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Developing advanced electrocatalysts to convert CO2 into liquid fuels such as ethanol is critical for utilizing intermittent renewable energy. The formation of ethanol, however, is generally less f...

Fine-grained inner-annual population data are instrumental in climate change response, resource allocation, and epidemic control. However, such data are currently scarce due to the lack of human-re...

Land surface hydrothermal conditions (LSHCs) reflect land surface moisture and heat conditions, and play an important role in energy and water cycles in soil-plant-atmosphere continuum. Based on comparison of four evaluation methods (namely, the classic statistical method, geostatistical method, information theory method, and fractal method), this study proposed a new scheme for evaluating the spatial heterogeneity of LSHCs. This scheme incorporates diverse remotely sensed surface parameters, e.g., leaf area index-LAI, the normalized difference vegetation index-NDVI, net radiation-Rn, and land surface temperature-LST. The LSHCs can be classified into three categories, namely homogeneous, moderately heterogeneous and highly heterogeneous based on the remotely sensed LAI data with a 30 m spatial resolution and the combination of normalized information entropy (S′) and coefficient of variation (CV). Based on the evaluation scheme, the spatial heterogeneity of land surface hydrothermal conditions at six typical flux observation stations in the Heihe River Basin during the vegetation growing season were evaluated. The evaluation results were consistent with the land surface type characteristics exhibited by Google Earth imagery and spatial heterogeneity assessed by high resolution remote sensing evapotranspiration data. Impact factors such as precipitation and irrigation events, spatial resolutions of remote sensing data, heterogeneity in the vertical direction, topography and sparse vegetation could also affect the evaluation results. For instance, short-term changes (precipitation and irrigation events) in the spatial heterogeneity of LSHCs can be diagnosed by energy factors, while long-term changes can be indicated by vegetation factors. The spatial heterogeneity of LSHCs decreases when decreasing the spatial resolution of remote sensing data. The proposed evaluation scheme would be useful for the quantification of spatial heterogeneity of LSHCs over flux observation stations toward the global scale, and also contribute to the improvement of the accuracy of estimation and validation for remotely sensed (or model simulated) evapotranspiration.

Highlights Nanocapsules made from metal–organic frameworks were designed for sustained release of additive (LiNO3) to passivate Li anode in commercial carbonate-based electrolyte.The nanocapsules with continuous supply of LiNO3 formed a nitride-rich solid electrolyte interphase layer on Li anode and persistently remedied the interphase during prolonged cycling.The practical Li-metal full cell delivered a prolonged lifespan with 90% capacity retention after 240 cycles which has been hardly achieved in commercial electrolyte. Electronic supplementary material The online version of this article (10.1007/s40820-020-00514-1) contains supplementary material, which is available to authorized users., A robust solid-electrolyte interphase (SEI) enabled by electrolyte additive is a promising approach to stabilize Li anode and improve Li cycling efficiency. However, the self-sacrificial nature of SEI forming additives limits their capability to stabilize Li anode for long-term cycling. Herein, we demonstrate nanocapsules made from metal–organic frameworks for sustained release of LiNO3 as surface passivation additive in commercial carbonate-based electrolyte. The nanocapsules can offer over 10 times more LiNO3 than the solubility of LiNO3. Continuous supply of LiNO3 by nanocapsules forms a nitride-rich SEI layer on Li anode and persistently remedies SEI during prolonged cycling. As a result, lifespan of thin Li anode in 50 μm, which experiences drastic volume change and repeated SEI formation during cycling, has been notably improved. By pairing with an industry-level thick LiCoO2 cathode, practical Li-metal full cell demonstrates a remarkable capacity retention of 90% after 240 cycles, in contrast to fast capacity drop after 60 cycles in LiNO3 saturated electrolyte. Electronic supplementary material The online version of this article (10.1007/s40820-020-00514-1) contains supplementary material, which is available to authorized users.

As an essential chemical feedstock, aromatics can be obtained from biomass by catalytic fast pyrolysis (CFP) technology, in which diffusion limitation is still a problem. In this study, several ZSM-5 zeolites with intercrystal stacking macropores were synthesized by adding organosilanes (OSAs) with different alkyl chain groups. Due to the structure-directing effect of the OSA, the prepared ZSM-5 zeolites possess a larger external surface area and pore volume than Blank-Z5. Moreover, the pore size is related to the extent of anchoring of the OSA and silicon-aluminum species in the zeolite precursor. Pyridine Fourier transform infrared (Py-FTIR) and NH

As the COVID-19 pandemic comes to an end, governments find themselves facing a new challenge: motivating citizens to resume economic activity. What is an effective way to do so? We investigate this question using a field experiment in the city of Zhengzhou, China, immediately following the end of the city’s COVID-19 lockdown. We assessed the effect of a descriptive norms intervention providing information about the proportion of participants’ neighbors who have resumed economic activity. We find that informing individuals about their neighbors’ plans to visit restaurants increases the fraction of participants visiting restaurants by 12 percentage points (37%), among those participants who underestimated the proportion of neighbors who resumed economic activity. Those who overestimated did not respond by reducing restaurant attendance (the intervention yielded no “boomerang” effect); thus, our descriptive norms intervention yielded a net positive effect. We explore the moderating role of risk preferences and the effect of the intervention on subjects’ perceived risk of going to restaurants, as well as the contrast with an intervention for parks, which were already perceived as safe. All of these analyses suggest our intervention worked by reducing the perceived risk of going to restaurants.

The COVID-19 pandemic has created unprecedented burdens on people’s physical health and subjective well-being. While countries worldwide have developed platforms to track the evolution of COVID-19 infections and deaths, frequent global measurements of affective states to gauge the emotional impacts of pandemic and related policy interventions remain scarce. Using 654 million geotagged social media posts in over 100 countries, covering 74% of world population, coupled with state-of-the-art natural language processing techniques, we develop a global dataset of expressed sentiment indices to track national- and subnational-level affective states on a daily basis. We present two motivating applications using data from the first wave of COVID-19 (from 1 January to 31 May 2020). First, using regression discontinuity design, we provide consistent evidence that COVID-19 outbreaks caused steep declines in expressed sentiment globally, followed by asymmetric, slower recoveries. Second, applying synthetic control methods, we find moderate to no effects of lockdown policies on expressed sentiment, with large heterogeneity across countries. This study shows how social media data, when coupled with machine learning techniques, can provide real-time measurements of affective states.

The rampant COVID-19 pandemic swept the globe rapidly in 2020, causing a tremendous impact on human health and the global economy. This pandemic has stimulated an explosive increase of related studies in various disciplines, including geography, which has contributed to pandemic mitigation with a unique spatiotemporal perspective. Reviewing relevant research has implications for understanding the contribution of geography to COVID-19 research. The sheer volume of publications, however, makes the review work more challenging. Here we use the support vector machine and term frequency-inverse document frequency algorithm to identify geographical studies and bibliometrics to discover primary research themes, accelerating the systematic review of COVID-19 geographical research. We confirmed 1,171 geographical papers about COVID-19 published from 1 January 2020 to 31 December 2021, of which a large proportion are in the areas of geographic information systems (GIS) and human geography. We identified four main research themes—the spread of the pandemic, social management, public behavior, and impacts of the pandemic—embodying the contribution of geography. Our findings show the feasibility of machine learning methods in reviewing large-scale literature and highlight the value of geography in the fight against COVID-19. This review could provide references for decision makers to formulate policies combined with spatial thinking and for scholars to find future research directions in which they can strengthen collaboration with geographers.

The electrochemical reduction of CO to methanol is a potentially cost-effective strategy to reduce the concentration of this greenhouse gas while at the same time producing a value-added chemical. Herein, we detail a highly efficient 2D nickel organic framework containing a large density of highly dispersed salophen NiNO active sites toward electrochemical CORR to methanol. By tuning the ligand environment of the salophen NiNO, the electrocatalytic activity of the material toward CO reduction can be significantly improved. We prove that by introducing a carbonyl group at the ligand environment of the Ni active sites, the electrochemical CO reduction activity is highly promoted and its product selectivity reaches a Faradaic efficiency of 27% toward the production of methanol at − 0.9 V vs RHE. The salophen-based π-d conjugated metal-organic framework presented here thus provides the best performance toward CO reduction to methanol among the previously developed nickel-based electrocatalysts., ICN2 is supported by the Severo Ochoa program from Spanish MINECO (Grant No. SEV-2017-0706) and is funded by the CERCA Programme/Generalitat de Catalunya. Part of the present work has been performed in the framework of Universitat Autònoma de Barcelona Materials Science PhD program. Z. Liang acknowledges funding from MINECO SO-FPT PhD grant (SEV-2013-0295-17-1). This project has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No 823717-ESTEEM3. The present work is supported by the I+D+I projects PID2019-105490RB-C32 and NANOGEN (PID2020-116093RB-C43), funded by MCIN/AEI/10.13039/501100011033/ and by “ERDF A way of making Europe”, by the “European Union”. X. Wang thanks the China Scholarship Council for the scholarship support. P. Tang acknowledges the Humboldt Research Fellowship. Authors acknowledge funding from Generalitat de Catalunya 2017SGR327 and 2017SGR1246. L. L acknowledges the support from Natural Sciences and Engineering Research Council Canada (NSERC, DG RGPIN-2020-06675). J. Llorca is a Serra Húnter Fellow and is grateful to MICINN/FEDER RTI2018-093996-B-C31, GC 2017 SGR 128 and to ICREA Academia Program. XAFS measurements were performed at the Canadian Light Source, a national research facility at the University of Saskatchewan, which is supported by the Canada Foundation for Innovation (CFI), the Natural Sciences and Engineering Research Council (NSERC), the National Research Council (NRC), the Canadian Institutes of Health Research (CIHR), the Government of Saskatchewan, and the University of Saskatchewan. W. Tang acknowledges the Chinese Postdoctoral Science Foundation (Nos. 2021M691008).This study was supported by MCIN with funding from European Union NextGenerationEU (PRTR-C17.I1) and Generalitat de Catalunya.

Non-pharmaceutical interventions (NPIs) and vaccination are two fundamental approaches to mitigate the coronavirus disease 2019 (Covid-19) pandemic. Vaccination strategies are generally less costly and socially/economically disruptive than NPI strategies, such as business closures, social distancing, and face mask mandates, as evidenced by highly vaccinated countries generally rolling back NPIs. However, the respective real-world impact of an NPI strategy versus vaccination strategy, or the combination of both, on mitigating Covid-19 transmission remains uncertain. To address this, we built a Bayesian inference model to explore the changing effectiveness of NPIs and vaccination based on the assembled large-scale dataset, including epidemiological parameters, variants, vaccines, and control variable. Here we show that NPIs were still considerably complementary or even synergistic to vaccination in the effort to curb the Covid-19 infection before reaching herd immunity. We found that (1) the synergistic effect of NPIs and vaccination was 46.9% (reduction in reproduction number) in September 2021, whereas the effects of NPIs and vaccination alone were 20.7% and 28.8%, respectively; (2) effectiveness of NPIs is less sensitive to emerging COVID-19 variants but decreases with vaccination progress, as NPIs may unnecessarily restrict the vaccinated population. The effectiveness of NPIs alone declined approximately 23% since the introduction of vaccination strategies, where the relaxation of NPIs promoted the decline from May 2021. Our results demonstrate that the decision to relax NPIs should consider the real-world vaccination rate of the relevant population, which is determined by the observed vaccine efficacy in relation to extant and emerging variants.

BACKGROUND COVID-19, as a global health crisis, has triggered the fear emotion with unprecedented intensity. Besides the fear of getting infected, the outbreak of COVID-19 also created significant disruptions in people’s daily life and thus evoked intensive psychological responses indirect to COVID-19 infections. OBJECTIVE This study aims to develop novel digital trackers of public fear emotion during the COVID-19 pandemic, and to uncover meaningful topics that the citizens are concerned about to inform policy decision-making. METHODS We construct an expressed fear database using 16 million social media posts generated by 536 thousand users in China between January 1st, 2019 and August 31st, 2020. We employ Bidirectional Encoder Representations from Transformers (BERT) to detect the fear emotion within each post and apply BERTopic to extract the central fear topics. RESULTS We find that on average, 2.45% of posts per day having fear as the dominant emotion in 2019. This share spiked after the COVID-19 outbreak and peaked at 9.1% on the date that China’s epi-center Wuhan city announced lockdown. Among the fear posts, topics related to health takes the largest share (39%). Specifically, we find that posts regarding sleep disorders (Nightmare and Insomnia) have the most significant increase during the pandemic. We also observe gender heterogeneity in fear topics, with females being more concerned with health while males being more concerned with job. CONCLUSIONS Our work leverages the social media data coupled with computational methods to track the emotional response on a large scale and with high temporal granularity. While we conduct this research in a tracing back mode, it is possible to use such a method to achieve real-time emotion monitoring, thus serving as a helpful tool to discern societal concerns and aid for policy decision-making.

Background Metagenomic next-generation sequencing (mNGS) offers the promise of unbiased detection of emerging pathogens. However, in indexed sequencing, the sequential paradigm of data acquisition, demultiplexing, and analysis restrain read assignment in advance and real-time analysis, resulting in lengthy turnaround time for clinical metagenomic detection. Methods We described the utility of internal-index adaptors with different lengths of barcode in multiplex sequencing. The base composition for each position within these adaptors was well-balanced to ensure nucleotide diversity and optimal sequencing performance and to achieve the early assignment of reads by first sequencing the barcodes. Combined with an automated library preparation device, we delivered a rapid and real-time bioinformatics pathogen identification solution for the Illumina NextSeq platform. The diagnostic performance was evaluated by testing 153 lower respiratory tract specimens using mNGS in comparison to culture, 16S/internal transcribed spacer amplicon sequencing, and additional PCR-based tests. Results By calculating the average F1 scores of all read lengths under different threshold values, we established the optimal threshold for pathogens identification, and found that 36 bp was the optimal shortest read length for rapid mNGS analysis. Rapid detection had a negative percentage agreement and positive percentage agreement of 100% and 85.1% for bacteria and 97.4% and 80.3% for fungi, when compared to a composite standard. The rapid mNGS solution enabled accurate pathogen identification in about 9.1 to 10.1 h sample-to-answer turnaround time. Conclusions Optimized internal index adaptors combined with a real-time analysis pipeline provide a potential tool for a first-line test in critically ill patients.

COVID-19, as a global health crisis, has triggered the fear emotion with unprecedented intensity. Besides the fear of getting infected, the outbreak of COVID-19 also created significant disruptions in people's daily life and thus evoked intensive psychological responses indirect to COVID-19 infections. Here, we construct an expressed fear database using 16 million social media posts generated by 536 thousand users between January 1st, 2019 and August 31st, 2020 in China. We employ deep learning techniques to detect the fear emotion within each post and apply topic models to extract the central fear topics. Based on this database, we find that sleep disorders ("nightmare" and "insomnia") take up the largest share of fear-labeled posts in the pre-pandemic period (January 2019-December 2019), and significantly increase during the COVID-19. We identify health and work-related concerns are the two major sources of fear induced by the COVID-19. We also detect gender differences, with females generating more posts containing the daily-life fear sources during the COVID-19 period. This research adopts a data-driven approach to trace back public emotion, which can be used to complement traditional surveys to achieve real-time emotion monitoring to discern societal concerns and support policy decision-making., 15 pages

The properties of geographical phenomena vary with changes in the scale of measurement. The information observed at one scale often cannot be directly used as information at another scale. Scaling addresses these changes in properties in relation to the scale of measurement, and plays an important role in Earth sciences by providing information at the scale of interest, which may be required for a range of applications, and may be useful for inferring geographical patterns and processes. This paper presents a review of geospatial scaling methods for Earth science data. Based on spatial properties, we propose a methodological framework for scaling addressing upscaling, downscaling and side-scaling. This framework combines scale-independent and scale-dependent properties of geographical variables. It allows treatment of the varying spatial heterogeneity of geographical phenomena, combines spatial autocorrelation and heterogeneity, addresses scale-independent and scale-dependent factors, explores changes in information, incorporates geospatial Earth surface processes and uncertainties, and identifies the optimal scale(s) of models. This study shows that the classification of scaling methods according to various heterogeneities has great potential utility as an underpinning conceptual basis for advances in many Earth science research domains. © 2019 Elsevier B.V.

It is crucial to develop highly sensitive and selective sensors for ammonia, one of the most common toxic gases which have been widely used in pharmaceutical, chemical, and manufacturing industries. In this study, graphene oxide (GO) film was spin-coated onto surfaces of ST-cut quartz surface acoustic wave (SAW) devices with a resonant frequency of 200 MHz for ammonia sensing. The oxygen-containing functional groups (such as hydroxyl and epoxy ones) on the surface of GO film strongly absorb ammonia molecules and thus increase the film stiffness. This is attributed to the main ammonia sensing mechanism of the Love mode SAW devices, which show not only a positive frequency shift of 620 Hz for 500 ppb ammonia gas, but also an excellent selectivity (as compared to other gases such as H2, H2S, CO, and NO2) and a good reproducibility, operated at room temperature of 22 °C.

Cities offer a large menu of possible employment and leisure opportunities. The gains from such consumer city leisure are likely to be lower on more polluted days. We study the association between daily consumption activity and outdoor air pollution in China and find evidence in favor of the hypothesis that clean air and leaving one's home for leisure trips are complements. Given the high levels of air pollution in cities in the developing world, regulation induced improvement in environmental quality is likely to further stimulate demand for the consumer city.

Constructing heterojunction semiconductor materials with a strong interfacial interaction are emerging as a forefront strategy for promoting excellent photocatalytic performance. Herein, we report a novel SnS2/SnO2 heterojunction material via in-situ trace vulcanization strategy to coat SnS2 on the SnO2. The thickness of the coating layer can be regulated by controlling the content of SnS2. Moreover, molar ratio of S to Sn, particle size of SnO2 precursor, and vulcanization time that governs the SnS2 content of heterojunction catalyst were controlled to optimize photocatalytic performance. SnS2/SnO2 heterojunction catalyst with 19.5% SnS2 content delivered a ultrahigh visible-light activity in Cr(VI) degradation, remarkably superior to the inert SnO2 precursors and full-vulcanized SnS2 under identical testing conditions. The enhanced interfacial interaction can remarkably enhance the separation and transfer of photogenerated charges. The systematic methodology of interface regulation in SnS2/SnO2 system reported in this work would promote the understanding of nano-heterojunction material for high-performance water treatment application.

Public transit is viewed as a potential means to mitigate traffic congestion and its resulting air pollution and health consequences. A recent wave of studies has emerged examining whether this public investment can achieve its goals. Employing the difference in difference method, this paper examines the medium-term effect of the opening of a completely new subway line on local air pollution in Changsha. Our findings show that carbon monoxide pollution, one key type of automobile pollution in areas close to the subway line experienced a greater reduction relative to areas further away from the stations in the first year after the subway line opened. However, there is no evidence that the opening of the subway line affected particulate matter or ozone pollution. Heterogeneity effects support that air pollution reduction resulted from substituting subway use for road use.

A coupled Alice–Bob modified Korteweg de-Vries (mKdV) system is established from the mKdV equation in this paper, which is nonlocal and suitable to model two-place entangled events. The Lax integra...

Inter-component communication (ICC) among Android apps is shown to be the source of many security vulnerabilities. Prior research has developed compositional analyses to detect the existence of ICC vulnerabilities in a set of installed apps. However, they all lack the ability to efficiently respond to incremental system changes—such as adding/removing apps. Every time the system changes, the entire analysis has to be repeated, making them too expensive for practical use, given the frequency with which apps are updated, installed, and removed on a typical Android device. This paper presents a novel technique, dubbed FLAIR, for efficient, yet formally precise, security analysis of Android apps in response to incremental system changes. Leveraging the fact that the changes are likely to impact only a small fraction of the prior analysis results, FLAIR recomputes the analysis only where required, thereby greatly improving analysis performance without sacrificing the soundness and completeness thereof. Our experimental results using numerous collections of real-world apps corroborate that FLAIR can provide an order of magnitude speedup over prior techniques.

BackgroundThe effect of the COVID-19 outbreak has led policymakers around the world to attempt transmission control. However, lockdown and shutdown interventions have caused new social problems and designating policy resumption for infection control when reopening society remains a crucial issue. We investigated the effects of different resumption strategies on COVID-19 transmission using a modeling study setting.MethodsWe employed a susceptible-exposed-infectious-removed model to simulate COVID-19 outbreaks under five reopening strategies based on China’s business resumption progress. The effect of each strategy was evaluated using the peak values of the epidemic curves vis-à-vis confirmed active cases and cumulative cases. Two-sample t-test was performed in order to affirm that the pick values in different scenarios are different.ResultsWe found that a hierarchy-based reopen strategy performed best when current epidemic prevention measures were maintained save for lockdown, reducing the peak number of active cases and cumulative cases by 50 and 44%, respectively. However, the modeled effect of each strategy decreased when the current intervention was lifted somewhat. Additional attention should be given to regions with significant numbers of migrants, as the potential risk of COVID-19 outbreaks amid society reopening is intrinsically high.ConclusionsBusiness resumption strategies have the potential to eliminate COVID-19 outbreaks amid society reopening without special control measures. The proposed resumption strategies focused mainly on decreasing the number of imported exposure cases, guaranteeing medical support for epidemic control, or decreasing active cases.

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Understanding the cost-effectiveness of possible interventions to reduce air pollution levels is crucial to developing sustainable mitigation and adaption strategies. Although people spend more than 80% of their time indoors, the role of air purifiers in mitigating personal exposure to indoor PM2.5 of outdoor origin has not yet been quantified, especially in under-developed regions. Here, we performed a comprehensive simulation at the 10 km × 10 km geographical resolution in mainland China to quantify the health benefits and costs of indoor air purification in four intervention scenarios, S1 to S4, where target indoor PM2.5 concentrations were 35, 25, 15, and 10 μg/m3. In intervention scenarios S1 to S4, 93,200 (95% uncertainty interval 78,900–113,600), 115,300 (97,700−140,800), 163,400 (138,300−198,800), and 207,900 (176,300−251,800) deaths that cost 82, 175, 438, and 798 billion Chinese Yuan can be avoided and 93%, 80%, 53%, and 26% of the cities have a positive net monetary benefit. We found that achieving indoor PM2.5 concentration of 35 or 25 μg/m3 using air purifiers is cost-effective at reducing PM2.5 related deaths and PM2.5 concentration of 25 μg/m3 is a suitable indoor PM2.5 target for China. Multifaceted efforts are necessary to ensure equitable access to air purifiers and the knowledge to effectively operate them to make sure the benefits reach the whole population.

Soil organic carbon (SOC) is the most critical component of global carbon cycle in grassland ecosystems. There has been growing interest in understanding SOC dynamics and driving forces of grassland biomes at various temporal and spatial scales. Up to now, estimates of long‐term and large‐scale changes in SOC of grassland biomes have been mostly based on modeling approaches and manipulative experiments, rather than direct measurements. During 2007–2011, we repeated 141 soil profiles of the sampling in 1963–1964 (up to 1‐m depth) to quantify the long‐term changes of SOC storage in the major grassland types of Inner Mongolia in order to tease apart the relative contributions of climate change and grazing. We found that SOC decreased in all soil types, except in the eolian sandy soils, from 1963 to 2007, with an average reduction rate of 1.8 kg C m−2 (~22.9% or 0.52% year−1) in the grassland biome of Inner Mongolia. We quantitatively clustered the soils into four groups using principal component analysis (PCA) and detected clear spatial dependency of the changes on climate and grazing. The climate change was responsible for 15.3–34.9% of the total SOC variations, whereas grazing intensity accounted for

The effect of the COVID-19 outbreak has led policymakers around the world to attempt transmission control. However, lockdown and shutdown interventions have caused new social problems and designating policy resumption for infection control when reopening society remains a crucial issue. We investigated the effects of different resumption strategies on COVID-19 transmission using a modeling study setting. We employed a susceptible-exposed-infectious-removed model to simulate COVID-19 outbreaks under five reopening strategies based on China’s business resumption progress. The effect of each strategy was evaluated using the peak values of the epidemic curves vis-à-vis confirmed active cases and cumulative cases. We found that a hierarchy-based reopen strategy performed best when current epidemic prevention measures were maintained save for lockdown, reducing the peak number of active cases and cumulative cases by 50% and 44%, respectively. However, the modeled effect of each strategy decreased when the current intervention was lifted somewhat. Additional attention should be given to regions with significant numbers of migrants, as the potential risk of COVID-19 outbreaks amid society reopening is intrinsically high. Business resumption strategies have the potential to eliminate COVID-19 outbreaks amid society reopening without special control measures. The proposed resumption strategies focused mainly on decreasing the number of imported exposure cases, guaranteeing medical support for epidemic control, or decreasing active cases.

Summary Understanding how the impacts of climate change are likely to modify individual well-being in the future is crucial for developing mitigation and adaptation strategies. Despite its importance, little is known about the day-to-day impacts of weather on individual subjective well-being in developing nations. To fill this gap, we use over 400 million geotagged posts across 43 million users from the social media Weibo in China, coupled with the meteorological conditions people face when posting, to estimate how climatic factors influence people's real-time expressed sentiment. We find that extreme weather worsens emotional expressions on social media. Females and individuals in poorer cities are more responsive to unpleasant temperatures. The centralized winter heating in North China effectively increases individuals' resilience against cold temperatures, whereas measures of air-conditioning prevalence do not show a substantial adaptation effect in summer. Our projections indicate the potentially harmful impacts of global warming on future subjective well-being.

This paper examines the determinants of the spatial and topological structure of three types of urban networks within the Yangtze River Delta. These networks consist of transport infrastructure links, business interactions in producer services firms, and leisure mobility. The influence of distance, size, administrative borders, landform contiguity, cultural affinities, economic alliances and administrative rank are examined. We position our findings as an empirical elaboration of the formation of multiplex urban networks. Our results show that in spite of significant correlations between all of these explanatory factors and the three urban networks, only some factors affect each of the three networks. More specifically, the business network has a weak dependence on distance and cultural affinities; intercity mobility is closely related to the size of cities' populations and distance; and landform patterns remain a fundamental basis for intercity transport linkages. Our results highlight China's hierarchical-administrative specifics in the shaping of urban networks.

Urban open public spaces that provide multiple services for residents are essential for improving life quality and urban ecosystem functionality and promoting healthy development, the safety of human settlements and the sustainable development of urban cities. Based on Sustainable Development Goal 11.7 of the United Nations (UN) 2030 Agenda, this study combines the big earth data with the Theil index, a coefficient of variation and Exploratory Spatial Data Analysis (ESDA) to analyze the regional differences and spatial distribution of urban open public space in 2015 for China, and uses geographical detectors to identify key factors that affect the distribution of open public spaces. The results show that (1) open public space scales in provincial-level cities have an &lsquo, East&ndash, Central&ndash, West&rsquo, low-lying land pattern in spatial distribution, where the eastern region has a relatively larger open public space scale. (2) In the prefecture-level cities, the open public space scale increases with an increase in city size and economic development level, and the differences in urban open public space reduce with an increase in city size and increase with a decrease in the economic development level. (3) Factors including economic development level, residents&rsquo, living standards, the urbanization level and the population size have sound explanatory powers in varying degrees on the scale of open public spaces, interactions between these factors have improved the explanatory power of the scale of urban open public space.

Ambient fine particulate matter (PM

Alloy is a lightweight specification language based on relational logic, with an analysis engine that relies on SAT solvers to automate bounded verification of specifications. In spite of its strengths, the reliance of the Alloy Analyzer on computationally heavy solvers means that it can take a significant amount of time to verify software properties, even within limited bounds. This challenge is exacerbated by the ever-evolving nature of complex software systems. This paper presents Platinum, a technique for efficient analysis of evolving Alloy specifications, that recognizes opportunities for constraint reduction and reuse of previously identified constraint solutions. The insight behind Platinum is that formula constraints recur often during the analysis of a single specification and across its revisions, and constraint solutions can be reused over sequences of analyses performed on evolving specifications. Our empirical results show that Platinum substantially reduces (by 66.4% on average) the analysis time required on specifications extracted from real-world software systems.

Climate change is a major threat to food security. The determination of policy actions requires accurate estimates of climatic impacts on both crop yields (intensive margin) and cropland area (extensive margin). However, the analysis on the latter has been limited, especially in developing countries. This paper assesses the impact of temperature on land use in China by matching high-resolution satellite data of land use with daily weather data from 1980 to 2010. We find extremely hot weather (daily average temperature above 30 °C) has a long-lasting effect on reducing cropland in China. In addition, we find that non-irrigated land is more susceptible to rising temperatures in the short term; however, irrigated land is subject to a similar impact in the long term. This result suggests that the adaptive effect of irrigation could be limited under persistent rising in temperature.

Applying copper nanowires (CuNWs) composite transparent conductive electrode (CTCE) as transparent conductive anode, a flexible organic light-emitting device (OLED) is demonstrated in this paper. Ultralong CuNWs were synthesized by a simple hydrothermal method. The random conductive grid of CuNWs was transferred to the surface of flexible substrates by vacuum filtration method. In order to reduce the surface roughness and improve work function, polymethyl methacrylate (PMMA) solution and poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) solution were spin-coated on the surface of CuNW transparent conductive electrode (TCE) in turn. The CuNW/PMMA/PEDOT:PSS CTCE was applied to an OLED, and the experiment shows that the OLED was of high efficiency. On comparing the OLED with PEDOT:PSS TCE, the maximum brightness and maximum current density of the OLED with CuNW/PMMA/PEDOT:PSS CTCE were increased by 104% and 4 times, respectively.

The modelling of human mobility and migration patterns has received much attention due to its substantial importance. Despite long-term efforts, we still lack a modelling framework that captures mo...

Bimetallic oxides ABOx (x = 2, 3, and 4) with multiple lattice sites have shown numerous properties, blossoming into diverse applications, while regulating the valence state at the A or B site usually causes a dramatic change in the crystal structure, giving rise to uncertainties in comprehending the structure–property relationships. Herein, we synthesized bimetallic layered crednerite CuMnO2 with double-coordinate Cu cations at the A site and hexa-coordinate Mn cations at the B site via a cetyltrimethylammonium bromide (CTAB) modified hydrothermal method. By controlling the crystal growth temperature, valence states tailoring was implemented along with the stabilization of the monoclinic layered structure. The regulation process was followed by morphology changes of the CuMnO2 crystal in a sequence: triangular sheets (140 °C), nanowires (160 °C), hexagonal prisms (180 °C), and octahedrons (over 200 °C). Interestingly, the oxidation states of Cu2+ and Mn2+ were found for triangular sheets, which transform...

Achieving efficient oxygen evolution reaction (OER) is crucial for advancing energy storage and conversion technologies. Several methodologies have been developed to expedite the OER process. However, producing catalysts with excellent performance still remains challenging. Herein, we successfully achieve an enhanced OER performance in amorphous (Co1-xFex)2BOy(OH)z (x = 0, 10, 20, 30, 40 and 50%) by improving electrode kinetics. The incorporation of Fe3+ not only improves the charge transfer rate, but also modulates the absorption ability of Fe3+ ions to hydroxyl, as evidenced by the decrease of 3d electron density from the Mossbauer measurement. As a consequence, (Co0.7Fe0.3)2BOy(OH)z shows a superior electrocatalytic performance with a current density of 10 mA cm-2 at an overpotential of 308 mV and a Tafel slope of 39 mV dec−1, which are smaller than those observed for undoped parent catalyst Co2BOy(OH)z and commercial IrO2. Moreover, (Co0.7Fe0.3)2BOy(OH)z catalyst has a high stability in OER electrocatalytic process. The current density still remains about 70% after continuous electrocatalytic reaction for 12 h. (Co0.7Fe0.3)2BOy(OH)z used as anode also catalyzes overall water splitting reaction to give a current density of 20 mA cm-2 at 1.62 V when taking Pt/C catalyst as cathode. The present study provides an effective approach to design new metal-based electrocatalystsby introducing foreign cation to alter outer electron density and further modulating the electrochemical activity.

The design and synthesis of heteroatom-doping porous materials with unique surface/interfaces are of great significance for enhancing the sensitive surface performance in the fields of catalytic energy, especially gas sensor, CO oxidation, and ammonium perchlorate decomposition. Usually, the template method followed by a high-temperature calcination process is considered as the routes of choice in preparing ion-doped porous materials, but it requires extra templates and will undergo complicated steps. Here, we present a simple fusion/diffusion-controlled intermetallics-transformation method to synthesize various heteroatom-doping porous SnO2 only by changing the species of intermetallics. By this new method, Ni-doped popcornlike SnO2 with plenty of ∼30 nm pores and two kinds of Cu-doped SnO2 nanocages was successfully constructed. Phase-evolution investigations demonstrated that growth kinetics, diffusion, and solubility of the intermediates are highly related to the architecture of final products. Moreov...

Maize rough dwarf disease (MRDD) is a severe viral disease of maize that occurs worldwide, particularly in the summer maize-growing areas in China, resulting in yield losses and quality deterioration in susceptible maize varieties. An effective solution to control MRDD is to use resistance genes to improve the behavior of susceptible genotypes. Here, we employed maize F2 populations derived from a cross between susceptible line S221 and resistant line K36 for the deep sequencing of the two DNA pools containing extremely resistant and susceptible F2 individuals, and used traditional linkage analysis to locate the resistance-related genomic region. The results showed that MRDD resistance in K36 was controlled by a single dominant locus, and an associated region was identified within the genomic interval of 68,396,487 bp and 69,523,478 bp on chromosome 6. Two simple sequence repeat (SSR) markers 6F29R29 and 6F34R34 were tightly linked to the MRDD resistance locus. The findings of the present study improve our understanding of the inheritance patterns of MRDD resistance, and should inform MRDD-resistant maize breeding programs.

This paper developed internationally compatible methods for delineating boundaries of urban areas in China. By integrating emission source data with existing official statistics as well as using rescaling methodology of data mapping for 1 km grid, the authors constructed high resolution emission gridded data in Beijing-Tianjin-Hebei (Jing-Jin-Ji) region in China for 2012. Comparisons between urban and non-urban areas of carbon emissions from industry, agriculture, household and transport exhibited regional disparities as well as sectoral differences. Except for the Hebei province, per capita total direct carbon emissions from urban extents in Beijing and Tianjin were both lower than provincial averages, indicating the climate benefit of urbanization, comparable to results from developed countries. Urban extents in the Hebei province were mainly industrial centers while those in Beijing and Tianjin were more service oriented. Further decomposition analysis revealed population to be a common major driver for increased carbon emissions but climate implications of urban design, economic productivity of land use, and carbon intensity of GDP were both cluster- and sector-specific. This study disapproves the one-size-fits-all solution for carbon mitigation but calls for down-scaled analysis of carbon emissions and formulation of localized carbon reduction strategies in the Jing-Jin-Ji as well as other regions in China.