PM_(2.5)concentrations have dramatically reduced in key regions of China during the period 2013-2017,while O_(3)has *** there is an urgent demand to develop a synergetic regional PM_(2.5)and O_(3)control *** study dev...
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PM_(2.5)concentrations have dramatically reduced in key regions of China during the period 2013-2017,while O_(3)has *** there is an urgent demand to develop a synergetic regional PM_(2.5)and O_(3)control *** study develops an emission-to-concentration response surface model and proposes a synergetic pathway for PM_(2.5)and O_(3)control in the Yangtze River Delta(YRD)based on the framework of the Air Benefit and Cost and Attainment Assessment System(ABaCAS).Results suggest that the regional emissions of NOx,SO_(2),NH3,VOCs(volatile organic compounds)and primary PM_(2.5)should be reduced by 18%,23%,14%,17%and 33%compared with 2017 to achieve 25%and 5% decreases of PM_(2.5)and O_(3)in 2025,and that the emission reduction ratios will need to be 50%,26%,28%,28% and 55%to attain the National Ambient Air Quality *** effectively reduce the O_(3) pollution in the central and eastern YRD,VOCs controls need to be strengthened to reduce O_(3)by 5%,and then NOx reduction should be accelerated for air quality ***,control of primary PM_(2.5)emissions shall be prioritized to address the severe PM_(2.5)pollution in the northern *** most cities in the YRD,the VOCs emission reduction ratio should be higher than that for NOx in Spring and *** control should be increased in summer rather than winter when a strong VOC-limited regime ***,regarding the emission control of industrial processes,on-road vehicle and residential sources shall be prioritized and the joint control area should be enlarged to include Shandong,Jiangxi and Hubei Province for effective O_(3)control.
THE development of agriculture faces significant challenges due to population growth, climate change, land depletion, and environmental pollution, threatening global food security [1]. This necessitates the developmen...
THE development of agriculture faces significant challenges due to population growth, climate change, land depletion, and environmental pollution, threatening global food security [1]. This necessitates the development of sustainable agriculture, where a fundamental step is crop breeding to improve agronomic or economic traits, e.g., increasing yields of crops while decreasing resource usage and minimizing pollution to the environment [2].
COMPUTATIONAL knowledge vision [1] is emphasized as a novel perspective or field in this paper. It first proposes the visual hierarchy and its connection to knowledge, stating that knowledge is a justified true belief...
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COMPUTATIONAL knowledge vision [1] is emphasized as a novel perspective or field in this paper. It first proposes the visual hierarchy and its connection to knowledge, stating that knowledge is a justified true belief. To further the previous research, we concisely summarize our recent works and suggest a new direction that knowledge is also a thought framework in vision.
This letter proposes a robust stochastic differential equation approach for learning point-to-point motions in an adversarial way. The proposed stochastic dynamical model combines the advantages of the stochastic diff...
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This letter proposes a robust stochastic differential equation approach for learning point-to-point motions in an adversarial way. The proposed stochastic dynamical model combines the advantages of the stochastic differential equation and the transformer-like function together to achieve both robustness and accuracy of the learning. The adversarial training method is proposed to simplify the way of updating the parameters of the model. The state of the proposed stochastic dynamical system is mathematically proved to converge asymptotically in the mean square sense, and it has been experimentally validated on the LASA dataset and by the trajectory-programming task of the Franka Emika robot. The experimental results show that: (1) the adversarial training method helps the model to achieve higher reproduction accuracy;(2) the trajectories generated by the proposed model achieve higher accuracy in both the noise-free condition (by approximately 14.9%) and the noisy condition (by approximately 17.8%) compared with the state-of-the-art methods in terms of the similarity to the demonstration;and (3) the proposed approach can learn smoother trajectories even if the observations are contaminated by noises.
Dear Editor,Light fields give relatively complete description of scenes from perspective of angles and positions of rays. At present time, most of the computer vision algorithms take 2D images as input which are simpl...
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Dear Editor,Light fields give relatively complete description of scenes from perspective of angles and positions of rays. At present time, most of the computer vision algorithms take 2D images as input which are simplified expression of light fields with depth information discarded. In theory, computer vision tasks may achieve better performance as long as complete light fields are acquired.
Dear Editor,This letter focuses on leveraging the object information in images to improve the performance of the U-Net based change *** detection is fundamental to many computer vision *** existing solutions based on ...
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Dear Editor,This letter focuses on leveraging the object information in images to improve the performance of the U-Net based change *** detection is fundamental to many computer vision *** existing solutions based on deep neural networks are able to achieve impressive results.
Soft pressure sensors have recently attracted considerable attention because of their applications in human-machine interface, soft robotics, and prosthetics. However, there remain some challenges in achieving satisfa...
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Soft pressure sensors have recently attracted considerable attention because of their applications in human-machine interface, soft robotics, and prosthetics. However, there remain some challenges in achieving satisfactory performance (e.g., high sensitivity, wide sensing range, high stability) for soft pressure sensors. This article reports an intentional blocking based photoelectric pressure sensor. Two different blocking methods are investigated: the single-row-pyramid blocking and the double-row-pyramid blocking. The sensor has a simple structure, which is made of a light-emitting diode, photosensitive element, and silicone sensor shell. Experiments demonstrate that the sensor has a high sensitivity (the maximum sensitivity is 48.07 kPa(-1), and the minimum measurement pressure is 0.8 Pa), large pressure-sensing range (the sensing range is up to 120 kPa), superior stability (a drift about 0.4% over 12,130 repetitive cycles at 0-80 kPa), low drift (< +/- 0.2% in different 3-day testing), negligible hysteresis, and high signal-to-noise ratio (over 55 dB). By mounting the pressure sensor at the end of a robotic arm, the robot can detect subtle collisions (such as touching a balloon through a pinpoint). In addition, this article fabricates a tactile glove based on the proposed pressure sensor and shows the application of this glove for music playing and object weighing. This study provides a new structure for photoelectric sensors to increase sensitivity and also provides a more convenient way to fabricate photoelectric pressure sensors.
Hand gesture recognition has become a vital subject in the fields of human-computer interaction and rehabilitation *** paper presents a multi-modal fusion for hand gesture recognition(MFHG)model,which uses two heterog...
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Hand gesture recognition has become a vital subject in the fields of human-computer interaction and rehabilitation *** paper presents a multi-modal fusion for hand gesture recognition(MFHG)model,which uses two heterogeneous networks to extract and fuse the features of the vision-based motion signals and the surface electromyography(s EMG)signals,*** extract the features of the vision-based motion signals,a graph neural network,named the cumulation graph attention(CGAT)model,is first proposed to characterize the prior knowledge of motion coupling between finger *** CGAT model uses the cumulation mechanism to combine the early and late extracted features to improve motion-based hand gesture *** the s EMG signals,a time-frequency convolutional neural network model,named TF-CNN,is proposed to extract both the signals'time-domain and frequency-domain *** improve the performance of hand gesture recognition,the deep features from multiple modes are merged with an average layer,and then the regularization items containing center loss and the mutual information loss are employed to enhance the robustness of this multi-modal ***,a data set containing the multi-modal signals from seven subjects on different days is built to verify the performance of the multi-modal *** experimental results indicate that the MFHG can reach 99.96%and 92.46%accuracy on hand gesture recognition in the cases of within-session and cross-day,respectively.
For many decades,acid deposition used to pose a significant regional air pollution challenge in *** substantial emission control of anthropogenically derived sulfur and nitrogen containing gasses,both sulfur and nitro...
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For many decades,acid deposition used to pose a significant regional air pollution challenge in *** substantial emission control of anthropogenically derived sulfur and nitrogen containing gasses,both sulfur and nitrogen deposition,as well as the acid rain-affected area,have significantly decreased compared to their peak ***,particularly in the humid subtropics,are sensitive to acid deposition,as evidenced by soil acidification,sulfate and nitrate leaching in stream water,and elevated soil nitrous oxide *** in the total deposition of sulfur and nitrogen,caused a significant decline in sulfate and nitrate leaching from subtropical forest and subsequently in sulfate and nitrate concentrations in stream water,although there was about a 5-year *** delay may be attributed to the desorption of accumulated sulfate and continued elevated mineralization of accumulated nitrogen *** of nitrous oxide,a potent greenhouse gas,also declined in nitrogen-saturated subtropical forest soils,as soil water nitrate concentration ***,subtropical forests in China suffering from elevated acid deposition have begun to ***,the current levels of sulfur and nitrogen deposition continue to exceed the critical loads,i.e.,the assigned threshold levels in accordance with emission control policies,in more than 10%of the country’s land area,respectively,indicating remaining risks of acidification and ***,further emission reductions are urgently needed,also because they will help achieving goals related to air quality and nitrous oxide emissions.
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