A new evaluation of the role of urbanization to warming at various spatial scales: Evidence from the Guangdong‐Hong Kong‐Macao Region, China

The urbanization impacts on Surface Air Temperature (SAT) change in the Guangdong‐Hong Kong‐Macao region (GHMR) from 1979 to 2018 are examined using homogeneous surface observations, reanalysis, and remote sensing. Results show that the warming due to urbanization tends to be smaller or insignificant as the spatial scale increases. The urbanization contribution to the local warming can reach as high as 50% in the center of each metropolis, remains high (~25%) in the Greater Bay Area (GBA), and decreases to about 10% in the whole GHMR. The warming in GHMR is nearly uniform throughout the day, and therefore the observed trend of the Diurnal Temperature Range (DTR) is not statistically significant. However, the urbanization contribution exhibits distinct seasonal variations, large in summer and autumn while smaller in winter and spring

Mask-guided modality difference reduction network for RGB-T semantic segmentation

By exploiting the complementary information of RGB modality and thermal modality, RGB-thermal (RGB-T) semantic segmentation is robust to adverse lighting conditions. When fusing features from RGB images and thermal images, the existing methods design different feature fusion strategies, but most of these methods overlook the modality differences caused by different imaging mechanisms. This may result in insufficient usage of complementary information. To address this issue, we propose a novel Mask-guided Modality Difference Reduction Network (MMDRNet), where the mask is utilized in the image reconstruction to ensure that the modality discrepancy within foreground regions is minimized. Doing so enables the generation of more discriminative representations for foreground pixels, thus facilitating the segmentation task. On top of this, we present a Dynamic Task Balance (DTB) method to balance the modality difference reduction task and semantic segmentation task dynamically. The experimental results on the MFNet dataset and the PST900 dataset demonstrate the superiority of the proposed mask-guided modality difference reduction strategy and the effectiveness of the DTB method

Progress and summary of reinforcement learning on energy management of MPS-EV

The high emission and low energy efficiency caused by internal combustion engines (ICE) have become unacceptable under environmental regulations and the energy crisis. As a promising alternative solution, multi-power source electric vehicles (MPS-EVs) introduce different clean energy systems to improve powertrain efficiency. The energy management strategy (EMS) is a critical technology for MPS-EVs to maximize efficiency, fuel economy, and range. Reinforcement learning (RL) has become an effective methodology for the development of EMS. RL has received continuous attention and research, but there is still a lack of systematic analysis of the design elements of RL-based EMS. To this end, this paper presents an in-depth analysis of the current research on RL-based EMS (RL-EMS) and summarizes the design elements of RL-based EMS. This paper first summarizes the previous applications of RL in EMS from five aspects: algorithm, perception scheme, decision scheme, reward function, and innovative training method. The contribution of advanced algorithms to the training effect is shown, the perception and control schemes in the literature are analyzed in detail, different reward function settings are classified, and innovative training methods with their roles are elaborated. Finally, by comparing the development routes of RL and RL-EMS, this paper identifies the gap between advanced RL solutions and existing RL-EMS. Finally, this paper suggests potential development directions for implementing advanced artificial intelligence (AI) solutions in EMS

Oral administration of interferon-α2b-transformed Bifidobacterium longum protects BALB/c mice against coxsackievirus B3-induced myocarditis

Multiple reports have claimed that low-dose orally administered interferon (IFN)-α is beneficial in the treatment of many infectious diseases and provides a viable alternative to high-dose intramuscular treatment. However, research is needed on how to express IFN stably in the gut. Bifidobacterium may be a suitable carrier for human gene expression and secretion in the intestinal tract for the treatment of gastrointestinal diseases. We reported previously that Bifidobacterium longum can be used as a novel oral delivery of IFN-α. IFN-transformed B. longum can exert an immunostimulatory role in mice; however the answer to whether this recombinant B. longum can be used to treat virus infection still remains elusive. Here, we investigated the efficacy of IFN-transformed B. longum administered orally on coxsackie virus B3 (CVB3)-induced myocarditis in BALB/c mice. Our data indicated that oral administration of IFN-transformed B. longum for 2 weeks after virus infection reduced significantly the severity of virus-induced myocarditis, markedly down regulated virus titers in the heart, and induced a T helper 1 cell pattern in the spleen and heart compared with controls. Oral administration of the IFN-transformed B. longum, therefore, may play a potential role in the treatment of CVB3-induced myocarditis

Probabilistic Reliability Analysis of Carbon/Carbon Composite Nozzle Cones with Uncertain Parameters

A methodology to perform the probabilistic and reliability-based design of a novel carbon/carbon rocket nozzle subjected to operational thermal and mechanical loads is described in this paper. In this methodology, the nozzle is represented by a multiphysics finite element model capable of predicting the temperature and stress fields of the exit cone. The analysis shows that the most likely failure modes of the exit cone are related to compressive stress along the axial and hoop directions, as well as interlaminar shear. The probabilistic models used in this methodology account for the uncertainty of the material properties by using uniform and normal distributions and different variances. The reliability analysis is performed by using surface response methods. A global sensitivity analysis is also carried out using polynomial expansion chaos surface response models. A particular novelty of the analysis is the use of Sobol indices to rank the importance of the single uncertain parameters in the models. The methodology provides a high level of confidence and robustness in determining that the axial thermal conductivity of the carbon/carbon material is the most critical material property to affect the three main failure modes, whereas the coefficient of the thermal expansion and the heat capacity play a very marginal role

Synergistic Influence of Local Climate Zones and Wind Speeds on the Urban Heat Island and Heat Waves in the Megacity of Beijing, China

Large-scale modifications to urban underlying surfaces owing to rapid urbanization have led to stronger urban heat island (UHI) effects and more frequent urban heat wave (HW) events. Based on observations of automatic weather stations in Beijing during the summers of 2014–2020, we studied the interaction between HW events and the UHI effect. Results showed that the UHI intensity (UHII) was significantly aggravated (by 0.55°C) during HW periods compared to non-heat wave (NHW) periods. Considering the strong impact of unfavorable weather conditions and altered land use on the urban thermal environment, we evaluated the modulation of HW events and the UHI effect by wind speed and local climatic zones (LCZs). Wind speeds in urban areas were weakened due to the obstruction of dense high-rise buildings, which favored the occurrence of HW events. In detail, 35 HW events occurred over the LCZ1 of a dense high-rise building area under low wind speed conditions, which was much higher than that in other LCZ types and under high wind speed conditions (< 30 HW events). The latent heat flux in rural areas has increased more due to the presence of sufficient water availability and more vegetation, while the increase in heat flux in urban areas is mainly in the form of sensible heat flux, resulting in stronger UHI effect during HW periods. Compared to NHW periods, lower boundary layer and wind speed in the HW events weakened the convective mixing of air, further expanding the temperature gap between urban and rural areas. Note that LCZP type with its high-density vegetation and water bodies in the urban park area generally exhibited, was found to have a mitigating effect on the UHI, whilst at the same time increasing the frequency and duration of HW events during HW periods. Synergies between HWs and the UHI amplify both the spatial and temporal coverage of high-temperature events, which in turn exposes urban residents to additional heat stress and seriously threatens their health. The findings have important implications for HWs and UHII forecasts, as well as for scientific guidance on decision-making to improve the thermal environment and to adjust the energy structure

Vegetation greening offsets urbanization induced fast warming in Guangdong, Hong Kong, and Macao region (GHMR)

Previous studies show that the environment in the Guangdong, Hong Kong, and Macao region is under the double stress of global warming and urbanization. Here, we show that due to the increase of regional greenness, the effect of urbanization warming on surface air temperature (SAT) decreased with time and became statistically insignificant from 2004 to 2018, compared to 1979 onward; while the urbanization itself has significantly warmed land surface temperature (LST), with a warming rate of 0.14°C ± 0.04°C/10a at daytime and 0.02°C ± 0.02°C/10a at nighttime during 2004–2018, respectively. The anthropogenic heat was found to have a limited influence on SAT, but more significant and tangible effects on LST. It is essential to improve the control of additional warming effects caused by urbanization

Fuel consumption and exhaust emissions of diesel vehicles in worldwide harmonized light vehicles test cycles and their sensitivities to eco-driving factors

Large amounts of fossil fuels are 14 consumed by motor vehicles annually, and hazardous exhaust emissions from the motor vehicles have caused serious problems to environment and human health. Eco-driving can effectively improve the fuel economy and decrease the exhaust emissions, which makes it vital to analyze the fuel consumption and exhaust emissions at given driving cycle, and investigate their sensitivities to eco-driving factors. In this paper, the fuel consumption and exhaust emissions of a Euro-6 compliant light-duty diesel vehicle were tested in Worldwide Harmonized Light Vehicles Test Cycles on a chassis dynamometer; further, the sensitivities of the eco-driving factors that influence the fuel economy and exhaust emissions were analyzed using validated vehicle model. For the vehicle model simulation, the effect of the coolant temperature on fuel consumption and exhaust emission only considered its effect on lubricating oil viscosity. The results showed that vehicle acceleration and velocity dominates the fuel consumption rates in Worldwide Harmonized Light Vehicles Test Cycles, where more than 50% of the exhaust emissions was emitted in the first 300 seconds; also, fuel economy and exhaust emission factors showed a significant dependency on the road grade, coolant temperature, vehicle velocity and mass. For the driver-controllable factors, high vehicle velocity and low road grade (via route-choice) were recommended to achieve low fuel consumption and exhaust emissions