Ventilation and dust removal is the most basic means of dust prevention in mines. In the paper, a highly simulated physical model of the goaf and multiple dust sources were established in order to ...obtain the optimal dust-removal air flow rate in the roadway. In addition, by combining the numerical simulation method, the influence of the flow rate on dust diffusion rules of the dust sources was analyzed. The research results showed that the mass concentration of the dust in the fully-mechanized working face was gradually decreased with the increase of the air flow rate at a certain range of 700–1600 m3/min. However, high air flow rate can cause the re-entrainment of the dust, contaminating the working environment again. It was confirmed that the optimal dust-removal air flow rate of the inlet air was within a range of 1500–1600 m3/min, which generated the lowest average mass of the dust in the working area suitable for normal operations. This range of air flow rate might be used as a reference in the mine ventilation design in order to provide the coal mine workers with a clean and safe production environment. In addition, the research method and results are of great significance to the formulation and development of effective dust control and dust removal cleaner production technology, and can be used as a reference for the ventilation design in underground projects such as non-coal mines and tunnels.
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•The innovative highly simulated physical model was established.•The effectiveness of numerical simulation was verified by field measurements.•The dust diffusion law under different air flow rate conditions was analyzed.•The optimal dust-removal air flow rate is obtained.
Tin (Sn)-based and mixed tin–lead (Sn–Pb) perovskites have attracted increased attention as promising candidates for new generation lead-free perovskite and all-perovskite tandem solar cells. ...However, as an inevitably critical issue, Sn(II) induced serious defects and oxidation and caused poor photovoltaic performance and unsatisfactory stability for Sn-based and mixed Sn–Pb perovskites. Herein, a comprehensive understanding on defect classification, defect formation, defect effect on performance, and defect passivation strategies is reviewed on the Sn(II) induced defects. The Sn(II)-based defects can be classified from the aspects of defect dimensions and shallow/deep levels in energy structure according to three main origins, i.e. low defect tolerance, oxidation, and fast crystallization. Then, the state-of-the-art defect passivation strategies including surface Lewis acid/base coordination, low/mixed dimensional perovskite design, composition regulation and crystal orientation modulation, and reducing agent assistance are summarized systematically. Lastly, several key scientific issues and future research prospectives are proposed for achieving stable and high-performance Sn-related perovskite photovoltaics.
The rational modulation of the nontraditional intrinsic luminescence (NTIL) of nonconventional luminophores remains difficult, on account of the limited understanding on the structure–property ...relationships and emission mechanisms. Herein, the effective modulation of NTIL is demonstrated based on a group of nonaromatic anhydrides and imides. Mutual bridging of isolated subgroups effectively promotes intramolecular through‐space conjugation (TSC), leading to red‐shifted emission, enhanced efficiency, and prolonged persistent room‐temperature phosphorescence (p‐RTP). The substitution of heteroatoms from oxygen to nitrogen drastically changes the TSC and enhances intermolecular interactions, resulting in enhanced emission efficiency. In addition, upon freezing, compression, or embedding into polymer matrices, the emission intensity and color remain well regulated. These results shed new light on the rational modulation of the NTIL and p‐RTP of nonconventional luminophores.
Fine modulation of the clusteroluminescence of nonconventional luminophores is realized in anhydrides and imides. Internal adjustment by bridging isolated subunits with CC or replacing oxygen with nitrogen changes the photoluminescence color with strikingly enhanced efficiency and prolonged persistent room‐temperature phosphorescence. Meanwhile, external regulation through freezing, compressing, and embedding technologies can also finely tune the light emission of the clusters.
To investigate the influence of dust produced by multi-dust sources at a fully mechanized mining face with a large mining height on the safety conditions in a coal mine, the No. 22305 fully ...mechanized mining face of the Bulianta coal mine was considered as the research object in this study, and the space–time evolution of dust was analyzed with computational fluid dynamics (CFD). The wind flow simulation results show that the distribution law of wind flow is mainly affected by the structure of the roadway, and the speed and direction of the wind flow change greatly while passing by corners and through large-scale equipment. The dust generation and pollution diffusion laws with respect to time and space were investigated based on simulations of dust production due to 5-s, 30-s, and 60-s coal cutting, continuous coal cutting, and hydraulic support shifting. The space–time evolution law under different dust-producing times shows the transportation and diffusion procedure of dust under the wind flow; the dust-generated via coal mining and shifting were superposed on the downwind side and a 36-m-long dust belt was formed, which filled the coal mining space; the dust concentration in the breathing zone 120 m downwind the front drum had a dust concentration higher than 1700 mg/m
3
, this was the crucial dust-proof area, and effective dust reduction methods should be addressed.
•We reveals the importance of solving the limitations of RPN and our proposed IoU-uniform R-CNN can alleviate the IoU distribution imbalance and inadequate training samples by generating samples with ...uniform IoU distribution.•We improve the performance of IoU prediction branch by eliminating the feature offsets of RoIs at inference.•Our proposed method consistently obtains significant improvements over multiple state-of-the-art detectors. Specially, it achieves 2.4 AP improvement than Faster R-CNN (with ResNet 101-FPN backbone) on MS COCO dataset.
Region Proposal Network (RPN) is the cornerstone of two-stage object detectors. It generates a sparse set of object proposals and alleviates the extrem foreground-background class imbalance problem during training. However, we find that the potential of the detector has not been fully exploited due to the IoU distribution imbalance and inadequate quantity of the training samples generated by RPN. With the increasing intersection over union (IoU), the exponentially smaller numbers of positive samples would lead to the distribution skewed towards lower IoUs, which hinders the optimization of detector at high IoU levels. In this paper, to break through the limitations of RPN, we propose IoU-Uniform R-CNN, a simple but effective method that directly generates training samples with uniform IoU distribution for the regression branch as well as the IoU prediction branch. Besides, we improve the performance of IoU prediction branch by eliminating the feature offsets of RoIs at inference, which helps the NMS procedure by preserving accurately localized bounding box. Extensive experiments on the PASCAL VOC and MS COCO dataset show the effectiveness of our method, as well as its compatibility and adaptivity to many object detection architectures. The code is made publicly available at https://github.com/zl1994/IoU-Uniform-R-CNN.
Smooth muscle cell (SMC) loss is the characteristic feature in the pathogenesis of aortic dissection (AD), and ferroptosis is a novel iron-dependent regulated cell death driven by the excessive lipid ...peroxidation accumulation. However, whether targeting ferroptosis is an effective approach for SMC loss and AD treatment remains unclear. Here, we found that the iron level, ferroptosis-related molecules TFR, HOMX1, ferritin and the lipid peroxidation product 4-hydroxynonenal were increased in the aorta of AD. Then, we screened several inhibitors of histone methyltransferases and found that BRD4770 had a protective effect on cystine deprivation-, imidazole ketone erastin- or RSL3-induced ferroptosis of SMCs. The classic ferroptosis pathways, System Xc--GPX4, FSP1-CoQ10 and GCH1-BH4 pathways which were inhibited by ferroptosis inducers, were re-activated by BRD4770 via inhibiting mono-, di- and tri- methylated histone H3 at lysine 9 (H3K9me1/2/3). RNA-sequencing analysis revealed that there was a positive feedback regulation between ferroptosis and inflammatory response, and BRD4770 can reverse the effects of inflammation activation on ferroptosis. More importantly, treatment with BRD4770 attenuated aortic dilation and decreased morbidity and mortality in a β-Aminopropionitrile monofumarate-induced mouse AD model via inhibiting the inflammatory response, lipid peroxidation and ferroptosis. Taken together, our findings demonstrate that ferroptosis is a novel and critical pathological mechanism that is involved in SMC loss and AD development. BRD4770 is a novel ferroptosis inhibitor and has equivalent protective effect to Ferrostatin-1 at the optimal concentration. Translating insights into the anti-ferroptosis effects of BRD4770 may reveal a potential therapeutic approach for targeting SMC ferroptosis in AD.
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•Ferroptosis is a novel and critical pathological mechanism involved in SMC loss and AD development.•BRD4770 is a novel inhibitor of ferroptosis and protects against SMC ferroptosis via maintaining redox homeostasis.•BRD4770 relieves BAPN-induced AD by inhibiting ferroptosis and inflammatory cell infiltration.
In dam engineering, the presence of cracks and crack width are important indicators for diagnosing the health of dams. The accurate measurement of cracks facilitates the safe use of dams. The manual ...detection of such defects is unsatisfactory in terms of cost, safety, accuracy, and the reliability of evaluation. The introduction of deep learning for crack detection can overcome these issues. However, the current deep learning algorithms possess a large volume of model parameters, high hardware requirements, and difficulty toward embedding in mobile devices such as drones. Therefore, we propose a lightweight MobileNetV2_DeepLabV3 image segmentation network. Furthermore, to prevent interference by noise, light, shadow, and other factors for long-length targets when segmenting, the atrous spatial pyramid pooling (ASPP) module parameters in the DeepLabV3+ network structure were modified, and a multifeature fusion structure was used instead of the parallel structure in ASPP, allowing the network to obtain richer crack features. We collected the images of dam cracks from different environments, established segmentation datasets, and obtained segmentation models through network training. Experiments show that the improved MobileNetV2_DeepLabV3 algorithm exhibited a higher crack segmentation accuracy than the original MobileNetV2_DeepLabV3 algorithm; the average intersection rate attained 83.23%; and the crack detail segmentation was highly accurate. Compared with other semantic segmentation networks, its training time was at least doubled, and the total parameters were reduced by more than 2 to 7 times. After extracting cracks through the semantic segmentation, we proposed to use the method of inscribed circle of crack outline to calculate the maximum width of the detected crack image and to convert it into the actual width of the crack. The maximum relative error rate was 11.22%. The results demonstrated the potential of innovative deep learning methods for dam crack detection.
In this paper, a multi-mode surface plasmon resonance absorber based on dart-type single-layer graphene is proposed, which has the advantages of polarization independence, tunability, high ...sensitivity, high figure of merit,
etc.
The device consists of a top layer dart-like patterned single-layer graphene array, a thicker silicon dioxide spacer layer and a metal reflector layer, and has simple structural characteristics. The numerical results show that the device achieves the perfect polarization-independent absorption at the resonance wavelengths of
λ
I
= 3369.55 nm,
λ
II
= 3508.35 nm,
λ
III
= 3689.09 nm and
λ
IV
= 4257.72 nm, with the absorption efficiencies of 99.78%, 99.40%, 99.04% and 99.91%, respectively. The absorption effect of the absorber can be effectively regulated and controlled by adjusting the numerical values such as the geometric parameters and the structural period p of the single-layer graphene array. In addition, by controlling the chemical potential and the relaxation time of the graphene layer, the resonant wavelength and the absorption efficiency of the mode can be dynamically tuned. And can keep high absorption in a wide incident angle range of 0° to 50°. At last, we exposed the structure to different environmental refractive indices, and obtained the corresponding maximum sensitivities in four resonance modes, which are
S
I
= 635.75 nm RIU
−1
,
S
II
= 695.13 nm RIU
−1
,
S
III
= 775.38 nm RIU
−1
and
S
IV
= 839.39 nm RIU
−1
. Maximum figure of merit are 54.03 RIU
−1
, 51.49 RIU
−1
, 43.56 RIU
−1
, and 52.14 RIU
−1
, respectively. Therefore, this study has provided a new inspiration for the design of the graphene-based tunable multi-band perfect metamaterial absorber, which can be applied to the fields such as photodetectors and chemical sensors.
We propose a multi-mode surface plasmon resonance absorber based on dart-type single-layer graphene, it has advantages of polarization independence, tunability and high sensitivity. Four modes of polarization-independent perfect absorption are achieved at 3000-5000 nm.
Although many cross-sectional studies have confirmed the positive associations between greenspaces and physical activity, evidence from natural experiments is scarce, especially for large-scale ...greenspace interventions. In addition, it is unclear how the physical-activity-related benefits of a greenspace intervention vary with distance from residences to greenspaces. We used a natural experimental approach to explore the impact on physical activity of a large-scale greenway intervention, namely the East Lake greenway, in Wuhan, China. Two waves of survey data (before and after the intervention in 2016 and 2019, respectively) were collected from 1020 participants residing in 52 neighbourhoods at different distances (0–1, 1–2, 2–3, 3–4, and 4–5 km) from the 102-km-long greenway. The results obtained using difference-in-difference models indicated that the greenway intervention had positive effects on both moderate-to-vigorous physical activity (MVPA) and overall physical activity (MET-minutes/week) after controlling for individual and neighbourhood covariates. Furthermore, the physical activity benefits of the greenway intervention were found to decrease with increasing distance between the greenway and the participants’ residences. Individuals living closer to this large-scale greenway accrued more substantial physical activity benefits. Our results, together with those of other natural experimental studies, suggest that large-scale greenspace interventions may provide long-term physical activity benefits to residents living in a wide geographic area.
•Greenway has significant effects on both MVPA and overall physical activity.•Physical activity benefits of greenway interventions decrease with distance.•We provided an alternative method to measure graded greenway exposure.
Network morphological analysis has emerged as a tool to quantify street network structures, providing a nuanced foundation for evaluating their impacts on traffic safety. Yet, there is a lack of ...disaggregate-level evidence on the spillover effects and spatial heterogeneity of these impacts. This research conducts a comprehensive, disaggregate-level, multi-scale examination on the overall impacts of street network morphologies on traffic safety. Our study focuses on the frequency of traffic injury collisions over a five-year period across more than 190,000 street links in Greater London. We characterise street-link morphologies at local (0–1 km), meso (0–3 km), and city (0–8 km) scales using a spatial design network analysis. For each spatial scale, we apply extended auto-negative binomial models to examine the overall impact of street-link morphological characteristics on the injury collision frequency, considering both the link being investigated and other surrounding links determined by the spatial scale.
We find significant spatial heterogeneity in the overall safety impacts of street-link morphologies. At the local scale, higher farness of a street link corresponds to an overall increase in injury collisions, whereas at the meso and city scales, it indicates an overall decrease. At the local and meso scales, higher betweenness of a street link is associated with an overall increase in injury collisions, but at the city scale, it correlates with an overall decrease. Independent of the spatial scale, a larger diversion ratio of a street link is linked to an overall decrease in injury collisions. These findings are similar to those on killed and seriously injured-only collisions. Our findings suggest that encouraging compact street network structures, which aligns well with New Urbanism and the Compact City policy, may not necessarily be effective for an overall reduction in injury collisions across an entire city.
•We examine the overall impacts of street network morphologies at the street-link level on injury collision frequency.•The overall impact of street-link morphologies on traffic safety presents spatial heterogeneity.•Promoting compact street network designs may not be effective for an overall reduction in collisions across an entire city.•We reflect on the limitations of New Urbanism planning and Compact City policy in ensuring traffic safety.
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