Panel Studies, we investigate the relationship between childhood socioeconomic status and depression in older adults. Additionally, we examine the mediating role of adult socioeconomic status and subjective well-being. RESULTS: 1) Childhood socioeconomic status of Chinese older adults differences by region of residence, while depression levels differences by gender, region of residence, and marital status. 2) Adult socioeconomic status mediated the relationship between childhood socioeconomic status and depression in older adults. 3) Adult socioeconomic status and subjective well-being had a chain-mediated role in the relationship between childhood socioeconomic status and depression in older adults. CONCLUSIONS: In terms of childhood socioeconomic status, older adults in urban regions were significantly higher than those in rural regions. As for depression level, female older adults were more depressed than males; married older people have the lowest depression levels, while unmarried and widowed older people have higher depression levels; older adults in rural regions had higher depression levels than those in urban regions. Evidence from our study further suggests that childhood socioeconomic status can suppress the depression level in older adults through adult socioeconomic status; it can also further reduce the depression level in older adults through the chain mediation of adult economic status affecting subjective well-being. As depression is more prevalent among older individuals with a lower childhood socioeconomic status, it is vital to prioritize the extensive impact of childhood socioeconomic status as a distal factor and investigate "upstream" solutions to enhance childhood socioeconomic status and reduce the gap during the early years of life.

Bleak prospects and targeted actions for achieving the Sustainable Development Goals.

At the mid-point to 2030, progress towards achieving the Sustainable Development Goals (SDGs) varies significantly across countries. While the classification of countries can lay the foundation for improving policy efficiency and promoting joint action, bottom-up, SDG data-driven country classifications have largely remained unexplored. Here, we classified 166 countries based on their performances in the 17 SDGs and further used the classification to analyze SDG interactions and compare development aid distributions. The countries were classified into five groups, ranging from "lowest development with good environment" to "high development needing climate action". None of them scored highly in all SDGs, and due to trade-offs related to environment and climate SDGs, none of them can achieve all SDGs eventually. To maximize the potential for achieving the SDGs, all countries need to undergo a sustainable transformation, and prioritizing certain SDGs, such as SDG 9 (industry, innovation and infrastructure), can help countries with lower sustainable development levels achieve more with less. Furthermore, global development aid should be better aligned with country needs, particularly in areas of education, energy, environment, and water supply and sanitation. By better characterizing different countries, this study reveals the bleak prospects of achieving all SDGs and provides valuable insights into more targeted actions for national sustainable development and global collaboration.

Three main dimensions reflected by national SDG performance.

Unraveling the complexity of the 17 interacting sustainable development goals (SDGs) is crucial for their achievement. Empirically revealing the dimensions of the SDGs helps generalize the dominant features of SDGs and better understand their drivers. Here, using a database of 166 countries' progress toward achieving each individual SDG, we found that about 70% of the variability of national SDG performance can be captured by three dimensions: socioeconomic development at the expense of resource and climate, the environment, and development at the expense of equality. Moreover, these dimensions are mainly affected by the economy; as gross domestic product (GDP) per capita increases, the first dimension increases monotonically, the environment dimension decreases and then increases, and the inequality dimension increases and then decreases. Our findings indicate a dim prospect of eventually achieving all SDGs because of the conflicts between economic growth and resource and climate goals under the current development paradigm, highlighting the importance of sustainable transformation.

Difference of high-salinity-induced inhibition of ammonia-oxidising bacteria and nitrite-oxidising bacteria and its applications.

The difficulty in achieving stable partial nitritation (PN) is a challenge that limits the application of mainstream anaerobic ammonium oxidation (anammox). This study proposes high-salinity treatment as a novel strategy for inactivating nitrite-oxidising bacteria (NOB). The study indicated that NOB are more sensitive to high salinity than ammonia-oxidising bacteria (AOB). The inhibitory effect on the nitrifier gradually increased with increasing salinity from 0 to 100 g NaCl/L. After 24 h and 35 g NaCl/L inhibition, the AOB and NOB activities were 36.65% and 7.15% of their original activities, respectively. After one high-salinity treatment, nitrite accumulation rate (NAR) was above 33% during nitrification. Moreover, the sludge characteristics remained almost unchanged after suppression. A novel process for achieving mainstream PN was proposed and evaluated based on the results. An energy consumption analysis showed that mainstream PN/anammox based on the ex situ high-salinity treatment can achieve higher energy self-sufficiency compared with activated sludge.

Natural and socio-environmental factors contribute to the transmissibility of COVID-19: evidence from an improved SEIR model.

COVID-19 has ravaged Brazil, and its spread showed spatial heterogeneity. Changes in the environment have been implicated as potential factors involved in COVID-19 transmission. However, considerable research efforts have not elucidated the risk of environmental factors on COVID-19 transmission from the perspective of infectious disease dynamics. The aim of this study is to model the influence of the environment on COVID-19 transmission and to analyze how the socio-ecological factors affecting the probability of virus transmission in 10 states dramatically shifted during the early stages of the epidemic in Brazil. First, this study used a Pearson correlation to analyze the interconnection between COVID-19 morbidity and socio-ecological factors and identified factors with significant correlations as the dominant factors affecting COVID-19 transmission. Then, the time-lag effect of dominant factors on the morbidity of COVID-19 was investigated by constructing a distributed lag nonlinear model and standard two-stage meta-analytic model, and the results were considered in the improved SEIR model. Lastly, a machine learning method was introduced to explore the nonlinear relationship between the environmental propagation probability and socio-ecological factors. By analyzing the impact of environmental factors on virus transmission, it can be found that population mobility directly caused by human activities had a greater impact on virus transmission than temperature and humidity. The heterogeneity of meteorological factors can be accounted for by the diverse climate patterns in Brazil. The improved SEIR model was adopted to explore the interconnection of COVID-19 transmission and the environment, which revealed a new strategy to probe the causal links between them.

Ecological restoration for sustainable development in China.

Facing the need for transdisciplinary research to promote ecological restoration that achieves both social and ecological benefits, research on past restoration efforts that have directly or indirectly contributed to regional or national sustainable development warrants reassessment. Using China as an example, in this review, we address three basic research questions that can be summarized as follows: ecological restoration-of what, for whom and to what purpose? Accordingly, a 'landscape pattern-ecosystem service-sustainable development' co-evolutionary framework is proposed here to describe landscape-scale ecological restoration and its impact on landscape patterns and ecological processes, ecosystem services for human well-being, sustainable livelihoods and socioeconomic development. From the strategic pattern of national ecological security to the pattern of major projects to protect and restore major national ecosystems, the spatial pattern of China's ecological restoration is more geographically integrative. From major function-oriented zoning to systematic ecological protection and restoration, and for the purpose of achieving the Beautiful China Initiative, there are three stages of ecosystem services management: classification, synergy and integration, respectively. The difference in geographic processes should be considered in the key requirements of ecological restoration for China's five national strategies for regional sustainable-development strategies. Deepening understanding of the relationship between humans and nature in different geographical contexts is a scientific prerequisite to support policymaking related to ecological restoration. To promote greater harmony between humans and nature, we propose four important research directions: (i) understanding coupling processes among key components, (ii) identifying ecosystem service flows, (iii) evaluating social-ecological benefits and (iv) supporting adaptive management for regional sustainable development.

Global assessment of nature's contributions to people.

Synergistically maintain or enhance the numerous beneficial contributions of nature to the quality of human life is an important but challenging question for achieving Sustainable Development Goals. However, the spatiotemporal distributions of global nature's contributions to people (NCPs) and their interactions remain unclear. We built a rapid assessment indicator framework and produced the first spatially explicit assessment of all 18 NCPs at a global scale. The 18 global NCPs in 1992 and 2018 were globally assessed in 15,204 subbasins based on two spatial indicator dimensions, including nature's potential contribution and the actual contribution to people. The results show that most of the high NCP values are highly localized. From 1992 to 2018, 6 regulating NCPs, 3 material NCPs, and 2 nonmaterial NCPs declined; 29 regulating-material NCP combinations (54 in total) dominated 76% of the terrestrial area, and the area with few NCPs accounted for 22%; and synergistic relationships were more common than tradeoff relationships, while the relationships among regulating and material NCPs generally traded-off with each other. Transitional climate areas contained few NCPs and have strong tradeoff relationships. However, the high synergistic relationship among NCPs in low latitudes could be threatened by future climate change. These findings provide a general spatiotemporal understanding of global NCP distributions and can be used to interpret the biogeographic information in a functional way to support regional coordination and achieve landscape multifunctionality for the enhancement of human well-being.

Planning a water-constrained ecological restoration pattern to enhance sustainable landscape management in drylands.

Ecological restoration is an important approach to improving landscape sustainability. However, ecological restoration in drylands is strongly limited by water resources. Therefore, a technical route for ecological restoration in drylands that creates sustainable landscapes based on those water constraints is needed. In this study, we develop a spatially explicit framework named "Constraint-Pattern-Benefit" to plan ecological restoration patterns in Inner Mongolia, China. Based on a prediction of the ecosystem service (ES) increase under limited evapotranspiration as a water constraint, we constructed 5 landscape sustainability-related strategies with 100 ecological restoration scenarios, which considered fragmentation of restoration locations, distance to city, water consumption, and the allocation scale to determine the spatial arrangement of ecological restoration. Results show that the ES increase potential of ecological restoration under water constraints is distributed in the center of Inner Mongolia. The multi-objective scenario simultaneously achieves 59.1% water yield, 74.2% soil conservation, 57.2% sand fixation, and 52.8% carbon sequestration with 50% restored landscape. Considering the indicators of fragmentation, water consumption, and distance to city decreases the restored landscape fragmentation from 0.44 to 0.26, improves the restoration efficiency by 14.41%, and increases the beneficiary population by 35.5%, respectively. Small-scale allocation can further increase the ES realization efficiency, which is on average 4.8% higher at the city scale than at the provincial scale. Moreover, this approach focuses on the sustainable effect of the spatial arrangement on dryland landscapes at different scales, which provides methodological support for improving the sustainability of drylands.

Soil moisture determines the recovery time of ecosystems from drought.

Recovery time, the time it takes for ecosystems to return to normal states after experiencing droughts, is critical for assessing the response of ecosystems to droughts; however, the spatial dominant factors determining recovery time are poorly understood. We identify the global patterns of terrestrial ecosystem recovery time based on remote sensed vegetation indices, analyse the affecting factors of recovery time using random forest regression model, and determine the spatial distribution of the dominant factors of recovery time based on partial correlation. The results show that the global average recovery time is approximately 3.3 months, and that the longest recovery time occurs in mid-latitude drylands. Analysis of affecting factors of recovery time suggests that the most important environmental factor affecting recovery time is soil moisture during the recovery period, followed by temperature and vapour pressure deficit (VPD). Recovery time shortens with increasing soil moisture and prolongs with increasing VPD; however, the response of recovery time to temperature is nonmonotonic, with colder or hotter temperatures leading to longer recovery time. Soil moisture dominates the drought recovery time over 58.4% of the assessed land area, mostly in the mid-latitudes. The concern is that soil moisture is projected to decline in more than 65% regions in the future, which will lengthen the drought recovery time and exacerbate drought impacts on terrestrial ecosystems, especially in southwestern United States, the Mediterranean region and southern Africa. Our research provides methodological insights for quantifying recovery time and spatially identifies dominant factors of recovery time, improving our understanding of ecosystem response to drought.

Drylands contribute disproportionately to observed global productivity increases.

Drylands cover about 40% of the terrestrial surface and are sensitive to climate change, but their relative contributions to global vegetation greening and productivity increase in recent decades are still poorly known. Here, by integrating satellite data and biosphere modeling, we showed that drylands contributed more to global gross primary productivity (GPP) increase (65% ± 16%) than to Earth greening (33% ± 15%) observed during 1982-2015. The enhanced productivity per unit leaf area, i.e., light-use efficiency (LUE), was the mechanism behind this pattern. We also found that LUE was more sensitive to soil moisture than to atmospheric vapor pressure deficit (VPD) in drylands, while the opposite was observed (i.e., LUE was more sensitive to VPD) in humid areas. Our findings suggest the importance of using different moisture stress metrics in projecting the vegetation productivity changes of dry versus humid regions and highlight the prominent role of drylands as key controllers of the global carbon cycle.

Land cover change in global drylands: A review.

As a sensitive region, identifying land cover change in drylands is critical to understanding global environmental change. However, the current findings related to land cover change in drylands are not uniform due to differences in data and methods among studies. We compared and judged the spatial and temporal characteristics, driving forces, and ecological effects by identifying the main findings of land cover change in drylands at global and regional scales (especially in China) to strengthen the overall understanding of land cover change in drylands. Four main points were obtained. First, while most studies found that drylands were experiencing vegetation greening, some evidence showed decreases in vegetation and large increases in bare land due to inconsistencies in the datasets and the study phases. Second, the dominant factors affecting land cover change in drylands are precipitation, agricultural activities, and urban expansion. Third, the impact of land cover change on the water cycle, especially the impact of afforestation on water resources in drylands, is of great concern. Finally, drylands experience severe land degradation and require dataset matching (classification standards, resolution, etc.) to quantify the impact of human activities on land cover.

The on-off-on Fluorescence Sensor of Hollow Carbon Dots for Detecting Hg2+ and Ascorbic Acid.

Carbon dots (CDs) have excellent fluorescence properties and can be used in many research fields. In this paper, carbon dots were prepared by microwave-assisted pyrolysis of citric acid and urea, characterized by transmission electron microscope (TEM), X-ray diffractometer (XRD), 13C-NMR spectrum, zeta potential, Fourier transform infrared spectroscopy (FT-IR), ultraviolet-visible (UV-vis) absorption and fluorescence spectra, and detected the Hg2+ and ascorbic acid (AA) sequentially. It showed that carbon dots were hollow, spherical particles and less than 10 nm, photoluminescence quantum yield of carbon dots was about 15%. The CDs were selective and sensitive to Hg2+ and AA based on the "on-off-on" fluorescence behavior. The detection limits of CDs for Hg2+ and AA were 0.138 µM and 0.212 µM, respectively. Fluorescence response mechanism of CDs was also discussed.

N-doped carbon dots as the multifunctional fluorescent probe for mercury ion, glutathione and pH detection.

Recently, carbon dots (CDs) have exhibited promising applications in the fluorescence detection of various ions and biomolecules. In this work, one kind of nitrogen-doped CDs (N-CDs) with high fluorescence intensity was synthesized, characterized by transmission electron microscopy, x-ray diffraction, x-ray photoelectron spectroscopy, Fourier-transform infrared, UV-vis absorption spectra, and fluorescence spectra. The results show that the spherical and uniform N-CDs (quantum yield: 60.2%) have remarkable fluorescence properties and photostability, which makes N-CDs can be utilized as an 'on-off-on' sensor for Hg2+and glutathione (GSH). In addition, the pH-sensitive behavior of N-CDs makes it also applicable to H+detection under acid conditions (pKa = 3.53). The linear range of the 'turn-off' sensor detecting Hg2+was 0.014-50µM, with a 0.014µM limit of detection (LOD). GSH was detected by the fluorescence 'turn-on' method with a linear range of 0.125-60µM and a LOD of 0.125µM. The outstanding performance of N-CDs makes it potential applications in ecological pollution and biomolecule visualization monitoring.

Changes in the relationship between vapour pressure deficit and water use efficiency with the drought recovery time: A case study of the Yellow River Basin.

Drought is a major driver of interannual variability in the gross primary productivity (GPP) of global terrestrial ecosystems, and drought recovery time has been widely used to assess ecosystem responses to drought. However, the response of the carbon-water coupled cycle to drought, especially changes in the correlation between drought intensity and carbon-water coupling throughout the recovery time, remains unclear. In this study, the Yellow River Basin (YRB) located mostly in drylands was the study area. We assessed the correlation between the standardized water vapour pressure deficit (VPD) and the water use efficiency of ecosystems (WUEe) and water use efficiency of canopies (WUEc) every month with the drought recovery time of GPP. We found that the drought intensity in the middle reach of the YRB (MYRB) was greater and the drought recovery time was longer than those in the upper reach (UYRB) and lower reach (LYRB) during the period from 2003 to 2017. In terms of the correlation between drought intensity and carbon-water coupling, the greater the VPD was, the lower the WUEc. In addition, the correlation of WUEc with VPD was higher than that of WUEe in most areas of the YRB, especially in the LYRB. On the watershed level, the correlation between the two types of WUE and VPD increased gradually with the recovery time, while the correlation between WUEc and VPD (mostly negative) changed more than the correlation between WUEe and VPD (mostly positive). Therefore, the response of WUEc to meteorological drought should be given more attention, especially during the middle and late stages of drought, since it exhibited an opposite signal compared to that of WUEe during drought recovery.

Contribution of Tibetan Plateau ecosystems to local and remote precipitation through moisture recycling.

The ecosystems of the Tibetan Plateau (TP) provide multiple important ecosystem services that benefit both local populations and those beyond, such as through climate regulation services on precipitation for East Asia and China. However, the precipitation regulation service of the TP ecosystems for supplying moisture and maintaining precipitation is yet to be evaluated. In this study, we used the moisture recycling framework and a moisture tracking model to quantify the precipitation regulation services of TP ecosystems for their contribution to precipitation. We found TP ecosystems contributed substantially to local and downwind precipitation, with a contribution of 221 mm/year for the TP and neighboring areas through evapotranspiration (ET) (104 mm/year through transpiration), declined to <10 mm/year for eastern China and other surrounding countries. Among ecosystem types, grassland contributed most to precipitation, followed by barren and snow lands, forests, and shrublands. In terms of seasonality, precipitation contribution from TP ecosystems was greater in summer months than in non-summer months for western China, while the opposite was true for eastern China-although the magnitude was much smaller. Over the past two decades, the significant ET increases in TP translated to a widespread increase in precipitation contribution for TP and downwind beneficiary regions from 2000 to 2020. Our study provides a quantitative way to understand the precipitation regulation services of TP ecosystems through moisture recycling, substantiating their key role to maintain precipitation and the water cycle for downwind regions-effectively acting as an ecological safeguard that could be perceived by the public.