Explore the vast range of titles available.

The Carbonate rock weathering Carbon Sink (CCS) and Silicate rock weathering Carbon Sink (SCS) play a significant role in the carbon cycle and global climate change. However, the spatial‐temporal patterns and trends of the CCS and SCS from 1950 to 2099 have not been systematically quantified. Thus, Supported by long‐term hydrometeorological data under the RCP8.5, we use the accepted Suchet and Hartmann models to determine the following. First, we found except for the difference in their weathering rates, the SCS covers 37.2 million km2 more area than the CCS. The CCS Flux (CCSF) and SCS Flux (SCSF) are 5.36 and 1.22 t/km2/yr, respectively. Similarly, the Full CCS (FCCS, 0.3 Pg/yr) is more than the Full SCS (FSCS, 0.08 Pg/yr). Furthermore, the CCS (7.01 kg/km2) and SCS (3.95 kg/km2) are in a state of overall increase. In addition, the mid‐to‐high latitudes of the northern hemisphere are aggravated by warming (0.03°C) and humidity (0.65 mm), while the decrease in runoff in the mid‐latitudes of the southern hemisphere reduces karstification. Specifically, by 2099, the CCSF in the mid‐latitudes of the southern hemisphere will decrease by 5.72%. Instead, the CCSF in the northern hemisphere and lower latitudes of the southern hemisphere will exhibit a gentle upward slope. Particularly, the peak regions of the global FCCS (65.63 Tg/yr) and FSCS (33.01 Tg/yr) are the tropical zone. In conclusion, this study contributes a high‐resolution and long‐time series CS datasets for the CCS and SCS. We provide data and a theory for solving terrestrial carbon sink loss. Plain Language Summary The carbon cycle and global‐climate change cannot ignore the Carbonate and Silicate rocks weathering Carbon Sink (CCS and SCS). However, the spatial‐temporal patterns and trends of CCS and SCS from 1950 to 2099 have not been quantified. We use the accepted Suchet and Hartmann models to determine the following. First, we found except for the difference in their weathering rates, the SCS covers 37.2 million km2 more area than the CCS. The CCS Flux (CCSF) and SCS Flux (SCSF) are 5.36 and 1.22 t/km2/yr, respectively. Similarly, the Full CCS (FCCS, 0.3 Pg/yr) is more than the Full SCS (FSCS, 0.08 Pg/yr). Furthermore, the CCS (7.01 kg/km2) and SCS (3.95 kg/km2) are in a state of overall increase. In addition, the mid‐to‐high latitudes of the northern hemisphere are aggravated by warming (0.03°C) and humidity (0.65 mm), while the decrease in runoff in the mid‐latitudes of the southern hemisphere reduces karstification. Specifically, by 2099, the CCSF in the mid‐latitudes of the southern hemisphere will decrease by 5.72%. Instead, the CCSF in the northern hemisphere and lower latitudes of the southern hemisphere will exhibit a gentle upward slope. In conclusion, this study contributes a high‐resolution data set for solving carbon sink loss. Key Points High‐resolution data set for global carbonate and spatial diversification carbon sinks was established Carbon cycle can't ignore CCS (5.36 t/km2/yr) and SCS (1.22 t/km2/yr). Especially CCS (7.01 kg/km2) and SCS (3.95 kg/km2) increased significantly The peak regions of the global FCCS (65.63 Tg/yr) and FSCS (33.01 Tg/yr) are the tropical zone

China is reported as the leading country in the Earth's greening. However, it is a challenge to capture the gradual recovery in forest cover and distinguish the contribution of trees from herbaceous vegetation using remote sensing data. We developed a new fractional tree cover product (GLOBMAP FTC China) from MODIS time series data to investigate change patterns of China's forests during 2000–2022. This annual product showed high consistency with China's National Forest Inventory. We found a significant increase (∼4 Mha/year) in the annual forest area in China from ∼154.47 Mha in 2000 to ∼236.01 Mha in 2015. This rate then slowed by 50% in 2015–2022 (∼2 Mha/year). The forest recovery primarily started in 2000–2004, and reached saturation in 2015. It was primarily contributed by the tree cover gain (92%) from forest conservation and restoration programs. Our findings can support forest management and carbon neutrality achievement for the country. Plain Language Summary As the largest carbon reservoir in terrestrial ecosystems, forests are an indispensable part of China's carbon sink. Explicitly monitoring when, where, and how the forest recovery happening in China is crucial. In this work, a fractional tree cover product (named GLOBMAP FTC China) is generated, providing the coverage of trees within pixels. Compared to other remote sensing products, this product is proved to have the best consistency with China's National Forest Inventory (NFI). Applying the product for analysis, we found that China's forests have been recovering since 2000, and the increasing rate then slowed by 50% after 2015. Forest area in southwestern China shows the fastest increasing rate during 2000–2022, which is more than 0.2 Mha per year. The changes primarily show a stepwise transition from forests with a low fractional tree cover to forests with a higher fractional tree cover, which mainly thanks to the forest conservation and restoration programs. This study underscores that trees' growth dominates the greening in China's forests, highlighting the importance of the new fractional tree cover product for future accurate forest change studies and implications for forest management. Our findings are crucial for climate change mitigation as proposed by the Paris Agreement. Key Points This work generates a fractional tree cover product GLOBMAP to separate the mixed effect of herbaceous vegetation from woody cover Using GLOBMAP, we can obtain detailed and nuanced forest recovery in China, which is consistent with China's National Forest Inventory During 2000–2022, China's forests primarily presented as a stepwise transition from low tree cover forests to higher ones

Aim As anuran reproduction is generally linked to the availability of water, frogs and toads are particularly sensitive to climate. We tested the effect of climate on anuran reproductive phenology and daily activity by analysing temporal patterns of reproductive behaviour based on citizen‐collected observations. Location Brazil. Methods We obtained vocalizations and photographs of frogs with inflated air sacs, as well as images of amplectant couples, nests, eggs or tadpoles in initial stages of development from iNaturalist. We analysed hourly patterns, seasonality and duration of the reproductive period using circular statistics in different climate types and tested phylogenetic signals. We analysed data for Bufonidae, Hylidae, Leptodactylidae and Phyllomedusidae in detail. We also reviewed relevant literature. Results Among the 8478 (acoustic and photographic) records, 738 (8.7%) had evidence of reproduction with 284 acoustic records and 454 photographs, representing 184 taxa identified at the species level belonging to 16 families. Climate affected the period and duration of the reproductive season, as well as daily patterns of vocalization. These results were considered phylogenetically independent, as the reconstructions of ancestral character states did not suggest strong phylogenetic signals for temporal patterns of vocalization or reproduction. In Brazil, most frogs reproduce between October and January. Patterns were similar to the results of the literature review, however in the literature data, Bufonidae start reproduction 2 months earlier, and many Hylidae species reproduce until February. In general, frogs from warmer and drier climate regions had shorter and aggregated reproductive seasons, while in tropical monsoon climate they had a uniform temporal pattern. Main conclusions At the continental scale, reproductive phenology of anurans and their daily activity is affected by climatic conditions regardless of phylogeny. We found that community science can provide valuable information in Brazil that can be harnessed to monitor effects of climate change on amphibian reproduction.

The literature demonstrates that people perceive temporal structure in sequences of auditory, tactile, or visual stimuli. However, to date, much less attention has been devoted to studying the perception of temporal structure that results from the presentation of stimuli to the chemical senses and/or crossmodally. In this review, we examine the literature on the perception of temporal features in the unisensory, multisensory and crossmodal domains in an attempt to answer, among others, the following foundational questions: Is the ability to perceive the temporal structure of stimuli demonstrated beyond the spatial senses (i.e., in the chemical senses)? Is the intriguing idea of an amodal, or supramodal, temporal processor in the human brain empirically grounded? Is the perception of temporal structure in crossmodal patterns (even) possible? Does the ability to perceive temporal patterns convey any biological advantage to humans? Overall, the reviewed literature suggests that humans perceive rhythmic structures, such as beat and metre, across audition, vision and touch, exhibiting similar behavioural traits. In contrast, only a limited number of studies have demonstrated this ability in crossmodal contexts (e.g., audiotactile interactions). Similar evidence within the chemical senses remains scarce and unconvincing, posing challenges to the concept of an amodal temporal processor and raising questions about its potential biological advantages. These limitations highlight the need for further investigation. To address these gaps, we propose several directions for future research, which may provide valuable insights into the nature and mechanisms of temporal processing across sensory modalities.

Cardiac arrest (CA) is the leading cause of death in critically ill patients. Clinical research has shown that early identification of CA reduces mortality. Algorithms capable of predicting CA with high sensitivity have been developed using multivariate time series data. However, these algorithms suffer from a high rate of false alarms, and their results are not clinically interpretable. We propose an ensemble approach using multiresolution statistical features and cosine similarity-based features for the timely prediction of CA. Furthermore, this approach provides clinically interpretable results that can be adopted by clinicians. Patients were retrospectively analyzed using data from the Medical Information Mart for Intensive Care-IV database and the eICU Collaborative Research Database. Based on the multivariate vital signs of a 24-hour time window for adults diagnosed with heart failure, we extracted multiresolution statistical and cosine similarity-based features. These features were used to construct and develop gradient boosting decision trees. Therefore, we adopted cost-sensitive learning as a solution. Then, 10-fold cross-validation was performed to check the consistency of the model performance, and the Shapley additive explanation algorithm was used to capture the overall interpretability of the proposed model. Next, external validation using the eICU Collaborative Research Database was performed to check the generalization ability. The proposed method yielded an overall area under the receiver operating characteristic curve (AUROC) of 0.86 and area under the precision-recall curve (AUPRC) of 0.58. In terms of the timely prediction of CA, the proposed model achieved an AUROC above 0.80 for predicting CA events up to 6 hours in advance. The proposed method simultaneously improved precision and sensitivity to increase the AUPRC, which reduced the number of false alarms while maintaining high sensitivity. This result indicates that the predictive performance of the proposed model is superior to the performances of the models reported in previous studies. Next, we demonstrated the effect of feature importance on the clinical interpretability of the proposed method and inferred the effect between the non-CA and CA groups. Finally, external validation was performed using the eICU Collaborative Research Database, and an AUROC of 0.74 and AUPRC of 0.44 were obtained in a general intensive care unit population. The proposed framework can provide clinicians with more accurate CA prediction results and reduce false alarm rates through internal and external validation. In addition, clinically interpretable prediction results can facilitate clinician understanding. Furthermore, the similarity of vital sign changes can provide insights into temporal pattern changes in CA prediction in patients with heart failure-related diagnoses. Therefore, our system is sufficiently feasible for routine clinical use. In addition, regarding the proposed CA prediction system, a clinically mature application has been developed and verified in the future digital health field.

Background Intestinal infectious diseases (IIDs) can impact the growth and development of children and weaken adults. This study aimed to establish a spatial panel model to analyze the relationship between factors such as population, economy and health resources, and the incidence of common IIDs. The objective was to provide a scientific basis for the formulation diseases prevention measures. Methods Data on monthly reported cases of IIDs in each district and county of Zhejiang Province were collected from 2011 to 2021. The spatial distribution trend was plotted, and nine factors related to population, economy and health resources were selected for analysis. A spatial panel model was developed to identify statistically significant spatial patterns of influencing factors ( P  < 0.05). Results The results revealed that each type of IIDs exhibited a certain level of clustering. Each IIDs had a significant radiation effect, HEV ( b  = 0.28, P  < 0.05), bacillary dysentery ( b  = 0.38, P  < 0.05), typhoid ( b  = 0.36, P  < 0.05), other infectious diarrheas (OIDs) ( b  = 0.28, P  < 0.05) and hand, foot and mouth disease (HFMD) ( b  = 0.39, P  < 0.05), indicating that regions with high morbidity rates spread to neighboring areas. Among the population characteristics, density of population acted as a protective factor for bacillary dysentery ( b =-1.81, P  < 0.05), sex ratio acted as a protective factor for HFMD ( b =-0.07, P  < 0.05), and aging rate increased the risk of OIDs ( b  = 2.39, P  < 0.05). Urbanization ratio posed a hazard factor for bacillary dysentery ( b  = 5.17, P  < 0.05) and OIDs ( b  = 0.64, P  < 0.05) while serving as a protective factor for typhoid ( b =-1.61, P  < 0.05) and HFMD ( b =-0.39, P  < 0.05). Per capita GDP was a risk factor for typhoid ( b  = 0.54, P  < 0.05), but acted as a protective factor for OIDs ( b =-0.45, P  < 0.05) and HFMD ( b =-0.27, P  < 0.05). Additionally, the subsistence allowances ratio was a risk factor for HEV ( b  = 0.24, P  < 0.05). Conclusion The incidence of IIDs in Zhejiang Province exhibited a certain degree of clustering, with major hotspots identified in Hangzhou, Shaoxing, and Jinhua. It would be essential to consider the spillover effects from neighboring regions and implement targeted measures to enhance disease prevention based on regional development.

Flash flood disaster is a prominent issue threatening public safety and social development throughout the world, especially in mountainous regions. Rainfall threshold is a widely accepted alternative to hydrological forecasting for flash flood warning due to the short response time and limited observations of flash flood events. However, determination of rainfall threshold is still very complicated due to multiple impact factors, particular for antecedent soil moisture and rainfall patterns. In this study, hydrological simulation approach (i.e., China Flash Flood-Hydrological Modeling System: CNFF-HMS) was adopted to capture the flash flood processes. Multiple scenarios were further designed with consideration of antecedent soil moisture and rainfall temporal patterns to determine the possible assemble of rainfall thresholds by driving the CNFF-HMS. Moreover, their effects on rainfall thresholds were investigated. Three mountainous catchments (Zhong, Balisi and Yu villages) in southern China were selected for case study. Results showed that the model performance of CNFF-HMS was very satisfactory for flash flood simulations in all these catchments, especially for multimodal flood events. Specifically, the relative errors of runoff and peak flow were within ± 20%, the error of time to peak flow was within ± 2 h and the Nash–Sutcliffe efficiency was greater than 0.90 for over 90% of the flash flood events. The rainfall thresholds varied between 93 and 334 mm at Zhong village, between 77 and 246 mm at Balisi village and between 111 and 420 mm at Yu village. Both antecedent soil moistures and rainfall temporal pattern significantly affected the variations of rainfall threshold. Rainfall threshold decreased by 8–38 and 0–42% as soil saturation increased from 0.20 to 0.50 and from 0.20 to 0.80, respectively. The effect of rainfall threshold was the minimum for the decreasing hyetograph (advanced pattern) and the maximum for the increasing hyetograph (delayed pattern), while it was similar for the design hyetograph and triangular hyetograph (intermediate patterns). Moreover, rainfall thresholds with short time spans were more suitable for early flood warning, especially in small rural catchments with humid climatic characteristics. This study was expected to provide insights into flash flood disaster forecasting and early warning in mountainous regions, and scientific references for the implementation of flash flood disaster prevention in China.

Extracting flow clusters consisting of many similar origin–destination (OD) trips is essential to uncover the spatio-temporal interactions and mobility patterns in the free-floating bike sharing (FFBS) system. However, due to occlusion and display clutter issues, efforts to identify inhomogeneous flow clusters from large journey data have been hampered to some extent. In this study, we present a two-stage flow clustering method, which integrates the Leiden community detection algorithm and the shared nearest-neighbor-based flow (SNN_flow) clustering method to efficiently identify flow clusters with arbitrary shapes and uneven densities. The applicability and performance of the method in detecting flow clusters are investigated empirically using the FFBS system of Nanjing, China as a case study. Some interesting findings can be drawn from the spatio-temporal patterns. For instance, the share of flow clusters used to meet the “first-/last-mile” demand at metro stations is reasonably high, both during the morning (71.85%) and evening (65.79%) peaks. Compared with the “first-/last-mile” flow clusters between metro stations and adjacent workplaces, the solution of the “first-/last-mile” flow clusters between metro stations and adjacent residences is more dependent on the FFBS system. In addition, we explored the shape and density distribution of flow clusters from the perspective of origin and destination points. The endpoint distribution characteristics demonstrate that the shape distribution of metro station point clusters is generally flatter and the spatial points within them are more concentrated than other sorts of point clusters. Our findings could help to better understand human movement patterns and home-work commute, thereby providing more rational and targeted decisions for allocating FFBS infrastructure resources.

The expansion of the public charging infrastructure for electric vehicles is seen as central to the development of electric mobility in many countries. Although national studies of charging infrastructure utilization based on real-world data would be a sound basis for demand planning, such studies are scarce. Using Switzerland as an example, this study examines the spatial and temporal patterns of charging infrastructure utilization. To this end, detailed, nationwide, real-time utilization data from 3086 electric vehicle supply equipment units (EVSEs) at electric vehicle charging stations were collected over a period of several months and analyzed exploratively and statistically. The maximum average utilization rate of the EVSEs surveyed during the study period is between 14% and 16%, depending on the day of the week and time of day. Most charging occurs Monday through Friday during peak working hours and on Saturday during the day. The median utilization time is higher in the largest cities than the statewide average. Charging stations along major transit routes do not have higher utilization rates than in other locations. The results suggest that public charging infrastructure is used primarily in cities and agglomeration during work hours. The findings from this study may help plan and make better use of funding to expand charging infrastructure.

Intergenerational health mobility serves as a crucial indicator that reflects both social class mobility and health inequality. In this study, we constructed a comprehensive index to evaluate the health of residents in terms of physical, psychological and social adaptation dimensions using data from the China Family Panel Studies from 2010 to 2018. It then measured intergenerational health mobility using the intergenerational rank correlation coefficient method. Furthermore, the dynamic evolutionary trend, spatial differences and their sources, and the convergence characteristics of intergenerational health mobility were revealed by nonparametric kernel density estimation, the Dagum Gini coefficient, and the σ(β) convergence model, respectively. The formation mechanisms were explored using the quadratic assignment procedure. The results showed a general improvement but unbalanced trend of intergenerational health mobility in China, and hypervariable density was identified as the primary factor contributing to this difference. The σ convergence characteristics and β convergence mechanism were verified in China and its three regions. Environmental quality, industrial structure, and accessibility of medical and health resources had significant and decreasing effects on the spatial differences in intergenerational health mobility across China, with varying impacts observed among the three regions. This study not only provides empirical insights into understanding the dynamics laws of intergenerational health mobility and promoting regional coordinated development in China but also offers valuable guidance for formulating healthcare policies in developing countries and for achieving the United Nations Sustainable Development Goals.