The global decline in the sensitivity of vegetation productivity to precipitation from 2001 to 2018.

The sensitivity of vegetation productivity to precipitation (Sppt ) is a key metric for understanding the variations in vegetation productivity under changing precipitation and predicting future changes in ecosystem functions. However, a comprehensive assessment of Sppt over all the global land is lacking. Here, we investigated spatial patterns and temporal changes of Sppt across the global land from 2001 to 2018 with multiple streams of satellite observations. We found consistent spatial patterns of Sppt with different satellite products: Sppt was highest in dry regions while low in humid regions. Grassland and shrubland showed the highest Sppt , and evergreen needle-leaf forest and wetland showed the lowest. Temporally, Sppt showed a generally declining trend over the past two decades (p < .05), yet with clear spatial heterogeneities. The decline in Sppt was especially noticeable in North America and Europe, likely due to the increase in precipitation. In central Russia and Australia, however, Sppt showed an increasing trend. Biome-wise, most ecosystem types exhibited significant decrease in Sppt , while grassland, evergreen broadleaf forest, and mixed forest showed slight increases or non-significant changes in Sppt . Our finding of the overall decline in Sppt implies a potential stabilization mechanism for ecosystem productivity under climate change. However, the revealed Sppt increase for some regions and ecosystem types, in particular global grasslands, suggests that grasslands might be increasingly vulnerable to climatic variability with continuing global climate change.

Isotopic Insights into Organic Composition Differences between Supermicron and Submicron Sea Spray Aerosol.

To elucidate the seawater biological and physicochemical factors driving differences in organic composition between supermicron and submicron sea spray aerosol (SSAsuper and SSAsub), carbon isotopic composition (δ13C) measurements were performed on size-segregated, nascent SSA collected during a phytoplankton bloom mesocosm experiment. The δ13C measurements indicate that SSAsuper contains a mixture of particulate and dissolved organic material in the bulk seawater. After phytoplankton growth, a greater amount of freshly produced carbon was observed in SSAsuper with the proportional contribution being modulated by bacterial activity, emphasizing the importance of the microbial loop in controlling the organic composition of SSAsuper. Conversely, SSAsub exhibited no apparent relationship with biological activity but tracked closely with surface tension measurements probing the topmost ∼0.2-1.5 µm of the sea surface microlayer. This probing depth is similar to a bubble's film thickness at the ocean surface, suggesting that SSAsub organic composition may be influenced by the presence of surfactants at the air-sea interface that are transferred into SSAsub by bubble bursting. Our findings illustrate the substantial impact of seawater dynamics on the pronounced organic compositional differences between SSAsuper and SSAsub and demonstrate that these two SSA populations should be considered separately when assessing their contribution to marine aerosols and climate.

An Epidemiologic Survey and Violent Behavior Analysis of Antisocial Personality Disorder in Young Men in Chengdu.

OBJECTIVES: To investigate the epidemiological characteristics of antisocial personality disorder (ASPD) in young men in Chengdu and explore the characteristics and risks of violence. METHODS: Stratified random sampling was used to conduct a self-assessment questionnaire survey in 4 108 males aged from 18 to 34 in Chengdu, including general demographic characteristics, structured clinical interview for the diagnostic and statistical manual of mental disorders-Ⅳ axis Ⅱ disorders (SCID-Ⅱ) personality disorder screen questionnaire, violence questionnaire, psychosis screening questionnaire (PSQ), Alcohol Use Disorders Identification Test (AUDIT) and drug use. χ2 test, univariate and multivariate logistic regression were used for analysis and odds ratio (OR) was calculated. RESULTS: The positive rate of ASPD was 5.91%, which was associated with young age, unmarried, unemployment state, low educational level, violent behavior, psychotic symptoms, alcohol and drug use (P<0.05). Young men with ASPD also had a risk (P<0.05) of violence (OR was 8.51), multiple violence (OR was 16.57), injury (OR was 6.68), intentional violence (OR was 11.41), etc., the risk decreased after controlling for psychotic symptoms and substance abuse, but was still statistically significant. CONCLUSIONS: The risk of violence, severe violence and intentional violence in young men in Chengdu is high, and psychotic symptoms and substance abuse increase the risk of ASPD violence and relate characteristics.

Profiling the differences of gut microbial structure between schizophrenia patients with and without violent behaviors based on 16S rRNA gene sequencing.

Understanding the violence behaviors in schizophrenia patients has always been the focus of forensic psychiatry. Although many studies show gut microbiota could regulate behavior, to our knowledge, no studies have profiled the gut microbiota structure in schizophrenia patients with violence. We profiled the characteristics of gut microbiota structure in 26 schizophrenia patients with violence (V.SCZ) by comparing with that of 16 schizophrenia patients without violence (NV.SCZ) under the control of confounders, and found the differences of gut microbiota structure between the two groups. Violence was assessed by the MacArthur Community Violence Instrument. Psychiatric symptoms were assessed by the Positive and Negative Syndrome Scale. The 16S rRNA gene sequencing was used to identify and relatively quantify gut microbial composition. Bioinformatics analysis was used to find differential gut microbial composition between the V.SCZ and NV.SCZ groups. Fifty-nine differential microbial taxonomic compositions were found between the two groups. Fifteen gut microbial compositions were the key microbial taxonomic compositions responsible for the differences between the V.SCZ and NV.SCZ groups, including five enriched microbial taxonomic compositions (p_Bacteroidetes, c_Bacteroidia, o_Bacteroidales, f_Prevotellaceae, s_Bacteroides_uniformis), and ten impoverished microbial taxonomic compositions (p_Actinobacteria, c_unidentified_Actinobacteria, o_Bifidobacteriales, f_ Enterococcaceae, f_Veillonellaceae, f_Bifidobacteriaceae, g_Enterococcus, g_Candidatus_Saccharimonas, g_Bifidobacterium, and s_Bifidobacterium_pseudocatenulatum). This study profiled the differences of gut microbiota between schizophrenia patients with violence and without violence. These results could enrich the etiological understanding of violence in schizophrenia and might be helpful to violence management in the future.

Dysregulation of amino acids and lipids metabolism in schizophrenia with violence.

BACKGROUND: Many studies have related biochemical characteristics to violence and have reported schizophrenia could elevated the risk of violent behaviour. However, the metabolic characteristics of schizophrenia patients with violence (V.SC) are unclear. METHODS: To explore the metabolic characteristics of schizophrenia with violence and to identify potential biomarkers, untargeted metabolomics was performed by using gas chromatography time-of-flight mass spectrometry to analyse the plasma metabolites of fifty-three V.SC and twenty-four schizophrenia patients without violence (NV.SC). Multivariate and univariate analyses were performed to identify differential metabolites and biomarkers. Violence was assessed by the MacArthur Violence Assessment Study method. Psychiatric symptoms were assessed by the Positive and Negative Syndrome Scale. RESULTS: Multivariate analysis was unable to distinguish V.SC from NV.SC. Glycerolipid metabolism and phenylalanine, tyrosine and tryptophan biosynthesis were the differential metabolic pathways between V.SC and NV.SC. We confirmed ten metabolites and five metabolites as metabolic biomarkers of V.SC by random forest and support vector machine analysis, respectively. The biomarker panel, including the ratio of L-asparagine to L-aspartic acid, vanillylmandelic acid and glutaric acid, yielded an area under the receiver operating characteristic curve of 0.808. CONCLUSIONS: This study gives a holistic view of the metabolic phenotype of schizophrenia with violence which is characterized by the dysregulation of lipids and amino acids. These results might provide information for the aetiological understanding and management of violence in schizophrenia; however, this is a preliminary metabolomics study about schizophrenia with violence, which needs to be repeated in future studies.

Revealing the spatio-temporal variability of evapotranspiration and its components based on an improved Shuttleworth-Wallace model in the Yellow River Basin.

Identifying the spatio-temporal variations of evapotranspiration (ET) from its components (soil evaporation and plant transpiration) can greatly improve our understanding of water-cycle and biogeochemical processes. However, partitioning evapotranspiration into evaporation (E) and transpiration (T) at regional scale with high accuracy still remains a challenge. This study has aimed to reveal the spatio-temporal variations of evapotranspiration and its components by using an improved Shuttleworth-Wallace (SWH) model to partition ET in the Yellow River Basin during 1981-2010. The environmental factors affecting the spatial and temporal variations of evapotranspiration and its components were also assessed. Results showed that the mean annual ET, T and E in the Yellow River Basin were 372.18 mm, 179.64 mm, and 192.54 mm, respectively, over the last 30 years. The spatial pattern of mean annual ET and T displayed a decreasing trend from southeast to northwest in the Yellow River Basin, and the temporal variation showed a significant increasing trend with rates of 1.72 mm yr-1 and 1.54 mm yr-1, respectively. It meant that T accounted for the variations of ET, while E showed no significant changes in recent decades. Moreover, the normalized differential vegetation index (NDVI) and temperature were identified as the main factors controlling the variations of ET and T in the Yellow River Basin. Among them, the area with NDVI as the dominant factor for ET and T could reach 63.82% and 78.47% of the whole basin respectively. However, the variations of E were affected by complex factors, and evaporation in the western alpine region was mainly controlled by temperature. Our findings are expected to not only have implications for developing sustainable policies of water management and ecological restoration in this region, but also provide valuable insight in methodology of ET partitioning in regional or global scale.

Sensor-Aware Recognition and Tracking for Wide-Area Augmented Reality on Mobile Phones.

Wide-area registration in outdoor environments on mobile phones is a challenging task in mobile augmented reality fields. We present a sensor-aware large-scale outdoor augmented reality system for recognition and tracking on mobile phones. GPS and gravity information is used to improve the VLAD performance for recognition. A kind of sensor-aware VLAD algorithm, which is self-adaptive to different scale scenes, is utilized to recognize complex scenes. Considering vision-based registration algorithms are too fragile and tend to drift, data coming from inertial sensors and vision are fused together by an extended Kalman filter (EKF) to achieve considerable improvements in tracking stability and robustness. Experimental results show that our method greatly enhances the recognition rate and eliminates the tracking jitters.

Subject-Independent EEG Classification of Motor Imagery Based on Dual-Branch Feature Fusion.

A brain computer interface (BCI) system helps people with motor dysfunction interact with the external environment. With the advancement of technology, BCI systems have been applied in practice, but their practicability and usability are still greatly challenged. A large amount of calibration time is often required before BCI systems are used, which can consume the patient's energy and easily lead to anxiety. This paper proposes a novel motion-assisted method based on a novel dual-branch multiscale auto encoder network (MSAENet) to decode human brain motion imagery intentions, while introducing a central loss function to compensate for the shortcomings of traditional classifiers that only consider inter-class differences and ignore intra-class coupling. The effectiveness of the method is validated on three datasets, namely BCIIV2a, SMR-BCI and OpenBMI, to achieve zero calibration of the MI-BCI system. The results show that our proposed network displays good results on all three datasets. In the case of subject-independence, the MSAENet outperformed the other four comparison methods on the BCIIV2a and SMR-BCI datasets, while achieving F1_score values as high as 69.34% on the OpenBMI dataset. Our method maintains better classification accuracy with a small number of parameters and short prediction times, and the method achieves zero calibration of the MI-BCI system.

Catalytic oxidation of polystyrene to aromatic oxygenates over a graphitic carbon nitride catalyst.

The continuous increase in manufacturing coupled with the difficulty of recycling of plastic products has generated huge amounts of waste plastics. Most of the existing chemical recycling and upcycling methods suffer from harsh conditions and poor product selectivity. Here we demonstrate a photocatalytic method to oxidize polystyrene to aromatic oxygenates under visible light irradiation using heterogeneous graphitic carbon nitride catalysts. Benzoic acid, acetophenone, and benzaldehyde are the dominant products in the liquid phase when the conversion of polystyrene reaches >90% at 150 °C. For the transformation of 0.5 g polystyrene plastic waste, 0.36 g of the aromatic oxygenates is obtained. The reaction mechanism is also investigated with various characterization methods and procedes via polystyrene activation to form hydroxyl and carbonyl groups over its backbone via C-H bond oxidation which is followed by oxidative bond breakage via C-C activation and further oxidation processes to aromatic oxygenates.

Atomically dispersed Ir/α-MoC catalyst with high metal loading and thermal stability for water-promoted hydrogenation reaction.

Synthesis of atomically dispersed catalysts with high metal loading and thermal stability is challenging but particularly valuable for industrial application in heterogeneous catalysis. Here, we report a facile synthesis of a thermally stable atomically dispersed Ir/α-MoC catalyst with metal loading as high as 4 wt%, an unusually high value for carbide supported metal catalysts. The strong interaction between Ir and the α-MoC substrate enables high dispersion of Ir on the α-MoC surface, and modulates the electronic structure of the supported Ir species. Using quinoline hydrogenation as a model reaction, we demonstrate that this atomically dispersed Ir/α-MoC catalyst exhibits remarkable reactivity, selectivity and stability, for which the presence of high-density isolated Ir atoms is the key to achieving high metal-normalized activity and mass-specific activity. We also show that the water-promoted quinoline hydrogenation mechanism is preferred over the Ir/α-MoC, and contributes to high selectivity towards 1,2,3,4-tetrahydroquinoline. The present work demonstrates a new strategy in constructing a high-loading atomically dispersed catalyst for the hydrogenation reaction.

Vegetation resistance and resilience to a decade-long dry period in the temperate grasslands in China.

The duration of climate anomalies has been increasing across the globe, leading to ecosystem function loss. Thus, we need to understand the responses of the ecosystem to long-term climate anomalies. It remains unclear how ecosystem resistance and resilience respond to long-term climate anomalies, for example, continuous dry years at a regional scale. Taking the opportunity of a 13-year dry period in the temperate grasslands in northern China, we quantified the resistance and resilience of the grassland in response to this periodic dry period. We found vegetation resistance to the dry period increased with mean annual precipitation (MAP), while resilience increased at first until at MAP of 250 mm and then decreased slightly. No trade-off between resistance and resilience was detected when MAP < 250 mm. Our results highlight that xeric ecosystems are most vulnerable to the long-term dry period. Given expected increases in drought severity and duration in the coming decades, our findings may be helpful to identify vulnerable ecosystems in the world for the purpose of adaptation.

Fe5C2 nanoparticles as low-cost HER electrocatalyst: the importance of Co substitution.

Constructing and understanding the doping effect of secondary metal in transition metal carbide (TMC) catalysts is pivotal for the design of low-cost hydrogen evolution reaction (HER) electrocatalysts. In this work, we developed a wet-chemistry strategy for synthesizing Co-modified Fe5C2 nanoparticles ((Fe1-xCox)5C2 NPs) as highly active HER electrocatalysts in basic solution. The structure of (Fe1-xCox)5C2 NPs was characterized by X-ray diffraction (XRD), extended X-ray absorption fine structure spectra (EXAFS) and scanning/transmission electron microscopy (S/TEM), indicating that the isomorphous substitution of cobalt in the lattice of Fe5C2. (Fe0.75Co0.25)5C2 exhibited the best HER activity (174 mV for j = -10 mA/cm2). Computational calculation results indicate that Co provides the most active site for HER. X-ray adsorption spectra (XAS) studies further suggested that the electron transfer in Fe-C bonds are enhanced by the substitution of Co, which modulates the hydrogen adsorption on the adjacent electronic-enriched carbon, and therefore promotes HER activity. Our results affirm the design of low-cost bimetallic TMCs based HER catalysts.