This study takes the Yangtze River Economic Belt as a study area and analyzes the impacts of natural and socioeconomic factors on air pollution based on a dataset of urban air quality monitoring data ...in 2015 and meteorological and economic statistical data. We first apply the grey relational degree to test for the quantitative relationships between the natural and socioeconomic factors and air pollution. We then employ a novel method, specifically, the geographical detector, from the perspective of spatial stratified heterogeneity to reveal the potential impacts and interaction impacts of the natural and socioeconomic factors on air pollution. The results are as follows. (1) The grey relational degree results reveal that all factors in the topographical and meteorological layer, pollution sources layer, economic development layer, and urbanization layer have high relational degrees, indicating that these factors are closely correlated with air pollution. (2) The factor detector analysis reveals that the PM2.5 factor has the biggest q value, indicating that it is the primary contributor to air pollution, followed by PM10 and elevation. (3) The interaction detector analysis reveals that the interaction of two factors plays a more important role in influencing air pollution than does each factor individually. Moreover, the interactions between pair factors of pollution sources are the strongest. (4) The risk detector analysis reveals that elevation and precipitation are negatively correlated with air pollution, whereas pollution and urbanization factors are positively correlated with air pollution. (5) Finally, two leading impact areas for atmospheric pollution, namely, the Yangtze River Delta urban agglomeration and the Wuhan metropolitan area are predominantly attributed to the combination of natural and urbanization factors, whereas Yunnan and Guizhou are the least impact areas for atmospheric pollution because of their topographical and meteorological factors.
•The relations between air pollution and natural and economic factors are found.•The novel geographical detector method is applied in this study.•PM2.5 factor has the biggest q value, implying the primary pollutant.•Interaction of factors plays a more important role in affecting air pollution.
Automatic modulation classification (AMC) is an essential part in a cognitive radio receiver. Benefited from the discriminative constellation characteristics among most modulations, AMC methods based ...on constellation diagrams usually achieve pleasant performance. However, in noncooperation communication systems, constellation diagrams expressing modulations explicitly are difficult to obtain via blind symbol timing synchronization, especially in complicated wireless channels. Therefore, this article proposes a novel constellation diagram-based AMC architecture called attentive Siamese networks (ASNs) by considering multitiming constellation diagrams (MCDs) and selecting the proper symbol timings at the feature level, which is a more robust way than the conventional signal-level symbol timing synchronization. In detail, convolutional neural networks sharing the same parameters first extract deep feature vectors for MCDs. Then, an attention inference module weights all the deep feature vectors. Finally, AMC is realized based on the weighted feature vectors. Moreover, the ASN architecture can be trained end-to-end. Comparing with the state-of-the-art methods that take diverse representations of received baseband signals as input, experimental results based on the RadioML 2018.01A dataset and non-Gaussian noise dataset demonstrate that ASN achieves a remarkable improvement, whose classification accuracy goes over 99% when the signal-to-noise ratio (SNR) > 10 dB.
The lithium (Li)–air battery has an ultrahigh theoretical specific energy, however, even in pure oxygen (O2), the vulnerability of conventional organic electrolytes and carbon cathodes towards ...reaction intermediates, especially O2−, and corrosive oxidation and crack/pulverization of Li metal anode lead to poor cycling stability of the Li‐air battery. Even worse, the water and/or CO2 in air bring parasitic reactions and safety issues. Therefore, applying such systems in open‐air environment is challenging. Herein, contrary to previous assertions, we have found that CO2 can improve the stability of both anode and electrolyte, and a high‐performance rechargeable Li–O2/CO2 battery is developed. The CO2 not only facilitates the in situ formation of a passivated protective Li2CO3 film on the Li anode, but also restrains side reactions involving electrolyte and cathode by capturing O2−. Moreover, the Pd/CNT catalyst in the cathode can extend the battery lifespan by effectively tuning the product morphology and catalyzing the decomposition of Li2CO3. The Li–O2/CO2 battery achieves a full discharge capacity of 6628 mAh g−1 and a long life of 715 cycles, which is even better than those of pure Li–O2 batteries.
CO2 can do: CO2 makes Li–O2 batteries more stable. On the anode side, CO2 can facilitate the formation of a protective and self‐healing Li2CO3 film, which can expel the H2O and aggressive intermediates during cycling. The cathode and electrolyte are also protected because the O2− intermediate is captured by CO2 to prevent the formation of 1O2.
Non-invasive visualization of dynamic molecular events in real-time via molecular imaging may enable the monitoring of cascade catalytic reactions in living systems, however effective imaging ...modalities and a robust catalytic reaction system are lacking. Here we utilize three-dimensional (3D) multispectral photoacoustic (PA) molecular imaging to monitor in vivo cascade catalytic therapy based on a dual enzyme-driven cyclic reaction platform. The system consists of a two-dimensional (2D) Pd-based nanozyme conjugated with glucose oxidase (GOx). The combination of nanozyme and GOx can induce the PA signal variation of endogenous molecules. Combined with the PA response of the nanozyme, we can simultaneously map the 3D PA signals of dynamic endogenous and exogenous molecules associated with the catalytic process, thus providing a real-time non-invasive visualization. We can also treat tumors under the navigation of the PA imaging. Therefore, our study demonstrates the imaging-guided potential of 3D multispectral PA imaging in feedback-looped cascade catalytic therapy.
Propane dehydrogenation (PDH) has great potential to meet the increasing global demand for propylene, but the widely used Pt‐based catalysts usually suffer from short‐term stability and ...unsatisfactory propylene selectivity. Herein, we develop a ligand‐protected direct hydrogen reduction method for encapsulating subnanometer bimetallic Pt–Zn clusters inside silicalite‐1 (S‐1) zeolite. The introduction of Zn species significantly improved the stability of the Pt clusters and gave a superhigh propylene selectivity of 99.3 % with a weight hourly space velocity (WHSV) of 3.6–54 h−1 and specific activity of propylene formation of 65.5 molC3H6
gPt−1 h−1 (WHSV=108 h−1) at 550 °C. Moreover, no obvious deactivation was observed over PtZn4@S‐1‐H catalyst even after 13000 min on stream (WHSV=3.6 h−1), affording an extremely low deactivation constant of 0.001 h−1, which is 200 times lower than that of the PtZn4/Al2O3 counterpart under the same conditions. We also show that the introduction of Cs+ ions into the zeolite can improve the regeneration stability of catalysts, and the catalytic activity kept unchanged after four continuous cycles.
A lean, mean, propylene machine: Subnanometer bimetallic Pt–Zn clusters are encapsulated inside silicalite‐1 (S‐1) zeolite via a ligand‐protected direct hydrogen reduction method. In the propane dehydrogenation (PDH) reaction, the PtZn4@S‐1‐H catalyst exhibited a very high propylene selectivity of 99.3 % and specific activity of propylene formation of 65.5 molC3H6
gPt−1 h−1 at 550 °C. Moreover, no obvious deactivation was observed over catalyst even after 13000 min on stream.
Designing high-performance and cost-effective electrocatalysts toward oxygen evolution and hydrogen evolution reactions in water-alkali electrolyzers is pivotal for large-scale and sustainable ...hydrogen production. Earth-abundant transition metal oxide-based catalysts are particularly active for oxygen evolution reaction; however, they are generally considered inactive toward hydrogen evolution reaction. Here, we show that strain engineering of the outermost surface of cobalt(II) oxide nanorods can turn them into efficient electrocatalysts for the hydrogen evolution reaction. They are competitive with the best electrocatalysts for this reaction in alkaline media so far. Our theoretical and experimental results demonstrate that the tensile strain strongly couples the atomic, electronic structure properties and the activity of the cobalt(II) oxide surface, which results in the creation of a large quantity of oxygen vacancies that facilitate water dissociation, and fine tunes the electronic structure to weaken hydrogen adsorption toward the optimum region.
A convenient and rapid detection method for methanol in ethanol remains a major challenge due to their indistinguishable physical properties. Herein, a novel fluorescence probe based on perovskite ...was successfully designed to overcome this bottleneck. We report a new zero‐dimensional (0D) hybrid perovskite of MP2InxSb1−xCl7 ⋅ 6 H2O (MP=2‐methylpiperazine) displaying an unusual green light emission with near‐unity photoluminescence quantum yield. Remarkably, this 0D perovskite exhibits reversible methanol‐response luminescence switching between green and yellow color but fail in any other organic vapors. Even for blended alcohol solutions, the luminescent probe exhibits excellent sensing performance with multiple superiorities of rapid response time (30 s) and ultra‐low detection limit (40 ppm), etc. Therefore, this 0D perovskite can be utilized as a perfect fluorescence probe to detect traces of methanol from ethanol with ultrahigh sensitivity, selectivity and repeatability. To the best of our knowledge, this work represents the first perovskite as fluorescence probe for methanol with wide potential in environmental monitoring and methanol detection, etc.
0D hybrid lead‐free halide displays highly efficient broadband green light emission with a near‐unity photoluminescence quantum yield, and acts as a unique fluorescence sensor for methanol in ethanol with ultrahigh selectivity, sensitivity and repeatability as well as fast response time.
SUMMARY
Cucumber (Cucumis sativus) originated in tropical areas and is very sensitive to low temperatures. Cold acclimation is a universal strategy that improves plant resistance to cold stress. In ...this study, we report that heat shock induces cold acclimation in cucumber seedlings, via a process involving the heat‐shock transcription factor HSFA1d. CsHSFA1d expression was improved by both heat shock and cold treatment. Moreover, CsHSFA1d transcripts accumulated more under cold treatment after a heat‐shock pre‐treatment than with either heat shock or cold treatment alone. After exposure to cold, cucumber lines overexpressing CsHSFA1d displayed stronger tolerance for cold stress than the wild type, whereas CsHSFA1d knockdown lines obtained by RNA interference were more sensitive to cold stress. Furthermore, both the overexpression of CsHSFA1d and heat‐shock pre‐treatment increased the endogenous jasmonic acid (JA) content in cucumber seedlings after cold treatment. Exogenous application of JA rescued the cold‐sensitive phenotype of CsHSFA1d knockdown lines, underscoring that JA biosynthesis is key for CsHSFA1d‐mediated cold tolerance. Higher JA content is likely to lead to the degradation of CsJAZ5, a repressor protein of the JA pathway. We also established that CsJAZ5 interacts with CsICE1. JA‐induced degradation of CsJAZ5 would be expected to release CsICE1, which would then activate the ICE–CBF–COR pathway. After cold treatment, the relative expression levels of ICE–CBF–COR signaling pathway genes, such as CsICE1, CsCBF1, CsCBF2 and CsCOR1, in CsHSFA1d overexpression lines were significantly higher than in the wild type and knockdown lines. Taken together, our results help to reveal the mechanism underlying heat shock‐induced cold acclimation in cucumber.
Significance Statement
Cold acclimation is a universal strategy that improves plant resistance to cold stress. In this study, we discovered that a heat‐shock pre‐treatment improves the tolerance of cucumber seedlings for low‐temperature stress, and that CsHSFA1d and JA play important roles in this cold acclimation process. Our results will help to reveal the mechanism underlying heat shock‐induced cold acclimation in cucumber.
To construct a long noncoding RNA (lncRNA)–microRNA (miRNA)–messenger RNA (mRNA) regulatory network related to epithelial ovarian cancer (EOC) cisplatin‐resistant, differentially expressed genes ...(DEGs), differentially expressed lncRNAs (DELs), and differentially expressed miRNAs (DEMs) between MDAH and TOV‐112D cells lines were identified. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were conducted to analyze the biological functions of DEGs. Downstream mRNAs or upstream lncRNAs for miRNAs were analyzed at miRTarBase 7.0 or DIANA‐LncBase V2, respectively. A total of 485 significant DEGs, 85 DELs, and 5 DEMs were identified. Protein–protein interaction (PPI) network of DEGs contrains 81 nodes and 141 edges was constructed, and 25 hub genes related to EOC cisplatin‐resistant were identified. Subsequently, a lncRNA–miRNA–mRNA regulatory network contains 4 lncRNAs, 4 miRNAs, and 35 mRNAs was established. Taken together, our study provided evidence concerning the alteration genes involved in EOC cisplatin‐resistant, which will help to unravel the mechanisms underlying drug resistant.
1.
A long noncoding RNA–microRNA–messenger RNA network related to epithelial ovarian cancer (EOC) cisplatin‐resistant was established.
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Genes involved in EOC cisplatin‐resistant were identified.
Flexible metal–organic frameworks (MOFs) receive much attention owing to their attractive properties that originate from their flexibility and dynamic behavior, and show great potential applications ...in many fields. Here, recent progress in the discovery, understanding, and property investigations of flexible MOFs are reviewed, and the examples of their potential applications in storage and separation, sensing, and guest capture and release are presented to highlight the developing trends in flexible MOFs.
Flexible metal–organic frameworks are widely investigated as functional materials based on their remarkable properties, and potential applications of these materials are found in many fields. The most recent advances in the discovery, understanding and property investigations are reviewed, and new trends for their applications are highlighted.
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