Highly active air electrode catalysts for Zn‐air batteries: Catalytic mechanism and active center from obfuscation to clearness

Carbon‐based materials have been found to accelerate the sluggish kinetic reaction and are largely subject to the overall Zn‐air batteries (ZABs) property, while their full catalytic mechanism is still not excavated because of the indistinct internal structure and immature in‐situ technology. Up to now, systematic methods have been utilized to study and design promising high‐performance carbon‐based catalysts. To resolve the real active units and catalytic mechanism, developing molecular catalyst is a significant strategy. Herein, the review will initiate to briefly introduce the working principle and composition of ZABs. An important statement is correspondingly provided about the typical structure and catalytic mechanisms for the air cathode material. It also presents the tremendous endeavors on the catalytic performance and stability of carbon‐based material. Furthermore, combined with theoretical calculation, the self‐defined active sites are analyzed to understand the catalytic character, where the molecular catalyst is subsequently summarized and discussed through highlighting the unambiguous and controllable structure, in the hope of surfacing the optimum catalyst. Building on the fundamental understanding of carbon‐based and molecular catalysts, this review is expected to provide guidance and direction toward designing future mechanistic studies and ORR electrocatalysts

Age-related differences in risk factors, clinical characteristics, and outcomes for intracerebral hemorrhage

Background and purposeIntracerebral hemorrhage (ICH) is a severe form of stroke that remains understudied in the young adults. We aimed to investigate the clinical presentation, and risk factors associated with ICH in this age group and compare them to older patients.MethodsOur study included ICH patients admitted between March 2016 and December 2021 in the First Affiliated Hospital of Chongqing Medical University from our ongoing prospective cohort database. Demographic characteristics, etiology, risk factors, and clinical outcomes were compared between elderly and young patients. Furthermore, logistic regression analysis was employed to explore risk factors associated with the functional outcome at 3-months.ResultsWe selected 1,003 patients (mean age, 59.9 ±13.8 years old), 746 (74.4%) patients were aged >50 years. The logistic regression analysis showed young patients have a higher proportion of secondary ICH, higher white blood cell count and higher body mass index (BMI), but less diabetes mellitus. Of all patients, predictors of 3-month functional independence was first-ever ICH and age ≤50 years. The history of nephropathy and stroke, higher baseline NIHSS score, larger hematoma volume, and the presence of hydrocephalus were associated with poor outcomes. And the white blood cell count could significantly influence the prognosis among young ICH patients. Three-month functional outcome based on modified Rankin scale score was better in young patients than the elderly (OR, 1.232; 95% CI, 1.095–1.388; p < 0.001).ConclusionsThe highest incidence of ICH occurs in the age groups of 50–59 and 60–69. ICH in young adults had higher white blood cell and BMI compared to the elderly, and differs in etiological distribution. The young patients also had similar short-term mortality but more favorable functional outcomes than the elderly. Furthermore, NIHSS score and larger hematoma volumes were associated with poor outcome in all patients

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

The Effectiveness of the Multilateral Coalition to Develop a Green Agricultural Products Market in China Based on a TU Cooperative Game Analysis

Green agriculture can improve biodiversity, increase farmers’ income, reduce agricultural non-point source pollution, solve food safety issues, and will be an important way to promote sustainable development in China. At present, the green transformation of China’s agriculture has encountered a bottleneck in the development of a green agricultural product market. How to develop a green agricultural product market has become an issue worthy of in-depth study in the academia. Previous studies have already given persuasive explanations for the inability to form a green agricultural product market, but few have explored its development path from the angle of cooperation. By employing the method of a Transferable Utilities (TU) cooperative game, and based on theoretical analyses and hypothetical data, this thesis aims to prove the effectiveness of the multilateral coalition to develop the green agricultural product market in China. The results show the effectiveness of the developed model of the green agricultural product market in which producers, consumers, food safety inspection departments, and e-commerce platforms cooperate with each other. This model meets the objective needs of the times and that of the market economy. According to the marginal contribution value of participants in different coalition orders, this thesis finds 6 kinds of coalition orders. When producers and consumers of green agricultural products enter the coalition in the last place, the marginal contribution value is maximized, which reflects the importance of the supply side and demand side of green agricultural products. In other words, the development of the green agricultural product market is a dynamic process—determined by consumers and promoted by producers—in which both sides promote and restrict each other. Finally, this article presents two policy recommendations: at the national level, to clearly proposes a strategy to build a green agricultural product e-commerce platform in China and to launch a pilot application for the specialized e-commerce platform for green agricultural products in the Guizhou province

Carbon emission reduction effect of China’s final demand structure change from 2013 to 2020: a scenario-based analysis

This study employs scenario analysis to measure the carbon emissions reduction potential of the final demand structure changes in China from 2013 to 2020. The results indicate that under the business as usual (BAU) scenario (i.e. in which China’s final demand structure, energy structure and technical level in 2020 are the same as those in 2012), China’s gross domestic product of 2020 calculated by 2005 constant price is 6,427,658,783×10,000 yuan and China’s total carbon emissions will reach 1,531,692.29×10,000 tons, with its carbon emission intensity standing at 2.3686 t/10,000 yuan (it is only 25.57% lower than in 2005). Furthermore, under the specific final demand product structure (when “government consumption”, “export consumption”, “residents’ consumption + capital formation” accounts for 12%, 18% and 70%of final demand, respectively), China’s total carbon emissions in 2020 will be reduced by between 167,595.33×10,000 and 204,142.45×10,000 tons compared to the BAU scenario, and carbon emission intensity nationwide will be reduced by 33.71-35.49% compared with 2005. Finally, based on the assumptions and conclusions, this study puts forward some suggestions to realize the China’s carbon emission reduction commitments

Geometric Self-Calibration of YaoGan-13 Images Using Multiple Overlapping Images

Geometric calibration is an important means of improving the absolute positioning accuracy of space-borne synthetic aperture radar imagery. The conventional calibration method is based on a calibration field, which is simple and convenient, but requires a great deal of manpower and material resources to obtain ground control points. Although newer cross-calibration methods do not require ground control points, calibration accuracy still depends on a periodically updated reference image. Accordingly, this study proposes a geometric self-calibration method based on the positioning consistency constraint of conjugate image points to provide rapid and accurate calibration of the YaoGan-13 satellite. The proposed method can accurately calibrate geometric parameters without requiring ground control points or high-precision reference images. To verify the absolute positioning accuracy obtained using the proposed self-calibration method, YaoGan-13 Stripmap images of multiple regions were collected and evaluated. The results indicate that high-accuracy absolute positioning can be achieved with a plane accuracy of 3.83 m or better for Stripmap data, without regarding elevation error. Compared to the conventional calibration method using high-accuracy control data, the difference between the two methods is only about 2.53 m, less than the 3-m resolution of the image, verifying the effectiveness of the proposed self-calibration method

SBHSR: single-band super-resolution method for hyperspectral images based on blind degradation and fusion of auxiliary band

AbstractDespite natural image super-resolution (SR) methods have achieved great success, super-resolution methods for hyperspectral image (HSI) with rich spectral features are still a very challenging task. Furthermore, due to the diversity of HSI captured by different cameras, their degradation conditions vary. Currently available HSI SR methods are mainly based on fixed degradation models, and their performance is severely affected when the actual degradation does not match the assumed degradation model. To address this issue, this paper proposes a single-band hyperspectral image super-resolution (SBHSR) method for HSI. This method assumes that the degradation Gaussian blur kernel parameters of the HSI are unknown, and adapts to various degradation conditions by conducting blind super-resolution on the image. It also combines another band with better spatial structure as an auxiliary band for feature fusion. To address the spectral differences between the super-resolution band and the auxiliary band, we use the Spatial Adaptation Module (SAM) to map the feature distribution, ensuring consistent spectral brightness between the auxiliary band and the super-resolution band. Due to the use of blind degradation super-resolution method, our method is more robust compared to previous HSI SR methods. Additionally, as it is specifically designed for single-band hyperspectral image super-resolution, it has the advantage of being faster and more efficient. Experimental validation on two hyperspectral datasets demonstrates the superiority of our method, as it improves the spatial resolution of the image while preserving the spectral features, and performs better than existing blind super-resolution methods

The Impact of Environmental Uncertainty on Corporate Innovation: Evidence from Chinese Listed Companies

Corporate innovation is an important topic in the academic community, but there are few studies on the impact of the micro operation environment on corporate innovation. Using the data of A-share listed companies in Shanghai and Shenzhen from 2009 to 2020, this paper examines the impact of environmental uncertainty on enterprise innovation from a micro perspective. The results show that there is an overall negative correlation between environmental uncertainty and corporate innovation. Companies facing a higher degree of environmental uncertainty are more cautious in their innovation investment. We also find that this negative correlation was more pronounced in companies with weaker risk-taking ability. Further research finds that financing constraints have a partial intermediary effect on the impact of environmental uncertainty on innovation, that is, environmental uncertainty can have a negative impact on innovation by increasing the financing constraints faced by corporations. Our research provides micro-level evidence for the impact of uncertainty on corporate innovation

Evaluating Vertical Accuracies of Open-Source Digital Elevation Models over Multiple Sites in China Using GPS Control Points

Digital elevation models (DEMs) are widely used across a range of fields. Several open-source global DEMs have been released, including the advanced land observing satellite world 3D 30 m DEM (AW3D30DEM), advanced spaceborne thermal emission and reflection radiometer global DEM (ASTER GDEM), shuttle radar topography mission DEM (SRTMDEM), and TerraSAR-X for digital elevation measurement (TanDEM-X). ASTER and SRTM are the most widely used DEMs, while the newer models AW3D30DEM and TanDEM-X are becoming increasingly popular. Many studies have evaluated the qualities of these DEMs; however, few multi-regional studies have been conducted in China. To comprehensively and systematically evaluate the qualities of these DEMs in China, the vertical accuracies of AW3D, ASTER, STRM (all 30 m), and TanDEM-X (90 m) were tested across 16 regions in China. Using high-precision global positioning system control points for reference, error values were determined by subtracting these reference values from corresponding global DEM elevation values. As the study only covered flat areas (slope < 5°), slope was treated as a controlled variable. After assessing the impacts of the slope aspect and land cover type, variations in vertical accuracy were examined with respect to longitude and latitude. Overall, TanDEM-X exhibited the highest stability and accuracy, AW3D30 and SRTM also performed well, while ASTER exhibited the worst accuracy. The DEMs showed relationships with the slope aspect and land cover type, assuming that slope had no influence on vertical accuracy. In general, vertical accuracy in high latitudes was slightly better than that in low latitudes, and no evident variations were observed with respect to longitude. This study is the first to conduct DEM analysis across many regions in China from open sources. Since most of the users rely on public domain DEM datasets, this work contributes to their analysis in academic and engineering fields