Enormous efforts have been devoted to the reduction of carbon dioxide (CO2) by utilizing various driving forces, such as heat, electricity, and radiation. However, the efficient reduction of CO2 is ...still challenging because of sluggish kinetics. Recent pioneering studies from several groups, including us, have demonstrated that the coupling of solar energy and thermal energy offers a novel and promising strategy to promote the activity and/or manipulate selectivity in CO2 reduction. Herein, we clarify the definition and principles of coupling solar energy and thermal energy, and comprehensively review the status and prospects of CO2 reduction by coupling solar energy and thermal energy. Catalyst design, reactor configuration, photo‐mediated activity/selectivity, and mechanism studies in photo‐thermo CO2 reduction will be emphasized. The aim of this Review is to promote understanding towards CO2 activation and provide guidelines for the design of new catalysts for the efficient reduction of CO2.
A bundle of energy: The coupling of solar energy and thermal energy is a promising strategy to mediate the activity and/or selectivity of CO2 reduction. The status and prospects of this topic are reviewed, with the aim of providing guidelines for the design of new catalysts.
Wuhan was the epicentre of the COVID-19 outbreak in China. We aimed to determine the seroprevalence and kinetics of anti-SARS-CoV-2 antibodies at population level in Wuhan to inform the development ...of vaccination strategies.
In this longitudinal cross-sectional study, we used a multistage, population-stratified, cluster random sampling method to systematically select 100 communities from the 13 districts of Wuhan. Households were systematically selected from each community and all family members were invited to community health-care centres to participate. Eligible individuals were those who had lived in Wuhan for at least 14 days since Dec 1, 2019. All eligible participants who consented to participate completed a standardised electronic questionnaire of demographic and clinical questions and self-reported any symptoms associated with COVID-19 or previous diagnosis of COVID-19. A venous blood sample was taken for immunological testing on April 14–15, 2020. Blood samples were tested for the presence of pan-immunoglobulins, IgM, IgA, and IgG antibodies against SARS-CoV-2 nucleocapsid protein and neutralising antibodies were assessed. We did two successive follow-ups between June 11 and June 13, and between Oct 9 and Dec 5, 2020, at which blood samples were taken.
Of 4600 households randomly selected, 3599 families (78·2%) with 9702 individuals attended the baseline visit. 9542 individuals from 3556 families had sufficient samples for analyses. 532 (5·6%) of 9542 participants were positive for pan-immunoglobulins against SARS-CoV-2, with a baseline adjusted seroprevalence of 6·92% (95% CI 6·41–7·43) in the population. 437 (82·1%) of 532 participants who were positive for pan-immunoglobulins were asymptomatic. 69 (13·0%) of 532 individuals were positive for IgM antibodies, 84 (15·8%) were positive for IgA antibodies, 532 (100%) were positive for IgG antibodies, and 212 (39·8%) were positive for neutralising antibodies at baseline. The proportion of individuals who were positive for pan-immunoglobulins who had neutralising antibodies in April remained stable for the two follow-up visits (162 44·6% of 363 in June, 2020, and 187 41·2% of 454 in October–December, 2020). On the basis of data from 335 individuals who attended all three follow-up visits and who were positive for pan-immunoglobulins, neutralising antibody levels did not significantly decrease over the study period (median 1/5·6 IQR 1/2·0 to 1/14·0 at baseline vs 1/5·6 1/4·0 to 1/11·2 at first follow-up p=1·0 and 1/6·3 1/2·0 to 1/12·6 at second follow-up p=0·29). However, neutralising antibody titres were lower in asymptomatic individuals than in confirmed cases and symptomatic individuals. Although titres of IgG decreased over time, the proportion of individuals who had IgG antibodies did not decrease substantially (from 30 100% of 30 at baseline to 26 89·7% of 29 at second follow-up among confirmed cases, 65 100% of 65 at baseline to 58 92·1% of 63 at second follow-up among symptomatic individuals, and 437 100% of 437 at baseline to 329 90·9% of 362 at second follow-up among asymptomatic individuals).
6·92% of a cross-sectional sample of the population of Wuhan developed antibodies against SARS-CoV-2, with 39·8% of this population seroconverting to have neutralising antibodies. Our durability data on humoral responses indicate that mass vaccination is needed to effect herd protection to prevent the resurgence of the epidemic.
Chinese Academy of Medical Sciences & Peking Union Medical College, National Natural Science Foundation, and Chinese Ministry of Science and Technology.
For the Chinese translation of the abstract see Supplementary Materials section.
Reduced-reference image quality assessment (RRIQA) methods estimate image quality degradations with partial information about the ldquoperfect-qualityrdquo reference image. In this paper, we propose ...an RRIQA algorithm based on a divisive normalization image representation. Divisive normalization has been recognized as a successful approach to model the perceptual sensitivity of biological vision. It also provides a useful image representation that significantly improves statistical independence for natural images. By using a Gaussian scale mixture statistical model of image wavelet coefficients, we compute a divisive normalization transformation (DNT) for images and evaluate the quality of a distorted image by comparing a set of reduced-reference statistical features extracted from DNT-domain representations of the reference and distorted images, respectively. This leads to a generic or general-purpose RRIQA method, in which no assumption is made about the types of distortions occurring in the image being evaluated. The proposed algorithm is cross-validated using two publicly-accessible subject-rated image databases (the UT-Austin LIVE database and the Cornell-VCL A57 database) and demonstrates good performance across a wide range of image distortions.
The nitrogenous nucleophile electrooxidation reaction (NOR) plays a vital role in the degradation and transformation of available nitrogen. Focusing on the NOR mediated by the β‐Ni(OH)2 electrode, we ...decipher the transformation mechanism of the nitrogenous nucleophile. For the two‐step NOR, proton‐coupled electron transfer (PCET) is the bridge between electrocatalytic dehydrogenation from β‐Ni(OH)2 to β‐Ni(OH)O, and the spontaneous nucleophile dehydrogenative oxidation reaction. This theory can give a good explanation for hydrazine and primary amine oxidation reactions, but is insufficient for the urea oxidation reaction (UOR). Through operando tracing of bond rupture and formation processes during the UOR, as well as theoretical calculations, we propose a possible UOR mechanism whereby intramolecular coupling of the N−N bond, accompanied by PCET, hydration and rearrangement processes, results in high performance and ca. 100 % N2 selectivity. These discoveries clarify the evolution of nitrogenous molecules during the NOR, and they elucidate fundamental aspects of electrocatalysis involving nitrogen‐containing species.
During urea electrooxidation over a Ni(OH)2 electrode the dehydrogenation reaction from β‐Ni(OH)2 to β‐Ni(OH)O can lead to spontaneous urea dehydrogenation. Spontaneous intramolecular coupling of the N−N bond and hydration of urea dehydrogenation intermediates play important roles in the oxidation path from urea to N2 and CO2.
Many state-of-the-art perceptual image quality assessment (IQA) algorithms share a common two-stage structure: local quality/distortion measurement followed by pooling. While significant progress has ...been made in measuring local image quality/distortion, the pooling stage is often done in ad-hoc ways, lacking theoretical principles and reliable computational models. This paper aims to test the hypothesis that when viewing natural images, the optimal perceptual weights for pooling should be proportional to local information content, which can be estimated in units of bit using advanced statistical models of natural images. Our extensive studies based upon six publicly-available subject-rated image databases concluded with three useful findings. First, information content weighting leads to consistent improvement in the performance of IQA algorithms. Second, surprisingly, with information content weighting, even the widely criticized peak signal-to-noise-ratio can be converted to a competitive perceptual quality measure when compared with state-of-the-art algorithms. Third, the best overall performance is achieved by combining information content weighting with multiscale structural similarity measures.
Tone-mapping operators (TMOs) that convert high dynamic range (HDR) to low dynamic range (LDR) images provide practically useful tools for the visualization of HDR images on standard LDR displays. ...Different TMOs create different tone-mapped images, and a natural question is which one has the best quality. Without an appropriate quality measure, different TMOs cannot be compared, and further improvement is directionless. Subjective rating may be a reliable evaluation method, but it is expensive and time consuming, and more importantly, is difficult to be embedded into optimization frameworks. Here we propose an objective quality assessment algorithm for tone-mapped images by combining: 1) a multiscale signal fidelity measure on the basis of a modified structural similarity index and 2) a naturalness measure on the basis of intensity statistics of natural images. Validations using independent subject-rated image databases show good correlations between subjective ranking score and the proposed tone-mapped image quality index (TMQI). Furthermore, we demonstrate the extended applications of TMQI using two examples - parameter tuning for TMOs and adaptive fusion of multiple tone-mapped images.
Water electrolysis is a sustainable technology for hydrogen production since this process can utilize the intermittent electricity generated by renewable energy such as solar, wind, and hydro. ...However, the large‐scale application of this process is restricted by the high electricity consumption due to the large potential gap (>1.23 V) between the anodic oxygen evolution reaction and the cathodic hydrogen evolution reaction (HER). Herein, a novel and efficient hydrogen production system is developed for coupling glucose‐assisted Cu(I)/Cu(II) redox with HER. The onset potential of the electrooxidation of Cu(I) to Cu(II) is as low as 0.7 VRHE (vs reversible hydrogen electrode). In situ Raman spectroscopy, ex situ X‐ray photoelectron spectroscopy, and density functional theory calculation demonstrates that glucose in the electrolyte can reduce the Cu(II) into Cu(I) instantaneously via a thermocatalysis process, thus completing the cycle of Cu(I)/Cu(II) redox. The assembled electrolyzer only requires a voltage input of 0.92 V to achieve a current density of 100 mA cm−2. Consequently, the electricity consumption for per cubic H2 produced in the system is 2.2 kWh, only half of the value for conventional water electrolysis (4.5 kWh). This work provides a promising strategy for the low‐cost, efficient production of high‐purity H2.
A new approach is proposed to achieve low‐voltage and continuous hydrogen production using glucose‐assisted Cu(I)/Cu(II) redox as the anode reaction. Glucose in the electrolyte can reduce the Cu(II) into Cu(I) spontaneously, thus completing the cycle of Cu(I)/Cu(II) redox. The assembled electrolyzer only requires a voltage input of 0.92 V to achieve a current density of 100 mA cm−2.
Triangular fuzzy multiplicative preference relation (TFMPR) is a widely used preference representation framework in the fuzzy analytic hierarchy process (FAHP). In this article, we develop a ...triangular fuzzy multiplication-based equation to characterize transitivity among original fuzzy assessments in a consistent TFMPR. A geometric consistency index is then proposed to measure the inconsistency of TFMPRs. By capturing row fuzziness proportionalities and the difference between the row increasing and decreasing part fuzziness indices, this article establishes two logarithmic least square models to find normalized fuzzy weights from two kinds of TFMPRs. The two logarithmic least square models are further integrated into one whose analytic solution is found by the method of Lagrange multipliers. A novel method is put forward to check the acceptability of TFMPRs by both examining acceptable consistency and acceptable fuzziness. This article devises a parametric defuzzification approach to obtain the real-valued weights of criteria for aggregating the local normalized fuzzy weights into the global fuzzy weights in the triangular FAHP. A comparative analysis of the proposed model with existing fuzzy eigenvector methods and fuzzy average methods is carried out by a numerical example with four TFMPRs to clarify its validity and merits. An outstanding teacher award selection problem is provided to show the practicality of the proposed triangular FAHP.
PDF
