Oxidizing CH4 into liquid products with O2 under mild conditions still mainly relies on metal catalysis. We prepared a series of sulfone‐modified conjugated organic polymers and found that the ...catalyst with proper SVI content (0.10) could drive O2→H2O2→⋅OH to oxidize CH4 into CH3OH and HCOOH directly and efficiently at room temperature under light irradiation. Experimental results showed that after 4 h reaction, decomposition rate and residual amounts of H2O2 were 81.21 % and 4.83 mmol gcat−1 respectively, and CH4 conversion rate was 22.81 %. Mechanism studies revealed that illumination could induce the homolytic dissociation of S=O bonds on catalyst to produce oxygen and sulfur radicals, where the ⋅O could adsorb and activate CH4, and the ⋅S could supply electrons for 1O2 to generate H2O2 and then for decomposing the H2O2 into ⋅OH timely to oxidize CH4. This research provided a novel organic catalysis approach for oxygen activation and utilization.
In a process of methane conversion photocatalyzed by the sulfone‐decorated conjugated organic polymer, S‐CTTP, light irradiation first induced the homolytic dissociation of S=O bonds in sulfone groups on the catalyst surface to generate free radicals. The radicals drive efficient conversion of 1O2 to H2O2 and then ⋅OH, for selective oxidation of adsorbed CH4 into CH3OH and HCOOH.
Segmentation and tracking of multiple humans in crowded situations is made difficult by interobject occlusion. We propose a model-based approach to interpret the image observations by multiple ...partially occluded human hypotheses in a Bayesian framework. We define a joint image likelihood for multiple humans based on the appearance of the humans, the visibility of the body obtained by occlusion reasoning, and foreground/background separation. The optimal solution is obtained by using an efficient sampling method, data-driven Markov chain Monte Carlo (DDMCMC), which uses image observations for proposal probabilities. Knowledge of various aspects, including human shape, camera model, and image cues, are integrated in one theoretically sound framework. We present experimental results and quantitative evaluation, demonstrating that the resulting approach is effective for very challenging data.
Unlike previous studies, this paper empirically investigates the impact of urbanization on energy consumption and CO2 emissions with consideration of provincial differences. The results show the ...following: (1) Urbanization increases energy consumption and CO2 emissions in China, but it is not the most outstanding contributor to the increases. (2) Significant differences exist between provinces in terms of the impact of urbanization on energy consumption and CO2 emissions. The distribution of urbanization strongly and relatively strongly affects energy consumption in regions with high-urbanization areas but also those with low-urbanization areas. Meanwhile, urbanization strongly and relatively strongly affects the regional CO2 emissions in northern China, where the major coal production areas, characterized by an energy-guzzling heavy industry base, are located. (3) Some evidence supports the arguments of urban environmental transition theory. Cities at a post-industrial stage (such as Beijing and Shanghai) experience a large effect from urbanization because of higher energy consumption in private residential and public service sectors, while in western and central China, the impact of urbanization can be associated with industrial development, which is characterized by low energy efficiency, high energy consumption and high emissions. In eastern China, the coexistence of light industrial structures and rapid urbanization has led to a smaller impact from urbanization on energy consumption and CO2 emissions than in the other two regions.
Low-carbon economy is an important part of national strategic objectives, which not only refers to an ecological and environmental economic model but also is the main direction for the development of ...the sports industry. Based on the characteristics and components of the low carbon economy, this paper utilizes the environmental Kuznets curve and decoupling theory to set the goal of low carbon economy development in the sports industry and explore the influence mechanism of low carbon economy on the structural development of the sports industry. Starting from the perspective of the development of the sports industry structure, a multi-period double-difference model is designed to calculate the net effect of a low-carbon economy on the sports industry structure. The relationship between the low carbon economy and the structural change of the sports industry is visualized using non-linear fitting and partial derivatives. The evaluation model of sports industry development capacity is constructed to evaluate the development of the sports industry from two perspectives: economic performance and economic value added. The experimental results show that the impact of a low carbon economy on the structure of the sports industry is divided into three stages, namely, coefficient value <0.15, coefficient value in 0.15, 0.25), and coefficient value ≤0.25. The low-carbon economy has a marginal positive effect on the sports industry in the second stage. The calculation of EVA value shows that the EVA value of the subject sports enterprises is greater than 0 from 2017 to 2023, which indicates that the sports industry realizes value creation along with the development of the low-carbon economy.
The western North Pacific anomalous anticyclone (WNPAC) is an important low-level circulation system that connects El Niño and the East Asian monsoon. In this study, the mechanisms responsible for ...the formation and maintenance of the WNPAC are explored. Part I of this study focuses on the WNPAC maintenance mechanisms during El Niño mature winter and the following spring. Moisture and moist static energy analyses indicated that the WNPAC is maintained by both the remote forcing from the equatorial central-eastern Pacific via the atmospheric bridge and the local air–sea interactions. Three pacemaker experiments by a coupled global climate model FGOALS-s2, with upper-700-m ocean temperature in the equatorial central-eastern Pacific restored to the observational anomalies plus model climatology, suggest that about 60% (70%) intensity of the WNPAC during the winter (spring) is contributed by the remote forcing from the equatorial central-eastern Pacific. The key remote forcing mechanism responsible for the maintenance of the WNPAC is revealed. In response to El Niño–related positive precipitation anomalies over the equatorial central-eastern Pacific, twin Rossby wave cyclonic anomalies are induced to the west. The northern branch of the twin cyclonic anomalies advects dry and low moist enthalpy air into the tropical western North Pacific, which suppresses local convection. The suppressed convection further drives the WNPAC.
This paper presents a density- and grid- based (DGB) clustering method for categorizing data with arbitrary shapes and noise. As most of the conventional clustering approaches work only with ...round-shaped clusters, other methods are needed to be explored to proceed classification of clusters with arbitrary shapes. Clustering approach by fast search and find of density peaks and density-based spatial clustering of applications with noise, and so many other methods are reported to be capable of completing this task but are limited by their computation time of mutual distances between points or patterns. Without the calculation of mutual distances, this paper presents an alternative method to fulfill clustering of data with any shape and noise even faster and with more efficiency. It was successfully verified in clustering industrial data (e.g., DNA microarray data) and several benchmark datasets with different kinds of noise. It turned out that the proposed DGB clustering method is more efficient and faster in clustering datasets with any shape than the conventional methods.
Active planar optical devices that can dynamically manipulate light are highly sought after in modern optics and nanophotonics. The geometric phase derived from the photonic spin-orbit interaction ...provides an integrated strategy. Corresponding elements usually suffer from static functions. Here, we introduce an inhomogeneously self-organized anisotropic medium featured by photo-invertible chiral superstructure to realize geometric phase elements with continuously tunable working spectrum and light-flipped phase profile. Via preprograming the alignment of a cholesteric liquid crystal mixed with a photo-responsive chiral dopant, we demonstrate light-activated deflector, lens, Airy beam and optical vortex generators. Their polychromatic working bands are reversibly tuned in an ultra-broadband over 1000 nm covering green to telecomm region. The chirality inversion triggers facile switching of functionalities, such as beam steering, focusing/defocusing and spin-to-orbital angular momentum conversion. This work offers a platform for advanced adaptive and multifunctional flat optics with merits of high compactness, low loss and broad bandwidth.
Detection and tracking of humans in video streams is important for many applications. We present an approach to automatically detect and track multiple, possibly partially occluded humans in a ...walking or standing pose from a single camera, which may be stationary or moving. A human body is represented as an assembly of body parts. Part detectors are learned by boosting a number of weak classifiers which are based on edgelet features. Responses of part detectors are combined to form a joint likelihood model that includes an analysis of possible occlusions. The combined detection responses and the part detection responses provide the observations used for tracking. Trajectory initialization and termination are both automatic and rely on the confidences computed from the detection responses. An object is tracked by data association and meanshift methods. Our system can track humans with both inter-object and scene occlusions with static or non-static backgrounds. Evaluation results on a number of images and videos and comparisons with some previous methods are given.PUBLICATION ABSTRACT
By incorporating temporal effects into the geographically weighted regression (GWR) model, an extended GWR model, geographically and temporally weighted regression (GTWR), has been developed to deal ...with both spatial and temporal nonstationarity simultaneously in real estate market data. Unlike the standard GWR model, GTWR integrates both temporal and spatial information in the weighting matrices to capture spatial and temporal heterogeneity. The GTWR design embodies a local weighting scheme wherein GWR and temporally weighted regression (TWR) become special cases of GTWR. In order to test its improved performance, GTWR was compared with global ordinary least squares, TWR, and GWR in terms of goodness-of-fit and other statistical measures using a case study of residential housing sales in the city of Calgary, Canada, from 2002 to 2004. The results showed that there were substantial benefits in modeling both spatial and temporal nonstationarity simultaneously. In the test sample, the TWR, GWR, and GTWR models, respectively, reduced absolute errors by 3.5%, 31.5%, and 46.4% relative to a global ordinary least squares model. More impressively, the GTWR model demonstrated a better goodness-of-fit (0.9282) than the TWR model (0.7794) and the GWR model (0.8897). McNamara's test supported the hypothesis that the improvements made by GTWR over the TWR and GWR models are statistically significant for the sample data.
Flame retardant polymers for a better future Wu, Bo
Advanced industrial and engineering polymer research,
April 2023, 2023-04-00, 2023-04-01, Volume:
6, Issue:
2
Journal Article
PDF
