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Abstract The grid-based precipitation dataset is an important source for studying precipitation change in the high mountains of Asia due to where precipitation stations are sparse. It is essential to evaluate the accuracy of grid-based precipitation datasets in the high mountains of Asia before selecting an appropriate grid-based dataset. Therefore, this study comprehensively evaluated the precipitation errors of four commonly utilized precipitation datasets (multi-source weighted-ensemble precipitation (MSWEP), global precipitation climatology centre (GPCC), global precipitation measurement (GPM), and soil moisture to rain-advanced scatterometer (SM2RAIN-ASCAT)) in the high mountains of Asia from temporal and spatial perspectives. It then decomposed the precipitation errors to reveal their sources. The results showed that MSWEP, GPCC, GPM, and SM2RAIN-ASCAT overestimated precipitation amount and probability compared with station observations. Meanwhile, all precipitation data sets except MSWEP data underestimated precipitation in the dry season. In terms of the average values of the error metrics, GPCC performed the best. There was an evident annual periodicity in the error assessment metrics for the four precipitation data sets. Multiple linear regression analysis revealed that four precipitation-related factors (false alarm precipitation, missed amount of precipitation, precipitation detected presented, and precipitation detected event) explained the root mean square error values for four precipitation data sets, with precipitation detected presented having the largest weight. The root mean square error of each product exhibits periodic fluctuations with changes in precipitation quantity, attributed to the occurrences of precipitation detected presented and precipitation detected events. These findings provide useful reference information for correcting biases in precipitation data sets for high mountains of Asia.

The Soil and Water Assessment Tool (SWAT) has been widely applied to simulate the hydrological cycle, investigate cause-and-effect relationships, and aid decision-making for better watershed management. However, the software tools for model dataset analysis and visualization to support informed decision-making in a web environment are not considered fully fledged and are technically intensive to implement. This study focuses on addressing these issues by establishing a tool and library (named PAVLIB4SWAT) that can largely reduce technical expertise requirements for developers to adopt and customize this work to their own demands. Specifically, we created PAVLIB4SWAT based on a Kepler.gl widget to visualize SWAT model data, including shapefiles from the watershed delineation process, model inputs, and simulated results via dynamic and interactive maps. We evaluated PAVLIB4SWAT through a Jinjiang watershed SWAT model use case to demonstrate its utility and ease of adoption. The case study shows that PAVLIB4SWAT can provide various geospatial analysis and mapping functionalities for SWAT models and can flexibly distribute visualized results as standalone offline web pages and web servers. In addition, PAVLIB4SWAT was designed as an open-source project and implemented purely in the Python programming language; thus, developers can easily adapt and customize it to suit their demands. HIGHLIGHTS PAVLIB4SWAT visualizes SWAT model data via dynamic and interactive maps.; PAVLIB4SWAT requires less technical expertise, enabling more developers to adopt it.; PAVLIB4SWAT can be easily extended to other hydrological models.;

Abstract Revealing changes in actual evapotranspiration is essential to understanding regional extreme hydrological events (e.g., droughts). This study utilized the Global Land Evaporation Amsterdam Model (GLEAM) to analyse the spatial and temporal characteristics of actual evapotranspiration over 40 years in the Southeast River basin of China. The relationship between changes in actual evapotranspiration and the drought index was quantified. The results indicated a significant increase in actual evapotranspiration in the Southeast River basin from 1981 to 2020 (2.51 mm/year, p

A novel demodulation scheme for a point-type fiber sensor is designed for salinity concentration monitoring based on a Sagnac interferometer (SI) composed of a tapered polarization-maintaining fiber (TPMF) and optical time stretching technology. The SI, constructed using a PMF with a taper region of 5.92 μm and an overall length of 30 cm, demonstrated a notable enhancement in the evanescent field, which intensifies the interaction between the light field and external salinity. This enhancement allows for a direct assessment of salinity concentration changes by analyzing the variations in the SI reflection spectra and the experimental results indicate that the sensitivity of the sensor is 0.151 nm/‰. In contrast to traditional fiber optic sensors that depend on spectral demodulation with slower response rates, this work introduces a new approach where the spectral shift is translated to the time domain, utilizing a dispersion compensation fiber (DCF) with the demodulation rate reaching up to 50 MHz. The experimental outcomes reveal that the sensor exhibits a sensitivity of −0.15 ns/‰ in the time domain. The designed sensor is anticipated to play a pivotal role in remote, real-time monitoring of ocean salinity.

In recent years, advancements in the Internet of Things (IoT), manufacturing processes, and material synthesis technologies have positioned flexible sensors as critical components in wearable devices. These developments are propelling wearable technologies based on flexible sensors towards higher intelligence, convenience, superior performance, and biocompatibility. Recently, two-dimensional nanomaterials known as MXenes have garnered extensive attention due to their excellent mechanical properties, outstanding electrical conductivity, large specific surface area, and abundant surface functional groups. These notable attributes confer significant potential on MXenes for applications in strain sensing, pressure measurement, gas detection, etc. Furthermore, polymer substrates such as polydimethylsiloxane (PDMS), polyurethane (PU), and thermoplastic polyurethane (TPU) are extensively utilized as support materials for MXene and its composites due to their light weight, flexibility, and ease of processing, thereby enhancing the overall performance and wearability of the sensors. This paper reviews the latest advancements in MXene and its composites within the domains of strain sensors, pressure sensors, and gas sensors. We present numerous recent case studies of MXene composite material-based wearable sensors and discuss the optimization of materials and structures for MXene composite material-based wearable sensors, offering strategies and methods to enhance the development of MXene composite material-based wearable sensors. Finally, we summarize the current progress of MXene wearable sensors and project future trends and analyses.

Climate change significantly impacts catchment hydrologic and water quality processes. Best management practices (BMPs) can serve as adaptation strategies to negate the impact of climate change on sediment and total nitrogen (TN) loads. One major controversial issue in climate change adaptation studies is the highly uncertain nature of such changes. Previous studies have rarely focused on the combined impact of the uncertainty in climate change and watershed model parameters, which could be the main sources of uncertainty in climate change adaptation research. In this study, the effectiveness and resilience (defined as continued effectiveness under a changing climate) of BMPs in reducing sediment and TN loads were explored under future climate change in the Shanmei Reservoir watershed (SMW) of Southeast China. Climate change projections provided by 10 general circulation models (GCMs) under the SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 scenarios from 2031 to 2060 were applied in the Annualized Agricultural Nonpoint Source (AnnAGNPS) model to evaluate the effectiveness and resilience of 4 BMPs (riparian buffers (RB), no-tillage (NT), fertilization reduction (FR), and parallel terraces (PT)). The ensemble average of 10 GCMs and 10 behavior parameter groups were adopted to reduce the uncertainty resulting from the hydrological model parameters and GCMs. The results indicated that the average annual temperature and precipitation in the SMW will increase in the future. On a seasonal scale, the average temperature during all seasons will increase, and precipitation will decrease in summer and autumn but increase in spring and winter. The annual sediment and TN loads will decrease, but the loads in spring and winter will increase. BMPs could be effective as climate adaptation strategies for reducing sediment and TN loads under future climate conditions, with PT as the most effective option. Structural BMPs were more effective in reducing sediment and TN loads in spring and winter, whereas nonstructural BMPs were more effective in reducing loads in summer and autumn. BMPs were more resilient when future watershed runoff changes were slight or climate sensitivity was reduced, with higher BMP resilience in spring and winter than in summer and autumn. This study aimed to provide systematic references for watersheds through the implementation of BMPs for mitigating the effects of climate change and extending the boundaries of the AnnAGNPS model application.

Study region: Southeast coast of China Study focus: The reservoirs in southeast coast of China are mostly small due to the limitations of terrain. In order to analyze the impact of these densely distributed small and medium-sized reservoirs (SMRs) with lacking observation and operational data on runoff, this paper uses a hydrological model & scenario simulation method to separate the impacts of climate variability (CV), land use change (LUC) and SMRs group change on streamflow variation in two river basins of Southeast China. New hydrological insights for the region: (1) The streamflow of two basins has changed greatly, with CV and SMRs change being the main influencing factors, while the impact of LUC was relatively small. The contribution rates of CV to the annual runoff change of three hydrological stations in two river basins were 90.19%, 61.75% and 26.64%; Contribution rates of SMRs changes were 9.34%, 37.24% and 71.04%, correspondingly. (2) The regulation of streamflow by SMRs changes led to a decrease in both annual and monthly runoff, which was due to the fact that the main functions of SMRs in this region are agricultural irrigation and domestic water supply. (3) The three-factor separation method based on hydrological modeling, which separated the cumulative effects of SMRs in the form of SMRs group, would be valuable for the study and management of watersheds with numerous SMRs and lack of observation and operational data.

Study region: Minjiang River Basin of China. Study focus: This paper aimed to study the spatiotemporal changes in water cycle components including evapotranspiration (ET) and terrestrial water storage in a watershed. To achieve this, we proposed a method that is based on the water balance and utilizes measured annual precipitation and runoff data to correct ET products. Subsequently, we derived the annual terrestrial water storage changes and performed trend analysis on the water cycle components by the Mann-Kendall trend test. New hydrological insights for the region: (1) The Global Land Data Assimilation System (GLDAS) product overestimated ET from 2000 to 2019 in the Minjiang River Basin (MJB), which was 105.18 mm higher than ET. Through sub-basin validation, the relative error between the corrected ET and the ET is less than 5.1%. The proposed method can construct a reasonable annual dataset of water cycle components. (2) From 2000–2019, the Minjiang River Basin witnessed non-significant increasing trends in precipitation and runoff. However, significant growth was observed in ET, indicated by a Mann-Kendall trend test Z-value of 2.63. The variation in ET was primarily influenced by the normalized difference vegetation index (NDVI) (correlation coefficients of 0.37) and temperature (correlation coefficients of 0.48). The terrestrial water storage change fluctuated between − 400 and 355 mm. The relationships among the water cycle components, as represented by the runoff coefficient and evapotranspiration coefficient show non-significant changing trends. Both displayed a non-significant decreasing trend. From 2000–2019, the water cycle process remained relatively stable under changing environments in the MJB.

Abstract Water scarcity has become a global severe challenge over the past few decades. Quantifying the impact of climate variability and land use on water resource availability is crucial for integrated water resource management. Many studies have focused on blue water but ignored green water which is important in the terrestrial ecosystem, especially on different temporal scales. In this study, we selected the Shanmei Reservoir, the most import drinking water resource for a rapidly development city of Southeast China, as a case for analysis of these impacts for the entire basin. We adopted the Soil and Water Assessment Tool (SWAT) to investigate the spatial and temporal distributions of blue water (BW), green water flow (GWF) and green water storage (GWS) in the Shanmei Reservoir Basin (SRB). The results of the blue and green water components (BW and GW) revealed that SRB is dominated by BW, accounting for 52.6% of the total water resources, while GW accounted for 47.4%. There was an insignificant upward trend of BW and a significant upward trend of GWF, with a tendency rate of 1.125 mm a−1. Precipitation was the key factor affecting BW on annual and monthly scales. The GWF was more sensitive to temperature at both the annual and monthly scales. The GWS was significantly correlated with precipitation at the monthly scale, while insignificant correlation occurred at the annual scale. The spatial distribution of BW was largely dominated by precipitation, and land-use types led to the differentiation of GW. It indicates that the BW of paddy fields is greater than that of forests, while the GWS of forests is greater than that of orchards and rainfed croplands.

Under climate change, the frequency of drought-flood abrupt alternation (DFAA) events is increasing in Southeast China. However, there is limited research on the evolution characteristics of DFAA in this region. This study evaluated the effectiveness of the drought and flood indexes including SPI (Standardized Precipitation Index), SPEI (Standardized Precipitation Evapotranspiration Index), and SWAP (Standardized Weighted Average Precipitation Index) in identifying DFAA events under varying days of antecedent precipitation. Additionally, the evolution characteristics of DFAA events in Fujian Province from 1961 to 2021 were explored. The results indicate that (1) SPI-12d had the advantages of high effectiveness, optimal generalization accuracy, and strong generalization ability of identification results, and it can be used as the optimal identification index of DFAA events in Southeast China. (2) There was an overall increase in DFAA events at a rate of 1.8 events/10a. The frequency of DFAA events showed a gradual increase from the northwest to the southeast. (3) DTF events were characterized by moderate drought to flood, particularly in February, July, and August, while FTD events were characterized by light/moderate flood to drought, with more events occurring from June to October. (4) DTF event intensity increased in the northern and western regions from 1961 to 2021. For FTD events, the intensity notably increased in the western region from 1961 to 2001, while a significant increase occurred in all regions except the central region from 2001 to 2021. These findings emphasize the need for precautionary measures to address the increasing frequency and severity of DFAA events in Southeast China.

Study region: Dongting Lake Basin of China. Study focus: This study aimed to analyze the nonstationary characteristics and future trends of flood extremes in the Dongting Lake Basin. The spatiotemporal variations in the flood extremes that occurred over the past 60 years were explored using the trend-free prewhitening-MK (TFPW-MK) method, the nonstationary characteristics of flood extremes were detected using the Pettitt test, and the nonstationarity analysis was performed using the GAMLSS model. Furthermore, a combination of TFPW-MK and the Hurst exponent was employed to predict the future trends in flood extremes. New hydrological insights for the region: (1) Evident variations were observed in the flood extremes from most hydrometric stations. Among the 10 stations with a decreasing extreme trend, seven exhibited evident decreases. Such decreases probably result from the impact of water conservancy projects. Among the remaining six stations with an increasing extreme trend, two exhibited evident increases. Such increases probably result from the effect of highly extreme precipitation. (2) Flood extremes from most (9 of 16) stations showed nonstationarity. The lognormal distribution was the optimal distribution of extreme values for nonstationary stations, whereas the Gamma distribution was the optimal distribution of extreme values for stationary stations. Despite the preferable fitting efficiency of the GAMLSS model, its simulation performance for nonstationary stations that showed significant trends must be improved. (3) The flood extremes of the 14 stations will maintain existing trends in the future. The Xiangtan Station exhibited anti-persistence and might show a decreasing trend in the future, whereas Shimen Station did not show persistence.

A component of terrestrial water storage, vegetation is also an influential driver of changes in terrestrial water storage. In the context of warming on the Tibetan Plateau, it is essential to explore the relationship between changes in terrestrial water storage and vegetation in this region to understand further the role of vegetation in the changes of water systems in alpine mountains. Our study combines terrestrial water storage anomalies data and vegetation indices to determine how their interact. The results indicate a warming rate of 0.44°C/decade (p

In the worldwide, uterine corpus endometrial carcinoma (UCEC) is the sixth most common malignancy in women, and the number of women diagnosed is increasing. Kinase plays an important role in the occurrence and development of malignant tumors. However, the research about kinase in endometrial cancer is still unclear. Here, we first downloaded the gene expression data of 552 UCEC patients and 23 healthy endometrial tissues from The Cancer Genome Atlas (TCGA), obtained 538 kinase-related genes from the previous literature, and calculated 67 differentially expressed kinases. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were referenced to identify multiple important biological functions and signaling pathways related to 67 differentially expressed kinases. Using univariate Cox regression and Least absolute shrinkage and selection operator (LASSO), seven kinases (ALPK2, CAMKV, TTK, PTK6, MAST1, CIT, and FAM198B) were identified to establish a prognostic model of endometrial cancer. Then, patients were divided into high- and low-risk groups based on risk scores. Receiver operating characteristic (ROC) curves were plotted to evaluate that the model had a favorable predictive ability. Kaplan–Meier survival analysis suggested that high-risk groups experienced worse overall survival than low-risk groups. qRT-PCR and ISH assays confirmed the consistency between predicted candidate genes and real sample contents. CIBERSORT algorithm and ssGSEA were adopted to investigate the relationship between this signature and tumor immune microenvironment, and revealed that in low- and high-risk groups, the types of tumor-infiltrating immune cells and the immune cell-related functions were significantly different. In summary, a seven-gene signature risk model has been constructed, and could accurately predict the prognosis of UCEC, which may offer ideas and breakthrough points to the kinase-associated development of UCEC.

Artificial skin, also known as bioinspired electronic skin (e-skin), refers to intelligent wearable electronics that imitate the tactile sensory function of human skin and identify the detected changes in external information through different electrical signals. Flexible e-skin can achieve a wide range of functions such as accurate detection and identification of pressure, strain, and temperature, which has greatly extended their application potential in the field of healthcare monitoring and human-machine interaction (HMI). During recent years, the exploration and development of the design, construction, and performance of artificial skin has received extensive attention from researchers. With the advantages of high permeability, great ratio surface of area, and easy functional modification, electrospun nanofibers are suitable for the construction of electronic skin and further demonstrate broad application prospects in the fields of medical monitoring and HMI. Therefore, the critical review is provided to comprehensively summarize the recent advances in substrate materials, optimized fabrication techniques, response mechanisms, and related applications of the flexible electrospun nanofiber-based bio-inspired artificial skin. Finally, some current challenges and future prospects are outlined and discussed, and we hope that this review will help researchers to better understand the whole field and take it to the next level.

Based on the observation data from 37 national ambient air automatic monitoring stations and the land use/cover data in Fujian Province, the effects of land use/cover on the annual and seasonal variations in the air quality index (AQI), PM2.5 concentration and PM10 concentration are analyzed. In addition, buffer zones with different radii are established to calculate landscape pattern metrics and the influences of landscape patterns on the AQI, PM2.5 concentration and PM10 concentration at different scales are discussed. The results show that land use/cover types have remarkable impacts on the variations in the atmospheric particulate matter concentrations. The AQI and PM10 concentration are the highest for construction land, and the PM2.5 concentration is the highest for cultivated land. The seasonal variations in all air pollutant concentrations show similar characteristics, i.e., high in spring and winter and low in summer and autumn. Different landscape metrics have diverse effects on atmospheric particulate matter concentrations at different scales. In the buffer zone with a 5000 m radius, the patch number and patch density of forest land are positively correlated with the PM2.5 concentration, while the edge density of construction land has a negative correlation with it, indicating that landscape fragmentation affects the PM2.5 concentration. More fragmented forest land has a weaker effect on the reduction in the PM2.5 concentration, and more fragmented construction land has a weaker effect on the increase in the PM2.5 concentration. Moreover, the seasonal variations in the atmospheric particulate matter concentrations are different under different land use/cover types. Except for autumn, the AQI and PM2.5 concentration are most noticeably affected by forest land in all seasons, showing negative correlations. In autumn, the impacts of cultivated land on the AQI and PM2.5 concentration are more pronounced. The PM10 concentration is substantially affected by forest land in spring and summer and is markedly influenced by construction land in autumn and winter. The analysis of the landscape metrics of forest land and construction land at different scales indicates that the optimal scale is 5000 m for studying the annual average of the AQI and PM10 concentration and is 3000 m for investigating the annual average of the PM2.5 concentration. The optimal scales to research the seasonal variations in the AQI, PM2.5 and PM10 concentrations are 4000–5000 m for forest land and construction land, while the optimal scale is 1000 m for cultivated land to research the AQI and PM2.5 in autumn. This study can provide a scientific basis for the optimization of land use/cover and landscape patterns in Fujian Province, the planning and management of green space and the selection of research scales in the future.

In this study, a one-step electrochemical aptasensor was developed to detect the biomarker vascular endothelial growth factor (VEGF), an important protein in the pathogenesis of many retinal diseases, including age-related macular degeneration, diabetic retinopathy, retinopathy of prematurity, and retinal vein occlusion. The aptamer has a good affinity and can rapidly identify and capture VEGF based on its unique structure. We designed a VEGF aptasensor based on the aptamer recognition and complex metallo nanoenzyme particles as an electron exchange center and bridge between capture DNA and electrode. The aptamers maintained the hairpin structure to avoid nonspecific surface adsorption and expose the capture sequence outwards when the target was inexistent. Conversely, the aptamers opened the hairpin structure to release space to accomplish binding between VEGF and DNA, resulting in increased impedance. The performance of the electrochemical aptasensor is detected by electrochemical impedance spectroscopy (EIS). The limit of detection by EIS was as low as 8.2 pg ml−1, and the linear range was 10 pg ml−1–1 μg ml−1. The electrochemical aptasensor also showed high specificity and reproducibility.

Herein, a novel natural wood derived macroporous carbon sheet with three-dimension inter-connected perpendicular-channels was engineered as gas diffusion layers (w-GDLs) for air-breathing proton exchange membrane fuel cells (PEMFCs). Beneficial to the unique accessible perpendicular channels and the presence of a microporous layer, the current density reached 0.139 A/cm2 (at 0.6 V) and the maximum power density elevated up to 0.102 W/cm2 (at 0.43 V), which are comparable to the best results reported for the air-breathing PEMFCs with high Pt loadings. Furthermore, it exhibited excellent durability during preliminary constant discharge operation, demonstrating the feasibility of this w-GDL for practical applications.

This paper presented a new kind of salinity and temperature dual-parameter sensor based on a fiber ring laser (FRL) with tapered side-hole fiber (SHF) embedded in a Sagnac interferometer. The sensing structure is majorly composed of tapered SHF located in the middle of SHF inside the Sagnac interferometer loop structure. The influences of the SHF’s diameters of different tapered in the Sagnac interferometer loop on the FRL sensing system are studied. The presence of air holes in the SHF makes the cladding mode easier to excite, and the interaction between the cladding mode with its surroundings is enhanced, thus having higher salinity sensitivity. Besides, the unique advantages of high resolution, narrower linewidth, and high signal-to-noise ratio (SNR) of fiber laser make the measurement results more accurate. In this experiment, the SHF with different taper diameters was made, and it was found that reducing the diameter of the taper waist diameter could further improve the salinity sensitivity. When the waist diameter was 9.70 μm, the maximum salinity sensitivity of 0.2867 nm/‰ was achieved. Temperature sensing experiments were also carried out. The maximum temperature sensitivity of the FRL sensing system was −0.3041 nm/°C at the temperature range from 20 to 30 °C. The sensor has the characteristics of easy manufacture, good selectivity, and high sensitivity, proving the feasibility of simultaneous measurement of seawater salinity and temperature.

Nanoparticles of four noble metal doped titanium dioxide (i.e., Pd/TiO2, Ag/TiO2, Pt/TiO2 and Cu/TiO2) were synthesized and investigated for their effectiveness to degrade polybrominated diphenyl ethers (PBDEs) under UV light. All the investigated noble metal additives can greatly enhance the performance of TiO2 to degrade 2,2′,4′,4′-tetrabromodiphenyl ether (BDE-47). However, the debromination pathways of BDE-47 in Ag/TiO2 and Cu/TiO2 systems are just contrary to those in Pd/TiO2 and Pt/TiO2 systems, and there was an induction period in the former systems but not in the latter systems. The hydrogenation experiment suggests a direct H-atom transfer mechanism in Pd/TiO2 and Pt/TiO2 systems, while in Ag/TiO2 and Cu/TiO2 systems, electron transfer is still the dominant mechanism. Electronic method was applied to explain why BDE-47 exhibit different debromination pathways based on different degradation mechanism. In addition, oxygen was proved to be able to capture both electrons and H atoms, and thus can greatly inhibit the degradation of PBDEs in all investigated systems. Finally, the merit and demerit of each metal doped TiO2 were discussed in detail, including the reactivity, stability and the generation of byproducts. We proposed our study greatly enhance our understanding on the mechanisms of PBDE degradation in various metal doped TiO2 systems. Keywords: Polybrominated diphenyl ethers, Debromination pathways, Photocatalytic degradation, Mechanisms, Titanium dioxide

Exploring how watershed partition influences hillslope and channel sediment in the Soil & Water Assessment Tool is important to identify the partition threshold and improve the model application in soil erosion evaluation. However, the influences on the channel phase, and the partition threshold for the entire watershed sediment process have not yet been well addressed. The Xixi basin located in southeast China was taken as an example with thirteen partition levels. Based on the idea of separating the simulations of the hillslope and channel phases, the partition threshold for channel sediment routing was identified according to changes in the parameters of channel sediment routing and the spatial distributions of channel deposition under different partition levels with two newly proposed indicators. This allowed the partition threshold of the entire watershed sediment process to be determined by comparing the thresholds for channel and hillslope sediment. The results indicate that (1) watershed partition has a substantial influence on the spatial distributions of channel deposition, and increasing sub-watersheds decreases the spatial variations of channel deposition. However, the influences can be obscured at the watershed outlet by changing channel routing parameters. (2) The changes in channel sediment routing are primarily due to the sensitivity of the channel dimensions in the model to watershed partition, which alter the hydraulic radius until a partition threshold, at which point the mean sub-watershed size is 2.4% of the total watershed area. (3) The thresholds for hillslope sediment generation and channel sediment routing are different, and the threshold for effectively simulating the entire watershed sediment process mainly depend on the hillslope sediment phase with a mean sub-watershed size of approximately 1.6% of the total watershed area.

Warming in mountainous areas has obvious elevation dependence (warming rate increases with elevation), which deeply impacts runoff change in mountainous areas. This study analysed the influence of elevation-dependent warming on runoff in the headwater region of the Urumqi River Basin (URB) based on meteorological data, remote sensing images, and runoff data. Results indicated a significant warming rate in the URB from 1960 to 2019 (0.362 °C/decade; p < 0.01). The temperature increased with an obvious elevation-dependent warming in the URB, especially during winter. Glaciers sharply retreated in the headwater region of the URB under regional warming, and remote-based results showed that glacier areas decreased by 29.45 km2 (−57.81%) from the 1960s to 2017. The response of glacier mass balance and meltwater runoff to temperature change has a lag of 3 years in the headwater region of the URB. The elevation-dependent warming of temperature changes significantly impacted glacial meltwater runoff in the URB (R2 = 0.49). Rising temperatures altered the glacial meltwater runoff, and the maximum annual runoff of the Urumqi Glacier No. 1 meltwater runoff increased 78.6% in 1990–2017 compared to 1960–1990. During the period of 1960–1996, the total glacial meltwater runoff amounted to 26.9 × 108 m3, accounting for 33.4% of the total runoff during this period, whereas the total glacial meltwater runoff accounted for 51.1% of the total runoff in 1996–2006. Therefore, these results provide a useful reference for exploring runoff changes in mountainous watersheds in the context of elevation-dependent warming.

Evapotranspiration is one of the critical processes in the terrestrial hydrological cycle, and the assessment of evapotranspiration is essential for understanding the regional hydrological cycle. In this study, the Minjiang River Basin, a typical watershed in the humid subtropical climate zone, is selected as the study region. The Penman-Monteith equation and the dual crop coefficient method are used to calculate the actual evapotranspiration (ETa) at seven meteorological stations within the study basin. Meanwhile, the applicability of the Global Land Data Assimilation System-Noah (GLDAS-Noah) ETa data in the Minjiang River Basin is evaluated based on stations P-M equation results, then to analyze the changes of the ETa in the Minjiang River Basin from 2000 to 2019. The results show that the GLDAS-Noah ETa data are well applicable in the Minjiang River Basin (R2 > 0.9 and NSE > 0.8). The ETa in the basin shows an increasing trend since 2000, and the increasing rate is 3.60 mm·yr−1 (p < 0.01). The seasonal variation results show that ETa tends to increase in winter and spring, with increasing rates of 1.10 mm·yr−1 (p < 0.01) and 2.60 mm·yr−1 (p < 0.01), respectively, while the ETa did not change significantly in summer and autumn. Annual air temperature has the largest effect on annual ETa (59.6%), followed by precipitation at 33.9%. ETa increased in spring was mainly influenced by increasing temperatures (89.4%) in the Minjiang River Basin from 2000 to 2019. The research results are of great benefit to further improve the understanding of ETa variations in the basin under global warming.

Introduction Inappropriate antimicrobial use increases the prevalence of antimicrobial-resistant bacteria. Surgeons are reluctant to implement recommendations of guidelines in clinical practice. Antimicrobial stewardship (AMS) is effective in antimicrobial management, but it remains labour intensive. The computerised decision support system (CDSS) has been identified as an effective way to enable key elements of AMS in clinical settings. However, insufficient evidence is available to evaluate the efficacy of computerised AMS in surgical settings.Methods and analysis The Evaluate of the Potential Impact of Computerised AMS trial is an open-label, single-centre, two-arm, cluster-randomised, controlled trial, which aims to determine whether a multicomponent CDSS intervention reduces overall antimicrobial use after cardiovascular surgeries compared with usual clinical care in a specialty hospital with a big volume of cardiovascular surgeries. Eighteen cardiovascular surgical teams will be randomised 1:1 to either the intervention or the control arm. The intervention will consist of (1) re-evaluation alerts and decision support for the duration of antimicrobial treatment decision, (2) re-evaluation alerts and decision support for the choice of antimicrobial, (3) quality control audit and feedback. The primary outcome will be the overall systemic antimicrobial use measured in days of therapy (DOT) per admission and DOT per 1000 patient-days over the whole intervention period (6 months). Secondary outcomes include a series of indices to evaluate antimicrobial use, microbial resistance, perioperative infection outcomes, patient safety, resource consumption, and user compliance and satisfaction.Ethics and dissemination The Ethics Committee in Fuwai Hospital approved this study (2020-1329). The results of the trial will be submitted for publication in a peer-reviewed journal.Trial registration number NCT04328090.

In this study, 2 m air temperature data from 24 meteorological stations in the Qilian Mountains (QLM) are examined to evaluate ERA-Interim reanalysis temperature data derived from the European Centre for Medium-Range Weather Forecasts (ECMWF) for the period of 1979–2017. ERA-Interim generally captures the monthly, seasonal, and annual variation very well. High daily correlations ranging from 0.956 to 0.996 indicate that ERA-Interim captures the daily temperature observations very well. However, an average root-mean-square error (RMSE) of ±2.7°C of all stations reveals that ERA-Interim should not be directly applied at individual sites. The biases are mainly attributed to the altitude differences between ERA-Interim grid points and stations. The positive trend (0.457°C/decade) is significant over the Qilian Mountains based on the 1979–2017 observations. ERA-Interim captures the warming trend very well with an increase rate of 0.384°C/decade. The observations and ERA-Interim both show the largest positive trends in summer with the values of 0.552°C/decade and 0.481°C/decade, respectively. We conclude that in general ERA-Interim captures the trend very well for observed 2 m air temperatures and ERA-Interim is generally reliable for climate change research over the Qilian Mountains.

Estimates of change in global land evapotranspiration (ET) are necessary for understanding the terrestrial hydrological cycle under changing environments. However, large uncertainties still exist in our estimates, mostly related to the uncertainties in upscaling in situ observations to large scale under non-stationary surface conditions. Here, we use machine learning models, artificial neural network and random forest informed by ground observations and atmospheric boundary layer theory, to retrieve consistent global long-term latent heat flux (ET in energy units) and sensible heat flux over recent decades. This study demonstrates that recent global land ET has increased significantly and that the main driver for the increased ET is increasing temperature. Moreover, the results suggest that the increasing ET is mostly in humid regions such as the tropics. These observation-driven findings are consistent with the idea that ET would increase with climate warming. Our study has important implications in providing constraints for ET and in understanding terrestrial water cycles in changing environments.

Summary: In vertebrates, hematopoiesis occurring in different niches is orchestrated by intrinsic and extrinsic regulators. Previous studies have revealed numerous linear and planar regulatory mechanisms. However, a multi-dimensional transcriptomic atlas of any given hematopoietic organ has not yet been established. Here, we use multiple RNA sequencing (RNA-seq) approaches, including cell type-specific, temporal bulk RNA-seq, in vivo GEO-seq, and single-cell RNA-seq (scRNA-seq), to characterize the detailed spatiotemporal transcriptome during hematopoietic stem and progenitor cell (HSPC) expansion in the caudal hematopoietic tissue (CHT) of zebrafish. Combinatorial expression profiling reveals that, in the CHT niche, HSPCs and their neighboring supporting cells are co-regulated by shared signaling pathways and intrinsic factors, such as integrin signaling and Smchd1. Moreover, scRNA-seq analysis unveils the strong association between cell cycle status and HSPC differentiation. Taken together, we report a global transcriptome landscape that provides valuable insights and a rich resource to understand HSPC expansion in an intact vertebrate hematopoietic organ. : In this work, Xue et al. establish a 3D atlas of zebrafish caudal hematopoietic tissue and reveal mechanisms underlying HSPC expansion in an intact hematopoietic organ by multi-dimensional RNA-seq. Keywords: hematopoietic stem and progenitor cell, multi-dimensional RNA-seq, 3D atlas, signaling, zebrafish

Summary: Although chronic inflammation increases many cancers’ risk, how inflammation facilitates cancer development is still not well studied. Recognizing whether and when inflamed tissues transition to cancerous tissues is of utmost importance. To unbiasedly infer molecular events, immune cell types, and secreted factors contributing to the inflammation-to-cancer (I2C) transition, we develop a computational package called “SwitchDetector” based on liver, gastric, and colon cancer I2C data. Using it, we identify angiogenesis associated with a common critical transition stage for multiple I2C events. Furthermore, we infer infiltrated immune cell type composition and their secreted or suppressed extracellular proteins to predict expression of important transition stage genes. This identifies extracellular proteins that may serve as early-detection biomarkers for pre-cancer and early-cancer stages. They alone or together with I2C hallmark angiogenesis genes are significantly related to cancer prognosis and can predict immune therapy response. The SwitchDetector and I2C database are publicly available at www.inflammation2cancer.org. : Chen et al. develop the SwitchDetector package for transcriptome module detection during inflammation-to-cancer (I2C) stage transitions. They show that angiogenesis is a common critical event for I2C in multiple cancers. The data also suggest that immune cells and secreted cytokines contribute to the I2C transition. Keywords: inflammation, cancer, network analysis, microenvironment, secreted factor, biomarker, cancer transition, immune therapy, cancer survival

A reasonable rain gauge network can provide valid precipitation information that reflects the spatial and temporal fluctuation characteristics for a given basin. Thus, it is indispensable for designing an optimal network with a minimal number of rain gauges (NRGs) in an optimal location as a means of providing reliable rainfall records, both in terms of the areal average rainfall and the spatiotemporal variability. This study presents a methodological framework that couples the ordinary kriging (OK) method and spatial correlation approach (SCA) to optimize current rain gauge networks, which involves the deletion of redundant gauges and the addition of new rain gauges in the ‘blank’ monitoring area of a basin. This framework was applied to a network of 38 rain gauges in the Jinjiang Basin in southeast China. The results indicated that: (1) the number of rain gauges was reduced from 38 to 11 by using the OK method to determine the redundant rain gauges, which were removed to obtain the ‘base’ rain gauge network. The base rain gauges were mainly distributed in the midstream of this basin. (2) The SCA and OK were employed for obtaining the number and location of new rain gauges in the ‘blank’ monitoring region, respectively. Two new rain gauges in the ‘blank’ monitoring region were identified. One rain gauge was located near the Anxi hydrological station and the other was located in the lower reaches of Anxi sub-basin, respectively. The locations of the two new rain gauges were proven to be reasonable. The number of optimal rain gauges in the Jinjiang Basin was increased to 13. The method proposed in this study provides a novel and simple approach to solve the problems of redundant rain gauges and blank monitoring areas in rain gauge networks. This method is beneficial for improving the optimization level of rain gauge networks and provides a reference for such an optimization.

Summary: Experimental large-scale screens for drug repositioning are limited by restriction to in vitro conditions and lack of applicability to real human conditions. Here, we developed an in silico screen in human in vivo conditions using a reference of single gene mutations’ non-tissue-specific “core transcriptome signatures” (CSs) of 8,476 genes generated from the TCGA database. We developed the core-signature drug-to-gene (csD2G) software to scan 3,546 drug treatment profiles against the reference signatures. csD2G significantly outperformed conventional cell line-based gene perturbation signatures and existing drug-repositioning methods in both coverage and specificity. We highlight this with 3 demonstrated applications: (1) repositioned category of psychiatric drugs to inhibit the TGF-β pathway; (2) antihypertensive calcium channel blockers predicted to activate AMPK and inhibit AKT pathways, and validated by clinical electronic medical records; and (3) 7 drugs predicted and validated to selectively target the AKT-FOXO and AMPK pathways and thus regulate worm lifespan. : Xu et al. generated core transcriptome signatures representing single-gene mutations for 8,476 human genes from the cancer transcriptomes in the TCGA database and developed a drug-repositioning method to predict high-specificity candidate target genes for 1,938 drugs. Applied to targeting aging pathways, 7 lifespan-extending drugs are found and functionally validated. Keywords: drug repositioning, drug target, cancer genomics, data integrative analysis

Guizhou Province, China, experienced several severe drought events over the period from 1960 to 2013, causing great economic loss and intractable conflicts over water. In this study, the spatial and temporal characteristics of droughts are analyzed with the standard precipitation index (SPI), comprehensive meteorological drought index (CI), and reconnaissance drought index (RDI). Meanwhile, historical drought records are used to test the performance of each index at identifying droughts. All three indices show decreasing annual and autumn trends, with the latter particularly prominent. 29, 30, and 32 drought events were identified during 1960–2013 by the SPI, CI, and RDI, respectively. Continuous drought is more frequent in winter–spring and summer–autumn. There is a significant increasing trend in drought event frequency, peak, and strength since the start of the 21st century. Drought duration indicated by CI shows longer durations in the higher-elevation region of central and western Guizhou. The corresponding drought severity is high in these regions. SPI and RDI indicate longer drought durations in the lower elevation central and eastern regions of Guizhou Province, where the corresponding drought severity is also very strong. SPI shows an increasing trend in drought duration and drought severity across most of the regions of Guizhou. In general, SPI and RDI show an increasing trend in the western Guizhou Province and a decreasing trend in central and eastern Guizhou. Comparing these three drought indices with historical records, the RDI is found to be more objective and reliable than the SPI and CI when identifying the periods of drought in Guizhou.

Using distributed hydrological models to evaluate the effectiveness of reducing non-point source pollution by applying best management practices (BMPs) is an important support to decision making for watershed management. However, complex interfaces and time-consuming simulations of the models have largely hindered the applications of these models. We designed and developed a prototype web-based decision support system for watershed management (DSS-WMRJ), which is user friendly and supports quasi-real-time decision making. DSS-WMRJ is based on integrating an open-source Web-based Geographical Information Systems (Web GIS) tool (Geoserver), a modeling component (SWAT, Soil and Water Assessment Tool), a cloud computing platform (Hadoop) and other open source components and libraries. In addition, a private cloud is used in an innovative manner to parallelize model simulations, which are time consuming and computationally costly. Then, the prototype DSS-WMRJ was tested with a case study. Successful implementation and testing of the prototype DSS-WMRJ lay a good foundation to develop DSS-WMRJ into a fully-fledged tool for watershed management. DSS-WMRJ can be easily customized for use in other watersheds and is valuable for constructing other environmental decision support systems, because of its performance, flexibility, scalability and economy.

Reservoirs are an important nitrogen sink as a result of their retention effect, but their retention performance may vary with hydrologic conditions with time-varying characteristics, which also change them from being a sink to source over time. This study uses a coupled modelling system (Soil and Water Assessment Tool (SWAT) and a two-dimensional hydrodynamic and water quality model (CE-QUAL-W2) to analyze the nitrogen retention effect and influential factors at annual, monthly, and daily scales in Shanmei Reservoir in southeast China. The results showed that there was a positive retention effect of total nitrogen (TN), nitrate-nitrogen (NO3-N) and ammonia nitrogen (NH4-N) in most years, with average retention rates up to 12.7%, 7.83% and 26.17%, respectively. The reservoir serves mainly as a nitrogen sink at an annual scale. The monthly retention performances of TN and NO3-N were observed during the wet season (April−October) with higher water temperature and lower velocity, while a release effect occurred during the dry season (November−March). For NH4-N, which is prone to nitrification, the retention effect lasted longer, from May to December. The daily nitrogen retention process changed more dramatically, with the retention rate varying from −292.49 to 58.17%. During the period of dispatch, the regulated discharge was the primary factor of daily retention performance, while the hydraulic residence time, velocity and water level were all significantly correlated with nitrogen retention during the period without dispatch.

This study developed a web-based open-source framework based on the Soil and Water Assessment Tool (SWAT), named WOF-SWAT (web-based open-source framework for SWAT), to investigate individual and combined impacts of climate change, land use change, and point-source pollutants on watershed-scale hydrological and chemical processes. The architecture, workflows, interfaces, and key processes of WOF-SWAT are described and discussed. Using a previously developed well-calibrated hydrological model of the Jinjiang River basin, four scenarios were simulated in WOF-SWAT and other traditional desktop-based tools (i.e., ArcSWAT and SWAT-CUP) to examine the credibility, efficiency, and functionality of WOF-SWAT. The results show that, in combination with a well-calibrated watershed model, WOF-SWAT is sufficiently sound and reasonable to investigate individual and combined impacts of climate change, land use change, and point-source pollutants. We thus conclude that WOF-SWAT can be used as a substitute for other tools to carry out similar tasks in a web-based environment while providing more user-friendly interfaces, accessibility, and efficiency. We also discuss ongoing and possible future efforts to develop WOF-SWAT into a fully-fledged watershed research and management framework.

Determining the amount of rainfall that will eventually become runoff and its pathway is a crucial process in hydrological modelling. We proposed a method to better estimate curve number by adding an additional component (AC) to better account for the effects of daily rainfall intensity on rainfall-runoff generation. This AC is determined by a regression equation developed from the relationship between the AC series derived from fine-tuned calibration processes and observed rainfall series. When incorporated into the Soil and Water Assessment Tool and tested in the Anxi Watershed, it is found, overall, the modified SWAT (SWAT-ICN) outperformed the original SWAT (SWAT-CN) in terms of stream flow, base flow, and annual extreme flow simulation. These models were further evaluated with the data sets of two adjacent watersheds. Similar results were achieved, indicating the ability of the proposed method to better estimate curve number.

Based on monthly streamflow and precipitation data from 1960 to 2010 in the Jinjiang River Basin of China, Standardized Precipitation Index (SPI) and Standardized Streamflow Index (SSI) were used to represent meteorological and hydrological drought, respectively. The response of hydrological drought to meteorological drought under the influence of Shanmei reservoir was investigated. The results indicate that SPI and SSI have a decreasing trend during recent several decades. Monthly scales of SSI series have a significant decreasing trend from November to the following February and a significant increasing trend from May to July at Shilong hydrological station. There are three significant periodic variations with a cycle of 6-7 years, 11-12 years, and 20-21 years for annual scales of SSI series. SPI series have the same periodic variations before the 1980s, but they have not been synchronous with SSI since the 1980s at Shilong due to influences of Shanmei reservoir, especially at the periodic variations of 20-21 years. The variation of the lag time of hydrological drought in response to meteorological drought is significant at the seasonal scale. The lag time of hydrological drought to meteorological drought extends one month on average in spring, summer, and autumn but about three months in winter.

This paper reports on a chip cooling solution using polydimethylsiloxane (PDMS) based microfluidic devices filled with n-Octadecane. A thick SU-8 layer of 150 µm is used as the master mold for patterning PDMS fabrication. With the SU-8 mold, patterns with straight lines at microscale have been fabricated with standard micro-electro-mechanical system (MEMS) technology. Thermal polymer bonding technique is used to bond the PDMS pattern directly to a flat polydimethylsiloxane (PDMS) film which results in the sealed microchannels. n-Octadecane as a phase-change material has been successfully filled in the microchannels using a dispensing machine. Infrared thermal image shows a sharp contrast of the temperature distribution between the chip with n-Octadecane and the empty chip during the same heating process. This result indicates an efficient cooling performance of the microchannel device with phase-change material. A thermal stimulation test demonstrates that a 16 °C-lower temperature difference can be achieved. This microchannel device, benefited from the flexibility of PDMS substrate, shows specific advantages in meeting the need for the heat dissipation of flexible electronics such as flexible displays, electronic skins, and wearable electronics. Latent heat of the phase-change material can keep the temperature of devices relatively lower over a period of time, which shows potential application values on discontinuously active flexible electronic devices.

Hydrological models often perform poorly in simulating dry years in regions with large inter-annual variability in rainfall. We calibrated the Soil and Water Assessment Tool (SWAT) model to dry and wet years separately, using the semi-arid Barrett watershed on the west coast of USA as an example. We used hydrological and meteorological data from 1980–2010 to calibrate the SWAT model parameters, compared the monthly runoff results simulated by SWAT using a traditional calibration for the entire runoff series with results using a calibration with the wet and dry year series, and analyzed differences in the most sensitive parameters between the wet and dry year series. The results showed that (1) the SWAT model calibrated to the entire runoff series produced significant differences in simulation efficiency between the wet years and dry years, with lower efficiency during the dry years; (2) the calibration with separate wet and dry years greatly enhanced the SWAT model’s simulation efficiency for both wet and dry years; (3) differences in hydrological conditions between wet and dry years were represented by changes in the values of the six most sensitive parameters, including baseflow recession rates, channel infiltration rates, Soil Conservation Service (SCS) curve number, soil evaporation, shallow aquifer flow, and soil water holding capacity. Future work can attempt to determine the physical processes that underlie these parameter changes and their impact on the hydrological response of the semi-arid watersheds.