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The nucleation of iodic acid (HIO 3 ) and iodous acid (HIO 2 ) play a significant role in marine new particle formation (NPF) events. However, the inability to explain intensive NPF bursts in polluted coasts indicates the participation of potential precursors. Herein, we identified a novel nucleation mechanism of HIO 3 –HIO 2 system enhanced by the urban pollutant sulfuric acid (H 2 SO 4 ). We found that H 2 SO 4 could largely enhance the cluster formation rates ( J , cm −3 s −1 ) of HIO 3 –HIO 2 system, especially in high [H 2 SO 4 ] regions near H 2 SO 4 emission sources. The enhanced J of HIO 3 –HIO 2 –H 2 SO 4 system performs better match than that of HIO 3 –HIO 2 system with the observational rates of polluted coasts and polar regions, such as Zhejiang and Marambio. Moreover, the H 2 SO 4 -involved cluster formation is realized without Gibbs free energy barrier and dominate broadly in marine regions with rich H 2 SO 4 and scarce iodine concentrations. These findings may help to explain some missing fluxes of marine new particles and emphasize the impact of urban components on marine nucleation processes.

Marine new particle formation (NPF) can affect cloud condensation nuclei (CCN) in the global atmosphere. Recently, iodic acid (IA) has been identified as a critical driver for marine NPF. However, atmospheric observations of IA cannot be associated with predicted particle formation rates. Given the complexity of atmospheric components, other species may promote IA particle formation. As an efficient stabilizer for acidic precursors, dimethylamine (DMA) has a wide distribution over the oceans. Hence, we investigated the nucleation process of DMA and IA under different atmospheric conditions and uncovered the corresponding nucleating mechanism using a quantum chemical approach and Atmospheric Cluster Dynamics Code (ACDC). The findings show that DMA can structurally stabilize IA via hydrogen and halogen bonds, and the clustering process is energy barrierless. Moreover, DMA can enhance the formation rate of IA clusters by five orders of magnitude, and its efficiency in promoting IA cluster formation is much higher than that of NH 3 . Compared to the nucleation via sequential addition of IA, the IA-DMA nucleation plays a more dominant role in nucleation kinetic. Thus, the effect of DMA on enhancing IA cluster stability and formation rate cannot be ignored, especially in the regions near the source of IA and DMA emissions. Broadly, the proposed IA-DMA nucleation mechanism may help to explain some missing sources of particles and, thus intensive marine NPF events.

Introduction To investigate the clinical significance of obesity measurement indicators in patients with type 2 diabetes mellitus(T2DM) complicated with carotid plaque. Methods A total of 1009 subjects with T2DM were recruited in the cross-sectional study, and body measurements were collected. According to the results of carotid artery ultrasound, the study subjects were divided into T2DM without carotid plaque group (NCP: n  = 617) and with carotid plaque group (WCP: n  = 392). Results Compared with the NCP group, the waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), Chinese visceral fat index (CVAI), body roundness index (BRI), body fat index (BAI), body shape index (ABSI), and abdominal volume index (AVI) were significantly increased in the WCP group ( P < 0.05). The results of multivariate stepwise logistic regression analysis showed that BAI, CVAI and ABSI had the greatest effect on carotid plaque ( P < 0.05). After adjusting for multiple confounding factors, CVAI and ABSI remained independently associated with carotid plaques, and the combination of the three indicators exhibited superior predictive value for carotid plaques. Conclusion CVAI and ABSI are closely related to the occurrence and development of carotid plaque in subjects with T2DM, and the combined application has a good effect on predicting carotid plaque.

Rodent focal ischemia models are widely used to mimic and examine human strokes. To the best of our knowledge, no investigation has systematically examined the expression changes of microRNA (miR)-449a and Amphiregulin (AREG) as well as their biological relationship during middle cerebral artery occlusion (MCAO) and oxygen and glucose deprivation/reperfusion (OGD/R). The present study examined the histological and behavioral outcomes of MCAO and the function of miR-449a and AREG in cerebral ischemic injury. Rats were subjected to 2 h MCAO, which was followed by reperfusion. miR-449a and AREG were examined in the injury tissues of MCAO rats and the OGD/R cell line by reverse transcription-quantitative polymerase chain reaction. Protein expressions of AREG in the injury tissues of MCAO rats was measured using an immunohistochemistry and the protein expression levels of AREG, epidermal growth factor receptor (EGFR), phosphatidylinositol 3-kinase (PI3K)/ protein kinase B (Akt) and the phosphorylation level of Akt (p-Akt) were analyzed by western blotting. Cell apoptosis was examined following the knock down and subsequent overexpression of AREG in a human OGD/R neuronal cell line by small interfering RNAs (siRNAs) and plasmid transfection. Luciferase reporter assays were used to validate the target of miR-449a. The expression changes and regulatory mechanisms of miR-449a and AREG in an ischemia/reperfusion (I/R) injury model were examined in vivo and in vitro. The neurological deficit score, brain edema volume, cerebral infarct area, and the number of apoptosis cells in ischemic rats were all markedly elevated, than that in the control rats. The expression of miR-449a was decreased and AREG was increased in the MCAO rats and human OGD/R neuronal cell line. miR-449a inhibition or AREG overexpression in OGD/R cells resulted in a significant decrease in apoptotic cells, and AREG was revealed to be one of the direct targets of miR-449a. Molecular recovery was observed following transfection with miR-449a mimics and AREG knockdown in an OGD/R model in vitro. The present study demonstrated that miR-449a was downregulated while AREG was upregulated in cerebral ischemic injury, and the recovery of neurological function can be obtained following the overexpression of miR-449a and the knockdown of AREG in an I/R injury model. miR-449a functions in ischemic stroke via directly targeting AREG. These findings suggest a novel mechanism involving in cerebral I/R injury model and may aid investigators in gaining a deeper understanding of strokes in a clinical setting.

Multi-stage launch vehicles are currently the primary tool for humans to reach extraterrestrial space. The technology of recovering and reusing rockets can effectively shorten rocket launch cycles and reduce space launch costs. With the development of deep representation learning, reinforcement learning (RL) has become a robust learning framework capable of learning complex policies in high-dimensional environments. In this paper, a deep reinforcement learning-based reusable rocket landing control method is proposed. The mathematical process of reusable rocket landing is modelled by considering the aerodynamic drag, thrust, gravitational force, and Earth’s rotation during the landing process. A reward function is designed according to the rewards and penalties derived from mission accomplishment, terminal constraints, and landing performance. Based on this, the Softmax double deep deterministic policy gradient (SD3) deep RL method is applied to build a robust reusable rocket landing control method. In the constructed simulation environment, the proposed method can achieve convergent and robust control results, proving the effectiveness of the proposed method.

The formation of environmentally persistent free radicals (EPFRs) is mediated by the particulate matter's surface, especially transition metal oxide surfaces. In the context of current atmospheric complex pollution, various atmospheric components, such as key atmospheric oxidants ·OH and O3, are often absorbed on particulate matter surfaces, forming particulate matter surfaces containing ·OH and O3. This, in turn, influences EPFRs formation. Here, density functional theory (DFT) calculations were used to explore the formation mechanism of EPFRs by C6H5OH on α-Fe2O3(0001) surface containing the ·OH and O3, and compare it with that on clean surface. The results show that, compared to EPFRs formation with an energy barrier on a clean surface, EPFRs can be rapidly formed through a barrierless process on these surfaces. Moreover, during the hydrogen abstraction mechanism leading to EPFRs formation, the hydrogen acceptor shifts from a surface O atom on a clean surface to an O atom of ·OH or O₃ on these surfaces. However, the detailed hydrogen abstraction process differs on surfaces containing oxidants: on surfaces containing ·OH, it occurs directly through a one-step mechanism, while, on surfaces containing O3, it occurs through a two-step mechanism. But, in both types of surfaces, the essence of this promotional effect mainly lies in increasing the electron transfer amounts during the reaction process. This research provides new insights into EPFRs formation on particle surfaces within the context of atmospheric composite pollution.

Diiodine trioxide (I 2 O 3 ) is one of the most common iodine oxides in the marine boundary layer (MBL). Both theoretical and experimental studies have confirmed that they can be quickly formed and are relatively stable under dry conditions. However, there is no report on the field observation of I 2 O 3 , which means that I 2 O 3 is likely to be lost in the actual marine atmosphere. But the specific loss pathways and mechanisms are still unclear. Considering that the humidity in the marine regions is generally high and the loss of I 2 O 3 will be affected by some substances in the marine atmosphere, water (H 2 O, W ) and iodic acid (HIO 3 , IA ) were selected as a catalyst to investigate the catalytic hydration mechanisms of I 2 O 3 at DLPNOCCSD(T)//ωB97X-D/aug-cc-pVTZ + aug-cc-pVTZ -PP (for iodine) level of theory. The results show that hydration of I 2 O 3 presents a high energy barrier, but IA can reduce it to 3.76 kcal/mol. Therefore, in the marine atmosphere, I 2 O 3 can be hydrolyzed under the catalysis of IA , and cannot directly participate in the new particle formation process.

SignificanceNew particle formation (NPF) is an important global phenomenon, contributing nearly half of the cloud condensation nuclei in nature. Today, NPF is believed to be mainly promoted by low-volatile species formed in atmosphere. Herein, we show that in certain cases, the formation of low-volatile species could undermine NPF. Specifically, we identify previously unreported catalytic reactions between alcohols and SO3 which yield low-volatile organic sulfates. Rather than being a promoter to NPF, the low-volatile organic sulfates can compete for consuming SO3, thereby disfavoring H2SO4 formation. Such unexpected quenching effects on NPF are most likely to occur in dry and polluted regions with abundant alcohols, illustrating the importance in understanding the interplay between nucleation precursor formation and subsequent NPF. Despite the high abundance in the atmosphere, alcohols in general and methanol in particular are believed to play a small role in atmospheric new particle formation (NPF) largely due to the weak binding abilities of alcohols with the major nucleation precursors, e.g., sulfuric acid (SA) and dimethylamine (DMA). Herein, we identify a catalytic reaction that was previously overlooked, namely, the reaction between methanol and SO3, catalyzed by SA, DMA, or water. We found that alcohols can have unexpected quenching effects on the NPF process, particularly in dry and highly polluted regions with high concentrations of alcohols. Specifically, the catalytic reaction between methanol and SO3 can convert methanol into a less-volatile species––methyl hydrogen sulfate (MHS). The latter was initially thought to be a good nucleation agent for NPF. However, our simulation results suggest that the formation of MHS consumes an appreciable amount of atmospheric SO3, disfavoring further reactions of SO3 with H2O. Indeed, we found that MHS formation can cause a reduction of SA concentration up to 87%, whereas the nucleation ability of MHS toward new particles is not as good as that of SA. Hence, a high abundance of methanol in the atmosphere can lower the particle nucleation rate by as much as two orders of magnitude. Such a quenching effect suggests that the recently identified catalytic reactions between alcohols and SO3 need to be considered in atmospheric modeling in order to predict SA concentration from SO2, while also account for their potentially negative effect on NPF.

Recent research [Wang et al., Nature 581, 184–189 (2020)] indicates nitric acid (NA) can participate in sulfuric acid (SA)–ammonia (NH₂) nucleation in the clean and cold upper free troposphere, whereas NA exhibits no obvious effects at the boundary layer with relatively high temperatures. Herein, considering that an SA–dimethylamine (DMA) nucleation mechanism was detected inmegacities [Yao et al., Science 361, 278–281 (2018)], the roles of NA in SA-DMA nucleation are investigated. Different from SA-NH₂ nucleation, we found that NA can enhance SA-DMA–based particle formation rates in the polluted atmospheric boundary layer, such as Beijing in winter, with the enhancement up to 80-fold. Moreover, we found that NA can promote the number concentrations of nucleation clusters (up to 27-fold) and contribute 76% of cluster formation pathways at 280 K. The enhancements on particle formation by NA are critical for particulate pollution in the polluted boundary layer with relatively high NA and DMA concentrations.

Safety helmets can effectively prevent accidental head injuries to construction personnel. Helmet wearing detection is of great significance to the safety management of the construction site. The existing detection algorithms are difficult to detect small targets and dense targets, and the target occlusion and complex and changeable construction environment will reduce the detection accuracy. To solve the above problems, an intelligent helmet recognition system is designed, which combines multi-target tracking algorithm DeepSort and YOLOv5 detector. Firstly, the target bounding box is extracted by YOLOv5 algorithm and input into DeepSort framework. Further, the target trajectory prediction and tracking are realized by Kalman filter and Hungarian Algorithm. The actual test results on the complex construction sites show that the helmet recognition system based on YOLOv5 and DeepSort improves the detection speed and accuracy compared with the single detection algorithm and partial tracking algorithm. The average accuracy of the system is 94.5%, and the detection speed can reach 40fps, basically realizing real-time detection and providing an effective guarantee for the helmet-wearing detection task.